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Sample records for functional mri fmri

  1. Brain functional BOLD perturbation modelling for forward fMRI and inverse mapping

    Science.gov (United States)

    Robinson, Jennifer; Calhoun, Vince

    2018-01-01

    Purpose To computationally separate dynamic brain functional BOLD responses from static background in a brain functional activity for forward fMRI signal analysis and inverse mapping. Methods A brain functional activity is represented in terms of magnetic source by a perturbation model: χ = χ0 +δχ, with δχ for BOLD magnetic perturbations and χ0 for background. A brain fMRI experiment produces a timeseries of complex-valued images (T2* images), whereby we extract the BOLD phase signals (denoted by δP) by a complex division. By solving an inverse problem, we reconstruct the BOLD δχ dataset from the δP dataset, and the brain χ distribution from a (unwrapped) T2* phase image. Given a 4D dataset of task BOLD fMRI, we implement brain functional mapping by temporal correlation analysis. Results Through a high-field (7T) and high-resolution (0.5mm in plane) task fMRI experiment, we demonstrated in detail the BOLD perturbation model for fMRI phase signal separation (P + δP) and reconstructing intrinsic brain magnetic source (χ and δχ). We also provided to a low-field (3T) and low-resolution (2mm) task fMRI experiment in support of single-subject fMRI study. Our experiments show that the δχ-depicted functional map reveals bidirectional BOLD χ perturbations during the task performance. Conclusions The BOLD perturbation model allows us to separate fMRI phase signal (by complex division) and to perform inverse mapping for pure BOLD δχ reconstruction for intrinsic functional χ mapping. The full brain χ reconstruction (from unwrapped fMRI phase) provides a new brain tissue image that allows to scrutinize the brain tissue idiosyncrasy for the pure BOLD δχ response through an automatic function/structure co-localization. PMID:29351339

  2. Brain functional BOLD perturbation modelling for forward fMRI and inverse mapping.

    Science.gov (United States)

    Chen, Zikuan; Robinson, Jennifer; Calhoun, Vince

    2018-01-01

    To computationally separate dynamic brain functional BOLD responses from static background in a brain functional activity for forward fMRI signal analysis and inverse mapping. A brain functional activity is represented in terms of magnetic source by a perturbation model: χ = χ0 +δχ, with δχ for BOLD magnetic perturbations and χ0 for background. A brain fMRI experiment produces a timeseries of complex-valued images (T2* images), whereby we extract the BOLD phase signals (denoted by δP) by a complex division. By solving an inverse problem, we reconstruct the BOLD δχ dataset from the δP dataset, and the brain χ distribution from a (unwrapped) T2* phase image. Given a 4D dataset of task BOLD fMRI, we implement brain functional mapping by temporal correlation analysis. Through a high-field (7T) and high-resolution (0.5mm in plane) task fMRI experiment, we demonstrated in detail the BOLD perturbation model for fMRI phase signal separation (P + δP) and reconstructing intrinsic brain magnetic source (χ and δχ). We also provided to a low-field (3T) and low-resolution (2mm) task fMRI experiment in support of single-subject fMRI study. Our experiments show that the δχ-depicted functional map reveals bidirectional BOLD χ perturbations during the task performance. The BOLD perturbation model allows us to separate fMRI phase signal (by complex division) and to perform inverse mapping for pure BOLD δχ reconstruction for intrinsic functional χ mapping. The full brain χ reconstruction (from unwrapped fMRI phase) provides a new brain tissue image that allows to scrutinize the brain tissue idiosyncrasy for the pure BOLD δχ response through an automatic function/structure co-localization.

  3. Bayesian Inference for Functional Dynamics Exploring in fMRI Data

    Directory of Open Access Journals (Sweden)

    Xuan Guo

    2016-01-01

    Full Text Available This paper aims to review state-of-the-art Bayesian-inference-based methods applied to functional magnetic resonance imaging (fMRI data. Particularly, we focus on one specific long-standing challenge in the computational modeling of fMRI datasets: how to effectively explore typical functional interactions from fMRI time series and the corresponding boundaries of temporal segments. Bayesian inference is a method of statistical inference which has been shown to be a powerful tool to encode dependence relationships among the variables with uncertainty. Here we provide an introduction to a group of Bayesian-inference-based methods for fMRI data analysis, which were designed to detect magnitude or functional connectivity change points and to infer their functional interaction patterns based on corresponding temporal boundaries. We also provide a comparison of three popular Bayesian models, that is, Bayesian Magnitude Change Point Model (BMCPM, Bayesian Connectivity Change Point Model (BCCPM, and Dynamic Bayesian Variable Partition Model (DBVPM, and give a summary of their applications. We envision that more delicate Bayesian inference models will be emerging and play increasingly important roles in modeling brain functions in the years to come.

  4. Functional connectivity analysis of the brain network using resting-state fMRI

    International Nuclear Information System (INIS)

    Hayashi, Toshihiro

    2011-01-01

    Spatial patterns of spontaneous fluctuations in blood oxygenation level-dependent (BOLD) signals reflect the underlying neural architecture. The study of the brain network based on these self-organized patterns is termed resting-state functional MRI (fMRI). This review article aims at briefly reviewing a basic concept of this technology and discussing its implications for neuropsychological studies. First, the technical aspects of resting-state fMRI, including signal sources, physiological artifacts, image acquisition, and analytical methods such as seed-based correlation analysis and independent component analysis, are explained, followed by a discussion on the major resting-state networks, including the default mode network. In addition, the structure-function correlation studied using diffuse tensor imaging and resting-state fMRI is briefly discussed. Second, I have discussed the reservations and potential pitfalls of 2 major imaging methods: voxel-based lesion-symptom mapping and task fMRI. Problems encountered with voxel-based lesion-symptom mapping can be overcome by using resting-state fMRI and evaluating undamaged brain networks in patients. Regarding task fMRI in patients, I have also emphasized the importance of evaluating the baseline brain activity because the amplitude of activation in BOLD fMRI is hard to interpret as the same baseline cannot be assumed for both patient and normal groups. (author)

  5. Functional MRI (fMRI) on lesions in and around the motor and the eloquent cortices

    International Nuclear Information System (INIS)

    Hara, Yoshie; Nakamura, Mitsugu; Tamura, Shogo; Tamaki, Norihiko; Kitamura, Junji

    1999-01-01

    From the view point of neurosurgeons, to aim the preoperative localized diagnosis on the motor and the eloquent cortices and postoperative preservation of neurological functions, fMRI was carried for patients with lesions in and around the motor and the eloquent cortices. Even in cases of mechanical oppression or brain edema, the motor and the eloquent cortices are localized on cerebral gyri. In perioperative period, identification and preserving the motor and the eloquent cortices are important for keeping brain function. Twenty six preoperative cases and 3 normal healthy subjects were observed. Exercise enhanced fMRI was performed on 3 normal healthy subjects, fMRI with motor stimulation in 24 cases and fMRI with speech stimulation in 4 cases. The signal intensity increased in all cases responsing to both stimulations. But the signal intensity in 8 cases decreased in some regions by motor stimulation and 1 case by speech stimulation. The decrease of signal intensity in this study seems to be a clinically important finding and it will be required to examine the significance in future. (K.H.)

  6. Real-time functional MR imaging (fMRI) for presurgical evaluation of paediatric epilepsy

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    Kesavadas, Chandrasekharan; Thomas, Bejoy; Kumar Gupta, Arun [Sree Chitra Tirunal Institute for Medical Sciences and Technology, Department of Imaging Sciences and Interventional Radiology, Trivandrum (India); Sujesh, Sreedharan [Sree Chitra Tirunal Institute for Medical Sciences and Technology, Biomedical Technology Wing, Trivandrum (India); Ashalata, Radhakrishnan; Radhakrishnan, Kurupath [Sree Chitra Tirunal Institute for Medical Sciences and Technology, Department of Neurology, Trivandrum (India); Abraham, Mathew [Sree Chitra Tirunal Institute for Medical Sciences and Technology, Department of Neurosurgery, Trivandrum (India)

    2007-10-15

    The role of fMRI in the presurgical evaluation of children with intractable epilepsy is being increasingly recognized. Real-time fMRI allows the clinician to visualize functional brain activation in real time. Since there is no off-line data analysis as in conventional fMRI, the overall time for the procedure is reduced, making it clinically feasible in a busy clinical sitting. (1) To study the accuracy of real-time fMRI in comparison to conventional fMRI with off-line processing; (2) to determine its effectiveness in mapping the eloquent cortex and language lateralization in comparison to invasive procedures such as intraoperative cortical stimulation and Wada testing; and (3) to evaluate the role of fMRI in presurgical decision making in children with epilepsy. A total of 23 patients (age range 6-18 years) underwent fMRI with sensorimotor, visual and language paradigms. Data processing was done in real time using in-line BOLD. The results of real-time fMRI matched those of off-line processing done using the well-accepted standard technique of statistical parametric mapping (SPM) in all the initial ten patients in whom the two techniques were compared. Coregistration of the fMRI data on a 3-D FLAIR sequence rather than a T1-weighted image gave better information regarding the relationship of the lesion to the area of activation. The results of intraoperative cortical stimulation and fMRI matched in six out of six patients, while the Wada test and fMRI had similar results in four out of five patients in whom these techniques were performed. In the majority of patients in this series the technique influenced patient management. Real-time fMRI is an easily performed and reliable technique in the presurgical workup of children with epilepsy. (orig.)

  7. Real-time functional MR imaging (fMRI) for presurgical evaluation of paediatric epilepsy

    International Nuclear Information System (INIS)

    Kesavadas, Chandrasekharan; Thomas, Bejoy; Kumar Gupta, Arun; Sujesh, Sreedharan; Ashalata, Radhakrishnan; Radhakrishnan, Kurupath; Abraham, Mathew

    2007-01-01

    The role of fMRI in the presurgical evaluation of children with intractable epilepsy is being increasingly recognized. Real-time fMRI allows the clinician to visualize functional brain activation in real time. Since there is no off-line data analysis as in conventional fMRI, the overall time for the procedure is reduced, making it clinically feasible in a busy clinical sitting. (1) To study the accuracy of real-time fMRI in comparison to conventional fMRI with off-line processing; (2) to determine its effectiveness in mapping the eloquent cortex and language lateralization in comparison to invasive procedures such as intraoperative cortical stimulation and Wada testing; and (3) to evaluate the role of fMRI in presurgical decision making in children with epilepsy. A total of 23 patients (age range 6-18 years) underwent fMRI with sensorimotor, visual and language paradigms. Data processing was done in real time using in-line BOLD. The results of real-time fMRI matched those of off-line processing done using the well-accepted standard technique of statistical parametric mapping (SPM) in all the initial ten patients in whom the two techniques were compared. Coregistration of the fMRI data on a 3-D FLAIR sequence rather than a T1-weighted image gave better information regarding the relationship of the lesion to the area of activation. The results of intraoperative cortical stimulation and fMRI matched in six out of six patients, while the Wada test and fMRI had similar results in four out of five patients in whom these techniques were performed. In the majority of patients in this series the technique influenced patient management. Real-time fMRI is an easily performed and reliable technique in the presurgical workup of children with epilepsy. (orig.)

  8. Motor function deficits in schizophrenia: an fMRI and VBM study

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    Singh, Sadhana; Modi, Shilpi; Kumar, Pawan; Singh, Namita; Khushu, Subash [Institute of Nuclear Medicine and Allied Sciences (INMAS), NMR Research Center, Delhi (India); Goyal, Satnam; Bhatia, Triptish; Deshpande, Smita N. [RML Hospital, PGIMER, New Delhi (India)

    2014-05-15

    To investigate whether the motor functional alterations in schizophrenia (SZ) are also associated with structural changes in the related brain areas using functional magnetic resonance imaging (fMRI) and voxel-based morphometry (VBM). A sample of 14 right-handed SZ patients and 14 right-handed healthy control subjects matched for age, sex, and education were examined with structural high-resolution T1-weighted MRI; fMRI images were obtained during right index finger-tapping task in the same session. fMRI results showed reduced functional activation in the motor areas (contralateral precentral and postcentral gyrus) and ipsilateral cerebellum in SZ subjects as compared to healthy controls (n = 14). VBM analysis also revealed reduced grey matter in motor areas and white matter reduction in cerebellum of SZ subjects as compared to controls. The present study provides an evidence for a possible association between structural alterations in the motor cortex and disturbed functional activation in the motor areas in persons affected with SZ during a simple finger-tapping task. (orig.)

  9. Motor function deficits in schizophrenia: an fMRI and VBM study

    International Nuclear Information System (INIS)

    Singh, Sadhana; Modi, Shilpi; Kumar, Pawan; Singh, Namita; Khushu, Subash; Goyal, Satnam; Bhatia, Triptish; Deshpande, Smita N.

    2014-01-01

    To investigate whether the motor functional alterations in schizophrenia (SZ) are also associated with structural changes in the related brain areas using functional magnetic resonance imaging (fMRI) and voxel-based morphometry (VBM). A sample of 14 right-handed SZ patients and 14 right-handed healthy control subjects matched for age, sex, and education were examined with structural high-resolution T1-weighted MRI; fMRI images were obtained during right index finger-tapping task in the same session. fMRI results showed reduced functional activation in the motor areas (contralateral precentral and postcentral gyrus) and ipsilateral cerebellum in SZ subjects as compared to healthy controls (n = 14). VBM analysis also revealed reduced grey matter in motor areas and white matter reduction in cerebellum of SZ subjects as compared to controls. The present study provides an evidence for a possible association between structural alterations in the motor cortex and disturbed functional activation in the motor areas in persons affected with SZ during a simple finger-tapping task. (orig.)

  10. Assessment of language lateralization with functional magnetic resonance imaging (fMRI)

    International Nuclear Information System (INIS)

    Salagierska-Barwinska, A.; Goraj, B.

    2004-01-01

    fMRI offers powerful methods to delineate which brain regions are engaged in language processing in the intact brain. Until now hemisphere dominance for language has been usually assessed by means of the intraoperative methods: the Wada test or electrocortical stimulation mapping. Recently functional MRI becomes the valuable method in determining hemisphere dominance for language. fMRI study was proved to be concordant with invasive measures. fMRI was carried out in 30 healthy selected participants (15 females: 10 strongly right-handed and 5 strongly left-handed; 15 males: 10 strongly right-handed and 5 strongly left-handed). The subject's handedness was assessed by standardized psychological tests inter alia the 'lateralization inventory'. Two different language tasks were used: a verb generation task and a phonological task. Subjects were scanned,while performing experimental block. The block contained alternately 8 active (language task) and 8 control conditions. Statistical analysis of evoked blood oxygenation level-dependent BOLD) responses, measured with echo planar imagining (1.5 T) were used. During a verb generation task in strongly right or left handed subjects the inferior frontal region was activated on the side opposite to the subject's handedness determined by the psychological test. Our fMRI studies demonstrated no gender effects on brain during these language tasks. Our study suggests that fMRI is a good device for the study of the language organization. The advantage of fMRI is its capacity for exact localization of activated areas. fMRI together with adequate neurolinguistic test could be promising routine preoperative tool in identification hemisphere dominance for language. These results encourage to further investigation for evaluating correlation in patients with brain injuries. (author)

  11. Bayesian spatiotemporal model of fMRI data using transfer functions.

    Science.gov (United States)

    Quirós, Alicia; Diez, Raquel Montes; Wilson, Simon P

    2010-09-01

    This research describes a new Bayesian spatiotemporal model to analyse BOLD fMRI studies. In the temporal dimension, we describe the shape of the hemodynamic response function (HRF) with a transfer function model. The spatial continuity and local homogeneity of the evoked responses are modelled by a Gaussian Markov random field prior on the parameter indicating activations. The proposal constitutes an extension of the spatiotemporal model presented in a previous approach [Quirós, A., Montes Diez, R. and Gamerman, D., 2010. Bayesian spatiotemporal model of fMRI data, Neuroimage, 49: 442-456], offering more flexibility in the estimation of the HRF and computational advantages in the resulting MCMC algorithm. Simulations from the model are performed in order to ascertain the performance of the sampling scheme and the ability of the posterior to estimate model parameters, as well as to check the model sensitivity to signal to noise ratio. Results are shown on synthetic data and on a real data set from a block-design fMRI experiment. Copyright (c) 2010 Elsevier Inc. All rights reserved.

  12. A SVM-based quantitative fMRI method for resting-state functional network detection.

    Science.gov (United States)

    Song, Xiaomu; Chen, Nan-kuei

    2014-09-01

    Resting-state functional magnetic resonance imaging (fMRI) aims to measure baseline neuronal connectivity independent of specific functional tasks and to capture changes in the connectivity due to neurological diseases. Most existing network detection methods rely on a fixed threshold to identify functionally connected voxels under the resting state. Due to fMRI non-stationarity, the threshold cannot adapt to variation of data characteristics across sessions and subjects, and generates unreliable mapping results. In this study, a new method is presented for resting-state fMRI data analysis. Specifically, the resting-state network mapping is formulated as an outlier detection process that is implemented using one-class support vector machine (SVM). The results are refined by using a spatial-feature domain prototype selection method and two-class SVM reclassification. The final decision on each voxel is made by comparing its probabilities of functionally connected and unconnected instead of a threshold. Multiple features for resting-state analysis were extracted and examined using an SVM-based feature selection method, and the most representative features were identified. The proposed method was evaluated using synthetic and experimental fMRI data. A comparison study was also performed with independent component analysis (ICA) and correlation analysis. The experimental results show that the proposed method can provide comparable or better network detection performance than ICA and correlation analysis. The method is potentially applicable to various resting-state quantitative fMRI studies. Copyright © 2014 Elsevier Inc. All rights reserved.

  13. The power of using functional fMRI on small rodents to study brain pharmacology and disease

    OpenAIRE

    Jonckers, Elisabeth; Shah, Disha; Hamaide, Julie; Verhoye, Marleen; Van der Linden, Annemie

    2015-01-01

    Abstract: Functional magnetic resonance imaging (fMRI) is an excellent tool to study the effect of pharmacological modulations on brain function in a non-invasive and longitudinal manner. We introduce several blood oxygenation level dependent (BOLD) fMRI techniques, including resting state (rsfMRI), stimulus-evoked (st-fMRI), and pharmacological MRI (phMRI). Respectively, these techniques permit the assessment of functional connectivity during rest as well as brain activation triggered by sen...

  14. Functional Topography of Human Corpus Callosum: An fMRI Mapping Study

    OpenAIRE

    Fabri, Mara; Polonara, Gabriele

    2013-01-01

    The concept of a topographical map of the corpus callosum (CC) has emerged from human lesion studies and from electrophysiological and anatomical tracing investigations in other mammals. Over the last few years a rising number of researchers have been reporting functional magnetic resonance imaging (fMRI) activation in white matter, particularly the CC. In this study the scope for describing CC topography with fMRI was explored by evoking activation through simple sensory stimulation and moto...

  15. fMRI. Basics and clinical applications

    Energy Technology Data Exchange (ETDEWEB)

    Ulmer, Stephan; Jansen, Olav (eds.) [University Hospital of Schleswig-Holstein, Kiel (Germany). Inst. of Neuroradiology, Neurocenter

    2010-07-01

    Functional MRI (fMRI) and the basic method of BOLD imaging were introduced in 1993 by Seiji Ogawa. From very basic experiments, fMRI has evolved into a clinical application for daily routine brain imaging. There have been various improvements in both the imaging technique as such as well as in the statistical analysis. In this volume, experts in the field share their knowledge and point out possible technical barriers and problems explaining how to solve them. Starting from the very basics on the origin of the BOLD signal, the book covers technical issues, anatomical landmarks, presurgical applications, and special issues in various clinical fields. Other modalities for brain mapping such as PET, TMS, and MEG are also compared with fMRI. This book is intended to give a state-of-the-art overview and to serve as a reference and guide for clinical applications of fMRI. (orig.)

  16. Functional magnetic resonance imaging (fMRI) of motor deficits in schizophrenia

    International Nuclear Information System (INIS)

    Wenz, F.; Floemer, F.; Kaick, G. van

    1995-01-01

    The purpose of this study was to investigate differences in the cerebral activation pattern in ten schizophrenic patients and ten healthy volunteers using functional MRI. fMRI was performed using a modified FLASH sequence (TR/TE/α=100/60/40 ) and a conventional 1.5 T MR scanner. Colorcoded statistical parametric maps based on Student's t-test were calculated. Activation strength was quantified using a 5x6 grid overlay. The volunteers showed a higher activation strength during left hand movement compared to right hand movement. This lateralization effect was reversed in patients who showed overall reduced activation strength. Disturbed interhemispheric balance in schizophrenic patients during motor task performance can be demonstrated using fMRI. (orig.) [de

  17. Integration of fMRI, NIROT and ERP for studies of human brain function.

    Science.gov (United States)

    Gore, John C; Horovitz, Silvina G; Cannistraci, Christopher J; Skudlarski, Pavel

    2006-05-01

    Different methods of assessing human brain function possess specific advantages and disadvantages compared to others, but it is believed that combining different approaches will provide greater information than can be obtained from each alone. For example, functional magnetic resonance imaging (fMRI) has good spatial resolution but poor temporal resolution, whereas the converse is true for electrophysiological recordings (event-related potentials or ERPs). In this review of recent work, we highlight a novel approach to combining these modalities in a manner designed to increase information on the origins and locations of the generators of specific ERPs and the relationship between fMRI and ERP signals. Near infrared imaging techniques have also been studied as alternatives to fMRI and can be readily integrated with simultaneous electrophysiological recordings. Each of these modalities may in principle be also used in so-called steady-state acquisitions in which the correlational structure of signals from the brain may be analyzed to provide new insights into brain function.

  18. Mapping of cognitive functions in chronic intractable epilepsy: Role of fMRI

    International Nuclear Information System (INIS)

    Chaudhary, Kapil; Kumaran, S Senthil; Chandra, Sarat P; Wadhawan, Ashima Nehra; Tripathi, Manjari

    2014-01-01

    Functional magnetic resonance imaging (fMRI), a non-invasive technique with high spatial resolution and blood oxygen level dependent (BOLD) contrast, has been applied to localize and map cognitive functions in the clinical condition of chronic intractable epilepsy. fMRI was used to map the language and memory network in patients of chronic intractable epilepsy pre- and post-surgery. After obtaining approval from the institutional ethics committee, six patients with intractable epilepsy with an equal number of age-matched controls were recruited in the study. A 1.5 T MR scanner with 12-channel head coil, integrated with audio-visual fMRI accessories was used. Echo planar imaging sequence was used for BOLD studies. There were two sessions in TLE (pre- and post-surgery). In TLE patients, BOLD activation increased post-surgery in comparison of pre-surgery in inferior frontal gyrus (IFG), middle frontal gyrus (MFG), and superior temporal gyrus (STG), during semantic lexical, judgment, comprehension, and semantic memory tasks. Functional MRI is useful to study the basic concepts related to language and memory lateralization in TLE and guide surgeons for preservation of important brain areas during ATLR. This will help in understanding future directions for the diagnosis and treatment of such disease

  19. Mapping of cognitive functions in chronic intractable epilepsy: Role of fMRI

    Directory of Open Access Journals (Sweden)

    Kapil Chaudhary

    2014-01-01

    Full Text Available Background: Functional magnetic resonance imaging (fMRI, a non-invasive technique with high spatial resolution and blood oxygen level dependent (BOLD contrast, has been applied to localize and map cognitive functions in the clinical condition of chronic intractable epilepsy. Purpose: fMRI was used to map the language and memory network in patients of chronic intractable epilepsy pre- and post-surgery. Materials and Methods: After obtaining approval from the institutional ethics committee, six patients with intractable epilepsy with an equal number of age-matched controls were recruited in the study. A 1.5 T MR scanner with 12-channel head coil, integrated with audio-visual fMRI accessories was used. Echo planar imaging sequence was used for BOLD studies. There were two sessions in TLE (pre- and post-surgery. Results: In TLE patients, BOLD activation increased post-surgery in comparison of pre-surgery in inferior frontal gyrus (IFG, middle frontal gyrus (MFG, and superior temporal gyrus (STG, during semantic lexical, judgment, comprehension, and semantic memory tasks. Conclusion: Functional MRI is useful to study the basic concepts related to language and memory lateralization in TLE and guide surgeons for preservation of important brain areas during ATLR. This will help in understanding future directions for the diagnosis and treatment of such disease.

  20. Functional brain segmentation using inter-subject correlation in fMRI.

    Science.gov (United States)

    Kauppi, Jukka-Pekka; Pajula, Juha; Niemi, Jari; Hari, Riitta; Tohka, Jussi

    2017-05-01

    The human brain continuously processes massive amounts of rich sensory information. To better understand such highly complex brain processes, modern neuroimaging studies are increasingly utilizing experimental setups that better mimic daily-life situations. A new exploratory data-analysis approach, functional segmentation inter-subject correlation analysis (FuSeISC), was proposed to facilitate the analysis of functional magnetic resonance (fMRI) data sets collected in these experiments. The method provides a new type of functional segmentation of brain areas, not only characterizing areas that display similar processing across subjects but also areas in which processing across subjects is highly variable. FuSeISC was tested using fMRI data sets collected during traditional block-design stimuli (37 subjects) as well as naturalistic auditory narratives (19 subjects). The method identified spatially local and/or bilaterally symmetric clusters in several cortical areas, many of which are known to be processing the types of stimuli used in the experiments. The method is not only useful for spatial exploration of large fMRI data sets obtained using naturalistic stimuli, but also has other potential applications, such as generation of a functional brain atlases including both lower- and higher-order processing areas. Finally, as a part of FuSeISC, a criterion-based sparsification of the shared nearest-neighbor graph was proposed for detecting clusters in noisy data. In the tests with synthetic data, this technique was superior to well-known clustering methods, such as Ward's method, affinity propagation, and K-means ++. Hum Brain Mapp 38:2643-2665, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  1. Blood Flow and Brain Function: Investigations of neurovascular coupling using BOLD fMRI at 7 tesla

    NARCIS (Netherlands)

    Siero, J.C.W.

    2013-01-01

    The advent of ultra high field (7 tesla) MRI systems has opened the possibility to probe biological processes of the human body in great detail. Especially for studying brain function using BOLD fMRI there is a large benefit from the increased magnetic field strength. BOLD fMRI is the working horse

  2. Advances in fMRI Real-Time Neurofeedback.

    Science.gov (United States)

    Watanabe, Takeo; Sasaki, Yuka; Shibata, Kazuhisa; Kawato, Mitsuo

    2017-12-01

    Functional magnetic resonance imaging (fMRI) neurofeedback is a type of biofeedback in which real-time online fMRI signals are used to self-regulate brain function. Since its advent in 2003 significant progress has been made in fMRI neurofeedback techniques. Specifically, the use of implicit protocols, external rewards, multivariate analysis, and connectivity analysis has allowed neuroscientists to explore a possible causal involvement of modified brain activity in modified behavior. These techniques have also been integrated into groundbreaking new neurofeedback technologies, specifically decoded neurofeedback (DecNef) and functional connectivity-based neurofeedback (FCNef). By modulating neural activity and behavior, DecNef and FCNef have substantially advanced both basic and clinical research. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

  3. Preoperative functional magnetic resonance imaging (fMRI) and transcranial magnetic stimulation (TMS)

    DEFF Research Database (Denmark)

    Hartwigsen, G.; Siebner, Hartwig R.; Stippich, C.

    2010-01-01

    Neurosurgical resection of brain lesions aims to maximize excision while minimizing the risk of permanent injury to the surrounding intact brain tissue and resulting neurological deficits. While direct electrical cortical stimulation at the time of surgery allows the precise identification...... of essential cortex, it cannot provide information preoperatively for surgical planning.Brain imaging techniques such as functional magnetic resonance imaging (fMRI), magnetoencephalography (MEG) and transcranial magnetic stimulation (TMS) are increasingly being used to localize functionally critical cortical......, if the stimulated cortex makes a critical contribution to the brain functions subserving the task. While the relationship between task and functional activation as revealed by fMRI is correlative in nature, the neurodisruptive effect of TMS reflects a causal effect on brain activity.The use of preoperative f...

  4. High-field fMRI unveils orientation columns in humans.

    Science.gov (United States)

    Yacoub, Essa; Harel, Noam; Ugurbil, Kâmil

    2008-07-29

    Functional (f)MRI has revolutionized the field of human brain research. fMRI can noninvasively map the spatial architecture of brain function via localized increases in blood flow after sensory or cognitive stimulation. Recent advances in fMRI have led to enhanced sensitivity and spatial accuracy of the measured signals, indicating the possibility of detecting small neuronal ensembles that constitute fundamental computational units in the brain, such as cortical columns. Orientation columns in visual cortex are perhaps the best known example of such a functional organization in the brain. They cannot be discerned via anatomical characteristics, as with ocular dominance columns. Instead, the elucidation of their organization requires functional imaging methods. However, because of insufficient sensitivity, spatial accuracy, and image resolution of the available mapping techniques, thus far, they have not been detected in humans. Here, we demonstrate, by using high-field (7-T) fMRI, the existence and spatial features of orientation- selective columns in humans. Striking similarities were found with the known spatial features of these columns in monkeys. In addition, we found that a larger number of orientation columns are devoted to processing orientations around 90 degrees (vertical stimuli with horizontal motion), whereas relatively similar fMRI signal changes were observed across any given active column. With the current proliferation of high-field MRI systems and constant evolution of fMRI techniques, this study heralds the exciting prospect of exploring unmapped and/or unknown columnar level functional organizations in the human brain.

  5. Clinical fMRI of language function in aphasic patients: Reading paradigm successful, while word generation paradigm fails

    International Nuclear Information System (INIS)

    Engstroem, Maria; Landtblom, Anne-Marie; Ragnehed, Mattias; Lundberg, Peter; Karlsson, Marie; Crone, Marie; Antepohl, Wolfram

    2010-01-01

    Background: In fMRI examinations, it is very important to select appropriate paradigms assessing the brain function of interest. In addition, the patients' ability to perform the required cognitive tasks during fMRI must be taken into account. Purpose: To evaluate two language paradigms, word generation and sentence reading for their usefulness in examinations of aphasic patients and to make suggestions for improvements of clinical fMRI. Material and Methods: Five patients with aphasia after stroke or trauma sequelae were examined by fMRI. The patients' language ability was screened by neurolinguistic tests and elementary pre-fMRI language tests. Results: The sentence-reading paradigm succeeded to elicit adequate language-related activation in perilesional areas whereas the word generation paradigm failed. These findings were consistent with results on the behavioral tests in that all patients showed very poor performance in phonemic fluency, but scored well above mean at a reading comprehension task. Conclusion: The sentence-reading paradigm is appropriate to assess language function in this patient group, while the word-generation paradigm seems to be inadequate. In addition, it is crucial to use elementary pre-fMRI language tests to guide the fMRI paradigm decision.

  6. Clinical fMRI of language function in aphasic patients: Reading paradigm successful, while word generation paradigm fails

    Energy Technology Data Exchange (ETDEWEB)

    Engstroem, Maria; Landtblom, Anne-Marie; Ragnehed, Mattias; Lundberg, Peter (Center for Medical Image Science and Visualization (CMIV), Linkoeping Univ., Linkoeping (Sweden)), e-mail: maria.engstrom@liu.se; Karlsson, Marie; Crone, Marie (Dept. of Clinical and Experimental Medicine/Logopedics, Linkoeping Univ., Linkoeping (Sweden)); Antepohl, Wolfram (Dept. of Clinical and Experimental Medicine/Rehabilitation, Linkoeping Univ., Linkoeping (Sweden))

    2010-07-15

    Background: In fMRI examinations, it is very important to select appropriate paradigms assessing the brain function of interest. In addition, the patients' ability to perform the required cognitive tasks during fMRI must be taken into account. Purpose: To evaluate two language paradigms, word generation and sentence reading for their usefulness in examinations of aphasic patients and to make suggestions for improvements of clinical fMRI. Material and Methods: Five patients with aphasia after stroke or trauma sequelae were examined by fMRI. The patients' language ability was screened by neurolinguistic tests and elementary pre-fMRI language tests. Results: The sentence-reading paradigm succeeded to elicit adequate language-related activation in perilesional areas whereas the word generation paradigm failed. These findings were consistent with results on the behavioral tests in that all patients showed very poor performance in phonemic fluency, but scored well above mean at a reading comprehension task. Conclusion: The sentence-reading paradigm is appropriate to assess language function in this patient group, while the word-generation paradigm seems to be inadequate. In addition, it is crucial to use elementary pre-fMRI language tests to guide the fMRI paradigm decision.

  7. Monkey cortex through fMRI glasses.

    Science.gov (United States)

    Vanduffel, Wim; Zhu, Qi; Orban, Guy A

    2014-08-06

    In 1998 several groups reported the feasibility of fMRI experiments in monkeys, with the goal to bridge the gap between invasive nonhuman primate studies and human functional imaging. These studies yielded critical insights in the neuronal underpinnings of the BOLD signal. Furthermore, the technology has been successful in guiding electrophysiological recordings and identifying focal perturbation targets. Finally, invaluable information was obtained concerning human brain evolution. We here provide a comprehensive overview of awake monkey fMRI studies mainly confined to the visual system. We review the latest insights about the topographic organization of monkey visual cortex and discuss the spatial relationships between retinotopy and category- and feature-selective clusters. We briefly discuss the functional layout of parietal and frontal cortex and continue with a summary of some fascinating functional and effective connectivity studies. Finally, we review recent comparative fMRI experiments and speculate about the future of nonhuman primate imaging. Copyright © 2014 Elsevier Inc. All rights reserved.

  8. Single-trial EEG-informed fMRI analysis of emotional decision problems in hot executive function.

    Science.gov (United States)

    Guo, Qian; Zhou, Tiantong; Li, Wenjie; Dong, Li; Wang, Suhong; Zou, Ling

    2017-07-01

    Executive function refers to conscious control in psychological process which relates to thinking and action. Emotional decision is a part of hot executive function and contains emotion and logic elements. As a kind of important social adaptation ability, more and more attention has been paid in recent years. Gambling task can be well performed in the study of emotional decision. As fMRI researches focused on gambling task show not completely consistent brain activation regions, this study adopted EEG-fMRI fusion technology to reveal brain neural activity related with feedback stimuli. In this study, an EEG-informed fMRI analysis was applied to process simultaneous EEG-fMRI data. First, relative power-spectrum analysis and K-means clustering method were performed separately to extract EEG-fMRI features. Then, Generalized linear models were structured using fMRI data and using different EEG features as regressors. The results showed that in the win versus loss stimuli, the activated regions almost covered the caudate, the ventral striatum (VS), the orbital frontal cortex (OFC), and the cingulate. Wide activation areas associated with reward and punishment were revealed by the EEG-fMRI integration analysis than the conventional fMRI results, such as the posterior cingulate and the OFC. The VS and the medial prefrontal cortex (mPFC) were found when EEG power features were performed as regressors of GLM compared with results entering the amplitudes of feedback-related negativity (FRN) as regressors. Furthermore, the brain region activation intensity was the strongest when theta-band power was used as a regressor compared with the other two fusion results. The EEG-based fMRI analysis can more accurately depict the whole-brain activation map and analyze emotional decision problems.

  9. Functional and structural abnormalities associated with empathy in patients with schizophrenia: An fMRI and VBM study

    OpenAIRE

    Singh, Sadhana; Modi, Shilpi; Goyal, Satnam; Kaur, Prabhjot; Singh, Namita; Bhatia, Triptish; Deshpande, Smita N; Khushu, Subash

    2015-01-01

    Empathy deficit is a core feature of schizophrenia which may lead to social dysfunction. The present study was carried out to investigate functional and structural abnormalities associated with empathy in patients with schizophrenia using functional magnetic resonance imaging (fMRI) and voxel-based morphometry (VBM). A sample of 14 schizophrenia patients and 14 healthy control subjects matched for age, sex and education were examined with structural high-resolution T1-weighted MRI; fMRI image...

  10. Simultaneous functional imaging using fPET and fMRI

    Energy Technology Data Exchange (ETDEWEB)

    Villien, Marjorie [CERMEP (France)

    2015-05-18

    Brain mapping of task-associated changes in metabolism with PET has been accomplished by subtracting scans acquired during two distinct static states. We have demonstrated that PET can provide truly dynamic information on cerebral energy metabolism using constant infusion of FDG and multiple stimuli in a single experiment. We demonstrate here that the functional PET (fPET-FDG) method accomplished simultaneously with fMRI, can enable the first direct comparisons in time, space and magnitude of hemodynamics and oxygen and glucose consumption. The imaging studies were performed on a 3T Tim-Trio MR scanner modified to support an MR-compatible BrainPET insert. Ten healthy subjects were included. The total PET acquisition and infusion time was 90 minutes. We did 3 blocks of right hand fingers tapping for 10 minutes at 30, 50 and 70 minutes after the beginning of the PET acquisition. ASL and BOLD imaging were acquired simultaneously during the motor paradigm. Changes in glucose utilization are easily observed as changes in the TAC slope of the PET data (FDG utilization rate) and in the derivative signal during motor stimuli in the activated voxels. PET and MRI (ASL, and BOLD) activations are largely colocalized but with very different statistical significance and temporal dynamic, especially in the ipsilateral side of the stimuli. This study demonstrated that motor activation can be measured dynamically during a single FDG PET scan. The complementary nature of fPET-FDG to fMRI capitalizes on the emerging technology of hybrid MR-PET scanners. fPET-FDG, combined with quantitative fMRI methods, allow us to simultaneously measure dynamic changes in glucose utilization and hemodynamic, addressing vital questions about neurovascular coupling.

  11. Simultaneous functional imaging using fPET and fMRI

    International Nuclear Information System (INIS)

    Villien, Marjorie

    2015-01-01

    Brain mapping of task-associated changes in metabolism with PET has been accomplished by subtracting scans acquired during two distinct static states. We have demonstrated that PET can provide truly dynamic information on cerebral energy metabolism using constant infusion of FDG and multiple stimuli in a single experiment. We demonstrate here that the functional PET (fPET-FDG) method accomplished simultaneously with fMRI, can enable the first direct comparisons in time, space and magnitude of hemodynamics and oxygen and glucose consumption. The imaging studies were performed on a 3T Tim-Trio MR scanner modified to support an MR-compatible BrainPET insert. Ten healthy subjects were included. The total PET acquisition and infusion time was 90 minutes. We did 3 blocks of right hand fingers tapping for 10 minutes at 30, 50 and 70 minutes after the beginning of the PET acquisition. ASL and BOLD imaging were acquired simultaneously during the motor paradigm. Changes in glucose utilization are easily observed as changes in the TAC slope of the PET data (FDG utilization rate) and in the derivative signal during motor stimuli in the activated voxels. PET and MRI (ASL, and BOLD) activations are largely colocalized but with very different statistical significance and temporal dynamic, especially in the ipsilateral side of the stimuli. This study demonstrated that motor activation can be measured dynamically during a single FDG PET scan. The complementary nature of fPET-FDG to fMRI capitalizes on the emerging technology of hybrid MR-PET scanners. fPET-FDG, combined with quantitative fMRI methods, allow us to simultaneously measure dynamic changes in glucose utilization and hemodynamic, addressing vital questions about neurovascular coupling.

  12. Behavior, neuropsychology and fMRI.

    Science.gov (United States)

    Bennett, Maxwell R; Hatton, Sean; Hermens, Daniel F; Lagopoulos, Jim

    Cognitive neuroscientists in the late 20th century began the task of identifying the part(s) of the brain concerned with normal behavior as manifest in the psychological capacities as affective powers, reasoning, behaving purposively and the pursuit of goals, following introduction of the 'functional magnetic resonance imaging' (fMRI) method for identifying brain activity. For this research program to be successful two questions require satisfactory answers. First, as the fMRI method can currently only be used on stationary subjects, to what extent can neuropsychological tests applicable to such stationary subjects be correlated with normal behavior. Second, to what extent can correlations between the various neuropsychological tests on the one hand, and sites of brain activity determined with fMRI on the other, be regarded as established. The extent to which these questions have yet received satisfactory answers is reviewed, and suggestions made both for improving correlations of neuropsychological tests with behavior as well as with the results of fMRI-based observations. Copyright © 2016. Published by Elsevier Ltd.

  13. EEG-Informed fMRI: A Review of Data Analysis Methods

    Science.gov (United States)

    Abreu, Rodolfo; Leal, Alberto; Figueiredo, Patrícia

    2018-01-01

    The simultaneous acquisition of electroencephalography (EEG) with functional magnetic resonance imaging (fMRI) is a very promising non-invasive technique for the study of human brain function. Despite continuous improvements, it remains a challenging technique, and a standard methodology for data analysis is yet to be established. Here we review the methodologies that are currently available to address the challenges at each step of the data analysis pipeline. We start by surveying methods for pre-processing both EEG and fMRI data. On the EEG side, we focus on the correction for several MR-induced artifacts, particularly the gradient and pulse artifacts, as well as other sources of EEG artifacts. On the fMRI side, we consider image artifacts induced by the presence of EEG hardware inside the MR scanner, and the contamination of the fMRI signal by physiological noise of non-neuronal origin, including a review of several approaches to model and remove it. We then provide an overview of the approaches specifically employed for the integration of EEG and fMRI when using EEG to predict the blood oxygenation level dependent (BOLD) fMRI signal, the so-called EEG-informed fMRI integration strategy, the most commonly used strategy in EEG-fMRI research. Finally, we systematically review methods used for the extraction of EEG features reflecting neuronal phenomena of interest. PMID:29467634

  14. EEG-Informed fMRI: A Review of Data Analysis Methods

    Directory of Open Access Journals (Sweden)

    Rodolfo Abreu

    2018-02-01

    Full Text Available The simultaneous acquisition of electroencephalography (EEG with functional magnetic resonance imaging (fMRI is a very promising non-invasive technique for the study of human brain function. Despite continuous improvements, it remains a challenging technique, and a standard methodology for data analysis is yet to be established. Here we review the methodologies that are currently available to address the challenges at each step of the data analysis pipeline. We start by surveying methods for pre-processing both EEG and fMRI data. On the EEG side, we focus on the correction for several MR-induced artifacts, particularly the gradient and pulse artifacts, as well as other sources of EEG artifacts. On the fMRI side, we consider image artifacts induced by the presence of EEG hardware inside the MR scanner, and the contamination of the fMRI signal by physiological noise of non-neuronal origin, including a review of several approaches to model and remove it. We then provide an overview of the approaches specifically employed for the integration of EEG and fMRI when using EEG to predict the blood oxygenation level dependent (BOLD fMRI signal, the so-called EEG-informed fMRI integration strategy, the most commonly used strategy in EEG-fMRI research. Finally, we systematically review methods used for the extraction of EEG features reflecting neuronal phenomena of interest.

  15. Statistical Analysis Methods for the fMRI Data

    Directory of Open Access Journals (Sweden)

    Huseyin Boyaci

    2011-08-01

    Full Text Available Functional magnetic resonance imaging (fMRI is a safe and non-invasive way to assess brain functions by using signal changes associated with brain activity. The technique has become a ubiquitous tool in basic, clinical and cognitive neuroscience. This method can measure little metabolism changes that occur in active part of the brain. We process the fMRI data to be able to find the parts of brain that are involve in a mechanism, or to determine the changes that occur in brain activities due to a brain lesion. In this study we will have an overview over the methods that are used for the analysis of fMRI data.

  16. Functional brain activation differences in stuttering identified with a rapid fMRI sequence

    Science.gov (United States)

    Kraft, Shelly Jo; Choo, Ai Leen; Sharma, Harish; Ambrose, Nicoline G.

    2011-01-01

    The purpose of this study was to investigate whether brain activity related to the presence of stuttering can be identified with rapid functional MRI (fMRI) sequences that involved overt and covert speech processing tasks. The long-term goal is to develop sensitive fMRI approaches with developmentally appropriate tasks to identify deviant speech motor and auditory brain activity in children who stutter closer to the age at which recovery from stuttering is documented. Rapid sequences may be preferred for individuals or populations who do not tolerate long scanning sessions. In this report, we document the application of a picture naming and phoneme monitoring task in three minute fMRI sequences with adults who stutter (AWS). If relevant brain differences are found in AWS with these approaches that conform to previous reports, then these approaches can be extended to younger populations. Pairwise contrasts of brain BOLD activity between AWS and normally fluent adults indicated the AWS showed higher BOLD activity in the right inferior frontal gyrus (IFG), right temporal lobe and sensorimotor cortices during picture naming and and higher activity in the right IFG during phoneme monitoring. The right lateralized pattern of BOLD activity together with higher activity in sensorimotor cortices is consistent with previous reports, which indicates rapid fMRI sequences can be considered for investigating stuttering in younger participants. PMID:22133409

  17. Quantifying functional connectivity in multi-subject fMRI data using component models

    DEFF Research Database (Denmark)

    Madsen, Kristoffer Hougaard; Churchill, Nathan William; Mørup, Morten

    2017-01-01

    of functional connectivity, evaluated on both simulated and experimental resting-state fMRI data. It was demonstrated that highly flexible subject-specific component subspaces, as well as very constrained average models, are poor predictors of whole-brain functional connectivity, whereas the best...

  18. Activation Detection in fMRI Using Jeffrey Divergence

    Science.gov (United States)

    Seghouane, Abd-Krim

    2009-12-01

    A statistical test for detecting activated pixels in functional MRI (fMRI) data is proposed. For the derivation of this test, the fMRI time series measured at each voxel is modeled as the sum of a response signal which arises due to the experimentally controlled activation-baseline pattern, a nuisance component representing effects of no interest, and Gaussian white noise. The test is based on comparing the dimension of the voxels fMRI time series fitted data models with and without controlled activation-baseline pattern. The Jeffrey divergence is used for this comparison. The test has the advantage of not requiring a level of significance or a threshold to be provided.

  19. Electrophysiological correlates of the BOLD signal for EEG-informed fMRI

    Science.gov (United States)

    Murta, Teresa; Leite, Marco; Carmichael, David W; Figueiredo, Patrícia; Lemieux, Louis

    2015-01-01

    Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) are important tools in cognitive and clinical neuroscience. Combined EEG–fMRI has been shown to help to characterise brain networks involved in epileptic activity, as well as in different sensory, motor and cognitive functions. A good understanding of the electrophysiological correlates of the blood oxygen level-dependent (BOLD) signal is necessary to interpret fMRI maps, particularly when obtained in combination with EEG. We review the current understanding of electrophysiological–haemodynamic correlates, during different types of brain activity. We start by describing the basic mechanisms underlying EEG and BOLD signals and proceed by reviewing EEG-informed fMRI studies using fMRI to map specific EEG phenomena over the entire brain (EEG–fMRI mapping), or exploring a range of EEG-derived quantities to determine which best explain colocalised BOLD fluctuations (local EEG–fMRI coupling). While reviewing studies of different forms of brain activity (epileptic and nonepileptic spontaneous activity; cognitive, sensory and motor functions), a significant attention is given to epilepsy because the investigation of its haemodynamic correlates is the most common application of EEG-informed fMRI. Our review is focused on EEG-informed fMRI, an asymmetric approach of data integration. We give special attention to the invasiveness of electrophysiological measurements and the simultaneity of multimodal acquisitions because these methodological aspects determine the nature of the conclusions that can be drawn from EEG-informed fMRI studies. We emphasise the advantages of, and need for, simultaneous intracranial EEG–fMRI studies in humans, which recently became available and hold great potential to improve our understanding of the electrophysiological correlates of BOLD fluctuations. PMID:25277370

  20. Acoustic fMRI noise : Linear time-invariant system model

    NARCIS (Netherlands)

    Sierra, Carlos V. Rizzo; Versluis, Maarten J.; Hoogduin, Johannes M.; Duifhuis, Hendrikus (Diek)

    Functional magnetic resonance imaging (fMRI) enables sites of brain activation to be localized in human subjects. For auditory system studies, however, the acoustic noise generated by the scanner tends to interfere with the assessments of this activation. Understanding and modeling fMRI acoustic

  1. Tracking the Re-organization of Motor Functions After Disconnective Surgery: A Longitudinal fMRI and DTI Study

    Directory of Open Access Journals (Sweden)

    Cristina Rosazza

    2018-06-01

    Full Text Available Objective: Mechanisms of motor plasticity are critical to maintain motor functions after cerebral damage. This study explores the mechanisms of motor reorganization occurring before and after surgery in four patients with drug-refractory epilepsy candidate to disconnective surgery.Methods: We studied four patients with early damage, who underwent tailored hemispheric surgery in adulthood, removing the cortical motor areas and disconnecting the corticospinal tract (CST from the affected hemisphere. Motor functions were assessed clinically, with functional MRI (fMRI tasks of arm and leg movement and Diffusion Tensor Imaging (DTI before and after surgery with assessments of up to 3 years. Quantifications of fMRI motor activations and DTI fractional anisotropy (FA color maps were performed to assess the lateralization of motor network. We hypothesized that lateralization of motor circuits assessed preoperatively with fMRI and DTI was useful to evaluate the motor outcome in these patients.Results: In two cases preoperative DTI-tractography did not reconstruct the CST, and FA-maps were strongly asymmetric. In the other two cases, the affected CST appeared reduced compared to the contralateral one, with modest asymmetry in the FA-maps. fMRI showed different degrees of lateralization of the motor network and the SMA of the intact hemisphere was mostly engaged in all cases. After surgery, patients with a strongly lateralized motor network showed a stable performance. By contrast, a patient with a more bilateral pattern showed worsening of the upper limb function. For all cases, fMRI activations shifted to the intact hemisphere. Structural alterations of motor circuits, observed with FA values, continued beyond 1 year after surgery.Conclusion: In our case series fMRI and DTI could track the longitudinal reorganization of motor functions. In these four patients the more the paretic limbs recruited the intact hemisphere in primary motor and associative

  2. Tracking the Re-organization of Motor Functions After Disconnective Surgery: A Longitudinal fMRI and DTI Study.

    Science.gov (United States)

    Rosazza, Cristina; Deleo, Francesco; D'Incerti, Ludovico; Antelmi, Luigi; Tringali, Giovanni; Didato, Giuseppe; Bruzzone, Maria G; Villani, Flavio; Ghielmetti, Francesco

    2018-01-01

    Objective: Mechanisms of motor plasticity are critical to maintain motor functions after cerebral damage. This study explores the mechanisms of motor reorganization occurring before and after surgery in four patients with drug-refractory epilepsy candidate to disconnective surgery. Methods: We studied four patients with early damage, who underwent tailored hemispheric surgery in adulthood, removing the cortical motor areas and disconnecting the corticospinal tract (CST) from the affected hemisphere. Motor functions were assessed clinically, with functional MRI (fMRI) tasks of arm and leg movement and Diffusion Tensor Imaging (DTI) before and after surgery with assessments of up to 3 years. Quantifications of fMRI motor activations and DTI fractional anisotropy (FA) color maps were performed to assess the lateralization of motor network. We hypothesized that lateralization of motor circuits assessed preoperatively with fMRI and DTI was useful to evaluate the motor outcome in these patients. Results: In two cases preoperative DTI-tractography did not reconstruct the CST, and FA-maps were strongly asymmetric. In the other two cases, the affected CST appeared reduced compared to the contralateral one, with modest asymmetry in the FA-maps. fMRI showed different degrees of lateralization of the motor network and the SMA of the intact hemisphere was mostly engaged in all cases. After surgery, patients with a strongly lateralized motor network showed a stable performance. By contrast, a patient with a more bilateral pattern showed worsening of the upper limb function. For all cases, fMRI activations shifted to the intact hemisphere. Structural alterations of motor circuits, observed with FA values, continued beyond 1 year after surgery. Conclusion: In our case series fMRI and DTI could track the longitudinal reorganization of motor functions. In these four patients the more the paretic limbs recruited the intact hemisphere in primary motor and associative areas, the

  3. Memory Deficits in Schizophrenia: A Selective Review of Functional Magnetic Resonance Imaging (fMRI Studies

    Directory of Open Access Journals (Sweden)

    Adrienne C. Lahti

    2013-06-01

    Full Text Available Schizophrenia is a complex chronic mental illness that is characterized by positive, negative and cognitive symptoms. Cognitive deficits are most predictive of long-term outcomes, with abnormalities in memory being the most robust finding. The advent of functional magnetic resonance imaging (fMRI has allowed exploring neural correlates of memory deficits in vivo. In this article, we will give a selective review of fMRI studies probing brain regions and functional networks that are thought to be related to abnormal memory performance in two memory systems prominently affected in schizophrenia; working memory and episodic memory. We revisit the classic “hypofrontality” hypothesis of working memory deficits and explore evidence for frontotemporal dysconnectivity underlying episodic memory abnormalities. We conclude that fMRI studies of memory deficits in schizophrenia are far from universal. However, the current literature does suggest that alterations are not isolated to a few brain regions, but are characterized by abnormalities within large-scale brain networks.

  4. fMRI in Parkinson’s Disease

    DEFF Research Database (Denmark)

    Siebner, Hartwig R.; Herz, Damian

    2013-01-01

    and reward-related behavior have shown that dopamine replacement can have detrimental effects on non-motor brain functions by altering physiological patterns of dopaminergic signaling. Neuroimaging can also be used to assess preclinical compensation of striatal dopaminergic denervation by studying......In this chapter we review recent advances in functional magnetic resonance imaging (fMRI) in Parkinson’s disease (PD). Covariance patterns of regional resting-state activity in functional brain networks can be used to distinguish Parkinson patients from healthy controls and might play an important...... role as a biomarker in the future. Analyses of motor activity and connectivity have revealed compensatory mechanisms for impaired function of cortico-subcortical feedback loops and have shown how attentional mechanisms modulate the activity in motor loops. Other fMRI studies probing cognitive functions...

  5. Multivoxel Pattern Analysis for fMRI Data: A Review

    Directory of Open Access Journals (Sweden)

    Abdelhak Mahmoudi

    2012-01-01

    Full Text Available Functional magnetic resonance imaging (fMRI exploits blood-oxygen-level-dependent (BOLD contrasts to map neural activity associated with a variety of brain functions including sensory processing, motor control, and cognitive and emotional functions. The general linear model (GLM approach is used to reveal task-related brain areas by searching for linear correlations between the fMRI time course and a reference model. One of the limitations of the GLM approach is the assumption that the covariance across neighbouring voxels is not informative about the cognitive function under examination. Multivoxel pattern analysis (MVPA represents a promising technique that is currently exploited to investigate the information contained in distributed patterns of neural activity to infer the functional role of brain areas and networks. MVPA is considered as a supervised classification problem where a classifier attempts to capture the relationships between spatial pattern of fMRI activity and experimental conditions. In this paper , we review MVPA and describe the mathematical basis of the classification algorithms used for decoding fMRI signals, such as support vector machines (SVMs. In addition, we describe the workflow of processing steps required for MVPA such as feature selection, dimensionality reduction, cross-validation, and classifier performance estimation based on receiver operating characteristic (ROC curves.

  6. Multivoxel Pattern Analysis for fMRI Data: A Review

    Science.gov (United States)

    Takerkart, Sylvain; Regragui, Fakhita; Boussaoud, Driss; Brovelli, Andrea

    2012-01-01

    Functional magnetic resonance imaging (fMRI) exploits blood-oxygen-level-dependent (BOLD) contrasts to map neural activity associated with a variety of brain functions including sensory processing, motor control, and cognitive and emotional functions. The general linear model (GLM) approach is used to reveal task-related brain areas by searching for linear correlations between the fMRI time course and a reference model. One of the limitations of the GLM approach is the assumption that the covariance across neighbouring voxels is not informative about the cognitive function under examination. Multivoxel pattern analysis (MVPA) represents a promising technique that is currently exploited to investigate the information contained in distributed patterns of neural activity to infer the functional role of brain areas and networks. MVPA is considered as a supervised classification problem where a classifier attempts to capture the relationships between spatial pattern of fMRI activity and experimental conditions. In this paper , we review MVPA and describe the mathematical basis of the classification algorithms used for decoding fMRI signals, such as support vector machines (SVMs). In addition, we describe the workflow of processing steps required for MVPA such as feature selection, dimensionality reduction, cross-validation, and classifier performance estimation based on receiver operating characteristic (ROC) curves. PMID:23401720

  7. Broadband Electrophysiological Dynamics Contribute to Global Resting-State fMRI Signal.

    Science.gov (United States)

    Wen, Haiguang; Liu, Zhongming

    2016-06-01

    Spontaneous activity observed with resting-state fMRI is used widely to uncover the brain's intrinsic functional networks in health and disease. Although many networks appear modular and specific, global and nonspecific fMRI fluctuations also exist and both pose a challenge and present an opportunity for characterizing and understanding brain networks. Here, we used a multimodal approach to investigate the neural correlates to the global fMRI signal in the resting state. Like fMRI, resting-state power fluctuations of broadband and arrhythmic, or scale-free, macaque electrocorticography and human magnetoencephalography activity were correlated globally. The power fluctuations of scale-free human electroencephalography (EEG) were coupled with the global component of simultaneously acquired resting-state fMRI, with the global hemodynamic change lagging the broadband spectral change of EEG by ∼5 s. The levels of global and nonspecific fluctuation and synchronization in scale-free population activity also varied across and depended on arousal states. Together, these results suggest that the neural origin of global resting-state fMRI activity is the broadband power fluctuation in scale-free population activity observable with macroscopic electrical or magnetic recordings. Moreover, the global fluctuation in neurophysiological and hemodynamic activity is likely modulated through diffuse neuromodulation pathways that govern arousal states and vigilance levels. This study provides new insights into the neural origin of resting-state fMRI. Results demonstrate that the broadband power fluctuation of scale-free electrophysiology is globally synchronized and directly coupled with the global component of spontaneous fMRI signals, in contrast to modularly synchronized fluctuations in oscillatory neural activity. These findings lead to a new hypothesis that scale-free and oscillatory neural processes account for global and modular patterns of functional connectivity observed

  8. Adaptation of a haptic robot in a 3T fMRI.

    Science.gov (United States)

    Snider, Joseph; Plank, Markus; May, Larry; Liu, Thomas T; Poizner, Howard

    2011-10-04

    Functional magnetic resonance imaging (fMRI) provides excellent functional brain imaging via the BOLD signal with advantages including non-ionizing radiation, millimeter spatial accuracy of anatomical and functional data, and nearly real-time analyses. Haptic robots provide precise measurement and control of position and force of a cursor in a reasonably confined space. Here we combine these two technologies to allow precision experiments involving motor control with haptic/tactile environment interaction such as reaching or grasping. The basic idea is to attach an 8 foot end effecter supported in the center to the robot allowing the subject to use the robot, but shielding it and keeping it out of the most extreme part of the magnetic field from the fMRI machine (Figure 1). The Phantom Premium 3.0, 6DoF, high-force robot (SensAble Technologies, Inc.) is an excellent choice for providing force-feedback in virtual reality experiments, but it is inherently non-MR safe, introduces significant noise to the sensitive fMRI equipment, and its electric motors may be affected by the fMRI's strongly varying magnetic field. We have constructed a table and shielding system that allows the robot to be safely introduced into the fMRI environment and limits both the degradation of the fMRI signal by the electrically noisy motors and the degradation of the electric motor performance by the strongly varying magnetic field of the fMRI. With the shield, the signal to noise ratio (SNR: mean signal/noise standard deviation) of the fMRI goes from a baseline of ~380 to ~330, and ~250 without the shielding. The remaining noise appears to be uncorrelated and does not add artifacts to the fMRI of a test sphere (Figure 2). The long, stiff handle allows placement of the robot out of range of the most strongly varying parts of the magnetic field so there is no significant effect of the fMRI on the robot. The effect of the handle on the robot's kinematics is minimal since it is lightweight (~2

  9. fMRI. Basics and clinical applications. 2. ed.

    Energy Technology Data Exchange (ETDEWEB)

    Ulmer, Stephan [Medizinisch Radiologisces Institut (MRI), Zuerich (Switzerland); Universitaetsklinikum Schleswig-Holstein, Kiel (Germany). Inst. fuer Neuroradiologie; Jansen, Olav (eds.) [Universitaetsklinikum Schleswig-Holstein, Kiel (Germany). Inst. fuer Neuroradiologie

    2013-11-01

    State of the art overview of fMRI. Covers technical issues, methods of statistical analysis, and the full range of clinical applications. Revised and expanded edition including discussion of novel aspects of analysis and further important applications. Includes comparisons with other brain mapping techniques and discussion of potential combined uses. Since functional MRI (fMRI) and the basic method of BOLD imaging were introduced in 1993 by Seiji Ogawa, fMRI has evolved into an invaluable clinical tool for routine brain imaging, and there have been substantial improvements in both the imaging technique itself and the associated statistical analysis. This book provides a state of the art overview of fMRI and its use in clinical practice. Experts in the field share their knowledge and explain how to overcome diverse potential technical barriers and problems. Starting from the very basics on the origin of the BOLD signal, the book covers technical issues, anatomical landmarks, the full range of clinical applications, methods of statistical analysis, and special issues in various clinical fields. Comparisons are made with other brain mapping techniques, such as DTI, PET, TMS, EEG, and MEG, and their combined use with fMRI is also discussed. Since the first edition, original chapters have been updated and new chapters added, covering both novel aspects of analysis and further important clinical applications.

  10. Functional connectivity in resting-state fMRI: Is linear correlation sufficient?

    Czech Academy of Sciences Publication Activity Database

    Hlinka, Jaroslav; Paluš, Milan; Vejmelka, Martin; Mantini, D.; Corbetta, M.

    2011-01-01

    Roč. 54, č. 3 (2011), s. 2218-2225 ISSN 1053-8119 R&D Projects: GA MŠk 7E08027 EU Projects: European Commission(XE) 200728 - BRAINSYNC Institutional research plan: CEZ:AV0Z10300504 Keywords : fMRI * functional connectivity * Gaussianity * nonlinearity * correlation * mutual information Subject RIV: FH - Neurology Impact factor: 5.895, year: 2011

  11. Probing the brain with molecular fMRI.

    Science.gov (United States)

    Ghosh, Souparno; Harvey, Peter; Simon, Jacob C; Jasanoff, Alan

    2018-04-09

    One of the greatest challenges of modern neuroscience is to incorporate our growing knowledge of molecular and cellular-scale physiology into integrated, organismic-scale models of brain function in behavior and cognition. Molecular-level functional magnetic resonance imaging (molecular fMRI) is a new technology that can help bridge these scales by mapping defined microscopic phenomena over large, optically inaccessible regions of the living brain. In this review, we explain how MRI-detectable imaging probes can be used to sensitize noninvasive imaging to mechanistically significant components of neural processing. We discuss how a combination of innovative probe design, advanced imaging methods, and strategies for brain delivery can make molecular fMRI an increasingly successful approach for spatiotemporally resolved studies of diverse neural phenomena, perhaps eventually in people. Copyright © 2018 Elsevier Ltd. All rights reserved.

  12. A receptor-based model for dopamine-induced fMRI signal

    Science.gov (United States)

    Mandeville, Joseph. B.; Sander, Christin Y. M.; Jenkins, Bruce G.; Hooker, Jacob M.; Catana, Ciprian; Vanduffel, Wim; Alpert, Nathaniel M.; Rosen, Bruce R.; Normandin, Marc D.

    2013-01-01

    This report describes a multi-receptor physiological model of the fMRI temporal response and signal magnitude evoked by drugs that elevate synaptic dopamine in basal ganglia. The model is formulated as a summation of dopamine’s effects at D1-like and D2-like receptor families, which produce functional excitation and inhibition, respectively, as measured by molecular indicators like adenylate cyclase or neuroimaging techniques like fMRI. Functional effects within the model are described in terms of relative changes in receptor occupancies scaled by receptor densities and neuro-vascular coupling constants. Using literature parameters, the model reconciles many discrepant observations and interpretations of pre-clinical data. Additionally, we present data showing that amphetamine stimulation produces fMRI inhibition at low doses and a biphasic response at higher doses in the basal ganglia of non-human primates (NHP), in agreement with model predictions based upon the respective levels of evoked dopamine. Because information about dopamine release is required to inform the fMRI model, we simultaneously acquired PET 11C-raclopride data in several studies to evaluate the relationship between raclopride displacement and assumptions about dopamine release. At high levels of dopamine release, results suggest that refinements of the model will be required to consistently describe the PET and fMRI data. Overall, the remarkable success of the model in describing a wide range of preclinical fMRI data indicate that this approach will be useful for guiding the design and analysis of basic science and clinical investigations and for interpreting the functional consequences of dopaminergic stimulation in normal subjects and in populations with dopaminergic neuroadaptations. PMID:23466936

  13. Functional resonance magnetic imaging (fMRI) in adolescents with idiopathic musculoskeletal pain: a paradigm of experimental pain

    OpenAIRE

    Molina, Juliana; Amaro, Edson; da Rocha, Liana Guerra Sanches; Jorge, Liliana; Santos, Flavia Heloisa; Len, Claudio A.

    2017-01-01

    Background Studies on functional magnetic resonance imaging (fMRI) have shown that adults with musculoskeletal pain syndromes tolerate smaller amount of pressure (pain) as well as differences in brain activation patterns in areas related to pain.The objective of this study was to evaluate, through fMRI, the brain activation in adolescents with idiopathic musculoskeletal pain (IMP) while performing an experimental paradigm of pain. Methods The study included 10 consecutive adolescents with idi...

  14. Improving fMRI reliability in presurgical mapping for brain tumours.

    Science.gov (United States)

    Stevens, M Tynan R; Clarke, David B; Stroink, Gerhard; Beyea, Steven D; D'Arcy, Ryan Cn

    2016-03-01

    Functional MRI (fMRI) is becoming increasingly integrated into clinical practice for presurgical mapping. Current efforts are focused on validating data quality, with reliability being a major factor. In this paper, we demonstrate the utility of a recently developed approach that uses receiver operating characteristic-reliability (ROC-r) to: (1) identify reliable versus unreliable data sets; (2) automatically select processing options to enhance data quality; and (3) automatically select individualised thresholds for activation maps. Presurgical fMRI was conducted in 16 patients undergoing surgical treatment for brain tumours. Within-session test-retest fMRI was conducted, and ROC-reliability of the patient group was compared to a previous healthy control cohort. Individually optimised preprocessing pipelines were determined to improve reliability. Spatial correspondence was assessed by comparing the fMRI results to intraoperative cortical stimulation mapping, in terms of the distance to the nearest active fMRI voxel. The average ROC-r reliability for the patients was 0.58±0.03, as compared to 0.72±0.02 in healthy controls. For the patient group, this increased significantly to 0.65±0.02 by adopting optimised preprocessing pipelines. Co-localisation of the fMRI maps with cortical stimulation was significantly better for more reliable versus less reliable data sets (8.3±0.9 vs 29±3 mm, respectively). We demonstrated ROC-r analysis for identifying reliable fMRI data sets, choosing optimal postprocessing pipelines, and selecting patient-specific thresholds. Data sets with higher reliability also showed closer spatial correspondence to cortical stimulation. ROC-r can thus identify poor fMRI data at time of scanning, allowing for repeat scans when necessary. ROC-r analysis provides optimised and automated fMRI processing for improved presurgical mapping. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence

  15. The Nuisance of Nuisance Regression: Spectral Misspecification in a Common Approach to Resting-State fMRI Preprocessing Reintroduces Noise and Obscures Functional Connectivity

    OpenAIRE

    Hallquist, Michael N.; Hwang, Kai; Luna, Beatriz

    2013-01-01

    Recent resting-state functional connectivity fMRI (RS-fcMRI) research has demonstrated that head motion during fMRI acquisition systematically influences connectivity estimates despite bandpass filtering and nuisance regression, which are intended to reduce such nuisance variability. We provide evidence that the effects of head motion and other nuisance signals are poorly controlled when the fMRI time series are bandpass-filtered but the regressors are unfiltered, resulting in the inadvertent...

  16. Resting-state fMRI and social cognition: An opportunity to connect.

    Science.gov (United States)

    Doruyter, Alex; Groenewold, Nynke A; Dupont, Patrick; Stein, Dan J; Warwick, James M

    2017-09-01

    Many psychiatric disorders are characterized by altered social cognition. The importance of social cognition has previously been recognized by the National Institute of Mental Health Research Domain Criteria project, in which it features as a core domain. Social task-based functional magnetic resonance imaging (fMRI) currently offers the most direct insight into how the brain processes social information; however, resting-state fMRI may be just as important in understanding the biology and network nature of social processing. Resting-state fMRI allows researchers to investigate the functional relationships between brain regions in a neutral state: so-called resting functional connectivity (RFC). There is evidence that RFC is predictive of how the brain processes information during social tasks. This is important because it shifts the focus from possibly context-dependent aberrations to context-independent aberrations in functional network architecture. Rather than being analysed in isolation, the study of resting-state brain networks shows promise in linking results of task-based fMRI results, structural connectivity, molecular imaging findings, and performance measures of social cognition-which may prove crucial in furthering our understanding of the social brain. Copyright © 2017 John Wiley & Sons, Ltd.

  17. fMRI paradigm designing and post-processing tools

    International Nuclear Information System (INIS)

    James, Jija S; Rajesh, PG; Chandran, Anuvitha VS; Kesavadas, Chandrasekharan

    2014-01-01

    In this article, we first review some aspects of functional magnetic resonance imaging (fMRI) paradigm designing for major cognitive functions by using stimulus delivery systems like Cogent, E-Prime, Presentation, etc., along with their technical aspects. We also review the stimulus presentation possibilities (block, event-related) for visual or auditory paradigms and their advantage in both clinical and research setting. The second part mainly focus on various fMRI data post-processing tools such as Statistical Parametric Mapping (SPM) and Brain Voyager, and discuss the particulars of various preprocessing steps involved (realignment, co-registration, normalization, smoothing) in these software and also the statistical analysis principles of General Linear Modeling for final interpretation of a functional activation result

  18. Functional and structural abnormalities associated with empathy in patients with schizophrenia: An fMRI and VBM study.

    Science.gov (United States)

    Singh, Sadhana; Modi, Shilpi; Goyal, Satnam; Kaur, Prabhjot; Singh, Namita; Bhatia, Triptish; Deshpande, Smita N; Khushu, Subash

    2015-06-01

    Empathy deficit is a core feature of schizophrenia which may lead to social dysfunction. The present study was carried out to investigate functional and structural abnormalities associated with empathy in patients with schizophrenia using functional magnetic resonance imaging (fMRI) and voxel-based morphometry (VBM). A sample of 14 schizophrenia patients and 14 healthy control subjects matched for age, sex and education were examined with structural highresolution T1-weighted MRI; fMRI images were obtained during empathy task in the same session. The analysis was carried out using SPM8 software. On behavioural assessment, schizophrenic patients (83.00+-29.04) showed less scores for sadness compared to healthy controls (128.70+-22.26) (p less than 0.001). fMRI results also showed reduced clusters of activation in the bilateral fusiform gyrus, left lingual gyrus, left middle and inferior occipital gyrus in schizophrenic subjects as compared to controls during empathy task. In the same brain areas, VBM results also showed reduced grey and white matter volumes. The present study provides an evidence for an association between structural alterations and disturbed functional brain activation during empathy task in persons affected with schizophrenia. These findings suggest a biological basis for social cognition deficits in schizophrenics.

  19. Identification of Voxels Confounded by Venous Signals Using Resting-State fMRI Functional Connectivity Graph Clustering

    Directory of Open Access Journals (Sweden)

    Klaudius eKalcher

    2015-12-01

    Full Text Available Identifying venous voxels in fMRI datasets is important to increase the specificity of fMRI analyses to microvasculature in the vicinity of the neural processes triggering the BOLD response. This is, however, difficult to achieve in particular in typical studies where magnitude images of BOLD EPI are the only data available. In this study, voxelwise functional connectivity graphs were computed on minimally preprocessed low TR (333 ms multiband resting-state fMRI data, using both high positive and negative correlations to define edges between nodes (voxels. A high correlation threshold for binarization ensures that most edges in the resulting sparse graph reflect the high coherence of signals in medium to large veins. Graph clustering based on the optimization of modularity was then employed to identify clusters of coherent voxels in this graph, and all clusters of 50 or more voxels were then interpreted as corresponding to medium to large veins. Indeed, a comparison with SWI reveals that 75.6 ± 5.9% of voxels within these large clusters overlap with veins visible in the SWI image or lie outside the brain parenchyma. Some of the remainingdifferences between the two modalities can be explained by imperfect alignment or geometric distortions between the two images. Overall, the graph clustering based method for identifying venous voxels has a high specificity as well as the additional advantages of being computed in the same voxel grid as the fMRI dataset itself and not needingany additional data beyond what is usually acquired (and exported in standard fMRI experiments.

  20. Material specific lateralization of medial temporal lobe function: An fMRI investigation.

    Science.gov (United States)

    Dalton, Marshall A; Hornberger, Michael; Piguet, Olivier

    2016-03-01

    The theory of material specific lateralization of memory function posits that left and right MTL regions are asymmetrically involved in mnemonic processing of verbal and nonverbal material respectively. Lesion and functional imaging (fMRI) studies provide robust evidence for a left MTL asymmetry in the verbal memory domain. Evidence for a right MTL/nonverbal asymmetry is not as robust. A handful of fMRI studies have investigated this issue but have generally utilised nonverbal stimuli which are amenable to semantic elaboration. This fMRI study aimed to investigate the neural correlates of recognition memory processing in 20 healthy young adults (mean age = 26 years) for verbal stimuli and nonverbal stimuli that were specifically designed to minimize verbalisation. Analyses revealed that the neural correlates of recognition memory processing for verbal and nonverbal stimuli were differentiable and asymmetrically recruited the left and right MTL respectively. The right perirhinal cortex and hippocampus were preferentially involved in successful recognition memory of items devoid of semantic information. In contrast, the left anterior hippocampus was preferentially involved in successful recognition memory of stimuli which contained semantic meaning. These results suggest that the left MTL is preferentially involved in mnemonic processing of verbal/semantic information. In contrast, the right MTL is preferentially involved in visual/non-semantic mnemonic processing. We propose that during development, the left MTL becomes specialised for verbal mnemonic processing due to its proximity with left lateralised cortical language processing areas while visual/non-semantic mnemonic processing gets 'crowded out' to become predominantly, but not completely, the domain of the right MTL. © 2015 Wiley Periodicals, Inc.

  1. Functional-anatomic study of episodic retrieval using fMRI. I. Retrieval effort versus retrieval success.

    Science.gov (United States)

    Buckner, R L; Koutstaal, W; Schacter, D L; Wagner, A D; Rosen, B R

    1998-04-01

    A number of recent functional imaging studies have identified brain areas activated during tasks involving episodic memory retrieval. The identification of such areas provides a foundation for targeted hypotheses regarding the more specific contributions that these areas make to episodic retrieval. As a beginning effort toward such an endeavor, whole-brain functional magnetic resonance imaging (fMRI) was used to examine 14 subjects during episodic word recognition in a block-designed fMRI experiment. Study conditions were manipulated by presenting either shallow or deep encoding tasks. This manipulation yielded two recognition conditions that differed with regard to retrieval effort and retrieval success: shallow encoding yielded low levels of recognition success with high levels of retrieval effort, and deep encoding yielded high levels of recognition success with low levels of effort. Many brain areas were activated in common by these two recognition conditions compared to a low-level fixation condition, including left and right prefrontal regions often detected during PET episodic retrieval paradigms (e.g., R. L. Buckner et al., 1996, J. Neurosci. 16, 6219-6235) thereby generalizing these findings to fMRI. Characterization of the activated regions in relation to the separate recognition conditions showed (1) bilateral anterior insular regions and a left dorsal prefrontal region were more active after shallow encoding, when retrieval demanded greatest effort, and (2) right anterior prefrontal cortex, which has been implicated in episodic retrieval, was most active during successful retrieval after deep encoding. We discuss these findings in relation to component processes involved in episodic retrieval and in the context of a companion study using event-related fMRI.

  2. The effect of fMRI task combinations on determining the hemispheric dominance of language functions

    International Nuclear Information System (INIS)

    Niskanen, Eini; Koenoenen, Mervi; Villberg, Ville; Aeikiae, Marja; Nissi, Mikko; Ranta-aho, Perttu; Karjalainen, Pasi; Saeisaenen, Laura; Mervaala, Esa; Kaelviaeinen, Reetta; Vanninen, Ritva

    2012-01-01

    The purpose of this study is to establish the most suitable combination of functional magnetic resonance imaging (fMRI) language tasks for clinical use in determining language dominance and to define the variability in laterality index (LI) and activation power between different combinations of language tasks. Activation patterns of different fMRI analyses of five language tasks (word generation, responsive naming, letter task, sentence comprehension, and word pair) were defined for 20 healthy volunteers (16 right-handed). LIs and sums of T values were calculated for each task separately and for four combinations of tasks in predefined regions of interest. Variability in terms of activation power and lateralization was defined in each analysis. In addition, the visual assessment of lateralization of language functions based on the individual fMRI activation maps was conducted by an experienced neuroradiologist. A combination analysis of word generation, responsive naming, and sentence comprehension was the most suitable in terms of activation power, robustness to detect essential language areas, and scanning time. In general, combination analyses of the tasks provided higher overall activation levels than single tasks and reduced the number of outlier voxels disturbing the calculation of LI. A combination of auditory and visually presented tasks that activate different aspects of language functions with sufficient activation power may be a useful task battery for determining language dominance in patients. (orig.)

  3. The effect of fMRI task combinations on determining the hemispheric dominance of language functions

    Energy Technology Data Exchange (ETDEWEB)

    Niskanen, Eini [University of Eastern Finland, Department of Applied Physics, Kuopio (Finland); Kuopio University Hospital, Department of Clinical Radiology, Kuopio (Finland); Koenoenen, Mervi [Kuopio University Hospital, Department of Clinical Radiology, Kuopio (Finland); Kuopio University Hospital, Department of Clinical Neurophysiology, Kuopio (Finland); Villberg, Ville; Aeikiae, Marja [Kuopio University Hospital, Department of Neurology, Kuopio (Finland); Nissi, Mikko; Ranta-aho, Perttu; Karjalainen, Pasi [University of Eastern Finland, Department of Applied Physics, Kuopio (Finland); Saeisaenen, Laura; Mervaala, Esa [Kuopio University Hospital, Department of Clinical Neurophysiology, Kuopio (Finland); University of Eastern Finland, Institute of Clinical Medicine, Clinical Neurophysiology, Kuopio (Finland); Kaelviaeinen, Reetta [Kuopio University Hospital, Department of Neurology, Kuopio (Finland); University of Eastern Finland, Institute of Clinical Medicine, Neurology, Kuopio (Finland); Vanninen, Ritva [Kuopio University Hospital, Department of Clinical Radiology, Kuopio (Finland); University of Eastern Finland, Institute of Clinical Medicine, Clinical Radiology, Kuopio (Finland)

    2012-04-15

    The purpose of this study is to establish the most suitable combination of functional magnetic resonance imaging (fMRI) language tasks for clinical use in determining language dominance and to define the variability in laterality index (LI) and activation power between different combinations of language tasks. Activation patterns of different fMRI analyses of five language tasks (word generation, responsive naming, letter task, sentence comprehension, and word pair) were defined for 20 healthy volunteers (16 right-handed). LIs and sums of T values were calculated for each task separately and for four combinations of tasks in predefined regions of interest. Variability in terms of activation power and lateralization was defined in each analysis. In addition, the visual assessment of lateralization of language functions based on the individual fMRI activation maps was conducted by an experienced neuroradiologist. A combination analysis of word generation, responsive naming, and sentence comprehension was the most suitable in terms of activation power, robustness to detect essential language areas, and scanning time. In general, combination analyses of the tasks provided higher overall activation levels than single tasks and reduced the number of outlier voxels disturbing the calculation of LI. A combination of auditory and visually presented tasks that activate different aspects of language functions with sufficient activation power may be a useful task battery for determining language dominance in patients. (orig.)

  4. The effect of fMRI task combinations on determining the hemispheric dominance of language functions.

    Science.gov (United States)

    Niskanen, Eini; Könönen, Mervi; Villberg, Ville; Nissi, Mikko; Ranta-Aho, Perttu; Säisänen, Laura; Karjalainen, Pasi; Aikiä, Marja; Kälviäinen, Reetta; Mervaala, Esa; Vanninen, Ritva

    2012-04-01

    The purpose of this study is to establish the most suitable combination of functional magnetic resonance imaging (fMRI) language tasks for clinical use in determining language dominance and to define the variability in laterality index (LI) and activation power between different combinations of language tasks. Activation patterns of different fMRI analyses of five language tasks (word generation, responsive naming, letter task, sentence comprehension, and word pair) were defined for 20 healthy volunteers (16 right-handed). LIs and sums of T values were calculated for each task separately and for four combinations of tasks in predefined regions of interest. Variability in terms of activation power and lateralization was defined in each analysis. In addition, the visual assessment of lateralization of language functions based on the individual fMRI activation maps was conducted by an experienced neuroradiologist. A combination analysis of word generation, responsive naming, and sentence comprehension was the most suitable in terms of activation power, robustness to detect essential language areas, and scanning time. In general, combination analyses of the tasks provided higher overall activation levels than single tasks and reduced the number of outlier voxels disturbing the calculation of LI. A combination of auditory and visually presented tasks that activate different aspects of language functions with sufficient activation power may be a useful task battery for determining language dominance in patients.

  5. Resting-State Seed-Based Analysis: An Alternative to Task-Based Language fMRI and Its Laterality Index.

    Science.gov (United States)

    Smitha, K A; Arun, K M; Rajesh, P G; Thomas, B; Kesavadas, C

    2017-06-01

    Language is a cardinal function that makes human unique. Preservation of language function poses a great challenge for surgeons during resection. The aim of the study was to assess the efficacy of resting-state fMRI in the lateralization of language function in healthy subjects to permit its further testing in patients who are unable to perform task-based fMRI. Eighteen healthy right-handed volunteers were prospectively evaluated with resting-state fMRI and task-based fMRI to assess language networks. The laterality indices of Broca and Wernicke areas were calculated by using task-based fMRI via a voxel-value approach. We adopted seed-based resting-state fMRI connectivity analysis together with parameters such as amplitude of low-frequency fluctuation and fractional amplitude of low-frequency fluctuation (fALFF). Resting-state fMRI connectivity maps for language networks were obtained from Broca and Wernicke areas in both hemispheres. We performed correlation analysis between the laterality index and the z scores of functional connectivity, amplitude of low-frequency fluctuation, and fALFF. Pearson correlation analysis between signals obtained from the z score of fALFF and the laterality index yielded a correlation coefficient of 0.849 ( P laterality index yielded an R 2 value of 0.721, indicating that 72.1% of the variance in the laterality index of task-based fMRI could be predicted from the fALFF of resting-state fMRI. The present study demonstrates that fALFF can be used as an alternative to task-based fMRI for assessing language laterality. There was a strong positive correlation between the fALFF of the Broca area of resting-state fMRI with the laterality index of task-based fMRI. Furthermore, we demonstrated the efficacy of fALFF for predicting the laterality of task-based fMRI. © 2017 by American Journal of Neuroradiology.

  6. Mixed-effects and fMRI studies

    DEFF Research Database (Denmark)

    Friston, K.J; Stephan, K.E; Ellegaard Lund, Torben

    2005-01-01

    This note concerns mixed-effect (MFX) analyses in multisession functional magnetic resonance imaging (fMRI) studies. It clarifies the relationship between mixed-effect analyses and the two-stage 'summary statistics' procedure (Holmes, A.P., Friston, K.J., 1998. Generalisability, random effects...

  7. A new paradigm for individual subject language mapping: Movie-watching fMRI

    Science.gov (United States)

    Tie, Yanmei; Rigolo, Laura; Ovalioglu, Aysegul Ozdemir; Olubiyi, Olutayo; Doolin, Kelly L.; Mukundan, Srinivasan; Golby, Alexandra J.

    2015-01-01

    Background Functional MRI (fMRI) based on language tasks has been used in pre-surgical language mapping in patients with lesions in or near putative language areas. However, if the patients have difficulty performing the tasks due to neurological deficits, it leads to unreliable or non-interpretable results. In this study, we investigate the feasibility of using a movie-watching fMRI for language mapping. Methods A 7-min movie clip with contrasting speech and non-speech segments was shown to 22 right-handed healthy subjects. Based on all subjects' language functional regions-of-interest, six language response areas were defined, within which a language response model (LRM) was derived by extracting the main temporal activation profile. Using a leave-one-out procedure, individuals' language areas were identified as the areas that expressed highly correlated temporal responses with the LRM derived from an independent group of subjects. Results Compared with an antonym generation task-based fMRI, the movie-watching fMRI generated language maps with more localized activations in the left frontal language area, larger activations in the left temporoparietal language area, and significant activations in their right-hemisphere homologues. Results of two brain tumor patients' movie-watching fMRI using the LRM derived from the healthy subjects indicated its ability to map putative language areas; while their task-based fMRI maps were less robust and noisier. Conclusions These results suggest that it is feasible to use this novel “task-free” paradigm as a complementary tool for fMRI language mapping when patients cannot perform the tasks. Its deployment in more neurosurgical patients and validation against gold-standard techniques need further investigation. PMID:25962953

  8. Clinical application of functional MRI

    International Nuclear Information System (INIS)

    Taniwaki, Takayuki

    2010-01-01

    Described is the present state of clinical application of fMRI in the preoperative assessment of brain tumors, and plasticity in and pathophysiology of central diseases. For the tumor resection, fMRI is useful for risk assessment of postoperative nerve dysfunction, for selection of the patient rather suitable for brain mapping at the invasive surgery than at the pre-operation and for guidance of the operation itself. Preoperative fMRI alone can neither distinguish the regions of the primary and secondary functions nor exhibit the relation between the tumor and white matter fibers but there are compensatory means for these drawbacks. Benefit of preoperative fMRI has not yet been based on the evidence on double blind trials. Combination of fMRI imaging and electroencephalography (EEG) finding has shown that, in generalized epilepsy, extensive and stimulated activation occurs in both frontal/occipital regions and in thalamus area, respectively, and that the concomitant lowered activities are conceivably the reflection of burst discharge in normal brain functions. Plasticity in the human brain has been demonstrated by fMRI in cerebral vascular diseases, multiple sclerosis and amyotrophic lateral sclerosis. Pathogenesis of Parkinson disease and depression has been better understood by fMRI investigations revealing regions with elevated and reduced activities. Studies of attention deficit hyperactivity disorder have shown similar change of activities with functional reductions of the right dorsolateral frontal anterior area and of dorsal frontal cingulate gyrus, together with stimulated wider regions to given tasks. As above, fMRI has greatly contributed to our understanding of diseases of central nervous system and is to be expected to expand wider in this field. (T.T.)

  9. Close relationship between fMRI signals and transient heart rate changes accompanying K-complex. Simultaneous EEG/fMRI study

    International Nuclear Information System (INIS)

    Kan, Shigeyuki; Koike, Takahiko; Miyauchi, Satoru; Misaki, Masaya

    2009-01-01

    Combining functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) allows the investigation of spontaneous activities in the human brain. Recently, by using this technique, increases in fMRI signal accompanying transient EEG activities such as sleep spindles and slow waves were reported. Although these fMRI signal increases appear to arise as a result of the neural activities being reflected in the EEG, when the influence of physiological activities upon fMRI signals are taken into consideration, it is highly controversial that fMRI signal increases accompanying transient EEG activities reflect actual neural activities. In the present study, we conducted simultaneous fMRI and polysomnograph recording of 18 normal adults, to study the effect of transient heart rate changes after a K-complex on fMRI signals. Significant fMRI signal increase was observed in the cerebellum, the ventral thalamus, the dorsal part of the brainstem, the periventricular white matter and the ventricle (quadrigeminal cistern). On the other hand, significant fMRI signal decrease was observed only in the right insula. Moreover, intensities of fMRI signal increase that was accompanied by a K-complex correlated positively with the magnitude of heart rate changes after a K-complex. Previous studies have reported that K-complex is closely related with sympathetic nervous activity and that the attributes of perfusion regulation in the brain differ during wakefulness and sleep. By taking these findings into consideration, our present results indicate that a close relationship exists between a K-complex and the changes in cardio- and neurovascular regulations that are mediated by the autonomic nervous system during sleep; further, these results indicate that transient heart rate changes after a K-complex can affect the fMRI signal generated in certain brain regions. (author)

  10. Aggression-related brain function assessed with the Point Subtraction Aggression Paradigm in fMRI

    DEFF Research Database (Denmark)

    Skibsted, Anine P; Cunha-Bang, Sofi da; Carré, Justin M

    2017-01-01

    The Point Subtraction Aggression Paradigm (PSAP) measures aggressive behavior in response to provocations. The aim of the study was to implement the PSAP in a functional neuroimaging environment (fMRI) and evaluate aggression-related brain reactivity including response to provocations and associa......The Point Subtraction Aggression Paradigm (PSAP) measures aggressive behavior in response to provocations. The aim of the study was to implement the PSAP in a functional neuroimaging environment (fMRI) and evaluate aggression-related brain reactivity including response to provocations...... and associations with aggression within the paradigm. Twenty healthy participants completed two 12-min PSAP sessions within the scanner. We evaluated brain responses to aggressive behavior (removing points from an opponent), provocations (point subtractions by the opponent), and winning points. Our results showed...... with the involvement of these brain regions in emotional and impulsive behavior. Striatal reactivity may suggest an involvement of reward during winning and stealing points....

  11. Language mapping using high gamma electrocorticography, fMRI, and TMS versus electrocortical stimulation.

    Science.gov (United States)

    Babajani-Feremi, Abbas; Narayana, Shalini; Rezaie, Roozbeh; Choudhri, Asim F; Fulton, Stephen P; Boop, Frederick A; Wheless, James W; Papanicolaou, Andrew C

    2016-03-01

    The aim of the present study was to compare localization of the language cortex using cortical stimulation mapping (CSM), high gamma electrocorticography (hgECoG), functional magnetic resonance imaging (fMRI), and transcranial magnetic stimulation (TMS). Language mapping using CSM, hgECoG, fMRI, and TMS were compared in nine patients with epilepsy. Considering CSM as reference, we compared language mapping approaches based on hgECoG, fMRI, and TMS using their sensitivity, specificity, and the results of receiver operating characteristic (ROC) analyses. Our results show that areas involved in language processing can be identified by hgECoG, fMRI, and TMS. The average sensitivity/specificity of hgECoG, fMRI, and TMS across all patients was 100%/85%, 50%/80%, and 67%/66%, respectively. The average area under the ROC curve of hgECoG, fMRI, and TMS across CSM-positive patients was 0.98, 0.76, and 0.68, respectively. There is considerable concordance between CSM, hgECoG, fMRI, and TMS language mapping. Our results reveal that hgECoG, fMRI, and TMS are valuable tools for presurgical language mapping. Language mapping on the basis of hgECoG, fMRI, and TMS can provide important additional information, therefore, these methods can be used in conjunction with CSM or as an alternative, when the latter is deemed impractical. Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

  12. Cortical control of gait in healthy humans: an fMRI study

    International Nuclear Information System (INIS)

    ChiHong, Wang; YauYau, Wai; BoCheng, Kuo; Yei-Yu, Yeh; JiunJie Wang

    2008-01-01

    This study examined the cortical control of gait in healthy humans using functional magnetic resonance imaging (fMRI). Two block-designed fMRI sessions were conducted during motor imagery of a locomotor-related task. Subjects watched a video clip that showed an actor standing and walking in an egocentric perspective. In a control session, additional fMRI images were collected when participants observed a video clip of the clutch movement of a right hand. In keeping with previous studies using SPECT and NIRS, we detected activation in many motor-related areas including supplementary motor area, bilateral precentral gyrus, left dorsal premotor cortex, and cingulate motor area. Smaller additional activations were observed in the bilateral precuneus, left thalamus, and part of right putamen. Based on these findings, we propose a novel paradigm to study the cortical control of gait in healthy humans using fMRI. Specifically, the task used in this study - involving both mirror neurons and mental imagery - provides a new feasible model to be used in functional neuroimaging studies in this area of research. (author)

  13. Functional network centrality in obesity: A resting-state and task fMRI study.

    Science.gov (United States)

    García-García, Isabel; Jurado, María Ángeles; Garolera, Maite; Marqués-Iturria, Idoia; Horstmann, Annette; Segura, Bàrbara; Pueyo, Roser; Sender-Palacios, María José; Vernet-Vernet, Maria; Villringer, Arno; Junqué, Carme; Margulies, Daniel S; Neumann, Jane

    2015-09-30

    Obesity is associated with structural and functional alterations in brain areas that are often functionally distinct and anatomically distant. This suggests that obesity is associated with differences in functional connectivity of regions distributed across the brain. However, studies addressing whole brain functional connectivity in obesity remain scarce. Here, we compared voxel-wise degree centrality and eigenvector centrality between participants with obesity (n=20) and normal-weight controls (n=21). We analyzed resting state and task-related fMRI data acquired from the same individuals. Relative to normal-weight controls, participants with obesity exhibited reduced degree centrality in the right middle frontal gyrus in the resting-state condition. During the task fMRI condition, obese participants exhibited less degree centrality in the left middle frontal gyrus and the lateral occipital cortex along with reduced eigenvector centrality in the lateral occipital cortex and occipital pole. Our results highlight the central role of the middle frontal gyrus in the pathophysiology of obesity, a structure involved in several brain circuits signaling attention, executive functions and motor functions. Additionally, our analysis suggests the existence of task-dependent reduced centrality in occipital areas; regions with a role in perceptual processes and that are profoundly modulated by attention. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  14. Bayesian switching factor analysis for estimating time-varying functional connectivity in fMRI.

    Science.gov (United States)

    Taghia, Jalil; Ryali, Srikanth; Chen, Tianwen; Supekar, Kaustubh; Cai, Weidong; Menon, Vinod

    2017-07-15

    There is growing interest in understanding the dynamical properties of functional interactions between distributed brain regions. However, robust estimation of temporal dynamics from functional magnetic resonance imaging (fMRI) data remains challenging due to limitations in extant multivariate methods for modeling time-varying functional interactions between multiple brain areas. Here, we develop a Bayesian generative model for fMRI time-series within the framework of hidden Markov models (HMMs). The model is a dynamic variant of the static factor analysis model (Ghahramani and Beal, 2000). We refer to this model as Bayesian switching factor analysis (BSFA) as it integrates factor analysis into a generative HMM in a unified Bayesian framework. In BSFA, brain dynamic functional networks are represented by latent states which are learnt from the data. Crucially, BSFA is a generative model which estimates the temporal evolution of brain states and transition probabilities between states as a function of time. An attractive feature of BSFA is the automatic determination of the number of latent states via Bayesian model selection arising from penalization of excessively complex models. Key features of BSFA are validated using extensive simulations on carefully designed synthetic data. We further validate BSFA using fingerprint analysis of multisession resting-state fMRI data from the Human Connectome Project (HCP). Our results show that modeling temporal dependencies in the generative model of BSFA results in improved fingerprinting of individual participants. Finally, we apply BSFA to elucidate the dynamic functional organization of the salience, central-executive, and default mode networks-three core neurocognitive systems with central role in cognitive and affective information processing (Menon, 2011). Across two HCP sessions, we demonstrate a high level of dynamic interactions between these networks and determine that the salience network has the highest temporal

  15. The effect of ageing on fMRI: Correction for the confounding effects of vascular reactivity evaluated by joint fMRI and MEG in 335 adults

    Science.gov (United States)

    Henson, Richard N. A.; Tyler, Lorraine K.; Davis, Simon W.; Shafto, Meredith A.; Taylor, Jason R.; Williams, Nitin; Cam‐CAN; Rowe, James B.

    2015-01-01

    Abstract In functional magnetic resonance imaging (fMRI) research one is typically interested in neural activity. However, the blood‐oxygenation level‐dependent (BOLD) signal is a composite of both neural and vascular activity. As factors such as age or medication may alter vascular function, it is essential to account for changes in neurovascular coupling when investigating neurocognitive functioning with fMRI. The resting‐state fluctuation amplitude (RSFA) in the fMRI signal (rsfMRI) has been proposed as an index of vascular reactivity. The RSFA compares favourably with other techniques such as breath‐hold and hypercapnia, but the latter are more difficult to perform in some populations, such as older adults. The RSFA is therefore a candidate for use in adjusting for age‐related changes in vascular reactivity in fMRI studies. The use of RSFA is predicated on its sensitivity to vascular rather than neural factors; however, the extent to which each of these factors contributes to RSFA remains to be characterized. The present work addressed these issues by comparing RSFA (i.e., rsfMRI variability) to proxy measures of (i) cardiovascular function in terms of heart rate (HR) and heart rate variability (HRV) and (ii) neural activity in terms of resting state magnetoencephalography (rsMEG). We derived summary scores of RSFA, a sensorimotor task BOLD activation, cardiovascular function and rsMEG variability for 335 healthy older adults in the population‐based Cambridge Centre for Ageing and Neuroscience cohort (Cam‐CAN; www.cam-can.com). Mediation analysis revealed that the effects of ageing on RSFA were significantly mediated by vascular factors, but importantly not by the variability in neuronal activity. Furthermore, the converse effects of ageing on the rsMEG variability were not mediated by vascular factors. We then examined the effect of RSFA scaling of task‐based BOLD in the sensorimotor task. The scaling analysis revealed that much of the effects

  16. Large-scale DCMs for resting-state fMRI

    Directory of Open Access Journals (Sweden)

    Adeel Razi

    2017-01-01

    Full Text Available This paper considers the identification of large directed graphs for resting-state brain networks based on biophysical models of distributed neuronal activity, that is, effective connectivity. This identification can be contrasted with functional connectivity methods based on symmetric correlations that are ubiquitous in resting-state functional MRI (fMRI. We use spectral dynamic causal modeling (DCM to invert large graphs comprising dozens of nodes or regions. The ensuing graphs are directed and weighted, hence providing a neurobiologically plausible characterization of connectivity in terms of excitatory and inhibitory coupling. Furthermore, we show that the use of Bayesian model reduction to discover the most likely sparse graph (or model from a parent (e.g., fully connected graph eschews the arbitrary thresholding often applied to large symmetric (functional connectivity graphs. Using empirical fMRI data, we show that spectral DCM furnishes connectivity estimates on large graphs that correlate strongly with the estimates provided by stochastic DCM. Furthermore, we increase the efficiency of model inversion using functional connectivity modes to place prior constraints on effective connectivity. In other words, we use a small number of modes to finesse the potentially redundant parameterization of large DCMs. We show that spectral DCM—with functional connectivity priors—is ideally suited for directed graph theoretic analyses of resting-state fMRI. We envision that directed graphs will prove useful in understanding the psychopathology and pathophysiology of neurodegenerative and neurodevelopmental disorders. We will demonstrate the utility of large directed graphs in clinical populations in subsequent reports, using the procedures described in this paper.

  17. Learning Computational Models of Video Memorability from fMRI Brain Imaging.

    Science.gov (United States)

    Han, Junwei; Chen, Changyuan; Shao, Ling; Hu, Xintao; Han, Jungong; Liu, Tianming

    2015-08-01

    Generally, various visual media are unequally memorable by the human brain. This paper looks into a new direction of modeling the memorability of video clips and automatically predicting how memorable they are by learning from brain functional magnetic resonance imaging (fMRI). We propose a novel computational framework by integrating the power of low-level audiovisual features and brain activity decoding via fMRI. Initially, a user study experiment is performed to create a ground truth database for measuring video memorability and a set of effective low-level audiovisual features is examined in this database. Then, human subjects' brain fMRI data are obtained when they are watching the video clips. The fMRI-derived features that convey the brain activity of memorizing videos are extracted using a universal brain reference system. Finally, due to the fact that fMRI scanning is expensive and time-consuming, a computational model is learned on our benchmark dataset with the objective of maximizing the correlation between the low-level audiovisual features and the fMRI-derived features using joint subspace learning. The learned model can then automatically predict the memorability of videos without fMRI scans. Evaluations on publically available image and video databases demonstrate the effectiveness of the proposed framework.

  18. Imaging gait analysis: An fMRI dual task study.

    Science.gov (United States)

    Bürki, Céline N; Bridenbaugh, Stephanie A; Reinhardt, Julia; Stippich, Christoph; Kressig, Reto W; Blatow, Maria

    2017-08-01

    In geriatric clinical diagnostics, gait analysis with cognitive-motor dual tasking is used to predict fall risk and cognitive decline. To date, the neural correlates of cognitive-motor dual tasking processes are not fully understood. To investigate these underlying neural mechanisms, we designed an fMRI paradigm to reproduce the gait analysis. We tested the fMRI paradigm's feasibility in a substudy with fifteen young adults and assessed 31 healthy older adults in the main study. First, gait speed and variability were quantified using the GAITRite © electronic walkway. Then, participants lying in the MRI-scanner were stepping on pedals of an MRI-compatible stepping device used to imitate gait during functional imaging. In each session, participants performed cognitive and motor single tasks as well as cognitive-motor dual tasks. Behavioral results showed that the parameters of both gait analyses, GAITRite © and fMRI, were significantly positively correlated. FMRI results revealed significantly reduced brain activation during dual task compared to single task conditions. Functional ROI analysis showed that activation in the superior parietal lobe (SPL) decreased less from single to dual task condition than activation in primary motor cortex and in supplementary motor areas. Moreover, SPL activation was increased during dual tasks in subjects exhibiting lower stepping speed and lower executive control. We were able to simulate walking during functional imaging with valid results that reproduce those from the GAITRite © gait analysis. On the neural level, SPL seems to play a crucial role in cognitive-motor dual tasking and to be linked to divided attention processes, particularly when motor activity is involved.

  19. Physiological and technical limitations of functional magnetic resonance imaging (fMRI) - consequences for clinical use

    International Nuclear Information System (INIS)

    Wuestenberg, T.; Jordan, K.; Giesel, F.L.; Villringer, A.

    2003-01-01

    Functional magnetic resonance imaging (fMRI) is the most common noninvasive technique in functional neuroanatomy. The capabilities and limitations of the method will be discussed based on a short review of the current knowledge about the neurovascular relationship. The focus of this article is on current methodical and technical problems regarding fMRI-based detection and localization of neuronal activity. Main error sources and their influence on the reliability and validity of fMRI-methods are presented. Appropriate solution strategies will be proposed and evaluated. Finally, the clinical relevance of MR-based diagnostic methods are discussed. (orig.) [de

  20. Modeling fMRI signals can provide insights into neural processing in the cerebral cortex.

    Science.gov (United States)

    Vanni, Simo; Sharifian, Fariba; Heikkinen, Hanna; Vigário, Ricardo

    2015-08-01

    Every stimulus or task activates multiple areas in the mammalian cortex. These distributed activations can be measured with functional magnetic resonance imaging (fMRI), which has the best spatial resolution among the noninvasive brain imaging methods. Unfortunately, the relationship between the fMRI activations and distributed cortical processing has remained unclear, both because the coupling between neural and fMRI activations has remained poorly understood and because fMRI voxels are too large to directly sense the local neural events. To get an idea of the local processing given the macroscopic data, we need models to simulate the neural activity and to provide output that can be compared with fMRI data. Such models can describe neural mechanisms as mathematical functions between input and output in a specific system, with little correspondence to physiological mechanisms. Alternatively, models can be biomimetic, including biological details with straightforward correspondence to experimental data. After careful balancing between complexity, computational efficiency, and realism, a biomimetic simulation should be able to provide insight into how biological structures or functions contribute to actual data processing as well as to promote theory-driven neuroscience experiments. This review analyzes the requirements for validating system-level computational models with fMRI. In particular, we study mesoscopic biomimetic models, which include a limited set of details from real-life networks and enable system-level simulations of neural mass action. In addition, we discuss how recent developments in neurophysiology and biophysics may significantly advance the modelling of fMRI signals. Copyright © 2015 the American Physiological Society.

  1. A 3 T event-related functional magnetic resonance imaging (fMRI) study of primary and secondary gustatory cortex localization using natural tastants

    International Nuclear Information System (INIS)

    Smits, Marion; Peeters, Ronald R.; Hecke, Paul van; Sunaert, Stefan

    2007-01-01

    It is known that taste is centrally represented in the insula, frontal and parietal operculum, as well as in the orbitofrontal cortex (secondary gustatory cortex). In functional MRI (fMRI) experiments activation in the insula has been confirmed, but activation in the orbitofrontal cortex is only infrequently found, especially at higher field strengths (3 T). Due to large susceptibility artefacts, the orbitofrontal cortex is a difficult region to examine with fMRI. Our aim was to localize taste in the human cortex at 3 T, specifically in the orbitofrontal cortex as well as in the primary gustatory cortex. Event-related fMRI was performed at 3 T in seven healthy volunteers. Taste stimuli consisted of lemon juice and chocolate. To visualize activation in the orbitofrontal cortex a dedicated 3D SENSE EPI fMRI sequence was used, in addition to a 2D SENSE EPI fMRI sequence for imaging the entire brain. Data were analyzed using a perception-based model. The dedicated 3D SENSE EPI sequence successfully reduced susceptibility artefacts in the orbitofrontal area. Significant taste-related activation was found in the orbitofrontal and insular cortices. fMRI of the orbitofrontal cortex is feasible at 3 T, using a dedicated sequence. Our results corroborate findings from previous studies. (orig.)

  2. A 3 T event-related functional magnetic resonance imaging (fMRI) study of primary and secondary gustatory cortex localization using natural tastants

    Energy Technology Data Exchange (ETDEWEB)

    Smits, Marion [Erasmus MC, University Medical Center Rotterdam, Department of Radiology, P.O. Box 2040, CA Rotterdam (Netherlands); K.U.Leuven, Department of Radiology, University Hospitals, Leuven (Belgium); Peeters, Ronald R.; Hecke, Paul van; Sunaert, Stefan [K.U.Leuven, Department of Radiology, University Hospitals, Leuven (Belgium)

    2007-01-15

    It is known that taste is centrally represented in the insula, frontal and parietal operculum, as well as in the orbitofrontal cortex (secondary gustatory cortex). In functional MRI (fMRI) experiments activation in the insula has been confirmed, but activation in the orbitofrontal cortex is only infrequently found, especially at higher field strengths (3 T). Due to large susceptibility artefacts, the orbitofrontal cortex is a difficult region to examine with fMRI. Our aim was to localize taste in the human cortex at 3 T, specifically in the orbitofrontal cortex as well as in the primary gustatory cortex. Event-related fMRI was performed at 3 T in seven healthy volunteers. Taste stimuli consisted of lemon juice and chocolate. To visualize activation in the orbitofrontal cortex a dedicated 3D SENSE EPI fMRI sequence was used, in addition to a 2D SENSE EPI fMRI sequence for imaging the entire brain. Data were analyzed using a perception-based model. The dedicated 3D SENSE EPI sequence successfully reduced susceptibility artefacts in the orbitofrontal area. Significant taste-related activation was found in the orbitofrontal and insular cortices. fMRI of the orbitofrontal cortex is feasible at 3 T, using a dedicated sequence. Our results corroborate findings from previous studies. (orig.)

  3. Diagnostic benefits of presurgical fMRI in patients with brain tumours in the primary sensorimotor cortex

    Energy Technology Data Exchange (ETDEWEB)

    Wengenroth, Martina; Blatow, M.; Guenther, J. [University of Heidelberg Medical School, Department of Neuroradiology, Heidelberg (Germany); Akbar, M. [University of Heidelberg Medical School, Department of Orthopaedics, Heidelberg (Germany); Tronnier, V.M. [University of Schleswig-Holstein, Department of Neurosurgery, Luebeck (Germany); Stippich, C. [University Hospital Basle, Department of Diagnostic and Interventional Neuroradiology, Basle (Switzerland)

    2011-07-15

    Reliable imaging of eloquent tumour-adjacent brain areas is necessary for planning function-preserving neurosurgery. This study evaluates the potential diagnostic benefits of presurgical functional magnetic resonance imaging (fMRI) in comparison to a detailed analysis of morphological MRI data. Standardised preoperative functional and structural neuroimaging was performed on 77 patients with rolandic mass lesions at 1.5 Tesla. The central region of both hemispheres was allocated using six morphological and three functional landmarks. fMRI enabled localisation of the motor hand area in 76/77 patients, which was significantly superior to analysis of structural MRI (confident localisation of motor hand area in 66/77 patients; p < 0.002). FMRI provided additional diagnostic information in 96% (tongue representation) and 97% (foot representation) of patients. FMRI-based presurgical risk assessment correlated in 88% with a positive postoperative clinical outcome. Routine presurgical FMRI allows for superior assessment of the spatial relationship between brain tumour and motor cortex compared with a very detailed analysis of structural 3D MRI, thus significantly facilitating the preoperative risk-benefit assessment and function-preserving surgery. The additional imaging time seems justified. FMRI has the potential to reduce postoperative morbidity and therefore hospitalisation time. (orig.)

  4. A Dictionary Learning Approach for Signal Sampling in Task-Based fMRI for Reduction of Big Data

    Science.gov (United States)

    Ge, Bao; Li, Xiang; Jiang, Xi; Sun, Yifei; Liu, Tianming

    2018-01-01

    The exponential growth of fMRI big data offers researchers an unprecedented opportunity to explore functional brain networks. However, this opportunity has not been fully explored yet due to the lack of effective and efficient tools for handling such fMRI big data. One major challenge is that computing capabilities still lag behind the growth of large-scale fMRI databases, e.g., it takes many days to perform dictionary learning and sparse coding of whole-brain fMRI data for an fMRI database of average size. Therefore, how to reduce the data size but without losing important information becomes a more and more pressing issue. To address this problem, we propose a signal sampling approach for significant fMRI data reduction before performing structurally-guided dictionary learning and sparse coding of whole brain's fMRI data. We compared the proposed structurally guided sampling method with no sampling, random sampling and uniform sampling schemes, and experiments on the Human Connectome Project (HCP) task fMRI data demonstrated that the proposed method can achieve more than 15 times speed-up without sacrificing the accuracy in identifying task-evoked functional brain networks. PMID:29706880

  5. A Dictionary Learning Approach for Signal Sampling in Task-Based fMRI for Reduction of Big Data.

    Science.gov (United States)

    Ge, Bao; Li, Xiang; Jiang, Xi; Sun, Yifei; Liu, Tianming

    2018-01-01

    The exponential growth of fMRI big data offers researchers an unprecedented opportunity to explore functional brain networks. However, this opportunity has not been fully explored yet due to the lack of effective and efficient tools for handling such fMRI big data. One major challenge is that computing capabilities still lag behind the growth of large-scale fMRI databases, e.g., it takes many days to perform dictionary learning and sparse coding of whole-brain fMRI data for an fMRI database of average size. Therefore, how to reduce the data size but without losing important information becomes a more and more pressing issue. To address this problem, we propose a signal sampling approach for significant fMRI data reduction before performing structurally-guided dictionary learning and sparse coding of whole brain's fMRI data. We compared the proposed structurally guided sampling method with no sampling, random sampling and uniform sampling schemes, and experiments on the Human Connectome Project (HCP) task fMRI data demonstrated that the proposed method can achieve more than 15 times speed-up without sacrificing the accuracy in identifying task-evoked functional brain networks.

  6. Automatic EEG-assisted retrospective motion correction for fMRI (aE-REMCOR).

    Science.gov (United States)

    Wong, Chung-Ki; Zotev, Vadim; Misaki, Masaya; Phillips, Raquel; Luo, Qingfei; Bodurka, Jerzy

    2016-04-01

    Head motions during functional magnetic resonance imaging (fMRI) impair fMRI data quality and introduce systematic artifacts that can affect interpretation of fMRI results. Electroencephalography (EEG) recordings performed simultaneously with fMRI provide high-temporal-resolution information about ongoing brain activity as well as head movements. Recently, an EEG-assisted retrospective motion correction (E-REMCOR) method was introduced. E-REMCOR utilizes EEG motion artifacts to correct the effects of head movements in simultaneously acquired fMRI data on a slice-by-slice basis. While E-REMCOR is an efficient motion correction approach, it involves an independent component analysis (ICA) of the EEG data and identification of motion-related ICs. Here we report an automated implementation of E-REMCOR, referred to as aE-REMCOR, which we developed to facilitate the application of E-REMCOR in large-scale EEG-fMRI studies. The aE-REMCOR algorithm, implemented in MATLAB, enables an automated preprocessing of the EEG data, an ICA decomposition, and, importantly, an automatic identification of motion-related ICs. aE-REMCOR has been used to perform retrospective motion correction for 305 fMRI datasets from 16 subjects, who participated in EEG-fMRI experiments conducted on a 3T MRI scanner. Performance of aE-REMCOR has been evaluated based on improvement in temporal signal-to-noise ratio (TSNR) of the fMRI data, as well as correction efficiency defined in terms of spike reduction in fMRI motion parameters. The results show that aE-REMCOR is capable of substantially reducing head motion artifacts in fMRI data. In particular, when there are significant rapid head movements during the scan, a large TSNR improvement and high correction efficiency can be achieved. Depending on a subject's motion, an average TSNR improvement over the brain upon the application of aE-REMCOR can be as high as 27%, with top ten percent of the TSNR improvement values exceeding 55%. The average

  7. FIACH: A biophysical model for automatic retrospective noise control in fMRI.

    Science.gov (United States)

    Tierney, Tim M; Weiss-Croft, Louise J; Centeno, Maria; Shamshiri, Elhum A; Perani, Suejen; Baldeweg, Torsten; Clark, Christopher A; Carmichael, David W

    2016-01-01

    Different noise sources in fMRI acquisition can lead to spurious false positives and reduced sensitivity. We have developed a biophysically-based model (named FIACH: Functional Image Artefact Correction Heuristic) which extends current retrospective noise control methods in fMRI. FIACH can be applied to both General Linear Model (GLM) and resting state functional connectivity MRI (rs-fcMRI) studies. FIACH is a two-step procedure involving the identification and correction of non-physiological large amplitude temporal signal changes and spatial regions of high temporal instability. We have demonstrated its efficacy in a sample of 42 healthy children while performing language tasks that include overt speech with known activations. We demonstrate large improvements in sensitivity when FIACH is compared with current methods of retrospective correction. FIACH reduces the confounding effects of noise and increases the study's power by explaining significant variance that is not contained within the commonly used motion parameters. The method is particularly useful in detecting activations in inferior temporal regions which have proven problematic for fMRI. We have shown greater reproducibility and robustness of fMRI responses using FIACH in the context of task induced motion. In a clinical setting this will translate to increasing the reliability and sensitivity of fMRI used for the identification of language lateralisation and eloquent cortex. FIACH can benefit studies of cognitive development in young children, patient populations and older adults. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

  8. Who gets afraid in the MRI-scanner? Neurogenetics of state-anxiety changes during an fMRI experiment.

    Science.gov (United States)

    Mutschler, Isabella; Wieckhorst, Birgit; Meyer, Andrea H; Schweizer, Tina; Klarhöfer, Markus; Wilhelm, Frank H; Seifritz, Erich; Ball, Tonio

    2014-11-07

    Experiments using functional magnetic resonance imaging (fMRI) play a fundamental role in affective neuroscience. When placed in an MR scanner, some volunteers feel safe and relaxed in this situation, while others experience uneasiness and fear. Little is known about the basis and consequences of such inter-individually different responses to the general experimental fMRI setting. In this study emotional stimuli were presented during fMRI and subjects' state-anxiety was assessed at the onset and end of the experiment while they were within the scanner. We show that Val/Val but neither Met/Met nor Val/Met carriers of the catechol-O-methyltransferase (COMT) Val(158)Met polymorphism-a prime candidate for anxiety vulnerability-became significantly more anxious during the fMRI experiment (N=97 females: 24 Val/Val, 51 Val/Met, and 22 Met/Met). Met carriers demonstrated brain responses with increased stability over time in the right parietal cortex and significantly better cognitive performances likely mediated by lower levels of anxiety. Val/Val, Val/Met and Met/Met did not significantly differ in state-anxiety at the beginning of the experiment. The exposure of a control group (N=56 females) to the same experiment outside the scanner did not cause a significant increase in state-anxiety, suggesting that the increase we observe in the fMRI experiment may be specific to the fMRI setting. Our findings reveal that genetics may play an important role in shaping inter-individual different emotional, cognitive and neuronal responses during fMRI experiments. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  9. The Functional Segregation and Integration Model: Mixture Model Representations of Consistent and Variable Group-Level Connectivity in fMRI

    DEFF Research Database (Denmark)

    Churchill, Nathan William; Madsen, Kristoffer Hougaard; Mørup, Morten

    2016-01-01

    flexibility: they only estimate segregated structure and do not model interregional functional connectivity, nor do they account for network variability across voxels or between subjects. To address these issues, this letter develops the functional segregation and integration model (FSIM). This extension......The brain consists of specialized cortical regions that exchange information between each other, reflecting a combination of segregated (local) and integrated (distributed) processes that define brain function. Functional magnetic resonance imaging (fMRI) is widely used to characterize...... brain regions where network expression predicts subject age in the experimental data. Thus, the FSIM is effective at summarizing functional connectivity structure in group-level fMRI, with applications in modeling the relationships between network variability and behavioral/demographic variables....

  10. Temporal and Spatial Independent Component Analysis for fMRI Data Sets Embedded in the AnalyzeFMRI R Package

    Directory of Open Access Journals (Sweden)

    Pierre Lafaye de Micheaux

    2011-10-01

    Full Text Available For statistical analysis of functional magnetic resonance imaging (fMRI data sets, we propose a data-driven approach based on independent component analysis (ICA implemented in a new version of the AnalyzeFMRI R package. For fMRI data sets, spatial dimension being much greater than temporal dimension, spatial ICA is the computationally tractable approach generally proposed. However, for some neuroscientific applications, temporal independence of source signals can be assumed and temporal ICA becomes then an attractive exploratory technique. In this work, we use a classical linear algebra result ensuring the tractability of temporal ICA. We report several experiments on synthetic data and real MRI data sets that demonstrate the potential interest of our R package.

  11. Using real-time fMRI brain-computer interfacing to treat eating disorders.

    Science.gov (United States)

    Sokunbi, Moses O

    2018-05-15

    Real-time functional magnetic resonance imaging based brain-computer interfacing (fMRI neurofeedback) has shown encouraging outcomes in the treatment of psychiatric and behavioural disorders. However, its use in the treatment of eating disorders is very limited. Here, we give a brief overview of how to design and implement fMRI neurofeedback intervention for the treatment of eating disorders, considering the basic and essential components. We also attempt to develop potential adaptations of fMRI neurofeedback intervention for the treatment of anorexia nervosa, bulimia nervosa and binge eating disorder. Copyright © 2018 Elsevier B.V. All rights reserved.

  12. Functional Subdivision of Group-ICA Results of fMRI Data Collected during Cinema Viewing

    Science.gov (United States)

    Pamilo, Siina; Malinen, Sanna; Hlushchuk, Yevhen; Seppä, Mika; Tikka, Pia; Hari, Riitta

    2012-01-01

    Independent component analysis (ICA) can unravel functional brain networks from functional magnetic resonance imaging (fMRI) data. The number of the estimated components affects both the spatial pattern of the identified networks and their time-course estimates. Here group-ICA was applied at four dimensionalities (10, 20, 40, and 58 components) to fMRI data collected from 15 subjects who viewed a 15-min silent film (“At land” by Maya Deren). We focused on the dorsal attention network, the default-mode network, and the sensorimotor network. The lowest dimensionalities demonstrated most prominent activity within the dorsal attention network, combined with the visual areas, and in the default-mode network; the sensorimotor network only appeared with ICA comprising at least 20 components. The results suggest that even very low-dimensional ICA can unravel the most prominent functionally-connected brain networks. However, increasing the number of components gives a more detailed picture and functionally feasible subdivision of the major networks. These results improve our understanding of the hierarchical subdivision of brain networks during viewing of a movie that provides continuous stimulation embedded in an attention-directing narrative. PMID:22860044

  13. Functional subdivision of group-ICA results of fMRI data collected during cinema viewing.

    Directory of Open Access Journals (Sweden)

    Siina Pamilo

    Full Text Available Independent component analysis (ICA can unravel functional brain networks from functional magnetic resonance imaging (fMRI data. The number of the estimated components affects both the spatial pattern of the identified networks and their time-course estimates. Here group-ICA was applied at four dimensionalities (10, 20, 40, and 58 components to fMRI data collected from 15 subjects who viewed a 15-min silent film ("At land" by Maya Deren. We focused on the dorsal attention network, the default-mode network, and the sensorimotor network. The lowest dimensionalities demonstrated most prominent activity within the dorsal attention network, combined with the visual areas, and in the default-mode network; the sensorimotor network only appeared with ICA comprising at least 20 components. The results suggest that even very low-dimensional ICA can unravel the most prominent functionally-connected brain networks. However, increasing the number of components gives a more detailed picture and functionally feasible subdivision of the major networks. These results improve our understanding of the hierarchical subdivision of brain networks during viewing of a movie that provides continuous stimulation embedded in an attention-directing narrative.

  14. Functional subdivision of group-ICA results of fMRI data collected during cinema viewing.

    Science.gov (United States)

    Pamilo, Siina; Malinen, Sanna; Hlushchuk, Yevhen; Seppä, Mika; Tikka, Pia; Hari, Riitta

    2012-01-01

    Independent component analysis (ICA) can unravel functional brain networks from functional magnetic resonance imaging (fMRI) data. The number of the estimated components affects both the spatial pattern of the identified networks and their time-course estimates. Here group-ICA was applied at four dimensionalities (10, 20, 40, and 58 components) to fMRI data collected from 15 subjects who viewed a 15-min silent film ("At land" by Maya Deren). We focused on the dorsal attention network, the default-mode network, and the sensorimotor network. The lowest dimensionalities demonstrated most prominent activity within the dorsal attention network, combined with the visual areas, and in the default-mode network; the sensorimotor network only appeared with ICA comprising at least 20 components. The results suggest that even very low-dimensional ICA can unravel the most prominent functionally-connected brain networks. However, increasing the number of components gives a more detailed picture and functionally feasible subdivision of the major networks. These results improve our understanding of the hierarchical subdivision of brain networks during viewing of a movie that provides continuous stimulation embedded in an attention-directing narrative.

  15. Bold-Independent Computational Entropy Assesses Functional Donut-Like Structures in Brain fMRI Images.

    Science.gov (United States)

    Peters, James F; Ramanna, Sheela; Tozzi, Arturo; İnan, Ebubekir

    2017-01-01

    We introduce a novel method for the measurement of information level in fMRI (functional Magnetic Resonance Imaging) neural data sets, based on image subdivision in small polygons equipped with different entropic content. We show how this method, called maximal nucleus clustering (MNC), is a novel, fast and inexpensive image-analysis technique, independent from the standard blood-oxygen-level dependent signals. MNC facilitates the objective detection of hidden temporal patterns of entropy/information in zones of fMRI images generally not taken into account by the subjective standpoint of the observer. This approach befits the geometric character of fMRIs. The main purpose of this study is to provide a computable framework for fMRI that not only facilitates analyses, but also provides an easily decipherable visualization of structures. This framework commands attention because it is easily implemented using conventional software systems. In order to evaluate the potential applications of MNC, we looked for the presence of a fourth dimension's distinctive hallmarks in a temporal sequence of 2D images taken during spontaneous brain activity. Indeed, recent findings suggest that several brain activities, such as mind-wandering and memory retrieval, might take place in the functional space of a four dimensional hypersphere, which is a double donut-like structure undetectable in the usual three dimensions. We found that the Rényi entropy is higher in MNC areas than in the surrounding ones, and that these temporal patterns closely resemble the trajectories predicted by the possible presence of a hypersphere in the brain.

  16. Clinical functional MRI. Persurgical functional neuroimaging. 2. ed.

    International Nuclear Information System (INIS)

    Stippich, Christoph

    2015-01-01

    The second, revised edition of this successful textbook provides an up-to-date description of the use of preoperative fMRI in patients with brain tumors and epilepsies. State of the art fMRI procedures are presented, with detailed consideration of practical aspects, imaging and data processing, normal and pathological findings, and diagnostic possibilities and limitations. Relevant information on brain physiology, functional neuroanatomy, imaging technique, and methodology is provided by recognized experts in these fields. Compared with the first edition, chapters have been updated to reflect the latest developments and in particular the current use of diffusion tensor imaging (DTI) and resting-state fMRI. Entirely new chapters are included on resting-state presurgical fMRI and the role of DTI and tractography in brain tumor surgery. Further chapters address multimodality functional neuroimaging, brain plasticity, and pitfalls, tips, and tricks.

  17. Clinical functional MRI. Persurgical functional neuroimaging. 2. ed.

    Energy Technology Data Exchange (ETDEWEB)

    Stippich, Christoph (ed.) [Univ. Hospitals Basel (Switzerland). Division of Diagnostic and Inventional Neuroradiology

    2015-06-01

    The second, revised edition of this successful textbook provides an up-to-date description of the use of preoperative fMRI in patients with brain tumors and epilepsies. State of the art fMRI procedures are presented, with detailed consideration of practical aspects, imaging and data processing, normal and pathological findings, and diagnostic possibilities and limitations. Relevant information on brain physiology, functional neuroanatomy, imaging technique, and methodology is provided by recognized experts in these fields. Compared with the first edition, chapters have been updated to reflect the latest developments and in particular the current use of diffusion tensor imaging (DTI) and resting-state fMRI. Entirely new chapters are included on resting-state presurgical fMRI and the role of DTI and tractography in brain tumor surgery. Further chapters address multimodality functional neuroimaging, brain plasticity, and pitfalls, tips, and tricks.

  18. Practical Introduction to Cerebral Functional Magnetic Resonance (fMRI)

    International Nuclear Information System (INIS)

    Delgado, Jorge Andres; Rascovsky Simon; Sanz, Alexander; Castrillon, Juan Gabriel

    2008-01-01

    Magnetic resonance (MR ) imaging holds a privileged position within neuroimaging techniques owing to its high anatomic detail and its capacity to study many physiological processes. The appearance of functional magnetic resonance (fMR I) brings more relevance to MR , turning it into a powerful tool with the ability to group, in a single exam, high-resolution anatomy and cerebral function. In this article we describe the principles and some advantages of fMRI compared to other neuro functional imaging modalities. In addition, we present the site wide and analysis requisites for the performance and post-processing of the most common neuro functional experiments in clinical practice. We also include neuro functional images obtained at Instituto de Alta Tecnologia Medica of Antioquia (IATM ) on a healthy volunteer group and two pathological cases. Lastly, we mention some of the practical indications of this technique which is still in an intense development, research and validation phase.

  19. The effect of hippocampal function, volume and connectivity on posterior cingulate cortex functioning during episodic memory fMRI in mild cognitive impairment

    International Nuclear Information System (INIS)

    Papma, Janne M.; Koudstaal, Peter J.; Swieten, John C. van; Smits, Marion; Lugt, Aad van der; Groot, Marius de; Vrooman, Henri A.; Mattace Raso, Francesco U.; Niessen, Wiro J.; Veen, Frederik M. van der; Prins, Niels D.

    2017-01-01

    Diminished function of the posterior cingulate cortex (PCC) is a typical finding in early Alzheimer's disease (AD). It is hypothesized that in early stage AD, PCC functioning relates to or reflects hippocampal dysfunction or atrophy. The aim of this study was to examine the relationship between hippocampus function, volume and structural connectivity, and PCC activation during an episodic memory task-related fMRI study in mild cognitive impairment (MCI). MCI patients (n = 27) underwent episodic memory task-related fMRI, 3D-T1w MRI, 2D T2-FLAIR MRI and diffusion tensor imaging. Stepwise linear regression analysis was performed to examine the relationship between PCC activation and hippocampal activation, hippocampal volume and diffusion measures within the cingulum along the hippocampus. We found a significant relationship between PCC and hippocampus activation during successful episodic memory encoding and correct recognition in MCI patients. We found no relationship between the PCC and structural hippocampal predictors. Our results indicate a relationship between PCC and hippocampus activation during episodic memory engagement in MCI. This may suggest that during episodic memory, functional network deterioration is the most important predictor of PCC functioning in MCI. (orig.)

  20. The effect of hippocampal function, volume and connectivity on posterior cingulate cortex functioning during episodic memory fMRI in mild cognitive impairment

    Energy Technology Data Exchange (ETDEWEB)

    Papma, Janne M.; Koudstaal, Peter J.; Swieten, John C. van [Erasmus MC - University Medical Center Rotterdam, Department of Neurology, Rotterdam (Netherlands); Smits, Marion; Lugt, Aad van der [Erasmus MC - University Medical Center Rotterdam, Department of Radiology, Rotterdam (Netherlands); Groot, Marius de; Vrooman, Henri A. [Erasmus MC - University Medical Center Rotterdam, Department of Radiology, Rotterdam (Netherlands); Erasmus MC - University Medical Center Rotterdam, Department of Medical Informatics, Rotterdam (Netherlands); Mattace Raso, Francesco U. [Erasmus MC - University Medical Center Rotterdam, Department of Geriatrics, Rotterdam (Netherlands); Niessen, Wiro J. [Erasmus MC - University Medical Center Rotterdam, Department of Radiology, Rotterdam (Netherlands); Erasmus MC - University Medical Center Rotterdam, Department of Medical Informatics, Rotterdam (Netherlands); Delft University of Technology, Faculty of Applied Sciences, Delft (Netherlands); Veen, Frederik M. van der [Erasmus University Rotterdam, Institute of Psychology, Rotterdam (Netherlands); Prins, Niels D. [VU University Medical Center, Alzheimer Center, Department of Neurology, Amsterdam (Netherlands)

    2017-09-15

    Diminished function of the posterior cingulate cortex (PCC) is a typical finding in early Alzheimer's disease (AD). It is hypothesized that in early stage AD, PCC functioning relates to or reflects hippocampal dysfunction or atrophy. The aim of this study was to examine the relationship between hippocampus function, volume and structural connectivity, and PCC activation during an episodic memory task-related fMRI study in mild cognitive impairment (MCI). MCI patients (n = 27) underwent episodic memory task-related fMRI, 3D-T1w MRI, 2D T2-FLAIR MRI and diffusion tensor imaging. Stepwise linear regression analysis was performed to examine the relationship between PCC activation and hippocampal activation, hippocampal volume and diffusion measures within the cingulum along the hippocampus. We found a significant relationship between PCC and hippocampus activation during successful episodic memory encoding and correct recognition in MCI patients. We found no relationship between the PCC and structural hippocampal predictors. Our results indicate a relationship between PCC and hippocampus activation during episodic memory engagement in MCI. This may suggest that during episodic memory, functional network deterioration is the most important predictor of PCC functioning in MCI. (orig.)

  1. Current stage of fMRI applications in newborns and children during the first year of life

    International Nuclear Information System (INIS)

    Boecker, H.; Scheef, L.; Jankowski, J.; Zimmermann, N.; Born, M.; Heep, A.

    2008-01-01

    Currently, a paradigm shift towards expanded early use of cranial MRI in newborns at risk and infants in the first year of life can be observed in neonatology. Beyond clinical MRI applications, there is progressive use of functional MRI (fMRI) in this age group. On the one hand, fMRI allows monitoring of functional developmental processes depending on maturational stage; on the other hand, this technique may provide the basis for early detection of pathophysiological processes as a prerequisite for functionally guided therapeutic interventions. This article provides a comprehensive review of current fMRI applications in neonates and infants during the first year of life and focuses on the associated methodological issues (e.g. signal physiology, sedation, safety aspects). (orig.)

  2. Markov models for fMRI correlation structure: Is brain functional connectivity small world, or decomposable into networks?

    Science.gov (United States)

    Varoquaux, G; Gramfort, A; Poline, J B; Thirion, B

    2012-01-01

    Correlations in the signal observed via functional Magnetic Resonance Imaging (fMRI), are expected to reveal the interactions in the underlying neural populations through hemodynamic response. In particular, they highlight distributed set of mutually correlated regions that correspond to brain networks related to different cognitive functions. Yet graph-theoretical studies of neural connections give a different picture: that of a highly integrated system with small-world properties: local clustering but with short pathways across the complete structure. We examine the conditional independence properties of the fMRI signal, i.e. its Markov structure, to find realistic assumptions on the connectivity structure that are required to explain the observed functional connectivity. In particular we seek a decomposition of the Markov structure into segregated functional networks using decomposable graphs: a set of strongly-connected and partially overlapping cliques. We introduce a new method to efficiently extract such cliques on a large, strongly-connected graph. We compare methods learning different graph structures from functional connectivity by testing the goodness of fit of the model they learn on new data. We find that summarizing the structure as strongly-connected networks can give a good description only for very large and overlapping networks. These results highlight that Markov models are good tools to identify the structure of brain connectivity from fMRI signals, but for this purpose they must reflect the small-world properties of the underlying neural systems. Copyright © 2012 Elsevier Ltd. All rights reserved.

  3. Diffusion, confusion and functional MRI

    International Nuclear Information System (INIS)

    Le Bihan, Denis

    2012-01-01

    Diffusion MRI has been introduced in 1985 and has had a very successful life on its own. While it has become a standard for imaging stroke and white matter disorders, the borders between diffusion MRI and the general field of fMRI have always remained fuzzy. First, diffusion MRI has been used to obtain images of brain function, based on the idea that diffusion MRI could also be made sensitive to blood flow, through the intra-voxel incoherent motion (IVIM) concept. Second, the IVIM concept helped better understand the contribution from different vasculature components to the BOLD fMRI signal. Third, it has been shown recently that a genuine fMRI signal can be obtained with diffusion MRI. This 'DfMRI' signal is notably different from the BOLD fMRI signal, especially for its much faster response to brain activation both at onset and offset, which points out to structural changes in the neural tissues, perhaps such as cell swelling, occurring in activated neural tissue. This short article reviews the major steps which have paved the way for this exciting development, underlying how technical progress with MRI equipment has each time been instrumental to expand the horizon of diffusion MRI toward the field of fMRI. (authors)

  4. Neuroethics and fMRI: Mapping a fledgling relationship

    DEFF Research Database (Denmark)

    Garnett, Alex; Whiteley, Louise Emma; Piwowar, Heather

    2011-01-01

    Human functional magnetic resonance imaging (fMRI) informs the understanding of the neural basis of mental function and is a key domain of ethical enquiry. It raises questions about the practice and implications of research, and reflexively informs ethics through the empirical investigation of mo...

  5. fMRI for mapping language networks in neurosurgical cases

    International Nuclear Information System (INIS)

    Gupta, Santosh S

    2014-01-01

    Evaluating language has been a long-standing application in functional magnetic resonance imaging (fMRI) studies, both in research and clinical circumstances, and still provides challenges. Localization of eloquent areas is important in neurosurgical cases, so that there is least possible damage to these areas during surgery, maintaining their function postoperatively, therefore providing good quality of life to the patient. Preoperative fMRI study is a non-invasive tool to localize the eloquent areas, including language, with other traditional methods generally used being invasive and at times perilous. In this article, we describe methods and various paradigms to study the language areas, in clinical neurosurgical cases, along with illustrations of cases from our institute

  6. Towards open sharing of task-based fMRI data: The OpenfMRI project

    Directory of Open Access Journals (Sweden)

    Russell A Poldrack

    2013-07-01

    Full Text Available The large-scale sharing of task-based functional neuroimaging data has the potential to allow novel insights into the organization of mental function in the brain, but the field of neuroimaging has lagged behind other areas of bioscience in the development of data sharing resources. This paper describes the OpenFMRI project (accessible online at http://www.openfmri.org, which aims to provide the neuroimaging community with a resource to support open sharing of task-based fMRI studies. We describe the motivation behind the project, focusing particularly on how this project addresses some of the well-known challenges to sharing of task-based fMRI data. Results from a preliminary analysis of the current database are presented, which demonstrate the ability to classify between task contrasts with high generalization accuracy across subjects, and the ability to identify individual subjects from their activation maps with moderately high accuracy. Clustering analyses show that the similarity relations between statistical maps have a somewhat orderly relation to the mental functions engaged by the relevant tasks. These results highlight the potential of the project to support large-scale multivariate analyses of the relation between mental processes and brain function.

  7. Study of human brain functions by functional magnetic resonance imaging (fMRI) and spectroscopy (fMRS)

    International Nuclear Information System (INIS)

    Jagannathan, N.R.

    1998-01-01

    Functional magnetic resonance imaging (fMRI) has become a powerful tool in the detection and assessment of cerebral pathophysiology and the regional mapping and characterization of cognitive processes such as motor skills, vision, language and memory. The results of the effect of motor cortex stimulation during repetitive hand squeezing task activation using in-vivo single voxel NMR spectroscopy carried out on normal volunteer subjects are presented

  8. Decoding subjective mental states from fMRI activity patterns

    International Nuclear Information System (INIS)

    Tamaki, Masako; Kamitani, Yukiyasu

    2011-01-01

    In recent years, functional magnetic resonance imaging (fMRI) decoding has emerged as a powerful tool to read out detailed stimulus features from multi-voxel brain activity patterns. Moreover, the method has been extended to perform a primitive form of 'mind-reading,' by applying a decoder 'objectively' trained using stimulus features to more 'subjective' conditions. In this paper, we first introduce basic procedures for fMRI decoding based on machine learning techniques. Second, we discuss the source of information used for decoding, in particular, the possibility of extracting information from subvoxel neural structures. We next introduce two experimental designs for decoding subjective mental states: the 'objective-to-subjective design' and the 'subjective-to-subjective design.' Then, we illustrate recent studies on the decoding of a variety of mental states, such as, attention, awareness, decision making, memory, and mental imagery. Finally, we discuss the challenges and new directions of fMRI decoding. (author)

  9. The nuisance of nuisance regression: spectral misspecification in a common approach to resting-state fMRI preprocessing reintroduces noise and obscures functional connectivity.

    Science.gov (United States)

    Hallquist, Michael N; Hwang, Kai; Luna, Beatriz

    2013-11-15

    Recent resting-state functional connectivity fMRI (RS-fcMRI) research has demonstrated that head motion during fMRI acquisition systematically influences connectivity estimates despite bandpass filtering and nuisance regression, which are intended to reduce such nuisance variability. We provide evidence that the effects of head motion and other nuisance signals are poorly controlled when the fMRI time series are bandpass-filtered but the regressors are unfiltered, resulting in the inadvertent reintroduction of nuisance-related variation into frequencies previously suppressed by the bandpass filter, as well as suboptimal correction for noise signals in the frequencies of interest. This is important because many RS-fcMRI studies, including some focusing on motion-related artifacts, have applied this approach. In two cohorts of individuals (n=117 and 22) who completed resting-state fMRI scans, we found that the bandpass-regress approach consistently overestimated functional connectivity across the brain, typically on the order of r=.10-.35, relative to a simultaneous bandpass filtering and nuisance regression approach. Inflated correlations under the bandpass-regress approach were associated with head motion and cardiac artifacts. Furthermore, distance-related differences in the association of head motion and connectivity estimates were much weaker for the simultaneous filtering approach. We recommend that future RS-fcMRI studies ensure that the frequencies of nuisance regressors and fMRI data match prior to nuisance regression, and we advocate a simultaneous bandpass filtering and nuisance regression strategy that better controls nuisance-related variability. Copyright © 2013 Elsevier Inc. All rights reserved.

  10. The effect of hippocampal function, volume and connectivity on posterior cingulate cortex functioning during episodic memory fMRI in mild cognitive impairment.

    Science.gov (United States)

    Papma, Janne M; Smits, Marion; de Groot, Marius; Mattace Raso, Francesco U; van der Lugt, Aad; Vrooman, Henri A; Niessen, Wiro J; Koudstaal, Peter J; van Swieten, John C; van der Veen, Frederik M; Prins, Niels D

    2017-09-01

    Diminished function of the posterior cingulate cortex (PCC) is a typical finding in early Alzheimer's disease (AD). It is hypothesized that in early stage AD, PCC functioning relates to or reflects hippocampal dysfunction or atrophy. The aim of this study was to examine the relationship between hippocampus function, volume and structural connectivity, and PCC activation during an episodic memory task-related fMRI study in mild cognitive impairment (MCI). MCI patients (n = 27) underwent episodic memory task-related fMRI, 3D-T1w MRI, 2D T2-FLAIR MRI and diffusion tensor imaging. Stepwise linear regression analysis was performed to examine the relationship between PCC activation and hippocampal activation, hippocampal volume and diffusion measures within the cingulum along the hippocampus. We found a significant relationship between PCC and hippocampus activation during successful episodic memory encoding and correct recognition in MCI patients. We found no relationship between the PCC and structural hippocampal predictors. Our results indicate a relationship between PCC and hippocampus activation during episodic memory engagement in MCI. This may suggest that during episodic memory, functional network deterioration is the most important predictor of PCC functioning in MCI. • PCC functioning during episodic memory relates to hippocampal functioning in MCI. • PCC functioning during episodic memory does not relate to hippocampal structure in MCI. • Functional network changes are an important predictor of PCC functioning in MCI.

  11. Principal Feature Analysis: A Multivariate Feature Selection Method for fMRI Data

    Directory of Open Access Journals (Sweden)

    Lijun Wang

    2013-01-01

    Full Text Available Brain decoding with functional magnetic resonance imaging (fMRI requires analysis of complex, multivariate data. Multivoxel pattern analysis (MVPA has been widely used in recent years. MVPA treats the activation of multiple voxels from fMRI data as a pattern and decodes brain states using pattern classification methods. Feature selection is a critical procedure of MVPA because it decides which features will be included in the classification analysis of fMRI data, thereby improving the performance of the classifier. Features can be selected by limiting the analysis to specific anatomical regions or by computing univariate (voxel-wise or multivariate statistics. However, these methods either discard some informative features or select features with redundant information. This paper introduces the principal feature analysis as a novel multivariate feature selection method for fMRI data processing. This multivariate approach aims to remove features with redundant information, thereby selecting fewer features, while retaining the most information.

  12. A technique to consider mismatches between fMRI and EEG/MEG sources for fMRI-constrained EEG/MEG source imaging: a preliminary simulation study

    International Nuclear Information System (INIS)

    Im, Chang-Hwan; Lee, Soo Yeol

    2006-01-01

    fMRI-constrained EEG/MEG source imaging can be a powerful tool in studying human brain functions with enhanced spatial and temporal resolutions. Recent studies on the combination of fMRI and EEG/MEG have suggested that fMRI prior information could be readily implemented by simply imposing different weighting factors to cortical sources overlapping with the fMRI activations. It has been also reported, however, that such a hard constraint may cause severe distortions or elimination of meaningful EEG/MEG sources when there are distinct mismatches between the fMRI activations and the EEG/MEG sources. If one wants to obtain the actual EEG/MEG source locations and uses the fMRI prior information as just an auxiliary tool to enhance focality of the distributed EEG/MEG sources, it is reasonable to weaken the strength of fMRI constraint when severe mismatches between fMRI and EEG/MEG sources are observed. The present study suggests an efficient technique to automatically adjust the strength of fMRI constraint according to the mismatch level. The use of the proposed technique rarely affects the results of conventional fMRI-constrained EEG/MEG source imaging if no major mismatch between the two modalities is detected; while the new results become similar to those of typical EEG/MEG source imaging without fMRI constraint if the mismatch level is significant. A preliminary simulation study using realistic EEG signals demonstrated that the proposed technique can be a promising tool to selectively apply fMRI prior information to EEG/MEG source imaging

  13. Imaging tools to study pharmacology: functional MRI on small rodents

    Directory of Open Access Journals (Sweden)

    Elisabeth eJonckers

    2015-10-01

    Full Text Available Functional Magnetic Resonance Imaging (fMRI is an excellent tool to study the effect of pharmacological modulations on brain function in a non-invasive and longitudinal manner. We introduce several blood oxygenation level dependent (BOLD fMRI techniques, including resting state (rsfMRI, stimulus-evoked (st-fMRI, and pharmacological MRI (phMRI. Respectively, these techniques permit the assessment of functional connectivity during rest as well as brain activation triggered by sensory stimulation and/or a pharmacological challenge. The first part of this review describes the physiological basis of BOLD fMRI and the hemodynamic response on which the MRI contrast is based. Specific emphasis goes to possible effects of anaesthesia and the animal’s physiological conditions on neural activity and the hemodynamic response. The second part of this review describes applications of the aforementioned techniques in pharmacologically-induced, as well as in traumatic and transgenic disease models and illustrates how multiple fMRI methods can be applied successfully to evaluate different aspects of a specific disorder. For example, fMRI techniques can be used to pinpoint the neural substrate of a disease beyond previously defined hypothesis-driven regions-of-interest (ROIs. In addition, fMRI techniques allow one to dissect how specific modifications (e.g. treatment, lesion etc. modulate the functioning of specific brain areas (st-fMRI, phMRI and how functional connectivity (rsfMRI between several brain regions is affected, both in acute and extended time frames. Furthermore, fMRI techniques can be used to assess/explore the efficacy of novel treatments in depth, both in fundamental research as well as in preclinical settings. In conclusion, by describing several exemplary studies, we aim to highlight the advantages of functional MRI in exploring the acute and long-term effects of pharmacological substances and/or pathology on brain functioning along with

  14. IClinfMRI Software for Integrating Functional MRI Techniques in Presurgical Mapping and Clinical Studies.

    Science.gov (United States)

    Hsu, Ai-Ling; Hou, Ping; Johnson, Jason M; Wu, Changwei W; Noll, Kyle R; Prabhu, Sujit S; Ferguson, Sherise D; Kumar, Vinodh A; Schomer, Donald F; Hazle, John D; Chen, Jyh-Horng; Liu, Ho-Ling

    2018-01-01

    Task-evoked and resting-state (rs) functional magnetic resonance imaging (fMRI) techniques have been applied to the clinical management of neurological diseases, exemplified by presurgical localization of eloquent cortex, to assist neurosurgeons in maximizing resection while preserving brain functions. In addition, recent studies have recommended incorporating cerebrovascular reactivity (CVR) imaging into clinical fMRI to evaluate the risk of lesion-induced neurovascular uncoupling (NVU). Although each of these imaging techniques possesses its own advantage for presurgical mapping, a specialized clinical software that integrates the three complementary techniques and promptly outputs the analyzed results to radiology and surgical navigation systems in a clinical format is still lacking. We developed the Integrated fMRI for Clinical Research (IClinfMRI) software to facilitate these needs. Beyond the independent processing of task-fMRI, rs-fMRI, and CVR mapping, IClinfMRI encompasses three unique functions: (1) supporting the interactive rs-fMRI mapping while visualizing task-fMRI results (or results from published meta-analysis) as a guidance map, (2) indicating/visualizing the NVU potential on analyzed fMRI maps, and (3) exporting these advanced mapping results in a Digital Imaging and Communications in Medicine (DICOM) format that are ready to export to a picture archiving and communication system (PACS) and a surgical navigation system. In summary, IClinfMRI has the merits of efficiently translating and integrating state-of-the-art imaging techniques for presurgical functional mapping and clinical fMRI studies.

  15. Comparison of PET and fMRI activation patterns during declarative memory processes

    International Nuclear Information System (INIS)

    Mottaghy, F.M.; Krause, B.J.; Schmidt, D.; Hautzel, H.; Mueller-Gaertner, H.-W.; Herzog, H.; Shah, N.J.; Halsband, U.

    2000-01-01

    Aim: In this study neuronal correlates of encoding and retrieval in paired association learning were compared using two different neuroimaging methods: Positron emission tomography (PET) and functional magnetic resonance imaging (fMRI). Methods: 6 right-handed normal male volunteers took part in the study. Each subject underwent six 0-15-butanol PET scans and an fMRI study comprising four single epochs on a different day. The subjects had to learn and retrieve 12 word pairs which were visually presented (highly imaginable words, not semantically related). Results: Mean recall accuracy was 93% in the PET as well as in the fMRI experiment. During encoding and retrieval we found anterior cingulate cortex activation, and bilateral prefrontal cortex activation in both imaging modalities. Furthermore, we demonstrate the importance of the precuneus in episodic memory. With PET the results demonstrate frontopolar activations whereas fMRI fails to show activations in this area probably due to susceptibility artifacts. In fMRI we found additionally parahippocampal activation and due to the whole-brain coverage cerebellar activation during encoding. The distance between the center-of-mass activations in both modalities was 7.2±6.5 mm. Conclusion: There is a preponderance of commonalities in the activation patterns yielded with fMRI and PET. However, there are also important differences. The decision to choose one or the other neuroimaging modality should among other aspects depend on the study design (single subject vs. group study) and the task of interest. (orig.) [de

  16. A task-related and resting state realistic fMRI simulator for fMRI data validation

    Science.gov (United States)

    Hill, Jason E.; Liu, Xiangyu; Nutter, Brian; Mitra, Sunanda

    2017-02-01

    After more than 25 years of published functional magnetic resonance imaging (fMRI) studies, careful scrutiny reveals that most of the reported results lack fully decisive validation. The complex nature of fMRI data generation and acquisition results in unavoidable uncertainties in the true estimation and interpretation of both task-related activation maps and resting state functional connectivity networks, despite the use of various statistical data analysis methodologies. The goal of developing the proposed STANCE (Spontaneous and Task-related Activation of Neuronally Correlated Events) simulator is to generate realistic task-related and/or resting-state 4D blood oxygenation level dependent (BOLD) signals, given the experimental paradigm and scan protocol, by using digital phantoms of twenty normal brains available from BrainWeb (http://brainweb.bic.mni.mcgill.ca/brainweb/). The proposed simulator will include estimated system and modelled physiological noise as well as motion to serve as a reference to measured brain activities. In its current form, STANCE is a MATLAB toolbox with command line functions serving as an open-source add-on to SPM8 (http://www.fil.ion.ucl.ac.uk/spm/software/spm8/). The STANCE simulator has been designed in a modular framework so that the hemodynamic response (HR) and various noise models can be iteratively improved to include evolving knowledge about such models.

  17. Collective Correlations of Brodmann Areas fMRI Study with RMT-Denoising

    OpenAIRE

    Burda, Zdzislaw; Kornelsen, Jennifer; Nowak, Maciej A.; Porebski, Bartosz; Sboto-Frankenstein, Uta; Tomanek, Boguslaw; Tyburczyk, Jacek

    2013-01-01

    We study collective behavior of Brodmann regions of human cerebral cortex using functional Magnetic Resonance Imaging (fMRI) and Random Matrix Theory (RMT). The raw fMRI data is mapped onto the cortex regions corresponding to the Brodmann areas with the aid of the Talairach coordinates. Principal Component Analysis (PCA) of the Pearson correlation matrix for 41 different Brodmann regions is carried out to determine their collective activity in the idle state and in the active state stimulated...

  18. Auditory processing in the brainstem and audiovisual integration in humans studied with fMRI

    NARCIS (Netherlands)

    Slabu, Lavinia Mihaela

    2008-01-01

    Functional magnetic resonance imaging (fMRI) is a powerful technique because of the high spatial resolution and the noninvasiveness. The applications of the fMRI to the auditory pathway remain a challenge due to the intense acoustic scanner noise of approximately 110 dB SPL. The auditory system

  19. Unified ICA-SPM analysis of fMRI experiments

    DEFF Research Database (Denmark)

    Bjerre, Troels; Henriksen, Jonas; Nielsen, Carsten Haagen

    2009-01-01

    We present a toolbox for exploratory analysis of functional magnetic resonance imaging (fMRI) data using independent component analysis (ICA) within the widely used SPM analysis pipeline. The toolbox enables dimensional reduction using principal component analysis, ICA using several different ICA...

  20. A 4-channel 3 Tesla phased array receive coil for awake rhesus monkey fMRI and diffusion MRI experiments.

    Science.gov (United States)

    Khachaturian, Mark Haig

    2010-01-01

    Awake monkey fMRI and diffusion MRI combined with conventional neuroscience techniques has the potential to study the structural and functional neural network. The majority of monkey fMRI and diffusion MRI experiments are performed with single coils which suffer from severe EPI distortions which limit resolution. By constructing phased array coils for monkey MRI studies, gains in SNR and anatomical accuracy (i.e., reduction of EPI distortions) can be achieved using parallel imaging. The major challenges associated with constructing phased array coils for monkeys are the variation in head size and space constraints. Here, we apply phased array technology to a 4-channel phased array coil capable of improving the resolution and image quality of full brain awake monkey fMRI and diffusion MRI experiments. The phased array coil is that can adapt to different rhesus monkey head sizes (ages 4-8) and fits in the limited space provided by monkey stereotactic equipment and provides SNR gains in primary visual cortex and anatomical accuracy in conjunction with parallel imaging and improves resolution in fMRI experiments by a factor of 2 (1.25 mm to 1.0 mm isotropic) and diffusion MRI experiments by a factor of 4 (1.5 mm to 0.9 mm isotropic).

  1. Infinite Relational Modeling of Functional Connectivity in Resting State fMRI

    DEFF Research Database (Denmark)

    Mørup, Morten; Madsen, Kristoffer H.; Dogonowski, Anne Marie

    2010-01-01

    Functional magnetic resonance imaging (fMRI) can be applied to study the functional connectivity of the neural elements which form complex network at a whole brain level. Most analyses of functional resting state networks (RSN) have been based on the analysis of correlation between the temporal...... dynamics of various regions of the brain. While these models can identify coherently behaving groups in terms of correlation they give little insight into how these groups interact. In this paper we take a different view on the analysis of functional resting state networks. Starting from the definition...... of resting state as functional coherent groups we search for functional units of the brain that communicate with other parts of the brain in a coherent manner as measured by mutual information. We use the infinite relational model (IRM) to quantify functional coherent groups of resting state networks...

  2. An fMRI study

    Indian Academy of Sciences (India)

    Home; Journals; Journal of Biosciences; Volume 38; Issue 5 ... Alcoholism; brain; fMRI; language processing; lexical; semantic judgment ... alcohol dependence is associated with neurocognitive deficits in tasks requiring memory, perceptual ...

  3. Autobiographical Memory in Semantic Dementia: A Longitudinal fMRI Study

    Science.gov (United States)

    Maguire, Eleanor A.; Kumaran, Dharshan; Hassabis, Demis; Kopelman, Michael D.

    2010-01-01

    Whilst patients with semantic dementia (SD) are known to suffer from semantic memory and language impairments, there is less agreement about whether memory for personal everyday experiences, autobiographical memory, is compromised. In healthy individuals, functional MRI (fMRI) has helped to delineate a consistent and distributed brain network…

  4. Testing competing hypotheses about single trial fMRI

    DEFF Research Database (Denmark)

    Hansen, Lars Kai; Purushotham, Archana; Kim, Seong-Ge

    2002-01-01

    We use a Bayesian framework to compute probabilities of competing hypotheses about functional activation based on single trial fMRI measurements. Within the framework we obtain a complete probabilistic picture of competing hypotheses, hence control of both type I and type II errors....

  5. Application of calibrated fMRI in Alzheimer's disease.

    Science.gov (United States)

    Lajoie, Isabelle; Nugent, Scott; Debacker, Clément; Dyson, Kenneth; Tancredi, Felipe B; Badhwar, AmanPreet; Belleville, Sylvie; Deschaintre, Yan; Bellec, Pierre; Doyon, Julien; Bocti, Christian; Gauthier, Serge; Arnold, Douglas; Kergoat, Marie-Jeanne; Chertkow, Howard; Monchi, Oury; Hoge, Richard D

    2017-01-01

    Calibrated fMRI based on arterial spin-labeling (ASL) and blood oxygen-dependent contrast (BOLD), combined with periods of hypercapnia and hyperoxia, can provide information on cerebrovascular reactivity (CVR), resting blood flow (CBF), oxygen extraction fraction (OEF), and resting oxidative metabolism (CMRO 2 ). Vascular and metabolic integrity are believed to be affected in Alzheimer's disease (AD), thus, the use of calibrated fMRI in AD may help understand the disease and monitor therapeutic responses in future clinical trials. In the present work, we applied a calibrated fMRI approach referred to as Quantitative O2 (QUO2) in a cohort of probable AD dementia and age-matched control participants. The resulting CBF, OEF and CMRO 2 values fell within the range from previous studies using positron emission tomography (PET) with 15 O labeling. Moreover, the typical parietotemporal pattern of hypoperfusion and hypometabolism in AD was observed, especially in the precuneus, a particularly vulnerable region. We detected no deficit in frontal CBF, nor in whole grey matter CVR, which supports the hypothesis that the effects observed were associated specifically with AD rather than generalized vascular disease. Some key pitfalls affecting both ASL and BOLD methods were encountered, such as prolonged arterial transit times (particularly in the occipital lobe), the presence of susceptibility artifacts obscuring medial temporal regions, and the challenges associated with the hypercapnic manipulation in AD patients and elderly participants. The present results are encouraging and demonstrate the promise of calibrated fMRI measurements as potential biomarkers in AD. Although CMRO 2 can be imaged with 15 O PET, the QUO2 method uses more widely available imaging infrastructure, avoids exposure to ionizing radiation, and integrates with other MRI-based measures of brain structure and function.

  6. Application of calibrated fMRI in Alzheimer's disease

    Directory of Open Access Journals (Sweden)

    Isabelle Lajoie

    2017-01-01

    Full Text Available Calibrated fMRI based on arterial spin-labeling (ASL and blood oxygen-dependent contrast (BOLD, combined with periods of hypercapnia and hyperoxia, can provide information on cerebrovascular reactivity (CVR, resting blood flow (CBF, oxygen extraction fraction (OEF, and resting oxidative metabolism (CMRO2. Vascular and metabolic integrity are believed to be affected in Alzheimer's disease (AD, thus, the use of calibrated fMRI in AD may help understand the disease and monitor therapeutic responses in future clinical trials. In the present work, we applied a calibrated fMRI approach referred to as Quantitative O2 (QUO2 in a cohort of probable AD dementia and age-matched control participants. The resulting CBF, OEF and CMRO2 values fell within the range from previous studies using positron emission tomography (PET with 15O labeling. Moreover, the typical parietotemporal pattern of hypoperfusion and hypometabolism in AD was observed, especially in the precuneus, a particularly vulnerable region. We detected no deficit in frontal CBF, nor in whole grey matter CVR, which supports the hypothesis that the effects observed were associated specifically with AD rather than generalized vascular disease. Some key pitfalls affecting both ASL and BOLD methods were encountered, such as prolonged arterial transit times (particularly in the occipital lobe, the presence of susceptibility artifacts obscuring medial temporal regions, and the challenges associated with the hypercapnic manipulation in AD patients and elderly participants. The present results are encouraging and demonstrate the promise of calibrated fMRI measurements as potential biomarkers in AD. Although CMRO2 can be imaged with 15O PET, the QUO2 method uses more widely available imaging infrastructure, avoids exposure to ionizing radiation, and integrates with other MRI-based measures of brain structure and function.

  7. Functional connectivity associated with social networks in older adults: A resting-state fMRI study.

    Science.gov (United States)

    Pillemer, Sarah; Holtzer, Roee; Blumen, Helena M

    2017-06-01

    Poor social networks and decreased levels of social support are associated with worse mood, health, and cognition in younger and older adults. Yet, we know very little about the brain substrates associated with social networks and social support, particularly in older adults. This study examined functional brain substrates associated with social networks using the Social Network Index (SNI) and resting-state functional magnetic resonance imaging (fMRI). Resting-state fMRI data from 28 non-demented older adults were analyzed with independent components analyses. As expected, four established resting-state networks-previously linked to motor, vision, speech, and other language functions-correlated with the quality (SNI-1: total number of high-contact roles of a respondent) and quantity (SNI-2: total number of individuals in a respondent's social network) of social networks: a sensorimotor, a visual, a vestibular/insular, and a left frontoparietal network. Moreover, SNI-1 was associated with greater functional connectivity in the lateral prefrontal regions of the left frontoparietal network, while SNI-2 was associated with greater functional connectivity in the medial prefrontal regions of this network. Thus, lateral prefrontal regions may be particularly linked to the quality of social networks while medial prefrontal regions may be particularly linked to the quantity of social networks.

  8. Gaussian process based independent analysis for temporal source separation in fMRI

    DEFF Research Database (Denmark)

    Hald, Ditte Høvenhoff; Henao, Ricardo; Winther, Ole

    2017-01-01

    Functional Magnetic Resonance Imaging (fMRI) gives us a unique insight into the processes of the brain, and opens up for analyzing the functional activation patterns of the underlying sources. Task-inferred supervised learning with restrictive assumptions in the regression set-up, restricts...... the exploratory nature of the analysis. Fully unsupervised independent component analysis (ICA) algorithms, on the other hand, can struggle to detect clear classifiable components on single-subject data. We attribute this shortcoming to inadequate modeling of the fMRI source signals by failing to incorporate its...

  9. Quality assurance in functional MRI

    DEFF Research Database (Denmark)

    Liu, Thomas T; Glover, Gary H; Mueller, Bryon A

    2015-01-01

    Over the past 20 years, functional magnetic resonance imaging (fMRI) has ben- efited greatly from improvements in MRI hardware and software. At the same time, fMRI researchers have pushed the technical limits of MRI systems and greatly in- fluenced the development of state-of-the-art systems...... consistent data throughout the course of a study, and consistent stability across time and sites is needed to allow data from different time periods or acquisition sites to be optimally integrated....

  10. Feasibility of using fMRI to study mothers responding to infant cries.

    Science.gov (United States)

    Lorberbaum, J P; Newman, J D; Dubno, J R; Horwitz, A R; Nahas, Z; Teneback, C C; Bloomer, C W; Bohning, D E; Vincent, D; Johnson, M R; Emmanuel, N; Brawman-Mintzer, O; Book, S W; Lydiard, R B; Ballenger, J C; George, M S

    1999-01-01

    While parenting is a universal human behavior, its neuroanatomic basis is currently unknown. Animal data suggest that the cingulate may play an important function in mammalian parenting behavior. For example, in rodents cingulate lesions impair maternal behavior. Here, in an attempt to understand the brain basis of human maternal behavior, we had mothers listen to recorded infant cries and white noise control sounds while they underwent functional MRI (fMRI) of the brain. We hypothesized that mothers would show significantly greater cingulate activity during the cries compared to the control sounds. Of 7 subjects scanned, 4 had fMRI data suitable for analysis. When fMRI data were averaged for these 4 subjects, the anterior cingulate and right medial prefrontal cortex were the only brain regions showing statistically increased activity with the cries compared to white noise control sounds (cluster analysis with one-tailed z-map threshold of P parent-infant bond and (2) examine whether markers of this bond, such as maternal brain response to infant crying, can predict maternal style (i.e., child neglect), offspring temperament, or offspring depression or anxiety.

  11. Network analysis of functional brain connectivity in borderline personality disorder using resting-state fMRI

    OpenAIRE

    Tingting Xu; Kathryn R. Cullen; Bryon Mueller; Mindy W. Schreiner; Kelvin O. Lim; S. Charles Schulz; Keshab K. Parhi

    2016-01-01

    Borderline personality disorder (BPD) is associated with symptoms such as affect dysregulation, impaired sense of self, and self-harm behaviors. Neuroimaging research on BPD has revealed structural and functional abnormalities in specific brain regions and connections. However, little is known about the topological organizations of brain networks in BPD. We collected resting-state functional magnetic resonance imaging (fMRI) data from 20 patients with BPD and 10 healthy controls, and construc...

  12. Effects of hypoglycemia on human brain activation measured with fMRI.

    Science.gov (United States)

    Anderson, Adam W; Heptulla, Rubina A; Driesen, Naomi; Flanagan, Daniel; Goldberg, Philip A; Jones, Timothy W; Rife, Fran; Sarofin, Hedy; Tamborlane, William; Sherwin, Robert; Gore, John C

    2006-07-01

    Functional magnetic resonance imaging (fMRI) was used to measure the effects of acute hypoglycemia caused by passive sensory stimulation on brain activation. Visual stimulation was used to generate blood-oxygen-level-dependent (BOLD) contrast, which was monitored during hyperinsulinemic hypoglycemic and euglycemic clamp studies. Hypoglycemia (50 +/- 1 mg glucose/dl) decreased the fMRI signal relative to euglycemia in 10 healthy human subjects: the fractional signal change was reduced by 28 +/- 12% (P variations in blood glucose levels may modulate BOLD signals in the healthy brain.

  13. Temporal comparison of functional brain imaging with diffuse optical tomography and fMRI during rat forepaw stimulation

    International Nuclear Information System (INIS)

    Siegel, Andrew M; Culver, Joseph P; Mandeville, Joseph B; Boas, David A

    2003-01-01

    The time courses of oxyhaemoglobin ([HbO 2 ]), deoxyhaemoglobin ([HbR]) and total haemoglobin ([HbT]) concentration changes following cortical activation in rats by electrical forepaw stimulation were measured using diffuse optical tomography (DOT) and compared to similar measurements performed previously with fMRI at 2.0 T and 4.7 T. We also explored the qualitative effects of varying stimulus parameters on the temporal evolution of the hemodynamic response. DOT images were reconstructed at a depth of 1.5 mm over a 1 cm square area from 2 mm anterior to bregma to 8 mm posterior to bregma. The measurement set included 9 sources and 16 detectors with an imaging frame rate of 10 Hz. Both DOT [HbR] and [HbO 2 ] time courses were compared to the fMRI BOLD time course during stimulation, and the DOT [HbT] time course was compared to the fMRI cerebral plasma volume (CPV) time course. We believe that DOT and fMRI can provide similar temporal information for both blood volume and deoxyhaemoglobin changes, which helps to cross-validate these two techniques and to demonstrate that DOT can be useful as a complementary modality to fMRI for investigating the hemodynamic response to neuronal activity

  14. Temporal comparison of functional brain imaging with diffuse optical tomography and fMRI during rat forepaw stimulation

    Energy Technology Data Exchange (ETDEWEB)

    Siegel, Andrew M [Tufts University Bioengineering Center, Medford, MA 02155 (United States); Culver, Joseph P [Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02129 (United States); Mandeville, Joseph B [Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02129 (United States); Boas, David A [Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02129 (United States)

    2003-05-21

    The time courses of oxyhaemoglobin ([HbO{sub 2}]), deoxyhaemoglobin ([HbR]) and total haemoglobin ([HbT]) concentration changes following cortical activation in rats by electrical forepaw stimulation were measured using diffuse optical tomography (DOT) and compared to similar measurements performed previously with fMRI at 2.0 T and 4.7 T. We also explored the qualitative effects of varying stimulus parameters on the temporal evolution of the hemodynamic response. DOT images were reconstructed at a depth of 1.5 mm over a 1 cm square area from 2 mm anterior to bregma to 8 mm posterior to bregma. The measurement set included 9 sources and 16 detectors with an imaging frame rate of 10 Hz. Both DOT [HbR] and [HbO{sub 2}] time courses were compared to the fMRI BOLD time course during stimulation, and the DOT [HbT] time course was compared to the fMRI cerebral plasma volume (CPV) time course. We believe that DOT and fMRI can provide similar temporal information for both blood volume and deoxyhaemoglobin changes, which helps to cross-validate these two techniques and to demonstrate that DOT can be useful as a complementary modality to fMRI for investigating the hemodynamic response to neuronal activity.

  15. Exploring connectivity with large-scale Granger causality on resting-state functional MRI.

    Science.gov (United States)

    DSouza, Adora M; Abidin, Anas Z; Leistritz, Lutz; Wismüller, Axel

    2017-08-01

    Large-scale Granger causality (lsGC) is a recently developed, resting-state functional MRI (fMRI) connectivity analysis approach that estimates multivariate voxel-resolution connectivity. Unlike most commonly used multivariate approaches, which establish coarse-resolution connectivity by aggregating voxel time-series avoiding an underdetermined problem, lsGC estimates voxel-resolution, fine-grained connectivity by incorporating an embedded dimension reduction. We investigate application of lsGC on realistic fMRI simulations, modeling smoothing of neuronal activity by the hemodynamic response function and repetition time (TR), and empirical resting-state fMRI data. Subsequently, functional subnetworks are extracted from lsGC connectivity measures for both datasets and validated quantitatively. We also provide guidelines to select lsGC free parameters. Results indicate that lsGC reliably recovers underlying network structure with area under receiver operator characteristic curve (AUC) of 0.93 at TR=1.5s for a 10-min session of fMRI simulations. Furthermore, subnetworks of closely interacting modules are recovered from the aforementioned lsGC networks. Results on empirical resting-state fMRI data demonstrate recovery of visual and motor cortex in close agreement with spatial maps obtained from (i) visuo-motor fMRI stimulation task-sequence (Accuracy=0.76) and (ii) independent component analysis (ICA) of resting-state fMRI (Accuracy=0.86). Compared with conventional Granger causality approach (AUC=0.75), lsGC produces better network recovery on fMRI simulations. Furthermore, it cannot recover functional subnetworks from empirical fMRI data, since quantifying voxel-resolution connectivity is not possible as consequence of encountering an underdetermined problem. Functional network recovery from fMRI data suggests that lsGC gives useful insight into connectivity patterns from resting-state fMRI at a multivariate voxel-resolution. Copyright © 2017 Elsevier B.V. All

  16. Tactile and non-tactile sensory paradigms for fMRI and neurophysiologic studies in rodents

    OpenAIRE

    Sanganahalli, Basavaraju G.; Bailey, Christopher J.; Herman, Peter; Hyder, Fahmeed

    2009-01-01

    Functional magnetic resonance imaging (fMRI) has become a popular functional imaging tool for human studies. Future diagnostic use of fMRI depends, however, on a suitable neurophysiologic interpretation of the blood oxygenation level dependent (BOLD) signal change. This particular goal is best achieved in animal models primarily due to the invasive nature of other methods used and/or pharmacological agents applied to probe different nuances of neuronal (and glial) activity coupled to the BOLD...

  17. Mild cognitive impairment and fMRI studies of brain functional connectivity: the state of the art

    Science.gov (United States)

    Farràs-Permanyer, Laia; Guàrdia-Olmos, Joan; Peró-Cebollero, Maribel

    2015-01-01

    In the last 15 years, many articles have studied brain connectivity in Mild Cognitive Impairment patients with fMRI techniques, seemingly using different connectivity statistical models in each investigation to identify complex connectivity structures so as to recognize typical behavior in this type of patient. This diversity in statistical approaches may cause problems in results comparison. This paper seeks to describe how researchers approached the study of brain connectivity in MCI patients using fMRI techniques from 2002 to 2014. The focus is on the statistical analysis proposed by each research group in reference to the limitations and possibilities of those techniques to identify some recommendations to improve the study of functional connectivity. The included articles came from a search of Web of Science and PsycINFO using the following keywords: f MRI, MCI, and functional connectivity. Eighty-one papers were found, but two of them were discarded because of the lack of statistical analysis. Accordingly, 79 articles were included in this review. We summarized some parts of the articles, including the goal of every investigation, the cognitive paradigm and methods used, brain regions involved, use of ROI analysis and statistical analysis, emphasizing on the connectivity estimation model used in each investigation. The present analysis allowed us to confirm the remarkable variability of the statistical analysis methods found. Additionally, the study of brain connectivity in this type of population is not providing, at the moment, any significant information or results related to clinical aspects relevant for prediction and treatment. We propose to follow guidelines for publishing fMRI data that would be a good solution to the problem of study replication. The latter aspect could be important for future publications because a higher homogeneity would benefit the comparison between publications and the generalization of results. PMID:26300802

  18. Adaptive Analysis of Functional MRI Data

    International Nuclear Information System (INIS)

    Friman, Ola

    2003-01-01

    Functional Magnetic Resonance Imaging (fMRI) is a recently developed neuro-imaging technique with capacity to map neural activity with high spatial precision. To locate active brain areas, the method utilizes local blood oxygenation changes which are reflected as small intensity changes in a special type of MR images. The ability to non-invasively map brain functions provides new opportunities to unravel the mysteries and advance the understanding of the human brain, as well as to perform pre-surgical examinations in order to optimize surgical interventions. This dissertation introduces new approaches for the analysis of fMRI data. The detection of active brain areas is a challenging problem due to high noise levels and artifacts present in the data. A fundamental tool in the developed methods is Canonical Correlation Analysis (CCA). CCA is used in two novel ways. First as a method with the ability to fully exploit the spatio-temporal nature of fMRI data for detecting active brain areas. Established analysis approaches mainly focus on the temporal dimension of the data and they are for this reason commonly referred to as being mass-univariate. The new CCA detection method encompasses and generalizes the traditional mass-univariate methods and can in this terminology be viewed as a mass-multivariate approach. The concept of spatial basis functions is introduced as a spatial counterpart of the temporal basis functions already in use in fMRI analysis. The spatial basis functions implicitly perform an adaptive spatial filtering of the fMRI images, which significantly improves detection performance. It is also shown how prior information can be incorporated into the analysis by imposing constraints on the temporal and spatial models and a constrained version of CCA is devised to this end. A general Principal Component Analysis technique for generating and constraining temporal and spatial subspace models is proposed to be used in combination with the constrained CCA

  19. Research progress of functional MRI in depression

    International Nuclear Information System (INIS)

    Xie Shenghui; Niu Guangming; Han Xiaodong; Qiao Pengfei

    2013-01-01

    The mood disorders of depression are associated with abnormalities of brain structure and function, and exploring their pathological mechanism has important significance for the choice of treatment and the curative effect evaluation. In recent years, the research of MRI on brain structure and function of depression has made great progress, especially in functional magnetic resonance imaging (fMRI). fMRI can detect the functional change in real time, and also can display the activity of brain and changes in the nerve pathways in patients with depression. This article summarizes the present research situation and progress of MRI in the diagnosis of depression. (authors)

  20. Non-white noise in fMRI: Does modelling have an impact?

    DEFF Research Database (Denmark)

    Lund, Torben Ellegaard; Madsen, Kristoffer Hougaard; Sidaros, Karam

    2006-01-01

    are typically modelled as an autoregressive (AR) process. In this paper, we propose an alternative approach: Nuisance Variable Regression (NVR). By inclusion of confounding effects in a general linear model (GLM), we first confirm that the spatial distribution of the various fMRI noise sources is similar......The sources of non-white noise in Blood Oxygenation Level Dependent (BOLD) functional magnetic resonance imaging (fMRI) are many. Familiar sources include low-frequency drift due to hardware imperfections, oscillatory noise due to respiration and cardiac pulsation and residual movement artefacts...

  1. An fMRI Study of Intra-Individual Functional Topography in the Human Cerebellum

    Directory of Open Access Journals (Sweden)

    Catherine J. Stoodley

    2010-01-01

    Full Text Available Neuroimaging studies report cerebellar activation during both motor and non-motor paradigms, and suggest a functional topography within the cerebellum. Sensorimotor tasks activate the anterior lobe, parts of lobule VI, and lobule VIII, whereas higher-level tasks activate lobules VI and VII in the posterior lobe. To determine whether these activation patterns are evident at a single-subject level, we conducted functional magnetic resonance imaging (fMRI during five tasks investigating sensorimotor (finger tapping, language (verb generation, spatial (mental rotation, working memory (N-back, and emotional processing (viewing images from the International Affective Picture System. Finger tapping activated the ipsilateral anterior lobe (lobules IV-V as well as lobules VI and VIII. Activation during verb generation was found in right lobules VII and VIIIA. Mental rotation activated left-lateralized clusters in lobules VII-VIIIA, VI-Crus I, and midline VIIAt. The N-back task showed bilateral activation in right lobules VI-Crus I and left lobules VIIB-VIIIA. Cerebellar activation was evident bilaterally in lobule VI while viewing arousing vs. neutral images. This fMRI study provides the first proof of principle demonstration that there is topographic organization of motor execution vs. cognitive/emotional domains within the cerebellum of a single individual, likely reflecting the anatomical specificity of cerebro-cerebellar circuits underlying different task domains. Inter-subject variability of motor and non-motor topography remains to be determined.

  2. Hybrid ICA-Seed-Based Methods for fMRI Functional Connectivity Assessment: A Feasibility Study

    Directory of Open Access Journals (Sweden)

    Robert E. Kelly

    2010-01-01

    Full Text Available Brain functional connectivity (FC is often assessed from fMRI data using seed-based methods, such as those of detecting temporal correlation between a predefined region (seed and all other regions in the brain; or using multivariate methods, such as independent component analysis (ICA. ICA is a useful data-driven tool, but reproducibility issues complicate group inferences based on FC maps derived with ICA. These reproducibility issues can be circumvented with hybrid methods that use information from ICA-derived spatial maps as seeds to produce seed-based FC maps. We report results from five experiments to demonstrate the potential advantages of hybrid ICA-seed-based FC methods, comparing results from regressing fMRI data against task-related a priori time courses, with “back-reconstruction” from a group ICA, and with five hybrid ICA-seed-based FC methods: ROI-based with (1 single-voxel, (2 few-voxel, and (3 many-voxel seed; and dual-regression-based with (4 single ICA map and (5 multiple ICA map seed.

  3. Improving language mapping in clinical fMRI through assessment of grammar.

    Science.gov (United States)

    Połczyńska, Monika; Japardi, Kevin; Curtiss, Susan; Moody, Teena; Benjamin, Christopher; Cho, Andrew; Vigil, Celia; Kuhn, Taylor; Jones, Michael; Bookheimer, Susan

    2017-01-01

    Brain surgery in the language dominant hemisphere remains challenging due to unintended post-surgical language deficits, despite using pre-surgical functional magnetic resonance (fMRI) and intraoperative cortical stimulation. Moreover, patients are often recommended not to undergo surgery if the accompanying risk to language appears to be too high. While standard fMRI language mapping protocols may have relatively good predictive value at the group level, they remain sub-optimal on an individual level. The standard tests used typically assess lexico-semantic aspects of language, and they do not accurately reflect the complexity of language either in comprehension or production at the sentence level. Among patients who had left hemisphere language dominance we assessed which tests are best at activating language areas in the brain. We compared grammar tests (items testing word order in actives and passives, wh -subject and object questions, relativized subject and object clauses and past tense marking) with standard tests (object naming, auditory and visual responsive naming), using pre-operative fMRI. Twenty-five surgical candidates (13 females) participated in this study. Sixteen patients presented with a brain tumor, and nine with epilepsy. All participants underwent two pre-operative fMRI protocols: one including CYCLE-N grammar tests (items testing word order in actives and passives, wh-subject and object questions, relativized subject and object clauses and past tense marking); and a second one with standard fMRI tests (object naming, auditory and visual responsive naming). fMRI activations during performance in both protocols were compared at the group level, as well as in individual candidates. The grammar tests generated more volume of activation in the left hemisphere (left/right angular gyrus, right anterior/posterior superior temporal gyrus) and identified additional language regions not shown by the standard tests (e.g., left anterior

  4. MRI in Optic Neuritis: Structure, Function, Interactions

    DEFF Research Database (Denmark)

    Fuglø, Dan

    2011-01-01

    resonance imaging (MRI), and the visual evoked potential (VEP) continues to show a delayed P100 indicating persistent demyelination. The explanation for this apparent discrepancy between structure and function could be due to either a redundancy in the visual pathways so that some degree of signal loss...... will have very few or no clinical symptoms, or it could be due to compensatory mechanisms in the visual pathway or the visual cortex. In order to understand the pathophysiology and recovery processes in ON it is essential to have sensitive methods to asses both structure and function. These methods...... are low. Functional MRI (fMRI) is a non-invasive technique that can measure brain activity with a high spatial resolution. Recently, technical and methodological advancements have made it feasible to record VEPs and fMRI simultaneously and the relationship between averaged VEPs and averaged fMRI signals...

  5. Machine learning algorithm accurately detects fMRI signature of vulnerability to major depression.

    Science.gov (United States)

    Sato, João R; Moll, Jorge; Green, Sophie; Deakin, John F W; Thomaz, Carlos E; Zahn, Roland

    2015-08-30

    Standard functional magnetic resonance imaging (fMRI) analyses cannot assess the potential of a neuroimaging signature as a biomarker to predict individual vulnerability to major depression (MD). Here, we use machine learning for the first time to address this question. Using a recently identified neural signature of guilt-selective functional disconnection, the classification algorithm was able to distinguish remitted MD from control participants with 78.3% accuracy. This demonstrates the high potential of our fMRI signature as a biomarker of MD vulnerability. Crown Copyright © 2015. Published by Elsevier Ireland Ltd. All rights reserved.

  6. Imaging tools to study pharmacology: functional MRI on small rodents

    OpenAIRE

    Elisabeth eJonckers; Disha eShah; Julie eHamaide; Marleen eVerhoye; Annemie eVan Der Linden

    2015-01-01

    Functional Magnetic Resonance Imaging (fMRI) is an excellent tool to study the effect of pharmacological modulations on brain function in a non-invasive and longitudinal manner. We introduce several blood oxygenation level dependent (BOLD) fMRI techniques, including resting state (rsfMRI), stimulus-evoked (st-fMRI), and pharmacological MRI (phMRI). Respectively, these techniques permit the assessment of functional connectivity during rest as well as brain activation triggered by sensory stimu...

  7. Regional homogeneity changes in prelingually deafened patients: a resting-state fMRI study

    Science.gov (United States)

    Li, Wenjing; He, Huiguang; Xian, Junfang; Lv, Bin; Li, Meng; Li, Yong; Liu, Zhaohui; Wang, Zhenchang

    2010-03-01

    Resting-state functional magnetic resonance imaging (fMRI) is a technique that measures the intrinsic function of brain and has some advantages over task-induced fMRI. Regional homogeneity (ReHo) assesses the similarity of the time series of a given voxel with its nearest neighbors on a voxel-by-voxel basis, which reflects the temporal homogeneity of the regional BOLD signal. In the present study, we used the resting state fMRI data to investigate the ReHo changes of the whole brain in the prelingually deafened patients relative to normal controls. 18 deaf patients and 22 healthy subjects were scanned. Kendall's coefficient of concordance (KCC) was calculated to measure the degree of regional coherence of fMRI time courses. We found that regional coherence significantly decreased in the left frontal lobe, bilateral temporal lobes and right thalamus, and increased in the postcentral gyrus, cingulate gyrus, left temporal lobe, left thalamus and cerebellum in deaf patients compared with controls. These results show that the prelingually deafened patients have higher degree of regional coherence in the paleocortex, and lower degree in neocortex. Since neocortex plays an important role in the development of auditory, these evidences may suggest that the deaf persons reorganize the paleocortex to offset the loss of auditory.

  8. A f-MRI study on memory function in normal subjects and patients with partial epilepsies

    International Nuclear Information System (INIS)

    Kamoda, Sachiko

    2004-01-01

    To investigate cerebral regions concerning a memory function and presence of memory lateralization, activated areas and the difference between the right and left hemisphere in functional magnetic resonance imaging (f-MRI) during verbal and visual memory tasks were examined in normal subjects and, as its clinical application, in patients with partial epilepsies. Subjects were 39 normal adult subjects and 10 adult patients. Of the 39 normal subjects, 30 were right-handed and 9 were left-handed. Further, of the 10 patients, 9 were right-handed and one was left-handed, and 7, 2 and 1 had temporal lobe, frontal lobe and undetermined partial epilepsies, respectively. Following the three type of memory task were designed; verbal memory tasks consisting of covert and overt recall tests of 10 words given auditory and visual memory task of covert recall tasks of 6 figures given visually. Activated cerebral areas were imaged with f-MRI using 1.5 tesla Magnetom Vision taken repeatedly during these tasks and neutral condition. Most of the 30 right-handed normal subjects showed activated areas over the left hemisphere specifically on the anterior cingulate, superior, middle and inferior frontal gyri during the verbal memory tasks of covert recall tests. Left hemisphere dominant activated areas in the precentral gyri were added during the verbal memory tasks of overt recall tests. On the other hand, 4 of the 9 left-handed normal subjects showed the left side-dominantly activated areas in the above-mentioned regions during the verbal memory tasks of covert and overt tests, in common with the right-handed subjects. However, 3 of the 9 left-handed normal subjects had right hemisphere dominant activation during the verbal memory tasks, while none of the 30 right-handed normal subjects showed such right side-dominancy. Further, the bilateral occipital lobes were activated during visual memory tasks. The reproducibility in this activation during these verbal and visual memory tasks

  9. Variational Bayesian Causal Connectivity Analysis for fMRI

    Directory of Open Access Journals (Sweden)

    Martin eLuessi

    2014-05-01

    Full Text Available The ability to accurately estimate effective connectivity among brain regions from neuroimaging data could help answering many open questions in neuroscience. We propose a method which uses causality to obtain a measure of effective connectivity from fMRI data. The method uses a vector autoregressive model for the latent variables describing neuronal activity in combination with a linear observation model based on a convolution with a hemodynamic response function. Due to the employed modeling, it is possible to efficiently estimate all latent variables of the model using a variational Bayesian inference algorithm. The computational efficiency of the method enables us to apply it to large scale problems with high sampling rates and several hundred regions of interest. We use a comprehensive empirical evaluation with synthetic and real fMRI data to evaluate the performance of our method under various conditions.

  10. Presurgical brain mapping of the language network in patients with brain tumors using resting-state fMRI: Comparison with task fMRI.

    Science.gov (United States)

    Sair, Haris I; Yahyavi-Firouz-Abadi, Noushin; Calhoun, Vince D; Airan, Raag D; Agarwal, Shruti; Intrapiromkul, Jarunee; Choe, Ann S; Gujar, Sachin K; Caffo, Brian; Lindquist, Martin A; Pillai, Jay J

    2016-03-01

    To compare language networks derived from resting-state fMRI (rs-fMRI) with task-fMRI in patients with brain tumors and investigate variables that affect rs-fMRI vs task-fMRI concordance. Independent component analysis (ICA) of rs-fMRI was performed with 20, 30, 40, and 50 target components (ICA20 to ICA50) and language networks identified for patients presenting for presurgical fMRI mapping between 1/1/2009 and 7/1/2015. 49 patients were analyzed fulfilling criteria for presence of brain tumors, no prior brain surgery, and adequate task-fMRI performance. Rs-vs-task-fMRI concordance was measured using Dice coefficients across varying fMRI thresholds before and after noise removal. Multi-thresholded Dice coefficient volume under the surface (DiceVUS) and maximum Dice coefficient (MaxDice) were calculated. One-way Analysis of Variance (ANOVA) was performed to determine significance of DiceVUS and MaxDice between the four ICA order groups. Age, Sex, Handedness, Tumor Side, Tumor Size, WHO Grade, number of scrubbed volumes, image intensity root mean square (iRMS), and mean framewise displacement (FD) were used as predictors for VUS in a linear regression. Artificial elevation of rs-fMRI vs task-fMRI concordance is seen at low thresholds due to noise. Noise-removed group-mean DiceVUS and MaxDice improved as ICA order increased, however ANOVA demonstrated no statistically significant difference between the four groups. Linear regression demonstrated an association between iRMS and DiceVUS for ICA30-50, and iRMS and MaxDice for ICA50. Overall there is moderate group level rs-vs-task fMRI language network concordance, however substantial subject-level variability exists; iRMS may be used to determine reliability of rs-fMRI derived language networks. © 2015 Wiley Periodicals, Inc.

  11. Phase-synchronization-based parcellation of resting state fMRI signals reveals topographically organized clusters in early visual cortex

    NARCIS (Netherlands)

    Gravel, Nicolás G; Harvey, Ben M; Renken, Remco K; Dumoulin, Serge O; Cornelissen, Frans W

    2018-01-01

    Resting-state fMRI is widely used to study brain function and connectivity. However, interpreting patterns of resting state (RS) fMRI activity remains challenging as they may arise from different neuronal mechanisms than those triggered by exogenous events. Currently, this limits the use of RS-fMRI

  12. Multiple "buy buttons" in the brain: Forecasting chocolate sales at point-of-sale based on functional brain activation using fMRI.

    Science.gov (United States)

    Kühn, Simone; Strelow, Enrique; Gallinat, Jürgen

    2016-08-01

    We set out to forecast consumer behaviour in a supermarket based on functional magnetic resonance imaging (fMRI). Data was collected while participants viewed six chocolate bar communications and product pictures before and after each communication. Then self-reports liking judgement were collected. fMRI data was extracted from a priori selected brain regions: nucleus accumbens, medial orbitofrontal cortex, amygdala, hippocampus, inferior frontal gyrus, dorsomedial prefrontal cortex assumed to contribute positively and dorsolateral prefrontal cortex and insula were hypothesized to contribute negatively to sales. The resulting values were rank ordered. After our fMRI-based forecast an instore test was conducted in a supermarket on n=63.617 shoppers. Changes in sales were best forecasted by fMRI signal during communication viewing, second best by a comparison of brain signal during product viewing before and after communication and least by explicit liking judgements. The results demonstrate the feasibility of applying neuroimaging methods in a relatively small sample to correctly forecast sales changes at point-of-sale. Copyright © 2016. Published by Elsevier Inc.

  13. Fully automated processing of fMRI data in SPM: from MRI scanner to PACS.

    Science.gov (United States)

    Maldjian, Joseph A; Baer, Aaron H; Kraft, Robert A; Laurienti, Paul J; Burdette, Jonathan H

    2009-01-01

    Here we describe the Wake Forest University Pipeline, a fully automated method for the processing of fMRI data using SPM. The method includes fully automated data transfer and archiving from the point of acquisition, real-time batch script generation, distributed grid processing, interface to SPM in MATLAB, error recovery and data provenance, DICOM conversion and PACS insertion. It has been used for automated processing of fMRI experiments, as well as for the clinical implementation of fMRI and spin-tag perfusion imaging. The pipeline requires no manual intervention, and can be extended to any studies requiring offline processing.

  14. The impact of fMRI on multimodal navigation in surgery of cerebral lesions: four years clinical experience

    International Nuclear Information System (INIS)

    Wurm, Gabriele; Schnizer, Mathilde; Fellner, Claudia

    2008-01-01

    Neuronavigation with display of intraoperative structures, instrument locations, orientation and relationships to nearby structures can increase anatomic precision while enhancing the surgeon's confidence and his/her perception of safety. Combination of neuronavigation with functional imaging provides multimodal guidance for surgery of cerebral lesions. We evaluated the impact of functional MRI (fMRI) on surgical decision making and outcome. A neuronavigational device (StealthStation (tm), Medtronic Inc.) was used as platform to merge fMRI data with anatomic images, and to implement intraoperative multimodal guidance. In a 52-month period, where 977 surgical procedures were performed with the aid of neuronavigation, 88 patients underwent image-guided procedures using multimodal guidance. Patient, surgical and outcome data of this series was prospectively collected. Evaluation of 88 procedures on cerebral lesions in complex regions where fMRI data were integrated using the navigation system demonstrated that the additional information was presented in a user-friendly way. Computer assisted fMRI integration was found to be especially helpful in planning the best approach, in assessing alternative approaches, and in defining the extent of the surgical exposure. Furthermore, the surgeons found it more effective to interpret fMRI information when shown in a navigation system as compared to the traditional display on a light board or monitor. Multimodal navigation enhanced by fMRI was judged useful for optimization of surgery of cerebral lesions, especially in and around eloquent regions by experienced neurosurgeons. (orig.)

  15. Resting-state fMRI study of patients with fragile X syndrome

    Science.gov (United States)

    Isanova, E.; Petrovskiy, E.; Savelov, A.; Yudkin, D.; Tulupov, A.

    2017-08-01

    The study aimed to assess the neural activity of different brain regions in patients with fragile X syndrome (FXS) and the healthy volunteers by resting-state functional magnetic resonance imaging (fMRI) on a 1.5 T MRI Achieva scanner (Philips). Results: The fMRI study showed a DMN of brain function in patients with FXS, as well as in the healthy volunteers. Furthermore, it was found that a default mode network of the brain in patients with FXS and healthy volunteers does not have statistically significant differences (p>0.05), which may indicate that the basal activity of neurons in patients with FXS is not reduced. In addition, we have found a significant (pright inferior parietal and right angular gyrus in the resting state in patients with FXS. Conclusion: New data of functional status of the brain in patients with FXS were received. The significant increase in the resting state functional connectivity within the right inferior parietal and right angular gyrus (p<0.001) in patients with FXS was found.

  16. Modeling the hemodynamic response in fMRI using smooth FIR filters

    DEFF Research Database (Denmark)

    Goutte, Cyril; Nielsen, Finn Årup; Hansen, Lars Kai

    2000-01-01

    Modeling the hemodynamic response in functional magnetic resonance (fMRI) experiments is an important aspect of the analysis of functional neuroimages. This has been done in the past using parametric response function, from a limited family. In this contribution, the authors adopt a semi...

  17. Using fMRI to Investigate Memory in Young Children Born Small for Gestational Age.

    Directory of Open Access Journals (Sweden)

    Henrica M A de Bie

    Full Text Available Intrauterine growth restriction (IUGR can lead to infants being born small for gestational age (SGA. SGA is associated with differences in brain anatomy and impaired cognition. We investigated learning and memory in children born SGA using neuropsychological testing and functional Magnetic Resonance Imaging (fMRI.18 children born appropriate for gestational age (AGA and 34 SGA born children (18 with and 16 without postnatal catch-up growth participated in this study. All children were between 4 and 7 years old. Cognitive functioning was assessed by IQ and memory testing (Digit/Word Span and Location Learning. A newly developed fMRI picture encoding task was completed by all children in order to assess brain regions involved in memory processes.Neuropsychological testing demonstrated that SGA children had IQ's within the normal range but lower than in AGA and poorer performances across measures of memory. Using fMRI, we observed memory related activity in posterior parahippocampal gyrus as well as the hippocampus proper. Additionally, activation was seen bilaterally in the prefrontal gyrus. Children born SGA showed less activation in the left parahippocampal region compared to AGA.This is the first fMRI study demonstrating different brain activation patterns in 4-7 year old children born SGA, suggesting that intrauterine growth restriction continues to affect neural functioning in children later-on.

  18. Using fMRI to Investigate Memory in Young Children Born Small for Gestational Age.

    Science.gov (United States)

    de Bie, Henrica M A; de Ruiter, Michiel B; Ouwendijk, Mieke; Oostrom, Kim J; Wilke, Marko; Boersma, Maria; Veltman, Dick J; Delemarre-van de Waal, Henriette A

    2015-01-01

    Intrauterine growth restriction (IUGR) can lead to infants being born small for gestational age (SGA). SGA is associated with differences in brain anatomy and impaired cognition. We investigated learning and memory in children born SGA using neuropsychological testing and functional Magnetic Resonance Imaging (fMRI). 18 children born appropriate for gestational age (AGA) and 34 SGA born children (18 with and 16 without postnatal catch-up growth) participated in this study. All children were between 4 and 7 years old. Cognitive functioning was assessed by IQ and memory testing (Digit/Word Span and Location Learning). A newly developed fMRI picture encoding task was completed by all children in order to assess brain regions involved in memory processes. Neuropsychological testing demonstrated that SGA children had IQ's within the normal range but lower than in AGA and poorer performances across measures of memory. Using fMRI, we observed memory related activity in posterior parahippocampal gyrus as well as the hippocampus proper. Additionally, activation was seen bilaterally in the prefrontal gyrus. Children born SGA showed less activation in the left parahippocampal region compared to AGA. This is the first fMRI study demonstrating different brain activation patterns in 4-7 year old children born SGA, suggesting that intrauterine growth restriction continues to affect neural functioning in children later-on.

  19. Effect of scanner acoustic background noise on strict resting-state fMRI

    Directory of Open Access Journals (Sweden)

    C. Rondinoni

    2013-04-01

    Full Text Available Functional MRI (fMRI resting-state experiments are aimed at identifying brain networks that support basal brain function. Although most investigators consider a ‘resting-state' fMRI experiment with no specific external stimulation, subjects are unavoidably under heavy acoustic noise produced by the equipment. In the present study, we evaluated the influence of auditory input on the resting-state networks (RSNs. Twenty-two healthy subjects were scanned using two similar echo-planar imaging sequences in the same 3T MRI scanner: a default pulse sequence and a reduced “silent” pulse sequence. Experimental sessions consisted of two consecutive 7-min runs with noise conditions (default or silent counterbalanced across subjects. A self-organizing group independent component analysis was applied to fMRI data in order to recognize the RSNs. The insula, left middle frontal gyrus and right precentral and left inferior parietal lobules showed significant differences in the voxel-wise comparison between RSNs depending on noise condition. In the presence of low-level noise, these areas Granger-cause oscillations in RSNs with cognitive implications (dorsal attention and entorhinal, while during high noise acquisition, these connectivities are reduced or inverted. Applying low noise MR acquisitions in research may allow the detection of subtle differences of the RSNs, with implications in experimental planning for resting-state studies, data analysis, and ergonomic factors.

  20. Effect of scanner acoustic background noise on strict resting-state fMRI.

    Science.gov (United States)

    Rondinoni, C; Amaro, E; Cendes, F; dos Santos, A C; Salmon, C E G

    2013-04-01

    Functional MRI (fMRI) resting-state experiments are aimed at identifying brain networks that support basal brain function. Although most investigators consider a 'resting-state' fMRI experiment with no specific external stimulation, subjects are unavoidably under heavy acoustic noise produced by the equipment. In the present study, we evaluated the influence of auditory input on the resting-state networks (RSNs). Twenty-two healthy subjects were scanned using two similar echo-planar imaging sequences in the same 3T MRI scanner: a default pulse sequence and a reduced "silent" pulse sequence. Experimental sessions consisted of two consecutive 7-min runs with noise conditions (default or silent) counterbalanced across subjects. A self-organizing group independent component analysis was applied to fMRI data in order to recognize the RSNs. The insula, left middle frontal gyrus and right precentral and left inferior parietal lobules showed significant differences in the voxel-wise comparison between RSNs depending on noise condition. In the presence of low-level noise, these areas Granger-cause oscillations in RSNs with cognitive implications (dorsal attention and entorhinal), while during high noise acquisition, these connectivities are reduced or inverted. Applying low noise MR acquisitions in research may allow the detection of subtle differences of the RSNs, with implications in experimental planning for resting-state studies, data analysis, and ergonomic factors.

  1. On the relationship between instantaneous phase synchrony and correlation-based sliding windows for time-resolved fMRI connectivity analysis.

    Science.gov (United States)

    Pedersen, Mangor; Omidvarnia, Amir; Zalesky, Andrew; Jackson, Graeme D

    2018-06-08

    Correlation-based sliding window analysis (CSWA) is the most commonly used method to estimate time-resolved functional MRI (fMRI) connectivity. However, instantaneous phase synchrony analysis (IPSA) is gaining popularity mainly because it offers single time-point resolution of time-resolved fMRI connectivity. We aim to provide a systematic comparison between these two approaches, on both temporal and topological levels. For this purpose, we used resting-state fMRI data from two separate cohorts with different temporal resolutions (45 healthy subjects from Human Connectome Project fMRI data with repetition time of 0.72 s and 25 healthy subjects from a separate validation fMRI dataset with a repetition time of 3 s). For time-resolved functional connectivity analysis, we calculated tapered CSWA over a wide range of different window lengths that were temporally and topologically compared to IPSA. We found a strong association in connectivity dynamics between IPSA and CSWA when considering the absolute values of CSWA. The association between CSWA and IPSA was stronger for a window length of ∼20 s (shorter than filtered fMRI wavelength) than ∼100 s (longer than filtered fMRI wavelength), irrespective of the sampling rate of the underlying fMRI data. Narrow-band filtering of fMRI data (0.03-0.07 Hz) yielded a stronger relationship between IPSA and CSWA than wider-band (0.01-0.1 Hz). On a topological level, time-averaged IPSA and CSWA nodes were non-linearly correlated for both short (∼20 s) and long (∼100 s) windows, mainly because nodes with strong negative correlations (CSWA) displayed high phase synchrony (IPSA). IPSA and CSWA were anatomically similar in the default mode network, sensory cortex, insula and cerebellum. Our results suggest that IPSA and CSWA provide comparable characterizations of time-resolved fMRI connectivity for appropriately chosen window lengths. Although IPSA requires narrow-band fMRI filtering, we recommend the use of

  2. Assessment of abstract reasoning abilities in alcohol-dependent subjects: an fMRI study

    International Nuclear Information System (INIS)

    Bagga, Deepika; Singh, Namita; Singh, Sadhana; Modi, Shilpi; Kumar, Pawan; Bhattacharya, D.; Garg, Mohan L.; Khushu, Subash

    2014-01-01

    Chronic alcohol abuse has been traditionally associated with impaired cognitive abilities. The deficits are most evident in higher order cognitive functions, such as abstract reasoning, problem solving and visuospatial processing. The present study sought to increase current understanding of the neuropsychological basis of poor abstract reasoning abilities in alcohol-dependent subjects using functional magnetic resonance imaging (fMRI). An abstract reasoning task-based fMRI study was carried out on alcohol-dependent subjects (n = 18) and healthy controls (n = 18) to examine neural activation pattern. The study was carried out using a 3-T whole-body magnetic resonance scanner. Preprocessing and post processing was performed using SPM 8 software. Behavioral data indicated that alcohol-dependent subjects took more time than controls for performing the task but there was no significant difference in their response accuracy. Analysis of the fMRI data indicated that for solving abstract reasoning-based problems, alcohol-dependent subjects showed enhanced right frontoparietal neural activation involving inferior frontal gyrus, post central gyrus, superior parietal lobule, and occipito-temporal gyrus. The extensive activation observed in alcohol dependents as compared to controls suggests that alcohol dependents recruit additional brain areas to meet the behavioral demands for equivalent task performance. The results are consistent with previous fMRI studies suggesting decreased neural efficiency of relevant brain networks or compensatory mechanisms for the execution of task for showing an equivalent performance. (orig.)

  3. Assessment of abstract reasoning abilities in alcohol-dependent subjects: an fMRI study

    Energy Technology Data Exchange (ETDEWEB)

    Bagga, Deepika; Singh, Namita; Singh, Sadhana; Modi, Shilpi; Kumar, Pawan [Institute of Nuclear Medicine and Allied Sciences (INMAS), NMR Research Centre, Delhi (India); Bhattacharya, D. [Base Hospital, Department of Psychiatry, Delhi Cantt (India); Garg, Mohan L. [Panjab University, Department of Biophysics, Chandigarh (India); Khushu, Subash [Institute of Nuclear Medicine and Allied Sciences (INMAS), NMR Research Centre, Delhi (India); INMAS, DRDO, NMR Research Centre, Delhi (India)

    2014-01-15

    Chronic alcohol abuse has been traditionally associated with impaired cognitive abilities. The deficits are most evident in higher order cognitive functions, such as abstract reasoning, problem solving and visuospatial processing. The present study sought to increase current understanding of the neuropsychological basis of poor abstract reasoning abilities in alcohol-dependent subjects using functional magnetic resonance imaging (fMRI). An abstract reasoning task-based fMRI study was carried out on alcohol-dependent subjects (n = 18) and healthy controls (n = 18) to examine neural activation pattern. The study was carried out using a 3-T whole-body magnetic resonance scanner. Preprocessing and post processing was performed using SPM 8 software. Behavioral data indicated that alcohol-dependent subjects took more time than controls for performing the task but there was no significant difference in their response accuracy. Analysis of the fMRI data indicated that for solving abstract reasoning-based problems, alcohol-dependent subjects showed enhanced right frontoparietal neural activation involving inferior frontal gyrus, post central gyrus, superior parietal lobule, and occipito-temporal gyrus. The extensive activation observed in alcohol dependents as compared to controls suggests that alcohol dependents recruit additional brain areas to meet the behavioral demands for equivalent task performance. The results are consistent with previous fMRI studies suggesting decreased neural efficiency of relevant brain networks or compensatory mechanisms for the execution of task for showing an equivalent performance. (orig.)

  4. Revealing the functional neuroanatomy of intrinsic alertness using fMRI: methodological peculiarities.

    Science.gov (United States)

    Clemens, Benjamin; Zvyagintsev, Mikhail; Sack, Alexander T; Sack, Alexander; Heinecke, Armin; Willmes, Klaus; Sturm, Walter

    2011-01-01

    Clinical observations and neuroimaging data revealed a right-hemisphere fronto-parietal-thalamic-brainstem network for intrinsic alertness, and additional left fronto-parietal activity during phasic alertness. The primary objective of this fMRI study was to map the functional neuroanatomy of intrinsic alertness as precisely as possible in healthy participants, using a novel assessment paradigm already employed in clinical settings. Both the paradigm and the experimental design were optimized to specifically assess intrinsic alertness, while at the same time controlling for sensory-motor processing. The present results suggest that the processing of intrinsic alertness is accompanied by increased activity within the brainstem, thalamus, anterior cingulate gyrus, right insula, and right parietal cortex. Additionally, we found increased activation in the left hemisphere around the middle frontal gyrus (BA 9), the insula, the supplementary motor area, and the cerebellum. Our results further suggest that rather minute aspects of the experimental design may induce aspects of phasic alertness, which in turn might lead to additional brain activation in left-frontal areas not normally involved in intrinsic alertness. Accordingly, left BA 9 activation may be related to co-activation of the phasic alertness network due to the switch between rest and task conditions functioning as an external warning cue triggering the phasic alertness network. Furthermore, activation of the intrinsic alertness network during fixation blocks due to enhanced expectancy shortly before the switch to the task block might, when subtracted from the task block, lead to diminished activation in the typical right hemisphere intrinsic alertness network. Thus, we cautiously suggest that--as a methodological artifact--left frontal activations might show up due to phasic alertness involvement and intrinsic alertness activations might be weakened due to contrasting with fixation blocks, when assessing the

  5. A Java-based fMRI processing pipeline evaluation system for assessment of univariate general linear model and multivariate canonical variate analysis-based pipelines.

    Science.gov (United States)

    Zhang, Jing; Liang, Lichen; Anderson, Jon R; Gatewood, Lael; Rottenberg, David A; Strother, Stephen C

    2008-01-01

    As functional magnetic resonance imaging (fMRI) becomes widely used, the demands for evaluation of fMRI processing pipelines and validation of fMRI analysis results is increasing rapidly. The current NPAIRS package, an IDL-based fMRI processing pipeline evaluation framework, lacks system interoperability and the ability to evaluate general linear model (GLM)-based pipelines using prediction metrics. Thus, it can not fully evaluate fMRI analytical software modules such as FSL.FEAT and NPAIRS.GLM. In order to overcome these limitations, a Java-based fMRI processing pipeline evaluation system was developed. It integrated YALE (a machine learning environment) into Fiswidgets (a fMRI software environment) to obtain system interoperability and applied an algorithm to measure GLM prediction accuracy. The results demonstrated that the system can evaluate fMRI processing pipelines with univariate GLM and multivariate canonical variates analysis (CVA)-based models on real fMRI data based on prediction accuracy (classification accuracy) and statistical parametric image (SPI) reproducibility. In addition, a preliminary study was performed where four fMRI processing pipelines with GLM and CVA modules such as FSL.FEAT and NPAIRS.CVA were evaluated with the system. The results indicated that (1) the system can compare different fMRI processing pipelines with heterogeneous models (NPAIRS.GLM, NPAIRS.CVA and FSL.FEAT) and rank their performance by automatic performance scoring, and (2) the rank of pipeline performance is highly dependent on the preprocessing operations. These results suggest that the system will be of value for the comparison, validation, standardization and optimization of functional neuroimaging software packages and fMRI processing pipelines.

  6. Comparison of fMRI paradigms assessing visuospatial processing: Robustness and reproducibility.

    Directory of Open Access Journals (Sweden)

    Verena Schuster

    Full Text Available The development of brain imaging techniques, in particular functional magnetic resonance imaging (fMRI, made it possible to non-invasively study the hemispheric lateralization of cognitive brain functions in large cohorts. Comprehensive models of hemispheric lateralization are, however, still missing and should not only account for the hemispheric specialization of individual brain functions, but also for the interactions among different lateralized cognitive processes (e.g., language and visuospatial processing. This calls for robust and reliable paradigms to study hemispheric lateralization for various cognitive functions. While numerous reliable imaging paradigms have been developed for language, which represents the most prominent left-lateralized brain function, the reliability of imaging paradigms investigating typically right-lateralized brain functions, such as visuospatial processing, has received comparatively less attention. In the present study, we aimed to establish an fMRI paradigm that robustly and reliably identifies right-hemispheric activation evoked by visuospatial processing in individual subjects. In a first study, we therefore compared three frequently used paradigms for assessing visuospatial processing and evaluated their utility to robustly detect right-lateralized brain activity on a single-subject level. In a second study, we then assessed the test-retest reliability of the so-called Landmark task-the paradigm that yielded the most robust results in study 1. At the single-voxel level, we found poor reliability of the brain activation underlying visuospatial attention. This suggests that poor signal-to-noise ratios can become a limiting factor for test-retest reliability. This represents a common detriment of fMRI paradigms investigating visuospatial attention in general and therefore highlights the need for careful considerations of both the possibilities and limitations of the respective fMRI paradigm-in particular

  7. Sparse dictionary learning of resting state fMRI networks.

    Science.gov (United States)

    Eavani, Harini; Filipovych, Roman; Davatzikos, Christos; Satterthwaite, Theodore D; Gur, Raquel E; Gur, Ruben C

    2012-07-02

    Research in resting state fMRI (rsfMRI) has revealed the presence of stable, anti-correlated functional subnetworks in the brain. Task-positive networks are active during a cognitive process and are anti-correlated with task-negative networks, which are active during rest. In this paper, based on the assumption that the structure of the resting state functional brain connectivity is sparse, we utilize sparse dictionary modeling to identify distinct functional sub-networks. We propose two ways of formulating the sparse functional network learning problem that characterize the underlying functional connectivity from different perspectives. Our results show that the whole-brain functional connectivity can be concisely represented with highly modular, overlapping task-positive/negative pairs of sub-networks.

  8. Convergence of EEG and fMRI measures of reward anticipation.

    Science.gov (United States)

    Gorka, Stephanie M; Phan, K Luan; Shankman, Stewart A

    2015-12-01

    Deficits in reward anticipation are putative mechanisms for multiple psychopathologies. Research indicates that these deficits are characterized by reduced left (relative to right) frontal electroencephalogram (EEG) activity and blood oxygenation level-dependent (BOLD) signal abnormalities in mesolimbic and prefrontal neural regions during reward anticipation. Although it is often assumed that these two measures capture similar mechanisms, no study to our knowledge has directly examined the convergence between frontal EEG alpha asymmetry and functional magnetic resonance imaging (fMRI) during reward anticipation in the same sample. Therefore, the aim of the current study was to investigate if and where in the brain frontal EEG alpha asymmetry and fMRI measures were correlated in a sample of 40 adults. All participants completed two analogous reward anticipation tasks--once during EEG data collection and the other during fMRI data collection. Results indicated that the two measures do converge and that during reward anticipation, increased relative left frontal activity is associated with increased left anterior cingulate cortex (ACC)/medial prefrontal cortex (mPFC) and left orbitofrontal cortex (OFC) activation. This suggests that the two measures may similarly capture PFC functioning, which is noteworthy given the role of these regions in reward processing and the pathophysiology of disorders such as depression and schizophrenia. Copyright © 2015 Elsevier B.V. All rights reserved.

  9. Functional MRI experiments : acquisition, analysis and interpretation of data

    NARCIS (Netherlands)

    Ramsey, NF; Hoogduin, H; Jansma, JM

    2002-01-01

    Functional MRI is widely used to address basic and clinical neuroscience questions. In the key domains of fMRI experiments, i.e. acquisition, processing and analysis, and interpretation of data, developments are ongoing. The main issues are sensitivity for changes in fMRI signal that are associated

  10. Self-regulation of primary motor cortex activity with motor imagery induces functional connectivity modulation: A real-time fMRI neurofeedback study.

    Science.gov (United States)

    Makary, Meena M; Seulgi, Eun; Kyungmo Park

    2017-07-01

    Recent developments in data acquisition of functional magnetic resonance imaging (fMRI) have led to rapid preprocessing and analysis of brain activity in a quasireal-time basis, what so called real-time fMRI neurofeedback (rtfMRI-NFB). This information is fed back to subjects allowing them to gain a voluntary control over their own region-specific brain activity. Forty-one healthy participants were randomized into an experimental (NFB) group, who received a feedback directly proportional to their brain activity from the primary motor cortex (M1), and a control (CTRL) group who received a sham feedback. The M1 ROI was functionally localized during motor execution and imagery tasks. A resting-state functional run was performed before and after the neurofeedback training to investigate the default mode network (DMN) modulation after training. The NFB group revealed increased DMN functional connectivity after training to the cortical and subcortical sensory/motor areas (M1/S1 and caudate nucleus, respectively), which may be associated with sensorimotor processing of learning in the resting state. These results show that motor imagery training through rtfMRI-NFB could modulate the DMN functional connectivity to motor-related areas, suggesting that this modulation potentially subserved the establishment of motor learning in the NFB group.

  11. fMRI of the motor speech center using EPI

    International Nuclear Information System (INIS)

    Yu, In Kyu; Chang, Kee Hyun; Song, In Chan; Kim, Hong Dae; Seong, Su Ok; Jang, Hyun Jung; Han, Moon Hee; Lee, Sang Kun

    1998-01-01

    The purpose of this study is to evaluate the feasibility of functional MR imaging (fMRI) using the echo planar imaging (EPI) technique to map the motor speech center and to provide the basic data for motor speech fMRI during internal word generations. This study involved ten young, healthy, right-handed volunteers (M:F=8:2; age: 21-27); a 1.5T whole body scanner with multislice EPI was used. Brain activation was mapped using gradient echo single shot EPI (TR/TE of 3000/40, slice numbers 6, slice thicknesses mm, no interslice gap, matrix numbers 128 x 128, and FOV 30 x 30). The paradigm consisted of a series of alternating rest and activation tasks, repeated eight times. During the rest task, each of ten Korean nouns composed of two to four syllables was shown continuously every 3 seconds. The subjects were required to see the words but not to generate speech, whereas during the activation task, they were asked to internally generate as many words as possible from each of ten non-concrete one-syllabled Korean letters shown on the screen every 3 seconds. During an eight-minute period, a total of 960 axial images were acquired in each subject. Data were analyzed using the Z-score (p<0.05), and following color processing, the activated signals were overlapped on T1-weighted images. The location of the activated area, mean activated signal intensity were evaluated. The results of this study indicate that in most subjects, fMRI using EPI can effectively map the motor speech center. The data obtained may be useful for the clinical application of fMRI. (author). 34 refs., 3 tabs., 5 figs

  12. Functional MRI in pre-surgical planning: case study and cautionary ...

    African Journals Online (AJOL)

    Background. Since its inception almost 20 years ago, functional magnetic resonance imaging (fMRI) has greatly advanced our knowledge of human brain function. Although the clinical applications of fMRI are still limited, there have recently been encouraging advances for its use in pre-operative functional cortical mapping ...

  13. Function-specific and Enhanced Brain Structural Connectivity Mapping via Joint Modeling of Diffusion and Functional MRI.

    Science.gov (United States)

    Chu, Shu-Hsien; Parhi, Keshab K; Lenglet, Christophe

    2018-03-16

    A joint structural-functional brain network model is presented, which enables the discovery of function-specific brain circuits, and recovers structural connections that are under-estimated by diffusion MRI (dMRI). Incorporating information from functional MRI (fMRI) into diffusion MRI to estimate brain circuits is a challenging task. Usually, seed regions for tractography are selected from fMRI activation maps to extract the white matter pathways of interest. The proposed method jointly analyzes whole brain dMRI and fMRI data, allowing the estimation of complete function-specific structural networks instead of interactively investigating the connectivity of individual cortical/sub-cortical areas. Additionally, tractography techniques are prone to limitations, which can result in erroneous pathways. The proposed framework explicitly models the interactions between structural and functional connectivity measures thereby improving anatomical circuit estimation. Results on Human Connectome Project (HCP) data demonstrate the benefits of the approach by successfully identifying function-specific anatomical circuits, such as the language and resting-state networks. In contrast to correlation-based or independent component analysis (ICA) functional connectivity mapping, detailed anatomical connectivity patterns are revealed for each functional module. Results on a phantom (Fibercup) also indicate improvements in structural connectivity mapping by rejecting false-positive connections with insufficient support from fMRI, and enhancing under-estimated connectivity with strong functional correlation.

  14. Brain correlates of aesthetic expertise: A parametric fMRI study

    DEFF Research Database (Denmark)

    Kirk, Ulrich; Skov, Martin; Christensen, Mark Schram

    2009-01-01

    Several studies have demonstrated that acquired expertise influences aesthetic judgments. In this paradigm we used functional magnetic resonance imaging (fMRI) to study aesthetic judgments of visually presented architectural stimuli and control-stimuli (faces) for a group of architects and a grou...

  15. Functional connectivity analysis of fMRI data using parameterized regions-of-interest.

    NARCIS (Netherlands)

    Weeda, W.D.; Waldorp, L.J.; Grasman, R.P.P.P.; van Gaal, S.; Huizenga, H.M.

    2011-01-01

    Connectivity analysis of fMRI data requires correct specification of regions-of-interest (ROIs). Selection of ROIs based on outcomes of a GLM analysis may be hindered by conservativeness of the multiple comparison correction, while selection based on brain anatomy may be biased due to inconsistent

  16. Effect of fMRI acoustic noise on non-auditory working memory task: comparison between continuous and pulsed sound emitting EPI.

    Science.gov (United States)

    Haller, Sven; Bartsch, Andreas J; Radue, Ernst W; Klarhöfer, Markus; Seifritz, Erich; Scheffler, Klaus

    2005-11-01

    Conventional blood oxygenation level-dependent (BOLD) based functional magnetic resonance imaging (fMRI) is accompanied by substantial acoustic gradient noise. This noise can influence the performance as well as neuronal activations. Conventional fMRI typically has a pulsed noise component, which is a particularly efficient auditory stimulus. We investigated whether the elimination of this pulsed noise component in a recent modification of continuous-sound fMRI modifies neuronal activations in a cognitively demanding non-auditory working memory task. Sixteen normal subjects performed a letter variant n-back task. Brain activity and psychomotor performance was examined during fMRI with continuous-sound fMRI and conventional fMRI. We found greater BOLD responses in bilateral medial frontal gyrus, left middle frontal gyrus, left middle temporal gyrus, left hippocampus, right superior frontal gyrus, right precuneus and right cingulate gyrus with continuous-sound compared to conventional fMRI. Conversely, BOLD responses were greater in bilateral cingulate gyrus, left middle and superior frontal gyrus and right lingual gyrus with conventional compared to continuous-sound fMRI. There were no differences in psychomotor performance between both scanning protocols. Although behavioral performance was not affected, acoustic gradient noise interferes with neuronal activations in non-auditory cognitive tasks and represents a putative systematic confound.

  17. Characterization of functional brain activity and connectivity using EEG and fMRI in patients with sickle cell disease.

    Science.gov (United States)

    Case, Michelle; Zhang, Huishi; Mundahl, John; Datta, Yvonne; Nelson, Stephen; Gupta, Kalpna; He, Bin

    2017-01-01

    Sickle cell disease (SCD) is a red blood cell disorder that causes many complications including life-long pain. Treatment of pain remains challenging due to a poor understanding of the mechanisms and limitations to characterize and quantify pain. In the present study, we examined simultaneously recording functional MRI (fMRI) and electroencephalogram (EEG) to better understand neural connectivity as a consequence of chronic pain in SCD patients. We performed independent component analysis and seed-based connectivity on fMRI data. Spontaneous power and microstate analysis was performed on EEG-fMRI data. ICA analysis showed that patients lacked activity in the default mode network (DMN) and executive control network compared to controls. EEG-fMRI data revealed that the insula cortex's role in salience increases with age in patients. EEG microstate analysis showed patients had increased activity in pain processing regions. The cerebellum in patients showed a stronger connection to the periaqueductal gray matter (involved in pain inhibition), and negative connections to pain processing areas. These results suggest that patients have reduced activity of DMN and increased activity in pain processing regions during rest. The present findings suggest resting state connectivity differences between patients and controls can be used as novel biomarkers of SCD pain.

  18. Nonvisual spatial navigation fMRI lateralizes mesial temporal lobe epilepsy in a patient with congenital blindness.

    Science.gov (United States)

    Toller, Gianina; Adhimoolam, Babu; Grunwald, Thomas; Huppertz, Hans-Jürgen; König, Kristina; Jokeit, Hennric

    2015-01-01

    Nonvisual spatial navigation functional magnetic resonance imaging (fMRI) may help clinicians determine memory lateralization in blind individuals with refractory mesial temporal lobe epilepsy (MTLE). We report on an exceptional case of a congenitally blind woman with late-onset left MTLE undergoing presurgical memory fMRI. To activate mesial temporal structures despite the lack of visual memory, the patient was requested to recall familiar routes using nonvisual multisensory and verbal cues. Our findings demonstrate the diagnostic value of a nonvisual fMRI task to lateralize MTLE despite congenital blindness and may therefore contribute to the risk assessment for postsurgical amnesia in rare cases with refractory MTLE and accompanying congenital blindness.

  19. fMRI activation in relation to sound intensity and loudness

    NARCIS (Netherlands)

    Langers, Dave R. M.; van Dijk, Pirn; Schoemaker, Esther S.; Backes, Walter H.

    2007-01-01

    The aim of this fMRI study was to relate cortical fMRI responses to both physical and perceptual sound level characteristics. Besides subjects with normal hearing, subjects with high-frequency sensorineural hearing loss were included, as distortion of loudness perception is a characteristic of such

  20. Functional MRI in human motor control studies and clinical applications

    International Nuclear Information System (INIS)

    Toma, Keiichiro

    2002-01-01

    Functional magnetic resonance imaging (fMRI) has been a useful tool for the noninvasive mapping of brain function associated with various motor and cognitive tasks. Because fMRI is based on the blood oxygenation level dependent (BOLD) effect, it does not directly record neural activity. With the fMRI technique, distinguishing BOLD signals creased by cortical projection neurons from those created by intracortical neurons appears to be difficult. Two major experimental designs are used in fMRI studies: block designs and event-related designs. Block-designed fMRI presupposes the steady state of regional cerebral blood flow and has been applied to examinations of brain activation caused by tasks requiring sustained or repetitive movements. By contrast, the more recently developed event-related fMRI with time resolution of a few seconds allows the mapping of brain activation associated with a single movement according to the transient aspects of the hemodynamic response. Increasing evidence suggests that multiple motor areas are engaged in a networked manner to execute various motor acts. In order to understand functional brain maps, it is important that one understands sequential and parallel organizations of anatomical connections between multiple motor areas. In fMRI studies of complex motor tasks, elementary parameters such as movement length, force, velocity, acceleration and frequency should be controlled, because inconsistency in those parameters may alter the extent and intensity of motor cortical activation, confounding interpretation of the findings obtained. In addition to initiation of movements, termination of movements plays an important role in the successful achievement of complex movements. Brain areas exclusively related to the termination of movements have been, for the first time, uncovered with an event-related fMRI technique. We propose the application of fMRI to the elucidation of the pathophysiology of movement disorders, particularly dystonia

  1. Functional MRI in human motor control studies and clinical applications

    Energy Technology Data Exchange (ETDEWEB)

    Toma, Keiichiro [Kyoto Univ. (Japan). Graduate School of Medicine; Nakai, Toshiharu [Inst. of Biomedical Research and Innovation, Kobe (Japan)

    2002-07-01

    Functional magnetic resonance imaging (fMRI) has been a useful tool for the noninvasive mapping of brain function associated with various motor and cognitive tasks. Because fMRI is based on the blood oxygenation level dependent (BOLD) effect, it does not directly record neural activity. With the fMRI technique, distinguishing BOLD signals creased by cortical projection neurons from those created by intracortical neurons appears to be difficult. Two major experimental designs are used in fMRI studies: block designs and event-related designs. Block-designed fMRI presupposes the steady state of regional cerebral blood flow and has been applied to examinations of brain activation caused by tasks requiring sustained or repetitive movements. By contrast, the more recently developed event-related fMRI with time resolution of a few seconds allows the mapping of brain activation associated with a single movement according to the transient aspects of the hemodynamic response. Increasing evidence suggests that multiple motor areas are engaged in a networked manner to execute various motor acts. In order to understand functional brain maps, it is important that one understands sequential and parallel organizations of anatomical connections between multiple motor areas. In fMRI studies of complex motor tasks, elementary parameters such as movement length, force, velocity, acceleration and frequency should be controlled, because inconsistency in those parameters may alter the extent and intensity of motor cortical activation, confounding interpretation of the findings obtained. In addition to initiation of movements, termination of movements plays an important role in the successful achievement of complex movements. Brain areas exclusively related to the termination of movements have been, for the first time, uncovered with an event-related fMRI technique. We propose the application of fMRI to the elucidation of the pathophysiology of movement disorders, particularly dystonia

  2. Clinical application of functional MRI for chronic epilepsy

    International Nuclear Information System (INIS)

    Woermann, F.G.; Labudda, K.

    2010-01-01

    Functional magnetic resonance imaging (fMRI) is frequently used in the presurgical diagnostic procedure of epilepsy patients, in particular for lateralization of speech and memory and for localization of the primary motor cortex to delineate the epileptogenic lesion from eloquent brain areas. fMRI is one of the non-invasive procedures in the presurgical diagnostic process, together with medical history, seizure semiology, neurological examination, interictal and ictal EEG, structural MRI, video EEG monitoring and neuropsychology. This diagnostic sequence leads either to the decision for or against elective epilepsy surgery or to the decision to proceed with invasive diagnostic techniques (Wada test, intra-operative or extra-operative cortical stimulation). It is difficult to evaluate the contribution of the fMRI test in isolation to the validity of the entire diagnostic sequence. Complications such as memory loss and aphasia in temporal lobe resections or paresis after frontal lobe resections are rare and rarely of disastrous extent. This further complicates the evaluation of the clinical relevance of fMRI as a predictive tool. In this article studies which investigated the concordance between fMRI and other diagnostic gold standards will be presented as well as the association between presurgical fMRI and postsurgical morbidity. (orig.) [de

  3. On the characterization of single-event related brain activity from functional Magnetic Resonance Imaging (fMRI) measurements

    KAUST Repository

    Khoram, Nafiseh

    2014-08-01

    We propose an efficient numerical technique for calibrating the mathematical model that describes the singleevent related brain response when fMRI measurements are given. This method employs a regularized Newton technique in conjunction with a Kalman filtering procedure. We have applied this method to estimate the biophysiological parameters of the Balloon model that describes the hemodynamic brain responses. Illustrative results obtained with both synthetic and real fMRI measurements are presented. © 2014 IEEE.

  4. Test-retest and between-site reliability in a multicenter fMRI study.

    Science.gov (United States)

    Friedman, Lee; Stern, Hal; Brown, Gregory G; Mathalon, Daniel H; Turner, Jessica; Glover, Gary H; Gollub, Randy L; Lauriello, John; Lim, Kelvin O; Cannon, Tyrone; Greve, Douglas N; Bockholt, Henry Jeremy; Belger, Aysenil; Mueller, Bryon; Doty, Michael J; He, Jianchun; Wells, William; Smyth, Padhraic; Pieper, Steve; Kim, Seyoung; Kubicki, Marek; Vangel, Mark; Potkin, Steven G

    2008-08-01

    In the present report, estimates of test-retest and between-site reliability of fMRI assessments were produced in the context of a multicenter fMRI reliability study (FBIRN Phase 1, www.nbirn.net). Five subjects were scanned on 10 MRI scanners on two occasions. The fMRI task was a simple block design sensorimotor task. The impulse response functions to the stimulation block were derived using an FIR-deconvolution analysis with FMRISTAT. Six functionally-derived ROIs covering the visual, auditory and motor cortices, created from a prior analysis, were used. Two dependent variables were compared: percent signal change and contrast-to-noise-ratio. Reliability was assessed with intraclass correlation coefficients derived from a variance components analysis. Test-retest reliability was high, but initially, between-site reliability was low, indicating a strong contribution from site and site-by-subject variance. However, a number of factors that can markedly improve between-site reliability were uncovered, including increasing the size of the ROIs, adjusting for smoothness differences, and inclusion of additional runs. By employing multiple steps, between-site reliability for 3T scanners was increased by 123%. Dropping one site at a time and assessing reliability can be a useful method of assessing the sensitivity of the results to particular sites. These findings should provide guidance toothers on the best practices for future multicenter studies.

  5. Task-related fMRI in hemiplegic cerebral palsy-A systematic review.

    Science.gov (United States)

    Gaberova, Katerina; Pacheva, Iliyana; Ivanov, Ivan

    2018-04-27

    Functional magnetic resonance imaging (fMRI) is used widely to study reorganization after early brain injuries. Unilateral cerebral palsy (UCP) is an appealing model for studying brain plasticity by fMRI. To summarize the results of task-related fMRI studies in UCP in order to get better understanding of the mechanism of neuroplasticity of the developing brain and its reorganization potential and better translation of this knowledge to clinical practice. A systematic search was conducted on the PubMed database by keywords: "cerebral palsy", "congenital hemiparesis", "unilateral", "Magnetic resonance imaging" , "fMRI", "reorganization", and "plasticity" The exclusion criteria were as follows: case reports; reviews; studies exploring non-UCP patients; and studies with results of rehabilitation. We found 7 articles investigated sensory tasks; 9 studies-motor tasks; 12 studies-speech tasks. Ipsilesional reorganization is dominant in sensory tasks (in 74/77 patients), contralesional-in only 3/77. In motor tasks, bilateral activation is found in 64/83, only contralesional-in 11/83, and only ipsilesional-8/83. Speech perception is bilateral in 35/51, only or dominantly ipsilesional (left-sided) in 8/51, and dominantly contralesional (right-sided) in 8/51. Speech production is only or dominantly contralesional (right-sided) in 88/130, bilateral-26/130, and only or dominantly ipsilesional (left-sided)-in 16/130. The sensory system is the most "rigid" to reorganization probably due to absence of ipsilateral (contralesional) primary somatosensory representation. The motor system is more "flexible" due to ipsilateral (contralesional) motor pathways. The speech perception and production show greater flexibility resulting in more bilateral or contralateral activation. The models of reorganization are variable, depending on the development and function of each neural system and the extent and timing of the damage. The plasticity patterns may guide therapeutic intervention and

  6. Correlated Disruption of Resting-State fMRI, LFP, and Spike Connectivity between Area 3b and S2 following Spinal Cord Injury in Monkeys.

    Science.gov (United States)

    Wu, Ruiqi; Yang, Pai-Feng; Chen, Li Min

    2017-11-15

    This study aims to understand how functional connectivity (FC) between areas 3b and S2 alters following input deprivation and the neuronal basis of disrupted FC of resting-state fMRI signals. We combined submillimeter fMRI with microelectrode recordings to localize the deafferented digit regions in areas 3b and S2 by mapping tactile stimulus-evoked fMRI activations before and after cervical dorsal column lesion in each male monkey. An average afferent disruption of 97% significantly reduced fMRI, local field potential (LFP), and spike responses to stimuli in both areas. Analysis of resting-state fMRI signal correlation, LFP coherence, and spike cross-correlation revealed significantly reduced functional connectivity between deafferented areas 3b and S2. The degrees of reductions in stimulus responsiveness and FC after deafferentation differed across fMRI, LFP, and spiking signals. The reduction of FC was much weaker than that of stimulus-evoked responses. Whereas the largest stimulus-evoked signal drop (∼80%) was observed in LFP signals, the greatest FC reduction was detected in the spiking activity (∼30%). fMRI signals showed mild reductions in stimulus responsiveness (∼25%) and FC (∼20%). The overall deafferentation-induced changes were quite similar in areas 3b and S2 across signals. Here we demonstrated that FC strength between areas 3b and S2 was much weakened by dorsal column lesion, and stimulus response reduction and FC disruption in fMRI covary with those of LFP and spiking signals in deafferented areas 3b and S2. These findings have important implications for fMRI studies aiming to probe FC alterations in pathological conditions involving deafferentation in humans. SIGNIFICANCE STATEMENT By directly comparing fMRI, local field potential, and spike signals in both tactile stimulation and resting states before and after severe disruption of dorsal column afferent, we demonstrated that reduction in fMRI responses to stimuli is accompanied by weakened

  7. Determination of hemispheric dominance with mental rotation using functional transcranial Doppler sonography and FMRI.

    Science.gov (United States)

    Hattemer, Katja; Plate, Annika; Heverhagen, Johannes T; Haag, Anja; Keil, Boris; Klein, Karl Martin; Hermsen, Anke; Oertel, Wolfgang H; Hamer, Hajo M; Rosenow, Felix; Knake, Susanne

    2011-01-01

    the aim of this study was to investigate specific activation patterns and potential gender differences during mental rotation and to investigate whether functional magnetic resonance imaging (fMRI) and functional transcranial Doppler sonography (fTCD) lateralize hemispheric dominance concordantly. regional brain activation and hemispheric dominance during mental rotation (cube perspective test) were investigated in 10 female and 10 male healthy subjects using fMRI and fTCD. significant activation was found in the superior parietal lobe, at the parieto-occipital border, in the middle and superior frontal gyrus bilaterally, and the right inferior frontal gyrus using fMRI. Men showed a stronger lateralization to the right hemisphere during fMRI and a tendency toward stronger right-hemispheric activation during fTCD. Furthermore, more activation in frontal and parieto-occipital regions of the right hemisphere was observed using fMRI. Hemispheric dominance for mental rotation determined by the 2 methods correlated well (P= .008), but did not show concordant results in every single subject. the neural basis of mental rotation depends on a widespread bilateral network. Hemispheric dominance for mental rotation determined by fMRI and fTCD, though correlating well, is not always concordant. Hemispheric lateralization of complex cortical functions such as spatial rotation therefore should be investigated using multimodal imaging approaches, especially if used clinically as a tool for the presurgical evaluation of patients undergoing neurosurgery. Copyright © 2009 by the American Society of Neuroimaging.

  8. Regional homogeneity of fMRI time series in autism spectrum disorders.

    Science.gov (United States)

    Shukla, Dinesh K; Keehn, Brandon; Müller, Ralph Axel

    2010-05-26

    Functional magnetic resonance imaging (fMRI) and functional connectivity MRI (fcMRI) studies of autism spectrum disorders (ASD) have suggested atypical patterns of activation and long-distance connectivity for diverse tasks and networks in ASD. We explored the regional homogeneity (ReHo) approach in ASD, which is analogous to conventional fcMRI, but focuses on local connectivity. FMRI data of 26 children with ASD and 29 typically developing (TD) children were acquired during continuous task performance (visual search). Effects of motion and task were removed and Kendall's coefficient of concordance (KCC) was computed, based on the correlation of the blood oxygen level dependent (BOLD) time series for each voxel and its six nearest neighbors. ReHo was lower in the ASD than the TD group in superior parietal and anterior prefrontal regions. Inverse effects of greater ReHo in the ASD group were detected in lateral and medial temporal regions, predominantly in the right hemisphere. Our findings suggest that ReHo is a sensitive measure for detecting cortical abnormalities in autism. However, impact of methodological factors (such as spatial resolution) on ReHo require further investigation. Published by Elsevier Ireland Ltd.

  9. The functional magnetic resonance imaging (fMRI) procedure as experienced by healthy participants and stroke patients – A pilot study

    International Nuclear Information System (INIS)

    Szameitat, André J; Shen, Shan; Sterr, Annette

    2009-01-01

    An important aspect in functional imaging research employing magnetic resonance imaging (MRI) is how participants perceive the MRI scanning itself. For instance, the knowledge of how (un)comfortable MRI scanning is perceived may help institutional review boards (IRBs) or ethics committees to decide on the approval of a study, or researchers to design their experiments. We provide empirical data from our lab gained from 70 neurologically healthy mainly student subjects and from 22 mainly elderly patients suffering from motor deficits after brain damage. All participants took part in various basic research fMRI studies using a 3T MRI scanner. Directly after the scanning, all participants completed a questionnaire assessing their experience with the fMRI procedure. 87.2% of the healthy subjects and 77.3% of the patients rated the MRI procedure as acceptable to comfortable. In healthy subjects, males found the procedure more comfortable, while the opposite was true for patients. 12.1% of healthy subjects considered scanning durations between 30 and 60 min as too long, while no patient considered their 30 min scanning interval as too long. 93.4% of the healthy subjects would like to participate in an fMRI study again, with a significantly lower rate for the subjects who considered the scanning as too long. Further factors, such as inclusion of a diffusion tensor imaging (DTI) scan, age, and study duration had no effect on the questionnaire responses. Of the few negative comments, the main issues were noise, the restriction to keep still for the whole time, and occasional feelings of dizziness. MRI scanning in the basic research setting is an acceptable procedure for elderly and patient participants as well as young healthy subjects

  10. Feature-Space Clustering for fMRI Meta-Analysis

    DEFF Research Database (Denmark)

    Goutte, Cyril; Hansen, Lars Kai; Liptrot, Mathew G.

    2001-01-01

    MRI sequences containing several hundreds of images, it is sometimes necessary to invoke feature extraction to reduce the dimensionality of the data space. A second interesting application is in the meta-analysis of fMRI experiment, where features are obtained from a possibly large number of single......-voxel analyses. In particular this allows the checking of the differences and agreements between different methods of analysis. Both approaches are illustrated on a fMRI data set involving visual stimulation, and we show that the feature space clustering approach yields nontrivial results and, in particular......, shows interesting differences between individual voxel analysis performed with traditional methods. © 2001 Wiley-Liss, Inc....

  11. Global Functional Connectivity Differences between Sleep-Like States in Urethane Anesthetized Rats Measured by fMRI.

    Directory of Open Access Journals (Sweden)

    Ekaterina Zhurakovskaya

    Full Text Available Sleep is essential for nervous system functioning and sleep disorders are associated with several neurodegenerative diseases. However, the macroscale connectivity changes in brain networking during different sleep states are poorly understood. One of the hindering factors is the difficulty to combine functional connectivity investigation methods with spontaneously sleeping animals, which prevents the use of numerous preclinical animal models. Recent studies, however, have implicated that urethane anesthesia can uniquely induce different sleep-like brain states, resembling rapid eye movement (REM and non-REM (NREM sleep, in rodents. Therefore, the aim of this study was to assess changes in global connectivity and topology between sleep-like states in urethane anesthetized rats, using blood oxygenation level dependent (BOLD functional magnetic resonance imaging. We detected significant changes in corticocortical (increased in NREM-like state and corticothalamic connectivity (increased in REM-like state. Additionally, in graph analysis the modularity, the measure of functional integration in the brain, was higher in NREM-like state than in REM-like state, indicating a decrease in arousal level, as in normal sleep. The fMRI findings were supported by the supplementary electrophysiological measurements. Taken together, our results show that macroscale functional connectivity changes between sleep states can be detected robustly with resting-state fMRI in urethane anesthetized rats. Our findings pave the way for studies in animal models of neurodegenerative diseases where sleep abnormalities are often one of the first markers for the disorder development.

  12. fMRI neurofeedback of amygdala response to aversive stimuli enhances prefrontal-limbic brain connectivity.

    Science.gov (United States)

    Paret, Christian; Ruf, Matthias; Gerchen, Martin Fungisai; Kluetsch, Rosemarie; Demirakca, Traute; Jungkunz, Martin; Bertsch, Katja; Schmahl, Christian; Ende, Gabriele

    2016-01-15

    Down-regulation of the amygdala with real-time fMRI neurofeedback (rtfMRI NF) potentially allows targeting brain circuits of emotion processing and may involve prefrontal-limbic networks underlying effective emotion regulation. Little research has been dedicated to the effect of rtfMRI NF on the functional connectivity of the amygdala and connectivity patterns in amygdala down-regulation with neurofeedback have not been addressed yet. Using psychophysiological interaction analysis of fMRI data, we present evidence that voluntary amygdala down-regulation by rtfMRI NF while viewing aversive pictures was associated with increased connectivity of the right amygdala with the ventromedial prefrontal cortex (vmPFC) in healthy subjects (N=16). In contrast, a control group (N=16) receiving sham feedback did not alter amygdala connectivity (Group×Condition t-contrast: pneurofeedback to influence functional connectivity in key networks of emotion processing and regulation. This may be beneficial for patients suffering from severe emotion dysregulation by improving neural self-regulation. Copyright © 2015 Elsevier Inc. All rights reserved.

  13. Functional magnetic resonance imaging (fMRI) for fetal oxygenation during maternal hypoxia: initial results

    International Nuclear Information System (INIS)

    Wedegaertner, U.; Adam, G.; Tchirikov, M.; Schroeder, H.; Koch, M.

    2002-01-01

    Purpose: To investigate the potential of fMRI to measure changes in fetal tissue oxygenation during acute maternal hypoxia in fetal lambs. Material and Methods: Two ewes carrying singleton fetuses (gestational age 125 and 131 days) underwent MR imaging under inhalation anesthesia. BOLD imaging of the fetal brain, liver and myocardium was performed during acute maternal hypoxia (oxygen replaced by N 2 O). Maternal oxygen saturation and heart rate were monitored by a pulse-oxymeter attached to the maternal tongue. Results: Changes of fetal tissue oxygenation during maternal hypoxia were clearly visible with BOLD MRI. Signal intensity decreases were more distinct in liver and heart (∝40%) from control than in the fetal brain (∝10%). Conclusions: fMRI is a promising diagnostic tool to determine fetal tissue oxygenation and may open new opportunities in monitoring fetal well being in high risk pregnancies complicated by uteroplacentar insufficiency. Different signal changes in liver/heart and brain may reflect a centralization of the fetal blood flow. (orig.) [de

  14. Two-stage decompositions for the analysis of functional connectivity for fMRI with application to Alzheimer’s disease risk

    OpenAIRE

    Caffo, Brian S.; Crainiceanu, Ciprian M.; Verduzco, Guillermo; Joel, Suresh; Mostofsky, Stewart H.; Bassett, Susan Spear; Pekar, James J.

    2010-01-01

    Functional connectivity is the study of correlations in measured neurophysiological signals. Altered functional connectivity has been shown to be associated with a variety of cognitive and memory impairments and dysfunction, including Alzheimer’s disease. In this manuscript we use a two-stage application of the singular value decomposition to obtain data driven population-level measures of functional connectivity in functional magnetic resonance imaging (fMRI). The method is computationally s...

  15. 19F-MRI of stomach and intestine using 50% FTPA emulsion under 2T MRI system

    International Nuclear Information System (INIS)

    Shimizu, Masahiro; Kobayashi, Teturou; Mishima, Hideyuki

    1991-01-01

    1 H-MRI is of clinical value in many lesions, but imaging of gastrointestinal lesions is still difficult by 1 H-MRI. To overcome this weak point of 1 H-MRI, rabbit stomachs were examined by 19 F-MRI using 50% FTPA emulsion. We also examined the stability of 50% FTPA emulsion in the stomach and its absorption from the gastrointestinal tract. We found that 50% FTPA emulsion was very stable at pH 1.5, and only a very small amount was absorbed. A rabbit (weighing 2 kg) was anesthetized, and 100 ml of 50% FTPA emulsion was infused into the stomach by catheter. 19 F-MRI was performed in this rabbit using a 2 T superconducting MRI system designed for human use, and clear pictures of the stomach were obtained. From our results we conclude that 19 F-MRI of the stomach using 50% FTPA emulsion is of practical value. (author)

  16. Cue-Elicited Craving in Heroin Addicts at Different Abstinent Time: An fMRI Pilot Study

    OpenAIRE

    Lou, Mingwu; Wang, Erlei; Shen, Yunxia; Wang, Jiping

    2012-01-01

    Objective: We evaluated the effect of short-term and long-term heroin abstinence on brain responses to heroin-related cues using functional magnetic resonance imaging (fMRI). Methods: Eighteen male heroin addicts following short-term abstinence and 19 male heroin addicts following long-term abstinence underwent fMRI scanning while viewing heroin-related and neutral images. Cue-elicited craving and withdrawal symptoms in the subjects were measured. Results: Following short-term abstinence, gre...

  17. Cognitive dissonance induction in everyday life: An fMRI study.

    Science.gov (United States)

    de Vries, Jan; Byrne, Mark; Kehoe, Elizabeth

    2015-01-01

    This functional magnetic resonance imaging (fMRI) study explored the neural substrates of cognitive dissonance during dissonance "induction." A novel task was developed based on the results of a separate item selection study (n = 125). Items were designed to generate dissonance by prompting participants to reflect on everyday personal experiences that were inconsistent with values they had expressed support for. One experimental condition (dissonance) and three control conditions (justification, consonance, and non-self-related inconsistency) were used for comparison. Items of all four types were presented to each participant (n = 14) in a randomized design. The fMRI analysis used a whole-brain approach focusing on the moments dissonance was induced. Results showed that in comparison with the control conditions the dissonance experience led to higher levels of activation in several brain regions. Specifically dissonance was associated with increased neural activation in key brain regions including the anterior cingulate cortex (ACC), anterior insula, inferior frontal gyrus, and precuneus. This supports current perspectives that emphasize the role of anterior cingulate and insula in dissonance processing. Less extensive activation in the prefrontal cortex than in some previous studies is consistent with this study's emphasis on dissonance induction, rather than reduction. This article also contains a short review and comparison with other fMRI studies of cognitive dissonance.

  18. Short- and long-term reliability of language fMRI.

    Science.gov (United States)

    Nettekoven, Charlotte; Reck, Nicola; Goldbrunner, Roland; Grefkes, Christian; Weiß Lucas, Carolin

    2018-08-01

    When using functional magnetic resonance imaging (fMRI) for mapping important language functions, a high test-retest reliability is mandatory, both in basic scientific research and for clinical applications. We, therefore, systematically tested the short- and long-term reliability of fMRI in a group of healthy subjects using a picture naming task and a sparse-sampling fMRI protocol. We hypothesized that test-retest reliability might be higher for (i) speech-related motor areas than for other language areas and for (ii) the short as compared to the long intersession interval. 16 right-handed subjects (mean age: 29 years) participated in three sessions separated by 2-6 (session 1 and 2, short-term) and 21-34 days (session 1 and 3, long-term). Subjects were asked to perform the same overt picture naming task in each fMRI session (50 black-white images per session). Reliability was tested using the following measures: (i) Euclidean distances (ED) between local activation maxima and Centers of Gravity (CoGs), (ii) overlap volumes and (iii) voxel-wise intraclass correlation coefficients (ICCs). Analyses were performed for three regions of interest which were chosen based on whole-brain group data: primary motor cortex (M1), superior temporal gyrus (STG) and inferior frontal gyrus (IFG). Our results revealed that the activation centers were highly reliable, independent of the time interval, ROI or hemisphere with significantly smaller ED for the local activation maxima (6.45 ± 1.36 mm) as compared to the CoGs (8.03 ± 2.01 mm). In contrast, the extent of activation revealed rather low reliability values with overlaps ranging from 24% (IFG) to 56% (STG). Here, the left hemisphere showed significantly higher overlap volumes than the right hemisphere. Although mean ICCs ranged between poor (ICC0.75) were found for all ROIs. Voxel-wise reliability of the different ROIs was influenced by the intersession interval. Taken together, we could show that, despite of

  19. Cerebral activity mapped by functional MRI

    International Nuclear Information System (INIS)

    Bruening, R.; Danek, A.; Wu, R.H.; Berchtenbreiter, C.; Reiser, M.

    1997-01-01

    Functional magnetic resonance imaging (fMRI) is a method to noninvasively measure the changes in cerebral activation during sensitive, cognitive or motor activity. fMRI detects activity by subtraction of states of activity and rest. During activity the signal is increased presumably due to a decrease of deoxyhemoglobin in the capillary and venous structures. Using a full field visual stimulation by flashlight goggles, a signal increase of 3% was detected in the primary visual cortex (V1). Different sequences and postprocessing algorythms will be discussed. Data from the primary cortical areas suggest a high reproducability of the experiments. Successfull experiments highly depend on cooperation of subjects. Despite success in experiments fMRI still has to be established for clinical purposes. (orig.) [de

  20. An in vivo MRI Template Set for Morphometry, Tissue Segmentation, and fMRI Localization in Rats

    Science.gov (United States)

    Valdés-Hernández, Pedro Antonio; Sumiyoshi, Akira; Nonaka, Hiroi; Haga, Risa; Aubert-Vásquez, Eduardo; Ogawa, Takeshi; Iturria-Medina, Yasser; Riera, Jorge J.; Kawashima, Ryuta

    2011-01-01

    Over the last decade, several papers have focused on the construction of highly detailed mouse high field magnetic resonance image (MRI) templates via non-linear registration to unbiased reference spaces, allowing for a variety of neuroimaging applications such as robust morphometric analyses. However, work in rats has only provided medium field MRI averages based on linear registration to biased spaces with the sole purpose of approximate functional MRI (fMRI) localization. This precludes any morphometric analysis in spite of the need of exploring in detail the neuroanatomical substrates of diseases in a recent advent of rat models. In this paper we present a new in vivo rat T2 MRI template set, comprising average images of both intensity and shape, obtained via non-linear registration. Also, unlike previous rat template sets, we include white and gray matter probabilistic segmentations, expanding its use to those applications demanding prior-based tissue segmentation, e.g., statistical parametric mapping (SPM) voxel-based morphometry. We also provide a preliminary digitalization of latest Paxinos and Watson atlas for anatomical and functional interpretations within the cerebral cortex. We confirmed that, like with previous templates, forepaw and hindpaw fMRI activations can be correctly localized in the expected atlas structure. To exemplify the use of our new MRI template set, were reported the volumes of brain tissues and cortical structures and probed their relationships with ontogenetic development. Other in vivo applications in the near future can be tensor-, deformation-, or voxel-based morphometry, morphological connectivity, and diffusion tensor-based anatomical connectivity. Our template set, freely available through the SPM extension website, could be an important tool for future longitudinal and/or functional extensive preclinical studies. PMID:22275894

  1. An in vivo MRI Template Set for Morphometry, Tissue Segmentation, and fMRI Localization in Rats.

    Science.gov (United States)

    Valdés-Hernández, Pedro Antonio; Sumiyoshi, Akira; Nonaka, Hiroi; Haga, Risa; Aubert-Vásquez, Eduardo; Ogawa, Takeshi; Iturria-Medina, Yasser; Riera, Jorge J; Kawashima, Ryuta

    2011-01-01

    Over the last decade, several papers have focused on the construction of highly detailed mouse high field magnetic resonance image (MRI) templates via non-linear registration to unbiased reference spaces, allowing for a variety of neuroimaging applications such as robust morphometric analyses. However, work in rats has only provided medium field MRI averages based on linear registration to biased spaces with the sole purpose of approximate functional MRI (fMRI) localization. This precludes any morphometric analysis in spite of the need of exploring in detail the neuroanatomical substrates of diseases in a recent advent of rat models. In this paper we present a new in vivo rat T2 MRI template set, comprising average images of both intensity and shape, obtained via non-linear registration. Also, unlike previous rat template sets, we include white and gray matter probabilistic segmentations, expanding its use to those applications demanding prior-based tissue segmentation, e.g., statistical parametric mapping (SPM) voxel-based morphometry. We also provide a preliminary digitalization of latest Paxinos and Watson atlas for anatomical and functional interpretations within the cerebral cortex. We confirmed that, like with previous templates, forepaw and hindpaw fMRI activations can be correctly localized in the expected atlas structure. To exemplify the use of our new MRI template set, were reported the volumes of brain tissues and cortical structures and probed their relationships with ontogenetic development. Other in vivo applications in the near future can be tensor-, deformation-, or voxel-based morphometry, morphological connectivity, and diffusion tensor-based anatomical connectivity. Our template set, freely available through the SPM extension website, could be an important tool for future longitudinal and/or functional extensive preclinical studies.

  2. Modafinil alters intrinsic functional connectivity of the right posterior insula: a pharmacological resting state fMRI study.

    Directory of Open Access Journals (Sweden)

    Nicoletta Cera

    Full Text Available Modafinil is employed for the treatment of narcolepsy and has also been, off-label, used to treat cognitive dysfunction in neuropsychiatric disorders. In a previous study, we have reported that single dose administration of modafinil in healthy young subjects enhances fluid reasoning and affects resting state activity in the Fronto Parietal Control (FPC and Dorsal Attention (DAN networks. No changes were found in the Salience Network (SN, a surprising result as the network is involved in the modulation of emotional and fluid reasoning. The insula is crucial hub of the SN and functionally divided in anterior and posterior subregions.Using a seed-based approach, we have now analyzed effects of modafinil on the functional connectivity (FC of insular subregions.Analysis of FC with resting state fMRI (rs-FMRI revealed increased FC between the right posterior insula and the putamen, the superior frontal gyrus and the anterior cingulate cortex in the modafinil-treated group.Modafinil is considered a putative cognitive enhancer. The rs-fMRI modifications that we have found are consistent with the drug cognitive enhancing properties and indicate subregional targets of action.ClinicalTrials.gov NCT01684306.

  3. Functional MRI: Genesis, State of the art and the Sequel

    International Nuclear Information System (INIS)

    Bharath, Rose Dawn

    2014-01-01

    The last 25 years have seen functional magnetic resonance imaging (fMRI) grow from an interesting experimental imaging technique in the hands of some to a primary investigation of choice in the localization and lateralization of brain function prior to surgery. Developments in the field of computational neurosciences have transformed fMRI analysis from classical subtractive type analysis to dynamic casual modeling, and now to graph theory analysis. This has widened the scope of fMRI, and is therefore finding applications in understanding neural correlates of diseases like autism and Alzheimer's disease, prognostication of diseases like traumatic brain injury, and has the potential to direct therapy. It is unfortunately true that this widened ambit has not received the clinical attention it deserves, probably because fMRI is susceptible to artifacts from skull base and blood products and has reduced sensitivity in patients with vascular malformations, or because a change in medical practice usually lags behind the technological and scientific developments that make it possible. This review focuses on the developmental chronology of fMRI image analysis in the last 25 years with highlights on major milestones like developments in the field of paradigms, analysis methods, resting state fMRI, and functional connectivity. To make the statistical images of brain at work more colorful, the article starts with genesis of fMRI and ends with the hope of a promising bright future. Many inputs for this article are obtained from a series of 103 review articles edited by Bandettini et al., compiling personal experiences of pioneers in this field. Interested readers are encouraged to refer to these for a more complete overview.

  4. Mapping cerebrovascular reactivity using concurrent fMRI and near infrared spectroscopy

    Science.gov (United States)

    Tong, Yunjie; Bergethon, Peter R.; Frederick, Blaise d.

    2011-02-01

    Cerebrovascular reactivity (CVR) reflects the compensatory dilatory capacity of cerebral vasculature to a dilatory stimulus and is an important indicator of brain vascular reserve. fMRI has been proven to be an effective imaging technique to obtain the CVR map when the subjects perform CO2 inhalation or the breath holding task (BH). However, the traditional data analysis inaccurately models the BOLD using a boxcar function with fixed time delay. We propose a novel way to process the fMRI data obtained during a blocked BH by using the simultaneously collected near infrared spectroscopy (NIRS) data as regressor1. In this concurrent NIRS and fMRI study, 6 healthy subjects performed a blocked BH (5 breath holds with 20s durations intermitted by 40s of regular breathing). A NIRS probe of two sources and two detectors separated by 3 cm was placed on the right side of prefrontal area of the subjects. The time course of changes in oxy-hemoglobin (Δ[HbO]) was calculated from NIRS data and shifted in time by various amounts, and resampled to the fMRI acquisition rate. Each shifted time course was used as regressor in FEAT (the analysis tool in FSL). The resulting z-statistic maps were concatenated in time and the maximal value was taken along the time for all the voxels to generate a 3-D CVR map. The new method produces more accurate and thorough CVR maps; moreover, it enables us to produce a comparable baseline cerebral vascular map if applied to resting state (RS) data.

  5. PyMVPA: A python toolbox for multivariate pattern analysis of fMRI data.

    Science.gov (United States)

    Hanke, Michael; Halchenko, Yaroslav O; Sederberg, Per B; Hanson, Stephen José; Haxby, James V; Pollmann, Stefan

    2009-01-01

    Decoding patterns of neural activity onto cognitive states is one of the central goals of functional brain imaging. Standard univariate fMRI analysis methods, which correlate cognitive and perceptual function with the blood oxygenation-level dependent (BOLD) signal, have proven successful in identifying anatomical regions based on signal increases during cognitive and perceptual tasks. Recently, researchers have begun to explore new multivariate techniques that have proven to be more flexible, more reliable, and more sensitive than standard univariate analysis. Drawing on the field of statistical learning theory, these new classifier-based analysis techniques possess explanatory power that could provide new insights into the functional properties of the brain. However, unlike the wealth of software packages for univariate analyses, there are few packages that facilitate multivariate pattern classification analyses of fMRI data. Here we introduce a Python-based, cross-platform, and open-source software toolbox, called PyMVPA, for the application of classifier-based analysis techniques to fMRI datasets. PyMVPA makes use of Python's ability to access libraries written in a large variety of programming languages and computing environments to interface with the wealth of existing machine learning packages. We present the framework in this paper and provide illustrative examples on its usage, features, and programmability.

  6. [fMRI study of the dominant hemisphere for language in patients with brain tumor].

    Science.gov (United States)

    Buklina, S B; Podoprigora, A E; Pronin, I N; Shishkina, L V; Boldyreva, G N; Bondarenko, A A; Fadeeva, L M; Kornienko, V N; Zhukov, V Iu

    2013-01-01

    Paper describes a study of language lateralization of patients with brain tumors, measured by preoperative functional magnetic resonance imaging (fMRI) and comparison results with tumor histology and profile of functional asymmetry. During the study 21 patient underwent fMRI scan. 15 patients had a tumor in the left and 6 in the right hemisphere. Tumors were localized mainly in the frontal, temporal and fronto-temporal regions. Histological diagnosis in 8 cases was malignant Grade IV, in 13 cases--Grade I-III. fMRI study was perfomed on scanner "Signa Exite" with a field strength of 1.5 As speech test reciting the months of the year in reverse order was used. fMRI scan results were compared with the profile of functional asymmetry, which was received with the results of questionnaire Annette and dichotic listening test. Broca's area was found in 7 cases in the left hemisphere, 6 had a tumor Grade I-III. And one patient with glioblastoma had a tumor of the right hemisphere. Broca's area in the right hemisphere was found in 3 patients (2 patients with left sided tumor, and one with right-sided tumor). One patient with left-sided tumor had mild motor aphasia. Bilateral activation in both hemispheres of the brain was observed in 6 patients. All of them had tumor Grade II-III of the left hemisphere. Signs of left-handedness were revealed only in half of these patients. Broca's area was not found in 4 cases. All of them had large malignant tumors Grade IV. One patient couldn't handle program of the research. Results of fMRI scans, questionnaire Annette and dichotic listening test frequently were not the same, which is significant. Bilateral activation in speech-loads may be a reflection of brain plasticity in cases of long-growing tumors. Thus it's important to consider the full range of clinical data in studying the problem of the dominant hemisphere for language.

  7. Combining task-evoked and spontaneous activity to improve pre-operative brain mapping with fMRI

    Science.gov (United States)

    Fox, Michael D.; Qian, Tianyi; Madsen, Joseph R.; Wang, Danhong; Li, Meiling; Ge, Manling; Zuo, Huan-cong; Groppe, David M.; Mehta, Ashesh D.; Hong, Bo; Liu, Hesheng

    2016-01-01

    Noninvasive localization of brain function is used to understand and treat neurological disease, exemplified by pre-operative fMRI mapping prior to neurosurgical intervention. The principal approach for generating these maps relies on brain responses evoked by a task and, despite known limitations, has dominated clinical practice for over 20 years. Recently, pre-operative fMRI mapping based on correlations in spontaneous brain activity has been demonstrated, however this approach has its own limitations and has not seen widespread clinical use. Here we show that spontaneous and task-based mapping can be performed together using the same pre-operative fMRI data, provide complimentary information relevant for functional localization, and can be combined to improve identification of eloquent motor cortex. Accuracy, sensitivity, and specificity of our approach are quantified through comparison with electrical cortical stimulation mapping in eight patients with intractable epilepsy. Broad applicability and reproducibility of our approach is demonstrated through prospective replication in an independent dataset of six patients from a different center. In both cohorts and every individual patient, we see a significant improvement in signal to noise and mapping accuracy independent of threshold, quantified using receiver operating characteristic curves. Collectively, our results suggest that modifying the processing of fMRI data to incorporate both task-based and spontaneous activity significantly improves functional localization in pre-operative patients. Because this method requires no additional scan time or modification to conventional pre-operative data acquisition protocols it could have widespread utility. PMID:26408860

  8. Functional localization in the human brain: Gradient-echo, spin-echo, and arterial spin-labeling fMRI compared with neuronavigated TMS.

    NARCIS (Netherlands)

    Diekhoff, S.; Uludag, K.; Sparing, R.; Tittgemeyer, M.; von Cramon, D.Y.; Grefkes, C.

    2010-01-01

    A spatial mismatch of up to 14 mm between optimal transcranial magnetic stimulation (TMS) site and functional magnetic resonance imaging (fMRI) signal has consistently been reported for the primary motor cortex. The underlying cause might be the effect of magnetic susceptibility around large

  9. Basis Expansion Approaches for Regularized Sequential Dictionary Learning Algorithms With Enforced Sparsity for fMRI Data Analysis.

    Science.gov (United States)

    Seghouane, Abd-Krim; Iqbal, Asif

    2017-09-01

    Sequential dictionary learning algorithms have been successfully applied to functional magnetic resonance imaging (fMRI) data analysis. fMRI data sets are, however, structured data matrices with the notions of temporal smoothness in the column direction. This prior information, which can be converted into a constraint of smoothness on the learned dictionary atoms, has seldomly been included in classical dictionary learning algorithms when applied to fMRI data analysis. In this paper, we tackle this problem by proposing two new sequential dictionary learning algorithms dedicated to fMRI data analysis by accounting for this prior information. These algorithms differ from the existing ones in their dictionary update stage. The steps of this stage are derived as a variant of the power method for computing the SVD. The proposed algorithms generate regularized dictionary atoms via the solution of a left regularized rank-one matrix approximation problem where temporal smoothness is enforced via regularization through basis expansion and sparse basis expansion in the dictionary update stage. Applications on synthetic data experiments and real fMRI data sets illustrating the performance of the proposed algorithms are provided.

  10. Functional MRI language mapping in pre-surgical epilepsy patients ...

    African Journals Online (AJOL)

    Background. Functional magnetic resonance imaging (fMRI) is commonly applied to study the neural substrates of language in clinical research and for neurosurgical planning. fMRI language mapping is used to assess language lateralisation, or determine hemispheric dominance, and to localise regions of the brain ...

  11. BROCCOLI: Software for Fast fMRI Analysis on Many-Core CPUs and GPUs

    Directory of Open Access Journals (Sweden)

    Anders eEklund

    2014-03-01

    Full Text Available Analysis of functional magnetic resonance imaging (fMRI data is becoming ever more computationally demanding as temporal and spatial resolutions improve, and large, publicly available data sets proliferate. Moreover, methodological improvements in the neuroimaging pipeline, such as non-linear spatial normalization, non-parametric permutation tests and Bayesian Markov Chain Monte Carlo approaches, can dramatically increase the computational burden. Despite these challenges, there do not yet exist any fMRI software packages which leverage inexpensive and powerful graphics processing units (GPUs to perform these analyses. Here, we therefore present BROCCOLI, a free software package written in OpenCL (Open Computing Language that can be used for parallel analysis of fMRI data on a large variety of hardware configurations. BROCCOLI has, for example, been tested with an Intel CPU, an Nvidia GPU and an AMD GPU. These tests show that parallel processing of fMRI data can lead to significantly faster analysis pipelines. This speedup can be achieved on relatively standard hardware, but further, dramatic speed improvements require only a modest investment in GPU hardware. BROCCOLI (running on a GPU can perform non-linear spatial normalization to a 1 mm3 brain template in 4-6 seconds, and run a second level permutation test with 10,000 permutations in about a minute. These non-parametric tests are generally more robust than their parametric counterparts, and can also enable more sophisticated analyses by estimating complicated null distributions. Additionally, BROCCOLI includes support for Bayesian first-level fMRI analysis using a Gibbs sampler. The new software is freely available under GNU GPL3 and can be downloaded from github (https://github.com/wanderine/BROCCOLI/.

  12. Brain Correlates of Aesthetic Expertise: A Parametric fMRI Study

    Science.gov (United States)

    Kirk, Ulrich; Skov, Martin; Christensen, Mark Schram; Nygaard, Niels

    2009-01-01

    Several studies have demonstrated that acquired expertise influences aesthetic judgments. In this paradigm we used functional magnetic resonance imaging (fMRI) to study aesthetic judgments of visually presented architectural stimuli and control-stimuli (faces) for a group of architects and a group of non-architects. This design allowed us to test…

  13. Intersession reliability of fMRI activation for heat pain and motor tasks.

    Science.gov (United States)

    Quiton, Raimi L; Keaser, Michael L; Zhuo, Jiachen; Gullapalli, Rao P; Greenspan, Joel D

    2014-01-01

    As the practice of conducting longitudinal fMRI studies to assess mechanisms of pain-reducing interventions becomes more common, there is a great need to assess the test-retest reliability of the pain-related BOLD fMRI signal across repeated sessions. This study quantitatively evaluated the reliability of heat pain-related BOLD fMRI brain responses in healthy volunteers across 3 sessions conducted on separate days using two measures: (1) intraclass correlation coefficients (ICC) calculated based on signal amplitude and (2) spatial overlap. The ICC analysis of pain-related BOLD fMRI responses showed fair-to-moderate intersession reliability in brain areas regarded as part of the cortical pain network. Areas with the highest intersession reliability based on the ICC analysis included the anterior midcingulate cortex, anterior insula, and second somatosensory cortex. Areas with the lowest intersession reliability based on the ICC analysis also showed low spatial reliability; these regions included pregenual anterior cingulate cortex, primary somatosensory cortex, and posterior insula. Thus, this study found regional differences in pain-related BOLD fMRI response reliability, which may provide useful information to guide longitudinal pain studies. A simple motor task (finger-thumb opposition) was performed by the same subjects in the same sessions as the painful heat stimuli were delivered. Intersession reliability of fMRI activation in cortical motor areas was comparable to previously published findings for both spatial overlap and ICC measures, providing support for the validity of the analytical approach used to assess intersession reliability of pain-related fMRI activation. A secondary finding of this study is that the use of standard ICC alone as a measure of reliability may not be sufficient, as the underlying variance structure of an fMRI dataset can result in inappropriately high ICC values; a method to eliminate these false positive results was used in this

  14. Intersession reliability of fMRI activation for heat pain and motor tasks

    Science.gov (United States)

    Quiton, Raimi L.; Keaser, Michael L.; Zhuo, Jiachen; Gullapalli, Rao P.; Greenspan, Joel D.

    2014-01-01

    As the practice of conducting longitudinal fMRI studies to assess mechanisms of pain-reducing interventions becomes more common, there is a great need to assess the test–retest reliability of the pain-related BOLD fMRI signal across repeated sessions. This study quantitatively evaluated the reliability of heat pain-related BOLD fMRI brain responses in healthy volunteers across 3 sessions conducted on separate days using two measures: (1) intraclass correlation coefficients (ICC) calculated based on signal amplitude and (2) spatial overlap. The ICC analysis of pain-related BOLD fMRI responses showed fair-to-moderate intersession reliability in brain areas regarded as part of the cortical pain network. Areas with the highest intersession reliability based on the ICC analysis included the anterior midcingulate cortex, anterior insula, and second somatosensory cortex. Areas with the lowest intersession reliability based on the ICC analysis also showed low spatial reliability; these regions included pregenual anterior cingulate cortex, primary somatosensory cortex, and posterior insula. Thus, this study found regional differences in pain-related BOLD fMRI response reliability, which may provide useful information to guide longitudinal pain studies. A simple motor task (finger-thumb opposition) was performed by the same subjects in the same sessions as the painful heat stimuli were delivered. Intersession reliability of fMRI activation in cortical motor areas was comparable to previously published findings for both spatial overlap and ICC measures, providing support for the validity of the analytical approach used to assess intersession reliability of pain-related fMRI activation. A secondary finding of this study is that the use of standard ICC alone as a measure of reliability may not be sufficient, as the underlying variance structure of an fMRI dataset can result in inappropriately high ICC values; a method to eliminate these false positive results was used in this

  15. Intrasubject reproducibility of presurgical language lateralization and mapping using fMRI.

    NARCIS (Netherlands)

    Fernandez, G.S.E.; Specht, K.; Weis, S.; Tendolkar, I.; Reuber, M.; Fell, J.; Klaver, P.; Ruhlmann, J.; Reul, J.; Elger, C.E.

    2003-01-01

    BACKGROUND: fMRI is becoming a standard tool for the presurgical lateralization and mapping of brain areas involved in language processing. However, its within-subject reproducibility has yet to be fully explored. OBJECTIVE: To evaluate within-test and test-retest reliability of language fMRI in

  16. Cerebellar induced differential polyglot aphasia: A neurolinguistic and fMRI study.

    Science.gov (United States)

    Mariën, Peter; van Dun, Kim; Van Dormael, Johanna; Vandenborre, Dorien; Keulen, Stefanie; Manto, Mario; Verhoeven, Jo; Abutalebi, Jubin

    2017-12-01

    Research has shown that linguistic functions in the bilingual brain are subserved by similar neural circuits as in monolinguals, but with extra-activity associated with cognitive and attentional control. Although a role for the right cerebellum in multilingual language processing has recently been acknowledged, a potential role of the left cerebellum remains largely unexplored. This paper reports the clinical and fMRI findings in a strongly right-handed (late) multilingual patient who developed differential polyglot aphasia, ataxic dysarthria and a selective decrease in executive function due to an ischemic stroke in the left cerebellum. fMRI revealed that lexical-semantic retrieval in the unaffected L1 was predominantly associated with activations in the left cortical areas (left prefrontal area and left postcentral gyrus), while naming in two affected non-native languages recruited a significantly larger bilateral functional network, including the cerebellum. It is hypothesized that the left cerebellar insult resulted in decreased right prefrontal hemisphere functioning due to a loss of cerebellar impulses through the cerebello-cerebral pathways. Copyright © 2017 Elsevier Inc. All rights reserved.

  17. fMRI responses to pictures of mutilation and contamination.

    Science.gov (United States)

    Schienle, Anne; Schäfer, Axel; Hermann, Andrea; Walter, Bertram; Stark, Rudolf; Vaitl, Dieter

    2006-01-30

    Findings from several functional magnetic resonance imaging (fMRI) studies implicate the existence of a distinct neural disgust substrate, whereas others support the idea of distributed and integrative brain systems involved in emotional processing. In the present fMRI experiment 12 healthy females viewed pictures from four emotion categories. Two categories were disgust-relevant and depicted contamination or mutilation. The other scenes showed attacks (fear) or were affectively neutral. The two types of disgust elicitors received comparable ratings for disgust, fear and arousal. Both were associated with activation of the occipitotemporal cortex, the amygdala, and the orbitofrontal cortex; insula activity was nonsignificant in the two disgust conditions. Mutilation scenes induced greater inferior parietal activity than contamination scenes, which might mirror their greater capacity to capture attention. Our results are in disagreement with the idea of selective disgust processing at the insula. They point to a network of brain regions involved in the decoding of stimulus salience and the regulation of attention.

  18. Comparison of two fMRI tasks for the evaluation of the expressive language function

    Energy Technology Data Exchange (ETDEWEB)

    Sanjuan, Ana; Avila, Cesar [Universitat Jaume I, Departamento de Psicologia Basica, Clinica y Psicobiologia, Castellon de la Plana (Spain); Hospital La Fe, Unidad de Epilepsia, Servicio de Neurologia, Valencia (Spain); Bustamante, Juan-Carlos; Forn, Cristina; Ventura-Campos, Noelia; Barros-Loscertales, Alfonso [Universitat Jaume I, Departamento de Psicologia Basica, Clinica y Psicobiologia, Castellon de la Plana (Spain); Martinez, Juan-Carlos [Hospital La Fe, Eresa, Valencia (Spain); Hospital La Fe, Unidad de Epilepsia, Servicio de Neurologia, Valencia (Spain); Villanueva, Vicente [Hospital La Fe, Unidad de Epilepsia, Servicio de Neurologia, Valencia (Spain)

    2010-05-15

    Presurgical evaluation of language is important in patients who are candidates for neurosurgery since language decline is a frequent complication after an operation. Different functional magnetic resonance imaging (fMRI) tasks, such as the verb generation task (VGT) and the verbal fluency task (VFT) have been employed. Our objective was to compare how effective these tasks are at evaluating language functioning in controls (study 1) and patients (study 2). Eighteen controls and 58 patient candidates for neurosurgery (16 patients with temporal lobe epilepsy and 42 patients with brain lesions: 11 astrocytomas, six cavernomas, 14 gliomas, four AVM and seven meningiomas) were recruited in order to compare the activation patterns of language areas as determined by the VGT and VFT. In both samples, the VGT produced a more specific activation of left Broca's area. In contrast, the VFT yielded a wider and more intense activation of the left Broca's area in controls, as well as other activations in the dorsolateral prefrontal cortex and the striatum. Additionally, both studies showed good agreement on language dominance derived from the tasks, although there was some variability in laterality index scores. Both language tasks are useful in evaluation of expressive language. The VGT is a more specific task, while the VFT is more unspecific but activates language-related areas that are not found with the VGT owing to its phonological component. Therefore, each task contributes to the lateralisation and localisation of expressive language areas with complementary information. The advisability of combining tasks to improve fMRI presurgical evaluation is confirmed. (orig.)

  19. Comparison of two fMRI tasks for the evaluation of the expressive language function

    International Nuclear Information System (INIS)

    Sanjuan, Ana; Avila, Cesar; Bustamante, Juan-Carlos; Forn, Cristina; Ventura-Campos, Noelia; Barros-Loscertales, Alfonso; Martinez, Juan-Carlos; Villanueva, Vicente

    2010-01-01

    Presurgical evaluation of language is important in patients who are candidates for neurosurgery since language decline is a frequent complication after an operation. Different functional magnetic resonance imaging (fMRI) tasks, such as the verb generation task (VGT) and the verbal fluency task (VFT) have been employed. Our objective was to compare how effective these tasks are at evaluating language functioning in controls (study 1) and patients (study 2). Eighteen controls and 58 patient candidates for neurosurgery (16 patients with temporal lobe epilepsy and 42 patients with brain lesions: 11 astrocytomas, six cavernomas, 14 gliomas, four AVM and seven meningiomas) were recruited in order to compare the activation patterns of language areas as determined by the VGT and VFT. In both samples, the VGT produced a more specific activation of left Broca's area. In contrast, the VFT yielded a wider and more intense activation of the left Broca's area in controls, as well as other activations in the dorsolateral prefrontal cortex and the striatum. Additionally, both studies showed good agreement on language dominance derived from the tasks, although there was some variability in laterality index scores. Both language tasks are useful in evaluation of expressive language. The VGT is a more specific task, while the VFT is more unspecific but activates language-related areas that are not found with the VGT owing to its phonological component. Therefore, each task contributes to the lateralisation and localisation of expressive language areas with complementary information. The advisability of combining tasks to improve fMRI presurgical evaluation is confirmed. (orig.)

  20. Age-related functional changes in gustatory and reward processing regions: An fMRI study.

    Science.gov (United States)

    Jacobson, Aaron; Green, Erin; Murphy, Claire

    2010-11-01

    Changes in appetite in older adults may result in unhealthy weight change and negatively affect overall nutrition. Research examining gustatory processing in young adults has linked changes in patterns of the hemodynamic response of gustatory and motivation related brain regions to the physiological states of hunger and satiety. Whether the same brain regions are involved in taste processing in older adults is unknown. The current study used functional magnetic resonance imaging (fMRI) to examine age-related changes in gustatory processing during hedonic assessment. Caffeine, citric acid, sucrose, and NaCl were administered orally during two event-related fMRI sessions, one during hunger and one after a pre-load. Participants assessed the pleasantness of the solutions in each session. Increased activity of the insula was seen in both age groups during hunger. Activity of secondary and higher order taste processing and reward regions such as the orbitofrontal cortex, amygdala, hippocampus, thalamus, and caudate nucleus was also observed. Hunger and satiety differentially affected the hemodynamic response, resulting in positive global activation during hunger and negative during satiety in both age groups. While in a state of hunger, the frequency and consistency of positive activation in gustatory and reward processing regions was greater in older adults. Additional regions not commonly associated with taste processing were also activated in older adults. Investigating the neurological response of older adults to taste stimuli under conditions of hunger and satiety may aid in understanding appetite, health, and functional changes in this population. Copyright 2010 Elsevier Inc. All rights reserved.

  1. Functional brain imaging in irritable bowel syndrome with rectal balloon-distention by using fMRI.

    Science.gov (United States)

    Yuan, Yao-Zong; Tao, Ran-Jun; Xu, Bin; Sun, Jing; Chen, Ke-Min; Miao, Fei; Zhang, Zhong-Wei; Xu, Jia-Yu

    2003-06-01

    Irritable bowel syndrome (IBS) is characterized by abdominal pain and changes in stool habits. Visceral hypersensitivity is a key factor in the pathophysiology of IBS. The aim of this study was to examine the effect of rectal balloon-distention stimulus by blood oxygenation level-dependent functional magnetic resonance imaging (BOLD-fMRI) in visceral pain center and to compare the distribution, extent, and intensity of activated areas between IBS patients and normal controls. Twenty-six patients with IBS and eleven normal controls were tested for rectal sensation, and the subjective pain intensity at 90 ml and 120 ml rectal balloon-distention was reported by using Visual Analogue Scale. Then, BOLD-fMRI was performed at 30 ml, 60 ml, 90 ml, and 120 ml rectal balloon-distention in all subjects. Rectal distention stimulation increased the activity of anterior cingulate cortex (35/37), insular cortex (37/37), prefrontal cortex (37/37), and thalamus (35/37) in most cases. At 120 ml of rectal balloon-distention, the activation area and percentage change in MR signal intensity of the regions of interest (ROI) at IC, PFC, and THAL were significantly greater in patients with IBS than that in controls. Score of pain sensation at 90 ml and 120 ml rectal balloon-distention was significantly higher in patients with IBS than that in controls. Using fMRI, some patients with IBS can be detected having visceral hypersensitivity in response to painful rectal balloon-distention. fMRI is an objective brain imaging technique to measure the change in regional cerebral activation more precisely. In this study, IC and PFC of the IBS patients were the major loci of the CNS processing of visceral perception.

  2. Extraction of temporal information in functional MRI

    Science.gov (United States)

    Singh, M.; Sungkarat, W.; Jeong, Jeong-Won; Zhou, Yongxia

    2002-10-01

    The temporal resolution of functional MRI (fMRI) is limited by the shape of the haemodynamic response function (hrf) and the vascular architecture underlying the activated regions. Typically, the temporal resolution of fMRI is on the order of 1 s. We have developed a new data processing approach to extract temporal information on a pixel-by-pixel basis at the level of 100 ms from fMRI data. Instead of correlating or fitting the time-course of each pixel to a single reference function, which is the common practice in fMRI, we correlate each pixel's time-course to a series of reference functions that are shifted with respect to each other by 100 ms. The reference function yielding the highest correlation coefficient for a pixel is then used as a time marker for that pixel. A Monte Carlo simulation and experimental study of this approach were performed to estimate the temporal resolution as a function of signal-to-noise ratio (SNR) in the time-course of a pixel. Assuming a known and stationary hrf, the simulation and experimental studies suggest a lower limit in the temporal resolution of approximately 100 ms at an SNR of 3. The multireference function approach was also applied to extract timing information from an event-related motor movement study where the subjects flexed a finger on cue. The event was repeated 19 times with the event's presentation staggered to yield an approximately 100-ms temporal sampling of the haemodynamic response over the entire presentation cycle. The timing differences among different regions of the brain activated by the motor task were clearly visualized and quantified by this method. The results suggest that it is possible to achieve a temporal resolution of /spl sim/200 ms in practice with this approach.

  3. The continuing challenge of understanding and modeling hemodynamic variation in fMRI

    OpenAIRE

    Handwerker, Daniel A.; Gonzalez-Castillo, Javier; D’Esposito, Mark; Bandettini, Peter A.

    2012-01-01

    Interpretation of fMRI data depends on our ability to understand or model the shape of the hemodynamic response (HR) to a neural event. Although the HR has been studied almost since the beginning of fMRI, we are still far from having robust methods to account for the full range of known HR variation in typical fMRI analyses. This paper reviews how the authors and others contributed to our understanding of HR variation. We present an overview of studies that describe HR variation across voxels...

  4. MEG and fMRI fusion for nonlinear estimation of neural and BOLD signal changes

    Directory of Open Access Journals (Sweden)

    Sergey M Plis

    2010-11-01

    Full Text Available The combined analysis of MEG/EEG and functional MRI measurements can lead to improvement in the description of the dynamical and spatial properties of brain activity. In this paper we empirically demonstrate this improvement using simulated and recorded task related MEG and fMRI activity. Neural activity estimates were derived using a dynamic Bayesian network with continuous real valued parameters by means of a sequential Monte Carlo technique. In synthetic data, we show that MEG and fMRI fusion improves estimation of the indirectly observed neural activity and smooths tracking of the BOLD response. In recordings of task related neural activity the combination of MEG and fMRI produces a result with greater SNR, that confirms the expectation arising from the nature of the experiment. The highly nonlinear model of the BOLD response poses a difficult inference problem for neural activity estimation; computational requirements are also high due to the time and space complexity. We show that joint analysis of the data improves the system's behavior by stabilizing the differential equations system and by requiring fewer computational resources.

  5. Reading positional codes with fMRI: Problems and solutions.

    Directory of Open Access Journals (Sweden)

    Kristjan Kalm

    Full Text Available Neural mechanisms which bind items into sequences have been investigated in a large body of research in animal neurophysiology and human neuroimaging. However, a major problem in interpreting this data arises from a fact that several unrelated processes, such as memory load, sensory adaptation, and reward expectation, also change in a consistent manner as the sequence unfolds. In this paper we use computational simulations and data from two fMRI experiments to show that a host of unrelated neural processes can masquerade as sequence representations. We show that dissociating such unrelated processes from a dedicated sequence representation is an especially difficult problem for fMRI data, which is almost exclusively the modality used in human experiments. We suggest that such fMRI results must be treated with caution and in many cases the assumed neural representation might actually reflect unrelated processes.

  6. Recovering task fMRI signals from highly under-sampled data with low-rank and temporal subspace constraints.

    Science.gov (United States)

    Chiew, Mark; Graedel, Nadine N; Miller, Karla L

    2018-07-01

    Recent developments in highly accelerated fMRI data acquisition have employed low-rank and/or sparsity constraints for image reconstruction, as an alternative to conventional, time-independent parallel imaging. When under-sampling factors are high or the signals of interest are low-variance, however, functional data recovery can be poor or incomplete. We introduce a method for improving reconstruction fidelity using external constraints, like an experimental design matrix, to partially orient the estimated fMRI temporal subspace. Combining these external constraints with low-rank constraints introduces a new image reconstruction model that is analogous to using a mixture of subspace-decomposition (PCA/ICA) and regression (GLM) models in fMRI analysis. We show that this approach improves fMRI reconstruction quality in simulations and experimental data, focusing on the model problem of detecting subtle 1-s latency shifts between brain regions in a block-design task-fMRI experiment. Successful latency discrimination is shown at acceleration factors up to R = 16 in a radial-Cartesian acquisition. We show that this approach works with approximate, or not perfectly informative constraints, where the derived benefit is commensurate with the information content contained in the constraints. The proposed method extends low-rank approximation methods for under-sampled fMRI data acquisition by leveraging knowledge of expected task-based variance in the data, enabling improvements in the speed and efficiency of fMRI data acquisition without the loss of subtle features. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

  7. Automated selection of brain regions for real-time fMRI brain-computer interfaces

    Science.gov (United States)

    Lührs, Michael; Sorger, Bettina; Goebel, Rainer; Esposito, Fabrizio

    2017-02-01

    Objective. Brain-computer interfaces (BCIs) implemented with real-time functional magnetic resonance imaging (rt-fMRI) use fMRI time-courses from predefined regions of interest (ROIs). To reach best performances, localizer experiments and on-site expert supervision are required for ROI definition. To automate this step, we developed two unsupervised computational techniques based on the general linear model (GLM) and independent component analysis (ICA) of rt-fMRI data, and compared their performances on a communication BCI. Approach. 3 T fMRI data of six volunteers were re-analyzed in simulated real-time. During a localizer run, participants performed three mental tasks following visual cues. During two communication runs, a letter-spelling display guided the subjects to freely encode letters by performing one of the mental tasks with a specific timing. GLM- and ICA-based procedures were used to decode each letter, respectively using compact ROIs and whole-brain distributed spatio-temporal patterns of fMRI activity, automatically defined from subject-specific or group-level maps. Main results. Letter-decoding performances were comparable to supervised methods. In combination with a similarity-based criterion, GLM- and ICA-based approaches successfully decoded more than 80% (average) of the letters. Subject-specific maps yielded optimal performances. Significance. Automated solutions for ROI selection may help accelerating the translation of rt-fMRI BCIs from research to clinical applications.

  8. Hidden Markov event sequence models: toward unsupervised functional MRI brain mapping.

    Science.gov (United States)

    Faisan, Sylvain; Thoraval, Laurent; Armspach, Jean-Paul; Foucher, Jack R; Metz-Lutz, Marie-Noëlle; Heitz, Fabrice

    2005-01-01

    Most methods used in functional MRI (fMRI) brain mapping require restrictive assumptions about the shape and timing of the fMRI signal in activated voxels. Consequently, fMRI data may be partially and misleadingly characterized, leading to suboptimal or invalid inference. To limit these assumptions and to capture the broad range of possible activation patterns, a novel statistical fMRI brain mapping method is proposed. It relies on hidden semi-Markov event sequence models (HSMESMs), a special class of hidden Markov models (HMMs) dedicated to the modeling and analysis of event-based random processes. Activation detection is formulated in terms of time coupling between (1) the observed sequence of hemodynamic response onset (HRO) events detected in the voxel's fMRI signal and (2) the "hidden" sequence of task-induced neural activation onset (NAO) events underlying the HROs. Both event sequences are modeled within a single HSMESM. The resulting brain activation model is trained to automatically detect neural activity embedded in the input fMRI data set under analysis. The data sets considered in this article are threefold: synthetic epoch-related, real epoch-related (auditory lexical processing task), and real event-related (oddball detection task) fMRI data sets. Synthetic data: Activation detection results demonstrate the superiority of the HSMESM mapping method with respect to a standard implementation of the statistical parametric mapping (SPM) approach. They are also very close, sometimes equivalent, to those obtained with an "ideal" implementation of SPM in which the activation patterns synthesized are reused for analysis. The HSMESM method appears clearly insensitive to timing variations of the hemodynamic response and exhibits low sensitivity to fluctuations of its shape (unsustained activation during task). Real epoch-related data: HSMESM activation detection results compete with those obtained with SPM, without requiring any prior definition of the expected

  9. Does the individual adaption of standardized speech paradigmas for clinical functional Magnetic Resonance Imaging (fMRI) effect the localization of the language-dominant hemisphere and of Broca's and Wernicke's areas

    International Nuclear Information System (INIS)

    Konrad, F.; Nennig, E.; Kress, B.; Sartor, K.; Stippich, C.; Ochmann, H.

    2005-01-01

    Purpose: Functional magnetic resonance imaging (fMRI) localizes Broca's area (B) and Wernicke's area (W) and the hemisphere dominant for language. In clinical fMRI, adapting the stimulation paradigms to each patient's individual cognitive capacity is crucial for diagnostic success. To interpret clinical fMRI findings correctly, we studied the effect of varying frequency and number of stimuli on functional localization, determination of language dominance and BOLD signals. Materials and Methods: Ten volunteers (VP) were investigated at 1.5 Tesla during visually triggered sentence generation using a standardized block design. In four different measurements, the stimuli were presented to each VP with frequencies of (1/1)s, (1/2)s,(1/3)s and (1/6)s. Results: The functional localizations and the correlations of the measured BOLD signals to the applied hemodynamic reference function (r) were almost independent from frequency and number of the stimuli in both hemispheres, whereas the relative BOLD signal changes (ΔS) in B and W increased with the stimulation rate, which also changed the lateralization indices. The strongest BOLD activations were achieved with the highest stimulation rate or with the maximum language production task, respectively. Conclusion: The adaptation of language paradigms necessary in clinical fMRI does not alter the functional localizations but changes the BOLD signals and language lateralization which should not be attributed to the underlying brain pathology. (orig.)

  10. [Does the individual adaptation of standardized speech paradigmas for clinical functional magnetic resonance imaging (fMRI) effect the localization of the language-dominant hemisphere and of Broca's and Wernicke's areas].

    Science.gov (United States)

    Konrad, F; Nennig, E; Ochmann, H; Kress, B; Sartor, K; Stippich, C

    2005-03-01

    Functional magnetic resonance imaging (fMRI) localizes Broca's area (B) and Wernicke's area (W) and the hemisphere dominant for language. In clinical fMRI, adapting the stimulation paradigms to each patient's individual cognitive capacity is crucial for diagnostic success. To interpret clinical fMRI findings correctly, we studied the effect of varying frequency and number of stimuli on functional localization, determination of language dominance and BOLD signals. Ten volunteers (VP) were investigated at 1.5 Tesla during visually triggered sentence generation using a standardized block design. In four different measurements, the stimuli were presented to each VP with frequencies of 1/1 s, (1/2) s, (1/3) s and (1/6) s. The functional localizations and the correlations of the measured BOLD signals to the applied hemodynamic reference function (r) were almost independent from frequency and number of the stimuli in both hemispheres, whereas the relative BOLD signal changes (DeltaS) in B and W increased with the stimulation rate, which also changed the lateralization indices. The strongest BOLD activations were achieved with the highest stimulation rate or with the maximum language production task, respectively. The adaptation of language paradigms necessary in clinical fMRI does not alter the functional localizations but changes the BOLD signals and language lateralization which should not be attributed to the underlying brain pathology.

  11. Increasing fMRI sampling rate improves Granger causality estimates.

    Directory of Open Access Journals (Sweden)

    Fa-Hsuan Lin

    Full Text Available Estimation of causal interactions between brain areas is necessary for elucidating large-scale functional brain networks underlying behavior and cognition. Granger causality analysis of time series data can quantitatively estimate directional information flow between brain regions. Here, we show that such estimates are significantly improved when the temporal sampling rate of functional magnetic resonance imaging (fMRI is increased 20-fold. Specifically, healthy volunteers performed a simple visuomotor task during blood oxygenation level dependent (BOLD contrast based whole-head inverse imaging (InI. Granger causality analysis based on raw InI BOLD data sampled at 100-ms resolution detected the expected causal relations, whereas when the data were downsampled to the temporal resolution of 2 s typically used in echo-planar fMRI, the causality could not be detected. An additional control analysis, in which we SINC interpolated additional data points to the downsampled time series at 0.1-s intervals, confirmed that the improvements achieved with the real InI data were not explainable by the increased time-series length alone. We therefore conclude that the high-temporal resolution of InI improves the Granger causality connectivity analysis of the human brain.

  12. Identifying patients with Alzheimer's disease using resting-state fMRI and graph theory.

    Science.gov (United States)

    Khazaee, Ali; Ebrahimzadeh, Ata; Babajani-Feremi, Abbas

    2015-11-01

    Study of brain network on the basis of resting-state functional magnetic resonance imaging (fMRI) has provided promising results to investigate changes in connectivity among different brain regions because of diseases. Graph theory can efficiently characterize different aspects of the brain network by calculating measures of integration and segregation. In this study, we combine graph theoretical approaches with advanced machine learning methods to study functional brain network alteration in patients with Alzheimer's disease (AD). Support vector machine (SVM) was used to explore the ability of graph measures in diagnosis of AD. We applied our method on the resting-state fMRI data of twenty patients with AD and twenty age and gender matched healthy subjects. The data were preprocessed and each subject's graph was constructed by parcellation of the whole brain into 90 distinct regions using the automated anatomical labeling (AAL) atlas. The graph measures were then calculated and used as the discriminating features. Extracted network-based features were fed to different feature selection algorithms to choose most significant features. In addition to the machine learning approach, statistical analysis was performed on connectivity matrices to find altered connectivity patterns in patients with AD. Using the selected features, we were able to accurately classify patients with AD from healthy subjects with accuracy of 100%. Results of this study show that pattern recognition and graph of brain network, on the basis of the resting state fMRI data, can efficiently assist in the diagnosis of AD. Classification based on the resting-state fMRI can be used as a non-invasive and automatic tool to diagnosis of Alzheimer's disease. Copyright © 2015 International Federation of Clinical Neurophysiology. All rights reserved.

  13. Combining task-evoked and spontaneous activity to improve pre-operative brain mapping with fMRI.

    Science.gov (United States)

    Fox, Michael D; Qian, Tianyi; Madsen, Joseph R; Wang, Danhong; Li, Meiling; Ge, Manling; Zuo, Huan-Cong; Groppe, David M; Mehta, Ashesh D; Hong, Bo; Liu, Hesheng

    2016-01-01

    Noninvasive localization of brain function is used to understand and treat neurological disease, exemplified by pre-operative fMRI mapping prior to neurosurgical intervention. The principal approach for generating these maps relies on brain responses evoked by a task and, despite known limitations, has dominated clinical practice for over 20years. Recently, pre-operative fMRI mapping based on correlations in spontaneous brain activity has been demonstrated, however this approach has its own limitations and has not seen widespread clinical use. Here we show that spontaneous and task-based mapping can be performed together using the same pre-operative fMRI data, provide complimentary information relevant for functional localization, and can be combined to improve identification of eloquent motor cortex. Accuracy, sensitivity, and specificity of our approach are quantified through comparison with electrical cortical stimulation mapping in eight patients with intractable epilepsy. Broad applicability and reproducibility of our approach are demonstrated through prospective replication in an independent dataset of six patients from a different center. In both cohorts and every individual patient, we see a significant improvement in signal to noise and mapping accuracy independent of threshold, quantified using receiver operating characteristic curves. Collectively, our results suggest that modifying the processing of fMRI data to incorporate both task-based and spontaneous activity significantly improves functional localization in pre-operative patients. Because this method requires no additional scan time or modification to conventional pre-operative data acquisition protocols it could have widespread utility. Copyright © 2015. Published by Elsevier Inc.

  14. Correlation between resting state fMRI total neuronal activity and PET metabolism in healthy controls and patients with disorders of consciousness.

    Science.gov (United States)

    Soddu, Andrea; Gómez, Francisco; Heine, Lizette; Di Perri, Carol; Bahri, Mohamed Ali; Voss, Henning U; Bruno, Marie-Aurélie; Vanhaudenhuyse, Audrey; Phillips, Christophe; Demertzi, Athena; Chatelle, Camille; Schrouff, Jessica; Thibaut, Aurore; Charland-Verville, Vanessa; Noirhomme, Quentin; Salmon, Eric; Tshibanda, Jean-Flory Luaba; Schiff, Nicholas D; Laureys, Steven

    2016-01-01

    The mildly invasive 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) is a well-established imaging technique to measure 'resting state' cerebral metabolism. This technique made it possible to assess changes in metabolic activity in clinical applications, such as the study of severe brain injury and disorders of consciousness. We assessed the possibility of creating functional MRI activity maps, which could estimate the relative levels of activity in FDG-PET cerebral metabolic maps. If no metabolic absolute measures can be extracted, our approach may still be of clinical use in centers without access to FDG-PET. It also overcomes the problem of recognizing individual networks of independent component selection in functional magnetic resonance imaging (fMRI) resting state analysis. We extracted resting state fMRI functional connectivity maps using independent component analysis and combined only components of neuronal origin. To assess neuronality of components a classification based on support vector machine (SVM) was used. We compared the generated maps with the FDG-PET maps in 16 healthy controls, 11 vegetative state/unresponsive wakefulness syndrome patients and four locked-in patients. The results show a significant similarity with ρ = 0.75 ± 0.05 for healthy controls and ρ = 0.58 ± 0.09 for vegetative state/unresponsive wakefulness syndrome patients between the FDG-PET and the fMRI based maps. FDG-PET, fMRI neuronal maps, and the conjunction analysis show decreases in frontoparietal and medial regions in vegetative patients with respect to controls. Subsequent analysis in locked-in syndrome patients produced also consistent maps with healthy controls. The constructed resting state fMRI functional connectivity map points toward the possibility for fMRI resting state to estimate relative levels of activity in a metabolic map.

  15. A Versatile Software Package for Inter-subject Correlation Based Analyses of fMRI

    Directory of Open Access Journals (Sweden)

    Jukka-Pekka eKauppi

    2014-01-01

    Full Text Available In the inter-subject correlation (ISC based analysis of the functional magnetic resonance imaging (fMRI data, the extent of shared processing across subjects during the experiment is determined by calculating correlation coefficients between the fMRI time series of the subjects in the corresponding brain locations. This implies that ISC can be used to analyze fMRI data without explicitly modelling the stimulus and thus ISC is a potential method to analyze fMRI data acquired under complex naturalistic stimuli. Despite of the suitability of ISC based approach to analyze complex fMRI data, no generic software tools have been made available for this purpose, limiting a widespread use of ISC based analysis techniques among neuroimaging community. In this paper, we present a graphical user interface (GUI based software package, ISC Toolbox, implemented in Matlab for computing various ISC based analyses. Many advanced computations such as comparison of ISCs between different stimuli, time window ISC, and inter-subject phase synchronization are supported by the toolbox. The analyses are coupled with re-sampling based statistical inference. The ISC based analyses are data and computation intensive and the ISC toolbox is equipped with mechanisms to execute the parallel computations in a cluster environment automatically and with an automatic detection of the cluster environment in use. Currently, SGE-based (Oracle Grid Engine, Son of a Grid Engine or Open Grid Scheduler and Slurm environments are supported. In this paper, we present a detailed account on the methods behind the ISC Toolbox, the implementation of the toolbox and demonstrate the possible use of the toolbox by summarizing selected example applications. We also report the computation time experiments both using a single desktop computer and two grid environments demonstrating that parallelization effectively reduces the computing time. The ISC Toolbox is available in https://code.google.com/p/isc-toolbox/.

  16. A versatile software package for inter-subject correlation based analyses of fMRI.

    Science.gov (United States)

    Kauppi, Jukka-Pekka; Pajula, Juha; Tohka, Jussi

    2014-01-01

    In the inter-subject correlation (ISC) based analysis of the functional magnetic resonance imaging (fMRI) data, the extent of shared processing across subjects during the experiment is determined by calculating correlation coefficients between the fMRI time series of the subjects in the corresponding brain locations. This implies that ISC can be used to analyze fMRI data without explicitly modeling the stimulus and thus ISC is a potential method to analyze fMRI data acquired under complex naturalistic stimuli. Despite of the suitability of ISC based approach to analyze complex fMRI data, no generic software tools have been made available for this purpose, limiting a widespread use of ISC based analysis techniques among neuroimaging community. In this paper, we present a graphical user interface (GUI) based software package, ISC Toolbox, implemented in Matlab for computing various ISC based analyses. Many advanced computations such as comparison of ISCs between different stimuli, time window ISC, and inter-subject phase synchronization are supported by the toolbox. The analyses are coupled with re-sampling based statistical inference. The ISC based analyses are data and computation intensive and the ISC toolbox is equipped with mechanisms to execute the parallel computations in a cluster environment automatically and with an automatic detection of the cluster environment in use. Currently, SGE-based (Oracle Grid Engine, Son of a Grid Engine, or Open Grid Scheduler) and Slurm environments are supported. In this paper, we present a detailed account on the methods behind the ISC Toolbox, the implementation of the toolbox and demonstrate the possible use of the toolbox by summarizing selected example applications. We also report the computation time experiments both using a single desktop computer and two grid environments demonstrating that parallelization effectively reduces the computing time. The ISC Toolbox is available in https://code.google.com/p/isc-toolbox/

  17. Probing the Interoceptive Network by Listening to Heartbeats: An fMRI Study.

    Directory of Open Access Journals (Sweden)

    Nina I Kleint

    Full Text Available Exposure to cues of homeostatic relevance (i.e. heartbeats is supposed to increase the allocation of attentional resources towards the cue, due to its importance for self-regulatory, interoceptive processes. This functional magnetic resonance imaging (fMRI study aimed at determining whether listening to heartbeats is accompanied by activation in brain areas associated with interoception, particularly the insular cortex. Brain activity was measured with fMRI during cue-exposure in 36 subjects while listening to heartbeats vs. sinus tones. Autonomic markers (skin conductance and subjective measures of state and trait anxiety were assessed. Stimulation with heartbeat sounds triggered activation in brain areas commonly associated with the processing of interoceptive information, including bilateral insular cortices, the inferior frontal operculum, and the middle frontal gyrus. A psychophysiological interaction analysis indicated a functional connectivity between the middle frontal gyrus (seed region and bilateral insular cortices, the left amygdala and the supplementary motor area. The magnitude of neural activation in the right anterior insular cortex was positively associated with autonomic arousal. The present findings indicate that listening to heartbeats induced activity in areas of the interoception network as well as changes in psychophysiological arousal and subjective emotional experience. As this approach constitutes a promising method for studying interoception in the fMRI environment, a clinical application in anxiety prone populations should be addressed by future studies.

  18. Calibrated fMRI for mapping absolute CMRO2: Practicalities and prospects.

    Science.gov (United States)

    Germuska, M; Wise, R G

    2018-03-29

    Functional magnetic resonance imaging (fMRI) is an essential workhorse of modern neuroscience, providing valuable insight into the functional organisation of the brain. The physiological mechanisms underlying the blood oxygenation level dependent (BOLD) effect are complex and preclude a straightforward interpretation of the signal. However, by employing appropriate calibration of the BOLD signal, quantitative measurements can be made of important physiological parameters including the absolute rate of cerebral metabolic oxygen consumption or oxygen metabolism (CMRO 2 ) and oxygen extraction (OEF). The ability to map such fundamental parameters has the potential to greatly expand the utility of fMRI and to broaden its scope of application in clinical research and clinical practice. In this review article we discuss some of the practical issues related to the calibrated-fMRI approach to the measurement of CMRO 2 . We give an overview of the necessary precautions to ensure high quality data acquisition, and explore some of the pitfalls and challenges that must be considered as it is applied and interpreted in a widening array of diseases and research questions. Copyright © 2018 Elsevier Inc. All rights reserved.

  19. Position-history and spin-history artifacts in fMRI time-series

    NARCIS (Netherlands)

    Muresan, L; Renken, R; Roerdink, JBTM; Duifhuis, H; Clough, AN; Chen, CT

    2002-01-01

    What is the impact of the spin history and position history on signal intensity after the alignment of acquired volumes? This question arises in many fMRI studies. We will focus on spin-history artefacts generated by the position-history of the scanned object. In fMRI an object is driven to steady

  20. Functional alterations of V1 cortex in patients with primary open angle glaucoma using functional MRI retinotopic mapping

    International Nuclear Information System (INIS)

    Shi Linping; Cai Ping; Li Changying; Li Xueqin; Xie Bing; Li Sha; Liu Ting; Chen Xing; Shi Yanshu; Wang Jian

    2011-01-01

    Objective: To evaluate the functional changes of visual cortex (V1) in patients with primary open angle glaucoma (POAG) by fMRI retinotopic mapping technology. Methods: Fifteen POAG patients and 15 healthy volunteers underwent stimulations with fMRI retinotopic mapping stimulus and contrast-reversing checkerboard patterns stimulus on a Siemens Trio 3.0 T MRI whole-body scanner for functional data collection. Comparisons of V1 fMRI responses between the glaucomatous eyes and the healthy eyes of the patients were carried out using paired samples t-test, while independent samples t-test was used to compare V1 fMRI responses and activations between the healthy eyes of patients and the age-, gender- and side- matched eyes of normal people. Differences of V1 cortical functions and visual functions were analyzed by linear correlation analysis when the glaucomatous and the healthy eyes were simulated individually., Results: (1) V1 fMRI responses of the individually stimulated glaucomatous eyes [(1.24±0.72)%] were weaker than those of the healthy eyes [(2.18±0.93)%] (t=4.757, P 0.05). (2) Differences of V1 cortical functions were negatively correlated with those of visual functions in the individually stimulated glaucomatous and healthy eyes (r=-0.887, P< 0.01). (3) The activated area indexes of V1 cortexes in the healthy eyes from patients (0.72±0.12) were lower than those in the matched eyes of normal people (0.85±0.09) (t=-3.801, P<0.01) . Conclusion: Cortical function impairment was in accordance with visual function impairment in glaucoma. Located and quantified measurement with fMRI retinotopic mapping was a useful method for clinical follow-up and evaluation of functional alteration of glaucomatous visual cortex, and a potentially useful means of studying trans-synaptic degeneration of visual pathways of in vivo glaucoma. (authors)

  1. Disrupted functional connectivity of the hippocampus in patients with hyperthyroidism: Evidence from resting-state fMRI

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Wei, E-mail: will.zhang.1111@gmail.com [Department of Radiology, Southwest Hospital, Third Military Medical University, Chongqing 400038 (China); Department of Radiology, Sichuan Provincial Corps Hospital, Chinese People' s Armed Police Forces, Leshan 614000 (China); Liu, Xianjun, E-mail: xianjun6.liu@gmail.com [Department of Radiology, Sichuan Provincial Corps Hospital, Chinese People' s Armed Police Forces, Leshan 614000 (China); Zhang, Yi, E-mail: yi.zhang.0833@gmail.com [Department of Radiology, Sichuan Provincial Corps Hospital, Chinese People' s Armed Police Forces, Leshan 614000 (China); Song, Lingheng, E-mail: songlh1023@hotmail.com [Department of Radiology, Southwest Hospital, Third Military Medical University, Chongqing 400038 (China); Hou, Jingming, E-mail: jingminghou@hotmail.com [Department of Radiology, Southwest Hospital, Third Military Medical University, Chongqing 400038 (China); Chen, Bing, E-mail: chenbing3@medmail.com.cn [Department of Endocrinology, Southwest Hospital, Third Military Medical University, Chongqing 400038 (China); He, Mei, E-mail: sunnusunny0105@gmail.com [Department of Clinical Psychology, Southwest Hospital, Third Military Medical University, Chongqing 400038 (China); Cai, Ping, E-mail: pingc_ddd@sina.com [Department of Radiology, Southwest Hospital, Third Military Medical University, Chongqing 400038 (China); Lii, Haitao, E-mail: haitaolii023@gmail.com [Department of Radiology, Southwest Hospital, Third Military Medical University, Chongqing 400038 (China)

    2014-10-15

    Objective: The hippocampus expresses high levels of thyroid hormone receptors, suggesting that hippocampal functions, including cognition and regulation of mood, can be disrupted by thyroid pathology. Indeed, structural and functional alterations within the hippocampus have been observed in hyperthyroid patients. In addition to internal circuitry, hippocampal processing is dependent on extensive connections with other limbic and neocortical structures, but the effects of hyperthyroidism on functional connectivity (FC) with these areas have not been studied. The purpose of this study was to investigate possible abnormalities in the FC between the hippocampus and other neural structures in hyperthyroid patients using resting-state fMRI. Methods: Seed-based correlation analysis was performed on resting-state fMRI data to reveal possible differences in hippocampal FC between hyperthyroid patients and healthy controls. Correlation analysis was used to investigate the relationships between the strength of FC in regions showing significant group differences and clinical variables. Results: Compared to controls, hyperthyroid patients showed weaker FC between the bilateral hippocampus and both the bilateral anterior cingulate cortex (ACC) and bilateral posterior cingulate cortex (PCC), as well as between the right hippocampus and right medial orbitofrontal cortex (mOFC). Disease duration was negatively correlated with FC strength between the bilateral hippocampus and bilateral ACC and PCC. Levels of depression and anxiety were negatively correlated with FC strength between the bilateral hippocampus and bilateral ACC. Conclusion: Decreased functional connectivity between the hippocampus and bilateral ACC, PCC, and right mOFC may contribute to the emotional and cognitive dysfunction associated with hyperthyroidism.

  2. Disrupted functional connectivity of the hippocampus in patients with hyperthyroidism: Evidence from resting-state fMRI

    International Nuclear Information System (INIS)

    Zhang, Wei; Liu, Xianjun; Zhang, Yi; Song, Lingheng; Hou, Jingming; Chen, Bing; He, Mei; Cai, Ping; Lii, Haitao

    2014-01-01

    Objective: The hippocampus expresses high levels of thyroid hormone receptors, suggesting that hippocampal functions, including cognition and regulation of mood, can be disrupted by thyroid pathology. Indeed, structural and functional alterations within the hippocampus have been observed in hyperthyroid patients. In addition to internal circuitry, hippocampal processing is dependent on extensive connections with other limbic and neocortical structures, but the effects of hyperthyroidism on functional connectivity (FC) with these areas have not been studied. The purpose of this study was to investigate possible abnormalities in the FC between the hippocampus and other neural structures in hyperthyroid patients using resting-state fMRI. Methods: Seed-based correlation analysis was performed on resting-state fMRI data to reveal possible differences in hippocampal FC between hyperthyroid patients and healthy controls. Correlation analysis was used to investigate the relationships between the strength of FC in regions showing significant group differences and clinical variables. Results: Compared to controls, hyperthyroid patients showed weaker FC between the bilateral hippocampus and both the bilateral anterior cingulate cortex (ACC) and bilateral posterior cingulate cortex (PCC), as well as between the right hippocampus and right medial orbitofrontal cortex (mOFC). Disease duration was negatively correlated with FC strength between the bilateral hippocampus and bilateral ACC and PCC. Levels of depression and anxiety were negatively correlated with FC strength between the bilateral hippocampus and bilateral ACC. Conclusion: Decreased functional connectivity between the hippocampus and bilateral ACC, PCC, and right mOFC may contribute to the emotional and cognitive dysfunction associated with hyperthyroidism

  3. Disrupted functional connectivity of the hippocampus in patients with hyperthyroidism: evidence from resting-state fMRI.

    Science.gov (United States)

    Zhang, Wei; Liu, Xianjun; Zhang, Yi; Song, Lingheng; Hou, Jingming; Chen, Bing; He, Mei; Cai, Ping; Lii, Haitao

    2014-10-01

    The hippocampus expresses high levels of thyroid hormone receptors, suggesting that hippocampal functions, including cognition and regulation of mood, can be disrupted by thyroid pathology. Indeed, structural and functional alterations within the hippocampus have been observed in hyperthyroid patients. In addition to internal circuitry, hippocampal processing is dependent on extensive connections with other limbic and neocortical structures, but the effects of hyperthyroidism on functional connectivity (FC) with these areas have not been studied. The purpose of this study was to investigate possible abnormalities in the FC between the hippocampus and other neural structures in hyperthyroid patients using resting-state fMRI. Seed-based correlation analysis was performed on resting-state fMRI data to reveal possible differences in hippocampal FC between hyperthyroid patients and healthy controls. Correlation analysis was used to investigate the relationships between the strength of FC in regions showing significant group differences and clinical variables. Compared to controls, hyperthyroid patients showed weaker FC between the bilateral hippocampus and both the bilateral anterior cingulate cortex (ACC) and bilateral posterior cingulate cortex (PCC), as well as between the right hippocampus and right medial orbitofrontal cortex (mOFC). Disease duration was negatively correlated with FC strength between the bilateral hippocampus and bilateral ACC and PCC. Levels of depression and anxiety were negatively correlated with FC strength between the bilateral hippocampus and bilateral ACC. Decreased functional connectivity between the hippocampus and bilateral ACC, PCC, and right mOFC may contribute to the emotional and cognitive dysfunction associated with hyperthyroidism. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  4. Real-time fMRI pattern decoding and neurofeedback using FRIEND: an FSL-integrated BCI toolbox.

    Science.gov (United States)

    Sato, João R; Basilio, Rodrigo; Paiva, Fernando F; Garrido, Griselda J; Bramati, Ivanei E; Bado, Patricia; Tovar-Moll, Fernanda; Zahn, Roland; Moll, Jorge

    2013-01-01

    The demonstration that humans can learn to modulate their own brain activity based on feedback of neurophysiological signals opened up exciting opportunities for fundamental and applied neuroscience. Although EEG-based neurofeedback has been long employed both in experimental and clinical investigation, functional MRI (fMRI)-based neurofeedback emerged as a promising method, given its superior spatial resolution and ability to gauge deep cortical and subcortical brain regions. In combination with improved computational approaches, such as pattern recognition analysis (e.g., Support Vector Machines, SVM), fMRI neurofeedback and brain decoding represent key innovations in the field of neuromodulation and functional plasticity. Expansion in this field and its applications critically depend on the existence of freely available, integrated and user-friendly tools for the neuroimaging research community. Here, we introduce FRIEND, a graphic-oriented user-friendly interface package for fMRI neurofeedback and real-time multivoxel pattern decoding. The package integrates routines for image preprocessing in real-time, ROI-based feedback (single-ROI BOLD level and functional connectivity) and brain decoding-based feedback using SVM. FRIEND delivers an intuitive graphic interface with flexible processing pipelines involving optimized procedures embedding widely validated packages, such as FSL and libSVM. In addition, a user-defined visual neurofeedback module allows users to easily design and run fMRI neurofeedback experiments using ROI-based or multivariate classification approaches. FRIEND is open-source and free for non-commercial use. Processing tutorials and extensive documentation are available.

  5. Real-time fMRI pattern decoding and neurofeedback using FRIEND: an FSL-integrated BCI toolbox.

    Directory of Open Access Journals (Sweden)

    João R Sato

    Full Text Available The demonstration that humans can learn to modulate their own brain activity based on feedback of neurophysiological signals opened up exciting opportunities for fundamental and applied neuroscience. Although EEG-based neurofeedback has been long employed both in experimental and clinical investigation, functional MRI (fMRI-based neurofeedback emerged as a promising method, given its superior spatial resolution and ability to gauge deep cortical and subcortical brain regions. In combination with improved computational approaches, such as pattern recognition analysis (e.g., Support Vector Machines, SVM, fMRI neurofeedback and brain decoding represent key innovations in the field of neuromodulation and functional plasticity. Expansion in this field and its applications critically depend on the existence of freely available, integrated and user-friendly tools for the neuroimaging research community. Here, we introduce FRIEND, a graphic-oriented user-friendly interface package for fMRI neurofeedback and real-time multivoxel pattern decoding. The package integrates routines for image preprocessing in real-time, ROI-based feedback (single-ROI BOLD level and functional connectivity and brain decoding-based feedback using SVM. FRIEND delivers an intuitive graphic interface with flexible processing pipelines involving optimized procedures embedding widely validated packages, such as FSL and libSVM. In addition, a user-defined visual neurofeedback module allows users to easily design and run fMRI neurofeedback experiments using ROI-based or multivariate classification approaches. FRIEND is open-source and free for non-commercial use. Processing tutorials and extensive documentation are available.

  6. Real-Time fMRI Pattern Decoding and Neurofeedback Using FRIEND: An FSL-Integrated BCI Toolbox

    Science.gov (United States)

    Sato, João R.; Basilio, Rodrigo; Paiva, Fernando F.; Garrido, Griselda J.; Bramati, Ivanei E.; Bado, Patricia; Tovar-Moll, Fernanda; Zahn, Roland; Moll, Jorge

    2013-01-01

    The demonstration that humans can learn to modulate their own brain activity based on feedback of neurophysiological signals opened up exciting opportunities for fundamental and applied neuroscience. Although EEG-based neurofeedback has been long employed both in experimental and clinical investigation, functional MRI (fMRI)-based neurofeedback emerged as a promising method, given its superior spatial resolution and ability to gauge deep cortical and subcortical brain regions. In combination with improved computational approaches, such as pattern recognition analysis (e.g., Support Vector Machines, SVM), fMRI neurofeedback and brain decoding represent key innovations in the field of neuromodulation and functional plasticity. Expansion in this field and its applications critically depend on the existence of freely available, integrated and user-friendly tools for the neuroimaging research community. Here, we introduce FRIEND, a graphic-oriented user-friendly interface package for fMRI neurofeedback and real-time multivoxel pattern decoding. The package integrates routines for image preprocessing in real-time, ROI-based feedback (single-ROI BOLD level and functional connectivity) and brain decoding-based feedback using SVM. FRIEND delivers an intuitive graphic interface with flexible processing pipelines involving optimized procedures embedding widely validated packages, such as FSL and libSVM. In addition, a user-defined visual neurofeedback module allows users to easily design and run fMRI neurofeedback experiments using ROI-based or multivariate classification approaches. FRIEND is open-source and free for non-commercial use. Processing tutorials and extensive documentation are available. PMID:24312569

  7. Task and task-free fMRI reproducibility comparison for motor network identification

    NARCIS (Netherlands)

    Kristo, G.; Rutten, G.J.; Raemaekers, M.; de Gelder, B.; Rombouts, S.A.R.B.; Ramsey, N.F.

    2014-01-01

    Test-retest reliability of individual functional magnetic resonance imaging (fMRI) results is of importance in clinical practice and longitudinal experiments. While several studies have investigated reliability of task-induced motor network activation, less is known about the reliability of the

  8. Linear Discriminant Analysis achieves high classification accuracy for the BOLD fMRI response to naturalistic movie stimuli.

    Directory of Open Access Journals (Sweden)

    Hendrik eMandelkow

    2016-03-01

    Full Text Available Naturalistic stimuli like movies evoke complex perceptual processes, which are of great interest in the study of human cognition by functional MRI (fMRI. However, conventional fMRI analysis based on statistical parametric mapping (SPM and the general linear model (GLM is hampered by a lack of accurate parametric models of the BOLD response to complex stimuli. In this situation, statistical machine-learning methods, a.k.a. multivariate pattern analysis (MVPA, have received growing attention for their ability to generate stimulus response models in a data-driven fashion. However, machine-learning methods typically require large amounts of training data as well as computational resources. In the past this has largely limited their application to fMRI experiments involving small sets of stimulus categories and small regions of interest in the brain. By contrast, the present study compares several classification algorithms known as Nearest Neighbour (NN, Gaussian Naïve Bayes (GNB, and (regularised Linear Discriminant Analysis (LDA in terms of their classification accuracy in discriminating the global fMRI response patterns evoked by a large number of naturalistic visual stimuli presented as a movie.Results show that LDA regularised by principal component analysis (PCA achieved high classification accuracies, above 90% on average for single fMRI volumes acquired 2s apart during a 300s movie (chance level 0.7% = 2s/300s. The largest source of classification errors were autocorrelations in the BOLD signal compounded by the similarity of consecutive stimuli. All classifiers performed best when given input features from a large region of interest comprising around 25% of the voxels that responded significantly to the visual stimulus. Consistent with this, the most informative principal components represented widespread distributions of co-activated brain regions that were similar between subjects and may represent functional networks. In light of these

  9. Hemodynamic modelling of BOLD fMRI - A machine learning approach

    DEFF Research Database (Denmark)

    Jacobsen, Danjal Jakup

    2007-01-01

    This Ph.D. thesis concerns the application of machine learning methods to hemodynamic models for BOLD fMRI data. Several such models have been proposed by different researchers, and they have in common a basis in physiological knowledge of the hemodynamic processes involved in the generation...... of the BOLD signal. The BOLD signal is modelled as a non-linear function of underlying, hidden (non-measurable) hemodynamic state variables. The focus of this thesis work has been to develop methods for learning the parameters of such models, both in their traditional formulation, and in a state space...... formulation. In the latter, noise enters at the level of the hidden states, as well as in the BOLD measurements themselves. A framework has been developed to allow approximate posterior distributions of model parameters to be learned from real fMRI data. This is accomplished with Markov chain Monte Carlo...

  10. Lateralization of functional magnetic resonance imaging (fMRI) activation in the auditory pathway of patients with lateralized tinnitus

    Energy Technology Data Exchange (ETDEWEB)

    Smits, Marion [Erasmus MC - University Medical Center Rotterdam, Department of Radiology, Hs 224, Rotterdam (Netherlands); Kovacs, Silvia; Peeters, Ronald R; Hecke, Paul van; Sunaert, Stefan [University Hospitals of the Catholic University Leuven, Department of Radiology, Leuven (Belgium); Ridder, Dirk de [University of Antwerp, Department of Neurosurgery, Edegem (Belgium)

    2007-08-15

    Tinnitus is hypothesized to be an auditory phantom phenomenon resulting from spontaneous neuronal activity somewhere along the auditory pathway. We performed fMRI of the entire auditory pathway, including the inferior colliculus (IC), the medial geniculate body (MGB) and the auditory cortex (AC), in 42 patients with tinnitus and 10 healthy volunteers to assess lateralization of fMRI activation. Subjects were scanned on a 3T MRI scanner. A T2*-weighted EPI silent gap sequence was used during the stimulation paradigm, which consisted of a blocked design of 12 epochs in which music presented binaurally through headphones, which was switched on and off for periods of 50 s. Using SPM2 software, single subject and group statistical parametric maps were calculated. Lateralization of activation was assessed qualitatively and quantitatively. Tinnitus was lateralized in 35 patients (83%, 13 right-sided and 22 left-sided). Significant signal change (P{sub corrected} < 0.05) was found bilaterally in the primary and secondary AC, the IC and the MGB. Signal change was symmetrical in patients with bilateral tinnitus. In patients with lateralized tinnitus, fMRI activation was lateralized towards the side of perceived tinnitus in the primary AC and IC in patients with right-sided tinnitus, and in the MGB in patients with left-sided tinnitus. In healthy volunteers, activation in the primary AC was left-lateralized. Our paradigm adequately visualized the auditory pathways in tinnitus patients. In lateralized tinnitus fMRI activation was also lateralized, supporting the hypothesis that tinnitus is an auditory phantom phenomenon. (orig.)

  11. Lateralization of functional magnetic resonance imaging (fMRI) activation in the auditory pathway of patients with lateralized tinnitus

    International Nuclear Information System (INIS)

    Smits, Marion; Kovacs, Silvia; Peeters, Ronald R.; Hecke, Paul van; Sunaert, Stefan; Ridder, Dirk de

    2007-01-01

    Tinnitus is hypothesized to be an auditory phantom phenomenon resulting from spontaneous neuronal activity somewhere along the auditory pathway. We performed fMRI of the entire auditory pathway, including the inferior colliculus (IC), the medial geniculate body (MGB) and the auditory cortex (AC), in 42 patients with tinnitus and 10 healthy volunteers to assess lateralization of fMRI activation. Subjects were scanned on a 3T MRI scanner. A T2*-weighted EPI silent gap sequence was used during the stimulation paradigm, which consisted of a blocked design of 12 epochs in which music presented binaurally through headphones, which was switched on and off for periods of 50 s. Using SPM2 software, single subject and group statistical parametric maps were calculated. Lateralization of activation was assessed qualitatively and quantitatively. Tinnitus was lateralized in 35 patients (83%, 13 right-sided and 22 left-sided). Significant signal change (P corrected < 0.05) was found bilaterally in the primary and secondary AC, the IC and the MGB. Signal change was symmetrical in patients with bilateral tinnitus. In patients with lateralized tinnitus, fMRI activation was lateralized towards the side of perceived tinnitus in the primary AC and IC in patients with right-sided tinnitus, and in the MGB in patients with left-sided tinnitus. In healthy volunteers, activation in the primary AC was left-lateralized. Our paradigm adequately visualized the auditory pathways in tinnitus patients. In lateralized tinnitus fMRI activation was also lateralized, supporting the hypothesis that tinnitus is an auditory phantom phenomenon. (orig.)

  12. A novel approach to analyzing fMRI and SNP data via parallel independent component analysis

    Science.gov (United States)

    Liu, Jingyu; Pearlson, Godfrey; Calhoun, Vince; Windemuth, Andreas

    2007-03-01

    There is current interest in understanding genetic influences on brain function in both the healthy and the disordered brain. Parallel independent component analysis, a new method for analyzing multimodal data, is proposed in this paper and applied to functional magnetic resonance imaging (fMRI) and a single nucleotide polymorphism (SNP) array. The method aims to identify the independent components of each modality and the relationship between the two modalities. We analyzed 92 participants, including 29 schizophrenia (SZ) patients, 13 unaffected SZ relatives, and 50 healthy controls. We found a correlation of 0.79 between one fMRI component and one SNP component. The fMRI component consists of activations in cingulate gyrus, multiple frontal gyri, and superior temporal gyrus. The related SNP component is contributed to significantly by 9 SNPs located in sets of genes, including those coding for apolipoprotein A-I, and C-III, malate dehydrogenase 1 and the gamma-aminobutyric acid alpha-2 receptor. A significant difference in the presences of this SNP component is found between the SZ group (SZ patients and their relatives) and the control group. In summary, we constructed a framework to identify the interactions between brain functional and genetic information; our findings provide new insight into understanding genetic influences on brain function in a common mental disorder.

  13. Learning effective connectivity from fMRI using autoregressive hidden Markov model with missing data.

    Science.gov (United States)

    Dang, Shilpa; Chaudhury, Santanu; Lall, Brejesh; Roy, Prasun Kumar

    2017-02-15

    Effective connectivity (EC) analysis of neuronal groups using fMRI delivers insights about functional-integration. However, fMRI signal has low-temporal resolution due to down-sampling and indirectly measures underlying neuronal activity. The aim is to address above issues for more reliable EC estimates. This paper proposes use of autoregressive hidden Markov model with missing data (AR-HMM-md) in dynamically multi-linked (DML) framework for learning EC using multiple fMRI time series. In our recent work (Dang et al., 2016), we have shown how AR-HMM-md for modelling single fMRI time series outperforms the existing methods. AR-HMM-md models unobserved neuronal activity and lost data over time as variables and estimates their values by joint optimization given fMRI observation sequence. The effectiveness in learning EC is shown using simulated experiments. Also the effects of sampling and noise are studied on EC. Moreover, classification-experiments are performed for Attention-Deficit/Hyperactivity Disorder subjects and age-matched controls for performance evaluation of real data. Using Bayesian model selection, we see that the proposed model converged to higher log-likelihood and demonstrated that group-classification can be performed with higher cross-validation accuracy of above 94% using distinctive network EC which characterizes patients vs. The full data EC obtained from DML-AR-HMM-md is more consistent with previous literature than the classical multivariate Granger causality method. The proposed architecture leads to reliable estimates of EC than the existing latent models. This framework overcomes the disadvantage of low-temporal resolution and improves cross-validation accuracy significantly due to presence of missing data variables and autoregressive process. Copyright © 2016 Elsevier B.V. All rights reserved.

  14. Estimation of the neuronal activation using fMRI data: An observer-based approach

    KAUST Repository

    Laleg-Kirati, Taous-Meriem; Arabi, Hossein; Tadjine, Mohamed; Zayane, Chadia

    2013-01-01

    This paper deals with the estimation of the neuronal activation and some unmeasured physiological information using the Blood Oxygenation Level Dependent (BOLD) signal measured using functional Magnetic Resonance Imaging (fMRI). We propose to use

  15. Combined fMRI- and eye movement-based decoding of bistable plaid motion perception.

    Science.gov (United States)

    Wilbertz, Gregor; Ketkar, Madhura; Guggenmos, Matthias; Sterzer, Philipp

    2018-05-01

    The phenomenon of bistable perception, in which perception alternates spontaneously despite constant sensory stimulation, has been particularly useful in probing the neural bases of conscious perception. The study of such bistability requires access to the observer's perceptual dynamics, which is usually achieved via active report. This report, however, constitutes a confounding factor in the study of conscious perception and can also be biased in the context of certain experimental manipulations. One approach to circumvent these problems is to track perceptual alternations using signals from the eyes or the brain instead of observers' reports. Here we aimed to optimize such decoding of perceptual alternations by combining eye and brain signals. Eye-tracking and functional magnetic resonance imaging (fMRI) was performed in twenty participants while they viewed a bistable visual plaid motion stimulus and reported perceptual alternations. Multivoxel pattern analysis (MVPA) for fMRI was combined with eye-tracking in a Support vector machine to decode participants' perceptual time courses from fMRI and eye-movement signals. While both measures individually already yielded high decoding accuracies (on average 86% and 88% correct, respectively) classification based on the two measures together further improved the accuracy (91% correct). These findings show that leveraging on both fMRI and eye movement data may pave the way for optimized no-report paradigms through improved decodability of bistable motion perception and hence for a better understanding of the neural correlates of consciousness. Copyright © 2018 Elsevier Inc. All rights reserved.

  16. Functional MRI in the Investigation of Blast-Related Traumatic Brain Injury

    Science.gov (United States)

    Graner, John; Oakes, Terrence R.; French, Louis M.; Riedy, Gerard

    2012-01-01

    This review focuses on the application of functional magnetic resonance imaging (fMRI) to the investigation of blast-related traumatic brain injury (bTBI). Relatively little is known about the exact mechanisms of neurophysiological injury and pathological and functional sequelae of bTBI. Furthermore, in mild bTBI, standard anatomical imaging techniques (MRI and computed tomography) generally fail to show focal lesions and most of the symptoms present as subjective clinical functional deficits. Therefore, an objective test of brain functionality has great potential to aid in patient diagnosis and provide a sensitive measurement to monitor disease progression and treatment. The goal of this review is to highlight the relevant body of blast-related TBI literature and present suggestions and considerations in the development of fMRI studies for the investigation of bTBI. The review begins with a summary of recent bTBI publications followed by discussions of various elements of blast-related injury. Brief reviews of some fMRI techniques that focus on mental processes commonly disrupted by bTBI, including working memory, selective attention, and emotional processing, are presented in addition to a short review of resting state fMRI. Potential strengths and weaknesses of these approaches as regards bTBI are discussed. Finally, this review presents considerations that must be made when designing fMRI studies for bTBI populations, given the heterogeneous nature of bTBI and its high rate of comorbidity with other physical and psychological injuries. PMID:23460082

  17. An fMRI study of Agency

    DEFF Research Database (Denmark)

    Charalampaki, Angeliki

    2017-01-01

    Motor area has a distinct directionality, depending on the stage of the volitional movement. In this study, we were interested in assessing the neuronal mechanism underlying this phenomenon. We therefore performed an fMRI study of Agency, to exploit the high spatial resolution this imaging technique...... displays. For the purposes of our study twenty participants were recruited. The experimental procedure we considered appropriate to study the Sense of Agency, involved participants laying inside the fMRI scanner and while they had no visual feedback of their hand, they were instructed to draw straight...... lines on a tablet with a digital pen. They could only see the consequences of their movement as a cursor’s movement on a screen. After finishing their movement, participants were requested to make a judgment over whether they felt they were the Agent of the observed movement or not. The analysis of our...

  18. The dynamic programming high-order Dynamic Bayesian Networks learning for identifying effective connectivity in human brain from fMRI.

    Science.gov (United States)

    Dang, Shilpa; Chaudhury, Santanu; Lall, Brejesh; Roy, Prasun Kumar

    2017-06-15

    Determination of effective connectivity (EC) among brain regions using fMRI is helpful in understanding the underlying neural mechanisms. Dynamic Bayesian Networks (DBNs) are an appropriate class of probabilistic graphical temporal-models that have been used in past to model EC from fMRI, specifically order-one. High-order DBNs (HO-DBNs) have still not been explored for fMRI data. A fundamental problem faced in the structure-learning of HO-DBN is high computational-burden and low accuracy by the existing heuristic search techniques used for EC detection from fMRI. In this paper, we propose using dynamic programming (DP) principle along with integration of properties of scoring-function in a way to reduce search space for structure-learning of HO-DBNs and finally, for identifying EC from fMRI which has not been done yet to the best of our knowledge. The proposed exact search-&-score learning approach HO-DBN-DP is an extension of the technique which was originally devised for learning a BN's structure from static data (Singh and Moore, 2005). The effectiveness in structure-learning is shown on synthetic fMRI dataset. The algorithm reaches globally-optimal solution in appreciably reduced time-complexity than the static counterpart due to integration of properties. The proof of optimality is provided. The results demonstrate that HO-DBN-DP is comparably more accurate and faster than currently used structure-learning algorithms used for identifying EC from fMRI. The real data EC from HO-DBN-DP shows consistency with previous literature than the classical Granger Causality method. Hence, the DP algorithm can be employed for reliable EC estimates from experimental fMRI data. Copyright © 2017 Elsevier B.V. All rights reserved.

  19. The resting state fMRI study of patients with Parkinson's disease associated with cognitive dysfunction

    International Nuclear Information System (INIS)

    Feng Jieying; Huang Biao

    2013-01-01

    Parkinson's disease (PD) is the most common neurodegenerative cause of Parkinsonism, but the high morbidity of PD accompanied cognitive dysfunction hasn't drawn enough attention by the clinicians. With the rapid development of the resting state functional MRI (fMRI) technique, the cause of PD patients with cognitive dysfunction may be associated with the damage of functional connectivity of the motor networks and the cognitive networks. The relationship between neuropathologic mechanism of PD patients with cognitive dysfunction and impaired cognitive circuits will be disclosed by building the changes of brain topological structure in patients. The resting state fMRI study can provide the rationale for prevention, diagnosis and treatment of PD. (authors)

  20. Methodological principles for optimising functional MRI experiments

    International Nuclear Information System (INIS)

    Wuestenberg, T.; Giesel, F.L.; Strasburger, H.

    2005-01-01

    Functional magnetic resonance imaging (fMRI) is one of the most common methods for localising neuronal activity in the brain. Even though the sensitivity of fMRI is comparatively low, the optimisation of certain experimental parameters allows obtaining reliable results. In this article, approaches for optimising the experimental design, imaging parameters and analytic strategies will be discussed. Clinical neuroscientists and interested physicians will receive practical rules of thumb for improving the efficiency of brain imaging experiments. (orig.) [de

  1. Implicit structured sequence learning: an fMRI study of the structural mere-exposure effect.

    Science.gov (United States)

    Folia, Vasiliki; Petersson, Karl Magnus

    2014-01-01

    In this event-related fMRI study we investigated the effect of 5 days of implicit acquisition on preference classification by means of an artificial grammar learning (AGL) paradigm based on the structural mere-exposure effect and preference classification using a simple right-linear unification grammar. This allowed us to investigate implicit AGL in a proper learning design by including baseline measurements prior to grammar exposure. After 5 days of implicit acquisition, the fMRI results showed activations in a network of brain regions including the inferior frontal (centered on BA 44/45) and the medial prefrontal regions (centered on BA 8/32). Importantly, and central to this study, the inclusion of a naive preference fMRI baseline measurement allowed us to conclude that these fMRI findings were the intrinsic outcomes of the learning process itself and not a reflection of a preexisting functionality recruited during classification, independent of acquisition. Support for the implicit nature of the knowledge utilized during preference classification on day 5 come from the fact that the basal ganglia, associated with implicit procedural learning, were activated during classification, while the medial temporal lobe system, associated with explicit declarative memory, was consistently deactivated. Thus, preference classification in combination with structural mere-exposure can be used to investigate structural sequence processing (syntax) in unsupervised AGL paradigms with proper learning designs.

  2. A new concept of a unified parameter management, experiment control, and data analysis in fMRI: application to real-time fMRI at 3T and 7T.

    Science.gov (United States)

    Hollmann, M; Mönch, T; Mulla-Osman, S; Tempelmann, C; Stadler, J; Bernarding, J

    2008-10-30

    In functional MRI (fMRI) complex experiments and applications require increasingly complex parameter handling as the experimental setup usually consists of separated soft- and hardware systems. Advanced real-time applications such as neurofeedback-based training or brain computer interfaces (BCIs) may even require adaptive changes of the paradigms and experimental setup during the measurement. This would be facilitated by an automated management of the overall workflow and a control of the communication between all experimental components. We realized a concept based on an XML software framework called Experiment Description Language (EDL). All parameters relevant for real-time data acquisition, real-time fMRI (rtfMRI) statistical data analysis, stimulus presentation, and activation processing are stored in one central EDL file, and processed during the experiment. A usability study comparing the central EDL parameter management with traditional approaches showed an improvement of the complete experimental handling. Based on this concept, a feasibility study realizing a dynamic rtfMRI-based brain computer interface showed that the developed system in combination with EDL was able to reliably detect and evaluate activation patterns in real-time. The implementation of a centrally controlled communication between the subsystems involved in the rtfMRI experiments reduced potential inconsistencies, and will open new applications for adaptive BCIs.

  3. On clustering fMRI time series

    DEFF Research Database (Denmark)

    Goutte, Cyril; Toft, Peter Aundal; Rostrup, E.

    1999-01-01

    Analysis of fMRI time series is often performed by extracting one or more parameters for the individual voxels. Methods based, e.g., on various statistical tests are then used to yield parameters corresponding to probability of activation or activation strength. However, these methods do...

  4. Altered task-based and resting-state amygdala functional connectivity following real-time fMRI amygdala neurofeedback training in major depressive disorder.

    Science.gov (United States)

    Young, Kymberly D; Siegle, Greg J; Misaki, Masaya; Zotev, Vadim; Phillips, Raquel; Drevets, Wayne C; Bodurka, Jerzy

    2018-01-01

    We have previously shown that in participants with major depressive disorder (MDD) trained to upregulate their amygdala hemodynamic response during positive autobiographical memory (AM) recall with real-time fMRI neurofeedback (rtfMRI-nf) training, depressive symptoms diminish. Here, we assessed the effect of rtfMRI-nf on amygdala functional connectivity during both positive AM recall and rest. The current manuscript consists of a secondary analysis on data from our published clinical trial of neurofeedback. Patients with MDD completed two rtfMRI-nf sessions (18 received amygdala rtfMRI-nf, 16 received control parietal rtfMRI-nf). One-week prior-to and following training participants also completed a resting-state fMRI scan. A GLM-based functional connectivity analysis was applied using a seed ROI in the left amygdala. We compared amygdala functional connectivity changes while recalling positive AMs from the baseline run to the final transfer run during rtfMRI-nf training, as well during rest from the baseline to the one-week follow-up visit. Finally, we assessed the correlation between change in depression scores and change in amygdala connectivity, as well as correlations between amygdala regulation success and connectivity changes. Following training, amygdala connectivity during positive AM recall increased with widespread regions in the frontal and limbic network. During rest, amygdala connectivity increased following training within the fronto-temporal-limbic network. During both task and resting-state analyses, amygdala-temporal pole connectivity decreased. We identified increased amygdala-precuneus and amygdala-inferior frontal gyrus connectivity during positive memory recall and increased amygdala-precuneus and amygdala-thalamus connectivity during rest as functional connectivity changes that explained significant variance in symptom improvement. Amygdala-precuneus connectivity changes also explain a significant amount of variance in neurofeedback

  5. Voluntary Enhancement of Neural Signatures of Affiliative Emotion Using fMRI Neurofeedback

    Science.gov (United States)

    Moll, Jorge; Weingartner, Julie H.; Bado, Patricia; Basilio, Rodrigo; Sato, João R.; Melo, Bruno R.; Bramati, Ivanei E.; de Oliveira-Souza, Ricardo; Zahn, Roland

    2014-01-01

    In Ridley Scott’s film “Blade Runner”, empathy-detection devices are employed to measure affiliative emotions. Despite recent neurocomputational advances, it is unknown whether brain signatures of affiliative emotions, such as tenderness/affection, can be decoded and voluntarily modulated. Here, we employed multivariate voxel pattern analysis and real-time fMRI to address this question. We found that participants were able to use visual feedback based on decoded fMRI patterns as a neurofeedback signal to increase brain activation characteristic of tenderness/affection relative to pride, an equally complex control emotion. Such improvement was not observed in a control group performing the same fMRI task without neurofeedback. Furthermore, the neurofeedback-driven enhancement of tenderness/affection-related distributed patterns was associated with local fMRI responses in the septohypothalamic area and frontopolar cortex, regions previously implicated in affiliative emotion. This demonstrates that humans can voluntarily enhance brain signatures of tenderness/affection, unlocking new possibilities for promoting prosocial emotions and countering antisocial behavior. PMID:24847819

  6. Investigating Inhibitory Control in Children with Epilepsy: An fMRI Study

    Science.gov (United States)

    Triplett, Regina L.; Velanova, Katerina; Luna, Beatriz; Padmanabhan, Aarthi; Gaillard, William D.; Asato, Miya R.

    2014-01-01

    SUMMARY Objective Deficits in executive function are increasingly noted in children with epilepsy and have been associated with poor academic and psychosocial outcomes. Impaired inhibitory control contributes to executive dysfunction in children with epilepsy; however, its neuroanatomic basis has not yet been investigated. We used functional Magnetic Resonance Imaging (fMRI) to probe the integrity of activation in brain regions underlying inhibitory control in children with epilepsy. Methods This cross-sectional study consisted of 34 children aged 8 to 17 years: 17 with well-controlled epilepsy and 17 age-and sex-matched controls. Participants performed the antisaccade (AS) task, representative of inhibitory control, during fMRI scanning. We compared AS performance during neutral and reward task conditions and evaluated task-related blood-oxygen level dependent (BOLD) activation. Results Children with epilepsy demonstrated impaired AS performance compared to controls during both neutral (non-reward) and reward trials, but exhibited significant task improvement during reward trials. Post-hoc analysis revealed that younger patients made more errors than older patients and all controls. fMRI results showed preserved activation in task-relevant regions in patients and controls, with the exception of increased activation in the left posterior cingulate gyrus in patients specifically with generalized epilepsy across neutral and reward trials. Significance Despite impaired inhibitory control, children with epilepsy accessed typical neural pathways as did their peers without epilepsy. Children with epilepsy showed improved behavioral performance in response to the reward condition, suggesting potential benefits of the use of incentives in cognitive remediation. PMID:25223606

  7. An in vivo MRI template set for morphometry, tissue segmentation and fMRI localization in rats

    Directory of Open Access Journals (Sweden)

    Pedro Antonio Valdes Hernandez

    2011-11-01

    Full Text Available Over the last decade, several papers have focused on the construction of highly detailed mouse high field MRI templates via nonlinear registration to unbiased reference spaces, allowing for a variety of neuroimaging applications such as robust morphometric analyses. However, work in rats has only provided medium field MRI averages based on linear registration to biased spaces with the sole purpose of approximate fMRI localization. This precludes any morphometric analysis in spite of the need of exploring in detail the neuroanatomical substrates of diseases in a recent advent of rat models. In this paper we present a new in vivo rat T2 MRI template set, comprising average images of both intensity and shape, obtained via nonlinear registration. Also, unlike previous rat template sets, we include white and gray matter probabilistic segmentations, expanding its use to those applications demanding prior-based tissue segmentation, e.g. SPM voxel-based morphometry. We also provide a preliminary digitalization of latest Paxinos & Watson atlas for anatomical and functional interpretations within the cerebral cortex. We confirmed that, like with previous templates, forepaw and hindpaw fMRI activations can be correctly localized in the expected atlas structure. To exemplify the use of our new MRI template set, we reported the volumes of brain tissues and cortical structures and probed their relationships with ontogenetic development. Other in vivo applications in the near future can be tensor-, deformation- or voxel-based morphometry, morphological connectivity and diffusion tensor-based anatomical connectivity. Our template set, freely available through the SPM extension website, could be an important tool for future longitudinal and/or functional extensive preclinical studies.

  8. Identifying Subgroups of Tinnitus Using Novel Resting State fMRI Biomarkers and Cluster Analysis

    Science.gov (United States)

    2017-10-13

    psychological therapies or pharmacological drugs. 2. KEYWORDS: fMRI (functional magnetic resonance imaging), tinnitus, brain imaging, cluster analysis...9/2016). Details in next section.  6-9 months: • Task 2: Participant recruitment, participant evaluation, MRI and behavioral data acquisition 3...WHASC: N = 40 patients and 20 controls o For year 2 (at end of first 24 months) details see next section. • Task 4: Behavioral and MRI data

  9. Volumetric BOLD fMRI simulation: from neurovascular coupling to multivoxel imaging

    International Nuclear Information System (INIS)

    Chen, Zikuan; Calhoun, Vince

    2012-01-01

    The blood oxygenation-level dependent (BOLD) functional magnetic resonance imaging (fMRI) modality has been numerically simulated by calculating single voxel signals. However, the observation on single voxel signals cannot provide information regarding the spatial distribution of the signals. Specifically, a single BOLD voxel signal simulation cannot answer the fundamental question: is the magnetic resonance (MR) image a replica of its underling magnetic susceptibility source? In this paper, we address this problem by proposing a multivoxel volumetric BOLD fMRI simulation model and a susceptibility expression formula for linear neurovascular coupling process, that allow us to examine the BOLD fMRI procedure from neurovascular coupling to MR image formation. Since MRI technology only senses the magnetism property, we represent a linear neurovascular-coupled BOLD state by a magnetic susceptibility expression formula, which accounts for the parameters of cortical vasculature, intravascular blood oxygenation level, and local neuroactivity. Upon the susceptibility expression of a BOLD state, we carry out volumetric BOLD fMRI simulation by calculating the fieldmap (established by susceptibility magnetization) and the complex multivoxel MR image (by intravoxel dephasing). Given the predefined susceptibility source and the calculated complex MR image, we compare the MR magnitude (phase, respectively) image with the predefined susceptibility source (the calculated fieldmap) by spatial correlation. The spatial correlation between the MR magnitude image and the magnetic susceptibility source is about 0.90 for the settings of T E = 30 ms, B 0 = 3 T, voxel size = 100 micron, vessel radius = 3 micron, and blood volume fraction = 2%. Using these parameters value, the spatial correlation between the MR phase image and the susceptibility-induced fieldmap is close to 1.00. Our simulation results show that the MR magnitude image is not an exact replica of the magnetic susceptibility

  10. Efficient solution methodology for calibrating the hemodynamic model using functional Magnetic Resonance Imaging (fMRI) measurements

    KAUST Repository

    Zambri, Brian

    2015-11-05

    Our aim is to propose a numerical strategy for retrieving accurately and efficiently the biophysiological parameters as well as the external stimulus characteristics corresponding to the hemodynamic mathematical model that describes changes in blood flow and blood oxygenation during brain activation. The proposed method employs the TNM-CKF method developed in [1], but in a prediction/correction framework. We present numerical results using both real and synthetic functional Magnetic Resonance Imaging (fMRI) measurements to highlight the performance characteristics of this computational methodology. © 2015 IEEE.

  11. Efficient solution methodology for calibrating the hemodynamic model using functional Magnetic Resonance Imaging (fMRI) measurements

    KAUST Repository

    Zambri, Brian; Djellouli, Rabia; Laleg-Kirati, Taous-Meriem

    2015-01-01

    Our aim is to propose a numerical strategy for retrieving accurately and efficiently the biophysiological parameters as well as the external stimulus characteristics corresponding to the hemodynamic mathematical model that describes changes in blood flow and blood oxygenation during brain activation. The proposed method employs the TNM-CKF method developed in [1], but in a prediction/correction framework. We present numerical results using both real and synthetic functional Magnetic Resonance Imaging (fMRI) measurements to highlight the performance characteristics of this computational methodology. © 2015 IEEE.

  12. Collective Correlations of Brodmann Areas fMRI Study with RMT-Denoising

    Science.gov (United States)

    Burda, Z.; Kornelsen, J.; Nowak, M. A.; Porebski, B.; Sboto-Frankenstein, U.; Tomanek, B.; Tyburczyk, J.

    We study collective behavior of Brodmann regions of human cerebral cortex using functional Magnetic Resonance Imaging (fMRI) and Random Matrix Theory (RMT). The raw fMRI data is mapped onto the cortex regions corresponding to the Brodmann areas with the aid of the Talairach coordinates. Principal Component Analysis (PCA) of the Pearson correlation matrix for 41 different Brodmann regions is carried out to determine their collective activity in the idle state and in the active state stimulated by tapping. The collective brain activity is identified through the statistical analysis of the eigenvectors to the largest eigenvalues of the Pearson correlation matrix. The leading eigenvectors have a large participation ratio. This indicates that several Broadmann regions collectively give rise to the brain activity associated with these eigenvectors. We apply random matrix theory to interpret the underlying multivariate data.

  13. Generative embedding for model-based classification of fMRI data.

    Directory of Open Access Journals (Sweden)

    Kay H Brodersen

    2011-06-01

    Full Text Available Decoding models, such as those underlying multivariate classification algorithms, have been increasingly used to infer cognitive or clinical brain states from measures of brain activity obtained by functional magnetic resonance imaging (fMRI. The practicality of current classifiers, however, is restricted by two major challenges. First, due to the high data dimensionality and low sample size, algorithms struggle to separate informative from uninformative features, resulting in poor generalization performance. Second, popular discriminative methods such as support vector machines (SVMs rarely afford mechanistic interpretability. In this paper, we address these issues by proposing a novel generative-embedding approach that incorporates neurobiologically interpretable generative models into discriminative classifiers. Our approach extends previous work on trial-by-trial classification for electrophysiological recordings to subject-by-subject classification for fMRI and offers two key advantages over conventional methods: it may provide more accurate predictions by exploiting discriminative information encoded in 'hidden' physiological quantities such as synaptic connection strengths; and it affords mechanistic interpretability of clinical classifications. Here, we introduce generative embedding for fMRI using a combination of dynamic causal models (DCMs and SVMs. We propose a general procedure of DCM-based generative embedding for subject-wise classification, provide a concrete implementation, and suggest good-practice guidelines for unbiased application of generative embedding in the context of fMRI. We illustrate the utility of our approach by a clinical example in which we classify moderately aphasic patients and healthy controls using a DCM of thalamo-temporal regions during speech processing. Generative embedding achieves a near-perfect balanced classification accuracy of 98% and significantly outperforms conventional activation-based and

  14. Robust extrapolation scheme for fast estimation of 3D Ising field partition functions: application to within subject fMRI data

    Energy Technology Data Exchange (ETDEWEB)

    Risser, L.; Vincent, T.; Ciuciu, Ph. [NeuroSpin CEA, F-91191 Gif sur Yvette (France); Risser, L.; Vincent, T. [Laboratoire de Neuroimagerie Assistee par Ordinateur (LNAO) CEA - DSV/I2BM/NEUROSPIN (France); Risser, L. [Institut de mecanique des fluides de Toulouse (IMFT), CNRS: UMR5502 - Universite Paul Sabatier - Toulouse III - Institut National Polytechnique de Toulouse - INPT (France); Idier, J. [Institut de Recherche en Communications et en Cybernetique de Nantes (IRCCyN) CNRS - UMR6597 - Universite de Nantes - ecole Centrale de Nantes - Ecole des Mines de Nantes - Ecole Polytechnique de l' Universite de Nantes (France)

    2009-07-01

    In this paper, we present a first numerical scheme to estimate Partition Functions (PF) of 3D Ising fields. Our strategy is applied to the context of the joint detection-estimation of brain activity from functional Magnetic Resonance Imaging (fMRI) data, where the goal is to automatically recover activated regions and estimate region-dependent, hemodynamic filters. For any region, a specific binary Markov random field may embody spatial correlation over the hidden states of the voxels by modeling whether they are activated or not. To make this spatial regularization fully adaptive, our approach is first based upon it, classical path-sampling method to approximate a small subset of reference PFs corresponding to pre-specified regions. Then, file proposed extrapolation method allows its to approximate the PFs associated with the Ising fields defined over the remaining brain regions. In comparison with preexisting approaches, our method is robust; to topological inhomogeneities in the definition of the reference regions. As a result, it strongly alleviates the computational burden and makes spatially adaptive regularization of whole brain fMRI datasets feasible. (authors)

  15. A wavelet method for modeling and despiking motion artifacts from resting-state fMRI time series

    Science.gov (United States)

    Patel, Ameera X.; Kundu, Prantik; Rubinov, Mikail; Jones, P. Simon; Vértes, Petra E.; Ersche, Karen D.; Suckling, John; Bullmore, Edward T.

    2014-01-01

    The impact of in-scanner head movement on functional magnetic resonance imaging (fMRI) signals has long been established as undesirable. These effects have been traditionally corrected by methods such as linear regression of head movement parameters. However, a number of recent independent studies have demonstrated that these techniques are insufficient to remove motion confounds, and that even small movements can spuriously bias estimates of functional connectivity. Here we propose a new data-driven, spatially-adaptive, wavelet-based method for identifying, modeling, and removing non-stationary events in fMRI time series, caused by head movement, without the need for data scrubbing. This method involves the addition of just one extra step, the Wavelet Despike, in standard pre-processing pipelines. With this method, we demonstrate robust removal of a range of different motion artifacts and motion-related biases including distance-dependent connectivity artifacts, at a group and single-subject level, using a range of previously published and new diagnostic measures. The Wavelet Despike is able to accommodate the substantial spatial and temporal heterogeneity of motion artifacts and can consequently remove a range of high and low frequency artifacts from fMRI time series, that may be linearly or non-linearly related to physical movements. Our methods are demonstrated by the analysis of three cohorts of resting-state fMRI data, including two high-motion datasets: a previously published dataset on children (N = 22) and a new dataset on adults with stimulant drug dependence (N = 40). We conclude that there is a real risk of motion-related bias in connectivity analysis of fMRI data, but that this risk is generally manageable, by effective time series denoising strategies designed to attenuate synchronized signal transients induced by abrupt head movements. The Wavelet Despiking software described in this article is freely available for download at www

  16. Comparison of semantic and episodic memory BOLD fMRI activation in predicting cognitive decline in older adults.

    Science.gov (United States)

    Hantke, Nathan; Nielson, Kristy A; Woodard, John L; Breting, Leslie M Guidotti; Butts, Alissa; Seidenberg, Michael; Carson Smith, J; Durgerian, Sally; Lancaster, Melissa; Matthews, Monica; Sugarman, Michael A; Rao, Stephen M

    2013-01-01

    Previous studies suggest that task-activated functional magnetic resonance imaging (fMRI) can predict future cognitive decline among healthy older adults. The present fMRI study examined the relative sensitivity of semantic memory (SM) versus episodic memory (EM) activation tasks for predicting cognitive decline. Seventy-eight cognitively intact elders underwent neuropsychological testing at entry and after an 18-month interval, with participants classified as cognitively "Stable" or "Declining" based on ≥ 1.0 SD decline in performance. Baseline fMRI scanning involved SM (famous name discrimination) and EM (name recognition) tasks. SM and EM fMRI activation, along with Apolipoprotein E (APOE) ε4 status, served as predictors of cognitive outcome using a logistic regression analysis. Twenty-seven (34.6%) participants were classified as Declining and 51 (65.4%) as Stable. APOE ε4 status alone significantly predicted cognitive decline (R(2) = .106; C index = .642). Addition of SM activation significantly improved prediction accuracy (R(2) = .285; C index = .787), whereas the addition of EM did not (R(2) = .212; C index = .711). In combination with APOE status, SM task activation predicts future cognitive decline better than EM activation. These results have implications for use of fMRI in prevention clinical trials involving the identification of persons at-risk for age-associated memory loss and Alzheimer's disease.

  17. Disrupted Cerebro-cerebellar Intrinsic Functional Connectivity in Young Adults with High-functioning Autism Spectrum Disorder: A Data-driven, Whole-brain, High Temporal Resolution fMRI Study.

    Science.gov (United States)

    Arnold Anteraper, Sheeba; Guell, Xavier; D'Mello, Anila; Joshi, Neha; Whitfield-Gabrieli, Susan; Joshi, Gagan

    2018-06-13

    To examine the resting-state functional-connectivity (RsFc) in young adults with high-functioning autism spectrum disorder (HF-ASD) using state-of-the-art fMRI data acquisition and analysis techniques. Simultaneous multi-slice, high temporal resolution fMRI acquisition; unbiased whole-brain connectome-wide multivariate pattern analysis (MVPA) techniques for assessing RsFc; and post-hoc whole-brain seed-to-voxel analyses using MVPA results as seeds. MVPA revealed two clusters of abnormal connectivity in the cerebellum. Whole-brain seed-based functional connectivity analyses informed by MVPA-derived clusters showed significant under connectivity between the cerebellum and social, emotional, and language brain regions in the HF-ASD group compared to healthy controls. The results we report are coherent with existing structural, functional, and RsFc literature in autism, extend previous literature reporting cerebellar abnormalities in the neuropathology of autism, and highlight the cerebellum as a potential target for therapeutic, diagnostic, predictive, and prognostic developments in ASD. The description of functional connectivity abnormalities using whole-brain, data-driven analyses as reported in the present study may crucially advance the development of ASD biomarkers, targets for therapeutic interventions, and neural predictors for measuring treatment response.

  18. Potential pitfalls when denoising resting state fMRI data using nuisance regression.

    Science.gov (United States)

    Bright, Molly G; Tench, Christopher R; Murphy, Kevin

    2017-07-01

    In resting state fMRI, it is necessary to remove signal variance associated with noise sources, leaving cleaned fMRI time-series that more accurately reflect the underlying intrinsic brain fluctuations of interest. This is commonly achieved through nuisance regression, in which the fit is calculated of a noise model of head motion and physiological processes to the fMRI data in a General Linear Model, and the "cleaned" residuals of this fit are used in further analysis. We examine the statistical assumptions and requirements of the General Linear Model, and whether these are met during nuisance regression of resting state fMRI data. Using toy examples and real data we show how pre-whitening, temporal filtering and temporal shifting of regressors impact model fit. Based on our own observations, existing literature, and statistical theory, we make the following recommendations when employing nuisance regression: pre-whitening should be applied to achieve valid statistical inference of the noise model fit parameters; temporal filtering should be incorporated into the noise model to best account for changes in degrees of freedom; temporal shifting of regressors, although merited, should be achieved via optimisation and validation of a single temporal shift. We encourage all readers to make simple, practical changes to their fMRI denoising pipeline, and to regularly assess the appropriateness of the noise model used. By negotiating the potential pitfalls described in this paper, and by clearly reporting the details of nuisance regression in future manuscripts, we hope that the field will achieve more accurate and precise noise models for cleaning the resting state fMRI time-series. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  19. Brain Activities Associated with Graphic Emoticons: An fMRI Study

    Science.gov (United States)

    Yuasa, Masahide; Saito, Keiichi; Mukawa, Naoki

    In this paper, we describe the brain activities that are associated with graphic emoticons by using functional MRI (fMRI). We use various types of faces from abstract to photorealistic in computer network applications. A graphics emoticon is an abstract face in communication over computer network. In this research, we created various graphic emoticons for the fMRI study and the graphic emoticons were classified according to friendliness and level of arousal. We investigated the brain activities of participants who were required to evaluate the emotional valence of the graphic emoticons (happy or sad). The experimental results showed that not only the right inferior frontal gyrus and the cingulate gyrus, but also the inferior and middle temporal gyrus and the fusiform gyrus, were found to be activated during the experiment. Forthermore, it is possible that the activation of the right inferior frontal gyrus and the cingulate gyrus is related to the type of abstract face. Since the inferior and middle temporal gyrus were activated, even though the graphic emoticons are static, we may perceive graphic emoticons as dynamic and living agents. Moreover, it is believed that text and graphics emoticons play an important role in enriching communication among users.

  20. Abnormal baseline brain activity in patients with neuromyelitis optica: A resting-state fMRI study

    International Nuclear Information System (INIS)

    Liu Yaou; Liang Peipeng; Duan Yunyun; Jia Xiuqin; Wang Fei; Yu Chunshui; Qin Wen; Dong Huiqing; Ye Jing; Li Kuncheng

    2011-01-01

    Purpose: Recent immunopathologic and MRI findings suggest that tissue damage in neuromyelitis optica (NMO) is not limited to spinal cord and optic nerve, but also in brain. Baseline brain activity can reveal the brain functional changes to the tissue damages and give clues to the pathophysiology of NMO, however, it has never been explored by resting-state functional MRI (fMRI). We used regional amplitude of low frequency fluctuation (ALFF) as an index in resting-state fMRI to investigate how baseline brain activity changes in patients with NMO. Methods: Resting-state fMRIs collected from seventeen NMO patients and seventeen age- and sex-matched normal controls were compared to investigate the ALFF difference between the two groups. The relationships between ALFF in regions with significant group differences and the EDSS (Expanded Disability Status Scale), disease duration were further explored. Results: Our results showed that NMO patients had significantly decreased ALFF in precuneus, posterior cingulate cortex (PCC) and lingual gyrus; and increased ALFF in middle frontal gyrus, caudate nucleus and thalamus, compared to normal controls. Moderate negative correlations were found between the EDSS and ALFF in the left middle frontal gyrus (r = -0.436, p = 0.040) and the left caudate (r = -0.542, p = 0.012). Conclusion: The abnormal baseline brain activity shown by resting-state fMRI in NMO is relevant to cognition, visual and motor systems. It implicates a complex baseline brain status of both functional impairments and adaptations caused by tissue damages in these systems, which gives clues to the pathophysiology of NMO.

  1. Abnormal baseline brain activity in patients with neuromyelitis optica: A resting-state fMRI study

    Energy Technology Data Exchange (ETDEWEB)

    Liu Yaou [Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing 100053 (China); Liang Peipeng [Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing 100053 (China); International WIC institute, Beijing University of Technology, Beijing 100024 (China); Duan Yunyun; Jia Xiuqin; Wang Fei; Yu Chunshui; Qin Wen [Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing 100053 (China); Dong Huiqing; Ye Jing [Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053 (China); Li Kuncheng, E-mail: likuncheng1955@yahoo.com.cn [Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing 100053 (China)

    2011-11-15

    Purpose: Recent immunopathologic and MRI findings suggest that tissue damage in neuromyelitis optica (NMO) is not limited to spinal cord and optic nerve, but also in brain. Baseline brain activity can reveal the brain functional changes to the tissue damages and give clues to the pathophysiology of NMO, however, it has never been explored by resting-state functional MRI (fMRI). We used regional amplitude of low frequency fluctuation (ALFF) as an index in resting-state fMRI to investigate how baseline brain activity changes in patients with NMO. Methods: Resting-state fMRIs collected from seventeen NMO patients and seventeen age- and sex-matched normal controls were compared to investigate the ALFF difference between the two groups. The relationships between ALFF in regions with significant group differences and the EDSS (Expanded Disability Status Scale), disease duration were further explored. Results: Our results showed that NMO patients had significantly decreased ALFF in precuneus, posterior cingulate cortex (PCC) and lingual gyrus; and increased ALFF in middle frontal gyrus, caudate nucleus and thalamus, compared to normal controls. Moderate negative correlations were found between the EDSS and ALFF in the left middle frontal gyrus (r = -0.436, p = 0.040) and the left caudate (r = -0.542, p = 0.012). Conclusion: The abnormal baseline brain activity shown by resting-state fMRI in NMO is relevant to cognition, visual and motor systems. It implicates a complex baseline brain status of both functional impairments and adaptations caused by tissue damages in these systems, which gives clues to the pathophysiology of NMO.

  2. A Hybrid Machine Learning Method for Fusing fMRI and Genetic Data: Combining both Improves Classification of Schizophrenia

    Directory of Open Access Journals (Sweden)

    Honghui Yang

    2010-10-01

    Full Text Available We demonstrate a hybrid machine learning method to classify schizophrenia patients and healthy controls, using functional magnetic resonance imaging (fMRI and single nucleotide polymorphism (SNP data. The method consists of four stages: (1 SNPs with the most discriminating information between the healthy controls and schizophrenia patients are selected to construct a support vector machine ensemble (SNP-SVME. (2 Voxels in the fMRI map contributing to classification are selected to build another SVME (Voxel-SVME. (3 Components of fMRI activation obtained with independent component analysis (ICA are used to construct a single SVM classifier (ICA-SVMC. (4 The above three models are combined into a single module using a majority voting approach to make a final decision (Combined SNP-fMRI. The method was evaluated by a fully-validated leave-one-out method using 40 subjects (20 patients and 20 controls. The classification accuracy was: 0.74 for SNP-SVME, 0.82 for Voxel-SVME, 0.83 for ICA-SVMC, and 0.87 for Combined SNP-fMRI. Experimental results show that better classification accuracy was achieved by combining genetic and fMRI data than using either alone, indicating that genetic and brain function representing different, but partially complementary aspects, of schizophrenia etiopathology. This study suggests an effective way to reassess biological classification of individuals with schizophrenia, which is also potentially useful for identifying diagnostically important markers for the disorder.

  3. BOLDSync: a MATLAB-based toolbox for synchronized stimulus presentation in functional MRI.

    Science.gov (United States)

    Joshi, Jitesh; Saharan, Sumiti; Mandal, Pravat K

    2014-02-15

    Precise and synchronized presentation of paradigm stimuli in functional magnetic resonance imaging (fMRI) is central to obtaining accurate information about brain regions involved in a specific task. In this manuscript, we present a new MATLAB-based toolbox, BOLDSync, for synchronized stimulus presentation in fMRI. BOLDSync provides a user friendly platform for design and presentation of visual, audio, as well as multimodal audio-visual (AV) stimuli in functional imaging experiments. We present simulation experiments that demonstrate the millisecond synchronization accuracy of BOLDSync, and also illustrate the functionalities of BOLDSync through application to an AV fMRI study. BOLDSync gains an advantage over other available proprietary and open-source toolboxes by offering a user friendly and accessible interface that affords both precision in stimulus presentation and versatility across various types of stimulus designs and system setups. BOLDSync is a reliable, efficient, and versatile solution for synchronized stimulus presentation in fMRI study. Copyright © 2013 Elsevier B.V. All rights reserved.

  4. Cortical language activation in aphasia: a functional MRI study

    International Nuclear Information System (INIS)

    Xu Xiaojun; Zhang Minming; Shang Desheng; Wang Qidong; Luo Benyan

    2004-01-01

    Objective: To investigate the differences of the underlying neural basis of language processing between normal subjects and aphasics, and to study the feasibility for functional magnetic resonance imaging (fMRI) in examining the cortical language activation in clinical aphasics. Methods: fMRI was used to map language network in 6 normal subjects and 3 patients with aphasia who were in the stage of recovery from acute stroke. The participants performed word generation task during fMRI scanning, which measured the signal changes associated with regional neural activity induced by the task. These signal changes were processed to statistically generate the activation map that represented the language area. Results: In normal subjects, a distributed language network was activated. Activations were present in the frontal, temporal, parietal and occipital regions in normal group. In the patient group, however, no activation was showed in the left inferior frontal gyrus whether or not the patient had lesion in the left frontal lobe. Two patients showed activations in some right hemisphere regions where no activation appeared in normal subjects. Conclusion: The remote effect of focal lesion and functional redistribution or reorganization was found in aphasic patients. fMRI was useful in evaluating the language function in aphasic patients. (authors)

  5. Measurement and imaging of brain function using MRI, MEG, and TMS

    International Nuclear Information System (INIS)

    Iramina, Keiji

    2008-01-01

    This paper reviews functional imaging techniques in neuroscience such as magnetic resonance imaging (MRI) functional MRI (fMRI), magnetoencephalogray (MEG), and transcranial magnetic stimulation (TMS). fMRI and MEG allow the neuronal activity of the brain to be measured non-invasively. MEG detects an electrical activity as neuronal activity, while, fMRI detects a hemodynamic response as neuronal activity. TMS is the application of a brief magnetic pulse or a train of pulses to the skull, which results in the induction of a local electric current in the underlying surface of the brain, thereby producing a localized axonal depolarization. As a non-invasive and effective method to make reversible lesions in the human brain, TMS has a long and successful history. All of these techniques have major potential for applications in the neuroscience and medicine. (author)

  6. Functional MRI in pre-surgical planning: Case study and cautionary notes

    Directory of Open Access Journals (Sweden)

    Bruce S Spottiswoode

    2012-09-01

    Full Text Available Background. Since its inception almost 20 years ago, functional magnetic resonance imaging (fMRI has greatly advanced our knowledge of human brain function. Although the clinical applications of fMRI are still limited, there have recently been encouraging advances for its use in pre-operative functional cortical mapping to identify potentially eloquent areas prior to neurosurgery. Objectives. We explore the potential use of this emerging technique by presenting a neurosurgical case study, as performed at the Cape Universities Brain Imaging Centre (CUBIC, Tygerberg, Cape Town. We conclude with a brief summary of the potential pitfalls of this technique, as well as cautionary guidelines based on our experience. Methods and results. A 22-year-old male patient from Tygerberg Hospital underwent the successful resection of an anaplastic astrocytoma after fMRI presurgical planning at our facility. The subject was able to leave the ward unassisted. Conclusion. If consideration is given to the many limitations of this emerging technique, fMRI can be useful in aiding the neurosurgeon in pre-operative planning of his surgical approach.

  7. ICN_Atlas: Automated description and quantification of functional MRI activation patterns in the framework of intrinsic connectivity networks.

    Science.gov (United States)

    Kozák, Lajos R; van Graan, Louis André; Chaudhary, Umair J; Szabó, Ádám György; Lemieux, Louis

    2017-12-01

    Generally, the interpretation of functional MRI (fMRI) activation maps continues to rely on assessing their relationship to anatomical structures, mostly in a qualitative and often subjective way. Recently, the existence of persistent and stable brain networks of functional nature has been revealed; in particular these so-called intrinsic connectivity networks (ICNs) appear to link patterns of resting state and task-related state connectivity. These networks provide an opportunity of functionally-derived description and interpretation of fMRI maps, that may be especially important in cases where the maps are predominantly task-unrelated, such as studies of spontaneous brain activity e.g. in the case of seizure-related fMRI maps in epilepsy patients or sleep states. Here we present a new toolbox (ICN_Atlas) aimed at facilitating the interpretation of fMRI data in the context of ICN. More specifically, the new methodology was designed to describe fMRI maps in function-oriented, objective and quantitative way using a set of 15 metrics conceived to quantify the degree of 'engagement' of ICNs for any given fMRI-derived statistical map of interest. We demonstrate that the proposed framework provides a highly reliable quantification of fMRI activation maps using a publicly available longitudinal (test-retest) resting-state fMRI dataset. The utility of the ICN_Atlas is also illustrated on a parametric task-modulation fMRI dataset, and on a dataset of a patient who had repeated seizures during resting-state fMRI, confirmed on simultaneously recorded EEG. The proposed ICN_Atlas toolbox is freely available for download at http://icnatlas.com and at http://www.nitrc.org for researchers to use in their fMRI investigations. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  8. Pinpointing Synaptic Loss Caused by Alzheimer?s Disease with fMRI

    OpenAIRE

    Brickman, Adam M.; Small, Scott A.; Fleisher, Adam

    2009-01-01

    During its earliest stage, before cell loss and independent of amyloid plaques and neurofibrillary tangles, Alzheimer's disease (AD) causes synaptic loss affecting the basal functional properties of neurons. In principle, synaptic loss can be detected by measuring AD-induced changes in basal function, or by measuring stimulus-evoked responses on top of basal changes. Functional magnetic resonance imaging (fMRI) is sensitive to both basal changes and evoked-responses, and there are therefore t...

  9. Statistical Analysis of fMRI Time-Series: A Critical Review of the GLM Approach

    Directory of Open Access Journals (Sweden)

    Martin M Monti

    2011-03-01

    Full Text Available Functional Magnetic Resonance Imaging (fMRI is one of the most widely used tools to study the neural underpinnings of human cognition. Standard analysis of fMRI data relies on a General Linear Model (GLM approach to separate stimulus induced signals from noise. Crucially, this approach relies on a number of assumptions about the data which, for inferences to be valid, must be met. The current paper reviews the GLM approach to analysis of fMRI time-series, focusing in particular on the degree to which such data abides by the assumptions of the GLM framework, and on the methods that have been developed to correct for any violation of those assumptions. Rather than biasing estimates of effect size, the major consequence of non-conformity to the assumptions is to introduce bias into estimates of the variance, thus affecting test statistics, power and false positive rates. Furthermore, this bias can have pervasive effects on both individual subject and group-level statistics, potentially yielding qualitatively different results across replications, especially after the thresholding procedures commonly used for inference-making.

  10. Hypercapnic evaluation of vascular reactivity in healthy aging and acute stroke via functional MRI.

    Science.gov (United States)

    Raut, Ryan V; Nair, Veena A; Sattin, Justin A; Prabhakaran, Vivek

    2016-01-01

    Functional MRI (fMRI) is well-established for the study of brain function in healthy populations, although its clinical application has proven more challenging. Specifically, cerebrovascular reactivity (CVR), which allows the assessment of the vascular response that serves as the basis for fMRI, has been shown to be reduced in healthy aging as well as in a range of diseases, including chronic stroke. However, the timing of when this occurs relative to the stroke event is unclear. We used a breath-hold fMRI task to evaluate CVR across gray matter in a group of acute stroke patients (< 10 days from stroke; N = 22) to address this question. These estimates were compared with those from both age-matched (N = 22) and younger (N = 22) healthy controls. As expected, young controls had the greatest mean CVR, as indicated by magnitude and extent of fMRI activation; however, stroke patients did not differ from age-matched controls. Moreover, the ipsilesional and contralesional hemispheres of stroke patients did not differ with respect to any of these measures. These findings suggest that fMRI remains a valid tool within the first few days of a stroke, particularly for group fMRI studies in which findings are compared with healthy subjects of similar age. However, given the relatively high variability in CVR observed in our stroke sample, caution is warranted when interpreting fMRI data from individual patients or a small cohort. We conclude that a breath-hold task can be a useful addition to functional imaging protocols for stroke patients.

  11. An fMRI Study of the Social Competition in Healthy Subjects

    Science.gov (United States)

    Polosan, M.; Baciu, M.; Cousin, E.; Perrone, M.; Pichat, C.; Bougerol, T.

    2011-01-01

    Social interaction requires the ability to infer another person's mental state (Theory of Mind, ToM) and also executive functions. This fMRI study aimed to identify the cerebral correlates activated by ToM during a specific social interaction, the human-human competition. In this framework, we tested a conflict resolution task (Stroop) adapted to…

  12. SCGICAR: Spatial concatenation based group ICA with reference for fMRI data analysis.

    Science.gov (United States)

    Shi, Yuhu; Zeng, Weiming; Wang, Nizhuan

    2017-09-01

    With the rapid development of big data, the functional magnetic resonance imaging (fMRI) data analysis of multi-subject is becoming more and more important. As a kind of blind source separation technique, group independent component analysis (GICA) has been widely applied for the multi-subject fMRI data analysis. However, spatial concatenated GICA is rarely used compared with temporal concatenated GICA due to its disadvantages. In this paper, in order to overcome these issues and to consider that the ability of GICA for fMRI data analysis can be improved by adding a priori information, we propose a novel spatial concatenation based GICA with reference (SCGICAR) method to take advantage of the priori information extracted from the group subjects, and then the multi-objective optimization strategy is used to implement this method. Finally, the post-processing means of principal component analysis and anti-reconstruction are used to obtain group spatial component and individual temporal component in the group, respectively. The experimental results show that the proposed SCGICAR method has a better performance on both single-subject and multi-subject fMRI data analysis compared with classical methods. It not only can detect more accurate spatial and temporal component for each subject of the group, but also can obtain a better group component on both temporal and spatial domains. These results demonstrate that the proposed SCGICAR method has its own advantages in comparison with classical methods, and it can better reflect the commonness of subjects in the group. Copyright © 2017 Elsevier B.V. All rights reserved.

  13. Ridding fMRI data of motion-related influences: Removal of signals with distinct spatial and physical bases in multiecho data.

    Science.gov (United States)

    Power, Jonathan D; Plitt, Mark; Gotts, Stephen J; Kundu, Prantik; Voon, Valerie; Bandettini, Peter A; Martin, Alex

    2018-02-27

    "Functional connectivity" techniques are commonplace tools for studying brain organization. A critical element of these analyses is to distinguish variance due to neurobiological signals from variance due to nonneurobiological signals. Multiecho fMRI techniques are a promising means for making such distinctions based on signal decay properties. Here, we report that multiecho fMRI techniques enable excellent removal of certain kinds of artifactual variance, namely, spatially focal artifacts due to motion. By removing these artifacts, multiecho techniques reveal frequent, large-amplitude blood oxygen level-dependent (BOLD) signal changes present across all gray matter that are also linked to motion. These whole-brain BOLD signals could reflect widespread neural processes or other processes, such as alterations in blood partial pressure of carbon dioxide (pCO 2 ) due to ventilation changes. By acquiring multiecho data while monitoring breathing, we demonstrate that whole-brain BOLD signals in the resting state are often caused by changes in breathing that co-occur with head motion. These widespread respiratory fMRI signals cannot be isolated from neurobiological signals by multiecho techniques because they occur via the same BOLD mechanism. Respiratory signals must therefore be removed by some other technique to isolate neurobiological covariance in fMRI time series. Several methods for removing global artifacts are demonstrated and compared, and were found to yield fMRI time series essentially free of motion-related influences. These results identify two kinds of motion-associated fMRI variance, with different physical mechanisms and spatial profiles, each of which strongly and differentially influences functional connectivity patterns. Distance-dependent patterns in covariance are nearly entirely attributable to non-BOLD artifacts.

  14. Network analysis of functional brain connectivity in borderline personality disorder using resting-state fMRI.

    Science.gov (United States)

    Xu, Tingting; Cullen, Kathryn R; Mueller, Bryon; Schreiner, Mindy W; Lim, Kelvin O; Schulz, S Charles; Parhi, Keshab K

    2016-01-01

    Borderline personality disorder (BPD) is associated with symptoms such as affect dysregulation, impaired sense of self, and self-harm behaviors. Neuroimaging research on BPD has revealed structural and functional abnormalities in specific brain regions and connections. However, little is known about the topological organizations of brain networks in BPD. We collected resting-state functional magnetic resonance imaging (fMRI) data from 20 patients with BPD and 10 healthy controls, and constructed frequency-specific functional brain networks by correlating wavelet-filtered fMRI signals from 82 cortical and subcortical regions. We employed graph-theory based complex network analysis to investigate the topological properties of the brain networks, and employed network-based statistic to identify functional dysconnections in patients. In the 0.03-0.06 Hz frequency band, compared to controls, patients with BPD showed significantly larger measures of global network topology, including the size of largest connected graph component, clustering coefficient, small-worldness, and local efficiency, indicating increased local cliquishness of the functional brain network. Compared to controls, patients showed lower nodal centrality at several hub nodes but greater centrality at several non-hub nodes in the network. Furthermore, an interconnected subnetwork in 0.03-0.06 Hz frequency band was identified that showed significantly lower connectivity in patients. The links in the subnetwork were mainly long-distance connections between regions located at different lobes; and the mean connectivity of this subnetwork was negatively correlated with the increased global topology measures. Lastly, the key network measures showed high correlations with several clinical symptom scores, and classified BPD patients against healthy controls with high accuracy based on linear discriminant analysis. The abnormal topological properties and connectivity found in this study may add new knowledge

  15. Network analysis of functional brain connectivity in borderline personality disorder using resting-state fMRI

    Directory of Open Access Journals (Sweden)

    Tingting Xu

    2016-01-01

    Full Text Available Borderline personality disorder (BPD is associated with symptoms such as affect dysregulation, impaired sense of self, and self-harm behaviors. Neuroimaging research on BPD has revealed structural and functional abnormalities in specific brain regions and connections. However, little is known about the topological organizations of brain networks in BPD. We collected resting-state functional magnetic resonance imaging (fMRI data from 20 patients with BPD and 10 healthy controls, and constructed frequency-specific functional brain networks by correlating wavelet-filtered fMRI signals from 82 cortical and subcortical regions. We employed graph-theory based complex network analysis to investigate the topological properties of the brain networks, and employed network-based statistic to identify functional dysconnections in patients. In the 0.03–0.06 Hz frequency band, compared to controls, patients with BPD showed significantly larger measures of global network topology, including the size of largest connected graph component, clustering coefficient, small-worldness, and local efficiency, indicating increased local cliquishness of the functional brain network. Compared to controls, patients showed lower nodal centrality at several hub nodes but greater centrality at several non-hub nodes in the network. Furthermore, an interconnected subnetwork in 0.03–0.06 Hz frequency band was identified that showed significantly lower connectivity in patients. The links in the subnetwork were mainly long-distance connections between regions located at different lobes; and the mean connectivity of this subnetwork was negatively correlated with the increased global topology measures. Lastly, the key network measures showed high correlations with several clinical symptom scores, and classified BPD patients against healthy controls with high accuracy based on linear discriminant analysis. The abnormal topological properties and connectivity found in this study

  16. Evaluation of various somatosensory stimulations for functional MRI

    International Nuclear Information System (INIS)

    Hara, Kazushi; Nakasato, Nobukazu; Mizoi, Kazuo; Yoshimoto, Takashi; Shimizu, Hiroaki.

    1997-01-01

    The aim of this functional magnetic resonance imaging (fMRI) study was to test detectability of activated area using various somatosensory stimulations. The following stimulations were performed in normal volunteers: regular or irregular electrical median nerve stimulation (n=5, each), tactile stimulation to the palm and fingers (n=8), pain stimulation to the index finger (n=5) or to the palm and fingers (n=5). fMRI was acquired with a spoiled gradient echo sequence at 1.5 T. Detectability of activated area was the highest when the pain stimulation was applied to the palm and fingers (80%). A successful rate for the tactile stimulation was 25%, and the other stimulations failed to demonstrate any activation. When successful, the highest signal activation on fMRI was seen on a sulcus, which presumably arose from a vein. The sulcus was defined as the central sulcus by somatosensory evoked field using a median nerve stimulation. Our study indicates that the pain stimulation to the palm and fingers may be a choice for the sensory fMRI. (author)

  17. Human brain functional MRI and DTI visualization with virtual reality.

    Science.gov (United States)

    Chen, Bin; Moreland, John; Zhang, Jingyu

    2011-12-01

    Magnetic resonance diffusion tensor imaging (DTI) and functional MRI (fMRI) are two active research areas in neuroimaging. DTI is sensitive to the anisotropic diffusion of water exerted by its macromolecular environment and has been shown useful in characterizing structures of ordered tissues such as the brain white matter, myocardium, and cartilage. The diffusion tensor provides two new types of information of water diffusion: the magnitude and the spatial orientation of water diffusivity inside the tissue. This information has been used for white matter fiber tracking to review physical neuronal pathways inside the brain. Functional MRI measures brain activations using the hemodynamic response. The statistically derived activation map corresponds to human brain functional activities caused by neuronal activities. The combination of these two methods provides a new way to understand human brain from the anatomical neuronal fiber connectivity to functional activities between different brain regions. In this study, virtual reality (VR) based MR DTI and fMRI visualization with high resolution anatomical image segmentation and registration, ROI definition and neuronal white matter fiber tractography visualization and fMRI activation map integration is proposed. Rationale and methods for producing and distributing stereoscopic videos are also discussed.

  18. Early disrupted neurovascular coupling and changed event level hemodynamic response function in type 2 diabetes: an fMRI study.

    Science.gov (United States)

    Duarte, João V; Pereira, João M S; Quendera, Bruno; Raimundo, Miguel; Moreno, Carolina; Gomes, Leonor; Carrilho, Francisco; Castelo-Branco, Miguel

    2015-10-01

    Type 2 diabetes (T2DM) patients develop vascular complications and have increased risk for neurophysiological impairment. Vascular pathophysiology may alter the blood flow regulation in cerebral microvasculature, affecting neurovascular coupling. Reduced fMRI signal can result from decreased neuronal activation or disrupted neurovascular coupling. The uncertainty about pathophysiological mechanisms (neurodegenerative, vascular, or both) underlying brain function impairments remains. In this cross-sectional study, we investigated if the hemodynamic response function (HRF) in lesion-free brains of patients is altered by measuring BOLD (Blood Oxygenation Level-Dependent) response to visual motion stimuli. We used a standard block design to examine the BOLD response and an event-related deconvolution approach. Importantly, the latter allowed for the first time to directly extract the true shape of HRF without any assumption and probe neurovascular coupling, using performance-matched stimuli. We discovered a change in HRF in early stages of diabetes. T2DM patients show significantly different fMRI response profiles. Our visual paradigm therefore demonstrated impaired neurovascular coupling in intact brain tissue. This implies that functional studies in T2DM require the definition of HRF, only achievable with deconvolution in event-related experiments. Further investigation of the mechanisms underlying impaired neurovascular coupling is needed to understand and potentially prevent the progression of brain function decrements in diabetes.

  19. Test-retest reliability of an fMRI paradigm for studies of cardiovascular reactivity.

    Science.gov (United States)

    Sheu, Lei K; Jennings, J Richard; Gianaros, Peter J

    2012-07-01

    We examined the reliability of measures of fMRI, subjective, and cardiovascular reactions to standardized versions of a Stroop color-word task and a multisource interference task. A sample of 14 men and 12 women (30-49 years old) completed the tasks on two occasions, separated by a median of 88 days. The reliability of fMRI BOLD signal changes in brain areas engaged by the tasks was moderate, and aggregating fMRI BOLD signal changes across the tasks improved test-retest reliability metrics. These metrics included voxel-wise intraclass correlation coefficients (ICCs) and overlap ratio statistics. Task-aggregated ratings of subjective arousal, valence, and control, as well as cardiovascular reactions evoked by the tasks showed ICCs of 0.57 to 0.87 (ps reliability. These findings support using these tasks as a battery for fMRI studies of cardiovascular reactivity. Copyright © 2012 Society for Psychophysiological Research.

  20. Neuropsychology and cognitive neuroscience in the fMRI era: A recapitulation of localizationist and connectionist views.

    Science.gov (United States)

    Sutterer, Matthew J; Tranel, Daniel

    2017-11-01

    We highlight the past 25 years of cognitive neuroscience and neuropsychology, focusing on the impact to the field of the introduction in 1992 of functional MRI (fMRI). We reviewed the past 25 years of literature in cognitive neuroscience and neuropsychology, focusing on the relation and interplay of fMRI studies and studies utilizing the "lesion method" in human participants with focal brain damage. Our review highlights the state of localist/connectionist research debates in cognitive neuroscience and neuropsychology circa 1992, and details how the introduction of fMRI into the field at that time catalyzed a new wave of efforts to map complex human behavior to specific brain regions. This, in turn, eventually evolved into many studies that focused on networks and connections between brain areas, culminating in recent years with large-scale investigations such as the Human Connectome Project. We argue that throughout the past 25 years, neuropsychology-and more precisely, the "lesion method" in humans-has continued to play a critical role in arbitrating conclusions and theories derived from inferred patterns of local brain activity or wide-spread connectivity from functional imaging approaches. We conclude by highlighting the future for neuropsychology in the context of an increasingly complex methodological armamentarium. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

  1. Controlling an avatar by thought using real-time fMRI

    Science.gov (United States)

    Cohen, Ori; Koppel, Moshe; Malach, Rafael; Friedman, Doron

    2014-06-01

    Objective. We have developed a brain-computer interface (BCI) system based on real-time functional magnetic resonance imaging (fMRI) with virtual reality feedback. The advantage of fMRI is the relatively high spatial resolution and the coverage of the whole brain; thus we expect that it may be used to explore novel BCI strategies, based on new types of mental activities. However, fMRI suffers from a low temporal resolution and an inherent delay, since it is based on a hemodynamic response rather than electrical signals. Thus, our objective in this paper was to explore whether subjects could perform a BCI task in a virtual environment using our system, and how their performance was affected by the delay. Approach. The subjects controlled an avatar by left-hand, right-hand and leg motion or imagery. The BCI classification is based on locating the regions of interest (ROIs) related with each of the motor classes, and selecting the ROI with maximum average values online. The subjects performed a cue-based task and a free-choice task, and the analysis includes evaluation of the performance as well as subjective reports. Main results. Six subjects performed the task with high accuracy when allowed to move their fingers and toes, and three subjects achieved high accuracy using imagery alone. In the cue-based task the accuracy was highest 8-12 s after the trigger, whereas in the free-choice task the subjects performed best when the feedback was provided 6 s after the trigger. Significance. We show that subjects are able to perform a navigation task in a virtual environment using an fMRI-based BCI, despite the hemodynamic delay. The same approach can be extended to other mental tasks and other brain areas.

  2. [Fusion of MRI, fMRI and intraoperative MRI data. Methods and clinical significance exemplified by neurosurgical interventions].

    Science.gov (United States)

    Moche, M; Busse, H; Dannenberg, C; Schulz, T; Schmitgen, A; Trantakis, C; Winkler, D; Schmidt, F; Kahn, T

    2001-11-01

    The aim of this work was to realize and clinically evaluate an image fusion platform for the integration of preoperative MRI and fMRI data into the intraoperative images of an interventional MRI system with a focus on neurosurgical procedures. A vertically open 0.5 T MRI scanner was equipped with a dedicated navigation system enabling the registration of additional imaging modalities (MRI, fMRI, CT) with the intraoperatively acquired data sets. These merged image data served as the basis for interventional planning and multimodal navigation. So far, the system has been used in 70 neurosurgical interventions (13 of which involved image data fusion--requiring 15 minutes extra time). The augmented navigation system is characterized by a higher frame rate and a higher image quality as compared to the system-integrated navigation based on continuously acquired (near) real time images. Patient movement and tissue shifts can be immediately detected by monitoring the morphological differences between both navigation scenes. The multimodal image fusion allowed a refined navigation planning especially for the resection of deeply seated brain lesions or pathologies close to eloquent areas. Augmented intraoperative orientation and instrument guidance improve the safety and accuracy of neurosurgical interventions.

  3. fMRI brain response during sentence reading comprehension in children with benign epilepsy with centro-temporal spikes.

    Science.gov (United States)

    Malfait, D; Tucholka, A; Mendizabal, S; Tremblay, J; Poulin, C; Oskoui, M; Srour, M; Carmant, L; Major, P; Lippé, S

    2015-11-01

    Children with benign epilepsy with centro-temporal spikes (BECTS) often have language problems. Abnormal epileptic activity is found in central and temporal brain regions, which are involved in reading and semantic and syntactic comprehension. Using functional magnetic resonance imaging (fMRI), we examined reading networks in BECTS children with a new sentence reading comprehension task involving semantic and syntactic processing. Fifteen children with BECTS (age=11y 1m ± 16 m; 12 boys) and 18 healthy controls (age=11 y 8m ± 20 m; 11 boys) performed an fMRI reading comprehension task in which they read a pair of syntactically complex sentences and decided whether the target sentence (the second sentence in the pair) was true or false with respect to the first sentence. All children also underwent an exhaustive neuropsychological assessment. We demonstrated weaknesses in several cognitive domains in BECTS children. During the sentence reading fMRI task, left inferior frontal regions and bilateral temporal areas were activated in BECTS children and healthy controls. However, additional brain regions such as the left hippocampus and precuneus were activated in BECTS children. Moreover, specific activation was found in the left caudate and putamen in BECTS children but not in healthy controls. Cognitive results and accuracy during the fMRI task were associated with specific brain activation patterns. BECTS children recruited a wider network to perform the fMRI sentence reading comprehension task, with specific activation in the left dorsal striatum. BECTS cognitive performance differently predicted functional activation in frontal and temporal regions compared to controls, suggesting differences in brain network organisation that contribute to reading comprehension. Crown Copyright © 2015. Published by Elsevier B.V. All rights reserved.

  4. Visual Network Asymmetry and Default Mode Network Function in ADHD: An fMRI Study

    Directory of Open Access Journals (Sweden)

    T. Sigi eHale

    2014-07-01

    Full Text Available Background: A growing body of research has identified abnormal visual information processing in ADHD. In particular, slow processing speed and increased reliance on visuo-perceptual strategies have become evident. Objective: The current study used recently developed fMRI methods to replicate and further examine abnormal rightward biased visual information processing in ADHD and to further characterize the nature of this effect; we tested its association to several large-scale distributed network systems. Method: We examined fMRI BOLD response during letter and location judgment tasks, and directly assessed visual network asymmetry and its association to large-scale networks using both a voxelwise and an averaged signal approach. Results: Initial within-group analyses revealed a pattern of left lateralized visual cortical activity in controls but right lateralized visual cortical activity in ADHD children. Direct analyses of visual network asymmetry confirmed atypical rightward bias in ADHD children compared to controls. This ADHD characteristic was atypically associated with reduced activation across several extra-visual networks, including the default mode network (DMN. We also found atypical associations between DMN activation and ADHD subjects’ inattentive symptoms and task performance. Conclusion: The current study demonstrated rightward VNA in ADHD during a simple letter discrimination task. This result adds an important novel consideration to the growing literature identifying abnormal visual processing in ADHD. We postulate that this characteristic reflects greater perceptual engagement of task-extraneous content, and that it may be a basic feature of less efficient top-down task-directed control over visual processing. We additionally argue that abnormal DMN function may contribute to this characteristic.

  5. Low-dimensional morphospace of topological motifs in human fMRI brain networks

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    Sarah E. Morgan

    2018-06-01

    Full Text Available We present a low-dimensional morphospace of fMRI brain networks, where axes are defined in a data-driven manner based on the network motifs. The morphospace allows us to identify the key variations in healthy fMRI networks in terms of their underlying motifs, and we observe that two principal components (PCs can account for 97% of the motif variability. The first PC of the motif distribution is correlated with efficiency and inversely correlated with transitivity. Hence this axis approximately conforms to the well-known economical small-world trade-off between integration and segregation in brain networks. Finally, we show that the economical clustering generative model proposed by Vértes et al. (2012 can approximately reproduce the motif morphospace of the real fMRI brain networks, in contrast to other generative models. Overall, the motif morphospace provides a powerful way to visualize the relationships between network properties and to investigate generative or constraining factors in the formation of complex human brain functional networks. Motifs have been described as the building blocks of complex networks. Meanwhile, a morphospace allows networks to be placed in a common space and can reveal the relationships between different network properties and elucidate the driving forces behind network topology. We combine the concepts of motifs and morphospaces to create the first motif morphospace of fMRI brain networks. Crucially, the morphospace axes are defined by the motifs, in a data-driven manner. We observe strong correlations between the networks’ positions in morphospace and their global topological properties, suggesting that motif morphospaces are a powerful way to capture the topology of networks in a low-dimensional space and to compare generative models of brain networks. Motif morphospaces could also be used to study other complex networks’ topologies.

  6. Robust Estimation of HDR in fMRI using H-infinity Filters

    DEFF Research Database (Denmark)

    Puthusserypady, Sadasivan; Jue, R.; Ratnarajah, T.

    2010-01-01

    Estimation and detection of the hemodynamic response (HDR) are of great importance in functional MRI (fMRI) data analysis. In this paper, we propose the use of three H-infinity adaptive filters (finite memory, exponentially weighted, and timevarying) for accurate estimation and detection of the HDR......-1487]. Performances of the proposed techniques are compared to the conventional t-test method as well as the well-known LMSs and recursive least squares algorithms. Extensive numerical simulations show that the proposed methods result in better HDR estimations and activation detections....

  7. Development of visual cortical function in infant macaques: A BOLD fMRI study.

    Directory of Open Access Journals (Sweden)

    Tom J Van Grootel

    Full Text Available Functional brain development is not well understood. In the visual system, neurophysiological studies in nonhuman primates show quite mature neuronal properties near birth although visual function is itself quite immature and continues to develop over many months or years after birth. Our goal was to assess the relative development of two main visual processing streams, dorsal and ventral, using BOLD fMRI in an attempt to understand the global mechanisms that support the maturation of visual behavior. Seven infant macaque monkeys (Macaca mulatta were repeatedly scanned, while anesthetized, over an age range of 102 to 1431 days. Large rotating checkerboard stimuli induced BOLD activation in visual cortices at early ages. Additionally we used static and dynamic Glass pattern stimuli to probe BOLD responses in primary visual cortex and two extrastriate areas: V4 and MT-V5. The resulting activations were analyzed with standard GLM and multivoxel pattern analysis (MVPA approaches. We analyzed three contrasts: Glass pattern present/absent, static/dynamic Glass pattern presentation, and structured/random Glass pattern form. For both GLM and MVPA approaches, robust coherent BOLD activation appeared relatively late in comparison to the maturation of known neuronal properties and the development of behavioral sensitivity to Glass patterns. Robust differential activity to Glass pattern present/absent and dynamic/static stimulus presentation appeared first in V1, followed by V4 and MT-V5 at older ages; there was no reliable distinction between the two extrastriate areas. A similar pattern of results was obtained with the two analysis methods, although MVPA analysis showed reliable differential responses emerging at later ages than GLM. Although BOLD responses to large visual stimuli are detectable, our results with more refined stimuli indicate that global BOLD activity changes as behavioral performance matures. This reflects an hierarchical development of

  8. Disentangling reward anticipation with simultaneous pupillometry / fMRI.

    Science.gov (United States)

    Schneider, Max; Leuchs, Laura; Czisch, Michael; Sämann, Philipp G; Spoormaker, Victor I

    2018-05-05

    The reward system may provide an interesting intermediate phenotype for anhedonia in affective disorders. Reward anticipation is characterized by an increase in arousal, and previous studies have linked the anterior cingulate cortex (ACC) to arousal responses such as dilation of the pupil. Here, we examined pupil dynamics during a reward anticipation task in forty-six healthy human subjects and evaluated its neural correlates using functional magnetic resonance imaging (fMRI). Pupil size showed a strong increase during monetary reward anticipation, a moderate increase during verbal reward anticipation and a decrease during control trials. For fMRI analyses, average pupil size and pupil change were computed in 1-s time bins during the anticipation phase. Activity in the ventral striatum was inversely related to the pupil size time course, indicating an early onset of activation and a role in reward prediction processing. Pupil dilations were linked to increased activity in the salience network (dorsal ACC and bilateral insula), which likely triggers an increase in arousal to enhance task performance. Finally, increased pupil size preceding the required motor response was associated with activity in the ventral attention network. In sum, pupillometry provides an effective tool for disentangling different phases of reward anticipation, with relevance for affective symptomatology. Copyright © 2018 Elsevier Inc. All rights reserved.

  9. In vivo functional connectome of human brainstem nuclei of the ascending arousal, autonomic, and motor systems by high spatial resolution 7-Tesla fMRI.

    Science.gov (United States)

    Bianciardi, Marta; Toschi, Nicola; Eichner, Cornelius; Polimeni, Jonathan R; Setsompop, Kawin; Brown, Emery N; Hämäläinen, Matti S; Rosen, Bruce R; Wald, Lawrence L

    2016-06-01

    Our aim was to map the in vivo human functional connectivity of several brainstem nuclei with the rest of the brain by using seed-based correlation of ultra-high magnetic field functional magnetic resonance imaging (fMRI) data. We used the recently developed template of 11 brainstem nuclei derived from multi-contrast structural MRI at 7 Tesla as seed regions to determine their connectivity to the rest of the brain. To achieve this, we used the increased contrast-to-noise ratio of 7-Tesla fMRI compared with 3 Tesla and time-efficient simultaneous multi-slice imaging to cover the brain with high spatial resolution (1.1-mm isotropic nominal resolution) while maintaining a short repetition time (2.5 s). The delineated Pearson's correlation-based functional connectivity diagrams (connectomes) of 11 brainstem nuclei of the ascending arousal, motor, and autonomic systems from 12 controls are presented and discussed in the context of existing histology and animal work. Considering that the investigated brainstem nuclei play a crucial role in several vital functions, the delineated preliminary connectomes might prove useful for future in vivo research and clinical studies of human brainstem function and pathology, including disorders of consciousness, sleep disorders, autonomic disorders, Parkinson's disease, and other motor disorders.

  10. Hypercapnic evaluation of vascular reactivity in healthy aging and acute stroke via functional MRI

    Directory of Open Access Journals (Sweden)

    Ryan V. Raut

    2016-01-01

    Full Text Available Functional MRI (fMRI is well-established for the study of brain function in healthy populations, although its clinical application has proven more challenging. Specifically, cerebrovascular reactivity (CVR, which allows the assessment of the vascular response that serves as the basis for fMRI, has been shown to be reduced in healthy aging as well as in a range of diseases, including chronic stroke. However, the timing of when this occurs relative to the stroke event is unclear. We used a breath-hold fMRI task to evaluate CVR across gray matter in a group of acute stroke patients (<10 days from stroke; N = 22 to address this question. These estimates were compared with those from both age-matched (N = 22 and younger (N = 22 healthy controls. As expected, young controls had the greatest mean CVR, as indicated by magnitude and extent of fMRI activation; however, stroke patients did not differ from age-matched controls. Moreover, the ipsilesional and contralesional hemispheres of stroke patients did not differ with respect to any of these measures. These findings suggest that fMRI remains a valid tool within the first few days of a stroke, particularly for group fMRI studies in which findings are compared with healthy subjects of similar age. However, given the relatively high variability in CVR observed in our stroke sample, caution is warranted when interpreting fMRI data from individual patients or a small cohort. We conclude that a breath-hold task can be a useful addition to functional imaging protocols for stroke patients.

  11. Motor imagery training: Kinesthetic imagery strategy and inferior parietal fMRI activation.

    Science.gov (United States)

    Lebon, Florent; Horn, Ulrike; Domin, Martin; Lotze, Martin

    2018-04-01

    Motor imagery (MI) is the mental simulation of action frequently used by professionals in different fields. However, with respect to performance, well-controlled functional imaging studies on MI training are sparse. We investigated changes in fMRI representation going along with performance changes of a finger sequence (error and velocity) after MI training in 48 healthy young volunteers. Before training, we tested the vividness of kinesthetic and visual imagery. During tests, participants were instructed to move or to imagine moving the fingers of the right hand in a specific order. During MI training, participants repeatedly imagined the sequence for 15 min. Imaging analysis was performed using a full-factorial design to assess brain changes due to imagery training. We also used regression analyses to identify those who profited from training (performance outcome and gain) with initial imagery scores (vividness) and fMRI activation magnitude during MI at pre-test (MI pre ). After training, error rate decreased and velocity increased. We combined both parameters into a common performance index. FMRI activation in the left inferior parietal lobe (IPL) was associated with MI and increased over time. In addition, fMRI activation in the right IPL during MI pre was associated with high initial kinesthetic vividness. High kinesthetic imagery vividness predicted a high performance after training. In contrast, occipital activation, associated with visual imagery strategies, showed a negative predictive value for performance. Our data echo the importance of high kinesthetic vividness for MI training outcome and consider IPL as a key area during MI and through MI training. © 2018 Wiley Periodicals, Inc.

  12. Altered functional connectivity of fusiform gyrus in subjects with amnestic mild cognitive impairment: a resting state fMRI study

    Directory of Open Access Journals (Sweden)

    SuPing eCai

    2015-08-01

    Full Text Available Visual cognition such as face recognition requires a high level of functional interaction between distributed regions of a network. It has been reported that the fusiform gyrus (FG is an important brain area involved in facial cognition; altered connectivity of FG to some other regions may lead to a deficit in visual cognition especially face recognition. However, whether functional connectivity between the FG and other brain regions changes remains unclear during the resting state in amnestic mild cognitive impairment (aMCI subjects. Here, we employed a resting state functional MRI (fMRI to examine changes in functional connectivity of left/right FG comparing aMCI patients with age-matched control subjects. Forty-eight aMCI and thirty-eight control subjects from the Alzheimer’s disease Neuroimaging Initiative (ADNI were analyzed. We focused on the correlation between low frequency fMRI signal fluctuations in the FG and those in all other brain regions. Compared to the control group, we found some discrepant regions in the aMCI group which presented increased or decreased connectivity with the left/right FG including the left precuneus, left lingual gyrus, right thalamus, supramarginal gyrus, left supplementary motor area, left inferior temporal gyrus, and left parahippocampus. More importantly, we also obtained that both left and right FG have increased functional connections with the left middle occipital gyrus (MOG and right anterior cingulate gyrus (ACC in aMCI patients. That was not a coincidence and might imply that the MOG and ACC also play a critical role in visual cognition, especially face recognition. These findings in a large part supported our hypothesis and provided a new insight in understanding the important subtype of MCI.

  13. In vivo evaluation of the effect of stimulus distribution on FIR statistical efficiency in event-related fMRI.

    Science.gov (United States)

    Jansma, J Martijn; de Zwart, Jacco A; van Gelderen, Peter; Duyn, Jeff H; Drevets, Wayne C; Furey, Maura L

    2013-05-15

    Technical developments in MRI have improved signal to noise, allowing use of analysis methods such as Finite impulse response (FIR) of rapid event related functional MRI (er-fMRI). FIR is one of the most informative analysis methods as it determines onset and full shape of the hemodynamic response function (HRF) without any a priori assumptions. FIR is however vulnerable to multicollinearity, which is directly related to the distribution of stimuli over time. Efficiency can be optimized by simplifying a design, and restricting stimuli distribution to specific sequences, while more design flexibility necessarily reduces efficiency. However, the actual effect of efficiency on fMRI results has never been tested in vivo. Thus, it is currently difficult to make an informed choice between protocol flexibility and statistical efficiency. The main goal of this study was to assign concrete fMRI signal to noise values to the abstract scale of FIR statistical efficiency. Ten subjects repeated a perception task with five random and m-sequence based protocol, with varying but, according to literature, acceptable levels of multicollinearity. Results indicated substantial differences in signal standard deviation, while the level was a function of multicollinearity. Experiment protocols varied up to 55.4% in standard deviation. Results confirm that quality of fMRI in an FIR analysis can significantly and substantially vary with statistical efficiency. Our in vivo measurements can be used to aid in making an informed decision between freedom in protocol design and statistical efficiency. Published by Elsevier B.V.

  14. Does functional MRI detect activation in white matter? A review of emerging evidence, issues, and future directions

    Science.gov (United States)

    Gawryluk, Jodie R.; Mazerolle, Erin L.; D'Arcy, Ryan C. N.

    2014-01-01

    Functional magnetic resonance imaging (fMRI) is a non-invasive technique that allows for visualization of activated brain regions. Until recently, fMRI studies have focused on gray matter. There are two main reasons white matter fMRI remains controversial: (1) the blood oxygen level dependent (BOLD) fMRI signal depends on cerebral blood flow and volume, which are lower in white matter than gray matter and (2) fMRI signal has been associated with post-synaptic potentials (mainly localized in gray matter) as opposed to action potentials (the primary type of neural activity in white matter). Despite these observations, there is no direct evidence against measuring fMRI activation in white matter and reports of fMRI activation in white matter continue to increase. The questions underlying white matter fMRI activation are important. White matter fMRI activation has the potential to greatly expand the breadth of brain connectivity research, as well as improve the assessment and diagnosis of white matter and connectivity disorders. The current review provides an overview of the motivation to investigate white matter fMRI activation, as well as the published evidence of this phenomenon. We speculate on possible neurophysiologic bases of white matter fMRI signals, and discuss potential explanations for why reports of white matter fMRI activation are relatively scarce. We end with a discussion of future basic and clinical research directions in the study of white matter fMRI. PMID:25152709

  15. Correlates of figure-ground segregation in fMRI.

    Science.gov (United States)

    Skiera, G; Petersen, D; Skalej, M; Fahle, M

    2000-01-01

    We investigated which correlates of figure-ground-segregation can be detected by means of functional magnetic resonance imaging (fMRI). Five subjects were scanned with a Siemens Vision 1.5 T system. Motion, colour, and luminance-defined checkerboards were presented with alternating control conditions containing one of the two features of the checkerboard. We find a segregation-specific activation in V1 for all subjects and all stimuli and conclude that neural mechanisms exist as early as in the primary visual cortex that are sensitive to figure-ground segregation.

  16. Extending Local Canonical Correlation Analysis to Handle General Linear Contrasts for fMRI Data

    Directory of Open Access Journals (Sweden)

    Mingwu Jin

    2012-01-01

    Full Text Available Local canonical correlation analysis (CCA is a multivariate method that has been proposed to more accurately determine activation patterns in fMRI data. In its conventional formulation, CCA has several drawbacks that limit its usefulness in fMRI. A major drawback is that, unlike the general linear model (GLM, a test of general linear contrasts of the temporal regressors has not been incorporated into the CCA formalism. To overcome this drawback, a novel directional test statistic was derived using the equivalence of multivariate multiple regression (MVMR and CCA. This extension will allow CCA to be used for inference of general linear contrasts in more complicated fMRI designs without reparameterization of the design matrix and without reestimating the CCA solutions for each particular contrast of interest. With the proper constraints on the spatial coefficients of CCA, this test statistic can yield a more powerful test on the inference of evoked brain regional activations from noisy fMRI data than the conventional t-test in the GLM. The quantitative results from simulated and pseudoreal data and activation maps from fMRI data were used to demonstrate the advantage of this novel test statistic.

  17. Heritability estimates on resting state fMRI data using ENIGMA analysis pipeline.

    Science.gov (United States)

    Adhikari, Bhim M; Jahanshad, Neda; Shukla, Dinesh; Glahn, David C; Blangero, John; Reynolds, Richard C; Cox, Robert W; Fieremans, Els; Veraart, Jelle; Novikov, Dmitry S; Nichols, Thomas E; Hong, L Elliot; Thompson, Paul M; Kochunov, Peter

    2018-01-01

    Big data initiatives such as the Enhancing NeuroImaging Genetics through Meta-Analysis consortium (ENIGMA), combine data collected by independent studies worldwide to achieve more generalizable estimates of effect sizes and more reliable and reproducible outcomes. Such efforts require harmonized image analyses protocols to extract phenotypes consistently. This harmonization is particularly challenging for resting state fMRI due to the wide variability of acquisition protocols and scanner platforms; this leads to site-to-site variance in quality, resolution and temporal signal-to-noise ratio (tSNR). An effective harmonization should provide optimal measures for data of different qualities. We developed a multi-site rsfMRI analysis pipeline to allow research groups around the world to process rsfMRI scans in a harmonized way, to extract consistent and quantitative measurements of connectivity and to perform coordinated statistical tests. We used the single-modality ENIGMA rsfMRI preprocessing pipeline based on modelfree Marchenko-Pastur PCA based denoising to verify and replicate resting state network heritability estimates. We analyzed two independent cohorts, GOBS (Genetics of Brain Structure) and HCP (the Human Connectome Project), which collected data using conventional and connectomics oriented fMRI protocols, respectively. We used seed-based connectivity and dual-regression approaches to show that the rsfMRI signal is consistently heritable across twenty major functional network measures. Heritability values of 20-40% were observed across both cohorts.

  18. Visual Learning Induces Changes in Resting-State fMRI Multivariate Pattern of Information.

    Science.gov (United States)

    Guidotti, Roberto; Del Gratta, Cosimo; Baldassarre, Antonello; Romani, Gian Luca; Corbetta, Maurizio

    2015-07-08

    When measured with functional magnetic resonance imaging (fMRI) in the resting state (R-fMRI), spontaneous activity is correlated between brain regions that are anatomically and functionally related. Learning and/or task performance can induce modulation of the resting synchronization between brain regions. Moreover, at the neuronal level spontaneous brain activity can replay patterns evoked by a previously presented stimulus. Here we test whether visual learning/task performance can induce a change in the patterns of coded information in R-fMRI signals consistent with a role of spontaneous activity in representing task-relevant information. Human subjects underwent R-fMRI before and after perceptual learning on a novel visual shape orientation discrimination task. Task-evoked fMRI patterns to trained versus novel stimuli were recorded after learning was completed, and before the second R-fMRI session. Using multivariate pattern analysis on task-evoked signals, we found patterns in several cortical regions, as follows: visual cortex, V3/V3A/V7; within the default mode network, precuneus, and inferior parietal lobule; and, within the dorsal attention network, intraparietal sulcus, which discriminated between trained and novel visual stimuli. The accuracy of classification was strongly correlated with behavioral performance. Next, we measured multivariate patterns in R-fMRI signals before and after learning. The frequency and similarity of resting states representing the task/visual stimuli states increased post-learning in the same cortical regions recruited by the task. These findings support a representational role of spontaneous brain activity. Copyright © 2015 the authors 0270-6474/15/359786-13$15.00/0.

  19. Combination of functional MRI with SAS and MRA

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    Sumida, Masayuki; Takeshita, Shinichirou; Kutsuna, Munenori; Akimitsu, Tomohide; Arita, Kazunori; Kurisu, Kaoru [Hiroshima Univ. (Japan). School of Medicine

    1999-02-01

    For presurgical diagnosis of brain surface, combination of functional MRI (fMRI) with the MR angiography was examined. This method could visualize brain bay, convolution and vein as index of surface. Five normal adults (male, mean age: 28-year-old) and 7 patients with brain tumor on the main locus to surface (male: 4, female: 3, mean age: 52.3-year-old) were studied. fMRI was performed by SPGR method (TR 70, TE 40, flip angle 60, one slice, thickness 10 mm, FOV 20 cm, matrix 128 x 128). The brain surface was visualized by SAS (surface anatomy scanning). SAS was performed by FSE method (TR 6000, TE 200, echo train 16, thickness 20 mm, slice 3, NEX 2). Cortical veins near superior sagittal sinus were visualized by MRA with 2D-TOF method (TR 50, TE 20, flip angle 60, thickness 2 mm, slice 28, NEX 1). These images were superimposed and functional image of peripheral sensorimotor region was evaluated anatomically. In normal adults, high signal was visualized at another side of near sensorimotor region at 8 of 10 sides. All high signal area of fMRI agreed with cortical vein near sensorimotor region that was visualized by MRA. In patients with brain tumor, signal was visualized at another side of sensorimotor region of tumor without 2 cases with palsy. In another side of tumor, signal of fMRI was visualized in 5 of 7 cases. The tumor was visualized as opposite low signal field in SAS. Locational relation between tumor and brain surface and brain function was visualized distinctly by combination of MRA, SAS and MRA. This method could become useful for presurgical diagnosis. (K.H.)

  20. Preliminary pilot fMRI study of neuropostural optimization with a noninvasive asymmetric radioelectric brain stimulation protocol in functional dysmetria

    Directory of Open Access Journals (Sweden)

    Mura M

    2012-04-01

    Full Text Available Marco Mura1, Alessandro Castagna2, Vania Fontani2, Salvatore Rinaldi21Institute of Radiology, University of Cagliari, 2Rinaldi Fontani Institute – Department of Neuro Psycho Physical Optimization, Florence, ItalyPurpose: This study assessed changes in functional dysmetria (FD and in brain activation observable by functional magnetic resonance imaging (fMRI during a leg flexion-extension motor task following brain stimulation with a single radioelectric asymmetric conveyer (REAC pulse, according to the precisely defined neuropostural optimization (NPO protocol.Population and methods: Ten healthy volunteers were assessed using fMRI conducted during a simple motor task before and immediately after delivery of a single REAC-NPO pulse. The motor task consisted of a flexion-extension movement of the legs with the knees bent. FD signs and brain activation patterns were compared before and after REAC-NPO.Results: A single 250-millisecond REAC-NPO treatment alleviated FD, as evidenced by patellar asymmetry during a sit-up motion, and modulated activity patterns in the brain, particularly in the cerebellum, during the performance of the motor task.Conclusion: Activity in brain areas involved in motor control and coordination, including the cerebellum, is altered by administration of a REAC-NPO treatment and this effect is accompanied by an alleviation of FD.Keywords: motor behavior, motor control, cerebellum, dysmetria, functional dysmetria, fluctuating asymmetry

  1. Mapping of the brain hemodynamic responses to sensorimotor stimulation in a rodent model: A BOLD fMRI study.

    Directory of Open Access Journals (Sweden)

    Salem Boussida

    Full Text Available Blood Oxygenation Level Dependent functional MRI (BOLD fMRI during electrical paw stimulation has been widely used in studies aimed at the understanding of the somatosensory network in rats. However, despite the well-established anatomical connections between cortical and subcortical structures of the sensorimotor system, most of these functional studies have been concentrated on the cortical effects of sensory electrical stimulation. BOLD fMRI study of the integration of a sensorimotor input across the sensorimotor network requires an appropriate methodology to elicit functional activation in cortical and subcortical areas owing to the regional differences in both neuronal and vascular architectures between these brain regions. Here, using a combination of low level anesthesia, long pulse duration of the electrical stimulation along with improved spatial and temporal signal to noise ratios, we provide a functional description of the main cortical and subcortical structures of the sensorimotor rat brain. With this calibrated fMRI protocol, unilateral non-noxious sensorimotor electrical hindpaw stimulation resulted in robust positive activations in the contralateral sensorimotor cortex and bilaterally in the sensorimotor thalamus nuclei, whereas negative activations were observed bilaterally in the dorsolateral caudate-putamen. These results demonstrate that, once the experimental setup allowing necessary spatial and temporal signal to noise ratios is reached, hemodynamic changes related to neuronal activity, as preserved by the combination of a soft anesthesia with a soft muscle relaxation, can be measured within the sensorimotor network. Moreover, the observed responses suggest that increasing pulse duration of the electrical stimulus adds a proprioceptive component to the sensory input that activates sensorimotor network in the brain, and that these activation patterns are similar to those induced by digits paw's movements. These findings may

  2. Parameterized hemodynamic response function data of healthy individuals obtained from resting-state functional MRI in a 7T MRI scanner

    Directory of Open Access Journals (Sweden)

    D. Rangaprakash

    2018-04-01

    Full Text Available Functional magnetic resonance imaging (fMRI, being an indirect measure of brain activity, is mathematically defined as a convolution of the unmeasured latent neural signal and the hemodynamic response function (HRF. The HRF is known to vary across the brain and across individuals, and it is modulated by neural as well as non-neural factors. Three parameters characterize the shape of the HRF, which is obtained by performing deconvolution on resting-state fMRI data: response height, time-to-peak and full-width at half-max. The data provided here, obtained from 47 healthy adults, contains these three HRF parameters at every voxel in the brain, as well as HRF parameters from the default-mode network (DMN. In addition, we have provided functional connectivity (FC data from the same DMN regions, obtained for two cases: data with deconvolution (HRF variability minimized and data with no deconvolution (HRF variability corrupted. This would enable researchers to compare regional changes in HRF with corresponding FC differences, to assess the impact of HRF variability on FC. Importantly, the data was obtained in a 7T MRI scanner. While most fMRI studies are conducted at lower field strengths, like 3T, ours is the first study to report HRF data obtained at 7T. FMRI data at ultra-high fields contains larger contributions from small vessels, consequently HRF variability is lower for small vessels at higher field strengths. This implies that findings made from this data would be more conservative than from data acquired at lower fields, such as 3T. Results obtained with this data and further interpretations are available in our recent research study (Rangaprakash et al., in press [1]. This is a valuable dataset for studying HRF variability in conjunction with FC, and for developing the HRF profile in healthy individuals, which would have direct implications for fMRI data analysis, especially resting-state connectivity modeling. This is the first public HRF

  3. Visual, Auditory, and Cross Modal Sensory Processing in Adults with Autism: An EEG Power and BOLD fMRI Investigation

    Science.gov (United States)

    Hames, Elizabeth’ C.; Murphy, Brandi; Rajmohan, Ravi; Anderson, Ronald C.; Baker, Mary; Zupancic, Stephen; O’Boyle, Michael; Richman, David

    2016-01-01

    Electroencephalography (EEG) and blood oxygen level dependent functional magnetic resonance imagining (BOLD fMRI) assessed the neurocorrelates of sensory processing of visual and auditory stimuli in 11 adults with autism (ASD) and 10 neurotypical (NT) controls between the ages of 20–28. We hypothesized that ASD performance on combined audiovisual trials would be less accurate with observable decreased EEG power across frontal, temporal, and occipital channels and decreased BOLD fMRI activity in these same regions; reflecting deficits in key sensory processing areas. Analysis focused on EEG power, BOLD fMRI, and accuracy. Lower EEG beta power and lower left auditory cortex fMRI activity were seen in ASD compared to NT when they were presented with auditory stimuli as demonstrated by contrasting the activity from the second presentation of an auditory stimulus in an all auditory block vs. the second presentation of a visual stimulus in an all visual block (AA2-VV2).We conclude that in ASD, combined audiovisual processing is more similar than unimodal processing to NTs. PMID:27148020

  4. Visual, Auditory, and Cross Modal Sensory Processing in Adults with Autism:An EEG Power and BOLD fMRI Investigation

    Directory of Open Access Journals (Sweden)

    Elizabeth C Hames

    2016-04-01

    Full Text Available Electroencephalography (EEG and Blood Oxygen Level Dependent Functional Magnetic Resonance Imagining (BOLD fMRI assessed the neurocorrelates of sensory processing of visual and auditory stimuli in 11 adults with autism (ASD and 10 neurotypical (NT controls between the ages of 20-28. We hypothesized that ASD performance on combined audiovisual trials would be less accurate with observable decreased EEG power across frontal, temporal, and occipital channels and decreased BOLD fMRI activity in these same regions; reflecting deficits in key sensory processing areas. Analysis focused on EEG power, BOLD fMRI, and accuracy. Lower EEG beta power and lower left auditory cortex fMRI activity were seen in ASD compared to NT when they were presented with auditory stimuli as demonstrated by contrasting the activity from the second presentation of an auditory stimulus in an all auditory block versus the second presentation of a visual stimulus in an all visual block (AA2­VV2. We conclude that in ASD, combined audiovisual processing is more similar than unimodal processing to NTs.

  5. A wavelet method for modeling and despiking motion artifacts from resting-state fMRI time series.

    Science.gov (United States)

    Patel, Ameera X; Kundu, Prantik; Rubinov, Mikail; Jones, P Simon; Vértes, Petra E; Ersche, Karen D; Suckling, John; Bullmore, Edward T

    2014-07-15

    The impact of in-scanner head movement on functional magnetic resonance imaging (fMRI) signals has long been established as undesirable. These effects have been traditionally corrected by methods such as linear regression of head movement parameters. However, a number of recent independent studies have demonstrated that these techniques are insufficient to remove motion confounds, and that even small movements can spuriously bias estimates of functional connectivity. Here we propose a new data-driven, spatially-adaptive, wavelet-based method for identifying, modeling, and removing non-stationary events in fMRI time series, caused by head movement, without the need for data scrubbing. This method involves the addition of just one extra step, the Wavelet Despike, in standard pre-processing pipelines. With this method, we demonstrate robust removal of a range of different motion artifacts and motion-related biases including distance-dependent connectivity artifacts, at a group and single-subject level, using a range of previously published and new diagnostic measures. The Wavelet Despike is able to accommodate the substantial spatial and temporal heterogeneity of motion artifacts and can consequently remove a range of high and low frequency artifacts from fMRI time series, that may be linearly or non-linearly related to physical movements. Our methods are demonstrated by the analysis of three cohorts of resting-state fMRI data, including two high-motion datasets: a previously published dataset on children (N=22) and a new dataset on adults with stimulant drug dependence (N=40). We conclude that there is a real risk of motion-related bias in connectivity analysis of fMRI data, but that this risk is generally manageable, by effective time series denoising strategies designed to attenuate synchronized signal transients induced by abrupt head movements. The Wavelet Despiking software described in this article is freely available for download at www

  6. Multiple fMRI system-level baseline connectivity is disrupted in patients with consciousness alterations.

    Science.gov (United States)

    Demertzi, Athena; Gómez, Francisco; Crone, Julia Sophia; Vanhaudenhuyse, Audrey; Tshibanda, Luaba; Noirhomme, Quentin; Thonnard, Marie; Charland-Verville, Vanessa; Kirsch, Murielle; Laureys, Steven; Soddu, Andrea

    2014-03-01

    In healthy conditions, group-level fMRI resting state analyses identify ten resting state networks (RSNs) of cognitive relevance. Here, we aim to assess the ten-network model in severely brain-injured patients suffering from disorders of consciousness and to identify those networks which will be most relevant to discriminate between patients and healthy subjects. 300 fMRI volumes were obtained in 27 healthy controls and 53 patients in minimally conscious state (MCS), vegetative state/unresponsive wakefulness syndrome (VS/UWS) and coma. Independent component analysis (ICA) reduced data dimensionality. The ten networks were identified by means of a multiple template-matching procedure and were tested on neuronality properties (neuronal vs non-neuronal) in a data-driven way. Univariate analyses detected between-group differences in networks' neuronal properties and estimated voxel-wise functional connectivity in the networks, which were significantly less identifiable in patients. A nearest-neighbor "clinical" classifier was used to determine the networks with high between-group discriminative accuracy. Healthy controls were characterized by more neuronal components compared to patients in VS/UWS and in coma. Compared to healthy controls, fewer patients in MCS and VS/UWS showed components of neuronal origin for the left executive control network, default mode network (DMN), auditory, and right executive control network. The "clinical" classifier indicated the DMN and auditory network with the highest accuracy (85.3%) in discriminating patients from healthy subjects. FMRI multiple-network resting state connectivity is disrupted in severely brain-injured patients suffering from disorders of consciousness. When performing ICA, multiple-network testing and control for neuronal properties of the identified RSNs can advance fMRI system-level characterization. Automatic data-driven patient classification is the first step towards future single-subject objective diagnostics

  7. Reducing task-based fMRI scanning time using simultaneous multislice echo planar imaging

    Energy Technology Data Exchange (ETDEWEB)

    Kiss, Mate [Hungarian Academy of Sciences, Brain Imaging Centre, Research Centre for Natural Sciences, Budapest (Hungary); Janos Szentagothai PhD School, MR Research Centre, Budapest (Hungary); National Institute of Clinical Neuroscience, Department of Neuroradiology, Budapest (Hungary); Hermann, Petra; Vidnyanszky, Zoltan; Gal, Viktor [Hungarian Academy of Sciences, Brain Imaging Centre, Research Centre for Natural Sciences, Budapest (Hungary)

    2018-03-15

    To maintain alertness and to remain motionless during scanning represent a substantial challenge for patients/subjects involved in both clinical and research functional magnetic resonance imaging (fMRI) examinations. Therefore, availability and application of new data acquisition protocols allowing the shortening of scan time without compromising the data quality and statistical power are of major importance. Higher order category-selective visual cortical areas were identified individually, and rapid event-related fMRI design was used to compare three different sampling rates (TR = 2000, 1000, and 410 ms, using state-of-the-art simultaneous multislice imaging) and four different scanning lengths to match the statistical power of the traditional scanning methods to high sampling-rate design. The results revealed that ∝ 4 min of the scan time with 1 Hz (TR = 1000 ms) sampling rate and ∝ 2 min scanning at ∝ 2.5 Hz (TR = 410 ms) sampling rate provide similar localization sensitivity and selectivity to that obtained with 11-min session at conventional, 0.5 Hz (TR = 2000 ms) sampling rate. Our findings suggest that task-based fMRI examination of clinical population prone to distress such as presurgical mapping experiments might substantially benefit from the reduced (20-40%) scanning time that can be achieved by the application of simultaneous multislice sequences. (orig.)

  8. Conjunction analysis and propositional logic in fMRI data analysis using Bayesian statistics.

    Science.gov (United States)

    Rudert, Thomas; Lohmann, Gabriele

    2008-12-01

    To evaluate logical expressions over different effects in data analyses using the general linear model (GLM) and to evaluate logical expressions over different posterior probability maps (PPMs). In functional magnetic resonance imaging (fMRI) data analysis, the GLM was applied to estimate unknown regression parameters. Based on the GLM, Bayesian statistics can be used to determine the probability of conjunction, disjunction, implication, or any other arbitrary logical expression over different effects or contrast. For second-level inferences, PPMs from individual sessions or subjects are utilized. These PPMs can be combined to a logical expression and its probability can be computed. The methods proposed in this article are applied to data from a STROOP experiment and the methods are compared to conjunction analysis approaches for test-statistics. The combination of Bayesian statistics with propositional logic provides a new approach for data analyses in fMRI. Two different methods are introduced for propositional logic: the first for analyses using the GLM and the second for common inferences about different probability maps. The methods introduced extend the idea of conjunction analysis to a full propositional logic and adapt it from test-statistics to Bayesian statistics. The new approaches allow inferences that are not possible with known standard methods in fMRI. (c) 2008 Wiley-Liss, Inc.

  9. fMRI evidence of improved visual function in patients with progressive retinitis pigmentosa by eye-movement training.

    Science.gov (United States)

    Yoshida, Masako; Origuchi, Maki; Urayama, Shin-Ichi; Takatsuki, Akira; Kan, Shigeyuki; Aso, Toshihiko; Shiose, Takayuki; Sawamoto, Nobukatsu; Miyauchi, Satoru; Fukuyama, Hidenao; Seiyama, Akitoshi

    2014-01-01

    To evaluate changes in the visual processing of patients with progressive retinitis pigmentosa (RP) who acquired improved reading capability by eye-movement training (EMT), we performed functional magnetic resonance imaging (fMRI) before and after EMT. Six patients with bilateral concentric contraction caused by pigmentary degeneration of the retina and 6 normal volunteers were recruited. Patients were given EMT for 5 min every day for 8-10 months. fMRI data were acquired on a 3.0-Tesla scanner while subjects were performing reading tasks. In separate experiments (before fMRI scanning), visual performances for readings were measured by the number of letters read correctly in 5 min. Before EMT, activation areas of the primary visual cortex of patients were 48.8% of those of the controls. The number of letters read correctly in 5 min was 36.6% of those by the normal volunteers. After EMT, the activation areas of patients were not changed or slightly decreased; however, reading performance increased in 5 of 6 patients, which was 46.6% of that of the normal volunteers (p< 0.05). After EMT, increased activity was observed in the frontal eye fields (FEFs) of all patients; however, increases in the activity of the parietal eye fields (PEFs) were observed only in patients who showed greater improvement in reading capability. The improvement in reading ability of the patients after EMT is regarded as an effect of the increased activity of FEF and PEF, which play important roles in attention and working memory as well as the regulation of eye movements.

  10. fMRI evidence of improved visual function in patients with progressive retinitis pigmentosa by eye-movement training

    Directory of Open Access Journals (Sweden)

    Masako Yoshida

    2014-01-01

    Full Text Available To evaluate changes in the visual processing of patients with progressive retinitis pigmentosa (RP who acquired improved reading capability by eye-movement training (EMT, we performed functional magnetic resonance imaging (fMRI before and after EMT. Six patients with bilateral concentric contraction caused by pigmentary degeneration of the retina and 6 normal volunteers were recruited. Patients were given EMT for 5 min every day for 8–10 months. fMRI data were acquired on a 3.0-Tesla scanner while subjects were performing reading tasks. In separate experiments (before fMRI scanning, visual performances for readings were measured by the number of letters read correctly in 5 min. Before EMT, activation areas of the primary visual cortex of patients were 48.8% of those of the controls. The number of letters read correctly in 5 min was 36.6% of those by the normal volunteers. After EMT, the activation areas of patients were not changed or slightly decreased; however, reading performance increased in 5 of 6 patients, which was 46.6% of that of the normal volunteers (p< 0.05. After EMT, increased activity was observed in the frontal eye fields (FEFs of all patients; however, increases in the activity of the parietal eye fields (PEFs were observed only in patients who showed greater improvement in reading capability. The improvement in reading ability of the patients after EMT is regarded as an effect of the increased activity of FEF and PEF, which play important roles in attention and working memory as well as the regulation of eye movements.

  11. A novel approach to calibrate the Hemodynamic Model using functional Magnetic Resonance Imaging (fMRI) measurements

    KAUST Repository

    Khoram, Nafiseh

    2016-01-21

    Background The calibration of the hemodynamic model that describes changes in blood flow and blood oxygenation during brain activation is a crucial step for successfully monitoring and possibly predicting brain activity. This in turn has the potential to provide diagnosis and treatment of brain diseases in early stages. New Method We propose an efficient numerical procedure for calibrating the hemodynamic model using some fMRI measurements. The proposed solution methodology is a regularized iterative method equipped with a Kalman filtering-type procedure. The Newton component of the proposed method addresses the nonlinear aspect of the problem. The regularization feature is used to ensure the stability of the algorithm. The Kalman filter procedure is incorporated here to address the noise in the data. Results Numerical results obtained with synthetic data as well as with real fMRI measurements are presented to illustrate the accuracy, robustness to the noise, and the cost-effectiveness of the proposed method. Comparison with Existing Method(s) We present numerical results that clearly demonstrate that the proposed method outperforms the Cubature Kalman Filter (CKF), one of the most prominent existing numerical methods. Conclusion We have designed an iterative numerical technique, called the TNM-CKF algorithm, for calibrating the mathematical model that describes the single-event related brain response when fMRI measurements are given. The method appears to be highly accurate and effective in reconstructing the BOLD signal even when the measurements are tainted with high noise level (as high as 30%).

  12. Cortical processing of pitch: Model-based encoding and decoding of auditory fMRI responses to real-life sounds.

    Science.gov (United States)

    De Angelis, Vittoria; De Martino, Federico; Moerel, Michelle; Santoro, Roberta; Hausfeld, Lars; Formisano, Elia

    2017-11-13

    Pitch is a perceptual attribute related to the fundamental frequency (or periodicity) of a sound. So far, the cortical processing of pitch has been investigated mostly using synthetic sounds. However, the complex harmonic structure of natural sounds may require different mechanisms for the extraction and analysis of pitch. This study investigated the neural representation of pitch in human auditory cortex using model-based encoding and decoding analyses of high field (7 T) functional magnetic resonance imaging (fMRI) data collected while participants listened to a wide range of real-life sounds. Specifically, we modeled the fMRI responses as a function of the sounds' perceived pitch height and salience (related to the fundamental frequency and the harmonic structure respectively), which we estimated with a computational algorithm of pitch extraction (de Cheveigné and Kawahara, 2002). First, using single-voxel fMRI encoding, we identified a pitch-coding region in the antero-lateral Heschl's gyrus (HG) and adjacent superior temporal gyrus (STG). In these regions, the pitch representation model combining height and salience predicted the fMRI responses comparatively better than other models of acoustic processing and, in the right hemisphere, better than pitch representations based on height/salience alone. Second, we assessed with model-based decoding that multi-voxel response patterns of the identified regions are more informative of perceived pitch than the remainder of the auditory cortex. Further multivariate analyses showed that complementing a multi-resolution spectro-temporal sound representation with pitch produces a small but significant improvement to the decoding of complex sounds from fMRI response patterns. In sum, this work extends model-based fMRI encoding and decoding methods - previously employed to examine the representation and processing of acoustic sound features in the human auditory system - to the representation and processing of a relevant

  13. Evaluation of a pre-surgical functional MRI workflow: From data acquisition to reporting.

    Science.gov (United States)

    Pernet, Cyril R; Gorgolewski, Krzysztof J; Job, Dominic; Rodriguez, David; Storkey, Amos; Whittle, Ian; Wardlaw, Joanna

    2016-02-01

    Present and assess clinical protocols and associated automated workflow for pre-surgical functional magnetic resonance imaging in brain tumor patients. Protocols were validated using a single-subject reliability approach based on 10 healthy control subjects. Results from the automated workflow were evaluated in 9 patients with brain tumors, comparing fMRI results to direct electrical stimulation (DES) of the cortex. Using a new approach to compute single-subject fMRI reliability in controls, we show that not all tasks are suitable in the clinical context, even if they show meaningful results at the group level. Comparison of the fMRI results from patients to DES showed good correspondence between techniques (odds ratio 36). Providing that validated and reliable fMRI protocols are used, fMRI can accurately delineate eloquent areas, thus providing an aid to medical decision regarding brain tumor surgery. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  14. Research progress of BOLD-functional MRI of hepatic encephalopathy

    International Nuclear Information System (INIS)

    Ni Ling; Zhang Longjiang; Lu Guangming

    2013-01-01

    Hepatic encephalopathy (HE), characterized by a wide spectrum of clinical manifestations, ranging from behavior abnormality, conscious disorder and even coma, is a consequence of liver dysfunction in both acute and chronic hepatic diseases. Minimal hepatic encephalopathy (MHE) refers to a subgroup of cirrhotic patients without clinical overt hepatic encephalopathy symptoms hut with abnormalities in neuro -cognitive functions. HE/MHE can have a far-reaching impact on quality of life and prognosis. The exact neuropathology mechanism was still unclear. Recently, functional MRI (fMRI) has been increasingly applied for investigating the neuro-pathophysiological mechanism of HE. This paper will review the fMRI research applied on uncovering the neuropathology mechanism of HE. (authors)

  15. Sensitivity and specificity considerations for fMRI encoding, decoding, and mapping of auditory cortex at ultra-high field.

    Science.gov (United States)

    Moerel, Michelle; De Martino, Federico; Kemper, Valentin G; Schmitter, Sebastian; Vu, An T; Uğurbil, Kâmil; Formisano, Elia; Yacoub, Essa

    2018-01-01

    Following rapid technological advances, ultra-high field functional MRI (fMRI) enables exploring correlates of neuronal population activity at an increasing spatial resolution. However, as the fMRI blood-oxygenation-level-dependent (BOLD) contrast is a vascular signal, the spatial specificity of fMRI data is ultimately determined by the characteristics of the underlying vasculature. At 7T, fMRI measurement parameters determine the relative contribution of the macro- and microvasculature to the acquired signal. Here we investigate how these parameters affect relevant high-end fMRI analyses such as encoding, decoding, and submillimeter mapping of voxel preferences in the human auditory cortex. Specifically, we compare a T 2 * weighted fMRI dataset, obtained with 2D gradient echo (GE) EPI, to a predominantly T 2 weighted dataset obtained with 3D GRASE. We first investigated the decoding accuracy based on two encoding models that represented different hypotheses about auditory cortical processing. This encoding/decoding analysis profited from the large spatial coverage and sensitivity of the T 2 * weighted acquisitions, as evidenced by a significantly higher prediction accuracy in the GE-EPI dataset compared to the 3D GRASE dataset for both encoding models. The main disadvantage of the T 2 * weighted GE-EPI dataset for encoding/decoding analyses was that the prediction accuracy exhibited cortical depth dependent vascular biases. However, we propose that the comparison of prediction accuracy across the different encoding models may be used as a post processing technique to salvage the spatial interpretability of the GE-EPI cortical depth-dependent prediction accuracy. Second, we explored the mapping of voxel preferences. Large-scale maps of frequency preference (i.e., tonotopy) were similar across datasets, yet the GE-EPI dataset was preferable due to its larger spatial coverage and sensitivity. However, submillimeter tonotopy maps revealed biases in assigned frequency

  16. Hypercapnic normalization of BOLD fMRI: comparison across field strengths and pulse sequences

    DEFF Research Database (Denmark)

    Cohen, Eric R.; Rostrup, Egill; Sidaros, Karam

    2004-01-01

    to be more accurately localized and quantified based on changes in venous blood oxygenation alone. The normalized BOLD signal induced by the motor task was consistent across different magnetic fields and pulse sequences, and corresponded well with cerebral blood flow measurements. Our data suggest...... size, as well as experimental, such as pulse sequence and static magnetic field strength (B(0)). Thus, it is difficult to compare task-induced fMRI signals across subjects, field strengths, and pulse sequences. This problem can be overcome by normalizing the neural activity-induced BOLD fMRI response...... for global stimulation, subjects breathed a 5% CO(2) gas mixture. Under all conditions, voxels containing primarily large veins and those containing primarily active tissue (i.e., capillaries and small veins) showed distinguishable behavior after hypercapnic normalization. This allowed functional activity...

  17. IMAGING OF BRAIN FUNCTION BASED ON THE ANALYSIS OF FUNCTIONAL CONNECTIVITY - IMAGING ANALYSIS OF BRAIN FUNCTION BY FMRI AFTER ACUPUNCTURE AT LR3 IN HEALTHY INDIVIDUALS

    OpenAIRE

    Zheng, Yu; Wang, Yuying; Lan, Yujun; Qu, Xiaodong; Lin, Kelin; Zhang, Jiping; Qu, Shanshan; Wang, Yanjie; Tang, Chunzhi; Huang, Yong

    2016-01-01

    Objective: This Study observed the relevant brain areas activated by acupuncture at the Taichong acupoint (LR3) and analyzed the functional connectivity among brain areas using resting state functional magnetic resonance imaging (fMRI) to explore the acupoint specificity of the Taichong acupoint. Methods: A total of 45 healthy subjects were randomly divided into the Taichong (LR3) group, sham acupuncture group and sham acupoint group. Subjects received resting state fMRI before acupuncture, a...

  18. The potential of functional MRI as a biomarker in early Alzheimer’s disease

    OpenAIRE

    Sperling, Reisa

    2011-01-01

    Functional magnetic resonance imaging (fMRI) is a relative newcomer in the field of biomarkers for Alzheimer’s disease (AD). fMRI has several potential advantages, particularly for clinical trials, as it is a non-invasive imaging technique that does not require the injection of contrast agent or radiation exposure and thus can be repeated many times during a longitudinal study. fMRI has relatively high spatial and reasonable temporal resolution, and can be acquired in the same session as stru...

  19. Resting State fMRI Functional Connectivity-Based Classification Using a Convolutional Neural Network Architecture.

    Science.gov (United States)

    Meszlényi, Regina J; Buza, Krisztian; Vidnyánszky, Zoltán

    2017-01-01

    Machine learning techniques have become increasingly popular in the field of resting state fMRI (functional magnetic resonance imaging) network based classification. However, the application of convolutional networks has been proposed only very recently and has remained largely unexplored. In this paper we describe a convolutional neural network architecture for functional connectome classification called connectome-convolutional neural network (CCNN). Our results on simulated datasets and a publicly available dataset for amnestic mild cognitive impairment classification demonstrate that our CCNN model can efficiently distinguish between subject groups. We also show that the connectome-convolutional network is capable to combine information from diverse functional connectivity metrics and that models using a combination of different connectivity descriptors are able to outperform classifiers using only one metric. From this flexibility follows that our proposed CCNN model can be easily adapted to a wide range of connectome based classification or regression tasks, by varying which connectivity descriptor combinations are used to train the network.

  20. Residual fMRI sensitivity for identity changes in acquired prosopagnosia.

    Science.gov (United States)

    Fox, Christopher J; Iaria, Giuseppe; Duchaine, Bradley C; Barton, Jason J S

    2013-01-01

    While a network of cortical regions contribute to face processing, the lesions in acquired prosopagnosia are highly variable, and likely result in different combinations of spared and affected regions of this network. To assess the residual functional sensitivities of spared regions in prosopagnosia, we designed a rapid event-related functional magnetic resonance imaging (fMRI) experiment that included pairs of faces with same or different identities and same or different expressions. By measuring the release from adaptation to these facial changes we determined the residual sensitivity of face-selective regions-of-interest. We tested three patients with acquired prosopagnosia, and all three of these patients demonstrated residual sensitivity for facial identity changes in surviving fusiform and occipital face areas of either the right or left hemisphere, but not in the right posterior superior temporal sulcus. The patients also showed some residual capabilities for facial discrimination with normal performance on the Benton Facial Recognition Test, but impaired performance on more complex tasks of facial discrimination. We conclude that fMRI can demonstrate residual processing of facial identity in acquired prosopagnosia, that this adaptation can occur in the same structures that show similar processing in healthy subjects, and further, that this adaptation may be related to behavioral indices of face perception.

  1. Residual fMRI sensitivity for identity changes in acquired prosopagnosia

    Directory of Open Access Journals (Sweden)

    Christopher J Fox

    2013-10-01

    Full Text Available While a network of cortical regions contribute to face processing, the lesions in acquired prosopagnosia are highly variable, and likely result in different combinations of spared and affected regions of this network. To assess the residual functional sensitivities of spared regions in prosopagnosia, we designed a rapid event-related functional magnetic resonance imaging (fMRI experiment that included pairs of faces with same or different identities and same or different expressions. By measuring the release from adaptation to these facial changes we determined the residual sensitivity of face-selective regions-of-interest. We tested three patients with acquired prosopagnosia, and all three of these patients demonstrated residual sensitivity for facial identity changes in surviving fusiform and occipital face areas of either the right or left hemisphere, but not in the right posterior superior temporal sulcus. The patients also showed some residual capabilities for facial discrimination with normal performance on the Benton Facial Recognition Test, but impaired performance on more complex tasks of facial discrimination. We conclude that fMRI can demonstrate residual processing of facial identity in acquired prosopagnosia, that this adaptation can occur in the same structures that show similar processing in healthy subjects, and further, that this adaptation may be related to behavioral indices of face perception.

  2. Directional patterns of cross frequency phase and amplitude coupling within the resting state mimic patterns of fMRI functional connectivity

    Science.gov (United States)

    Weaver, Kurt E.; Wander, Jeremiah D.; Ko, Andrew L.; Casimo, Kaitlyn; Grabowski, Thomas J.; Ojemann, Jeffrey G.; Darvas, Felix

    2016-01-01

    Functional imaging investigations into the brain's resting state interactions have yielded a wealth of insight into the intrinsic and dynamic neural architecture supporting cognition and behavior. Electrophysiological studies however have highlighted the fact that synchrony across large-scale cortical systems is composed of spontaneous interactions occurring at timescales beyond the traditional resolution of fMRI, a feature that limits the capacity of fMRI to draw inference on the true directional relationship between network nodes. To approach the question of directionality in resting state signals, we recorded resting state functional MRI (rsfMRI) and electrocorticography (ECoG) from four human subjects undergoing invasive epilepsy monitoring. Using a seed-point based approach, we employed phase-amplitude coupling (PAC) and biPhase Locking Values (bPLV), two measures of cross-frequency coupling (CFC) to explore both outgoing and incoming connections between the seed and all non-seed, site electrodes. We observed robust PAC between a wide range of low-frequency phase and high frequency amplitude estimates. However, significant bPLV, a CFC measure of phase-phase synchrony, was only observed at specific narrow low and high frequency bandwidths. Furthermore, the spatial patterns of outgoing PAC connectivity were most closely associated with the rsfMRI connectivity maps. Our results support the hypothesis that PAC is relatively ubiquitous phenomenon serving as a mechanism for coordinating high-frequency amplitudes across distant neuronal assemblies even in absence of overt task structure. Additionally, we demonstrate that the spatial distribution of a seed-point rsfMRI sensorimotor network is strikingly similar to specific patterns of directional PAC. Specifically, the high frequency activities of distal patches of cortex owning membership in a rsfMRI sensorimotor network were most likely to be entrained to the phase of a low frequency rhythm engendered from the

  3. Working memory capacity and the functional connectome - insights from resting-state fMRI and voxelwise centrality mapping.

    Science.gov (United States)

    Markett, Sebastian; Reuter, Martin; Heeren, Behrend; Lachmann, Bernd; Weber, Bernd; Montag, Christian

    2018-02-01

    The functional connectome represents a comprehensive network map of functional connectivity throughout the human brain. To date, the relationship between the organization of functional connectivity and cognitive performance measures is still poorly understood. In the present study we use resting-state functional magnetic resonance imaging (fMRI) data to explore the link between the functional connectome and working memory capacity in an individual differences design. Working memory capacity, which refers to the maximum amount of context information that an individual can retain in the absence of external stimulation, was assessed outside the MRI scanner and estimated based on behavioral data from a change detection task. Resting-state time series were analyzed by means of voxelwise degree and eigenvector centrality mapping, which are data-driven network analytic approaches for the characterization of functional connectivity. We found working memory capacity to be inversely correlated with both centrality in the right intraparietal sulcus. Exploratory analyses revealed that this relationship was putatively driven by an increase in negative connectivity strength of the structure. This resting-state connectivity finding fits previous task based activation studies that have shown that this area responds to manipulations of working memory load.

  4. Role of mitochondrial calcium uptake homeostasis in resting state fMRI brain networks.

    Science.gov (United States)

    Kannurpatti, Sridhar S; Sanganahalli, Basavaraju G; Herman, Peter; Hyder, Fahmeed

    2015-11-01

    Mitochondrial Ca(2+) uptake influences both brain energy metabolism and neural signaling. Given that brain mitochondrial organelles are distributed in relation to vascular density, which varies considerably across brain regions, we hypothesized different physiological impacts of mitochondrial Ca(2+) uptake across brain regions. We tested the hypothesis by monitoring brain "intrinsic activity" derived from the resting state functional MRI (fMRI) blood oxygen level dependent (BOLD) fluctuations in different functional networks spanning the somatosensory cortex, caudate putamen, hippocampus and thalamus, in normal and perturbed mitochondrial Ca(2+) uptake states. In anesthetized rats at 11.7 T, mitochondrial Ca(2+) uptake was inhibited or enhanced respectively by treatments with Ru360 or kaempferol. Surprisingly, mitochondrial Ca(2+) uptake inhibition by Ru360 and enhancement by kaempferol led to similar dose-dependent decreases in brain-wide intrinsic activities in both the frequency domain (spectral amplitude) and temporal domain (resting state functional connectivity; RSFC). The fact that there were similar dose-dependent decreases in the frequency and temporal domains of the resting state fMRI-BOLD fluctuations during mitochondrial Ca(2+) uptake inhibition or enhancement indicated that mitochondrial Ca(2+) uptake and its homeostasis may strongly influence the brain's functional organization at rest. Interestingly, the resting state fMRI-derived intrinsic activities in the caudate putamen and thalamic regions saturated much faster with increasing dosage of either drug treatment than the drug-induced trends observed in cortical and hippocampal regions. Regional differences in how the spectral amplitude and RSFC changed with treatment indicate distinct mitochondrion-mediated spontaneous neuronal activity coupling within the various RSFC networks determined by resting state fMRI. Copyright © 2015 John Wiley & Sons, Ltd.

  5. Cerebral somatic pain modulation during autogenic training in fMRI.

    Science.gov (United States)

    Naglatzki, R P; Schlamann, M; Gasser, T; Ladd, M E; Sure, U; Forsting, M; Gizewski, E R

    2012-10-01

    Functional magnetic resonance imaging (fMRI) studies are increasingly employed in different conscious states. Autogenic training (AT) is a common clinically used relaxation method. The purpose of this study was to investigate the cerebral modulation of pain activity patterns due to AT and to correlate the effects to the degree of experience with AT and strength of stimuli. Thirteen volunteers familiar with AT were studied with fMRI during painful electrical stimulation in a block design alternating between resting state and electrical stimulation, both without AT and while employing the same paradigm when utilizing their AT abilities. The subjective rating of painful stimulation and success in modulation during AT was assessed. During painful electrical stimulation without AT, fMRI revealed activation of midcingulate, right secondary sensory, right supplementary motor, and insular cortices, the right thalamus and left caudate nucleus. In contrast, utilizing AT only activation of left insular and supplementary motor cortices was revealed. The paired t-test revealed pain-related activation in the midcingulate, posterior cingulate and left anterior insular cortices for the condition without AT, and activation in the left ventrolateral prefrontal cortex under AT. Activation of the posterior cingulate cortex and thalamus correlated with the amplitude of electrical stimulation. This study revealed an effect on cerebral pain processing while performing AT. This might represent the cerebral correlate of different painful stimulus processing by subjects who are trained in performing relaxation techniques. However, due to the absence of a control group, further studies are needed to confirm this theory. © 2012 European Federation of International Association for the Study of Pain Chapters.

  6. Archetypal Analysis for Modeling Multisubject fMRI Data

    DEFF Research Database (Denmark)

    Hinrich, Jesper Løve; Bardenfleth, Sophia Elizabeth; Røge, Rasmus

    2016-01-01

    are assumed to be generated by a set of 'prototype' time series. Archetypal analysis (AA) provides a promising alternative, combining the advantages of component-model flexibility with highly interpretable latent 'archetypes' (similar to cluster-model prototypes). To date, AA has not been applied to group......-level fMRI; a major limitation is that it does not generalize to multi-subject datasets, which may have significant variations in blood oxygenation-level-dependent signal and heteroscedastic noise. We develop multi-subject AA (MS-AA), which accounts for group-level data by assuming that archetypal...... performance when modelling archetypes for a motor task experiment. The procedure extracts a 'seed map' across subjects, used to provide brain parcellations with subject-specific temporal profiles. Our approach thus decomposes multisubject fMRI data into distinct interpretable component archetypes that may...

  7. Resting-state fMRI activity predicts unsupervised learning and memory in an immersive virtual reality environment.

    Directory of Open Access Journals (Sweden)

    Chi Wah Wong

    Full Text Available In the real world, learning often proceeds in an unsupervised manner without explicit instructions or feedback. In this study, we employed an experimental paradigm in which subjects explored an immersive virtual reality environment on each of two days. On day 1, subjects implicitly learned the location of 39 objects in an unsupervised fashion. On day 2, the locations of some of the objects were changed, and object location recall performance was assessed and found to vary across subjects. As prior work had shown that functional magnetic resonance imaging (fMRI measures of resting-state brain activity can predict various measures of brain performance across individuals, we examined whether resting-state fMRI measures could be used to predict object location recall performance. We found a significant correlation between performance and the variability of the resting-state fMRI signal in the basal ganglia, hippocampus, amygdala, thalamus, insula, and regions in the frontal and temporal lobes, regions important for spatial exploration, learning, memory, and decision making. In addition, performance was significantly correlated with resting-state fMRI connectivity between the left caudate and the right fusiform gyrus, lateral occipital complex, and superior temporal gyrus. Given the basal ganglia's role in exploration, these findings suggest that tighter integration of the brain systems responsible for exploration and visuospatial processing may be critical for learning in a complex environment.

  8. Dual-Tasking Alleviated Sleep Deprivation Disruption in Visuomotor Tracking: An fMRI Study

    Science.gov (United States)

    Gazes, Yunglin; Rakitin, Brian C.; Steffener, Jason; Habeck, Christian; Butterfield, Brady; Basner, Robert C.; Ghez, Claude; Stern, Yaakov

    2012-01-01

    Effects of dual-responding on tracking performance after 49-h of sleep deprivation (SD) were evaluated behaviorally and with functional magnetic resonance imaging (fMRI). Continuous visuomotor tracking was performed simultaneously with an intermittent color-matching visual detection task in which a pair of color-matched stimuli constituted a…

  9. Analyzing functional, structural, and anatomical correlation of hemispheric language lateralization in healthy subjects using functional MRI, diffusion tensor imaging, and voxel-based morphometry.

    Science.gov (United States)

    James, Jija S; Kumari, Sheela R; Sreedharan, Ruma Madhu; Thomas, Bejoy; Radhkrishnan, Ashalatha; Kesavadas, Chandrasekharan

    2015-01-01

    To evaluate the efficacy of diffusion fiber tractography (DFT) and voxel-based morphometry (VBM) for lateralizing language in comparison with functional magnetic resonance imaging (fMRI) to noninvasively assess hemispheric language lateralization in normal healthy volunteers. The aim of the present study is to evaluate the concordance of language lateralization obtained by diffusion tensor imaging (DTI) and VBM to fMRI, and thus to see whether there exists an anatomical correlate for language lateralization result obtained using fMRI. This is an advanced neuroimaging study conducted in normal healthy volunteers. Fifty-seven normal healthy subjects (39 males and 18 females; age range: 15-40 years) underwent language fMRI and 30 underwent direction DTI. fMRI language laterality index (LI), fiber tract asymmetry index (AI), and tract-based statistics of dorsal and ventral language pathways were calculated. The combined results were correlated with VBM-based volumetry of Heschl's gyrus (HG), planum temporale (PT), and insula for lateralization of language function. A linear regression analysis was done to study the correlation between fMRI, DTI, and VBM measurements. A good agreement was found between language fMRI LI and fiber tract AI, more specifically for arcuate fasciculus (ArcF) and inferior longitudinal fasciculus (ILF). The study demonstrated significant correlations (P based statistics, and PT and HG volumetry for determining language lateralization. A strong one-to-one correlation between fMRI, laterality index, DTI tractography measures, and VBM-based volumetry measures for determining language lateralization exists.

  10. Classification of fMRI independent components using IC-fingerprints and support vector machine classifiers.

    Science.gov (United States)

    De Martino, Federico; Gentile, Francesco; Esposito, Fabrizio; Balsi, Marco; Di Salle, Francesco; Goebel, Rainer; Formisano, Elia

    2007-01-01

    We present a general method for the classification of independent components (ICs) extracted from functional MRI (fMRI) data sets. The method consists of two steps. In the first step, each fMRI-IC is associated with an IC-fingerprint, i.e., a representation of the component in a multidimensional space of parameters. These parameters are post hoc estimates of global properties of the ICs and are largely independent of a specific experimental design and stimulus timing. In the second step a machine learning algorithm automatically separates the IC-fingerprints into six general classes after preliminary training performed on a small subset of expert-labeled components. We illustrate this approach in a multisubject fMRI study employing visual structure-from-motion stimuli encoding faces and control random shapes. We show that: (1) IC-fingerprints are a valuable tool for the inspection, characterization and selection of fMRI-ICs and (2) automatic classifications of fMRI-ICs in new subjects present a high correspondence with those obtained by expert visual inspection of the components. Importantly, our classification procedure highlights several neurophysiologically interesting processes. The most intriguing of which is reflected, with high intra- and inter-subject reproducibility, in one IC exhibiting a transiently task-related activation in the 'face' region of the primary sensorimotor cortex. This suggests that in addition to or as part of the mirror system, somatotopic regions of the sensorimotor cortex are involved in disambiguating the perception of a moving body part. Finally, we show that the same classification algorithm can be successfully applied, without re-training, to fMRI collected using acquisition parameters, stimulation modality and timing considerably different from those used for training.

  11. N-back Working Memory Task: Meta-analysis of Normative fMRI Studies With Children.

    Science.gov (United States)

    Yaple, Zachary; Arsalidou, Marie

    2018-05-07

    The n-back task is likely the most popular measure of working memory for functional magnetic resonance imaging (fMRI) studies. Despite accumulating neuroimaging studies with the n-back task and children, its neural representation is still unclear. fMRI studies that used the n-back were compiled, and data from children up to 15 years (n = 260) were analyzed using activation likelihood estimation. Results show concordance in frontoparietal regions recognized for their role in working memory as well as regions not typically highlighted as part of the working memory network, such as the insula. Findings are discussed in terms of developmental methodology and potential contribution to developmental theories of cognition. © 2018 Society for Research in Child Development.

  12. The effectiveness of the computerized visual perceptual training program on individuals with Down syndrome: An fMRI study.

    Science.gov (United States)

    Wan, Yi-Ting; Chiang, Ching-Sui; Chen, Sharon Chia-Ju; Wuang, Yee-Pay

    2017-07-01

    This study investigated the effectiveness of the Computerized Visual Perception Training (CVPT) program on individuals with Down syndrome (DS, mean age=13.17±4.35years, age range: 6.54-20.75 years). All participants have mild intellectual disability classified by the standard IQ measures (mean=61.2, ranges from 55 to 68). Both the Test of Visual Perceptual Skill- Third Edition (TVPS-3) and functional magnetic resonance imaging (fMRI) were used to evaluate the training outcomes. Results of TVPS-3 and fMRI showed that DS group had visual perceptual deficits and abnormal neural networks related to visual organization. The results showed that DS intervention group had significant improvements on TVPS-3 after intervention. The fMRI results indicated more activation in superior and inferior parietal lobes (spatial manipulation), as well as precentral gyrus and dorsal premotor cortex (motor imagery) in DS intervention group. The CVPT program was effective in improving visual perceptual functions and enhancing associated cortical activations in DS. Copyright © 2017 Elsevier Ltd. All rights reserved.

  13. Functional MRI in children: clinical and research applications

    International Nuclear Information System (INIS)

    Leach, James L.; Holland, Scott K.

    2010-01-01

    Functional MRI has become a critical research tool for evaluating brain function and developmental trajectories in children. Its clinical use in children is becoming more common. This presentation will review the basic underlying physiologic and technical aspects of fMRI, review research applications that have direct clinical relevance, and outline the current clinical uses of this technology. (orig.)

  14. fMRI Evidence for Dorsal Stream Processing Abnormality in Adults Born Preterm

    Science.gov (United States)

    Chaminade, Thierry; Leutcher, Russia Ha-Vinh; Millet, Veronique; Deruelle, Christine

    2013-01-01

    We investigated the consequences of premature birth on the functional neuroanatomy of the dorsal stream of visual processing. fMRI was recorded while sixteen healthy participants, 8 (two men) adults (19 years 6 months old, SD 10 months) born premature (mean gestational age 30 weeks), referred to as Premas, and 8 (two men) matched controls (20…

  15. Integrating fMRI with psychophysiological measurements in the study of decision-making

    OpenAIRE

    Wong, Savio W.H.; Xue, Gui; Bechara, Antoine

    2011-01-01

    Neuroimaging techniques have recently been used to examine the neural mechanism of decision-making. Nevertheless, most of the neuroimaging studies overlook the importance of emotion and autonomic response in modulating the process of decision-making. In this paper, we discussed how to integrating fMRI with psychophysiological measurements in studying decision-making. We suggested that psychophysiological data would complement with fMRI findings in providing a more comprehensive understanding ...

  16. Brain Activity Unique to Orgasm in Women: An fMRI Analysis.

    Science.gov (United States)

    Wise, Nan J; Frangos, Eleni; Komisaruk, Barry R

    2017-11-01

    Although the literature on imaging of regional brain activity during sexual arousal in women and men is extensive and largely consistent, that on orgasm is relatively limited and variable, owing in part to the methodologic challenges posed by variability in latency to orgasm in participants and head movement. To compare brain activity at orgasm (self- and partner-induced) with that at the onset of genital stimulation, immediately before the onset of orgasm, and immediately after the cessation of orgasm and to upgrade the methodology for obtaining and analyzing functional magnetic resonance imaging (fMRI) findings. Using fMRI, we sampled equivalent time points across female participants' variable durations of stimulation and orgasm in response to self- and partner-induced clitoral stimulation. The first 20-second epoch of orgasm was contrasted with the 20-second epochs at the beginning of stimulation and immediately before and after orgasm. Separate analyses were conducted for whole-brain and brainstem regions of interest. For a finer-grained analysis of the peri-orgasm phase, we conducted a time-course analysis on regions of interest. Head movement was minimized to a mean less than 1.3 mm using a custom-fitted thermoplastic whole-head and neck brace stabilizer. Ten women experienced orgasm elicited by self- and partner-induced genital stimulation in a Siemens 3-T Trio fMRI scanner. Brain activity gradually increased leading up to orgasm, peaked at orgasm, and then decreased. We found no evidence of deactivation of brain regions leading up to or during orgasm. The activated brain regions included sensory, motor, reward, frontal cortical, and brainstem regions (eg, nucleus accumbens, insula, anterior cingulate cortex, orbitofrontal cortex, operculum, right angular gyrus, paracentral lobule, cerebellum, hippocampus, amygdala, hypothalamus, ventral tegmental area, and dorsal raphe). Insight gained from the present findings could provide guidance toward a rational basis

  17. Emerging role of functional brain MRI in low-grade glioma surgery

    DEFF Research Database (Denmark)

    Friismose, Ancuta; Traise, Peter; Markovic, Ljubo

    Learning objectives 1. To describe the use of functional MRI (fMRI) in cranial surgery planning for patients with low-grade gliomas (LGG). 2. To show the increasing importance of fMRI in the clinical setting. Background LGG include brain tumors classified by the World Health Organization as grade I...... be used to map eloquent cortex areas, thus minimizing postoperative deficits and improving surgical performance. Findings and procedure details Patients diagnosed with low-grade gliomas located in eloquent brain areas undergo fMRI prior to surgery. The exams are performed on a 3T MR system (Achieva TX....... Language comprehension and visual tasks can be added to visualize Wernicke’s area or the visual cortex. Diffusion tensor imaging (DTI) is used to map nerve tract course relative to the tumour. Conclusion FMRI has proven its clinical utility in locating eloquent brain areas with relation to tumor site...

  18. Neural mechanisms of the mind, Aristotle, Zadeh, and fMRI.

    Science.gov (United States)

    Perlovsky, Leonid I

    2010-05-01

    Processes in the mind: perception, cognition, concepts, instincts, emotions, and higher cognitive abilities for abstract thinking, beautiful music are considered here within a neural modeling fields (NMFs) paradigm. Its fundamental mathematical mechanism is a process "from vague-fuzzy to crisp," called dynamic logic (DL). This paper discusses why this paradigm is necessary mathematically, and relates it to a psychological description of the mind. Surprisingly, the process from "vague to crisp" corresponds to Aristotelian understanding of mental functioning. Recent functional magnetic resonance imaging (fMRI) measurements confirmed this process in neural mechanisms of perception.

  19. Impaired risk evaluation in people with Internet gaming disorder: fMRI evidence from a probability discounting task.

    Science.gov (United States)

    Lin, Xiao; Zhou, Hongli; Dong, Guangheng; Du, Xiaoxia

    2015-01-02

    This study examined how Internet gaming disorder (IGD) subjects modulating reward and risk at a neural level under a probability-discounting task with functional magnetic resonance imaging (fMRI). Behavioral and imaging data were collected from 19 IGD subjects (22.2 ± 3.08 years) and 21 healthy controls (HC, 22.8 ± 3.5 years). Behavior results showed that IGD subjects prefer the probabilistic options to fixed ones and were associated with shorter reaction time, when comparing to HC. The fMRI results revealed that IGD subjects show decreased activation in the inferior frontal gyrus and the precentral gyrus when choosing the probabilistic options than HC. Correlations were also calculated between behavioral performances and brain activities in relevant brain regions. Both of the behavioral performance and fMRI results indicate that people with IGD show impaired risk evaluation, which might be the reason why IGD subjects continue playing online games despite the risks of widely known negative consequence. Copyright © 2014 Elsevier Inc. All rights reserved.

  20. How Verbal and Spatial Manipulation Networks Contribute to Calculation: An fMRI Study

    Science.gov (United States)

    Zago, Laure; Petit, Laurent; Turbelin, Marie-Renee; Andersson, Frederic; Vigneau, Mathieu; Tzourio-Mazoyer, Nathalie

    2008-01-01

    The manipulation of numbers required during calculation is known to rely on working memory (WM) resources. Here, we investigated the respective contributions of verbal and/or spatial WM manipulation brain networks during the addition of four numbers performed by adults, using functional magnetic resonance imaging (fMRI). Both manipulation and…

  1. Time course based artifact identification for independent components of resting state fMRI

    Directory of Open Access Journals (Sweden)

    Christian eRummel

    2013-05-01

    Full Text Available In functional magnetic resonance imaging (fMRI coherent oscillations of the blood oxygen level dependent (BOLD signal can be detected. These arise when brain regions respond to external stimuli or are activated by tasks. The same networks have been characterized during wakeful rest when functional connectivity of the human brain is organized in generic resting state networks (RSN. Alterations of RSN emerge as neurobiological markers of pathological conditions such as altered mental state. In single-subject fMRI data the coherent components can be identified by blind source separation of the pre-processed BOLD data using spatial independent component analysis (ICA and related approaches. The resulting maps may represent physiological RSNs or may be due to various artifacts. In this methodological study, we propose a conceptually simple and fully automatic time course based filtering procedure to detect obvious artifacts in the ICA output for resting state fMRI. The filter is trained on six and tested on 29 healthy subjects, yielding mean filter accuracy, sensitivity and specificity of 0.80, 0.82 and 0.75 in out-of-sample tests. To estimate the impact of clearly artifactual single-subject components on group resting state studies we analyze unfiltered and filtered output with a second level ICA procedure. Although the automated filter does not reach performance values of visual analysis by human raters, we propose that resting state compatible analysis of ICA time courses could be very useful to complement the existing map or task/event oriented artifact classification algorithms.

  2. fMRI and brain activation after sport concussion: a tale of two cases

    Directory of Open Access Journals (Sweden)

    Michael G Hutchison

    2014-04-01

    Full Text Available Sport-related concussions are now recognized as a major public health concern: The number of participants in sport and recreation is growing, possibly playing their games faster, and there is heightened public awareness of injuries to some high-profile athletes. However, many clinicians still rely on subjective symptom reports for the clinical determination of recovery. Relying on subjective symptom reports can be dangerous, as it has been shown that some concussed athletes may downplay their symptoms. The use of neuropsychological (NP testing tools has enabled clinicians to measure the effects and extent of impairment following concussion more precisely, providing more objective metrics for determining recovery after concussion. Nevertheless, there is a remaining concern that brain abnormalities may exist beyond the point at which individuals achieve recovery in self-reported symptoms and cognition measured by NP testing. Our understanding of brain recovery after concussion is important not only from a neuroscience perspective, but also from the perspective of clinical decision making for safe return-to-play (RTP. A number of advanced neuroimaging tools, including blood oxygen level dependent (BOLD functional magnetic resonance imaging (fMRI, have independently yielded early information on these abnormal brain functions. In the two cases presented in this article, we report contrasting brain activation patterns and recovery profiles using fMRI. Importantly, fMRI was conducted using adapted versions of the most sensitive computerized NP tests administered in current clinical practice to determine impairments and recovery after sport-related concussion. One of the cases is consistent with the concept of lagging brain recovery.

  3. On the characterization of single-event related brain activity from functional Magnetic Resonance Imaging (fMRI) measurements

    KAUST Repository

    Khoram, Nafiseh; Zayane, Chadia; Laleg-Kirati, Taous-Meriem; Djellouli, Rabia

    2014-01-01

    We propose an efficient numerical technique for calibrating the mathematical model that describes the singleevent related brain response when fMRI measurements are given. This method employs a regularized Newton technique in conjunction with a

  4. Reward for food odors: an fMRI study of liking and wanting as a function of metabolic state and BMI.

    Science.gov (United States)

    Jiang, Tao; Soussignan, Robert; Schaal, Benoist; Royet, Jean-Pierre

    2015-04-01

    Brain reward systems mediate liking and wanting for food reward. Here, we explore the differential involvement of the following structures for these two components: the ventral and dorsal striatopallidal area, orbitofrontal cortex (OFC), anterior insula and anterior cingulate. Twelve healthy female participants were asked to rate pleasantness (liking of food and non-food odors) and the desire to eat (wanting of odor-evoked food) during event-related functional magnetic resonance imaging (fMRI). The subjective ratings and fMRI were performed in hunger and satiety states. Activations of regions of interest were compared as a function of task (liking vs wanting), odor category (food vs non-food) and metabolic state (hunger vs satiety). We found that the nucleus accumbens and ventral pallidum were differentially involved in liking or wanting during the hunger state, which suggests a reciprocal inhibitory influence between these structures. Neural activation of OFC subregions was correlated with either liking or wanting ratings, suggesting an OFC role in reward processing magnitude. Finally, during the hunger state, participants with a high body mass index exhibited less activation in neural structures underlying food reward processing. Our results suggest that food liking and wanting are two separable psychological constructs and may be functionally segregated within the cortico-striatopallidal circuit. © The Author (2014). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  5. The quest for EEG power band correlation with ICA derived fMRI resting state networks

    NARCIS (Netherlands)

    Meyer, M.C.; Janssen, R.J.; van Oort, E.S.B.; Beckmann, Christian; Barth, M.

    2013-01-01

    The neuronal underpinnings of blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) resting state networks (RSNs) are still unclear. To investigate the underlying mechanisms, specifically the relation to the electrophysiological signal, we used simultaneous recordings of

  6. Intrusive Memories of Distressing Information: An fMRI Study.

    Directory of Open Access Journals (Sweden)

    Eva Battaglini

    Full Text Available Although intrusive memories are characteristic of many psychological disorders, the neurobiological underpinning of these involuntary recollections are largely unknown. In this study we used functional magentic resonance imaging (fMRI to identify the neural networks associated with encoding of negative stimuli that are subsequently experienced as intrusive memories. Healthy partipants (N = 42 viewed negative and neutral images during a visual/verbal processing task in an fMRI context. Two days later they were assessed on the Impact of Event Scale for occurrence of intrusive memories of the encoded images. A sub-group of participants who reported significant intrusions (n = 13 demonstrated stronger activation in the amygdala, bilateral ACC and parahippocampal gyrus during verbal encoding relative to a group who reported no intrusions (n = 13. Within-group analyses also revealed that the high intrusion group showed greater activity in the dorsomedial (dmPFC and dorsolateral prefrontal cortex (dlPFC, inferior frontal gyrus and occipital regions during negative verbal processing compared to neutral verbal processing. These results do not accord with models of intrusions that emphasise visual processing of information at encoding but are consistent with models that highlight the role of inhibitory and suppression processes in the formation of subsequent intrusive memories.

  7. The potential of infant fMRI research and the study of early life stress as a promising exemplar

    Directory of Open Access Journals (Sweden)

    Alice M. Graham

    2015-04-01

    Full Text Available Functional magnetic resonance imaging (fMRI research with infants and toddlers has increased rapidly over the past decade, and provided a unique window into early brain development. In the current report, we review the state of the literature, which has established the feasibility and utility of task-based fMRI and resting state functional connectivity MRI (rs-fcMRI during early periods of brain maturation. These methodologies have been successfully applied beginning in the neonatal period to increase understanding of how the brain both responds to environmental stimuli, and becomes organized into large-scale functional systems that support complex behaviors. We discuss the methodological challenges posed by this promising area of research. We also highlight that despite these challenges, early work indicates a strong potential for these methods to influence multiple research domains. As an example, we focus on the study of early life stress and its influence on brain development and mental health outcomes. We illustrate the promise of these methodologies for building on, and making important contributions to, the existing literature in this field.

  8. Mapping, Learning, Visualization, Classification, and Understanding of fMRI Data in the NeuCube Evolving Spatiotemporal Data Machine of Spiking Neural Networks.

    Science.gov (United States)

    Kasabov, Nikola K; Doborjeh, Maryam Gholami; Doborjeh, Zohreh Gholami

    2017-04-01

    This paper introduces a new methodology for dynamic learning, visualization, and classification of functional magnetic resonance imaging (fMRI) as spatiotemporal brain data. The method is based on an evolving spatiotemporal data machine of evolving spiking neural networks (SNNs) exemplified by the NeuCube architecture [1]. The method consists of several steps: mapping spatial coordinates of fMRI data into a 3-D SNN cube (SNNc) that represents a brain template; input data transformation into trains of spikes; deep, unsupervised learning in the 3-D SNNc of spatiotemporal patterns from data; supervised learning in an evolving SNN classifier; parameter optimization; and 3-D visualization and model interpretation. Two benchmark case study problems and data are used to illustrate the proposed methodology-fMRI data collected from subjects when reading affirmative or negative sentences and another one-on reading a sentence or seeing a picture. The learned connections in the SNNc represent dynamic spatiotemporal relationships derived from the fMRI data. They can reveal new information about the brain functions under different conditions. The proposed methodology allows for the first time to analyze dynamic functional and structural connectivity of a learned SNN model from fMRI data. This can be used for a better understanding of brain activities and also for online generation of appropriate neurofeedback to subjects for improved brain functions. For example, in this paper, tracing the 3-D SNN model connectivity enabled us for the first time to capture prominent brain functional pathways evoked in language comprehension. We found stronger spatiotemporal interaction between left dorsolateral prefrontal cortex and left temporal while reading a negated sentence. This observation is obviously distinguishable from the patterns generated by either reading affirmative sentences or seeing pictures. The proposed NeuCube-based methodology offers also a superior classification accuracy

  9. Dominance of layer-specific microvessel dilation in contrast-enhanced high-resolution fMRI: Comparison between hemodynamic spread and vascular architecture with CLARITY.

    Science.gov (United States)

    Poplawsky, Alexander John; Fukuda, Mitsuhiro; Kang, Bok-Man; Kim, Jae Hwan; Suh, Minah; Kim, Seong-Gi

    2017-08-16

    Contrast-enhanced cerebral blood volume-weighted (CBVw) fMRI response peaks are specific to the layer of evoked synaptic activity (Poplawsky et al., 2015), but the spatial resolution limit of CBVw fMRI is unknown. In this study, we measured the laminar spread of the CBVw fMRI evoked response in the external plexiform layer (EPL, 265 ± 65 μm anatomical thickness, mean ± SD, n = 30 locations from 5 rats) of the rat olfactory bulb during electrical stimulation of the lateral olfactory tract and examined its potential vascular source. First, we obtained the evoked CBVw fMRI responses with a 55 × 55 μm 2 in-plane resolution and a 500-μm thickness at 9.4 T, and found that the fMRI signal peaked predominantly in the inner half of EPL (136 ± 54 μm anatomical thickness). The mean full-width at half-maximum of these fMRI peaks was 347 ± 102 μm and the functional spread was approximately 100 or 200 μm when the effects of the laminar thicknesses of EPL or inner EPL were removed, respectively. Second, we visualized the vascular architecture of EPL from a different rat using a Clear Lipid-exchanged Anatomically Rigid Imaging/immunostaining-compatible Tissue hYdrogel (CLARITY)-based tissue preparation method and confocal microscopy. Microvascular segments with an outer diameter of limit of the fMRI spatial resolution is approximately the average length of 1-2 microvessel segments, which may be sufficient for examining sublaminar circuits. Copyright © 2017 Elsevier Inc. All rights reserved.

  10. Human fMRI Reveals That Delayed Action Re-Recruits Visual Perception

    OpenAIRE

    Singhal, Anthony; Monaco, Simona; Kaufman, Liam D.; Culham, Jody C.

    2013-01-01

    Behavioral and neuropsychological research suggests that delayed actions rely on different neural substrates than immediate actions; however, the specific brain areas implicated in the two types of actions remain unknown. We used functional magnetic resonance imaging (fMRI) to measure human brain activation during delayed grasping and reaching. Specifically, we examined activation during visual stimulation and action execution separated by a 18-s delay interval in which subjects had to rememb...

  11. Comparative study of SVM methods combined with voxel selection for object category classification on fMRI data.

    Science.gov (United States)

    Song, Sutao; Zhan, Zhichao; Long, Zhiying; Zhang, Jiacai; Yao, Li

    2011-02-16

    Support vector machine (SVM) has been widely used as accurate and reliable method to decipher brain patterns from functional MRI (fMRI) data. Previous studies have not found a clear benefit for non-linear (polynomial kernel) SVM versus linear one. Here, a more effective non-linear SVM using radial basis function (RBF) kernel is compared with linear SVM. Different from traditional studies which focused either merely on the evaluation of different types of SVM or the voxel selection methods, we aimed to investigate the overall performance of linear and RBF SVM for fMRI classification together with voxel selection schemes on classification accuracy and time-consuming. Six different voxel selection methods were employed to decide which voxels of fMRI data would be included in SVM classifiers with linear and RBF kernels in classifying 4-category objects. Then the overall performances of voxel selection and classification methods were compared. Results showed that: (1) Voxel selection had an important impact on the classification accuracy of the classifiers: in a relative low dimensional feature space, RBF SVM outperformed linear SVM significantly; in a relative high dimensional space, linear SVM performed better than its counterpart; (2) Considering the classification accuracy and time-consuming holistically, linear SVM with relative more voxels as features and RBF SVM with small set of voxels (after PCA) could achieve the better accuracy and cost shorter time. The present work provides the first empirical result of linear and RBF SVM in classification of fMRI data, combined with voxel selection methods. Based on the findings, if only classification accuracy was concerned, RBF SVM with appropriate small voxels and linear SVM with relative more voxels were two suggested solutions; if users concerned more about the computational time, RBF SVM with relative small set of voxels when part of the principal components were kept as features was a better choice.

  12. cudaBayesreg: Parallel Implementation of a Bayesian Multilevel Model for fMRI Data Analysis

    Directory of Open Access Journals (Sweden)

    Adelino R. Ferreira da Silva

    2011-10-01

    Full Text Available Graphic processing units (GPUs are rapidly gaining maturity as powerful general parallel computing devices. A key feature in the development of modern GPUs has been the advancement of the programming model and programming tools. Compute Unified Device Architecture (CUDA is a software platform for massively parallel high-performance computing on Nvidia many-core GPUs. In functional magnetic resonance imaging (fMRI, the volume of the data to be processed, and the type of statistical analysis to perform call for high-performance computing strategies. In this work, we present the main features of the R-CUDA package cudaBayesreg which implements in CUDA the core of a Bayesian multilevel model for the analysis of brain fMRI data. The statistical model implements a Gibbs sampler for multilevel/hierarchical linear models with a normal prior. The main contribution for the increased performance comes from the use of separate threads for fitting the linear regression model at each voxel in parallel. The R-CUDA implementation of the Bayesian model proposed here has been able to reduce significantly the run-time processing of Markov chain Monte Carlo (MCMC simulations used in Bayesian fMRI data analyses. Presently, cudaBayesreg is only configured for Linux systems with Nvidia CUDA support.

  13. POBE: A Computer Program for Optimal Design of Multi-Subject Blocked fMRI Experiments

    Directory of Open Access Journals (Sweden)

    Bärbel Maus

    2014-01-01

    Full Text Available For functional magnetic resonance imaging (fMRI studies, researchers can use multi-subject blocked designs to identify active brain regions for a certain stimulus type of interest. Before performing such an experiment, careful planning is necessary to obtain efficient stimulus effect estimators within the available financial resources. The optimal number of subjects and the optimal scanning time for a multi-subject blocked design with fixed experimental costs can be determined using optimal design methods. In this paper, the user-friendly computer program POBE 1.2 (program for optimal design of blocked experiments, version 1.2 is presented. POBE provides a graphical user interface for fMRI researchers to easily and efficiently design their experiments. The computer program POBE calculates the optimal number of subjects and the optimal scanning time for user specified experimental factors and model parameters so that the statistical efficiency is maximised for a given study budget. POBE can also be used to determine the minimum budget for a given power. Furthermore, a maximin design can be determined as efficient design for a possible range of values for the unknown model parameters. In this paper, the computer program is described and illustrated with typical experimental factors for a blocked fMRI experiment.

  14. PARTICLE FILTERING WITH SEQUENTIAL PARAMETER LEARNING FOR NONLINEAR BOLD fMRI SIGNALS.

    Science.gov (United States)

    Xia, Jing; Wang, Michelle Yongmei

    Analyzing the blood oxygenation level dependent (BOLD) effect in the functional magnetic resonance imaging (fMRI) is typically based on recent ground-breaking time series analysis techniques. This work represents a significant improvement over existing approaches to system identification using nonlinear hemodynamic models. It is important for three reasons. First, instead of using linearized approximations of the dynamics, we present a nonlinear filtering based on the sequential Monte Carlo method to capture the inherent nonlinearities in the physiological system. Second, we simultaneously estimate the hidden physiological states and the system parameters through particle filtering with sequential parameter learning to fully take advantage of the dynamic information of the BOLD signals. Third, during the unknown static parameter learning, we employ the low-dimensional sufficient statistics for efficiency and avoiding potential degeneration of the parameters. The performance of the proposed method is validated using both the simulated data and real BOLD fMRI data.

  15. Decision Making under Risk Condition in Patients with Parkinson’s Disease: A Behavioural and fMRI Study

    Directory of Open Access Journals (Sweden)

    Kirsten Labudda

    2010-01-01

    Full Text Available We aimed to study whether previously described impairment in decision making under risky conditions in patients with Parkinson's disease (PD is affected by deficits in using information about potential incentives or by processing feedback (in terms of fictitious gains and losses following each decision. Additionally, we studied whether the neural correlates of using explicit information in decision making under risk differ between PD patients and healthy subjects. We investigated ten cognitively intact PD patients and twelve healthy subjects with the Game of Dice Task (GDT to assess risky decision making, and with an fMRI paradigm to analyse the neural correlates of information integration in the deliberative decision phase. Behaviourally, PD patients showed selective impairment in the GDT but not on the fMRI task that did not include a feedback component. Healthy subjects exhibited lateral prefrontal, anterior cingulate and parietal activations when integrating decision-relevant information. Despite similar behavioural patterns on the fMRI task, patients exhibited reduced parietal activation. Behavioural results suggest that PD patients’ deficits in risky decision making are dominated by impaired feedback utilization not compensable by intact cognitive functions. Our fMRI results suggest similarities but also differences in neural correlates when using explicit information for the decision process, potentially indicating different strategy application even if the interfering feedback component is excluded.

  16. fMRI activation patterns in an analytic reasoning task: consistency with EEG source localization

    Science.gov (United States)

    Li, Bian; Vasanta, Kalyana C.; O'Boyle, Michael; Baker, Mary C.; Nutter, Brian; Mitra, Sunanda

    2010-03-01

    Functional magnetic resonance imaging (fMRI) is used to model brain activation patterns associated with various perceptual and cognitive processes as reflected by the hemodynamic (BOLD) response. While many sensory and motor tasks are associated with relatively simple activation patterns in localized regions, higher-order cognitive tasks may produce activity in many different brain areas involving complex neural circuitry. We applied a recently proposed probabilistic independent component analysis technique (PICA) to determine the true dimensionality of the fMRI data and used EEG localization to identify the common activated patterns (mapped as Brodmann areas) associated with a complex cognitive task like analytic reasoning. Our preliminary study suggests that a hybrid GLM/PICA analysis may reveal additional regions of activation (beyond simple GLM) that are consistent with electroencephalography (EEG) source localization patterns.

  17. Key issues in decomposing fMRI during naturalistic and continuous music experience with independent component analysis.

    Science.gov (United States)

    Cong, Fengyu; Puoliväli, Tuomas; Alluri, Vinoo; Sipola, Tuomo; Burunat, Iballa; Toiviainen, Petri; Nandi, Asoke K; Brattico, Elvira; Ristaniemi, Tapani

    2014-02-15

    Independent component analysis (ICA) has been often used to decompose fMRI data mostly for the resting-state, block and event-related designs due to its outstanding advantage. For fMRI data during free-listening experiences, only a few exploratory studies applied ICA. For processing the fMRI data elicited by 512-s modern tango, a FFT based band-pass filter was used to further pre-process the fMRI data to remove sources of no interest and noise. Then, a fast model order selection method was applied to estimate the number of sources. Next, both individual ICA and group ICA were performed. Subsequently, ICA components whose temporal courses were significantly correlated with musical features were selected. Finally, for individual ICA, common components across majority of participants were found by diffusion map and spectral clustering. The extracted spatial maps (by the new ICA approach) common across most participants evidenced slightly right-lateralized activity within and surrounding the auditory cortices. Meanwhile, they were found associated with the musical features. Compared with the conventional ICA approach, more participants were found to have the common spatial maps extracted by the new ICA approach. Conventional model order selection methods underestimated the true number of sources in the conventionally pre-processed fMRI data for the individual ICA. Pre-processing the fMRI data by using a reasonable band-pass digital filter can greatly benefit the following model order selection and ICA with fMRI data by naturalistic paradigms. Diffusion map and spectral clustering are straightforward tools to find common ICA spatial maps. Copyright © 2013 Elsevier B.V. All rights reserved.

  18. Real time fMRI: a tool for the routine presurgical localisation of the motor cortex

    Energy Technology Data Exchange (ETDEWEB)

    Moeller, M.; Freund, M.; Schwindt, W.; Gaus, C.; Heindel, W. [University of Muenster, Department of Clinical Radiology, Munster (Germany); Greiner, C. [University of Muenster, Department of Neurosurgery, Munster (Germany)

    2005-02-01

    In patients with brain lesions adjacent to the central area, exact preoperative knowledge of the spatial relation of the tumour to the motor cortex is of major importance. Many studies have shown that functional magnetic resonance imaging (fMRI) is a reliable tool to identify the motor cortex. However, fMRI data acquisition and data processing are time-consuming procedures, and this prevents general routine clinical application. We report a new application of real time fMRI that allows immediate access to fMRI results by automatic on-line data processing. Prior to surgery we examined ten patients with a brain tumour adjacent to the central area. Three measurements were performed at a 1.5-T Magnetom Vision Scanner (Siemens, Forchheim, Germany) on seven patients and at a 1.5-T Intera Scanner (Philips, Best, The Netherlands) on three patients using a sequential finger-tapping paradigm for motor cortex activation versus at rest condition. Blood oxygen level-dependant (BOLD) images were acquired using a multislice EPI sequence (16 slices, TE 60, TR 6000, FOV 210 x 210, matrix 64 x 64). The central sulcus of the left hemisphere could be clearly identified by a maximum of cortical activity after finger tapping of the right hand in all investigated patients. In eight of ten patients the right central sulcus was localised by a signal maximum, whereas in two patients the central sulcus could not be identified due to a hemiparesis in one and strong motion artefacts in the second patient. Finger tapping with one side versus rest condition seems to result in more motion artefacts, while finger tapping of the right versus the left hand yielded the strongest signal in the central area. Real time fMRI is a quick and reliable method to identify the central sulcus and has the potential to become a clinical tool to assess patients non-invasively before neurosurgical treatment. (orig.)

  19. Functional resonance magnetic imaging (fMRI) in adolescents with idiopathic musculoskeletal pain: a paradigm of experimental pain.

    Science.gov (United States)

    Molina, Juliana; Amaro, Edson; da Rocha, Liana Guerra Sanches; Jorge, Liliana; Santos, Flavia Heloisa; Len, Claudio A

    2017-11-14

    Studies on functional magnetic resonance imaging (fMRI) have shown that adults with musculoskeletal pain syndromes tolerate smaller amount of pressure (pain) as well as differences in brain activation patterns in areas related to pain.The objective of this study was to evaluate, through fMRI, the brain activation in adolescents with idiopathic musculoskeletal pain (IMP) while performing an experimental paradigm of pain. The study included 10 consecutive adolescents with idiopathic musculoskeletal pain (average age 16.3±1.0) and 10 healthy adolescents age-matched. fMRI exams were performed in a 3 T scanner (Magnetom Trio, Siemens) using an event-related design paradigm. Pressure stimuli were performed in the nondominant hand thumb, divided into two stages, fixed pain and variable pain. The two local Research Ethics Committees (Ethics Committee from Universidade Federal de São Paulo- Brazil, process number 0688/11, on July 1st, 2011 and Ethics Committee from Hospital Israelita Albert Einsten - Brazil, process number 1673, on October 19th, 2011) approved the study. The idiopathic musculoskeletal pain (IMP) group showed a reduced threshold for pain (3.7 kg/cm 2 versus 4.45 kg/cm 2 , p = 0.005). Control group presented increased bain activation when compared to IMP group in the following areas: thalamus (p = 0.00001), precentral gyrus (p = 0.0004) and middle frontal gyrus (p = 0.03). In intragroup analysis, IMP group showed greater brain activation during the unpredictable stimuli of the variable pain stage, especially in the lingual gyrus (p = 0.0001), frontal lobe (p = 0.0001), temporal gyrus (p = 0.0001) and precentral gyrus (p = 0.03), when compared to predictable stimulus of fixed pain. The same intragroup analysis with the control group showed greater activation during the unpredictable stimuli in regions of the precentral gyrus (p = 0.0001), subcallosal area (p = 0.0001), right and left occipital fusiform gyrus (p

  20. Integration of EEG source imaging and fMRI during continuous viewing of natural movies.

    Science.gov (United States)

    Whittingstall, Kevin; Bartels, Andreas; Singh, Vanessa; Kwon, Soyoung; Logothetis, Nikos K

    2010-10-01

    Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) are noninvasive neuroimaging tools which can be used to measure brain activity with excellent temporal and spatial resolution, respectively. By combining the neural and hemodynamic recordings from these modalities, we can gain better insight into how and where the brain processes complex stimuli, which may be especially useful in patients with different neural diseases. However, due to their vastly different spatial and temporal resolutions, the integration of EEG and fMRI recordings is not always straightforward. One fundamental obstacle has been that paradigms used for EEG experiments usually rely on event-related paradigms, while fMRI is not limited in this regard. Therefore, here we ask whether one can reliably localize stimulus-driven EEG activity using the continuously varying feature intensities occurring in natural movie stimuli presented over relatively long periods of time. Specifically, we asked whether stimulus-driven aspects in the EEG signal would be co-localized with the corresponding stimulus-driven BOLD signal during free viewing of a movie. Secondly, we wanted to integrate the EEG signal directly with the BOLD signal, by estimating the underlying impulse response function (IRF) that relates the BOLD signal to the underlying current density in the primary visual area (V1). We made sequential fMRI and 64-channel EEG recordings in seven subjects who passively watched 2-min-long segments of a James Bond movie. To analyze EEG data in this natural setting, we developed a method based on independent component analysis (ICA) to reject EEG artifacts due to blinks, subject movement, etc., in a way unbiased by human judgment. We then calculated the EEG source strength of this artifact-free data at each time point of the movie within the entire brain volume using low-resolution electromagnetic tomography (LORETA). This provided for every voxel in the brain (i.e., in 3D space) an

  1. Brain activity modification produced by a single radioelectric asymmetric brain stimulation pulse: a new tool for neuropsychiatric treatments. Preliminary fMRI study

    Directory of Open Access Journals (Sweden)

    Castagna A

    2011-10-01

    Full Text Available Salvatore Rinaldi1,2, Vania Fontani1, Alessandro Castagna1 1Department of Neuro-Psycho-Physio Pathology, Rinaldi Fontani Institute, Florence, Italy; 2Medical School of Occupational Medicine, University of Florence, Florence, Italy Purpose: Radioelectric asymmetric brain stimulation technology with its treatment protocols has shown efficacy in various psychiatric disorders. The aim of this work was to highlight the mechanisms by which these positive effects are achieved. The current study was conducted to determine whether a single 500-millisecond radioelectric asymmetric conveyor (REAC brain stimulation pulse (BSP, applied to the ear, can effect a modification of brain activity that is detectable using functional magnetic resonance imaging (fMRI. Methods: Ten healthy volunteers, six females and four males, underwent fMRI during a simple finger-tapping motor task before and after receiving a single 500-millisecond REAC-BSP. Results: The fMRI results indicate that the average variation in task-induced encephalic activation patterns is lower in subjects following the single REAC pulse. Conclusion: The current report demonstrates that a single REAC-BSP is sufficient to modulate brain activity in awake subjects, able to be measured using fMRI. These initial results open new perspectives into the understanding of the effects of weak and brief radio pulses upon brain activity, and provide the basis for further indepth studies using REAC-BSP and fMRI. Keywords: fMRI, brain stimulation, brain modulation, REAC, neuropsychiatric treatments

  2. Functional MRI for immediate monitoring stereotactic thalamotomy in a patient with essential tremor

    International Nuclear Information System (INIS)

    Hesselmann, Volker; Schaaf, Maike; Krug, Barbara; Lackner, Klaus; Maarouf, Mohammed; Hunsche, Stefan; Sturm, Volker; Lasek, Kathrin; Wedekind, Christoph

    2006-01-01

    The effect of stereotactic thalamotomy was assessed with pre- and postoperative functional magnetic resonance imaging (fMRI) under motor stimulation. A patient with unilateral essential tremor (ET) of the left arm underwent stereotactically guided thalamotomy of the right ventral intermediate thalamic nucleus (VIM). FMRI was done directly before and after surgery on a 1.5-Tesla scanner. The stimulation paradigm was maintainance of the affected arm in an extended position and hand clenching being performed in a block design manner. Statistical analysis was done with Brain Voyager 2000. After thalamotomy the tremor diminished completely. As a difference between the pre- and postoperative fMRI, a significant activation was found in the VIM contralateral to the activation site, adjacent to the inferior olivary nucleus contralateral to the activation site and in the dorsal cingulum. In conclusion, fMRI can detect the functional effect of thalamotomy for tremor treatment. Direct postoperative fMRI provides a sufficient method for estimating the effect of thalamotomy immediately after intervention. The importance of the intermediate thalamic nucleus and the olivary nucleus in tremor generation is supported by our findings. (orig.)

  3. Functional MRI, DTI and neurophysiology in horizontal gaze palsy with progressive scoliosis

    Energy Technology Data Exchange (ETDEWEB)

    Haller, Sven; Wetzel, Stephan G. [University Hospital Basel, Institute of Radiology, Department of Neuroradiology, Basel (Switzerland); Luetschg, Juerg [University Children' s Hospital (UKBB), Basel (Switzerland)

    2008-05-15

    Horizontal gaze palsy with progressive scoliosis (HGPPS) is an autosomal recessive disease due to a mutation in the ROBO3 gene. This rare disease is of particular interest because the absence, or at least reduction, of crossing of the ascending lemniscal and descending corticospinal tracts in the medulla predicts abnormal ipsilateral sensory and motor systems. We evaluated the use of functional magnetic resonance imaging (fMRI) for the first time in this disease and compared it to diffusion tensor imaging (DTI) tractography and neurophysiological findings in the same patient with genetically confirmed ROBO3 mutation. As expected, motor fMRI, somatosensory evoked potentials (SSEP) and motor evoked potentials (MEP) were dominantly ipsilateral to the stimulation side. DTI tractography revealed ipsilateral ascending and descending connectivity in the brainstem yet normal interhemispheric connections in the corpus callosum. Auditory fMRI revealed bilateral auditory activation to monaural left-sided auditory stimulation. No significant cortical activation was observed after monaural right-sided stimulation, a hearing defect having been excluded. Prosaccades fMRI showed no activations in the eye-movement network. Motor fMRI confirmed the established findings of DTI and neurophysiology in the same patient. In suspected HGPPS, any technique appears appropriate for further investigation. Auditory fMRI suggests that a monaural auditory system with bilateral auditory activations might be a physiological advantage as compared to a binaural yet only unilateral auditory system, in analogy to anisometropic amblyopia. Moving-head fMRI studies in the future might show whether the compensatory head movements instead of normal eye movements activate the eye-movement network. (orig.)

  4. Functional MRI, DTI and neurophysiology in horizontal gaze palsy with progressive scoliosis

    International Nuclear Information System (INIS)

    Haller, Sven; Wetzel, Stephan G.; Luetschg, Juerg

    2008-01-01

    Horizontal gaze palsy with progressive scoliosis (HGPPS) is an autosomal recessive disease due to a mutation in the ROBO3 gene. This rare disease is of particular interest because the absence, or at least reduction, of crossing of the ascending lemniscal and descending corticospinal tracts in the medulla predicts abnormal ipsilateral sensory and motor systems. We evaluated the use of functional magnetic resonance imaging (fMRI) for the first time in this disease and compared it to diffusion tensor imaging (DTI) tractography and neurophysiological findings in the same patient with genetically confirmed ROBO3 mutation. As expected, motor fMRI, somatosensory evoked potentials (SSEP) and motor evoked potentials (MEP) were dominantly ipsilateral to the stimulation side. DTI tractography revealed ipsilateral ascending and descending connectivity in the brainstem yet normal interhemispheric connections in the corpus callosum. Auditory fMRI revealed bilateral auditory activation to monaural left-sided auditory stimulation. No significant cortical activation was observed after monaural right-sided stimulation, a hearing defect having been excluded. Prosaccades fMRI showed no activations in the eye-movement network. Motor fMRI confirmed the established findings of DTI and neurophysiology in the same patient. In suspected HGPPS, any technique appears appropriate for further investigation. Auditory fMRI suggests that a monaural auditory system with bilateral auditory activations might be a physiological advantage as compared to a binaural yet only unilateral auditory system, in analogy to anisometropic amblyopia. Moving-head fMRI studies in the future might show whether the compensatory head movements instead of normal eye movements activate the eye-movement network. (orig.)

  5. Functional MRI, DTI and neurophysiology in horizontal gaze palsy with progressive scoliosis.

    Science.gov (United States)

    Haller, Sven; Wetzel, Stephan G; Lütschg, Jürg

    2008-05-01

    Horizontal gaze palsy with progressive scoliosis (HGPPS) is an autosomal recessive disease due to a mutation in the ROBO3 gene. This rare disease is of particular interest because the absence, or at least reduction, of crossing of the ascending lemniscal and descending corticospinal tracts in the medulla predicts abnormal ipsilateral sensory and motor systems. We evaluated the use of functional magnetic resonance imaging (fMRI) for the first time in this disease and compared it to diffusion tensor imaging (DTI) tractography and neurophysiological findings in the same patient with genetically confirmed ROBO3 mutation. As expected, motor fMRI, somatosensory evoked potentials (SSEP) and motor evoked potentials (MEP) were dominantly ipsilateral to the stimulation side. DTI tractography revealed ipsilateral ascending and descending connectivity in the brainstem yet normal interhemispheric connections in the corpus callosum. Auditory fMRI revealed bilateral auditory activation to monaural left-sided auditory stimulation. No significant cortical activation was observed after monaural right-sided stimulation, a hearing defect having been excluded. Prosaccades fMRI showed no activations in the eye-movement network. Motor fMRI confirmed the established findings of DTI and neurophysiology in the same patient. In suspected HGPPS, any technique appears appropriate for further investigation. Auditory fMRI suggests that a monaural auditory system with bilateral auditory activations might be a physiological advantage as compared to a binaural yet only unilateral auditory system, in analogy to anisometropic amblyopia. Moving-head fMRI studies in the future might show whether the compensatory head movements instead of normal eye movements activate the eye-movement network.

  6. An fMRI investigation of the impact of interracial contact on executive function.

    Science.gov (United States)

    Richeson, Jennifer A; Baird, Abigail A; Gordon, Heather L; Heatherton, Todd F; Wyland, Carrie L; Trawalter, Sophie; Shelton, J Nicole

    2003-12-01

    We investigated whether individual differences in racial bias among white participants predict the recruitment, and potential depletion, of executive attentional resources during contact with black individuals. White individuals completed an unobtrusive measure of racial bias, then interacted with a black individual, and finally completed an ostensibly unrelated Stroop color-naming test. In a separate functional magnetic resonance imaging (fMRI) session, subjects were presented with unfamiliar black male faces, and the activity of brain regions thought to be critical to executive control was assessed. We found that racial bias predicted activity in right dorsolateral prefrontal cortex (DLPFC) in response to black faces. Furthermore, activity in this region predicted Stroop interference after an actual interracial interaction, and it statistically mediated the relation between racial bias and Stroop interference. These results are consistent with a resource depletion account of the temporary executive dysfunction seen in racially biased individuals after interracial contact.

  7. “Awake” intraoperative functional MRI (ai-fMRI) for mapping the eloquent cortex: Is it possible in awake craniotomy?☆

    Science.gov (United States)

    Lu, Jun-Feng; Zhang, Han; Wu, Jin-Song; Yao, Cheng-Jun; Zhuang, Dong-Xiao; Qiu, Tian-Ming; Jia, Wen-Bin; Mao, Ying; Zhou, Liang-Fu

    2012-01-01

    As a promising noninvasive imaging technique, functional MRI (fMRI) has been extensively adopted as a functional localization procedure for surgical planning. However, the information provided by preoperative fMRI (pre-fMRI) is hampered by the brain deformation that is secondary to surgical procedures. Therefore, intraoperative fMRI (i-fMRI) becomes a potential alternative that can compensate for brain shifts by updating the functional localization information during craniotomy. However, previous i-fMRI studies required that patients be under general anesthesia, preventing the wider application of such a technique as the patients cannot perform tasks unless they are awake. In this study, we propose a new technique that combines awake surgery and i-fMRI, named “awake” i-fMRI (ai-fMRI). We introduced ai-fMRI to the real-time localization of sensorimotor areas during awake craniotomy in seven patients. The results showed that ai-fMRI could successfully detect activations in the bilateral primary sensorimotor areas and supplementary motor areas for all patients, indicating the feasibility of this technique in eloquent area localization. The reliability of ai-fMRI was further validated using intraoperative stimulation mapping (ISM) in two of the seven patients. Comparisons between the pre-fMRI-derived localization result and the ai-fMRI derived result showed that the former was subject to a heavy brain shift and led to incorrect localization, while the latter solved that problem. Additionally, the approaches for the acquisition and processing of the ai-fMRI data were fully illustrated and described. Some practical issues on employing ai-fMRI in awake craniotomy were systemically discussed, and guidelines were provided. PMID:24179766

  8. Optimizing Within-Subject Experimental Designs for jICA of Multi-Channel ERP and fMRI

    Science.gov (United States)

    Mangalathu-Arumana, Jain; Liebenthal, Einat; Beardsley, Scott A.

    2018-01-01

    Joint independent component analysis (jICA) can be applied within subject for fusion of multi-channel event-related potentials (ERP) and functional magnetic resonance imaging (fMRI), to measure brain function at high spatiotemporal resolution (Mangalathu-Arumana et al., 2012). However, the impact of experimental design choices on jICA performance has not been systematically studied. Here, the sensitivity of jICA for recovering neural sources in individual data was evaluated as a function of imaging SNR, number of independent representations of the ERP/fMRI data, relationship between instantiations of the joint ERP/fMRI activity (linear, non-linear, uncoupled), and type of sources (varying parametrically and non-parametrically across representations of the data), using computer simulations. Neural sources were simulated with spatiotemporal and noise attributes derived from experimental data. The best performance, maximizing both cross-modal data fusion and the separation of brain sources, occurred with a moderate number of representations of the ERP/fMRI data (10–30), as in a mixed block/event related experimental design. Importantly, the type of relationship between instantiations of the ERP/fMRI activity, whether linear, non-linear or uncoupled, did not in itself impact jICA performance, and was accurately recovered in the common profiles (i.e., mixing coefficients). Thus, jICA provides an unbiased way to characterize the relationship between ERP and fMRI activity across brain regions, in individual data, rendering it potentially useful for characterizing pathological conditions in which neurovascular coupling is adversely affected. PMID:29410611

  9. Abnormal brain function in neuromyelitis optica: A fMRI investigation of mPASAT.

    Science.gov (United States)

    Wang, Fei; Liu, Yaou; Li, Jianjun; Sondag, Matthew; Law, Meng; Zee, Chi-Shing; Dong, Huiqing; Li, Kuncheng

    2017-10-01

    Cognitive impairment with the Neuromyelitis Optica (NMO) patients is debated. The present study is to study patterns of brain activation in NMO patients during a pair of task-related fMRI. We studied 20 patients with NMO and 20 control subjects matched for age, gender, education and handedness. All patients with NMO met the 2006 Wingerchuk diagnostic criteria. The fMRI paradigm included an auditory attention monitoring task and a modified version of the Paced Auditory Serial Addition Task (mPASAT). Both tasks were temporally and spatially balanced, with the exception of task difficulty. In mPASAT, Activation regions in control subjects included bilateral superior temporal gyri (BA22), left inferior frontal gyrus (BA45), bilateral inferior parietal lobule (BA7), left cingulate gyrus (BA32), left insula (BA13), and cerebellum. Activation regions in NMO patients included bilateral superior temporal gyri (BA22), left inferior frontal gyrus (BA9), right cingulate gyrus (BA32), right inferior parietal gyrus (BA40), left insula (BA13) and cerebellum. Some dispersed cognition related regions are greater in the patients. The present study showed altered cerebral activation during mPASAT in patients with NMO relative to healthy controls. These results are speculated to provide further evidence for brain plasticity in patients with NMO. Copyright © 2017 Elsevier B.V. All rights reserved.

  10. Generalized INverse imaging (GIN): ultrafast fMRI with physiological noise correction.

    Science.gov (United States)

    Boyacioğlu, Rasim; Barth, Markus

    2013-10-01

    An ultrafast functional magnetic resonance imaging (fMRI) technique, called generalized inverse imaging (GIN), is proposed, which combines inverse imaging with a phase constraint-leading to a less underdetermined reconstruction-and physiological noise correction. A single 3D echo planar imaging (EPI) prescan is sufficient to obtain the necessary coil sensitivity information and reference images that are used to reconstruct standard images, so that standard analysis methods are applicable. A moving dots stimulus paradigm was chosen to assess the performance of GIN. We find that the spatial localization of activation for GIN is comparable to an EPI protocol and that maximum z-scores increase significantly. The high temporal resolution of GIN (50 ms) and the acquisition of the phase information enable unaliased sampling and regression of physiological signals. Using the phase time courses obtained from the 32 channels of the receiver coils as nuisance regressors in a general linear model results in significant improvement of the functional activation, rendering the acquisition of external physiological signals unnecessary. The proposed physiological noise correction can in principle be used for other fMRI protocols, such as simultaneous multislice acquisitions, which acquire the phase information sufficiently fast and sample physiological signals unaliased. Copyright © 2012 Wiley Periodicals, Inc.

  11. Comparison of fMRI data from passive listening and active-response story processing tasks in children.

    Science.gov (United States)

    Vannest, Jennifer J; Karunanayaka, Prasanna R; Altaye, Mekibib; Schmithorst, Vincent J; Plante, Elena M; Eaton, Kenneth J; Rasmussen, Jerod M; Holland, Scott K

    2009-04-01

    To use functional MRI (fMRI) methods to visualize a network of auditory and language-processing brain regions associated with processing an aurally-presented story. We compare a passive listening (PL) story paradigm to an active-response (AR) version including online performance monitoring and a sparse acquisition technique. Twenty children (ages 11-13 years) completed PL and AR story processing tasks. The PL version presented alternating 30-second blocks of stories and tones; the AR version presented story segments, comprehension questions, and 5-second tone sequences, with fMRI acquisitions between stimuli. fMRI data was analyzed using a general linear model approach and paired t-test identifying significant group activation. Both tasks showed activation in the primary auditory cortex, superior temporal gyrus bilaterally, and left inferior frontal gyrus (IFG). The AR task demonstrated more extensive activation, including the dorsolateral prefrontal cortex and anterior/posterior cingulate cortex. Comparison of effect size in each paradigm showed a larger effect for the AR paradigm in a left inferior frontal region-of-interest (ROI). Activation patterns for story processing in children are similar in PL and AR tasks. Increases in extent and magnitude of activation in the AR task are likely associated with memory and attention resources engaged across acquisition intervals.

  12. A scalable multi-resolution spatio-temporal model for brain activation and connectivity in fMRI data

    KAUST Repository

    Castruccio, Stefano; Ombao, Hernando; Genton, Marc G.

    2018-01-01

    Functional Magnetic Resonance Imaging (fMRI) is a primary modality for studying brain activity. Modeling spatial dependence of imaging data at different spatial scales is one of the main challenges of contemporary neuroimaging, and it could allow

  13. Neuroimaging of love: fMRI meta-analysis evidence toward new perspectives in sexual medicine.

    Science.gov (United States)

    Ortigue, Stephanie; Bianchi-Demicheli, Francesco; Patel, Nisa; Frum, Chris; Lewis, James W

    2010-11-01

    Brain imaging is becoming a powerful tool in the study of human cerebral functions related to close personal relationships. Outside of subcortical structures traditionally thought to be involved in reward-related systems, a wide range of neuroimaging studies in relationship science indicate a prominent role for different cortical networks and cognitive factors. Thus, the field needs a better anatomical/network/whole-brain model to help translate scientific knowledge from lab bench to clinical models and ultimately to the patients suffering from disorders associated with love and couple relationships. The aim of the present review is to provide a review across wide range of functional magnetic resonance imaging (fMRI) studies to critically identify the cortical networks associated with passionate love, and to compare and contrast it with other types of love (such as maternal love and unconditional love for persons with intellectual disabilities). Retrospective review of pertinent neuroimaging literature. Review of published literature on fMRI studies of love illustrating brain regions associated with different forms of love. Although all fMRI studies of love point to the subcortical dopaminergic reward-related brain systems (involving dopamine and oxytocin receptors) for motivating individuals in pair-bonding, the present meta-analysis newly demonstrated that different types of love involve distinct cerebral networks, including those for higher cognitive functions such as social cognition and bodily self-representation. These metaresults provide the first stages of a global neuroanatomical model of cortical networks involved in emotions related to different aspects of love. Developing this model in future studies should be helpful for advancing clinical approaches helpful in sexual medicine and couple therapy. © 2010 International Society for Sexual Medicine.

  14. Acquisition and analysis strategies in functional MRI at high fields

    International Nuclear Information System (INIS)

    Windischberger, C.

    2001-08-01

    Functional magnetic resonance imaging represents a non-invasive technique to examine neuronal activity in the brain. It applies radio waves to excite nuclear spins, using the emitted signal during relaxation for image generation. Signal modulations from local blood flow and oxygenation level changes caused by neuronal activity are the basis for calculating functional brain maps with high spatial resolution. The present work discusses concepts for improving the spatial and temporal resolution, as well as sophisticated analysis approaches. Besides an exhaustive description of image reconstruction algorithms, computational simulations on echo-shifting in echo-planar imaging are presented and effects on spatial resolution are quantified. The results demonstrate that echo-shifting causes only minimal resolution losses for high signal-to-noise data, but leads to severe resolution degradation (up to 30 %) in images with low signal-to-noise ratios. After an overview of the mechanisms that cause fMRI signal changes subsequent to neuronal activity, explorative analysis algorithms like Fuzzy Cluster Analysis, as well as parametric approaches are described and discussed. In the context of fMRI artifacts, effects of respiratory motion are examined. For the first time, well-defined breathing patterns are used to quantify the influences on fMRI signal intensity. Also, the variability of fMRI activation in a mental rotation paradigm are investigated, using single-trial analysis. Such, intra-subject activation consistency was determined successfully. Finally, in a second study on mental rotation explorative data analysis was applied to retrieve neuro-functional hypotheses. (author)

  15. Machine learning algorithm accurately detects fMRI signature of vulnerability to major depression

    OpenAIRE

    Sato, Jo?o R.; Moll, Jorge; Green, Sophie; Deakin, John F.W.; Thomaz, Carlos E.; Zahn, Roland

    2015-01-01

    Standard functional magnetic resonance imaging (fMRI) analyses cannot assess the potential of a neuroimaging signature as a biomarker to predict individual vulnerability to major depression (MD). Here, we use machine learning for the first time to address this question. Using a recently identified neural signature of guilt-selective functional disconnection, the classification algorithm was able to distinguish remitted MD from control participants with 78.3% accuracy. This demonstrates the hi...

  16. Real-time fMRI feedback training may improve chronic tinnitus

    Energy Technology Data Exchange (ETDEWEB)

    Haller, Sven [University Hospital Basel, Institute of Radiology, Department of Neuroradiology, Basel (Switzerland); Department of Imaging and Medical Informatics, Geneva University Hospital, Institute of Neuroradiology, Geneva (Switzerland); Birbaumer, Niels [University of Tuebingen, Institute of Medical Psychology and Behavioral Neurobiology, Tuebingen (Germany); Instituto di Ricovero e Cura a Carattere Scientifico, Ospedale San Camillo, Venezia (Italy); Veit, Ralf [University of Tuebingen, Institute of Medical Psychology and Behavioral Neurobiology, Tuebingen (Germany)

    2010-03-15

    Tinnitus consists of a more or less constant aversive tone or noise and is associated with excess auditory activation. Transient distortion of this activation (repetitive transcranial magnetic stimulation, rTMS) may improve tinnitus. Recently proposed operant training in real-time functional magnetic resonance imaging (rtfMRI) neurofeedback allows voluntary modification of specific circumscribed neuronal activations. Combining these observations, we investigated whether patients suffering from tinnitus can (1) learn to voluntarily reduce activation of the auditory system by rtfMRI neurofeedback and whether (2) successful learning improves tinnitus symptoms. Six participants with chronic tinnitus were included. First, location of the individual auditory cortex was determined in a standard fMRI auditory block-design localizer. Then, participants were trained to voluntarily reduce the auditory activation (rtfMRI) with visual biofeedback of the current auditory activation. Auditory activation significantly decreased after rtfMRI neurofeedback. This reduced the subjective tinnitus in two of six participants. These preliminary results suggest that tinnitus patients learn to voluntarily reduce spatially specific auditory activations by rtfMRI neurofeedback and that this may reduce tinnitus symptoms. Optimized training protocols (frequency, duration, etc.) may further improve the results. (orig.)

  17. Real-time fMRI feedback training may improve chronic tinnitus

    International Nuclear Information System (INIS)

    Haller, Sven; Birbaumer, Niels; Veit, Ralf

    2010-01-01

    Tinnitus consists of a more or less constant aversive tone or noise and is associated with excess auditory activation. Transient distortion of this activation (repetitive transcranial magnetic stimulation, rTMS) may improve tinnitus. Recently proposed operant training in real-time functional magnetic resonance imaging (rtfMRI) neurofeedback allows voluntary modification of specific circumscribed neuronal activations. Combining these observations, we investigated whether patients suffering from tinnitus can (1) learn to voluntarily reduce activation of the auditory system by rtfMRI neurofeedback and whether (2) successful learning improves tinnitus symptoms. Six participants with chronic tinnitus were included. First, location of the individual auditory cortex was determined in a standard fMRI auditory block-design localizer. Then, participants were trained to voluntarily reduce the auditory activation (rtfMRI) with visual biofeedback of the current auditory activation. Auditory activation significantly decreased after rtfMRI neurofeedback. This reduced the subjective tinnitus in two of six participants. These preliminary results suggest that tinnitus patients learn to voluntarily reduce spatially specific auditory activations by rtfMRI neurofeedback and that this may reduce tinnitus symptoms. Optimized training protocols (frequency, duration, etc.) may further improve the results. (orig.)

  18. Detection of Brain Reorganization in Pediatric Multiple Sclerosis Using Functional MRI

    Science.gov (United States)

    2015-10-01

    including the Wechsler Intelligence Scale for Children (WISC-IV) for verbal and non-verbal intelligence; the Boston Naming Test , which evaluates a...demonstrated congruency between fMRI mappings and patient performance; 2) testing of the fMRI methods we developed for use in POMS patients was carried out...adaptive functional reorganization as a way to explain how some early-stage MS patients are able to perform well in clinical cognitive testing

  19. fMRI orientation decoding in V1 does not require global maps or globally coherent orientation stimuli.

    Science.gov (United States)

    Alink, Arjen; Krugliak, Alexandra; Walther, Alexander; Kriegeskorte, Nikolaus

    2013-01-01

    The orientation of a large grating can be decoded from V1 functional magnetic resonance imaging (fMRI) data, even at low resolution (3-mm isotropic voxels). This finding has suggested that columnar-level neuronal information might be accessible to fMRI at 3T. However, orientation decodability might alternatively arise from global orientation-preference maps. Such global maps across V1 could result from bottom-up processing, if the preferences of V1 neurons were biased toward particular orientations (e.g., radial from fixation, or cardinal, i.e., vertical or horizontal). Global maps could also arise from local recurrent or top-down processing, reflecting pre-attentive perceptual grouping, attention spreading, or predictive coding of global form. Here we investigate whether fMRI orientation decoding with 2-mm voxels requires (a) globally coherent orientation stimuli and/or (b) global-scale patterns of V1 activity. We used opposite-orientation gratings (balanced about the cardinal orientations) and spirals (balanced about the radial orientation), along with novel patch-swapped variants of these stimuli. The two stimuli of a patch-swapped pair have opposite orientations everywhere (like their globally coherent parent stimuli). However, the two stimuli appear globally similar, a patchwork of opposite orientations. We find that all stimulus pairs are robustly decodable, demonstrating that fMRI orientation decoding does not require globally coherent orientation stimuli. Furthermore, decoding remained robust after spatial high-pass filtering for all stimuli, showing that fine-grained components of the fMRI patterns reflect visual orientations. Consistent with previous studies, we found evidence for global radial and vertical preference maps in V1. However, these were weak or absent for patch-swapped stimuli, suggesting that global preference maps depend on globally coherent orientations and might arise through recurrent or top-down processes related to the perception of

  20. Effect of Integrated Cognitive Therapy on Hippocampal Functional Connectivity Patterns in Stroke Patients with Cognitive Dysfunction: A Resting-State fMRI Study

    Directory of Open Access Journals (Sweden)

    Shanli Yang

    2014-01-01

    Full Text Available Objective. This study aimed to identify abnormal hippocampal functional connectivity (FC following ischemic stroke using resting-state fMRI. We also explored whether abnormal hippocampal FC could be modulated by integrated cognitive therapy and tested whether these alterations were associated with cognitive performance. Methods. 18 right-handed cognitively impaired ischemic stroke patients and 18 healty control (HC subjects were included in this study. Stroke subjects were scanned at baseline and after integrated cognitive therapy, while HCs were only scanned at baseline, to identify regions that show significant correlations with the seed region. Behavioral and cognitive assessments were obtained before each scan. Results. During the resting state, we found abnormal hippocampal FC associated with temporal regions, insular cortex, cerebellum, and prefrontal cortex in stroke patients compared to HCs. After integrated cognitive therapy, however, the stroke group showed increased hippocampal FC mainly located in the prefrontal gyrus and the default mode network (DMN. Altered hippocampal FC was associated with cognitive improvement. Conclusion. Resting-state fMRI may provide novel insight into the study of functional networks in the brain after stroke. Furthermore, altered hippocampal FC may be a compensatory mechanism for cognitive recovery after ischemic stroke.

  1. Comparison of causality analysis on simultaneously measured fMRI and NIRS signals during motor tasks.

    Science.gov (United States)

    Anwar, Abdul Rauf; Muthalib, Makii; Perrey, Stephane; Galka, Andreas; Granert, Oliver; Wolff, Stephan; Deuschl, Guenther; Raethjen, Jan; Heute, Ulrich; Muthuraman, Muthuraman

    2013-01-01

    Brain activity can be measured using different modalities. Since most of the modalities tend to complement each other, it seems promising to measure them simultaneously. In to be presented research, the data recorded from Functional Magnetic Resonance Imaging (fMRI) and Near Infrared Spectroscopy (NIRS), simultaneously, are subjected to causality analysis using time-resolved partial directed coherence (tPDC). Time-resolved partial directed coherence uses the principle of state space modelling to estimate Multivariate Autoregressive (MVAR) coefficients. This method is useful to visualize both frequency and time dynamics of causality between the time series. Afterwards, causality results from different modalities are compared by estimating the Spearman correlation. In to be presented study, we used directionality vectors to analyze correlation, rather than actual signal vectors. Results show that causality analysis of the fMRI correlates more closely to causality results of oxy-NIRS as compared to deoxy-NIRS in case of a finger sequencing task. However, in case of simple finger tapping, no clear difference between oxy-fMRI and deoxy-fMRI correlation is identified.

  2. Active pain coping is associated with the response in real-time fMRI neurofeedback during pain.

    Science.gov (United States)

    Emmert, Kirsten; Breimhorst, Markus; Bauermann, Thomas; Birklein, Frank; Rebhorn, Cora; Van De Ville, Dimitri; Haller, Sven

    2017-06-01

    Real-time functional magnetic resonance imaging (rt-fMRI) neurofeedback is used as a tool to gain voluntary control of activity in various brain regions. Little emphasis has been put on the influence of cognitive and personality traits on neurofeedback efficacy and baseline activity. Here, we assessed the effect of individual pain coping on rt-fMRI neurofeedback during heat-induced pain. Twenty-eight healthy subjects completed the Coping Strategies Questionnaire (CSQ) prior to scanning. The first part of the fMRI experiment identified target regions using painful heat stimulation. Then, subjects were asked to down-regulate the pain target brain region during four neurofeedback runs with painful heat stimulation. Functional MRI analysis included correlation analysis between fMRI activation and pain ratings as well as CSQ ratings. At the behavioral level, the active pain coping (first principal component of CSQ) was correlated with pain ratings during neurofeedback. Concerning neuroimaging, pain sensitive regions were negatively correlated with pain coping. During neurofeedback, the pain coping was positively correlated with activation in the anterior cingulate cortex, prefrontal cortex, hippocampus and visual cortex. Thermode temperature was negatively correlated with anterior insula and dorsolateral prefrontal cortex activation. In conclusion, self-reported pain coping mechanisms and pain sensitivity are a source of variance during rt-fMRI neurofeedback possibly explaining variations in regulation success. In particular, active coping seems to be associated with successful pain regulation.

  3. Potential brain language reorganization in a boy with refractory epilepsy; an fNIRS–EEG and fMRI comparison

    Directory of Open Access Journals (Sweden)

    Phetsamone Vannasing

    2016-01-01

    Full Text Available As part of a presurgical investigation for a resection of a tumor located in the left temporal brain region, we evaluated pre- and postsurgical language lateralization in a right-handed boy with refractory epilepsy. In this study, we compared functional near infrared spectroscopy (fNIRS results obtained while the participant performed expressive and receptive language tasks with those obtained using functional magnetic resonance imaging (fMRI. This case study illustrates the potential for NIRS to contribute favorably to the localization of language functions in children with epilepsy and cognitive or behavioral problems and its potential advantages over fMRI in presurgical assessment. Moreover, it suggests that fNIRS is sensitive in localizing an atypical language network or potential brain reorganization related to epilepsy in young patients.

  4. Improving temporal resolution in fMRI using a 3D spiral acquisition and low rank plus sparse (L+S) reconstruction.

    Science.gov (United States)

    Petrov, Andrii Y; Herbst, Michael; Andrew Stenger, V

    2017-08-15

    Rapid whole-brain dynamic Magnetic Resonance Imaging (MRI) is of particular interest in Blood Oxygen Level Dependent (BOLD) functional MRI (fMRI). Faster acquisitions with higher temporal sampling of the BOLD time-course provide several advantages including increased sensitivity in detecting functional activation, the possibility of filtering out physiological noise for improving temporal SNR, and freezing out head motion. Generally, faster acquisitions require undersampling of the data which results in aliasing artifacts in the object domain. A recently developed low-rank (L) plus sparse (S) matrix decomposition model (L+S) is one of the methods that has been introduced to reconstruct images from undersampled dynamic MRI data. The L+S approach assumes that the dynamic MRI data, represented as a space-time matrix M, is a linear superposition of L and S components, where L represents highly spatially and temporally correlated elements, such as the image background, while S captures dynamic information that is sparse in an appropriate transform domain. This suggests that L+S might be suited for undersampled task or slow event-related fMRI acquisitions because the periodic nature of the BOLD signal is sparse in the temporal Fourier transform domain and slowly varying low-rank brain background signals, such as physiological noise and drift, will be predominantly low-rank. In this work, as a proof of concept, we exploit the L+S method for accelerating block-design fMRI using a 3D stack of spirals (SoS) acquisition where undersampling is performed in the k z -t domain. We examined the feasibility of the L+S method to accurately separate temporally correlated brain background information in the L component while capturing periodic BOLD signals in the S component. We present results acquired in control human volunteers at 3T for both retrospective and prospectively acquired fMRI data for a visual activation block-design task. We show that a SoS fMRI acquisition with an

  5. A Simple fMRI Compatible Robotic Stimulator to Study the Neural Mechanisms of Touch and Pain.

    Science.gov (United States)

    Riillo, F; Bagnato, C; Allievi, A G; Takagi, A; Fabrizi, L; Saggio, G; Arichi, T; Burdet, E

    2016-08-01

    This paper presents a simple device for the investigation of the human somatosensory system with functional magnetic imaging (fMRI). PC-controlled pneumatic actuation is employed to produce innocuous or noxious mechanical stimulation of the skin. Stimulation patterns are synchronized with fMRI and other relevant physiological measurements like electroencephalographic activity and vital physiological parameters. The system allows adjustable regulation of stimulation parameters and provides consistent patterns of stimulation. A validation experiment demonstrates that the system safely and reliably identifies clusters of functional activity in brain regions involved in the processing of pain. This new device is inexpensive, portable, easy-to-assemble and customizable to suit different experimental requirements. It provides robust and consistent somatosensory stimulation, which is of crucial importance to investigating the mechanisms of pain and its strong connection with the sense of touch.

  6. Perceiving Age and Gender in Unfamiliar Faces: An fMRI Study on Face Categorization

    Science.gov (United States)

    Wiese, Holger; Kloth, Nadine; Gullmar, Daniel; Reichenbach, Jurgen R.; Schweinberger, Stefan R.

    2012-01-01

    Efficient processing of unfamiliar faces typically involves their categorization (e.g., into old vs. young or male vs. female). However, age and gender categorization may pose different perceptual demands. In the present study, we employed functional magnetic resonance imaging (fMRI) to compare the activity evoked during age vs. gender…

  7. Fixing the stimulus-as-fixed-effect fallacy in task fMRI [version 2; referees: 1 approved, 2 approved with reservations

    Directory of Open Access Journals (Sweden)

    Jacob Westfall

    2017-03-01

    Full Text Available Most functional magnetic resonance imaging (fMRI experiments record the brain’s responses to samples of stimulus materials (e.g., faces or words. Yet the statistical modeling approaches used in fMRI research universally fail to model stimulus variability in a manner that affords population generalization, meaning that researchers’ conclusions technically apply only to the precise stimuli used in each study, and cannot be generalized to new stimuli. A direct consequence of this stimulus-as-fixed-effect fallacy is that the majority of published fMRI studies have likely overstated the strength of the statistical evidence they report. Here we develop a Bayesian mixed model (the random stimulus model; RSM that addresses this problem, and apply it to a range of fMRI datasets. Results demonstrate considerable inflation (50-200% in most of the studied datasets of test statistics obtained from standard “summary statistics”-based approaches relative to the corresponding RSM models. We demonstrate how RSMs can be used to improve parameter estimates, properly control false positive rates, and test novel research hypotheses about stimulus-level variability in human brain responses.

  8. Effects of Field-Map Distortion Correction on Resting State Functional Connectivity MRI

    Directory of Open Access Journals (Sweden)

    Hiroki Togo

    2017-12-01

    Full Text Available Magnetic field inhomogeneities cause geometric distortions of echo planar images used for functional magnetic resonance imaging (fMRI. To reduce this problem, distortion correction (DC with field map is widely used for both task and resting-state fMRI (rs-fMRI. Although DC with field map has been reported to improve the quality of task fMRI, little is known about its effects on rs-fMRI. Here, we tested the influence of field-map DC on rs-fMRI results using two rs-fMRI datasets derived from 40 healthy subjects: one with DC (DC+ and the other without correction (DC−. Independent component analysis followed by the dual regression approach was used for evaluation of resting-state functional connectivity networks (RSN. We also obtained the ratio of low-frequency to high-frequency signal power (0.01–0.1 Hz and above 0.1 Hz, respectively; LFHF ratio to assess the quality of rs-fMRI signals. For comparison of RSN between DC+ and DC− datasets, the default mode network showed more robust functional connectivity in the DC+ dataset than the DC− dataset. Basal ganglia RSN showed some decreases in functional connectivity primarily in white matter, indicating imperfect registration/normalization without DC. Supplementary seed-based and simulation analyses supported the utility of DC. Furthermore, we found a higher LFHF ratio after field map correction in the anterior cingulate cortex, posterior cingulate cortex, ventral striatum, and cerebellum. In conclusion, field map DC improved detection of functional connectivity derived from low-frequency rs-fMRI signals. We encourage researchers to include a DC step in the preprocessing pipeline of rs-fMRI analysis.

  9. Resting-State fMRI in MS: General Concepts and Brief Overview of Its Application

    Directory of Open Access Journals (Sweden)

    Emilia Sbardella

    2015-01-01

    Full Text Available Brain functional connectivity (FC is defined as the coherence in the activity between cerebral areas under a task or in the resting-state (RS. By applying functional magnetic resonance imaging (fMRI, RS FC shows several patterns which define RS brain networks (RSNs involved in specific functions, because brain function is known to depend not only on the activity within individual regions, but also on the functional interaction of different areas across the whole brain. Region-of-interest analysis and independent component analysis are the two most commonly applied methods for RS investigation. Multiple sclerosis (MS is characterized by multiple lesions mainly affecting the white matter, determining both structural and functional disconnection between various areas of the central nervous system. The study of RS FC in MS is mainly aimed at understanding alterations in the intrinsic functional architecture of the brain and their role in disease progression and clinical impairment. In this paper, we will examine the results obtained by the application of RS fMRI in different multiple sclerosis (MS phenotypes and the correlations of FC changes with clinical features in this pathology. The knowledge of RS FC changes may represent a substantial step forward in the MS research field, both for clinical and therapeutic purposes.

  10. A human brain atlas derived via n-cut parcellation of resting-state and task-based fMRI data.

    Science.gov (United States)

    James, George Andrew; Hazaroglu, Onder; Bush, Keith A

    2016-02-01

    The growth of functional MRI has led to development of human brain atlases derived by parcellating resting-state connectivity patterns into functionally independent regions of interest (ROIs). All functional atlases to date have been derived from resting-state fMRI data. But given that functional connectivity between regions varies with task, we hypothesized that an atlas incorporating both resting-state and task-based fMRI data would produce an atlas with finer characterization of task-relevant regions than an atlas derived from resting-state alone. To test this hypothesis, we derived parcellation atlases from twenty-nine healthy adult participants enrolled in the Cognitive Connectome project, an initiative to improve functional MRI's translation into clinical decision-making by mapping normative variance in brain-behavior relationships. Participants underwent resting-state and task-based fMRI spanning nine cognitive domains: motor, visuospatial, attention, language, memory, affective processing, decision-making, working memory, and executive function. Spatially constrained n-cut parcellation derived brain atlases using (1) all participants' functional data (Task) or (2) a single resting-state scan (Rest). An atlas was also derived from random parcellation for comparison purposes (Random). Two methods were compared: (1) a parcellation applied to the group's mean edge weights (mean), and (2) a two-stage approach with parcellation of individual edge weights followed by parcellation of mean binarized edges (two-stage). The resulting Task and Rest atlases had significantly greater similarity with each other (mean Jaccard indices JI=0.72-0.85) than with the Random atlases (JI=0.59-0.63; all pRest atlas similarity was greatest for the two-stage method (JI=0.85), which has been shown as more robust than the mean method; these atlases also better reproduced voxelwise seed maps of the left dorsolateral prefrontal cortex during rest and performing the n-back working memory

  11. Functional MRI for planning in neurosurgery

    International Nuclear Information System (INIS)

    Erb, M.; Saur, R.

    2007-01-01

    Beside structural images from CT and MR, functional data about localization of brain activations with different tasks becomes more and more important for presurgical planning. With this method, it's possible to depict mainly primary sensory and motoric areas, but also higher functions like speech and memory. To judge this information adequately, one has to be aware of the variability of activation pattern dependent on chosen threshold. Especially, the absence of such activation at a given location does not necessary mean that this area has no function. The reliability of a measurement strongly depends on efficiency of experimental design and cooperation of the patient. Therefore, short and easy tasks which can be performed in a block design should be preferred. Information about localization of functions determined by fMRI can mainly be used for presurgical planning. Intraoperative usage in the navigation system is problematic due to the brain shift. Therefore, intraoperative imaging together with dynamic adaptation using nonlinear deformation algorithms may improve the value of fMRI in the future. (orig.)

  12. Quantitative comparisons on hand motor functional areas determined by resting state and task BOLD fMRI and anatomical MRI for pre-surgical planning of patients with brain tumors

    Directory of Open Access Journals (Sweden)

    Bob L. Hou

    2016-01-01

    Full Text Available For pre-surgical planning we present quantitative comparison of the location of the hand motor functional area determined by right hand finger tapping BOLD fMRI, resting state BOLD fMRI, and anatomically using high resolution T1 weighted images. Data were obtained on 10 healthy subjects and 25 patients with left sided brain tumors. Our results show that there are important differences in the locations (i.e., >20 mm of the determined hand motor voxels by these three MR imaging methods. This can have significant effect on the pre-surgical planning of these patients depending on the modality used. In 13 of the 25 cases (i.e., 52% the distances between the task-determined and the rs-fMRI determined hand areas were more than 20 mm; in 13 of 25 cases (i.e., 52% the distances between the task-determined and anatomically determined hand areas were >20 mm; and in 16 of 25 cases (i.e., 64% the distances between the rs-fMRI determined and anatomically determined hand areas were more than 20 mm. In just three cases, the distances determined by all three modalities were within 20 mm of each other. The differences in the location or fingerprint of the hand motor areas, as determined by these three MR methods result from the different underlying mechanisms of these three modalities and possibly the effects of tumors on these modalities.

  13. On the plurality of (methodological worlds: Estimating the analytic flexibility of fMRI experiments.

    Directory of Open Access Journals (Sweden)

    Joshua eCarp

    2012-10-01

    Full Text Available How likely are published findings in the functional neuroimaging literature to be false? According to a recent mathematical model, the potential for false positives increases with the flexibility of analysis methods. Functional MRI (fMRI experiments can be analyzed using a large number of commonly used tools, with little consensus on how, when, or whether to apply each one. This situation may lead to substantial variability in analysis outcomes. Thus, the present study sought to estimate the flexibility of neuroimaging analysis by submitting a single event-related fMRI experiment to a large number of unique analysis procedures. Ten analysis steps for which multiple strategies appear in the literature were identified, and two to four strategies were enumerated for each step. Considering all possible combinations of these strategies yielded 6,912 unique analysis pipelines. Activation maps from each pipeline were corrected for multiple comparisons using five thresholding approaches, yielding 34,560 significance maps. While some outcomes were relatively consistent across pipelines, others showed substantial methods-related variability in activation strength, location, and extent. Some analysis decisions contributed to this variability more than others, and different decisions were associated with distinct patterns of variability across the brain. Qualitative outcomes also varied with analysis parameters: many contrasts yielded significant activation under some pipelines but not others. Altogether, these results reveal considerable flexibility in the analysis of fMRI experiments. This observation, when combined with mathematical simulations linking analytic flexibility with elevated false positive rates, suggests that false positive results may be more prevalent than expected in the literature. This risk of inflated false positive rates may be mitigated by constraining the flexibility of analytic choices or by abstaining from selective analysis

  14. Visual grading of 2D and 3D functional MRI compared with image-based descriptive measures

    Energy Technology Data Exchange (ETDEWEB)

    Ragnehed, Mattias [Linkoeping University, Division of Radiological Sciences, Radiology, IMH, Linkoeping (Sweden); Linkoeping University, Center for Medical Image Science and Visualization, CMIV, Linkoeping (Sweden); Linkoeping University, Department of Medical and Health Sciences, Division of Radiological Sciences/Radiology, Faculty of Health Sciences, Linkoeping (Sweden); Leinhard, Olof Dahlqvist; Pihlsgaard, Johan; Lundberg, Peter [Linkoeping University, Center for Medical Image Science and Visualization, CMIV, Linkoeping (Sweden); Linkoeping University, Division of Radiological Sciences, Radiation Physics, IMH, Linkoeping (Sweden); Wirell, Staffan [Linkoeping University, Division of Radiological Sciences, Radiology, IMH, Linkoeping (Sweden); Linkoeping University Hospital, Department of Radiology, Linkoeping (Sweden); Soekjer, Hannibal; Faegerstam, Patrik [Linkoeping University Hospital, Department of Radiology, Linkoeping (Sweden); Jiang, Bo [Linkoeping University, Center for Medical Image Science and Visualization, CMIV, Linkoeping (Sweden); Smedby, Oerjan; Engstroem, Maria [Linkoeping University, Division of Radiological Sciences, Radiology, IMH, Linkoeping (Sweden); Linkoeping University, Center for Medical Image Science and Visualization, CMIV, Linkoeping (Sweden)

    2010-03-15

    A prerequisite for successful clinical use of functional magnetic resonance imaging (fMRI) is the selection of an appropriate imaging sequence. The aim of this study was to compare 2D and 3D fMRI sequences using different image quality assessment methods. Descriptive image measures, such as activation volume and temporal signal-to-noise ratio (TSNR), were compared with results from visual grading characteristics (VGC) analysis of the fMRI results. Significant differences in activation volume and TSNR were not directly reflected by differences in VGC scores. The results suggest that better performance on descriptive image measures is not always an indicator of improved diagnostic quality of the fMRI results. In addition to descriptive image measures, it is important to include measures of diagnostic quality when comparing different fMRI data acquisition methods. (orig.)

  15. Changes in thalamus connectivity in mild cognitive impairment: Evidence from resting state fMRI

    International Nuclear Information System (INIS)

    Wang Zhiqun; Jia Xiuqin; Liang Peipeng; Qi Zhigang; Yang Yanhui; Zhou Weidong; Li Kuncheng

    2012-01-01

    Purpose: The subcortical region such as thalamus was believed to have close relationship with many cerebral cortexes which made it especially interesting in the study of functional connectivity. Here, we used resting state functional MRI (fMRI) to examine changes in thalamus connectivity in mild cognitive impairment (MCI), which presented a neuro-disconnection syndrome. Materials and methods: Data from 14 patients and 14 healthy age-matched controls were analyzed. Thalamus connectivity was investigated by examination of the correlation between low frequency fMRI signal fluctuations in the thalamus and those in all other brain regions. Results: We found that functional connectivity between the left thalamus and a set of regions was decreased in MCI; these regions are: bilateral cuneus, middle occipital gyrus (MOG), superior frontal gyrus (SFG), medial prefrontal cortex (MPFC), precuneus, inferior frontal gyrus (IFG) and precentral gyrus (PreCG). There are also some regions showed reduced connectivity to right thalamus; these regions are bilateral cuneus, MOG, fusiform gyrus (FG), MPFC, paracentral lobe (PCL), precuneus, superior parietal lobe (SPL) and IFG. We also found increased functional connectivity between the left thalamus and the right thalamus in MCI. Conclusion: The decreased connectivity between the thalamus and the other brain regions might indicate reduced integrity of thalamus-related cortical networks in MCI. Furthermore, the increased connectivity between the left and right thalamus suggest compensation for the loss of cognitive function. Briefly, impairment and compensation of thalamus connectivity coexist in the MCI patients.

  16. The cooperation of the functional activation areas in human brain: an application of event-related fMRI study of the voluntary motor function

    International Nuclear Information System (INIS)

    Li Enzhong; Tian Jie; Dai Ruwei

    2002-01-01

    Objective: To detect the cooperation of the functional activation areas in human brain using event-related fMRI technique developed in recent years. Methods: Forty-four subjects were selected in this experiment and scanned by GE Signa Horizon 1.5 Tesla superconductive MR system. A CUE-GO paradigm was used in this experiment. The data were analyzed in SUN and SGI workstation. Results: The activation areas were found in contralateral primary motor area (Ml), bilateral supplementary motor areas (SMA), pre-motor areas (PMA), basal ganglia, and cerebellar cortices. The time-signal curve of Ml was a typical single-peak curve, but the curves in PMA, basal ganglia, and cerebellar cortices were double-peak curves. SMA had 2 parts, one was Pre-SMA, and another was SMA Proper. The curve was double-peak type in Pre-SMA and single-peak type in SMA Proper. There was difference between the time-signal intensity curves in above-mentioned areas. Conclusion: (1) Ml is mainly associated with motor execution, while others with both motor preparation and execution. There are differences in the function at the variant areas in the brain. (2) The fact that bilateral SMA, PMA, basal ganglia, and cerebellar cortices were activated, is different from what the classical theories told. (3) Event-related fMRI technique has higher temporary and spatial resolutions. (4) There is cooperation among different cortical areas, basal ganglia, and cerebellum

  17. An investigation of fMRI time series stationarity during motor sequence learning foot tapping tasks.

    Science.gov (United States)

    Muhei-aldin, Othman; VanSwearingen, Jessie; Karim, Helmet; Huppert, Theodore; Sparto, Patrick J; Erickson, Kirk I; Sejdić, Ervin

    2014-04-30

    Understanding complex brain networks using functional magnetic resonance imaging (fMRI) is of great interest to clinical and scientific communities. To utilize advanced analysis methods such as graph theory for these investigations, the stationarity of fMRI time series needs to be understood as it has important implications on the choice of appropriate approaches for the analysis of complex brain networks. In this paper, we investigated the stationarity of fMRI time series acquired from twelve healthy participants while they performed a motor (foot tapping sequence) learning task. Since prior studies have documented that learning is associated with systematic changes in brain activation, a sequence learning task is an optimal paradigm to assess the degree of non-stationarity in fMRI time-series in clinically relevant brain areas. We predicted that brain regions involved in a "learning network" would demonstrate non-stationarity and may violate assumptions associated with some advanced analysis approaches. Six blocks of learning, and six control blocks of a foot tapping sequence were performed in a fixed order. The reverse arrangement test was utilized to investigate the time series stationarity. Our analysis showed some non-stationary signals with a time varying first moment as a major source of non-stationarity. We also demonstrated a decreased number of non-stationarities in the third block as a result of priming and repetition. Most of the current literature does not examine stationarity prior to processing. The implication of our findings is that future investigations analyzing complex brain networks should utilize approaches robust to non-stationarities, as graph-theoretical approaches can be sensitive to non-stationarities present in data. Copyright © 2014 Elsevier B.V. All rights reserved.

  18. Resting State fMRI in the moving fetus: a robust framework for motion, bias field and spin history correction.

    Science.gov (United States)

    Ferrazzi, Giulio; Kuklisova Murgasova, Maria; Arichi, Tomoki; Malamateniou, Christina; Fox, Matthew J; Makropoulos, Antonios; Allsop, Joanna; Rutherford, Mary; Malik, Shaihan; Aljabar, Paul; Hajnal, Joseph V

    2014-11-01

    There is growing interest in exploring fetal functional brain development, particularly with Resting State fMRI. However, during a typical fMRI acquisition, the womb moves due to maternal respiration and the fetus may perform large-scale and unpredictable movements. Conventional fMRI processing pipelines, which assume that brain movements are infrequent or at least small, are not suitable. Previous published studies have tackled this problem by adopting conventional methods and discarding as much as 40% or more of the acquired data. In this work, we developed and tested a processing framework for fetal Resting State fMRI, capable of correcting gross motion. The method comprises bias field and spin history corrections in the scanner frame of reference, combined with slice to volume registration and scattered data interpolation to place all data into a consistent anatomical space. The aim is to recover an ordered set of samples suitable for further analysis using standard tools such as Group Independent Component Analysis (Group ICA). We have tested the approach using simulations and in vivo data acquired at 1.5 T. After full motion correction, Group ICA performed on a population of 8 fetuses extracted 20 networks, 6 of which were identified as matching those previously observed in preterm babies. Copyright © 2014 Elsevier Inc. All rights reserved.

  19. Functional mapping of the sensorimotor cortex: combined use of magnetoencephalography, functional MRI, and motor evoked potentials

    International Nuclear Information System (INIS)

    Morioka, T.; Fujii, K.; Fukui, M.; Mizushima, A.; Matsumoto, S.; Hasuo, K.; Yamamoto, T.; Tobimatsu, S.

    1995-01-01

    Combined use of magnetoencephalography (MEG), functional magnetic resonance imaging (f-MRI), and motor evoked potentials (MEPs) was carried out on one patient in an attempt to localise precisely a structural lesion to the central sulcus. A small cyst in the right frontoparietal region was thought to be the cause of generalised seizures in an otherwise asymptomatic woman. First the primary sensory cortex was identified with magnetic source imaging (MSI) of somatosensory evoked magnetic fields using MEG and MRI. Second, the motor area of the hand was identified using f-MRI during handsqueezing. Then transcranial magnetic stimulation localised the hand motor area on the scalp, which was mapped onto the MRI. There was a good agreement between MSI, f-MRI and MEP as to the location of the sensorimotor cortex and its relationship to the lesion. Multimodality mapping techniques may thus prove useful in the precise localisation of cortical lesions, and in the preoperative determination of the best treatment for peri-rolandic lesions. (orig.)

  20. Functional mapping of the sensorimotor cortex: combined use of magnetoencephalography, functional MRI, and motor evoked potentials

    Energy Technology Data Exchange (ETDEWEB)

    Morioka, T. [Dept. of Neurosurgery, Neurological Inst., Kyshu Univ., Fukuoka (Japan); Fujii, K. [Dept. of Neurosurgery, Neurological Inst., Kyshu Univ., Fukuoka (Japan); Fukui, M. [Dept. of Neurosurgery, Neurological Inst., Kyshu Univ., Fukuoka (Japan); Mizushima, A. [Dept. of Radiology, Kyushu Univ. Fukuoka (Japan); Matsumoto, S. [Dept. of Radiology, Kyushu Univ. Fukuoka (Japan); Hasuo, K. [Dept. of Radiology, Kyushu Univ. Fukuoka (Japan); Yamamoto, T. [Dept. of Otolaryngology, Kyushu Univ. Fukuoka (Japan); Tobimatsu, S. [Dept. of Clinical Neurophysiology, Neurological Inst., Kyushu Univ., Fukuoka (Japan)

    1995-10-01

    Combined use of magnetoencephalography (MEG), functional magnetic resonance imaging (f-MRI), and motor evoked potentials (MEPs) was carried out on one patient in an attempt to localise precisely a structural lesion to the central sulcus. A small cyst in the right frontoparietal region was thought to be the cause of generalised seizures in an otherwise asymptomatic woman. First the primary sensory cortex was identified with magnetic source imaging (MSI) of somatosensory evoked magnetic fields using MEG and MRI. Second, the motor area of the hand was identified using f-MRI during handsqueezing. Then transcranial magnetic stimulation localised the hand motor area on the scalp, which was mapped onto the MRI. There was a good agreement between MSI, f-MRI and MEP as to the location of the sensorimotor cortex and its relationship to the lesion. Multimodality mapping techniques may thus prove useful in the precise localisation of cortical lesions, and in the preoperative determination of the best treatment for peri-rolandic lesions. (orig.)

  1. Impaired sense of agency in functional movement disorders: An fMRI study.

    Directory of Open Access Journals (Sweden)

    Fatta B Nahab

    Full Text Available The sense of agency (SA is an established framework that refers to our ability to exert and perceive control over our own actions. Having an intact SA provides the basis for the human perception of voluntariness, while impairments in SA are hypothesized to lead to the perception of movements being involuntary that may be seen many neurological or psychiatric disorders. Individuals with functional movement disorders (FMD experience a lack of control over their movements, yet these movements appear voluntary by physiology. We used fMRI to explore whether alterations in SA in an FMD population could explain why these patients feel their movements are involuntary. We compared the FMD group to a control group that was previously collected using an ecologically valid, virtual-reality movement paradigm that could modulate SA. We found selective dysfunction of the SA neural network, whereby the dorsolateral prefrontal cortex and pre-supplementary motor area on the right did not respond differentially to the loss of movement control. These findings provide some of the strongest evidence to date for a physiological basis underlying these disabling disorders.

  2. Abnormal regional homogeneity in Parkinson's disease: a resting state fMRI study

    International Nuclear Information System (INIS)

    Li, Y.; Liang, P.; Jia, X.; Li, K.

    2016-01-01

    Aim: To examine the functional brain alterations in Parkinson's disease (PD) by measuring blood oxygenation level dependent (BOLD) functional MRI (fMRI) signals at rest while controlling for the structural atrophy. Materials and methods: Twenty-three PD patients and 20 age, gender, and education level matched normal controls (NC) were included in this study. Resting state fMRI and structural MRI data were acquired. The resting state brain activity was measured by the regional homogeneity (ReHo) method and the grey matter (GM) volume was attained by the voxel-based morphology (VBM) analysis. Two-sample t-test was then performed to detect the group differences with structural atrophy as a covariate. Results: VBM analysis showed GM volume reductions in the left superior frontal gyrus, left paracentral lobule, and left middle frontal gyrus in PD patients as compared to NC. There were widespread ReHo differences between NC and PD patients. Compared to NC, PD patients showed significant alterations in the motor network, including decreased ReHo in the right primary sensory cortex (S1), while increased ReHo in the left premotor area (PMA) and left dorsolateral prefrontal cortex (DLPFC). In addition, a cluster in the left superior occipital gyrus (SOG) also showed increased ReHo in PD patients. Conclusion: The current findings indicate that significant changes of ReHo in the motor and non-motor cortices have been detected in PD patients, independent of age, gender, education level, and structural atrophy. The present study thus suggests ReHo abnormalities as a potential biomarker for the diagnosis of PD and further provides insights into the biological mechanism of the disease. - Highlights: • Functional changes were found in PD patients independent of structural atrophy. • Both increased and decreased ReHo were observed in motor network regions in PD. • Increased ReHo was detected in visual association cortex for PD patients.

  3. Low-frequency hippocampal-cortical activity drives brain-wide resting-state functional MRI connectivity.

    Science.gov (United States)

    Chan, Russell W; Leong, Alex T L; Ho, Leon C; Gao, Patrick P; Wong, Eddie C; Dong, Celia M; Wang, Xunda; He, Jufang; Chan, Ying-Shing; Lim, Lee Wei; Wu, Ed X

    2017-08-15

    The hippocampus, including the dorsal dentate gyrus (dDG), and cortex engage in bidirectional communication. We propose that low-frequency activity in hippocampal-cortical pathways contributes to brain-wide resting-state connectivity to integrate sensory information. Using optogenetic stimulation and brain-wide fMRI and resting-state fMRI (rsfMRI), we determined the large-scale effects of spatiotemporal-specific downstream propagation of hippocampal activity. Low-frequency (1 Hz), but not high-frequency (40 Hz), stimulation of dDG excitatory neurons evoked robust cortical and subcortical brain-wide fMRI responses. More importantly, it enhanced interhemispheric rsfMRI connectivity in various cortices and hippocampus. Subsequent local field potential recordings revealed an increase in slow oscillations in dorsal hippocampus and visual cortex, interhemispheric visual cortical connectivity, and hippocampal-cortical connectivity. Meanwhile, pharmacological inactivation of dDG neurons decreased interhemispheric rsfMRI connectivity. Functionally, visually evoked fMRI responses in visual regions also increased during and after low-frequency dDG stimulation. Together, our results indicate that low-frequency activity robustly propagates in the dorsal hippocampal-cortical pathway, drives interhemispheric cortical rsfMRI connectivity, and mediates visual processing.

  4. Different brain activation under left and right ventricular stimulation: an fMRI study in anesthetized rats.

    Science.gov (United States)

    Suzuki, Hideaki; Sumiyoshi, Akira; Kawashima, Ryuta; Shimokawa, Hiroaki

    2013-01-01

    Myocardial ischemia in the anterior wall of the left ventricule (LV) and in the inferior wall and/or right ventricle (RV) shows different manifestations that can be explained by the different innervations of cardiac afferent nerves. However, it remains unclear whether information from different areas of the heart, such as the LV and RV, are differently processed in the brain. In this study, we investigated the brain regions that process information from the LV or RV using cardiac electrical stimulation and functional magnetic resonance imaging (fMRI) in anesthetized rats because the combination of these two approaches cannot be used in humans. An electrical stimulation catheter was inserted into the LV or RV (n = 12 each). Brain fMRI scans were recorded during LV or RV stimulation (9 Hz and 0.3 ms width) over 10 blocks consisting of alternating periods of 2 mA for 30 sec followed by 0.2 mA for 60 sec. The validity of fMRI signals was confirmed by first and second-level analyses and temporal profiles. Increases in fMRI signals were observed in the anterior cingulate cortex and the right somatosensory cortex under LV stimulation. In contrast, RV stimulation activated the right somatosensory cortex, which was identified more anteriorly compared with LV stimulation but did not activate the anterior cingulate cortex. This study provides the first evidence for differences in brain activation under LV and RV stimulation. These different brain processes may be associated with different clinical manifestations between anterior wall and inferoposterior wall and/or RV myocardial ischemia.

  5. Spatio-temporal models of mental processes from fMRI.

    Science.gov (United States)

    Janoos, Firdaus; Machiraju, Raghu; Singh, Shantanu; Morocz, Istvan Ákos

    2011-07-15

    Understanding the highly complex, spatially distributed and temporally organized phenomena entailed by mental processes using functional MRI is an important research problem in cognitive and clinical neuroscience. Conventional analysis methods focus on the spatial dimension of the data discarding the information about brain function contained in the temporal dimension. This paper presents a fully spatio-temporal multivariate analysis method using a state-space model (SSM) for brain function that yields not only spatial maps of activity but also its temporal structure along with spatially varying estimates of the hemodynamic response. Efficient algorithms for estimating the parameters along with quantitative validations are given. A novel low-dimensional feature-space for representing the data, based on a formal definition of functional similarity, is derived. Quantitative validation of the model and the estimation algorithms is provided with a simulation study. Using a real fMRI study for mental arithmetic, the ability of this neurophysiologically inspired model to represent the spatio-temporal information corresponding to mental processes is demonstrated. Moreover, by comparing the models across multiple subjects, natural patterns in mental processes organized according to different mental abilities are revealed. Copyright © 2011 Elsevier Inc. All rights reserved.

  6. Hand grips strength effect on motor function in human brain using fMRI: a pilot study

    International Nuclear Information System (INIS)

    Ismail, S S; Mohamad, M; Syazarina, S O; Nafisah, W Y

    2014-01-01

    Several methods of motor tasks for fMRI scanning have been evolving from simple to more complex tasks. Motor tasks on upper extremity were applied in order to excite the increscent of motor activation on contralesional and ipsilateral hemispheres in brain. The main objective of this study is to study the different conditions for motor tasks on upper extremity that affected the brain activation. Ten healthy right handed with normal vision (3 male and 7 female, age range=20-30 years, mean=24.6 years, SD=2.21) participated in this study. Prior to the scanning, participants were trained on hand grip tasks using rubber ball and pressure gauge tool outside the scanner. During fMRI session, a block design with 30-s task blocks and alternating 30-s rest periods was employed while participants viewed a computer screen via a back projection-mirror system and instructed to follow the instruction by gripping their hand with normal and strong grips using a rubber ball. Statistical Parametric mapping (SPM8) software was used to determine the brain activation. Both tasks activated the primary motor (M1), supplementary motor area (SMA), dorsal and ventral of premotor cortex area (PMA) in left hemisphere while in right hemisphere the area of primary motor (M1) somatosensory was activated. However, the comparison between both tasks revealed that the strong hand grip showed the higher activation at M1, PMA and SMA on left hemisphere and also the area of SMA on right hemisphere. Both conditions of motor tasks could provide insights the functional organization on human brain

  7. Hand grips strength effect on motor function in human brain using fMRI: a pilot study

    Science.gov (United States)

    Ismail, S. S.; Mohamad, M.; Syazarina, S. O.; Nafisah, W. Y.

    2014-11-01

    Several methods of motor tasks for fMRI scanning have been evolving from simple to more complex tasks. Motor tasks on upper extremity were applied in order to excite the increscent of motor activation on contralesional and ipsilateral hemispheres in brain. The main objective of this study is to study the different conditions for motor tasks on upper extremity that affected the brain activation. Ten healthy right handed with normal vision (3 male and 7 female, age range=20-30 years, mean=24.6 years, SD=2.21) participated in this study. Prior to the scanning, participants were trained on hand grip tasks using rubber ball and pressure gauge tool outside the scanner. During fMRI session, a block design with 30-s task blocks and alternating 30-s rest periods was employed while participants viewed a computer screen via a back projection-mirror system and instructed to follow the instruction by gripping their hand with normal and strong grips using a rubber ball. Statistical Parametric mapping (SPM8) software was used to determine the brain activation. Both tasks activated the primary motor (M1), supplementary motor area (SMA), dorsal and ventral of premotor cortex area (PMA) in left hemisphere while in right hemisphere the area of primary motor (M1) somatosensory was activated. However, the comparison between both tasks revealed that the strong hand grip showed the higher activation at M1, PMA and SMA on left hemisphere and also the area of SMA on right hemisphere. Both conditions of motor tasks could provide insights the functional organization on human brain.

  8. Glucose Administration Enhances fMRI Brain Activation and Connectivity Related to Episodic Memory Encoding for Neutral and Emotional Stimuli

    Science.gov (United States)

    Parent, Marise B.; Krebs-Kraft, Desiree L.; Ryan, John P.; Wilson, Jennifer S.; Harenski, Carla; Hamann, Stephan

    2011-01-01

    Glucose enhances memory in a variety of species. In humans, glucose administration enhances episodic memory encoding, although little is known regarding the neural mechanisms underlying these effects. Here we examined whether elevating blood glucose would enhance functional MRI (fMRI) activation and connectivity in brain regions associated with…

  9. Effects of haloperidol and aripiprazole on the human mesolimbic motivational system: A pharmacological fMRI study.

    Science.gov (United States)

    Bolstad, Ingeborg; Andreassen, Ole A; Groote, Inge; Server, Andres; Sjaastad, Ivar; Kapur, Shitij; Jensen, Jimmy

    2015-12-01

    The atypical antipsychotic drug aripiprazole is a partial dopamine (DA) D2 receptor agonist, which differentiates it from most other antipsychotics. This study compares the brain activation characteristic produced by aripiprazole with that of haloperidol, a typical D2 receptor antagonist. Healthy participants received an acute oral dose of haloperidol, aripiprazole or placebo, and then performed an active aversive conditioning task with aversive and neutral events presented as sounds, while blood-oxygen-level-dependent (BOLD) functional magnetic resonance imaging (fMRI) was carried out. The fMRI task, targeting the mesolimbic motivational system that is thought to be disturbed in psychosis, was based on the conditioned avoidance response (CAR) animal model - a widely used test of therapeutic potential of antipsychotic drugs. In line with the CAR animal model, the present results show that subjects given haloperidol were not able to avoid more aversive than neutral task trials, even though the response times were shorter during aversive events. In the aripiprazole and placebo groups more aversive than neutral events were avoided. Accordingly, the task-related BOLD-fMRI response in the mesolimbic motivational system was diminished in the haloperidol group compared to the placebo group, particularly in the ventral striatum, whereas the aripiprazole group showed task-related activations intermediate of the placebo and haloperidol groups. The current results show differential effects on brain function by aripiprazole and haloperidol, probably related to altered DA transmission. This supports the use of pharmacological fMRI to study antipsychotic properties in humans. Copyright © 2015 Elsevier B.V. and ECNP. All rights reserved.

  10. fMRI activation in the middle frontal gyrus as an indicator of hemispheric dominance for language in brain tumor patients: a comparison with Broca's area.

    Science.gov (United States)

    Dong, Jian W; Brennan, Nicole M Petrovich; Izzo, Giana; Peck, Kyung K; Holodny, Andrei I

    2016-05-01

    Functional MRI (fMRI) can assess language lateralization in brain tumor patients; however, this can be limited if the primary language area-Broca's area (BA)-is affected by the tumor. We hypothesized that the middle frontal gyrus (MFG) can be used as a clinical indicator of hemispheric dominance for language during presurgical workup. Fifty-two right-handed subjects with solitary left-hemispheric primary brain tumors were retrospectively studied. Subjects performed a verbal fluency task during fMRI. The MFG was compared to BA for fMRI voxel activation, language laterality index (LI), and the effect of tumor grade on the LI. Language fMRI (verbal fluency) activated more voxels in MFG than in BA (MFG = 315, BA = 216, p hemispheric MFG and BA were positively correlated (r = 0.69, p hemispheric dominance for language using a measure of verbal fluency and may be an adjunct measure in the clinical determination of language laterality for presurgical planning.

  11. Asymmetrical hippocampal connectivity in mesial temporal lobe epilepsy: evidence from resting state fMRI

    Directory of Open Access Journals (Sweden)

    Castellano Gabriela

    2010-06-01

    Full Text Available Abstract Background Mesial temporal lobe epilepsy (MTLE, the most common type of focal epilepsy in adults, is often caused by hippocampal sclerosis (HS. Patients with HS usually present memory dysfunction, which is material-specific according to the hemisphere involved and has been correlated to the degree of HS as measured by postoperative histopathology as well as by the degree of hippocampal atrophy on magnetic resonance imaging (MRI. Verbal memory is mostly affected by left-sided HS, whereas visuo-spatial memory is more affected by right HS. Some of these impairments may be related to abnormalities of the network in which individual hippocampus takes part. Functional connectivity can play an important role to understand how the hippocampi interact with other brain areas. It can be estimated via functional Magnetic Resonance Imaging (fMRI resting state experiments by evaluating patterns of functional networks. In this study, we investigated the functional connectivity patterns of 9 control subjects, 9 patients with right MTLE and 9 patients with left MTLE. Results We detected differences in functional connectivity within and between hippocampi in patients with unilateral MTLE associated with ipsilateral HS by resting state fMRI. Functional connectivity resulted to be more impaired ipsilateral to the seizure focus in both patient groups when compared to control subjects. This effect was even more pronounced for the left MTLE group. Conclusions The findings presented here suggest that left HS causes more reduction of functional connectivity than right HS in subjects with left hemisphere dominance for language.

  12. Enhanced disease characterization through multi network functional normalization in fMRI.

    Science.gov (United States)

    Çetin, Mustafa S; Khullar, Siddharth; Damaraju, Eswar; Michael, Andrew M; Baum, Stefi A; Calhoun, Vince D

    2015-01-01

    Conventionally, structural topology is used for spatial normalization during the pre-processing of fMRI. The co-existence of multiple intrinsic networks which can be detected in the resting brain are well-studied. Also, these networks exhibit temporal and spatial modulation during cognitive task vs. rest which shows the existence of common spatial excitation patterns between these identified networks. Previous work (Khullar et al., 2011) has shown that structural and functional data may not have direct one-to-one correspondence and functional activation patterns in a well-defined structural region can vary across subjects even for a well-defined functional task. The results of this study and the existence of the neural activity patterns in multiple networks motivates us to investigate multiple resting-state networks as a single fusion template for functional normalization for multi groups of subjects. We extend the previous approach (Khullar et al., 2011) by co-registering multi group of subjects (healthy control and schizophrenia patients) and by utilizing multiple resting-state networks (instead of just one) as a single fusion template for functional normalization. In this paper we describe the initial steps toward using multiple resting-state networks as a single fusion template for functional normalization. A simple wavelet-based image fusion approach is presented in order to evaluate the feasibility of combining multiple functional networks. Our results showed improvements in both the significance of group statistics (healthy control and schizophrenia patients) and the spatial extent of activation when a multiple resting-state network applied as a single fusion template for functional normalization after the conventional structural normalization. Also, our results provided evidence that the improvement in significance of group statistics lead to better accuracy results for classification of healthy controls and schizophrenia patients.

  13. Improving the spatial accuracy in functional magnetic resonance imaging (fMRI) based on the blood oxygenation level dependent (BOLD) effect: benefits from parallel imaging and a 32-channel head array coil at 1.5 Tesla.

    Science.gov (United States)

    Fellner, C; Doenitz, C; Finkenzeller, T; Jung, E M; Rennert, J; Schlaier, J

    2009-01-01

    Geometric distortions and low spatial resolution are current limitations in functional magnetic resonance imaging (fMRI). The aim of this study was to evaluate if application of parallel imaging or significant reduction of voxel size in combination with a new 32-channel head array coil can reduce those drawbacks at 1.5 T for a simple hand motor task. Therefore, maximum t-values (tmax) in different regions of activation, time-dependent signal-to-noise ratios (SNR(t)) as well as distortions within the precentral gyrus were evaluated. Comparing fMRI with and without parallel imaging in 17 healthy subjects revealed significantly reduced geometric distortions in anterior-posterior direction. Using parallel imaging, tmax only showed a mild reduction (7-11%) although SNR(t) was significantly diminished (25%). In 7 healthy subjects high-resolution (2 x 2 x 2 mm3) fMRI was compared with standard fMRI (3 x 3 x 3 mm3) in a 32-channel coil and with high-resolution fMRI in a 12-channel coil. The new coil yielded a clear improvement for tmax (21-32%) and SNR(t) (51%) in comparison with the 12-channel coil. Geometric distortions were smaller due to the smaller voxel size. Therefore, the reduction in tmax (8-16%) and SNR(t) (52%) in the high-resolution experiment seems to be tolerable with this coil. In conclusion, parallel imaging is an alternative to reduce geometric distortions in fMRI at 1.5 T. Using a 32-channel coil, reduction of the voxel size might be the preferable way to improve spatial accuracy.

  14. Amygdala fMRI Signal as a Predictor of Reaction Time

    Directory of Open Access Journals (Sweden)

    Philipp Riedel

    2016-10-01

    Full Text Available Reaction times (RT are a valuable measure for assessing cognitive processes. However, RTs are susceptible to confounds and therefore variable. Exposure to threat, for example, speeds up or slows down responses. Distinct task types to some extent account for differential effects of threat on RTs. But also do inter-individual differences like trait anxiety. In this functional magnetic resonance imaging study, we investigated whether activation within the amygdala, a brain region closely linked to the processing of threat, may also function as a predictor of RTs, similar to trait anxiety scores. After threat conditioning by means of aversive electric shocks, 45 participants performed a choice RT task during alternating 30s blocks in the presence of the threat conditioned stimulus CS+ or of the safe control stimulus CS-. Trait anxiety was assessed with the State-Trait-Anxiety-Inventory and participants were median split into a high- and a low-anxiety subgroup. We tested three hypotheses: 1 RTs will be faster during the exposure to threat compared to the safe condition in individuals with high trait anxiety. 2 The amygdala fMRI signal will be higher in the threat condition compared to the safe condition. 3 Amygdala fMRI signal prior to a RT trial will be correlated with the corresponding RT. We found that, the high-anxious subgroup showed faster responses in the threat condition compared to the safe condition, while the low-anxious subgroup showed no significant difference in RTs in the threat condition compared to the safe condition. Though the fMRI analysis did not reveal an effect of condition on amygdala activity, we found a trial-by-trial correlation between blood-oxygen-level-dependent signal within the right amygdala prior to the CRT task and the subsequent RT. Taken together, the results of this study showed that: Exposure to threat modulates task performance. This modulation is influenced by personality trait. Additionally and most

  15. Test-retest reliability of evoked BOLD signals from a cognitive-emotive fMRI test battery.

    Science.gov (United States)

    Plichta, Michael M; Schwarz, Adam J; Grimm, Oliver; Morgen, Katrin; Mier, Daniela; Haddad, Leila; Gerdes, Antje B M; Sauer, Carina; Tost, Heike; Esslinger, Christine; Colman, Peter; Wilson, Frederick; Kirsch, Peter; Meyer-Lindenberg, Andreas

    2012-04-15

    Even more than in cognitive research applications, moving fMRI to the clinic and the drug development process requires the generation of stable and reliable signal changes. The performance characteristics of the fMRI paradigm constrain experimental power and may require different study designs (e.g., crossover vs. parallel groups), yet fMRI reliability characteristics can be strongly dependent on the nature of the fMRI task. The present study investigated both within-subject and group-level reliability of a combined three-task fMRI battery targeting three systems of wide applicability in clinical and cognitive neuroscience: an emotional (face matching), a motivational (monetary reward anticipation) and a cognitive (n-back working memory) task. A group of 25 young, healthy volunteers were scanned twice on a 3T MRI scanner with a mean test-retest interval of 14.6 days. FMRI reliability was quantified using the intraclass correlation coefficient (ICC) applied at three different levels ranging from a global to a localized and fine spatial scale: (1) reliability of group-level activation maps over the whole brain and within targeted regions of interest (ROIs); (2) within-subject reliability of ROI-mean amplitudes and (3) within-subject reliability of individual voxels in the target ROIs. Results showed robust evoked activation of all three tasks in their respective target regions (emotional task=amygdala; motivational task=ventral striatum; cognitive task=right dorsolateral prefrontal cortex and parietal cortices) with high effect sizes (ES) of ROI-mean summary values (ES=1.11-1.44 for the faces task, 0.96-1.43 for the reward task, 0.83-2.58 for the n-back task). Reliability of group level activation was excellent for all three tasks with ICCs of 0.89-0.98 at the whole brain level and 0.66-0.97 within target ROIs. Within-subject reliability of ROI-mean amplitudes across sessions was fair to good for the reward task (ICCs=0.56-0.62) and, dependent on the particular ROI

  16. Sources of variation influencing concordance between functional MRI and direct cortical stimulation in brain tumor surgery

    Directory of Open Access Journals (Sweden)

    Melanie A Morrison

    2016-10-01

    Full Text Available Object: Preoperative functional magnetic resonance imaging (fMRI remains a promising method to aid in the surgical management of patients diagnosed with brain tumors. For patients that are candidates for awake craniotomies, surgical decisions can potentially be improved by fMRI but this depends on the level of concordance between preoperative brain maps and the maps provided by the gold standard intraoperative method, direct cortical stimulation (DCS. There have been numerous studies of the concordance between fMRI and DCS using sensitivity and specificity measures, however the results are variable across studies and the key factors influencing variability are not well understood. Thus, the present work addresses the influence of technical factors on fMRI and DCS concordance. Methods: Motor and language mapping data were collected for a group of glioma patients (n = 14 who underwent both preoperative fMRI and intraoperative DCS in an awake craniotomy procedure for tumor removal. Normative fMRI data were also acquired in a healthy control group (n = 12. The fMRI and DCS mapping data were co-registered; true positive (TP, true negative (TN, false positive (FP and false negative (FN occurrences were tabulated over the exposed brain surface. Sensitivity and specificity were measured for the total group, and the motor and language sub-groups. The influence of grid placement, fMRI statistical thresholding, and task standardization were assessed. Correlations between proportions of agreement and error were carefully scrutinized to evaluate concordance more in-depth. Results: Concordance was significantly better for motor versus language mapping. There was an inverse relationship between TP and TN with increasing statistical threshold, and FP dominated the total error. Sensitivity and specificity were reduced when tasks were not standardized across fMRI and DCS. Conclusions: Although the agreement between fMRI and DCS is good, variability is introduced

  17. Discriminating between brain rest and attention states using fMRI connectivity graphs and subtree SVM

    Science.gov (United States)

    Mokhtari, Fatemeh; Bakhtiari, Shahab K.; Hossein-Zadeh, Gholam Ali; Soltanian-Zadeh, Hamid

    2012-02-01

    Decoding techniques have opened new windows to explore the brain function and information encoding in brain activity. In the current study, we design a recursive support vector machine which is enriched by a subtree graph kernel. We apply the classifier to discriminate between attentional cueing task and resting state from a block design fMRI dataset. The classifier is trained using weighted fMRI graphs constructed from activated regions during the two mentioned states. The proposed method leads to classification accuracy of 1. It is also able to elicit discriminative regions and connectivities between the two states using a backward edge elimination algorithm. This algorithm shows the importance of regions including cerebellum, insula, left middle superior frontal gyrus, post cingulate cortex, and connectivities between them to enhance the correct classification rate.

  18. Exploring fMRI Data for Periodic Signal Components

    DEFF Research Database (Denmark)

    Hansen, Lars Kai; Nielsen, Finn Årup; Larsen, Jan

    2002-01-01

    We use a Bayesian framework to detect periodic components in fMRI data. The resulting detector is sensitive to periodic components with a flexible number of harmonics and with arbitrary amplitude and phases of the harmonics. It is possible to detect the correct number of harmonics in periodic sig...

  19. HIV Infection Is Associated with Impaired Striatal Function during Inhibition with Normal Cortical Functioning on Functional MRI

    NARCIS (Netherlands)

    du Plessis, Stéfan; Vink, Matthijs; Joska, John A; Koutsilieri, Eleni; Bagadia, Asif; Stein, Dan J; Emsley, Robin

    2015-01-01

    The aim of the present study was to investigate the effect of HIV infection on cortical and subcortical regions of the frontal-striatal system involved in the inhibition of voluntary movement. Functional MRI (fMRI) studies suggest that human immunodeficiency virus (HIV) infection is associated with

  20. Multiscale mining of fMRI data with hierarchical structured sparsity

    International Nuclear Information System (INIS)

    Jenatton, R.; Obozinski, G.; Bach, F.; Gramfort, Alexandre; Michel, Vincent; Thirion, Bertrand; Eger, Evelyne

    2012-01-01

    Reverse inference, or 'brain reading', is a recent paradigm for analyzing functional magnetic resonance imaging (fMRI) data, based on pattern recognition and statistical learning. By predicting some cognitive variables related to brain activation maps, this approach aims at decoding brain activity. Reverse inference takes into account the multivariate information between voxels and is currently the only way to assess how precisely some cognitive information is encoded by the activity of neural populations within the whole brain. However, it relies on a prediction function that is plagued by the curse of dimensionality, since there are far more features than samples, i.e., more voxels than fMRI volumes. To address this problem, different methods have been proposed, such as, among others, univariate feature selection, feature agglomeration and regularization techniques. In this paper, we consider a sparse hierarchical structured regularization. Specifically, the penalization we use is constructed from a tree that is obtained by spatially-constrained agglomerative clustering. This approach encodes the spatial structure of the data at different scales into the regularization, which makes the overall prediction procedure more robust to inter-subject variability. The regularization used induces the selection of spatially coherent predictive brain regions simultaneously at different scales. We test our algorithm on real data acquired to study the mental representation of objects, and we show that the proposed algorithm not only delineates meaningful brain regions but yields as well better prediction accuracy than reference methods. (authors)

  1. Neurobiology of Insight Deficits in Schizophrenia: An fMRI Study

    Science.gov (United States)

    Shad, Mujeeb U.; Keshavan, Matcheri S.

    2015-01-01

    Prior research has shown insight deficits in schizophrenia to be associated with specific neuroimaging changes (primarily structural) especially in the prefrontal sub-regions. However, little is known about the functional correlates of impaired insight. Seventeen patients with schizophrenia (mean age 40.0±10.3; M/F= 14/3) underwent fMRI on a Philips 3.0 T Achieva system while performing on a self-awareness task containing self- vs. other-directed sentence stimuli. SPM5 was used to process the imaging data. Preprocessing consisted of realignment, coregistration, and normalization, and smoothing. A regression analysis was used to examine the relationship between brain activation in response to self-directed versus other-directed sentence stimuli and average scores on behavioral measures of awareness of symptoms and attribution of symptoms to the illness from Scale to Assess Unawareness of Mental Disorders. Family Wise Error correction was employed in the fMRI analysis. Average scores on awareness of symptoms (1 = aware; 5 = unaware) were associated with activation of multiple brain regions, including prefrontal, parietal and limbic areas as well as basal ganglia. However, average scores on correct attribution of symptoms (1 = attribute; 5 = misattribute) were associated with relatively more localized activation of prefrontal cortex and basal ganglia. These findings suggest that unawareness and misattribution of symptoms may have different neurobiological basis in schizophrenia. While symptom unawareness may be a function of a more complex brain network, symptom misattribution may be mediated by specific brain regions. PMID:25957484

  2. Assessment of Cortical Visual Impairment in Infants with Periventricular Leukomalacia: a Pilot Event-Related fMRI Study

    Energy Technology Data Exchange (ETDEWEB)

    Yu, Bing; Guo, Qiyong [Shengjing Hospital of China Medical University, Shenyang (China); Fan, Guoguang [The First Hospital of China Medical University, Shenyang (China); Liu, Na [Greater China Region of Philips, Shanghai (China)

    2011-08-15

    We wanted to investigate the usefulness of event-related (ER) functional MRI (fMRI) for the assessment of cortical visual impairment in infants with periventricular leukomalacia (PVL). FMRI data were collected from 24 infants who suffered from PVL and from 12 age-matched normal controls. Slow ER fMRI was performed using a 3.0T MR scanner while visual stimuli were being presented. Data analysis was performed using Statistical Parametric Mapping software (SPM2), the SPM toolbox MarsBar was used to analyze the region of interest data, and the time to peak (TTP) of hemodynamic response functions (HRFs) was estimated for the surviving voxels. The number of activated voxels and the TTP values of HRFs were compared. Pearson correlation analysis was performed to compare visual impairment evaluated by using Teller Acuity Cards (TAC) with the number of activated voxels in the occipital lobes in all patients. In all 12 control infants, the blood oxygenation level-dependent (BOLD) signal was negative and the maximum response was located in the anterior and superior part of the calcarine fissure, and this might correspond to the anterior region of the primary visual cortex (PVC). In contrast, for the 24 cases of PVL, there were no activated pixels in the PVC in four subjects, small and weak activations in six subjects, deviated activations in seven subjects and both small and deviated activations in three subjects. The number of active voxels in the occipital lobe was significantly correlated with the TAC-evaluated visual impairment (p < 0.001). The mean TTP of the HRFs was significantly delayed in the cases of PVL as compared with that of the normal controls. Determining the characteristics of both the BOLD response and the ER fMRI activation may play an important role in the cortical visual assessment of infants with PVL.

  3. Tactile and non-tactile sensory paradigms for fMRI and neurophysiologic studies in rodents.

    Science.gov (United States)

    Sanganahalli, Basavaraju G; Bailey, Christopher J; Herman, Peter; Hyder, Fahmeed

    2009-01-01

    Functional magnetic resonance imaging (fMRI) has become a popular functional imaging tool for human studies. Future diagnostic use of fMRI depends, however, on a suitable neurophysiologic interpretation of the blood oxygenation level dependent (BOLD) signal change. This particular goal is best achieved in animal models primarily due to the invasive nature of other methods used and/or pharmacological agents applied to probe different nuances of neuronal (and glial) activity coupled to the BOLD signal change. In the last decade, we have directed our efforts towards the development of stimulation protocols for a variety of modalities in rodents with fMRI. Cortical perception of the natural world relies on the formation of multi-dimensional representation of stimuli impinging on the different sensory systems, leading to the hypothesis that a sensory stimulus may have very different neurophysiologic outcome(s) when paired with a near simultaneous event in another modality. Before approaching this level of complexity, reliable measures must be obtained of the relatively small changes in the BOLD signal and other neurophysiologic markers (electrical activity, blood flow) induced by different peripheral stimuli. Here we describe different tactile (i.e., forepaw, whisker) and non-tactile (i.e., olfactory, visual) sensory paradigms applied to the anesthetized rat. The main focus is on development and validation of methods for reproducible stimulation of each sensory modality applied independently or in conjunction with one another, both inside and outside the magnet. We discuss similarities and/or differences across the sensory systems as well as advantages they may have for studying essential neuroscientific questions. We envisage that the different sensory paradigms described here may be applied directly to studies of multi-sensory interactions in anesthetized rats, en route to a rudimentary understanding of the awake functioning brain where various sensory cues presumably

  4. Specificity of Esthetic Experience for Artworks: An fMRI Study

    Science.gov (United States)

    Di Dio, Cinzia; Canessa, Nicola; Cappa, Stefano F.; Rizzolatti, Giacomo

    2011-01-01

    In a previous functional magnetic resonance imaging (fMRI) study, where we investigated the neural correlates of esthetic experience, we found that observing canonical sculptures, relative to sculptures whose proportions had been modified, produced the activation of a network that included the lateral occipital gyrus, precuneus, prefrontal areas, and, most interestingly, the right anterior insula. We interpreted this latter activation as the neural signature underpinning hedonic response during esthetic experience. With the aim of exploring whether this specific hedonic response is also present during the observation of non-art biological stimuli, in the present fMRI study we compared the activations associated with viewing masterpieces of classical sculpture with those produced by the observation of pictures of young athletes. The two stimulus-categories were matched on various factors, including body postures, proportion, and expressed dynamism. The stimuli were presented in two conditions: observation and esthetic judgment. The two stimulus-categories produced a rather similar global activation pattern. Direct comparisons between sculpture and real-body images revealed, however, relevant differences, among which the activation of right antero-dorsal insula during sculptures viewing only. Along with our previous data, this finding suggests that the hedonic state associated with activation of right dorsal anterior insula underpins esthetic experience for artworks. PMID:22121344

  5. Adaptive smoothing based on Gaussian processes regression increases the sensitivity and specificity of fMRI data.

    Science.gov (United States)

    Strappini, Francesca; Gilboa, Elad; Pitzalis, Sabrina; Kay, Kendrick; McAvoy, Mark; Nehorai, Arye; Snyder, Abraham Z

    2017-03-01

    Temporal and spatial filtering of fMRI data is often used to improve statistical power. However, conventional methods, such as smoothing with fixed-width Gaussian filters, remove fine-scale structure in the data, necessitating a tradeoff between sensitivity and specificity. Specifically, smoothing may increase sensitivity (reduce noise and increase statistical power) but at the cost loss of specificity in that fine-scale structure in neural activity patterns is lost. Here, we propose an alternative smoothing method based on Gaussian processes (GP) regression for single subjects fMRI experiments. This method adapts the level of smoothing on a voxel by voxel basis according to the characteristics of the local neural activity patterns. GP-based fMRI analysis has been heretofore impractical owing to computational demands. Here, we demonstrate a new implementation of GP that makes it possible to handle the massive data dimensionality of the typical fMRI experiment. We demonstrate how GP can be used as a drop-in replacement to conventional preprocessing steps for temporal and spatial smoothing in a standard fMRI pipeline. We present simulated and experimental results that show the increased sensitivity and specificity compared to conventional smoothing strategies. Hum Brain Mapp 38:1438-1459, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  6. 11.74T fMRI of cortical and subcortical visual networks in the rat

    DEFF Research Database (Denmark)

    Bailey, Christopher; Sanganahalli, Basavaraju G.; Siefert, Alyssa

    Though a predominantly nocturnal animal, the rat has a functional visual system, albeit of low acuity, and has at least a basic form of color vision extending into the UV range. Our aim here was to develop methods to probe this system with both high field fMRI and electrophysiological techniques....

  7. Investigation of cerebral cortical functional areas of the acupoints in zusanli and xiajuxu by fMRI

    International Nuclear Information System (INIS)

    Gong Honghan; Xiao Xiangzuo; Qiu Chunmei; Wang Liya; Ji Yuqiang; Wang Min; Wang Minjun; Wang Jinghua; Zeng Xianjun; Wang Yongzheng

    2003-01-01

    Objective: To study the functional areas of Zusanli (ST36) and Xiajuxu (ST39) in the cerebral cortex with fMRI and acupuncture stimulation. Material and Methods: 64 healthy Volunteers were divided into two groups. Acupuncture stimulation was induced to both of them by manipulating acupuncture needle at the acupuncture point at right ST36 and then ST39 respectively. FMRI was performed in the experimental group during state of the reaction to the acupuncture ('De-Qi') and in the control group during state of no reaction. Functional responses were investigated by students group t-test analysis. Results: Chi-square test showed that there was no significant difference (P>0.05) in ROI in state of 'De-Qi' and in state of no reaction. In state of 'De-Qi', acupuncture mainly resulted in activating bilateral cingulate cortex, insula, upper wall of lateral sulcus and bilateral postcentral gyrus. However, in state of no reaction, acupuncture mainly resulted in activating left postcentral gyrus. Significant difference of between ROI in state of 'De-Qi' and no reaction (P<0.01) at each acupoint was shown. Conclusion: Treatment of gastroenteric disease by acupuncturing ST36 and ST39 has its scientific basis. There are close relations between the central neural system (CNS) and the acupoints. It may be that the acupuncture stimulates the corresponding functional areas in cerebral cortex via the CNS at first, thereby treating disorders of organs

  8. Parahippocampal activation during successful recognition of words: a self-paced event-related fMRI study

    NARCIS (Netherlands)

    Daselaar, S. M.; Rombouts, S. A.; Veltman, D. J.; Raaijmakers, J. G.; Lazeron, R. H.; Jonker, C.

    2001-01-01

    In this study, we investigated retrieval from verbal episodic memory using a self-paced event-related fMRI paradigm, similar to the designs typically used in behavioral studies of memory function. We tested the hypothesis that the medial temporal lobe (MTL) is involved in the actual recovery of

  9. A method for independent component graph analysis of resting-state fMRI

    DEFF Research Database (Denmark)

    de Paula, Demetrius Ribeiro; Ziegler, Erik; Abeyasinghe, Pubuditha M.

    2017-01-01

    Introduction Independent component analysis (ICA) has been extensively used for reducing task-free BOLD fMRI recordings into spatial maps and their associated time-courses. The spatially identified independent components can be considered as intrinsic connectivity networks (ICNs) of non-contiguou......Introduction Independent component analysis (ICA) has been extensively used for reducing task-free BOLD fMRI recordings into spatial maps and their associated time-courses. The spatially identified independent components can be considered as intrinsic connectivity networks (ICNs) of non......-contiguous regions. To date, the spatial patterns of the networks have been analyzed with techniques developed for volumetric data. Objective Here, we detail a graph building technique that allows these ICNs to be analyzed with graph theory. Methods First, ICA was performed at the single-subject level in 15 healthy...... parcellated regions. Third, between-node functional connectivity was established by building edge weights for each networks. Group-level graph analysis was finally performed for each network and compared to the classical network. Results Network graph comparison between the classically constructed network...

  10. Replicability of time-varying connectivity patterns in large resting state fMRI samples.

    Science.gov (United States)

    Abrol, Anees; Damaraju, Eswar; Miller, Robyn L; Stephen, Julia M; Claus, Eric D; Mayer, Andrew R; Calhoun, Vince D

    2017-12-01

    The past few years have seen an emergence of approaches that leverage temporal changes in whole-brain patterns of functional connectivity (the chronnectome). In this chronnectome study, we investigate the replicability of the human brain's inter-regional coupling dynamics during rest by evaluating two different dynamic functional network connectivity (dFNC) analysis frameworks using 7 500 functional magnetic resonance imaging (fMRI) datasets. To quantify the extent to which the emergent functional connectivity (FC) patterns are reproducible, we characterize the temporal dynamics by deriving several summary measures across multiple large, independent age-matched samples. Reproducibility was demonstrated through the existence of basic connectivity patterns (FC states) amidst an ensemble of inter-regional connections. Furthermore, application of the methods to conservatively configured (statistically stationary, linear and Gaussian) surrogate datasets revealed that some of the studied state summary measures were indeed statistically significant and also suggested that this class of null model did not explain the fMRI data fully. This extensive testing of reproducibility of similarity statistics also suggests that the estimated FC states are robust against variation in data quality, analysis, grouping, and decomposition methods. We conclude that future investigations probing the functional and neurophysiological relevance of time-varying connectivity assume critical importance. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  11. Pomegranate Juice Augments Memory and fMRI Activity in Middle-Aged and Older Adults with Mild Memory Complaints

    Directory of Open Access Journals (Sweden)

    Susan Y. Bookheimer

    2013-01-01

    Full Text Available Despite increasing emphasis on the potential of dietary antioxidants in preventing memory loss and on diet as a precursor of neurological health, rigorous studies investigating the cognitive effects of foods and their components are rare. Recent animal studies have reported memory and other cognitive benefits of polyphenols, found abundantly in pomegranate juice. We performed a preliminary, placebo-controlled randomized trial of pomegranate juice in older subjects with age-associated memory complaints using memory testing and functional brain activation (fMRI as outcome measures. Thirty-two subjects (28 completers were randomly assigned to drink 8 ounces of either pomegranate juice or a flavor-matched placebo drink for 4 weeks. Subjects received memory testing, fMRI scans during cognitive tasks, and blood draws for peripheral biomarkers before and after the intervention. Investigators and subjects were all blind to group membership. After 4 weeks, only the pomegranate group showed a significant improvement in the Buschke selective reminding test of verbal memory and a significant increase in plasma trolox-equivalent antioxidant capacity (TEAC and urolithin A-glucuronide. Furthermore, compared to the placebo group, the pomegranate group had increased fMRI activity during verbal and visual memory tasks. While preliminary, these results suggest a role for pomegranate juice in augmenting memory function through task-related increases in functional brain activity.

  12. Measurement of human advanced brain function in calculation processing using functional magnetic resonance imaging (fMRI)

    International Nuclear Information System (INIS)

    Hashida, Masahiro; Yamauchi, Syuichi; Wu, Jing-Long

    2001-01-01

    Using functional magnetic resonance imaging (fMRI), we investigated the activated areas of the human brain related with calculation processing as an advanced function of the human brain. Furthermore, we investigated differences in activation between visual and auditory calculation processing. The eight subjects (all healthy men) were examined on a clinical MR unit (1.5 tesla) with a gradient echo-type EPI sequence. SPM99 software was used for data processing. Arithmetic problems were used for the visual stimulus (visual image) as well as for the auditory stimulus (audible voice). The stimuli were presented to the subjects as follows: no stimulation, presentation of random figures, and presentation of arithmetic problems. Activated areas of the human brain related with calculation processing were the inferior parietal lobule, middle frontal gyrus, and inferior frontal gyrus. Comparing the arithmetic problems with the presentation of random figures, we found that the activated areas of the human brain were not differently affected by visual and auditory systems. The areas activated in the visual and auditory experiments were observed at nearly the same place in the brain. It is possible to study advanced functions of the human brain such as calculation processing in a general clinical hospital when adequate tasks and methods of presentation are used. (author)

  13. Language Lateralization in Children Aged 10 to 11 Years: A Combined fMRI and Dichotic Listening Study

    Science.gov (United States)

    Norrelgen, Fritjof; Lilja, Anders; Ingvar, Martin; Gisselgård, Jens; Fransson, Peter

    2012-01-01

    Objective The aims of this study were to develop and assess a method to map language networks in children with two auditory fMRI protocols in combination with a dichotic listening task (DL). The method is intended for pediatric patients prior to epilepsy surgery. To evaluate the potential clinical usefulness of the method we first wanted to assess data from a group of healthy children. Methods In a first step language test materials were developed, intended for subsequent implementation in fMRI protocols. An evaluation of this material was done in 30 children with typical development, 10 from the 1st, 4th and the 7th grade, respectively. The language test material was then adapted and implemented in two fMRI protocols intended to target frontal and posterior language networks. In a second step language lateralization was assessed in 17 typical 10–11 year olds with fMRI and DL. To reach a conclusion about language lateralization, firstly, quantitative analyses of the index data from the two fMRI tasks and the index data from the DL task were done separately. In a second step a set of criteria were applied to these results to reach a conclusion about language lateralization. The steps of these analyses are described in detail. Results The behavioral assessment of the language test material showed that it was well suited for typical children. The results of the language lateralization assessments, based on fMRI data and DL data, showed that for 15 of the 17 subjects (88%) a conclusion could be reached about hemispheric language dominance. In 2 cases (12%) DL provided critical data. Conclusions The employment of DL combined with language mapping using fMRI for assessing hemispheric language dominance is novel and it was deemed valuable since it provided additional information compared to the results gained from each method individually. PMID:23284796

  14. Language lateralization in children aged 10 to 11 years: a combined fMRI and dichotic listening study.

    Directory of Open Access Journals (Sweden)

    Fritjof Norrelgen

    Full Text Available OBJECTIVE: The aims of this study were to develop and assess a method to map language networks in children with two auditory fMRI protocols in combination with a dichotic listening task (DL. The method is intended for pediatric patients prior to epilepsy surgery. To evaluate the potential clinical usefulness of the method we first wanted to assess data from a group of healthy children. METHODS: In a first step language test materials were developed, intended for subsequent implementation in fMRI protocols. An evaluation of this material was done in 30 children with typical development, 10 from the 1(st, 4(th and the 7(th grade, respectively. The language test material was then adapted and implemented in two fMRI protocols intended to target frontal and posterior language networks. In a second step language lateralization was assessed in 17 typical 10-11 year olds with fMRI and DL. To reach a conclusion about language lateralization, firstly, quantitative analyses of the index data from the two fMRI tasks and the index data from the DL task were done separately. In a second step a set of criteria were applied to these results to reach a conclusion about language lateralization. The steps of these analyses are described in detail. RESULTS: The behavioral assessment of the language test material showed that it was well suited for typical children. The results of the language lateralization assessments, based on fMRI data and DL data, showed that for 15 of the 17 subjects (88% a conclusion could be reached about hemispheric language dominance. In 2 cases (12% DL provided critical data. CONCLUSIONS: The employment of DL combined with language mapping using fMRI for assessing hemispheric language dominance is novel and it was deemed valuable since it provided additional information compared to the results gained from each method individually.

  15. A novel approach to calibrate the Hemodynamic Model using functional Magnetic Resonance Imaging (fMRI) measurements

    KAUST Repository

    Khoram, Nafiseh; Zayane, Chadia; Djellouli, Rabia; Laleg-Kirati, Taous-Meriem

    2016-01-01

    We have designed an iterative numerical technique, called the TNM-CKF algorithm, for calibrating the mathematical model that describes the single-event related brain response when fMRI measurements are given. The method appears to be highly accurate and effective in reconstructing the BOLD signal even when the measurements are tainted with high noise level (as high as 30%).

  16. Functional Laterality of Task-Evoked Activation in Sensorimotor Cortex of Preterm Infants: An Optimized 3 T fMRI Study Employing a Customized Neonatal Head Coil.

    Science.gov (United States)

    Scheef, Lukas; Nordmeyer-Massner, Jurek A; Smith-Collins, Adam Pr; Müller, Nicole; Stegmann-Woessner, Gaby; Jankowski, Jacob; Gieseke, Jürgen; Born, Mark; Seitz, Hermann; Bartmann, Peter; Schild, Hans H; Pruessmann, Klaas P; Heep, Axel; Boecker, Henning

    2017-01-01

    Functional magnetic resonance imaging (fMRI) in neonates has been introduced as a non-invasive method for studying sensorimotor processing in the developing brain. However, previous neonatal studies have delivered conflicting results regarding localization, lateralization, and directionality of blood oxygenation level dependent (BOLD) responses in sensorimotor cortex (SMC). Amongst the confounding factors in interpreting neonatal fMRI studies include the use of standard adult MR-coils providing insufficient signal to noise, and liberal statistical thresholds, compromising clinical interpretation at the single subject level. Here, we employed a custom-designed neonatal MR-coil adapted and optimized to the head size of a newborn in order to improve robustness, reliability and validity of neonatal sensorimotor fMRI. Thirteen preterm infants with a median gestational age of 26 weeks were scanned at term-corrected age using a prototype 8-channel neonatal head coil at 3T (Achieva, Philips, Best, NL). Sensorimotor stimulation was elicited by passive extension/flexion of the elbow at 1 Hz in a block design. Analysis of temporal signal to noise ratio (tSNR) was performed on the whole brain and the SMC, and was compared to data acquired with an 'adult' 8 channel head coil published previously. Task-evoked activation was determined by single-subject SPM8 analyses, thresholded at p lateralization of SMC activation, as found in children and adults, is already present in the newborn period.

  17. Reorganization of Language Areas in Patient with a Frontal Lobe Low Grade Glioma – fMRI Case Study

    International Nuclear Information System (INIS)

    Kośla, Katarzyna; Bryszewski, Bartosz; Jaskólski, Dariusz; Błasiak-Kołacińska, Nina; Stefańczyk, Ludomir; Majos, Agata

    2015-01-01

    Functional magnetic resonance (fMRI) studies results in case of an adult patient with low grade glioma (LGG) in dominant hemisphere suggest brain plasticity process with acquisition of language functions by the non-dominant hemisphere speech regions. A 36-years old right-handed woman was admitted to the Department of Neurosurgery for surgical treatment of brain tumor. An MRI examination revealed a pathological mass in the left frontal lobe, in close topographical relationship to the Broca’s area. A left fronto-parietal craniotomy was performed, with an intraoperative awake language mapping procedure. A total resection of the pathological mass was achieved. The tumor was examined histologically as LGG. In the follow-up MRI exam 32 months after the operation a tumor recurrence was suggested. The fMRI exams performed preoperative and 3, 32 and 41 months after the operation showed changes in language regions activation patterns, with a progressive right-sided activation of Broca’s and Wernicke’s areas. Pre- and postoperative cognitive evaluation by a neuropsychologist did not detect any language impairment. We present a running process of reorganization of language areas in a patient after brain tumor resection, from strong left-sided to symmetrical lateralization. 1. FMRI results in comparison with the psychological status of the patient proved contribution of functional reorganization to the preservation of language performance. 2. A slow growing LGG as well as the recurrence of the tumor near the left Broca’s area might be the factors leading to reorganization of language-related areas by recruiting the right hemisphe

  18. Modality Specific Cerebro-Cerebellar Activations in Verbal Working Memory: An fMRI Study

    Directory of Open Access Journals (Sweden)

    Matthew P. Kirschen

    2010-01-01

    Full Text Available Verbal working memory (VWM engages frontal and temporal/parietal circuits subserving the phonological loop, as well as, superior and inferior cerebellar regions which have projections from these neocortical areas. Different cerebro-cerebellar circuits may be engaged for integrating aurally- and visually-presented information for VWM. The present fMRI study investigated load (2, 4, or 6 letters and modality (auditory and visual dependent cerebro-cerebellar VWM activation using a Sternberg task. FMRI revealed modality-independent activations in left frontal (BA 6/9/44, insular, cingulate (BA 32, and bilateral inferior parietal/supramarginal (BA 40 regions, as well as in bilateral superior (HVI and right inferior (HVIII cerebellar regions. Visual presentation evoked prominent activations in right superior (HVI/CrusI cerebellum, bilateral occipital (BA19 and left parietal (BA7/40 cortex while auditory presentation showed robust activations predominately in bilateral temporal regions (BA21/22. In the cerebellum, we noted a visual to auditory emphasis of function progressing from superior to inferior and from lateral to medial regions. These results extend our previous findings of fMRI activation in cerebro-cerebellar networks during VWM, and demonstrate both modality dependent commonalities and differences in activations with increasing memory load.

  19. Modality Specific Cerebro-Cerebellar Activations in Verbal Working Memory: An fMRI Study

    Science.gov (United States)

    Kirschen, Matthew P.; Chen, S. H. Annabel; Desmond, John E.

    2010-01-01

    Verbal working memory (VWM) engages frontal and temporal/parietal circuits subserving the phonological loop, as well as, superior and inferior cerebellar regions which have projections from these neocortical areas. Different cerebro-cerebellar circuits may be engaged for integrating aurally- and visually-presented information for VWM. The present fMRI study investigated load (2, 4, or 6 letters) and modality (auditory and visual) dependent cerebro-cerebellar VWM activation using a Sternberg task. FMRI revealed modality-independent activations in left frontal (BA 6/9/44), insular, cingulate (BA 32), and bilateral inferior parietal/supramarginal (BA 40) regions, as well as in bilateral superior (HVI) and right inferior (HVIII) cerebellar regions. Visual presentation evoked prominent activations in right superior (HVI/CrusI) cerebellum, bilateral occipital (BA19) and left parietal (BA7/40) cortex while auditory presentation showed robust activations predominately in bilateral temporal regions (BA21/22). In the cerebellum, we noted a visual to auditory emphasis of function progressing from superior to inferior and from lateral to medial regions. These results extend our previous findings of fMRI activation in cerebro-cerebellar networks during VWM, and demonstrate both modality dependent commonalities and differences in activations with increasing memory load. PMID:20714061

  20. Functional MRI of Language Processing and Recovery

    NARCIS (Netherlands)

    C. Méndez Orellana (Carolina)

    2015-01-01

    markdownabstract__Abstract__ My thesis describe the utility of implementing fMRI to investigate how the language system is reorganized in brain damaged patients. Specifically for aphasia research fMRI allows to show how specific language treatment methods have the potential to enhance language

  1. Language changes coincide with motor and fMRI changes following upper extremity motor therapy for hemiparesis: a brief report.

    Science.gov (United States)

    Harnish, Stacy; Meinzer, Marcus; Trinastic, Jonathan; Fitzgerald, David; Page, Stephen

    2014-09-01

    To formally assess changes in language, affected UE movement, and motor functional activation changes via functional magnetic resonance imaging (fMRI) following participation in motor therapy without any accompanying language intervention. Pre-post case series. Five subjects with stroke exhibiting chronic, stable UE hemiparesis. The upper extremity section of the Fugl-Meyer (FM), the Western Aphasia Battery (WAB), and functional magnetic resonance imaging (fMRI), administered during performance of an affected UE motor task. All subjects were administered six weeks of repetitive task specific training (RTP), performed for approximately 2.5 hours per day, split into two sessions. For the first four weeks of the intervention period, RTP was administered every weekday, whereas, for the subsequent two weeks, RTP was administered 3 days/week. Epidural cortical stimulation was co-administered with the RTP via an electrode array and implanted pulse generator. For all sessions, one subject worked with a single therapist. Four weeks before and four weeks after the intervention period, all subjects were administered the FM, WAB, and fMRI. Three of the subjects exhibited clinically significant language changes on the WAB. These individuals exhibited the largest motor changes as measured by the FM. Functional MRI revealed distinct motor activation patterns in these subjects, characterized by more strongly right lateralized focal BOLD activity or a shift in activation toward the right hemisphere. Language changes appear to co-occur with motor changes after UE RTP. Understanding the underlying mechanisms of these findings may lead to more efficient and synergistic rehabilitative therapy delivery.

  2. Arterial Spin Labeling (ASL) fMRI: advantages, theoretical constrains, and experimental challenges in neurosciences.

    Science.gov (United States)

    Borogovac, Ajna; Asllani, Iris

    2012-01-01

    Cerebral blood flow (CBF) is a well-established correlate of brain function and therefore an essential parameter for studying the brain at both normal and diseased states. Arterial spin labeling (ASL) is a noninvasive fMRI technique that uses arterial water as an endogenous tracer to measure CBF. ASL provides reliable absolute quantification of CBF with higher spatial and temporal resolution than other techniques. And yet, the routine application of ASL has been somewhat limited. In this review, we start by highlighting theoretical complexities and technical challenges of ASL fMRI for basic and clinical research. While underscoring the main advantages of ASL versus other techniques such as BOLD, we also expound on inherent challenges and confounds in ASL perfusion imaging. In closing, we expound on several exciting developments in the field that we believe will make ASL reach its full potential in neuroscience research.

  3. Alternation learning in pathological gamblers: an fMRI Study.

    Science.gov (United States)

    Dannon, Pinhas N; Kushnir, Tammar; Aizer, Anat; Gross-Isseroff, Ruth; Kotler, Moshe; Manor, David

    2011-03-01

    We have previously reported that pathological gamblers have impaired performance on the Stroop color word naming task, go-no-go task and speed accuracy tradeoff performance, tasks used to assess executive function and interference control. The aim of the present neuroimaging study was to explore the relationship between frontal cortex function and gambling severity in pathological gamblers. Functional MRI (fMRI) was used to estimate brain activity of ten male medication-free pathological gamblers during performance of an alternation learning task. Performance of this task has been shown to depend on the function of regions in the frontal cortex. The executive functions needed to perform the alternation learning task were expressed as brain activation in lateral and medial frontal as well as parietal and occipital regions. By correlating the level of local brain activation to task performance, parietal regions and lateral frontal and orbitofrontal regions were demonstrated. A higher score in SOGS was associated with intrusion on the task-specific activation in the left hemisphere, to some extant in parietal regions and even more pronouncedly in left frontal and orbitofrontal regions. Our preliminary data suggests that pathological gambling may be characterized by specific neuro-cognitive changes related to the frontal cortex.

  4. Unique functional abnormalities in youth with combined marijuana use and depression: an fMRI study

    Directory of Open Access Journals (Sweden)

    Kristen A Ford

    2014-09-01

    Full Text Available Prior research has shown a relationship between early onset marijuana (MJ use and depression, however this relationship is complex and poorly understood. Here, we utilized passive music listening and fMRI to examine functional brain activation to a rewarding stimulus in 75 participants (healthy controls (HC, patients with Major Depressive Disorder (MDD, frequent MJ users (MJ, and the combination of MDD and MJ (MDD+MJ. For each participant a preferred and neutral piece of instrumental music was determined (utilizing ratings on a standardized scale, and each completed two 6-minute fMRI scans of a passive music listening task. Data underwent preprocessing and 61 participants were carried forward for analysis (17 HC, 15 MDD, 15 MJ, 14 MDD+MJ. Two statistical analyses were performed using SPM8, an ANCOVA with two factors (group x music-type and a whole brain, multiple regression analysis incorporating two predictors of interest (MJ use in past 28 days; and Beck Depression Inventory (BDI score. We identified a significant group x music-type interaction. Post hoc comparisons showed the preferred music had significantly greater activation in the MDD+MJ group in areas including the right middle and inferior frontal gyri extending into the claustrum and putamen and the anterior cingulate. No significant differences were identified in MDD, MJ or HC groups. Multiple regression analysis showed that activation in medial frontal cortex was positively correlated with amount of MJ use, and activation in areas including the insula was negatively correlated with BDI score. Results showed modulation in brain activation during passive music listening specific to MDD, frequent MJ users. This supports the suggestion that frequent MJ use, when combined with MDD, is associated with changes in neurocircuitry involved in reward-processing in ways that are absent with either frequent marijuana use or MDD alone. This could help inform clinical recommendations for youth with

  5. Differences in Processing of Taxonomic and Sequential Relations in Semantic Memory: An fMRI Investigation

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    Kuchinke, Lars; van der Meer, Elke; Krueger, Frank

    2009-01-01

    Conceptual knowledge of our world is represented in semantic memory in terms of concepts and semantic relations between concepts. We used functional magnetic resonance imaging (fMRI) to examine the cortical regions underlying the processing of sequential and taxonomic relations. Participants were presented verbal cues and performed three tasks:…

  6. Functional Connectivity Estimated from Resting-State fMRI Reveals Selective Alterations in Male Adolescents with Pure Conduct Disorder.

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    Feng-Mei Lu

    Full Text Available Conduct disorder (CD is characterized by a persistent pattern of antisocial behavior and aggression in childhood and adolescence. Previous task-based and resting-state functional magnetic resonance imaging (fMRI studies have revealed widespread brain regional abnormalities in adolescents with CD. However, whether the resting-state networks (RSNs are altered in adolescents with CD remains unknown. In this study, resting-state fMRI data were first acquired from eighteen male adolescents with pure CD and eighteen age- and gender-matched typically developing (TD individuals. Independent component analysis (ICA was implemented to extract nine representative RSNs, and the generated RSNs were then compared to show the differences between the CD and TD groups. Interestingly, it was observed from the brain mapping results that compared with the TD group, the CD group manifested decreased functional connectivity in four representative RSNs: the anterior default mode network (left middle frontal gyrus, which is considered to be correlated with impaired social cognition, the somatosensory network (bilateral supplementary motor area and right postcentral gyrus, the lateral visual network (left superior occipital gyrus, and the medial visual network (right fusiform, left lingual gyrus and right calcarine, which are expected to be relevant to the perceptual systems responsible for perceptual dysfunction in male adolescents with CD. Importantly, the novel findings suggested that male adolescents with pure CD were identified to have dysfunctions in both low-level perceptual networks (the somatosensory network and visual network and a high-order cognitive network (the default mode network. Revealing the changes in the functional connectivity of these RSNs enhances our understanding of the neural mechanisms underlying the modulation of emotion and social cognition and the regulation of perception in adolescents with CD.

  7. Functional connectivity of motor cortical network in patients with brachial plexus avulsion injury after contralateral cervical nerve transfer: a resting-state fMRI study

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    Yu, Aihong; Cheng, Xiaoguang; Liang, Wei; Bai, Rongjie [The 4th Medical College of Peking University, Department of Radiology, Beijing Jishuitan Hospital, Xicheng Qu, Beijing (China); Wang, Shufeng; Xue, Yunhao; Li, Wenjun [The 4th Medical College of Peking University, Department of Hand Surgery, Beijing Jishuitan Hospital, Beijing (China)

    2017-03-15

    The purpose of this study is to assess the functional connectivity of the motor cortical network in patients with brachial plexus avulsion injury (BPAI) after contralateral C7 nerve transfer, using resting-state functional magnetic resonance imaging (RS-fMRI). Twelve patients with total brachial plexus root avulsion underwent RS-fMRI after contralateral C7 nerve transfer. Seventeen healthy volunteers were also included in this fMRI study as controls. The hand motor seed regions were defined as region of interests in the bilateral hemispheres. The seed-based functional connectivity was calculated in all the subjects. Differences in functional connectivity of the motor cortical network between patients and healthy controls were compared. The inter-hemispheric functional connectivity of the M1 areas was increased in patients with BPAI compared with the controls. The inter-hemispheric functional connectivity between the supplementary motor areas was reduced bilaterally. The resting-state inter-hemispheric functional connectivity of the bilateral M1 areas is altered in patients after contralateral C7 nerve transfer, suggesting a functional reorganization of cerebral cortex. (orig.)

  8. Functional connectivity of motor cortical network in patients with brachial plexus avulsion injury after contralateral cervical nerve transfer: a resting-state fMRI study

    International Nuclear Information System (INIS)

    Yu, Aihong; Cheng, Xiaoguang; Liang, Wei; Bai, Rongjie; Wang, Shufeng; Xue, Yunhao; Li, Wenjun

    2017-01-01

    The purpose of this study is to assess the functional connectivity of the motor cortical network in patients with brachial plexus avulsion injury (BPAI) after contralateral C7 nerve transfer, using resting-state functional magnetic resonance imaging (RS-fMRI). Twelve patients with total brachial plexus root avulsion underwent RS-fMRI after contralateral C7 nerve transfer. Seventeen healthy volunteers were also included in this fMRI study as controls. The hand motor seed regions were defined as region of interests in the bilateral hemispheres. The seed-based functional connectivity was calculated in all the subjects. Differences in functional connectivity of the motor cortical network between patients and healthy controls were compared. The inter-hemispheric functional connectivity of the M1 areas was increased in patients with BPAI compared with the controls. The inter-hemispheric functional connectivity between the supplementary motor areas was reduced bilaterally. The resting-state inter-hemispheric functional connectivity of the bilateral M1 areas is altered in patients after contralateral C7 nerve transfer, suggesting a functional reorganization of cerebral cortex. (orig.)

  9. Chronotype Modulates Language Processing-Related Cerebral Activity during Functional MRI (fMRI.

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    Jessica Rosenberg

    Full Text Available Based on individual daily physiological cycles, humans can be classified as early (EC, late (LC and intermediate (IC chronotypes. Recent studies have verified that chronotype-specificity relates to performance on cognitive tasks: participants perform more efficiently when tested in the chronotype-specific optimal time of day than when tested in their non-optimal time. Surprisingly, imaging studies focussing on the underlying neural mechanisms of potential chronotype-specificities are sparse. Moreover, chronotype-specific alterations of language-related semantic processing have been neglected so far.16 male, healthy ECs, 16 ICs and 16 LCs participated in a fast event-related functional Magnetic Resonance Imaging (fMRI paradigm probing semantic priming. Subjects read two subsequently presented words (prime, target and were requested to determine whether the target word was an existing word or a non-word. Subjects were tested during their individual evening hours when homeostatic sleep pressure and circadian alertness levels are high to ensure equal entrainment.Chronotype-specificity is associated with task-performance and brain activation. First, ECs exhibited slower reaction times than LCs. Second, ECs showed attenuated BOLD responses in several language-related brain areas, e.g. in the left postcentral gyrus, left and right precentral gyrus and in the right superior frontal gyrus. Additionally, increased BOLD responses were revealed for LCs as compared to ICs in task-related areas, e.g. in the right inferior parietal lobule and in the right postcentral gyrus.These findings reveal that even basic language processes are associated with chronotype-specific neuronal mechanisms. Consequently, results might change the way we schedule patient evaluations and/or healthy subjects in e.g. experimental research and adding "chronotype" as a statistical covariate.

  10. Cortical Reorganization in Patients Recovered from Bell’s Palsy: An Orofacial and Finger Movements Task-State fMRI Study

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    Jaeyoun Lee

    2016-01-01

    Full Text Available Objective. To explore cortical reorganization of patients recovered from Bell’s palsy (BP by task-state functional magnetic resonance imaging (fMRI during finger and orofacial movements and provide more evidence for acupuncture clinical treatment of BP. Methods. We collected 17 BP patients with complete clinical recovery (BP group and 20 healthy volunteers (control group accepted the task-state fMRI scans with lip pursing movements and finger movements, respectively. Results. It was found that there were significant differences of brain functional status between the two groups. Conclusions. The results showed that there was cortical reorganization in the brain of patients recovered from BP after acupuncture treatment, which also suggested the relationship between the hand motor areas and facial motor areas of BP patients.

  11. Combining fMRI and behavioral measures to examine the process of human learning.

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    Karuza, Elisabeth A; Emberson, Lauren L; Aslin, Richard N

    2014-03-01

    Prior to the advent of fMRI, the primary means of examining the mechanisms underlying learning were restricted to studying human behavior and non-human neural systems. However, recent advances in neuroimaging technology have enabled the concurrent study of human behavior and neural activity. We propose that the integration of behavioral response with brain activity provides a powerful method of investigating the process through which internal representations are formed or changed. Nevertheless, a review of the literature reveals that many fMRI studies of learning either (1) focus on outcome rather than process or (2) are built on the untested assumption that learning unfolds uniformly over time. We discuss here various challenges faced by the field and highlight studies that have begun to address them. In doing so, we aim to encourage more research that examines the process of learning by considering the interrelation of behavioral measures and fMRI recording during learning. Copyright © 2013 Elsevier Inc. All rights reserved.

  12. Ultrafast bold fMRI using single-shot spin-echo echo planar imaging

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    Boujraf Said

    2009-01-01

    Full Text Available The choice of imaging parameters for functional MRI can have an impact on the accuracy of functional localization by affecting the image quality and the degree of blood oxygenation-dependent (BOLD contrast achieved. By improving sampling efficiency, parallel acquisition techniques such as sensitivity encoding (SENSE have been used to shorten readout trains in single-shot (SS echo planar imaging (EPI. This has been applied to susceptibility artifact reduction and improving spatial resolution. SENSE together with single-shot spin-echo (SS-SE imaging may also reduce off-resonance artifacts. The goal of this work was to investigate the BOLD response of a SENSE-adapted SE-EPI on a three Tesla scanner. Whole-brain fMRI studies of seven healthy right hand-dominant volunteers were carried out in a three Tesla scanner. fMRI was performed using an SS-SE EPI sequence with SENSE. The data was processed using statistical parametric mapping. Both, group and individual subject data analyses were performed. Individual average percentage and maximal percentage signal changes attributed to the BOLD effect in M1 were calculated for all the subjects as a function of echo time. Corresponding activation maps and the sizes of the activated clusters were also calculated. Our results show that susceptibility artifacts were reduced with the use of SENSE; and the acquired BOLD images were free of the typical quadrature artifacts of SS-EPI. Such measures are crucial at high field strengths. SS SE-EPI with SENSE offers further benefits in this regard and is more specific for oxygenation changes in the microvasculature bed. Functional brain activity can be investigated with the help of single-shot spin echo EPI using SENSE at high magnetic fields.

  13. Functional Laterality of Task-Evoked Activation in Sensorimotor Cortex of Preterm Infants: An Optimized 3 T fMRI Study Employing a Customized Neonatal Head Coil.

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    Lukas Scheef

    Full Text Available Functional magnetic resonance imaging (fMRI in neonates has been introduced as a non-invasive method for studying sensorimotor processing in the developing brain. However, previous neonatal studies have delivered conflicting results regarding localization, lateralization, and directionality of blood oxygenation level dependent (BOLD responses in sensorimotor cortex (SMC. Amongst the confounding factors in interpreting neonatal fMRI studies include the use of standard adult MR-coils providing insufficient signal to noise, and liberal statistical thresholds, compromising clinical interpretation at the single subject level.Here, we employed a custom-designed neonatal MR-coil adapted and optimized to the head size of a newborn in order to improve robustness, reliability and validity of neonatal sensorimotor fMRI. Thirteen preterm infants with a median gestational age of 26 weeks were scanned at term-corrected age using a prototype 8-channel neonatal head coil at 3T (Achieva, Philips, Best, NL. Sensorimotor stimulation was elicited by passive extension/flexion of the elbow at 1 Hz in a block design. Analysis of temporal signal to noise ratio (tSNR was performed on the whole brain and the SMC, and was compared to data acquired with an 'adult' 8 channel head coil published previously. Task-evoked activation was determined by single-subject SPM8 analyses, thresholded at p < 0.05, whole-brain FWE-corrected.Using a custom-designed neonatal MR-coil, we found significant positive BOLD responses in contralateral SMC after unilateral passive sensorimotor stimulation in all neonates (analyses restricted to artifact-free data sets = 8/13. Improved imaging characteristics of the neonatal MR-coil were evidenced by additional phantom and in vivo tSNR measurements: phantom studies revealed a 240% global increase in tSNR; in vivo studies revealed a 73% global and a 55% local (SMC increase in tSNR, as compared to the 'adult' MR-coil.Our findings strengthen the

  14. Modulation of brain response to emotional conflict as a function of current mood in bipolar disorder: preliminary findings from a follow-up state-based fMRI study.

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    Rey, Gwladys; Desseilles, Martin; Favre, Sophie; Dayer, Alexandre; Piguet, Camille; Aubry, Jean-Michel; Vuilleumier, Patrik

    2014-08-30

    We used functional magnetic resonance imaging (fMRI) to examine affective control longitudinally in a group of patients with bipolar disorder (BD). Participants comprised 12 BD patients who underwent repeated fMRI scans in euthymic (n=11), depressed (n=9), or hypomanic (n=9) states, and were compared with 12 age-matched healthy controls. During fMRI, participants performed an emotional face-word interference task with either low or high attentional demands. Relative to healthy controls, patients showed decreased activation of the cognitive control network normally associated with conflict processing, more severely during hypomania than during depression, but regardless of level of task demand in both cases. During euthymia, a decreased response to conflict was observed only during the high load condition. Additionally, unlike healthy participants, patients exhibited deactivation in several key areas in response to emotion-conflict trials - including the rostral anterior cingulate cortex during euthymia, the hippocampus during depression, and the posterior cingulate cortex during hypomania. Our results indicate that the ability of BD patients to recruit control networks when processing affective conflict, and the abnormal suppression of activity in distinct components of the default mode network, may depend on their current clinical state and attentional demand. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  15. Brain Network Response to Acupuncture Stimuli in Experimental Acute Low Back Pain: An fMRI Study

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    Yu Shi

    2015-01-01

    Full Text Available Most neuroimaging studies have demonstrated that acupuncture can significantly modulate brain activation patterns in healthy subjects, while only a few studies have examined clinical pain. In the current study, we combined an experimental acute low back pain (ALBP model and functional magnetic resonance imaging (fMRI to explore the neural mechanisms of acupuncture analgesia. All ALBP subjects first underwent two resting state fMRI scans at baseline and during a painful episode and then underwent two additional fMRI scans, once during acupuncture stimulation (ACUP and once during tactile stimulation (SHAM pseudorandomly, at the BL40 acupoint. Our results showed that, compared with the baseline, the pain state had higher regional homogeneity (ReHo values in the pain matrix, limbic system, and default mode network (DMN and lower ReHo values in frontal gyrus and temporal gyrus; compared with the OFF status, ACUP yielded broad deactivation in subjects, including nearly all of the limbic system, pain status, and DMN, and also evoked numerous activations in the attentional and somatosensory systems; compared with SHAM, we found that ACUP induced more deactivations and fewer activations in the subjects. Multiple brain networks play crucial roles in acupuncture analgesia, suggesting that ACUP exceeds a somatosensory-guided mind-body therapy for ALBP.

  16. When We like What We Know--A Parametric fMRI Analysis of Beauty and Familiarity

    Science.gov (United States)

    Bohrn, Isabel C.; Altmann, Ulrike; Lubrich, Oliver; Menninghaus, Winfried; Jacobs, Arthur M.

    2013-01-01

    This paper presents a neuroscientific study of aesthetic judgments on written texts. In an fMRI experiment participants read a number of proverbs without explicitly evaluating them. In a post-scan rating they rated each item for familiarity and beauty. These individual ratings were correlated with the functional data to investigate the neural…

  17. How restful is it with all that noise? Comparison of Interleaved silent steady state (ISSS) and conventional imaging in resting-state fMRI.

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    Andoh, J; Ferreira, M; Leppert, I R; Matsushita, R; Pike, B; Zatorre, R J

    2017-02-15

    Resting-state fMRI studies have become very important in cognitive neuroscience because they are able to identify BOLD fluctuations in brain circuits involved in motor, cognitive, or perceptual processes without the use of an explicit task. Such approaches have been fruitful when applied to various disordered populations, or to children or the elderly. However, insufficient attention has been paid to the consequences of the loud acoustic scanner noise associated with conventional fMRI acquisition, which could be an important confounding factor affecting auditory and/or cognitive networks in resting-state fMRI. Several approaches have been developed to mitigate the effects of acoustic noise on fMRI signals, including sparse sampling protocols and interleaved silent steady state (ISSS) acquisition methods, the latter being used only for task-based fMRI. Here, we developed an ISSS protocol for resting-state fMRI (rs-ISSS) consisting of rapid acquisition of a set of echo planar imaging volumes following each silent period, during which the steady state longitudinal magnetization was maintained with a train of relatively silent slice-selective excitation pulses. We evaluated the test-retest reliability of intensity and spatial extent of connectivity networks of fMRI BOLD signal across three different days for rs-ISSS and compared it with a standard resting-state fMRI (rs-STD). We also compared the strength and distribution of connectivity networks between rs-ISSS and rs-STD. We found that both rs-ISSS and rs-STD showed high reproducibility of fMRI signal across days. In addition, rs-ISSS showed a more robust pattern of functional connectivity within the somatosensory and motor networks, as well as an auditory network compared with rs-STD. An increased connectivity between the default mode network and the language network and with the anterior cingulate cortex (ACC) network was also found for rs-ISSS compared with rs-STD. Finally, region of interest analysis showed

  18. Arcuate fasciculus laterality by diffusion tensor imaging correlates with language laterality by functional MRI in preadolescent children.

    Science.gov (United States)

    Sreedharan, Ruma Madhu; Menon, Amitha C; James, Jija S; Kesavadas, Chandrasekharan; Thomas, Sanjeev V

    2015-03-01

    Language lateralization is unique to humans. Functional MRI (fMRI) and diffusion tensor imaging (DTI) enable the study of language areas and white matter fibers involved in language, respectively. The objective of this study was to correlate arcuate fasciculus (AF) laterality by diffusion tensor imaging with that by fMRI in preadolescent children which has not yet been reported. Ten children between 8 and 12 years were subjected to fMRI and DTI imaging using Siemens 1.5 T MRI. Two language fMRI paradigms--visual verb generation and word pair task--were used. Analysis was done using SPM8 software. In DTI, the fiber volume of the arcuate fasciculus (AFV) and fractional anisotropy (FA) was measured. The fMRI Laterality Index (fMRI-LI) and DTI Laterality Index (DTI-LI) were calculated and their correlation assessed using the Pearson Correlation Index. Of ten children, mean age 10.6 years, eight showed left lateralization while bilateral language lateralization was seen in two. AFV by DTI was more on the left side in seven of the eight children who had left lateralization by fMRI. DTI could not trace the AF in one child. Of the two with bilateral language lateralization on fMRI, one showed larger AFV on the right side while the other did not show any asymmetry. There was a significant correlation (p laterality in children with a high degree of correlation between the two imaging modalities.

  19. ADHD-200 Global Competition: Diagnosing ADHD using personal characteristic data can outperform resting state fMRI measurements

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    Matthew R G Brown

    2012-09-01

    Full Text Available Neuroimaging-based diagnostics could potentially assist clinicians to make more accurate diagnoses resulting in faster, more effective treatment. We participated in the 2011 ADHD-200 Global Competition which involved analyzing a large dataset of 973 participants including ADHD patients and healthy controls. Each participant's data included a resting state functional magnetic resonance imaging (fMRI scan as well as personal characteristic and diagnostic data. The goal was to learn a machine learning classifier that used a participant's resting state fMRI scan to diagnose (classify that individual into one of three categories: healthy control, ADHD combined type, or ADHD inattentive type. We used participants' personal characteristic data (site of data collection, age, gender, handedness, performance IQ, verbal IQ, and full scale IQ, without any fMRI data, as input to a logistic classifier to generate diagnostic predictions. Surprisingly, this approach achieved the highest diagnostic accuracy (62.52% as well as the highest score (124 of 195 of any of the 21 teams participating in the competition. These results demonstrate the importance of accounting for differences in age, gender, and other personal characteristics in imaging diagnostics research. We discuss further implications of these results for fMRI-based diagnosis as well as fMRI-based clinical research. We also document our tests with a variety of imaging-based diagnostic methods, none of which performed as well as the logistic classifier using only personal characteristic data.

  20. fMRI neurofeedback facilitates anxiety regulation in females with spider phobia

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    Anna eZilverstand

    2015-06-01

    Full Text Available Background: Spider phobics show an exaggerated fear response when encountering spiders. This fear response is aggravated by negative and irrational beliefs about the feared object. Cognitive reappraisal can target these beliefs, and therefore has a fear regulating effect. The presented study investigated if neurofeedback derived from functional magnetic resonance imaging (fMRI would facilitate anxiety regulation by cognitive reappraisal, using spider phobia as a model of anxiety disorders. Feedback was provided based on activation in left dorsolateral prefrontal cortex and right insula, as indicators of engagement and regulation success, respectively.Methods: Eighteen female spider phobics participated in a randomized, controlled, single-blinded study. All participants completed a training session in the MRI scanner. Participants assigned to the neurofeedback condition were instructed to shape their regulatory strategy based on the provided feedback. Participants assigned to the control condition were asked to adapt their strategy intuitively.Results: Neurofeedback participants exhibited lower anxiety levels than the control group at the end of the training. In addition, only neurofeedback participants achieved down-regulation of insula activation levels by cognitive reappraisal. Group differences became more pronounced over time, supporting learning as a mechanism behind this effect. Importantly, within the neurofeedback group, achieved changes in insula activation levels during training predicted long-term anxiety reduction.Conclusions: The conducted study provides first evidence that fMRI neurofeedback has a facilitating effect on anxiety regulation in spider phobia.

  1. Multimodal functional network connectivity: an EEG-fMRI fusion in network space.

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    Xu Lei

    Full Text Available EEG and fMRI recordings measure the functional activity of multiple coherent networks distributed in the cerebral cortex. Identifying network interaction from the complementary neuroelectric and hemodynamic signals may help to explain the complex relationships between different brain regions. In this paper, multimodal functional network connectivity (mFNC is proposed for the fusion of EEG and fMRI in network space. First, functional networks (FNs are extracted using spatial independent component analysis (ICA in each modality separately. Then the interactions among FNs in each modality are explored by Granger causality analysis (GCA. Finally, fMRI FNs are matched to EEG FNs in the spatial domain using network-based source imaging (NESOI. Investigations of both synthetic and real data demonstrate that mFNC has the potential to reveal the underlying neural networks of each modality separately and in their combination. With mFNC, comprehensive relationships among FNs might be unveiled for the deep exploration of neural activities and metabolic responses in a specific task or neurological state.

  2. Increased interhemispheric resting-state functional connectivity after sleep deprivation: a resting-state fMRI study.

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    Zhu, Yuanqiang; Feng, Zhiyan; Xu, Junling; Fu, Chang; Sun, Jinbo; Yang, Xuejuan; Shi, Dapeng; Qin, Wei

    2016-09-01

    Several functional imaging studies have investigated the regional effects of sleep deprivation (SD) on impaired brain function; however, potential changes in the functional interactions between the cerebral hemispheres after SD are not well understood. In this study, we used a recently validated approach, voxel-mirrored homotopic connectivity (VMHC), to directly examine the changes in interhemispheric homotopic resting-state functional connectivity (RSFC) after SD. Resting-state functional MRI (fMRI) was performed in 28 participants both after rest wakefulness (RW) and a total night of SD. An interhemispheric RSFC map was obtained by calculating the Pearson correlation (Fisher Z transformed) between each pair of homotopic voxel time series for each subject in each condition. The between-condition differences in interhemispheric RSFC were then examined at global and voxelwise levels separately. Significantly increased global VMHC was found after sleep deprivation; specifically, a significant increase in VMHC was found in specific brain regions, including the thalamus, paracentral lobule, supplementary motor area, postcentral gyrus and lingual gyrus. No regions showed significantly reduced VMHC after sleep deprivation. Further analysis indicates that these findings did not depend on the various sizes of smoothing kernels that were adopted in the preprocessing steps and that the differences in these regions were still significant with or without global signal regression. Our data suggest that the increased VMHC might reflect the compensatory involvement of bilateral brain areas, especially the bilateral thalamus, to prevent cognitive performance deterioration when sleep pressure is elevated after sleep deprivation. Our findings provide preliminary evidence of interhemispheric correlation changes after SD and contribute to a better understanding of the neural mechanisms of SD.

  3. Decrease in fMRI brain activation during working memory performed after sleeping under 10 lux light.

    Science.gov (United States)

    Kang, Seung-Gul; Yoon, Ho-Kyoung; Cho, Chul-Hyun; Kwon, Soonwook; Kang, June; Park, Young-Min; Lee, Eunil; Kim, Leen; Lee, Heon-Jeong

    2016-11-09

    The aim of this study was to investigate the effect of exposure to dim light at night (dLAN) when sleeping on functional brain activation during a working-memory tasks. We conducted the brain functional magnetic resonance imaging (fMRI) analysis on 20 healthy male subjects. All participants slept in a polysomnography laboratory without light exposure on the first and second nights and under a dim-light condition of either 5 or 10 lux on the third night. The fMRI scanning was conducted during n-back tasks after second and third nights. Statistical parametric maps revealed less activation in the right inferior frontal gyrus (IFG) after exposure to 10-lux light. The brain activity in the right and left IFG areas decreased more during the 2-back task than during the 1- or 0-back task in the 10-lux group. The exposure to 5-lux light had no significant effect on brain activities. The exposure to dLAN might influence the brain function which is related to the cognition.

  4. Characterization of dynamic changes of current source localization based on spatiotemporal fMRI constrained EEG source imaging

    Science.gov (United States)

    Nguyen, Thinh; Potter, Thomas; Grossman, Robert; Zhang, Yingchun

    2018-06-01

    Objective. Neuroimaging has been employed as a promising approach to advance our understanding of brain networks in both basic and clinical neuroscience. Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) represent two neuroimaging modalities with complementary features; EEG has high temporal resolution and low spatial resolution while fMRI has high spatial resolution and low temporal resolution. Multimodal EEG inverse methods have attempted to capitalize on these properties but have been subjected to localization error. The dynamic brain transition network (DBTN) approach, a spatiotemporal fMRI constrained EEG source imaging method, has recently been developed to address these issues by solving the EEG inverse problem in a Bayesian framework, utilizing fMRI priors in a spatial and temporal variant manner. This paper presents a computer simulation study to provide a detailed characterization of the spatial and temporal accuracy of the DBTN method. Approach. Synthetic EEG data were generated in a series of computer simulations, designed to represent realistic and complex brain activity at superficial and deep sources with highly dynamical activity time-courses. The source reconstruction performance of the DBTN method was tested against the fMRI-constrained minimum norm estimates algorithm (fMRIMNE). The performances of the two inverse methods were evaluated both in terms of spatial and temporal accuracy. Main results. In comparison with the commonly used fMRIMNE method, results showed that the DBTN method produces results with increased spatial and temporal accuracy. The DBTN method also demonstrated the capability to reduce crosstalk in the reconstructed cortical time-course(s) induced by neighboring regions, mitigate depth bias and improve overall localization accuracy. Significance. The improved spatiotemporal accuracy of the reconstruction allows for an improved characterization of complex neural activity. This improvement can be

  5. Diagnostic precision of PET imaging and functional MRI in disorders of consciousness

    DEFF Research Database (Denmark)

    Stender, Johan; Gosseries, Olivia; Bruno, Marie-Aurélie

    2014-01-01

    a validation study of two neuroimaging-based diagnostic methods: PET imaging and functional MRI (fMRI). METHODS: For this clinical validation study, we included patients referred to the University Hospital of Liège, Belgium, between January, 2008, and June, 2012, who were diagnosed by our unit...... with unresponsive wakefulness syndrome, locked-in syndrome, or minimally conscious state with traumatic or non-traumatic causes. We did repeated standardised clinical assessments with the Coma Recovery Scale-Revised (CRS-R), cerebral (18)F-fluorodeoxyglucose (FDG) PET, and fMRI during mental activation tasks. We...... state (48=traumatic, 78=non-traumatic; 110=chronic, 16=subacute). (18)F-FDG PET had high sensitivity for identification of patients in a minimally conscious state (93%, 95% CI 85-98) and high congruence (85%, 77-90) with behavioural CRS-R scores. The active fMRI method was less sensitive at diagnosis...

  6. Effect of Unpleasant Loud Noise on Hippocampal Activities during Picture Encoding: An fMRI Study

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    Hirano, Yoshiyuki; Fujita, Masafumi; Watanabe, Kazuko; Niwa, Masami; Takahashi, Toru; Kanematsu, Masayuki; Ido, Yasushi; Tomida, Mihoko; Onozuka, Minoru

    2006-01-01

    The functional link between the amygdala and hippocampus in humans has not been well documented. We examined the effect of unpleasant loud noise on hippocampal and amygdaloid activities during picture encoding by means of fMRI, and on the correct response in humans. The noise reduced activity in the hippocampus during picture encoding, decreased…

  7. The olfactory deficit and fMRI in the Alzheimer's disease

    International Nuclear Information System (INIS)

    Yin Jianzhong; Wang Jianli; Yang Qingxian; Qi Ji

    2008-01-01

    Olfactory deficit is a common symptom occurring at the early stage of Alzheimer's disease, the purpose of this review is to summarize MRI research on olfactory deficit in the Alzheimer's disease and potential clinical relevance of fMRI in this area. (authors)

  8. Real-time fMRI neurofeedback in adolescents with attention deficit hyperactivity disorder.

    Science.gov (United States)

    Alegria, Analucia A; Wulff, Melanie; Brinson, Helen; Barker, Gareth J; Norman, Luke J; Brandeis, Daniel; Stahl, Daniel; David, Anthony S; Taylor, Eric; Giampietro, Vincent; Rubia, Katya

    2017-06-01

    Attention Deficit Hyperactivity Disorder (ADHD) is associated with poor self-control, underpinned by inferior fronto-striatal deficits. Real-time functional magnetic resonance neurofeedback (rtfMRI-NF) allows participants to gain self-control over dysregulated brain regions. Despite evidence for beneficial effects of electrophysiological-NF on ADHD symptoms, no study has applied the spatially superior rtfMRI-NF neurotherapy to ADHD. A randomized controlled trial tested the efficacy of rtfMRI-NF of right inferior prefrontal cortex (rIFG), a key region that is compromised in ADHD and upregulated with psychostimulants, on improvement of ADHD symptoms, cognition, and inhibitory fMRI activation. To control for region-specificity, an active control group received rtfMRI-NF of the left parahippocampal gyrus (lPHG). Thirty-one ADHD boys were randomly allocated and had to learn to upregulate their target brain region in an average of 11 rtfMRI-NF runs over 2 weeks. Feedback was provided through a video-clip of a rocket that had to be moved up into space. A transfer session without feedback tested learning retention as a proximal measure of transfer to everyday life. Both NF groups showed significant linear activation increases with increasing number of runs in their respective target regions and significant reduction in ADHD symptoms after neurotherapy and at 11-month follow-up. Only the group targeting rIFG, however, showed a transfer effect, which correlated with ADHD symptom reductions, improved at trend level in sustained attention, and showed increased IFG activation during an inhibitory fMRI task. This proof-of-concept study demonstrates for the first time feasibility, safety, and shorter- and longer-term efficacy of rtfMRI-NF of rIFG in adolescents with ADHD. Hum Brain Mapp 38:3190-3209, 2017. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

  9. Single-task fMRI overlap predicts concurrent multitasking interference.

    Science.gov (United States)

    Nijboer, Menno; Borst, Jelmer; van Rijn, Hedderik; Taatgen, Niels

    2014-10-15

    There is no consensus regarding the origin of behavioral interference that occurs during concurrent multitasking. Some evidence points toward a multitasking locus in the brain, while other results imply that interference is the consequence of task interactions in several brain regions. To investigate this issue, we conducted a functional MRI (fMRI) study consisting of three component tasks, which were performed both separately and in combination. The results indicated that no specific multitasking area exists. Instead, different patterns of activation across conditions could be explained by assuming that the interference is a result of task interactions. Additionally, similarity in single-task activation patterns correlated with a decrease in accuracy during dual-task conditions. Taken together, these results support the view that multitasking interference is not due to a bottleneck in a single "multitasking" brain region, but is a result of interactions between concurrently running processes. Copyright © 2014 Elsevier Inc. All rights reserved.

  10. PreSurgMapp: a MATLAB Toolbox for Presurgical Mapping of Eloquent Functional Areas Based on Task-Related and Resting-State Functional MRI.

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    Huang, Huiyuan; Ding, Zhongxiang; Mao, Dewang; Yuan, Jianhua; Zhu, Fangmei; Chen, Shuda; Xu, Yan; Lou, Lin; Feng, Xiaoyan; Qi, Le; Qiu, Wusi; Zhang, Han; Zang, Yu-Feng

    2016-10-01

    The main goal of brain tumor surgery is to maximize tumor resection while minimizing the risk of irreversible postoperative functional sequelae. Eloquent functional areas should be delineated preoperatively, particularly for patients with tumors near eloquent areas. Functional magnetic resonance imaging (fMRI) is a noninvasive technique that demonstrates great promise for presurgical planning. However, specialized data processing toolkits for presurgical planning remain lacking. Based on several functions in open-source software such as Statistical Parametric Mapping (SPM), Resting-State fMRI Data Analysis Toolkit (REST), Data Processing Assistant for Resting-State fMRI (DPARSF) and Multiple Independent Component Analysis (MICA), here, we introduce an open-source MATLAB toolbox named PreSurgMapp. This toolbox can reveal eloquent areas using comprehensive methods and various complementary fMRI modalities. For example, PreSurgMapp supports both model-based (general linear model, GLM, and seed correlation) and data-driven (independent component analysis, ICA) methods and processes both task-based and resting-state fMRI data. PreSurgMapp is designed for highly automatic and individualized functional mapping with a user-friendly graphical user interface (GUI) for time-saving pipeline processing. For example, sensorimotor and language-related components can be automatically identified without human input interference using an effective, accurate component identification algorithm using discriminability index. All the results generated can be further evaluated and compared by neuro-radiologists or neurosurgeons. This software has substantial value for clinical neuro-radiology and neuro-oncology, including application to patients with low- and high-grade brain tumors and those with epilepsy foci in the dominant language hemisphere who are planning to undergo a temporal lobectomy.

  11. Effective Connectivity of Cortical Sensorimotor Networks During Finger Movement Tasks: A Simultaneous fNIRS, fMRI, EEG Study.

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    Anwar, A R; Muthalib, M; Perrey, S; Galka, A; Granert, O; Wolff, S; Heute, U; Deuschl, G; Raethjen, J; Muthuraman, Muthuraman

    2016-09-01

    Recently, interest has been growing to understand the underlying dynamic directional relationship between simultaneously activated regions of the brain during motor task performance. Such directionality analysis (or effective connectivity analysis), based on non-invasive electrophysiological (electroencephalography-EEG) and hemodynamic (functional near infrared spectroscopy-fNIRS; and functional magnetic resonance imaging-fMRI) neuroimaging modalities can provide an estimate of the motor task-related information flow from one brain region to another. Since EEG, fNIRS and fMRI modalities achieve different spatial and temporal resolutions of motor-task related activation in the brain, the aim of this study was to determine the effective connectivity of cortico-cortical sensorimotor networks during finger movement tasks measured by each neuroimaging modality. Nine healthy subjects performed right hand finger movement tasks of different complexity (simple finger tapping-FT, simple finger sequence-SFS, and complex finger sequence-CFS). We focused our observations on three cortical regions of interest (ROIs), namely the contralateral sensorimotor cortex (SMC), the contralateral premotor cortex (PMC) and the contralateral dorsolateral prefrontal cortex (DLPFC). We estimated the effective connectivity between these ROIs using conditional Granger causality (GC) analysis determined from the time series signals measured by fMRI (blood oxygenation level-dependent-BOLD), fNIRS (oxygenated-O2Hb and deoxygenated-HHb hemoglobin), and EEG (scalp and source level analysis) neuroimaging modalities. The effective connectivity analysis showed significant bi-directional information flow between the SMC, PMC, and DLPFC as determined by the EEG (scalp and source), fMRI (BOLD) and fNIRS (O2Hb and HHb) modalities for all three motor tasks. However the source level EEG GC values were significantly greater than the other modalities. In addition, only the source level EEG showed a

  12. Introducing Alternative-Based Thresholding for Defining Functional Regions of Interest in fMRI

    Directory of Open Access Journals (Sweden)

    Jasper Degryse

    2017-04-01

    Full Text Available In fMRI research, one often aims to examine activation in specific functional regions of interest (fROIs. Current statistical methods tend to localize fROIs inconsistently, focusing on avoiding detection of false activation. Not missing true activation is however equally important in this context. In this study, we explored the potential of an alternative-based thresholding (ABT procedure, where evidence against the null hypothesis of no effect and evidence against a prespecified alternative hypothesis is measured to control both false positives and false negatives directly. The procedure was validated in the context of localizer tasks on simulated brain images and using a real data set of 100 runs per subject. Voxels categorized as active with ABT can be confidently included in the definition of the fROI, while inactive voxels can be confidently excluded. Additionally, the ABT method complements classic null hypothesis significance testing with valuable information by making a distinction between voxels that show evidence against both the null and alternative and voxels for which the alternative hypothesis cannot be rejected despite lack of evidence against the null.

  13. Optimal HRF and smoothing parameters for fMRI time series within an autoregressive modeling framework.

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    Galka, Andreas; Siniatchkin, Michael; Stephani, Ulrich; Groening, Kristina; Wolff, Stephan; Bosch-Bayard, Jorge; Ozaki, Tohru

    2010-12-01

    The analysis of time series obtained by functional magnetic resonance imaging (fMRI) may be approached by fitting predictive parametric models, such as nearest-neighbor autoregressive models with exogeneous input (NNARX). As a part of the modeling procedure, it is possible to apply instantaneous linear transformations to the data. Spatial smoothing, a common preprocessing step, may be interpreted as such a transformation. The autoregressive parameters may be constrained, such that they provide a response behavior that corresponds to the canonical haemodynamic response function (HRF). We present an algorithm for estimating the parameters of the linear transformations and of the HRF within a rigorous maximum-likelihood framework. Using this approach, an optimal amount of both the spatial smoothing and the HRF can be estimated simultaneously for a given fMRI data set. An example from a motor-task experiment is discussed. It is found that, for this data set, weak, but non-zero, spatial smoothing is optimal. Furthermore, it is demonstrated that activated regions can be estimated within the maximum-likelihood framework.

  14. The mean-variance relationship reveals two possible strategies for dynamic brain connectivity analysis in fMRI.

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    Thompson, William H; Fransson, Peter

    2015-01-01

    When studying brain connectivity using fMRI, signal intensity time-series are typically correlated with each other in time to compute estimates of the degree of interaction between different brain regions and/or networks. In the static connectivity case, the problem of defining which connections that should be considered significant in the analysis can be addressed in a rather straightforward manner by a statistical thresholding that is based on the magnitude of the correlation coefficients. More recently, interest has come to focus on the dynamical aspects of brain connectivity and the problem of deciding which brain connections that are to be considered relevant in the context of dynamical changes in connectivity provides further options. Since we, in the dynamical case, are interested in changes in connectivity over time, the variance of the correlation time-series becomes a relevant parameter. In this study, we discuss the relationship between the mean and variance of brain connectivity time-series and show that by studying the relation between them, two conceptually different strategies to analyze dynamic functional brain connectivity become available. Using resting-state fMRI data from a cohort of 46 subjects, we show that the mean of fMRI connectivity time-series scales negatively with its variance. This finding leads to the suggestion that magnitude- versus variance-based thresholding strategies will induce different results in studies of dynamic functional brain connectivity. Our assertion is exemplified by showing that the magnitude-based strategy is more sensitive to within-resting-state network (RSN) connectivity compared to between-RSN connectivity whereas the opposite holds true for a variance-based analysis strategy. The implications of our findings for dynamical functional brain connectivity studies are discussed.

  15. Brain Activity Associated with Emoticons: An fMRI Study

    Science.gov (United States)

    Yuasa, Masahide; Saito, Keiichi; Mukawa, Naoki

    In this paper, we describe that brain activities associated with emoticons by using fMRI. In communication over a computer network, we use abstract faces such as computer graphics (CG) avatars and emoticons. These faces convey users' emotions and enrich their communications. However, the manner in which these faces influence the mental process is as yet unknown. The human brain may perceive the abstract face in an entirely different manner, depending on its level of reality. We conducted an experiment using fMRI in order to investigate the effects of emoticons. The results show that right inferior frontal gyrus, which associated with nonverbal communication, is activated by emoticons. Since the emoticons were created to reflect the real human facial expressions as accurately as possible, we believed that they would activate the right fusiform gyrus. However, this region was not found to be activated during the experiment. This finding is useful in understanding how abstract faces affect our behaviors and decision-making in communication over a computer network.

  16. Scale-Free Brain-Wave Music from Simultaneously EEG and fMRI Recordings

    Science.gov (United States)

    Lu, Jing; Wu, Dan; Yang, Hua; Luo, Cheng; Li, Chaoyi; Yao, Dezhong

    2012-01-01

    In the past years, a few methods have been developed to translate human EEG to music. In 2009, PloS One 4 e5915, we developed a method to generate scale-free brainwave music where the amplitude of EEG was translated to music pitch according to the power law followed by both of them, the period of an EEG waveform is translated directly to the duration of a note, and the logarithm of the average power change of EEG is translated to music intensity according to the Fechner's law. In this work, we proposed to adopt simultaneously-recorded fMRI signal to control the intensity of the EEG music, thus an EEG-fMRI music is generated by combining two different and simultaneous brain signals. And most importantly, this approach further realized power law for music intensity as fMRI signal follows it. Thus the EEG-fMRI music makes a step ahead in reflecting the physiological process of the scale-free brain. PMID:23166768

  17. Scale-free brain-wave music from simultaneously EEG and fMRI recordings.

    Science.gov (United States)

    Lu, Jing; Wu, Dan; Yang, Hua; Luo, Cheng; Li, Chaoyi; Yao, Dezhong

    2012-01-01

    In the past years, a few methods have been developed to translate human EEG to music. In 2009, PloS One 4 e5915, we developed a method to generate scale-free brainwave music where the amplitude of EEG was translated to music pitch according to the power law followed by both of them, the period of an EEG waveform is translated directly to the duration of a note, and the logarithm of the average power change of EEG is translated to music intensity according to the Fechner's law. In this work, we proposed to adopt simultaneously-recorded fMRI signal to control the intensity of the EEG music, thus an EEG-fMRI music is generated by combining two different and simultaneous brain signals. And most importantly, this approach further realized power law for music intensity as fMRI signal follows it. Thus the EEG-fMRI music makes a step ahead in reflecting the physiological process of the scale-free brain.

  18. Hormone effects on fMRI and cognitive measures of encoding: importance of hormone preparation.

    Science.gov (United States)

    Gleason, C E; Schmitz, T W; Hess, T; Koscik, R L; Trivedi, M A; Ries, M L; Carlsson, C M; Sager, M A; Asthana, S; Johnson, S C

    2006-12-12

    We compared fMRI and cognitive data from nine hormone therapy (HT)-naive women with data from women exposed to either opposed conjugated equine estrogens (CEE) (n = 10) or opposed estradiol (n = 4). Exposure to either form of HT was associated with healthier fMRI response; however, CEE-exposed women exhibited poorer memory performance than either HT-naive or estradiol-exposed subjects. These preliminary findings emphasize the need to characterize differential neural effects of various HTs.

  19. Holding Biological Motion in Working Memory: An fMRI Study

    Directory of Open Access Journals (Sweden)

    Xiqian eLu

    2016-06-01

    Full Text Available Holding biological motion (BM, the movements of animate entities, in working memory (WM is important to our daily life activities. However, the neural substrates underlying the WM processing of BM remain largely unknown. Employing the functional magnetic resonance imaging (fMRI technique, the current study directly investigated this issue. We used point-light BM animations as the tested stimuli, and explored the neural substrates involved in encoding and retaining BM information in WM. Participants were required to remember two or four BM stimuli in a change-detection task. We first defined a set of potential brain regions devoted to the BM processing in WM in one experiment. We then conducted the second fMRI experiment, and performed time-course analysis over the pre-defined regions, which allowed us to differentiate the encoding and maintenance phases of WM. The results showed that a set of brain regions were involved in encoding BM into WM, including the middle frontal gyrus, inferior frontal gyrus, superior parietal lobule, inferior parietal lobule, superior temporal sulcus, fusiform gyrus, and middle occipital gyrus. However, only the middle frontal gyrus, inferior frontal gyrus, superior parietal lobule, and inferior parietal lobule were involved in retaining BM into WM. These results suggest that an overlapped network exists between the WM encoding and maintenance for BM; however, retaining BM in WM predominately relies on the mirror neuron system.

  20. Contrasting brain patterns of writing-related DTI parameters, fMRI connectivity, and DTI–fMRI connectivity correlations in children with and without dysgraphia or dyslexia

    Science.gov (United States)

    Richards, T.L.; Grabowski, T.J.; Boord, P.; Yagle, K.; Askren, M.; Mestre, Z.; Robinson, P.; Welker, O.; Gulliford, D.; Nagy, W.; Berninger, V.

    2015-01-01

    Based on comprehensive testing and educational history, children in grades 4–9 (on average 12 years) were diagnosed with dysgraphia (persisting handwriting impairment) or dyslexia (persisting word spelling/reading impairment) or as typical writers and readers (controls). The dysgraphia group (n = 14) and dyslexia group (n = 17) were each compared to the control group (n = 9) and to each other in separate analyses. Four brain region seed points (left occipital temporal gyrus, supramarginal gyrus, precuneus, and inferior frontal gyrus) were used in these analyses which were shown in a metaanalysis to be related to written word production on four indicators of white matter integrity and fMRI functional connectivity for four tasks (self-guided mind wandering during resting state, writing letter that follows a visually displayed letter in alphabet, writing missing letter to create a correctly spelled real word, and planning for composing after scanning on topic specified by researcher). For those DTI indicators on which the dysgraphic group or dyslexic group differed from the control group (fractional anisotropy, relative anisotropy, axial diffusivity but not radial diffusivity), correlations were computed between the DTI parameter and fMRI functional connectivity for the two writing tasks (alphabet and spelling) by seed points. Analyses, controlled for multiple comparisons, showed that (a) the control group exhibited more white matter integrity than either the dysgraphic or dyslexic group; (b) the dysgraphic and dyslexic groups showed more functional connectivity than the control group but differed in patterns of functional connectivity for task and seed point; and (c) the dysgraphic and dyslexic groups showed different patterns of significant DTI–fMRI connectivity correlations for specific seed points and written language tasks. Thus, dysgraphia and dyslexia differ in white matter integrity, fMRI functional connectivity, and white matter–gray matter