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Sample records for functional mri fmri

  1. fMRI Neuroinformatics

    DEFF Research Database (Denmark)

    Nielsen, Finn Årup; Christensen, Mark Schram; Madsen, Kristoffer M.

    2006-01-01

    Functional magnetic resonance imaging (fMRI) generates vast amounts of data. The handling, processing, and analysis of fMRI data would be inconceivable without computer-based methods. fMRI neuroinformatics is concerned with research, development, and operation of these methods. Reconstruction...

  2. Magnetic Resonance, Functional (fMRI) -- Brain

    Science.gov (United States)

    ... their nature and the strength of the MRI magnet. Many implanted devices will have a pamphlet explaining ... large cylinder-shaped tube surrounded by a circular magnet. You will lie on a moveable examination table ...

  3. Haptic fMRI: combining functional neuroimaging with haptics for studying the brain's motor control representation.

    Science.gov (United States)

    Menon, Samir; Brantner, Gerald; Aholt, Chris; Kay, Kendrick; Khatib, Oussama

    2013-01-01

    A challenging problem in motor control neuroimaging studies is the inability to perform complex human motor tasks given the Magnetic Resonance Imaging (MRI) scanner's disruptive magnetic fields and confined workspace. In this paper, we propose a novel experimental platform that combines Functional MRI (fMRI) neuroimaging, haptic virtual simulation environments, and an fMRI-compatible haptic device for real-time haptic interaction across the scanner workspace (above torso ∼ .65×.40×.20m(3)). We implement this Haptic fMRI platform with a novel haptic device, the Haptic fMRI Interface (HFI), and demonstrate its suitability for motor neuroimaging studies. HFI has three degrees-of-freedom (DOF), uses electromagnetic motors to enable high-fidelity haptic rendering (>350Hz), integrates radio frequency (RF) shields to prevent electromagnetic interference with fMRI (temporal SNR >100), and is kinematically designed to minimize currents induced by the MRI scanner's magnetic field during motor displacement (Tesla fMRI scanner's baseline noise variation (∼.85±.1%). Finally, HFI is haptically transparent and does not interfere with human motor tasks (tested for .4m reaches). By allowing fMRI experiments involving complex three-dimensional manipulation with haptic interaction, Haptic fMRI enables-for the first time-non-invasive neuroscience experiments involving interactive motor tasks, object manipulation, tactile perception, and visuo-motor integration.

  4. Variable Selection for Functional Logistic Regression in fMRI Data Analysis

    Directory of Open Access Journals (Sweden)

    Nedret BILLOR

    2015-03-01

    Full Text Available This study was motivated by classification problem in Functional Magnetic Resonance Imaging (fMRI, a noninvasive imaging technique which allows an experimenter to take images of a subject's brain over time. As fMRI studies usually have a small number of subjects and we assume that there is a smooth, underlying curve describing the observations in fMRI data, this results in incredibly high-dimensional datasets that are functional in nature. High dimensionality is one of the biggest problems in statistical analysis of fMRI data. There is also a need for the development of better classification methods. One of the best things about fMRI technique is its noninvasiveness. If statistical classification methods are improved, it could aid the advancement of noninvasive diagnostic techniques for mental illness or even degenerative diseases such as Alzheimer's. In this paper, we develop a variable selection technique, which tackles high dimensionality and correlation problems in fMRI data, based on L1 regularization-group lasso for the functional logistic regression model where the response is binary and represent two separate classes; the predictors are functional. We assess our method with a simulation study and an application to a real fMRI dataset.

  5. Functional connectomics from resting-state fMRI

    NARCIS (Netherlands)

    Smith, S.M.; Vidaurre, D.; Beckmann, C.F.; Jenkinson, M.; Nichols, T.E.; Robinson, E.C.; Woolrich, M.W.; Barch, D.M.

    2013-01-01

    Spontaneous fluctuations in activity in different parts of the brain can be used to study functional brain networks. We review the use of resting-state functional MRI (rfMRI) for the purpose of mapping the macroscopic functional connectome. After describing MRI acquisition and image-processing metho

  6. fMRI adaptation revisited.

    Science.gov (United States)

    Larsson, Jonas; Solomon, Samuel G; Kohn, Adam

    2016-07-01

    Adaptation has been widely used in functional magnetic imaging (fMRI) studies to infer neuronal response properties in human cortex. fMRI adaptation has been criticized because of the complex relationship between fMRI adaptation effects and the multiple neuronal effects that could underlie them. Many of the longstanding concerns about fMRI adaptation have received empirical support from neurophysiological studies over the last decade. We review these studies here, and also consider neuroimaging studies that have investigated how fMRI adaptation effects are influenced by high-level perceptual processes. The results of these studies further emphasize the need to interpret fMRI adaptation results with caution, but they also provide helpful guidance for more accurate interpretation and better experimental design. In addition, we argue that rather than being used as a proxy for measurements of neuronal stimulus selectivity, fMRI adaptation may be most useful for studying population-level adaptation effects across cortical processing hierarchies.

  7. Sparse representation of whole-brain fMRI signals for identification of functional networks.

    Science.gov (United States)

    Lv, Jinglei; Jiang, Xi; Li, Xiang; Zhu, Dajiang; Chen, Hanbo; Zhang, Tuo; Zhang, Shu; Hu, Xintao; Han, Junwei; Huang, Heng; Zhang, Jing; Guo, Lei; Liu, Tianming

    2015-02-01

    There have been several recent studies that used sparse representation for fMRI signal analysis and activation detection based on the assumption that each voxel's fMRI signal is linearly composed of sparse components. Previous studies have employed sparse coding to model functional networks in various modalities and scales. These prior contributions inspired the exploration of whether/how sparse representation can be used to identify functional networks in a voxel-wise way and on the whole brain scale. This paper presents a novel, alternative methodology of identifying multiple functional networks via sparse representation of whole-brain task-based fMRI signals. Our basic idea is that all fMRI signals within the whole brain of one subject are aggregated into a big data matrix, which is then factorized into an over-complete dictionary basis matrix and a reference weight matrix via an effective online dictionary learning algorithm. Our extensive experimental results have shown that this novel methodology can uncover multiple functional networks that can be well characterized and interpreted in spatial, temporal and frequency domains based on current brain science knowledge. Importantly, these well-characterized functional network components are quite reproducible in different brains. In general, our methods offer a novel, effective and unified solution to multiple fMRI data analysis tasks including activation detection, de-activation detection, and functional network identification. Copyright © 2014 Elsevier B.V. All rights reserved.

  8. 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

  9. 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.

  10. [fMRI functional connectivity analysis of anxiety disease patients based on spatiotemporal Lyapunov exponent method].

    Science.gov (United States)

    Wang, Zhikang; Lou, Haifang; Sun, Jianzhong

    2011-07-01

    Attempting to use nonlinear spatiotemporal Lyapunov exponent to characterize fMRI brain functional connectivity of anxiety disease patients, we adopted the methods of nonlinear spatiotemporal Lyapunov exponent and linear correlation coefficients to analyses fMRI datum of 11 anxiety disease patients and 11 healthy volunteers, respectively. The results show that there are significant normalized variance exponent (NVE) differences in Inferior Frontal Gyrus (rIFG) and Medial Frontal Gyrus (MFG) between the two groups (PLyapunov exponent method had higher sensitivity than the correlation coefficient method in the characterization of functional connectivity; Anxiety disease patients have abnormal functional connectivity in rIFG and MFG during our experiment.

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

    Directory of Open Access Journals (Sweden)

    Mara Fabri

    2013-01-01

    Full Text Available 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 motor tasks. We reviewed our published and unpublished fMRI and diffusion tensor imaging data on the cortical representation of tactile, gustatory, auditory, and visual sensitivity and of motor activation, obtained in 36 normal volunteers and in 6 patients with partial callosotomy. Activation foci were consistently detected in discrete CC regions: anterior (taste stimuli, central (motor tasks, central and posterior (tactile stimuli, and splenium (auditory and visual stimuli. Reconstruction of callosal fibers connecting activated primary gustatory, motor, somatosensory, auditory, and visual cortices by diffusion tensor tracking showed bundles crossing, respectively, through the genu, anterior and posterior body, and splenium, at sites harboring fMRI foci. These data confirm that the CC commissure has a topographical organization and demonstrate that its functional topography can be explored with fMRI.

  12. Select and Cluster: A Method for Finding Functional Networks of Clustered Voxels in fMRI

    Science.gov (United States)

    DonGiovanni, Danilo

    2016-01-01

    Extracting functional connectivity patterns among cortical regions in fMRI datasets is a challenge stimulating the development of effective data-driven or model based techniques. Here, we present a novel data-driven method for the extraction of significantly connected functional ROIs directly from the preprocessed fMRI data without relying on a priori knowledge of the expected activations. This method finds spatially compact groups of voxels which show a homogeneous pattern of significant connectivity with other regions in the brain. The method, called Select and Cluster (S&C), consists of two steps: first, a dimensionality reduction step based on a blind multiresolution pairwise correlation by which the subset of all cortical voxels with significant mutual correlation is selected and the second step in which the selected voxels are grouped into spatially compact and functionally homogeneous ROIs by means of a Support Vector Clustering (SVC) algorithm. The S&C method is described in detail. Its performance assessed on simulated and experimental fMRI data is compared to other methods commonly used in functional connectivity analyses, such as Independent Component Analysis (ICA) or clustering. S&C method simplifies the extraction of functional networks in fMRI by identifying automatically spatially compact groups of voxels (ROIs) involved in whole brain scale activation networks. PMID:27656202

  13. Bayesian Inference for Functional Dynamics Exploring in fMRI Data.

    Science.gov (United States)

    Guo, Xuan; Liu, Bing; Chen, Le; Chen, Guantao; Pan, Yi; Zhang, Jing

    2016-01-01

    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.

  14. 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.

  15. Functional correlates of cognitive dysfunction in multiple sclerosis: A multicenter fMRI Study.

    Science.gov (United States)

    Rocca, Maria A; Valsasina, Paola; Hulst, Hanneke E; Abdel-Aziz, Khaled; Enzinger, Christian; Gallo, Antonio; Pareto, Debora; Riccitelli, Gianna; Muhlert, Nils; Ciccarelli, Olga; Barkhof, Frederik; Fazekas, Franz; Tedeschi, Gioacchino; Arévalo, Maria J; Filippi, Massimo

    2014-12-01

    In this multicenter study, we applied functional magnetic resonance imaging (fMRI) to define the functional correlates of cognitive dysfunction in patients with multiple sclerosis (MS). fMRI scans during the performance of the N-back task were acquired from 42 right-handed relapsing remitting (RR) MS patients and 52 sex-matched right-handed healthy controls, studied at six European sites using 3.0 Tesla scanners. Patients with at least two abnormal (<2 standard deviations from the normative values) neuropsychological tests at a standardized evaluation were considered cognitively impaired (CI). FMRI data were analyzed using the SPM8 software, modeling regions showing load-dependent activations/deactivations with increasing task difficulty. Twenty (47%) MS patients were CI. During the N-back load condition, compared to controls and CI patients, cognitively preserved (CP) patients had increased recruitment of the right dorsolateral prefrontal cortex. As a function of increasing task difficulty, CI MS patients had reduced activations of several areas located in the fronto-parieto-temporal lobes as well as reduced deactivations of regions which are part of the default mode network compared to the other two groups. Significant correlations were found between abnormal fMRI patterns of activations and deactivations and behavioral measures, cognitive performance, and brain T2 and T1 lesion volumes. This multicenter study supports the theory that a preserved fMRI activity of the frontal lobe is associated with a better cognitive profile in MS patients. It also indicates the feasibility of fMRI to monitor disease evolution and treatment effects in future studies.

  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. Enhanced Thalamic Functional Connectivity with No fMRI Responses to Affected Forelimb Stimulation in Stroke-Recovered Rats

    Science.gov (United States)

    Shim, Woo H.; Suh, Ji-Yeon; Kim, Jeong K.; Jeong, Jaeseung; Kim, Young R.

    2017-01-01

    Neurological recovery after stroke has been extensively investigated to provide better understanding of neurobiological mechanism, therapy, and patient management. Recent advances in neuroimaging techniques, particularly functional MRI (fMRI), have widely contributed to unravel the relationship between the altered neural function and stroke-affected brain areas. As results of previous investigations, the plastic reorganization and/or gradual restoration of the hemodynamic fMRI responses to neural stimuli have been suggested as relevant mechanisms underlying the stroke recovery process. However, divergent study results and modality-dependent outcomes have clouded the proper interpretation of variable fMRI signals. Here, we performed both evoked and resting state fMRI (rs-fMRI) to clarify the link between the fMRI phenotypes and post-stroke functional recovery. The experiments were designed to examine the altered neural activity within the contra-lesional hemisphere and other undamaged brain regions using rat models with large unilateral stroke, which despite the severe injury, exhibited nearly full recovery at ∼6 months after stroke. Surprisingly, both blood oxygenation level-dependent and blood volume-weighted (CBVw) fMRI activities elicited by electrical stimulation of the stroke-affected forelimb were completely absent, failing to reveal the neural origin of the behavioral recovery. In contrast, the functional connectivity maps showed highly robust rs-fMRI activity concentrated in the contra-lesional ventromedial nucleus of thalamus (VM). The negative finding in the stimuli-induced fMRI study using the popular rat middle cerebral artery model denotes weak association between the fMRI hemodynamic responses and neurological improvement. The results strongly caution the indiscreet interpretation of stroke-affected fMRI signals and demonstrate rs-fMRI as a complementary tool for efficiently characterizing stroke recovery. PMID:28119575

  18. Subject specific BOLD fMRI respiratory and cardiac response functions obtained from global signal.

    Science.gov (United States)

    Falahpour, Maryam; Refai, Hazem; Bodurka, Jerzy

    2013-05-15

    Subtle changes in either breathing pattern or cardiac pulse rate alter blood oxygen level dependent functional magnetic resonance imaging signal (BOLD fMRI). This is problematic because such fluctuations could possibly not be related to underlying neuronal activations of interest but instead the source of physiological noise. Several methods have been proposed to eliminate physiological noise in BOLD fMRI data. One such method is to derive a template based on average multi-subject data for respiratory response function (RRF) and cardiac response function (CRF) by simultaneously utilizing an external recording of cardiac and respiratory waveforms with the fMRI. Standard templates can then be used to model, map, and remove respiration and cardiac fluctuations from fMRI data. Utilizing these does not, however, account for intra-subject variations in physiological response. Thus, performing a more individualized approach for single subject physiological noise correction becomes more desirable, especially for clinical purposes. Here we propose a novel approach that employs subject-specific RRF and CRF response functions obtained from the whole brain or brain tissue-specific global signals (GS). Averaging multiple voxels in global signal computation ensures physiological noise dominance over thermal and system noise in even high-spatial-resolution fMRI data, making the GS suitable for deriving robust estimations of both RRF and CRF for individual subjects. Using these individualized response functions instead of standard templates based on multi-subject averages judiciously removes physiological noise from the data, assuming that there is minimal neuronal contribution in the derived individualized filters. Subject-specific physiological response functions obtained from the GS better maps individuals' physiological characteristics.

  19. Enhanced Thalamic Functional Connectivity with No fMRI Responses to Affected Forelimb Stimulation in Stroke-Recovered Rats

    OpenAIRE

    Shim, Woo H.; Suh, Ji-Yeon; Kim, Jeong K.; Jeong, Jaeseung; Kim, Young R.

    2017-01-01

    Neurological recovery after stroke has been extensively investigated to provide better understanding of neurobiological mechanism, therapy, and patient management. Recent advances in neuroimaging techniques, particularly functional MRI (fMRI), have widely contributed to unravel the relationship between the altered neural function and stroke-affected brain areas. As results of previous investigations, the plastic reorganization and/or gradual restoration of the hemodynamic fMRI responses to ne...

  20. Assessing hippocampal functional reserve in temporal lobe epilepsy: A multi-voxel pattern analysis of fMRI data

    OpenAIRE

    Bonnici, Heidi M; Sidhu, Meneka; Chadwick, Martin J.; Duncan, John S.; Maguire, Eleanor A.

    2013-01-01

    Summary Assessing the functional reserve of key memory structures in the medial temporal lobes (MTL) of pre-surgical patients with intractable temporal lobe epilepsy (TLE) remains a challenge. Conventional functional MRI (fMRI) memory paradigms have yet to fully convince of their ability to confidently assess the risk of a post-surgical amnesia. An alternative fMRI analysis method, multi-voxel pattern analysis (MVPA), focuses on the patterns of activity across voxels in specific brain regions...

  1. Functional Imaging of Broca’s Area in Native Persian Speakers: An fMRI Study

    Directory of Open Access Journals (Sweden)

    A Mahdavi

    2008-12-01

    Full Text Available Background/Objective: The problem of localization of speech associated cortices using noninvasive methods has been of utmost importance in many neuroimaging studies, but the results are difficult to resolve for specific neurosurgical applications. In this study, we used fMRI to delineate language-related brain activation patterns with emphasis on the Broca's area during the execution of two Persian language tasks."nPatients and Methods: The subjects comprised of nine healthy right-handed men who participated voluntarily in this study. They performed two consequent fMRI paradigms namely; "Word Production" and "Reverse Word Reading". The fMRI data were collected and analyzed. Then, functional images were registered to anatomical images using FSL software. The laterality indices were also calculated in regions of interest with different threshold levels."nResults: The results indicate that Broca's area, as the classical language-production center, was robustly activated while performing these two tasks. In eight out of nine subjects, the left hemisphere dominancy and Broca's area activation were observed and in one case activation was prominent in the homologous area in the right hemisphere."nConclusion: Similar pattern of cortical activation during Persian word production and Anglophone languages such as English was revealed. fMRI is a valuable means for brain mapping in language studies.

  2. 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

    motor as well as higher cognitive functions (i.e. language). Pre-operative fMRI can be used to identify the brain regions that are activated during specific sensorimotor or language tasks. TMS is able to disrupt neuronal processing in the targeted brain area which in turn may affect task performance......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......MRI is well established although the number of studies on presurgical language fMRI is still limited. In contrast, the reliability and accuracy of preoperative TMS remains to be determined....

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

    Energy Technology Data Exchange (ETDEWEB)

    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.)

  4. 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.

  5. The impact of "physiological correction" on functional connectivity analysis of pharmacological resting state fMRI

    NARCIS (Netherlands)

    Khalili-Mahani, N.; Chang, C.; Osch, M.J.; Veer, I.M.; Buchem, van M.A.; Dahan, A.; Beckmann, C.F.

    2013-01-01

    Growing interest in pharmacological resting state fMRI (RSfMRI) necessitates developing standardized and robust analytical approaches that are insensitive to spurious correlated physiological signals. However, in pharmacological experiments physiological variations constitute an important aspect of

  6. 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.)

  7. Interplay between functional connectivity and scale-free dynamics in intrinsic fMRI networks.

    Science.gov (United States)

    Ciuciu, Philippe; Abry, Patrice; He, Biyu J

    2014-07-15

    Studies employing functional connectivity-type analyses have established that spontaneous fluctuations in functional magnetic resonance imaging (fMRI) signals are organized within large-scale brain networks. Meanwhile, fMRI signals have been shown to exhibit 1/f-type power spectra - a hallmark of scale-free dynamics. We studied the interplay between functional connectivity and scale-free dynamics in fMRI signals, utilizing the fractal connectivity framework - a multivariate extension of the univariate fractional Gaussian noise model, which relies on a wavelet formulation for robust parameter estimation. We applied this framework to fMRI data acquired from healthy young adults at rest and while performing a visual detection task. First, we found that scale-invariance existed beyond univariate dynamics, being present also in bivariate cross-temporal dynamics. Second, we observed that frequencies within the scale-free range do not contribute evenly to inter-regional connectivity, with a systematically stronger contribution of the lowest frequencies, both at rest and during task. Third, in addition to a decrease of the Hurst exponent and inter-regional correlations, task performance modified cross-temporal dynamics, inducing a larger contribution of the highest frequencies within the scale-free range to global correlation. Lastly, we found that across individuals, a weaker task modulation of the frequency contribution to inter-regional connectivity was associated with better task performance manifesting as shorter and less variable reaction times. These findings bring together two related fields that have hitherto been studied separately - resting-state networks and scale-free dynamics, and show that scale-free dynamics of human brain activity manifest in cross-regional interactions as well.

  8. Neural correlate of vernier acuity tasks assessed by functional MRI (FMRI).

    Science.gov (United States)

    Sheth, Kevin N; Walker, B Michael; Modestino, Edward J; Miki, Atsushi; Terhune, Kyla P; Francis, Ellie L; Haselgrove, John C; Liu, Grant T

    2007-01-01

    Vernier acuity refers to the ability to discern a small offset within a line. However, while Vernier acuity has been extensively studied psychophysically, its neural correlates are uncertain. Based upon previous psychophysical and electrophysiologic data, we hypothesized that extrastriate areas of the brain would be involved in Vernier acuity tasks, so we designed event-related functional MRI (fMRI) paradigms to identify cortical regions of the brain involved in this behavior. Normal subjects identified suprathreshold and subthreshold Vernier offsets. The results suggest a cortical network including frontal, parietal, occipital, and cerebellar regions subserves the observation, processing, interpretation, and acknowledgment of briefly presented Vernier offsets.

  9. Chronotype Modulates Language Processing-Related Cerebral Activity during Functional MRI (fMRI.

    Directory of Open Access Journals (Sweden)

    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. Time Slice Analysis Method Based on OTCA Used in fMRI Weak Signal Function Extraction

    Institute of Scientific and Technical Information of China (English)

    LUO Sen-lin; LI Li; ZHANG Xin-li; ZHANG Tie-mei

    2007-01-01

    The original temporal clustering analysis (OTCA) is an effective technique for obtaining brain activation maps when the timing and location of the activation are completely unknown, but its deficiency of sensitivity is exposed in processing brain activation signal which is relatively weak. The time slice analysis method based on OTCA is proposed considering the weakness of the functional magnetic resonance imaging (fMRI) signal of the rat model. By dividing the stimulation period into several time slices and analyzing each slice to detect the activated pixels respectively after the background removal, the sensitivity is significantly improved. The inhibitory response in the hypothalamus after glucose loading is detected successfully with this method in the experiment on rat. Combined with the OTCA method, the time slice analysis method based on OTCA is effective on detecting when, where and which type of response will happen after stimulation, even if the fMRI signal is weak.

  11. 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.

  12. A robust independent component analysis (ICA) model for functional magnetic resonance imaging (fMRI) data

    Science.gov (United States)

    Ao, Jingqi; Mitra, Sunanda; Liu, Zheng; Nutter, Brian

    2011-03-01

    The coupling of carefully designed experiments with proper analysis of functional magnetic resonance imaging (fMRI) data provides us with a powerful as well as noninvasive tool to help us understand cognitive processes associated with specific brain regions and hence could be used to detect abnormalities induced by a diseased state. The hypothesisdriven General Linear Model (GLM) and the data-driven Independent Component Analysis (ICA) model are the two most commonly used models for fMRI data analysis. A hybrid ICA-GLM model combines the two models to take advantages of benefits from both models to achieve more accurate mapping of the stimulus-induced activated brain regions. We propose a modified hybrid ICA-GLM model with probabilistic ICA that includes a noise model. In this modified hybrid model, a probabilistic principle component analysis (PPCA)-based component number estimation is used in the ICA stage to extract the intrinsic number of original time courses. In addition, frequency matching is introduced into the time course selection stage, along with temporal correlation, F-test based model fitting estimation, and time course combination, to produce a more accurate design matrix for GLM. A standard fMRI dataset is used to compare the results of applying GLM and the proposed hybrid ICA-GLM in generating activation maps.

  13. 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

    2017-03-03

    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

  14. Fusing Simultaneous EEG and fMRI Using Functional and Anatomical Information

    DEFF Research Database (Denmark)

    Hansen, Sofie Therese; Winkler, Irene; Hansen, Lars Kai;

    2015-01-01

    SPoC), to not only use functional but also anatomical information. The goal is to extract correlated source components from electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). Anatomical information enters our proposed extension to mSPoC via the forward model, which relates the activity...... on cortex level to the EEG sensors. The augmented mSPoC is shown to outperform the original version in realistic simulations where the signal to noise ratio is low or where training epochs are scarce....

  15. 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.

  16. 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.

  17. Vicarious function within the human primary motor cortex? A longitudinal fMRI stroke study

    National Research Council Canada - National Science Library

    Jaillard, Assia; Martin, Chantal Delon; Garambois, Katia; Lebas, Jean François; Hommel, Marc

    2005-01-01

    .... We examined four patients with one ischaemic stroke limited to M1, and four sex- and age-matched healthy controls in a temporally balanced prospective longitudinal fMRI study over three sessions...

  18. 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.)

  19. 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.

  20. 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

    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......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...

  1. Cerebral reorganization as a function of linguistic recovery in children: An fMRI study.

    Science.gov (United States)

    Elkana, Odelia; Frost, Ram; Kramer, Uri; Ben-Bashat, Dafna; Hendler, Talma; Schmidt, David; Schweiger, Avraham

    2011-02-01

    Characterizing and mapping the relationship between neuronal reorganization and functional recovery are essential to the understanding of cerebral plasticity and the dynamic processes which occur following brain damage. The neuronal mechanisms underlying linguistic recovery following left hemisphere (LH) lesions are still unknown. Using functional magnetic resonance imaging (fMRI), we investigated whether the extent of brain lateralization of linguistic functioning in specific regions of interest (ROIs) is correlated with the level of linguistic performance following recovery from acquired childhood aphasia. The study focused on a rare group of children in whom lesions occurred after normal language acquisition, but prior to complete maturation of the brain. During fMRI scanning, rhyming, comprehension and verb generation activation tasks were monitored. The imaging data were evaluated with reference to linguistic performance measured behaviorally during imaging, as well as outside the scanner. Compared with normal controls, we found greater right hemisphere (RH) lateralization in patients. However, correlations with linguistic performance showed that increased proficiency in linguistic tasks was associated with greater lateralization to the LH. These results were replicated in a longitudinal case study of a patient scanned twice, 3 years apart. Additional improvement in linguistic performance of the patient was accompanied by increasing lateralization to the LH in the anterior language region. This, however, was the result of a decreased involvement of the RH. These findings suggest that recovery is a dynamic, ongoing process, which may last for years after onset. The role of each hemisphere in the recovery process may continuously change within the chronic stage.

  2. Exploring the brain network: a review on resting-state fMRI functional connectivity.

    Science.gov (United States)

    van den Heuvel, Martijn P; Hulshoff Pol, Hilleke E

    2010-08-01

    Our brain is a network. It consists of spatially distributed, but functionally linked regions that continuously share information with each other. Interestingly, recent advances in the acquisition and analysis of functional neuroimaging data have catalyzed the exploration of functional connectivity in the human brain. Functional connectivity is defined as the temporal dependency of neuronal activation patterns of anatomically separated brain regions and in the past years an increasing body of neuroimaging studies has started to explore functional connectivity by measuring the level of co-activation of resting-state fMRI time-series between brain regions. These studies have revealed interesting new findings about the functional connections of specific brain regions and local networks, as well as important new insights in the overall organization of functional communication in the brain network. Here we present an overview of these new methods and discuss how they have led to new insights in core aspects of the human brain, providing an overview of these novel imaging techniques and their implication to neuroscience. We discuss the use of spontaneous resting-state fMRI in determining functional connectivity, discuss suggested origins of these signals, how functional connections tend to be related to structural connections in the brain network and how functional brain communication may form a key role in cognitive performance. Furthermore, we will discuss the upcoming field of examining functional connectivity patterns using graph theory, focusing on the overall organization of the functional brain network. Specifically, we will discuss the value of these new functional connectivity tools in examining believed connectivity diseases, like Alzheimer's disease, dementia, schizophrenia and multiple sclerosis. Copyright 2010 Elsevier B.V. All rights reserved.

  3. 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.

  4. Detecting functional connectivity change points for single-subject fMRI data.

    Science.gov (United States)

    Cribben, Ivor; Wager, Tor D; Lindquist, Martin A

    2013-01-01

    Recently in functional magnetic resonance imaging (fMRI) studies there has been an increased interest in understanding the dynamic manner in which brain regions communicate with one another, as subjects perform a set of experimental tasks or as their psychological state changes. Dynamic Connectivity Regression (DCR) is a data-driven technique used for detecting temporal change points in functional connectivity between brain regions where the number and location of the change points are unknown a priori. After finding the change points, DCR estimates a graph or set of relationships between the brain regions for data that falls between pairs of change points. In previous work, the method was predominantly validated using multi-subject data. In this paper, we concentrate on single-subject data and introduce a new DCR algorithm. The new algorithm increases accuracy for individual subject data with a small number of observations and reduces the number of false positives in the estimated undirected graphs. We also introduce a new Likelihood Ratio test for comparing sparse graphs across (or within) subjects; thus allowing us to determine whether data should be combined across subjects. We perform an extensive simulation analysis on vector autoregression (VAR) data as well as to an fMRI data set from a study (n = 23) of a state anxiety induction using a socially evaluative threat challenge. The focus on single-subject data allows us to study the variation between individuals and may provide us with a deeper knowledge of the workings of the brain.

  5. The Brain Functional State of Music Creation: an fMRI Study of Composers.

    Science.gov (United States)

    Lu, Jing; Yang, Hua; Zhang, Xingxing; He, Hui; Luo, Cheng; Yao, Dezhong

    2015-07-23

    In this study, we used functional magnetic resonance imaging (fMRI) to explore the functional networks in professional composers during the creation of music. We compared the composing state and resting state imagery of 17 composers and found that the functional connectivity of primary networks in the bilateral occipital lobe and bilateral postcentral cortex decreased during the composing period. However, significantly stronger functional connectivity appeared between the anterior cingulate cortex (ACC), the right angular gyrus and the bilateral superior frontal gyrus during composition. These findings indicate that a specific brain state of musical creation is formed when professional composers are composing, in which the integration of the primary visual and motor areas is not necessary. Instead, the neurons of these areas are recruited to enhance the functional connectivity between the ACC and the default mode network (DMN) to plan the integration of musical notes with emotion.

  6. Fusing Simultaneous EEG and fMRI Using Functional and Anatomical Information

    DEFF Research Database (Denmark)

    Hansen, Sofie Therese; Winkler, Irene; Hansen, Lars Kai

    2015-01-01

    Simultaneously measuring electro physical and hemodynamic signals has become more accessible in the last years and the need for modeling techniques that can fuse the modalities is growing. In this work we augment a specific fusion method, the multimodal Source Power Co-modulation (m......SPoC), to not only use functional but also anatomical information. The goal is to extract correlated source components from electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). Anatomical information enters our proposed extension to mSPoC via the forward model, which relates the activity...... on cortex level to the EEG sensors. The augmented mSPoC is shown to outperform the original version in realistic simulations where the signal to noise ratio is low or where training epochs are scarce....

  7. Interpreting the effects of altered brain anatomical connectivity on fMRI functional connectivity: a role for computational neural modeling.

    Science.gov (United States)

    Horwitz, Barry; Hwang, Chuhern; Alstott, Jeff

    2013-01-01

    Recently, there have been a large number of studies using resting state fMRI to characterize abnormal brain connectivity in patients with a variety of neurological, psychiatric, and developmental disorders. However, interpreting what the differences in resting state fMRI functional connectivity (rsfMRI-FC) actually reflect in terms of the underlying neural pathology has proved to be elusive because of the complexity of brain anatomical connectivity. The same is the case for task-based fMRI studies. In the last few years, several groups have used large-scale neural modeling to help provide some insight into the relationship between brain anatomical connectivity and the corresponding patterns of fMRI-FC. In this paper we review several efforts at using large-scale neural modeling to investigate the relationship between structural connectivity and functional/effective connectivity to determine how alterations in structural connectivity are manifested in altered patterns of functional/effective connectivity. Because the alterations made in the anatomical connectivity between specific brain regions in the model are known in detail, one can use the results of these simulations to determine the corresponding alterations in rsfMRI-FC. Many of these simulation studies found that structural connectivity changes do not necessarily result in matching changes in functional/effective connectivity in the areas of structural modification. Often, it was observed that increases in functional/effective connectivity in the altered brain did not necessarily correspond to increases in the strength of the anatomical connection weights. Note that increases in rsfMRI-FC in patients have been interpreted in some cases as resulting from neural plasticity. These results suggest that this interpretation can be mistaken. The relevance of these simulation findings to the use of functional/effective fMRI connectivity as biomarkers for brain disorders is also discussed.

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

    Directory of Open Access Journals (Sweden)

    Benjamin Clemens

    Full Text Available 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

  9. Altered Functional Connectivity in Essential Tremor: A Resting-State fMRI Study.

    Science.gov (United States)

    Benito-León, Julián; Louis, Elan D; Romero, Juan Pablo; Hernández-Tamames, Juan Antonio; Manzanedo, Eva; Álvarez-Linera, Juan; Bermejo-Pareja, Félix; Posada, Ignacio; Rocon, Eduardo

    2015-12-01

    Essential tremor (ET) has been associated with a spectrum of clinical features, with both motor and nonmotor elements, including cognitive deficits. We employed resting-state functional magnetic resonance imaging (fMRI) to assess whether brain networks that might be involved in the pathogenesis of nonmotor manifestations associated with ET are altered, and the relationship between abnormal connectivity and ET severity and neuropsychological function.Resting-state fMRI data in 23 ET patients (12 women and 11 men) and 22 healthy controls (HC) (12 women and 10 men) were analyzed using independent component analysis, in combination with a "dual-regression" technique, to identify the group differences of resting-state networks (RSNs) (default mode network [DMN] and executive, frontoparietal, sensorimotor, cerebellar, auditory/language, and visual networks). All participants underwent a neuropsychological and neuroimaging session, where resting-state data were collected.Relative to HC, ET patients showed increased connectivity in RSNs involved in cognitive processes (DMN and frontoparietal networks) and decreased connectivity in the cerebellum and visual networks. Changes in network integrity were associated not only with ET severity (DMN) and ET duration (DMN and left frontoparietal network), but also with cognitive ability. Moreover, in at least 3 networks (DMN and frontoparietal networks), increased connectivity was associated with worse performance on different cognitive domains (attention, executive function, visuospatial ability, verbal memory, visual memory, and language) and depressive symptoms. Further, in the visual network, decreased connectivity was associated with worse performance on visuospatial ability.ET was associated with abnormal brain connectivity in major RSNs that might be involved in both motor and nonmotor symptoms. Our findings underscore the importance of examining RSNs in this population as a biomarker of disease.

  10. 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

  11. fMRI Study Revealing Neural Mechanisms of the Functions of SOA in Spatial Orienting

    Institute of Scientific and Technical Information of China (English)

    Yin Tian; Qian Zhang; De-Zhong Yao

    2009-01-01

    It is well documented that orienting attention plays an important role in visual search. However, it remains unclear how the executive brain regions will act when two different stimulus onset asynchrony (SOA) are used in visual search. In this work, event-related fMRI was used to investigate neural mechanisms on the functions of SOA in endogenous and exogenous orienting. The results showed that in the endogenous orienting, long SOA versus short SOA resulted in widespread cortical activation mainly including right medial frontal gyrus and bilateral middle frontal gyri. Conversely, in exogenous orienting, long SOA compared to short SOA resulted in only activations in bilateral middle frontal gyri. These findings indicated that these two spatial orienting involved different brain areas and neural mechanisms.

  12. Detecting functional connectivity change points for single-subject fMRI data

    Directory of Open Access Journals (Sweden)

    Ivor eCribben

    2013-10-01

    Full Text Available Recently in functional magnetic resonance imaging (fMRI studies there has been an increased interest in understanding the dynamic manner in which brain regions communicate with one another, as subjects perform a set of experimental tasks or as their psychological state changes. Dynamic Connectivity Regression (DCR is a data-driven technique used for detecting temporal change points in functional connectivity between brain regions where the number and location of the change points are unknown a priori. After finding the change points, DCR estimates a graph or set of relationships between the brain regions for data that falls between pairs of change points. In previous work, the method was predominantly validated using multi-subject data. In this paper, we concentrate on single-subject data and introduce a new DCR algorithm. The new algorithm increases accuracy for individual subject data with a small number of observations and reduces the number of false positives in the estimated undirected graphs. We also introduce a new Likelihood Ratio test for comparing sparse graphs across (or within subjects; thus allowing us to determine whether data should be combined across subjects. We perform an extensive simulation analysis on vector autoregression (VAR data as well as to an fMRI data set from a study (n=23 of a state anxiety induction using a socially evaluative threat challenge. The focus on single-subject data allows us to study the variation between individuals and may provide us with a deeper knowledge of the workings of the brain.

  13. 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.)

  14. Combining fMRI and SNP Data to Investigate Connections Between Brain Function and Genetics Using Parallel ICA

    Science.gov (United States)

    Liu, Jingyu; Pearlson, Godfrey; Windemuth, Andreas; Ruano, Gualberto; Perrone-Bizzozero, Nora I.; Calhoun, Vince

    2009-01-01

    There is current interest in understanding genetic influences on both healthy and disordered brain function. We assessed brain function with functional magnetic resonance imaging (fMRI) data collected during an auditory oddball task—detecting an infrequent sound within a series of frequent sounds. Then, task-related imaging findings were utilized as potential intermediate phenotypes (endophenotypes) to investigate genomic factors derived from a single nucleotide polymorphism (SNP) array. Our target is the linkage of these genomic factors to normal/abnormal brain functionality. We explored parallel independent component analysis (paraICA) as a new method for analyzing multimodal data. The method was aimed to identify simultaneously independent components of each modality and the relationships between them. When 43 healthy controls and 20 schizophrenia patients, all Caucasian, were studied, we found a correlation of 0.38 between one fMRI component and one SNP component. This fMRI component consisted mainly of parietal lobe activations. The relevant SNP component was contributed to significantly by 10 SNPs located in genes, including those coding for the nicotinic α-7cholinergic receptor, aromatic amino acid decarboxylase, disrupted in schizophrenia 1, among others. Both fMRI and SNP components showed significant differences in loading parameters between the schizophrenia and control groups (P = 0.0006 for the fMRI component; P = 0.001 for the SNP component). In summary, we constructed a framework to identify interactions between brain functional and genetic information; our findings provide a proof-of-concept that genomic SNP factors can be investigated by using endophenotypic imaging findings in a multivariate format. PMID:18072279

  15. The Integration of Prosodic Speech in High Functioning Autism: A Preliminary fMRI Study

    Science.gov (United States)

    Hesling, Isabelle; Dilharreguy, Bixente; Peppé, Sue; Amirault, Marion; Bouvard, Manuel; Allard, Michèle

    2010-01-01

    Background Autism is a neurodevelopmental disorder characterized by a specific triad of symptoms such as abnormalities in social interaction, abnormalities in communication and restricted activities and interests. While verbal autistic subjects may present a correct mastery of the formal aspects of speech, they have difficulties in prosody (music of speech), leading to communication disorders. Few behavioural studies have revealed a prosodic impairment in children with autism, and among the few fMRI studies aiming at assessing the neural network involved in language, none has specifically studied prosodic speech. The aim of the present study was to characterize specific prosodic components such as linguistic prosody (intonation, rhythm and emphasis) and emotional prosody and to correlate them with the neural network underlying them. Methodology/Principal Findings We used a behavioural test (Profiling Elements of the Prosodic System, PEPS) and fMRI to characterize prosodic deficits and investigate the neural network underlying prosodic processing. Results revealed the existence of a link between perceptive and productive prosodic deficits for some prosodic components (rhythm, emphasis and affect) in HFA and also revealed that the neural network involved in prosodic speech perception exhibits abnormal activation in the left SMG as compared to controls (activation positively correlated with intonation and emphasis) and an absence of deactivation patterns in regions involved in the default mode. Conclusions/Significance These prosodic impairments could not only result from activation patterns abnormalities but also from an inability to adequately use the strategy of the default network inhibition, both mechanisms that have to be considered for decreasing task performance in High Functioning Autism. PMID:20644633

  16. 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

  17. 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.

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

    Indian Academy of Sciences (India)

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

    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 high-resolution 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) ( < 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.

  20. fMRI as a molecular imaging procedure for the functional reorganization of motor systems in chronic stroke

    OpenAIRE

    Lazaridou, Asimina; ASTRAKAS, LOUKAS; Mintzopoulos, Dionyssios; KHANCHICEH, AZADEH; Singhal, Aneesh; Moskowitz, Michael; Rosen, Bruce; Tzika, Aria

    2013-01-01

    Previous brain imaging studies suggest that stroke alters functional connectivity in motor execution networks. Moreover, current understanding of brain plasticity has led to new approaches in stroke rehabilitation. Recent studies showed a significant role of effective coupling of neuronal activity in the SMA (supplementary motor area) and M1 (primary motor cortex) network for motor outcome in patients after stroke. After a subcortical stroke, functional magnetic resonance imaging (fMRI) durin...

  1. Prediction of fMRI time series of a single voxel using radial basis function neural network

    Science.gov (United States)

    Song, Sutao; Zhang, Jiacai; Yao, Li

    2011-03-01

    A great deal of current literature regarding functional neuroimaging has elucidated the relationships of neurons distributed all over the brain. Modern neuroimaging techniques, such as the functional MRI (fMRI), provide a convenient tool for people to study the correlation among different voxels as well as the spatio-temporal patterns of brain activity. In this study, we present a computational model using radial basis function neural network (RBF-NN) to predict the fMRI voxel activation with the activation of other voxels acquired at the same time. The fMRI data from a visual images stimuli presentation experiment was separated into two sets; one was used to train the model, and the other to validate the accuracy or generalizability of the model. In the visual stimuli presentation experiment, the subject did simple one-back-repetition tasks when four categories of stimuli (houses, faces, cars, and cats) were presented. Voxel sets A and B were selected from fMRI data by two different voxel selection criterion: (1) Voxel set A are those activated for any kind of object stronger than the other three objects in regions of interest (ROIs) without correction (P=0.001); (2) Voxel set B are those activated for at least one of the categories of stimuli within the ROIs (FWE correction, P=0.05). RBF-NN regression models construct the nonlinear relationship between the activation of voxels in A and B. Our test results showed that RBF-NN can capture the nonlinear relationship existing in neurons and reveal the relationship between voxel's activation from different brain regions.

  2. Neural correlates of consciousness during general anesthesia using functional magnetic resonance imaging (fMRI).

    Science.gov (United States)

    Bonhomme, V; Boveroux, P; Brichant, J F; Laureys, S; Boly, M

    2012-01-01

    This paper reviews the current knowledge about the mechanisms of anesthesia-induced alteration of consciousness. It is now evident that hypnotic anesthetic agents have specific brain targets whose function is hierarchically altered in a dose-dependent manner. Higher order networks, thought to be involved in mental content generation, as well as sub-cortical networks involved in thalamic activity regulation seems to be affected first by increasing concentrations of hypnotic agents that enhance inhibitory neurotransmission. Lower order sensory networks are preserved, including thalamo-cortical connectivity into those networks, even at concentrations that suppress responsiveness, but cross-modal sensory interactions are inhibited. Thalamo-cortical connectivity into the consciousness networks decreases with increasing concentrations of those agents, and is transformed into an anti-correlated activity between the thalamus and the cortex for the deepest levels of sedation, when the subject is non responsive. Future will tell us whether these brain function alterations are also observed with hypnotic agents that mainly inhibit excitatory neurotransmission. The link between the observations made using fMRI and the identified biochemical targets of hypnotic anesthetic agents still remains to be identified.

  3. A method for using blocked and event-related fMRI data to study "resting state" functional connectivity.

    Science.gov (United States)

    Fair, Damien A; Schlaggar, Bradley L; Cohen, Alexander L; Miezin, Francis M; Dosenbach, Nico U F; Wenger, Kristin K; Fox, Michael D; Snyder, Abraham Z; Raichle, Marcus E; Petersen, Steven E

    2007-03-01

    Resting state functional connectivity MRI (fcMRI) has become a particularly useful tool for studying regional relationships in typical and atypical populations. Because many investigators have already obtained large data sets of task-related fMRI, the ability to use this existing task data for resting state fcMRI is of considerable interest. Two classes of data sets could potentially be modified to emulate resting state data. These data sets include: (1) "interleaved" resting blocks from blocked or mixed blocked/event-related sets, and (2) residual timecourses from event-related sets that lack rest blocks. Using correlation analysis, we compared the functional connectivity of resting epochs taken from a mixed blocked/event-related design fMRI data set and the residuals derived from event-related data with standard continuous resting state data to determine which class of data can best emulate resting state data. We show that, despite some differences, the functional connectivity for the interleaved resting periods taken from blocked designs is both qualitatively and quantitatively very similar to that of "continuous" resting state data. In contrast, despite being qualitatively similar to "continuous" resting state data, residuals derived from event-related design data had several distinct quantitative differences. These results suggest that the interleaved resting state data such as those taken from blocked or mixed blocked/event-related fMRI designs are well-suited for resting state functional connectivity analyses. Although using event-related data residuals for resting state functional connectivity may still be useful, results should be interpreted with care.

  4. 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.

  5. The impact of "physiological correction" on functional connectivity analysis of pharmacological resting state fMRI.

    Science.gov (United States)

    Khalili-Mahani, Najmeh; Chang, Catie; van Osch, Matthias J; Veer, Ilya M; van Buchem, Mark A; Dahan, Albert; Beckmann, Christian F; van Gerven, Joop M A; Rombouts, Serge A R B

    2013-01-15

    Growing interest in pharmacological resting state fMRI (RSfMRI) necessitates developing standardized and robust analytical approaches that are insensitive to spurious correlated physiological signals. However, in pharmacological experiments physiological variations constitute an important aspect of the pharmacodynamic/pharmacokinetic profile of drug action; therefore retrospective corrective methods that discard physiological signals as noise may not be suitable. Previously, we have shown that template-based dual regression analysis is a sensitive method for model-free and objective detection of drug-specific effects on functional brain connectivity. In the current study, the robustness of this standard approach to physiological variations in a placebo controlled, repeated measures pharmacological RSfMRI study of morphine and alcohol in 12 healthy young men is tested. The impact of physiology-related variations on statistical inferences has been studied by: 1) modeling average physiological rates in higher level group analysis; 2) Regressing out the instantaneous respiration variation (RV); 3) applying retrospective image correction (RETROICOR) in the preprocessing stage; and 4) performing combined RV and heart rate correction (RVHRCOR) by regressing out physiological pulses convolved with canonical respiratory and cardiac hemodynamic response functions. Results indicate regional sensitivity of the BOLD signal to physiological variations, especially in the vicinity of large vessels, plus certain brain structures that are reported to be involved in physiological regulation, such as posterior cingulate, precuneus, medial prefrontal and insular cortices, as well as the thalamus, cerebellum and the brainstem. The largest impact of "correction" on final statistical test outcomes resulted from including the average respiration frequency and heart rate in the higher-level group analysis. Overall, the template-based dual regression method seems robust against physical

  6. fMRI as a molecular imaging procedure for the functional reorganization of motor systems in chronic stroke

    Science.gov (United States)

    LAZARIDOU, ASIMINA; ASTRAKAS, LOUKAS; MINTZOPOULOS, DIONYSSIOS; KHANCHICEH, AZADEH; SINGHAL, ANEESH; MOSKOWITZ, MICHAEL; ROSEN, BRUCE; TZIKA, ARIA

    2013-01-01

    Previous brain imaging studies suggest that stroke alters functional connectivity in motor execution networks. Moreover, current understanding of brain plasticity has led to new approaches in stroke rehabilitation. Recent studies showed a significant role of effective coupling of neuronal activity in the SMA (supplementary motor area) and M1 (primary motor cortex) network for motor outcome in patients after stroke. After a subcortical stroke, functional magnetic resonance imaging (fMRI) during movement reveals cortical reorganization that is associated with the recovery of function. The aim of the present study was to explore connectivity alterations within the motor-related areas combining motor fMRI with a novel MR-compatible hand-induced robotic device (MR_CHIROD) training. Patients completed training at home and underwent serial MR evaluation at baseline and after 8 weeks of training. Training at home consisted of squeezing a gel exercise ball with the paretic hand at ~75% of maximum strength for 1 h/day, 3 days/week. The fMRI analysis revealed alterations in M1, SMA, PMC (premotor cortex) and Cer (cerebellum) in both stroke patients and healthy controls after the training. Findings of the present study suggest that enhancement of SMA activity could benefit M1 dysfunction in stroke survivors. These results also indicate that connectivity alterations between motor areas might assist the counterbalance of a functionally abnormal M1 in chronic stroke survivors and possibly other patients with motor dysfunction. PMID:23900349

  7. Implications of cortical balanced excitation and inhibition, functional heterogeneity, and sparseness of neuronal activity in fMRI

    Science.gov (United States)

    Xu, Jiansong

    2015-01-01

    Blood-oxygenation-level-dependent (BOLD) functional magnetic resonance imaging (fMRI) studies often report inconsistent findings, probably due to brain properties such as balanced excitation and inhibition and functional heterogeneity. These properties indicate that different neurons in the same voxels may show variable activities including concurrent activation and deactivation, that the relationships between BOLD signal and neural activity (i.e., neurovascular coupling) are complex, and that increased BOLD signal may reflect reduced deactivation, increased activation, or both. The traditional general-linear-model-based-analysis (GLM-BA) is a univariate approach, cannot separate different components of BOLD signal mixtures from the same voxels, and may contribute to inconsistent findings of fMRI. Spatial independent component analysis (sICA) is a multivariate approach, can separate the BOLD signal mixture from each voxel into different source signals and measure each separately, and thus may reconcile previous conflicting findings generated by GLM-BA. We propose that methods capable of separating mixed signals such as sICA should be regularly used for more accurately and completely extracting information embedded in fMRI datasets. PMID:26341939

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

    Directory of Open Access Journals (Sweden)

    Laia eFarràs-Permanyer

    2015-08-01

    Full Text Available In the last fifteen 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: fMRI, MCI and functional connectivity. Eighty-one papers were found, but 2 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.

  9. Lying about Facial Recognition: An fMRI Study

    Science.gov (United States)

    Bhatt, S.; Mbwana, J.; Adeyemo, A.; Sawyer, A.; Hailu, A.; VanMeter, J.

    2009-01-01

    Novel deception detection techniques have been in creation for centuries. Functional magnetic resonance imaging (fMRI) is a neuroscience technology that non-invasively measures brain activity associated with behavior and cognition. A number of investigators have explored the utilization and efficiency of fMRI in deception detection. In this study,…

  10. Lying about Facial Recognition: An fMRI Study

    Science.gov (United States)

    Bhatt, S.; Mbwana, J.; Adeyemo, A.; Sawyer, A.; Hailu, A.; VanMeter, J.

    2009-01-01

    Novel deception detection techniques have been in creation for centuries. Functional magnetic resonance imaging (fMRI) is a neuroscience technology that non-invasively measures brain activity associated with behavior and cognition. A number of investigators have explored the utilization and efficiency of fMRI in deception detection. In this study,…

  11. 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...... effects in fMRI data from a visual experiment....

  12. Search for patterns of functional specificity in the brain: a nonparametric hierarchical Bayesian model for group fMRI data.

    Science.gov (United States)

    Lashkari, Danial; Sridharan, Ramesh; Vul, Edward; Hsieh, Po-Jang; Kanwisher, Nancy; Golland, Polina

    2012-01-16

    Functional MRI studies have uncovered a number of brain areas that demonstrate highly specific functional patterns. In the case of visual object recognition, small, focal regions have been characterized with selectivity for visual categories such as human faces. In this paper, we develop an algorithm that automatically learns patterns of functional specificity from fMRI data in a group of subjects. The method does not require spatial alignment of functional images from different subjects. The algorithm is based on a generative model that comprises two main layers. At the lower level, we express the functional brain response to each stimulus as a binary activation variable. At the next level, we define a prior over sets of activation variables in all subjects. We use a Hierarchical Dirichlet Process as the prior in order to learn the patterns of functional specificity shared across the group, which we call functional systems, and estimate the number of these systems. Inference based on our model enables automatic discovery and characterization of dominant and consistent functional systems. We apply the method to data from a visual fMRI study comprised of 69 distinct stimulus images. The discovered system activation profiles correspond to selectivity for a number of image categories such as faces, bodies, and scenes. Among systems found by our method, we identify new areas that are deactivated by face stimuli. In empirical comparisons with previously proposed exploratory methods, our results appear superior in capturing the structure in the space of visual categories of stimuli.

  13. Cognitive deterioration and functional compensation in ALS measured with fMRI using an inhibitory task.

    Science.gov (United States)

    Witiuk, Kelsey; Fernandez-Ruiz, Juan; McKee, Ryan; Alahyane, Nadia; Coe, Brian C; Melanson, Michel; Munoz, Douglas P

    2014-10-22

    Amyotrophic lateral sclerosis (ALS) is characterized by degeneration of upper and lower motor neurons, resulting in progressive weakness and muscle atrophy. Recent studies suggest that nondemented ALS patients can show selective cognitive impairments, predominantly executive dysfunction, but little is known about the neural basis of these impairments. Oculomotor studies in ALS have described deficits in antisaccade execution, which requires the implementation of a task set that includes inhibition of automatic responses followed by generation of a voluntary action. It has been suggested that the dorsolateral prefrontal cortex (DLPFC) contributes in this process. Thus, we investigated whether deterioration of executive functions in ALS patients, such as the ability to implement flexible behavior during the antisaccade task, is related to DLPFC dysfunction. While undergoing an fMRI scan, 12 ALS patients and 12 age-matched controls performed an antisaccade task with concurrent eye tracking. We hypothesized that DLPFC deficits would appear during the antisaccade preparation stage, when the task set is being established. ALS patients made more antisaccade direction errors and showed significant reductions in DLPFC activation. In contrast, regions, such as supplementary eye fields and frontal eye fields, showed increased activation that was anticorrelated with the number of errors. The ALS group also showed reduced saccadic latencies that correlated with increased activation across the oculomotor saccade system. These findings suggest that ALS results in deficits in the inhibition of automatic responses that are related to impaired DLPFC activation. However, they also suggest that ALS patients undergo functional changes that partially compensate the neurological impairment. Copyright © 2014 the authors 0270-6474/14/3414260-12$15.00/0.

  14. 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.)

  15. Comparison of IVA and GIG-ICA in Brain Functional Network Estimation Using fMRI Data.

    Science.gov (United States)

    Du, Yuhui; Lin, Dongdong; Yu, Qingbao; Sui, Jing; Chen, Jiayu; Rachakonda, Srinivas; Adali, Tulay; Calhoun, Vince D

    2017-01-01

    Spatial group independent component analysis (GICA) methods decompose multiple-subject functional magnetic resonance imaging (fMRI) data into a linear mixture of spatially independent components (ICs), some of which are subsequently characterized as brain functional networks. Group information guided independent component analysis (GIG-ICA) as a variant of GICA has been proposed to improve the accuracy of the subject-specific ICs estimation by optimizing their independence. Independent vector analysis (IVA) is another method which optimizes the independence among each subject's components and the dependence among corresponding components of different subjects. Both methods are promising in neuroimaging study and showed a better performance than the traditional GICA. However, the difference between IVA and GIG-ICA has not been well studied. A detailed comparison between them is demanded to provide guidance for functional network analyses. In this work, we employed multiple simulations to evaluate the performances of the two approaches in estimating subject-specific components and time courses under conditions of different data quality and quantity, varied number of sources generated and inaccurate number of components used in computation, as well as the presence of spatially subject-unique sources. We also compared the two methods using healthy subjects' test-retest resting-state fMRI data in terms of spatial functional networks and functional network connectivity (FNC). Results from simulations support that GIG-ICA showed better recovery accuracy of both components and time courses than IVA for those subject-common sources, and IVA outperformed GIG-ICA in component and time course estimation for the subject-unique sources. Results from real fMRI data suggest that GIG-ICA resulted in more reliable spatial functional networks and yielded higher and more robust modularity property of FNC, compared to IVA. Taken together, GIG-ICA is appropriate for estimating networks

  16. 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

  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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. Quantitative fMRI and oxidative neuroenergetics.

    Science.gov (United States)

    Hyder, Fahmeed; Rothman, Douglas L

    2012-08-15

    The discovery of functional magnetic resonance imaging (fMRI) has greatly impacted neuroscience. The blood oxygenation level-dependent (BOLD) signal, using deoxyhemoglobin as an endogenous paramagnetic contrast agent, exposes regions of interest in task-based and resting-state paradigms. However the BOLD contrast is at best a partial measure of neuronal activity, because the functional maps obtained by differencing or correlations ignore the total neuronal activity in the baseline state. Here we describe how studies of brain energy metabolism at Yale, especially with (13)C magnetic resonance spectroscopy and related techniques, contributed to development of quantitative functional brain imaging with fMRI by providing a reliable measurement of baseline energy. This narrative takes us on a journey, from molecules to mind, with illuminating insights about neuronal-glial activities in relation to energy demand of synaptic activity. These results, along with key contributions from laboratories worldwide, comprise the energetic basis for quantitative interpretation of fMRI data. Copyright © 2012 Elsevier Inc. All rights reserved.

  3. 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. PMID:28203153

  4. 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.

  5. 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

  6. Measurement of human advanced brain function in calculation processing using functional magnetic resonance imaging (fMRI)

    Energy Technology Data Exchange (ETDEWEB)

    Hashida, Masahiro; Yamauchi, Syuichi [Yamaguchi Univ., Ube (Japan). Hospital; Wu, Jing-Long (and others)

    2001-06-01

    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)

  7. 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 BACKGROUND: 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. METHODOLOGY: Using a seed-based approach, we have now analyzed effects of modafinil on the functional connectivity (FC of insular subregions. PRINCIPAL FINDINGS: 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. CONCLUSIONS: 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. TRIAL REGISTRATION: ClinicalTrials.gov NCT01684306.

  8. Resting State fMRI in Mice Reveals Anesthesia Specific Signatures of Brain Functional Networks and Their Interactions

    Science.gov (United States)

    Bukhari, Qasim; Schroeter, Aileen; Cole, David M.; Rudin, Markus

    2017-01-01

    fMRI studies in mice typically require the use of anesthetics. Yet, it is known that anesthesia alters responses to stimuli or functional networks at rest. In this work, we have used Dual Regression analysis Network Modeling to investigate the effects of two commonly used anesthetics, isoflurane and medetomidine, on rs-fMRI derived functional networks, and in particular to what extent anesthesia affected the interaction within and between these networks. Experimental data have been used from a previous study (Grandjean et al., 2014). We applied multivariate ICA analysis and Dual Regression to infer the differences in functional connectivity between isoflurane- and medetomidine-anesthetized mice. Further network analysis was performed to investigate within- and between-network connectivity differences between these anesthetic regimens. The results revealed five major networks in the mouse brain: lateral cortical, associative cortical, default mode, subcortical, and thalamic network. The anesthesia regime had a profound effect both on within- and between-network interactions. Under isoflurane anesthesia predominantly intra- and inter-cortical interactions have been observed, with only minor interactions involving subcortical structures and in particular attenuated cortico-thalamic connectivity. In contrast, medetomidine-anesthetized mice displayed subcortical functional connectivity including interactions between cortical and thalamic ICA components. Combining the two anesthetics at low dose resulted in network interaction that constituted the superposition of the interaction observed for each anesthetic alone. The study demonstrated that network modeling is a promising tool for analyzing the brain functional architecture in mice and comparing alterations therein caused by different physiological or pathological states. Understanding the differential effects of anesthetics on brain networks and their interaction is essential when interpreting fMRI data recorded under

  9. Resting State fMRI in Mice Reveals Anesthesia Specific Signatures of Brain Functional Networks and Their Interactions.

    Science.gov (United States)

    Bukhari, Qasim; Schroeter, Aileen; Cole, David M; Rudin, Markus

    2017-01-01

    fMRI studies in mice typically require the use of anesthetics. Yet, it is known that anesthesia alters responses to stimuli or functional networks at rest. In this work, we have used Dual Regression analysis Network Modeling to investigate the effects of two commonly used anesthetics, isoflurane and medetomidine, on rs-fMRI derived functional networks, and in particular to what extent anesthesia affected the interaction within and between these networks. Experimental data have been used from a previous study (Grandjean et al., 2014). We applied multivariate ICA analysis and Dual Regression to infer the differences in functional connectivity between isoflurane- and medetomidine-anesthetized mice. Further network analysis was performed to investigate within- and between-network connectivity differences between these anesthetic regimens. The results revealed five major networks in the mouse brain: lateral cortical, associative cortical, default mode, subcortical, and thalamic network. The anesthesia regime had a profound effect both on within- and between-network interactions. Under isoflurane anesthesia predominantly intra- and inter-cortical interactions have been observed, with only minor interactions involving subcortical structures and in particular attenuated cortico-thalamic connectivity. In contrast, medetomidine-anesthetized mice displayed subcortical functional connectivity including interactions between cortical and thalamic ICA components. Combining the two anesthetics at low dose resulted in network interaction that constituted the superposition of the interaction observed for each anesthetic alone. The study demonstrated that network modeling is a promising tool for analyzing the brain functional architecture in mice and comparing alterations therein caused by different physiological or pathological states. Understanding the differential effects of anesthetics on brain networks and their interaction is essential when interpreting fMRI data recorded under

  10. Pharmaco fMRI: Determining the functional anatomy of the effects of medication

    Directory of Open Access Journals (Sweden)

    Britta Wandschneider

    2016-01-01

    Full Text Available Functional MRI studies have helped to elucidate underlying mechanisms in complex neurological and neuropsychiatric disorders. Disease processes often involve complex large-scale network interactions, extending beyond the presumed main disease focus. Given both the complexity of the clinical phenotype and the underlying dysfunctional brain circuits, so called pharmaco-fMRI (ph-MRI studies probe pharmacological effects on functional neuro-anatomy, and can help to determine early treatment response, mechanisms of drug efficacy and side effects, and potentially advance CNS drug development. In this review, we discuss recent ph-MRI research in three major neuropsychiatric and neurological disorders and associated network alterations, namely selective serotonin and noradrenergic reuptake inhibitors in affective disorders and emotional processing circuits; antiepileptic drugs in epilepsy and cognitive networks; and stimulants in attention-deficit/hyperactivity disorder and networks of attention control. We conclude that ph-MRI studies show consistent and reproducible changes on disease relevant networks, and prove sensitive to early pharmacological effects on functional anatomy associated with disease. Further CNS drug research and development would benefit greatly from improved disease phenotyping, or biomarkers, using advanced imaging techniques.

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

    Institute of Scientific and Technical Information of China (English)

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

    2003-01-01

    AIM: 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 leveldependent functional magnetic resonance imaging (BOLDfMRI) in visceral pain center and to compare the distribution,extent, and intensity of activated areas between IBS patients and normal controls. METHODS: 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, BOLDfMRI was performed at 30 ml, 60 ml, 90 ml, and 120 ml rectal balloon-distention in all subjects. RESULTS: 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. CONCLUSION: 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.

  12. Impact of functional magnetic resonance imaging (fMRI) scanner noise on affective state and attentional performance.

    Science.gov (United States)

    Jacob, Shawna N; Shear, Paula K; Norris, Matthew; Smith, Matthew; Osterhage, Jeff; Strakowski, Stephen M; Cerullo, Michael; Fleck, David E; Lee, Jing-Huei; Eliassen, James C

    2015-01-01

    Previous research has shown that performance on cognitive tasks administered in the scanner can be altered by the scanner environment. There are no previous studies that have investigated the impact of scanner noise using a well-validated measure of affective change. The goal of this study was to determine whether performance on an affective attentional task or emotional response to the task would change in the presence of distracting acoustic noise, such as that encountered in a magnetic resonance imaging (MRI) environment. Thirty-four young adults with no self-reported history of neurologic disorder or mental illness completed three blocks of the affective Posner task outside of the scanner. The task was meant to induce frustration through monetary contingencies and rigged feedback. Participants completed a Self-Assessment Manikin at the end of each block to rate their mood, arousal level, and sense of dominance. During the task, half of the participants heard noise (recorded from a 4T MRI system), and half heard no noise. The affective Posner task led to significant reductions in mood and increases in arousal in healthy participants. The presence of scanner noise did not impact task performance; however, individuals in the noise group did report significantly poorer mood throughout the task. The results of the present study suggest that the acoustic qualities of MRI enhance frustration effects on an affective attentional task and that scanner noise may influence mood during similar functional magnetic resonance imaging (fMRI) tasks.

  13. 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

    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 these func...

  14. Mapping Numerical Processing, Reading, and Executive Functions in the Developing Brain: An fMRI Meta-Analysis of 52 Studies Including 842 Children

    Science.gov (United States)

    Houde, Olivier; Rossi, Sandrine; Lubin, Amelie; Joliot, Marc

    2010-01-01

    Tracing the connections from brain functions to children's cognitive development and education is a major goal of modern neuroscience. We performed the first meta-analysis of functional magnetic resonance imaging (fMRI) data obtained over the past decade (1999-2008) on more than 800 children and adolescents in three core systems of cognitive…

  15. 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

    2013-01-01

    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 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. PMID:23747457

  16. Cerebral Functional Reorganization in Ischemic Stroke after Repetitive Transcranial Magnetic Stimulation: An fMRI Study.

    Science.gov (United States)

    Li, Jing; Zhang, Xue-Wei; Zuo, Zhen-Tao; Lu, Jie; Meng, Chun-Ling; Fang, Hong-Ying; Xue, Rong; Fan, Yong; Guan, Yu-Zhou; Zhang, Wei-Hong

    2016-12-01

    Our study aimed to figure out brain functional reorganization evidence after repetitive transcranial magnetic stimulation (rTMS) using the resting-state functional magnetic resonance imaging (rsfMRI). Twelve patients with unilateral subcortex lesion in the middle cerebral artery territory were recruited. Seven of them received a 10-day rTMS treatment beginning at about 5 days after stroke onset. The remaining five received sham treatment. RsfMRI and motor functional scores were obtained before and after rTMS or sham rTMS. The rTMS group showed motor recovery according to the behavioral testing scores, while there was no significant difference of motor functional scores in the sham group before and after the sham rTMS. It proved that rTMS facilitates motor recovery of early ischemic stroke patients. Compared with the sham, the rTMS treatment group achieved increased functional connectivity (FC) between ipsilesional M1 and contralesional M1, supplementary motor area, bilateral thalamus, and contralesional postcentral gyrus. And decreased FC was found between ipsilesional M1 and ipsilesional M1, postcentral gyrus and inferior and middle frontal gyrus. Increased or decreased FC detected by rsfMRI is an important finding to understand the mechanism of brain functional reorganization. The rTMS treatment is a promising therapeutic approach to facilitate motor rehabilitation for early stroke patients. © 2016 John Wiley & Sons Ltd.

  17. Estimation of the cortical functional connectivity with the multimodal integration of high-resolution EEG and fMRI data by directed transfer function.

    Science.gov (United States)

    Babiloni, F; Cincotti, F; Babiloni, C; Carducci, F; Mattia, D; Astolfi, L; Basilisco, A; Rossini, P M; Ding, L; Ni, Y; Cheng, J; Christine, K; Sweeney, J; He, B

    2005-01-01

    Nowadays, several types of brain imaging device are available to provide images of the functional activity of the cerebral cortex based on hemodynamic, metabolic, or electromagnetic measurements. However, static images of brain regions activated during particular tasks do not convey the information of how these regions communicate with each other. In this study, advanced methods for the estimation of cortical connectivity from combined high-resolution electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data are presented. These methods include a subject's multicompartment head model (scalp, skull, dura mater, cortex) constructed from individual magnetic resonance images, multidipole source model, and regularized linear inverse source estimates of cortical current density. Determination of the priors in the resolution of the linear inverse problem was performed with the use of information from the hemodynamic responses of the cortical areas as revealed by block-designed (strength of activated voxels) fMRI. We estimate functional cortical connectivity by computing the directed transfer function (DTF) on the estimated cortical current density waveforms in regions of interest (ROIs) on the modeled cortical mantle. The proposed method was able to unveil the direction of the information flow between the cortical regions of interest, as it is directional in nature. Furthermore, this method allows to detect changes in the time course of information flow between cortical regions in different frequency bands. The reliability of these techniques was further demonstrated by elaboration of high-resolution EEG and fMRI signals collected during visually triggered finger movements in four healthy subjects. Connectivity patterns estimated for this task reveal an involvement of right parietal and bilateral premotor and prefrontal cortical areas. This cortical region involvement resembles that revealed in previous studies where visually triggered finger

  18. Optimizing stimulation and analysis protocols for neonatal fMRI.

    Science.gov (United States)

    Cusack, Rhodri; Wild, Conor; Linke, Annika C; Arichi, Tomoki; Lee, David S C; Han, Victor K

    2015-01-01

    The development of brain function in young infants is poorly understood. The core challenge is that infants have a limited behavioral repertoire through which brain function can be expressed. Neuroimaging with fMRI has great potential as a way of characterizing typical development, and detecting abnormal development early. But, a number of methodological challenges must first be tackled to improve the robustness and sensitivity of neonatal fMRI. A critical one of these, addressed here, is that the hemodynamic response function (HRF) in pre-term and term neonates differs from that in adults, which has a number of implications for fMRI. We created a realistic model of noise in fMRI data, using resting-state fMRI data from infants and adults, and then conducted simulations to assess the effect of HRF of the power of different stimulation protocols and analysis assumptions (HRF modeling). We found that neonatal fMRI is most powerful if block-durations are kept at the lower range of those typically used in adults (full on/off cycle duration 25-30s). Furthermore, we show that it is important to use the age-appropriate HRF during analysis, as mismatches can lead to reduced power or even inverted signal. Where the appropriate HRF is not known (for example due to potential developmental delay), a flexible basis set performs well, and allows accurate post-hoc estimation of the HRF.

  19. Relation between functional magnetic resonance imaging (fMRI) and single neuron, local field potential (LFP) and electrocorticography (ECoG) activity in human cortex.

    Science.gov (United States)

    Ojemann, George A; Ojemann, Jeffrey; Ramsey, Nick F

    2013-01-01

    The relation between changes in the blood oxygen dependent metabolic changes imaged by functional magnetic resonance imaging (fMRI) and neural events directly recorded from human cortex from single neurons, local field potentials (LFPs) and electrocorticogram (ECoG) is critically reviewed, based on the published literature including findings from the authors' laboratories. All these data are from special populations, usually patients with medically refractory epilepsy, as this provides the major opportunity for direct cortical neuronal recording in humans. For LFP and ECoG changes are often sought in different frequency bands, for single neurons in frequency of action potentials. Most fMRI studies address issues of functional localization. The relation of those findings to localized changes in neuronal recordings in humans has been established in several ways. Only a few studies have directly compared changes in activity from the same sites in the same individual, using the same behavioral measure. More often the comparison has been between fMRI and electrophysiologic changes in populations recorded from the same functional anatomic system as defined by lesion effects; in a few studies those systems have been defined by fMRI changes such as the "default" network. The fMRI-electrophysiologic relationships have been evaluated empirically by colocalization of significant changes, and by quantitative analyses, often multiple linear regression. There is some evidence that the fMRI-electrophysiology relationships differ in different cortical areas, particularly primary motor and sensory cortices compared to association cortex, but also within areas of association cortex. Although crucial for interpretation of fMRI changes as reflecting neural activity in human cortex, controversy remains as to these relationships. Supported by: Dutch Technology Foundation and University of Utrecht Grant UGT7685, ERC-Advanced grant 320708 (NR) and NIH grant NS065186 (JO).

  20. Functional imaging of olfaction by CBV fMRI in monkeys: insight into the role of olfactory bulb in habituation.

    Science.gov (United States)

    Zhao, Fuqiang; Holahan, Marie A; Houghton, Andrea K; Hargreaves, Richard; Evelhoch, Jeffrey L; Winkelmann, Christopher T; Williams, Donald S

    2015-02-01

    Cerebral blood volume (CBV) fMRI with superparamagnetic iron oxide nanoparticles (USPIO) as contrast agent was used to investigate the odorant-induced olfaction in anesthetized rhesus monkeys. fMRI data were acquired in 24 axial slices covering the entire brain, with isoamyl-acetate as the odor stimulant. For each experiment, multiple fMRI measurements were made during a 1- or 2-h period, with each measurement consisting of a baseline period, a stimulation period, and a recovery period. Three different stimulation paradigms with a stimulation period of 1 min, 2 min, or 8 min, respectively, were used to study the olfactory responses in the olfactory bulb (OB). Odorant-induced CBV increases were observed in the OB of each individual monkey. The spatial and temporal activation patterns were reproducible within and between animals. The sensitivity of CBV fMRI in OB was comparable with the sensitivities reported in previous animal fMRI studies. The CBV responses during the 1-min, 2-min, or 8-min odor stimulation period were relatively stable, and did not show attenuation. The amplitudes of CBV response to the repeated stimuli during the 1- or 2-h period were also stable. The stable CBV response in the OB to both continuous and repeated odor stimuli suggests that the OB may not play a major role in olfactory habituation. The technical approach described in this report can enable more extensive fMRI studies of olfactory processing in OB of both humans and non-human primates.

  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. Relation between functional magnetic resonance imaging (fMRI and single neuron, local field potential (LFP and electrocorticography (ECoG activity in human cortex

    Directory of Open Access Journals (Sweden)

    George A. Ojemann

    2013-02-01

    Full Text Available The relation between changes in the blood oxygen dependent metabolic changes imaged by fMRI and neural events directly recorded from human cortex from single neurons, LFPs and ECoG is critically reviewed, based on the published literature including findings from the authors’ laboratories. All these data are from special populations, usually patients with medically refractory epilepsy, as this provides the major opportunity for direct cortical neuronal recording in humans. For LFP and ECoG changes are often sought in different frequency bands, for single neurons in frequency of action potentials. Most fMRI studies address issues of functional localization. The relation of those findings to localized changes in neuronal recordings in humans has been established in several ways. Only a few studies have directly compared changes in activity from the same sites in the same individual, using the same behavioral measure. More often the comparison has been between fMRI and electrophysiologic changes in populations recorded from the same functional anatomic system as defined by lesion effects; in a few studies those systems have been defined by fMRI changes such as the default network. The fMRI-electrophysiologic relationships have been evaluated empirically by colocalization of significant changes, and by quantitative analyses, often multiple linear regression. There is some evidence that the fMRI-electrophysiology relationships differ in different cortical areas, particularly primary motor and sensory cortices compared to association cortex, but also within areas of association cortex. Although crucial for interpretation of fMRI changes as reflecting neural activity in human cortex, controversy remains as to these relationships.Supported by: Dutch Technology Foundation and University of Utrecht Grant UGT7685, ERC-Advanced grant 320708 (NR and NIH grant NS065186 (JO

  3. Functional Connectivity Estimated from Resting-State fMRI Reveals Selective Alterations in Male Adolescents with Pure Conduct Disorder.

    Directory of Open Access Journals (Sweden)

    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.

  4. Functional Connectivity Estimated from Resting-State fMRI Reveals Selective Alterations in Male Adolescents with Pure Conduct Disorder.

    Science.gov (United States)

    Lu, Feng-Mei; Zhou, Jian-Song; Zhang, Jiang; Xiang, Yu-Tao; Zhang, Jian; Liu, Qi; Wang, Xiao-Ping; Yuan, Zhen

    2015-01-01

    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.

  5. On clustering fMRI time series

    DEFF Research Database (Denmark)

    Goutte, C; Toft, P; 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 not indi......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...... between the activation stimulus and the fMRI signal. We present two different clustering algorithms and use them to identify regions of similar activations in an fMRI experiment involving a visual stimulus....

  6. 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

  7. A study-specific fMRI normalization approach that operates directly on high resolution functional EPI data at 7 Tesla

    NARCIS (Netherlands)

    Grabner, G.; Poser, B.; Fujimoto, K.; Polimeni, J.R.; Wald, L.L.; Trattnig, S.; Toni, I.; Barth, M.

    2014-01-01

    Due to the availability of ultra-high field scanners and novel imaging methods, high resolution, whole brain functional MR imaging (fMRI) has become increasingly feasible. However, it is common to use extensive spatial smoothing to account for inter-subject anatomical variation when pooling over

  8. Relation between functional magnetic resonance imaging (fMRI) and single neuron, local field potential (LFP) and electrocorticography (ECoG) activity in human cortex

    NARCIS (Netherlands)

    Ojemann, George A.; Ojemann, Jeffrey; Ramsey, Nick F.

    2013-01-01

    The relation between changes in the blood oxygen dependent metabolic changes imaged by functional magnetic resonance imaging (fMRI) and neural events directly recorded from human cortex from single neurons, local field potentials (LFPs) and electrocorticogram (ECoG) is critically reviewed, based on

  9. A study-specific fMRI normalization approach that operates directly on high resolution functional EPI data at 7 Tesla

    NARCIS (Netherlands)

    Grabner, G.; Poser, B.; Fujimoto, K.; Polimeni, J.R.; Wald, L.L.; Trattnig, S.; Toni, I.; Barth, M.

    2014-01-01

    Due to the availability of ultra-high field scanners and novel imaging methods, high resolution, whole brain functional MR imaging (fMRI) has become increasingly feasible. However, it is common to use extensive spatial smoothing to account for inter-subject anatomical variation when pooling over sub

  10. 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 drainin

  11. fMRI repetition suppression: neuronal adaptation or stimulus expectation?

    Science.gov (United States)

    Larsson, Jonas; Smith, Andrew T

    2012-03-01

    Measurements of repetition suppression with functional magnetic resonance imaging (fMRI adaptation) have been used widely to probe neuronal population response properties in human cerebral cortex. fMRI adaptation techniques assume that fMRI repetition suppression reflects neuronal adaptation, an assumption that has been challenged on the basis of evidence that repetition-related response changes may reflect unrelated factors, such as attention and stimulus expectation. Specifically, Summerfield et al. (Summerfield C, Trittschuh EH, Monti JM, Mesulam MM, Egner T. 2008. Neural repetition suppression reflects fulfilled perceptual expectations. Nat Neurosci. 11:1004-1006) reported that the relative frequency of stimulus repetitions and non-repetitions influenced the magnitude of repetition suppression in the fusiform face area, suggesting that stimulus expectation accounted for most of the effect of repetition. We confirm that stimulus expectation can significantly influence fMRI repetition suppression throughout visual cortex and show that it occurs with long as well as short adaptation durations. However, the effect was attention dependent: When attention was diverted away from the stimuli, the effects of stimulus expectation completely disappeared. Nonetheless, robust and significant repetition suppression was still evident. These results suggest that fMRI repetition suppression reflects a combination of neuronal adaptation and attention-dependent expectation effects that can be experimentally dissociated. This implies that with an appropriate experimental design, fMRI adaptation can provide valid measures of neuronal adaptation and hence response specificity.

  12. 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....... Minimizing image noise and maximizing system stability is critical in fMRI because the blood oxygenation level- dependent (BOLD) signal changes that are used for most fMRI studies represent only a small fraction of the total MR signal. In addition, multiple imaging volumes must be acquired over time to track...... cognitive processes. As a result, MRI scanners must have excellent time-series stability to accurately measure BOLD signal changes over the course of a long time series (typically on the order of 10 min per scan). fMRI studies are particularly demanding on the scanner hardware because they utilize fast...

  13. Semi-blind independent component analysis of fMRI based on real-time fMRI system.

    Science.gov (United States)

    Ma, Xinyue; Zhang, Hang; Zhao, Xiaojie; Yao, Li; Long, Zhiying

    2013-05-01

    Real-time functional magnetic resonance imaging (fMRI) is a type of neurofeedback tool that enables researchers to train individuals to actively gain control over their brain activation. Independent component analysis (ICA) based on data-driven model is seldom used in real-time fMRI studies due to large time cost, though it has been very popular to offline analysis of fMRI data. The feasibility of performing real-time ICA (rtICA) processing has been demonstrated by previous study. However, rtICA was only applied to analyze single-slice data rather than full-brain data. In order to improve the performance of rtICA, we proposed semi-blind real-time ICA (sb-rtICA) for our real-time fMRI system by adding regularization of certain estimated time courses using the experiment paradigm information to rtICA. Both simulated and real-time fMRI experiment were conducted to compare the two approaches. Results from simulated and real full-brain fMRI data demonstrate that sb-rtICA outperforms rtICA in robustness, computational time and spatial detection power. Moreover, in contrast to rtICA, the first component estimated by sb-rtICA tends to be the target component in more sliding windows.

  14. A wavelet-based estimator of the degrees of freedom in denoised fMRI time series for probabilistic testing of functional connectivity and brain graphs.

    Science.gov (United States)

    Patel, Ameera X; Bullmore, Edward T

    2016-11-15

    Connectome mapping using techniques such as functional magnetic resonance imaging (fMRI) has become a focus of systems neuroscience. There remain many statistical challenges in analysis of functional connectivity and network architecture from BOLD fMRI multivariate time series. One key statistic for any time series is its (effective) degrees of freedom, df, which will generally be less than the number of time points (or nominal degrees of freedom, N). If we know the df, then probabilistic inference on other fMRI statistics, such as the correlation between two voxel or regional time series, is feasible. However, we currently lack good estimators of df in fMRI time series, especially after the degrees of freedom of the "raw" data have been modified substantially by denoising algorithms for head movement. Here, we used a wavelet-based method both to denoise fMRI data and to estimate the (effective) df of the denoised process. We show that seed voxel correlations corrected for locally variable df could be tested for false positive connectivity with better control over Type I error and greater specificity of anatomical mapping than probabilistic connectivity maps using the nominal degrees of freedom. We also show that wavelet despiked statistics can be used to estimate all pairwise correlations between a set of regional nodes, assign a P value to each edge, and then iteratively add edges to the graph in order of increasing P. These probabilistically thresholded graphs are likely more robust to regional variation in head movement effects than comparable graphs constructed by thresholding correlations. Finally, we show that time-windowed estimates of df can be used for probabilistic connectivity testing or dynamic network analysis so that apparent changes in the functional connectome are appropriately corrected for the effects of transient noise bursts. Wavelet despiking is both an algorithm for fMRI time series denoising and an estimator of the (effective) df of denoised

  15. Physiologically informed dynamic causal modeling of fMRI data.

    Science.gov (United States)

    Havlicek, Martin; Roebroeck, Alard; Friston, Karl; Gardumi, Anna; Ivanov, Dimo; Uludag, Kamil

    2015-11-15

    The functional MRI (fMRI) signal is an indirect measure of neuronal activity. In order to deconvolve the neuronal activity from the experimental fMRI data, biophysical generative models have been proposed describing the link between neuronal activity and the cerebral blood flow (the neurovascular coupling), and further the hemodynamic response and the BOLD signal equation. These generative models have been employed both for single brain area deconvolution and to infer effective connectivity in networks of multiple brain areas. In the current paper, we introduce a new fMRI model inspired by experimental observations about the physiological underpinnings of the BOLD signal and compare it with the generative models currently used in dynamic causal modeling (DCM), a widely used framework to study effective connectivity in the brain. We consider three fundamental aspects of such generative models for fMRI: (i) an adaptive two-state neuronal model that accounts for a wide repertoire of neuronal responses during and after stimulation; (ii) feedforward neurovascular coupling that links neuronal activity to blood flow; and (iii) a balloon model that can account for vascular uncoupling between the blood flow and the blood volume. Finally, we adjust the parameterization of the BOLD signal equation for different magnetic field strengths. This paper focuses on the form, motivation and phenomenology of DCMs for fMRI and the characteristics of the various models are demonstrated using simulations. These simulations emphasize a more accurate modeling of the transient BOLD responses - such as adaptive decreases to sustained inputs during stimulation and the post-stimulus undershoot. In addition, we demonstrate using experimental data that it is necessary to take into account both neuronal and vascular transients to accurately model the signal dynamics of fMRI data. By refining the models of the transient responses, we provide a more informed perspective on the underlying neuronal

  16. Dynamic network participation of functional connectivity hubs assessed by resting-state fMRI

    Directory of Open Access Journals (Sweden)

    Alexander eSchaefer

    2014-05-01

    Full Text Available Network studies of large-scale brain connectivity have demonstrated that highly connected areas, or ‘hubs’, are a key feature of human functional and structural brain organization. We use resting-state functional MRI data and connectivity clustering to identify multi network hubs and show that while hubs can belong to multiple networks their degree of integration into these different networks varies dynamically over time. In addition, we found that these network dynamics were inversely related to positive self-generated thoughts reported by individuals and were further decreased with older age. Moreover, the left caudate varied its degree of participation between a default mode subnetwork and a limbic network. This variation was predictive of individual differences in the reports of past-related thoughts. These results support an association between ongoing thought processes and network dynamics and offer a new approach to investigate the brain dynamics underlying mental experience.

  17. Effects of aging on functional connectivity of the amygdala during negative evaluation: A network analysis of fMRI data

    Science.gov (United States)

    St. Jacques, Peggy; Dolcos, Florin; Cabeza, Roberto

    2012-01-01

    Previous evidence has suggested both preserved emotional function in aging and age-related differences in emotional processing, but the neural networks underlying such processing alterations in the context of preserved affective function are not clear. Using event-related fMRI, we scanned young and older adults while they made valence ratings for emotional pictures. Behavioral results showed a similar pattern of emotional evaluation, but older adults experienced negatively valenced pictures as being less negative. Consistent with behavioral findings, we identified common activity in the right amygdala, but age-related differences in the functional connectivity of this region with the rest of the brain. Compared to young adults, older adults had greater functional connectivity between the right amygdala and ventral anterior cingulate cortex, possibly reflecting increased emotional regulation. Conversely, older adults showed decreased functional connectivity with posterior brain regions, likely reflecting decreased perceptual processing. Thus, age-related differences in evaluating negatively valenced stimuli might reflect decreased perceptual processing of these stimuli, as well as the engagement of control processes that inhibit the response to negative emotion. PMID:18455837

  18. 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.

  19. 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.)

  20. The functional magnetic resonance imaging (fMRI) procedure as experienced by healthy participants and stroke patients--a pilot study.

    Science.gov (United States)

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

    2009-07-31

    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.

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

    Directory of Open Access Journals (Sweden)

    Shen Shan

    2009-07-01

    Full Text Available Abstract Background 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 (uncomfortable 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. Methods 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. Results 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. Conclusion MRI scanning in the basic research setting is an acceptable procedure for elderly and patient participants as well as young healthy subjects.

  2. Archetypal Analysis for Modeling Multisubject fMRI Data

    DEFF Research Database (Denmark)

    Hinrich, Jesper Løve; Bardenfleth, Sophia Elizabeth; Røge, Rasmus

    2016-01-01

    Functional magnetic resonance imaging (fMRI) is widely used to measure brain function during various cognitive states. However, it remains a challenge to obtain low-rank models of functional networks in fMRI that have interpretable latent features and generalize across groups of subjects, due...... 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...

  3. Decreased Functional Connectivity of Homotopic Brain Regions in Chronic Stroke Patients: A Resting State fMRI Study

    Science.gov (United States)

    Chen, Chuang; Zheng, Xiaohui; Sun, Fenfen; Zhang, Xiaoli; Tian, Jing; Fan, Mingxia; Wu, Yi; Jia, Jie

    2016-01-01

    The recovery of motor functions is accompanied by brain reorganization, and identifying the inter-hemispheric interaction post stroke will conduce to more targeted treatments. However, the alterations of bi-hemispheric coordination pattern between homologous areas in the whole brain for chronic stroke patients were still unclear. The present study focuses on the functional connectivity (FC) of mirror regions of the whole brain to investigate the inter-hemispheric interaction using a new fMRI method named voxel-mirrored homotopic connectivity (VMHC). Thirty left subcortical chronic stroke patients with pure motor deficits and 37 well-matched healthy controls (HCs) underwent resting-state fMRI scans. We employed a VMHC analysis to determine the brain areas showed significant differences between groups in FC between homologous regions, and we explored the relationships between the mean VMHC of each survived area and clinical tests within patient group using Pearson correlation. In addition, the brain areas showed significant correlations between the mean VMHC and clinical tests were defined as the seed regions for whole brain FC analysis. Relative to HCs, patients group displayed lower VMHC in the precentral gyrus, postcentral gyrus, inferior frontal gyrus, middle temporal gyrus, calcarine gyrus, thalamus, cerebellum anterior lobe, and cerebellum posterior lobe (CPL). Moreover, the VMHC of CPL was positively correlated with the Fugl–Meyer Score of hand (FMA-H), while a negative correlation between illness duration and the VMHC of this region was also detected. Furthermore, we found that when compared with HCs, the right CPL exhibited reduced FC with the left precentral gyrus, inferior frontal gyrus, inferior parietal lobule, middle temporal gyrus, thalamus and hippocampus. Our results suggest that the functional coordination across hemispheres is impaired in chronic stroke patients, and increased VMHC of the CPL is significantly associated with higher FMA-H scores

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

    OpenAIRE

    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...

  5. Brain Function and Upper Limb Outcome in Stroke: A Cross-Sectional fMRI Study.

    Directory of Open Access Journals (Sweden)

    Floor E Buma

    Full Text Available The nature of changes in brain activation related to good recovery of arm function after stroke is still unclear. While the notion that this is a reflection of neuronal plasticity has gained much support, confounding by compensatory strategies cannot be ruled out. We address this issue by comparing brain activity in recovered patients 6 months after stroke with healthy controls.We included 20 patients with upper limb paresis due to ischemic stroke and 15 controls. We measured brain activation during a finger flexion-extension task with functional MRI, and the relationship between brain activation and hand function. Patients exhibited various levels of recovery, but all were able to perform the task.Comparison between patients and controls with voxel-wise whole-brain analysis failed to reveal significant differences in brain activation. Equally, a region of interest analysis constrained to the motor network to optimize statistical power, failed to yield any differences. Finally, no significant relationship between brain activation and hand function was found in patients. Patients and controls performed scanner task equally well.Brain activation and behavioral performance during finger flexion-extensions in (moderately well recovered patients seems normal. The absence of significant differences in brain activity even in patients with a residual impairment may suggest that infarcts do not necessarily induce reorganization of motor function. While brain activity could be abnormal with higher task demands, this may also introduce performance confounds. It is thus still uncertain to what extent capacity for true neuronal repair after stroke exists.

  6. Dynamic network participation of functional connectivity hubs assessed by resting-state fMRI

    Science.gov (United States)

    Schaefer, Alexander; Margulies, Daniel S.; Lohmann, Gabriele; Gorgolewski, Krzysztof J.; Smallwood, Jonathan; Kiebel, Stefan J.; Villringer, Arno

    2014-01-01

    Network studies of large-scale brain connectivity have demonstrated that highly connected areas, or “hubs,” are a key feature of human functional and structural brain organization. We use resting-state functional MRI data and connectivity clustering to identify multi-network hubs and show that while hubs can belong to multiple networks their degree of integration into these different networks varies dynamically over time. The extent of the network variation was related to the connectedness of the hub. In addition, we found that these network dynamics were inversely related to positive self-generated thoughts reported by individuals and were further decreased with older age. Moreover, the left caudate varied its degree of participation between a default mode subnetwork and a limbic network. This variation was predictive of individual differences in the reports of past-related thoughts. These results support an association between ongoing thought processes and network dynamics and offer a new approach to investigate the brain dynamics underlying mental experience. PMID:24860458

  7. Extracting multiscale pattern information of fMRI based functional brain connectivity with application on classification of autism spectrum disorders.

    Directory of Open Access Journals (Sweden)

    Hui Wang

    Full Text Available We employed a multi-scale clustering methodology known as "data cloud geometry" to extract functional connectivity patterns derived from functional magnetic resonance imaging (fMRI protocol. The method was applied to correlation matrices of 106 regions of interest (ROIs in 29 individuals with autism spectrum disorders (ASD, and 29 individuals with typical development (TD while they completed a cognitive control task. Connectivity clustering geometry was examined at both "fine" and "coarse" scales. At the coarse scale, the connectivity clustering geometry produced 10 valid clusters with a coherent relationship to neural anatomy. A supervised learning algorithm employed fine scale information about clustering motif configurations and prevalence, and coarse scale information about intra- and inter-regional connectivity; the algorithm correctly classified ASD and TD participants with sensitivity of 82.8% and specificity of 82.8%. Most of the predictive power of the logistic regression model resided at the level of the fine-scale clustering geometry, suggesting that cellular versus systems level disturbances are more prominent in individuals with ASD. This article provides validation for this multi-scale geometric approach to extracting brain functional connectivity pattern information and for its use in classification of ASD.

  8. Extracting multiscale pattern information of fMRI based functional brain connectivity with application on classification of autism spectrum disorders.

    Science.gov (United States)

    Wang, Hui; Chen, Chen; Fushing, Hsieh

    2012-01-01

    We employed a multi-scale clustering methodology known as "data cloud geometry" to extract functional connectivity patterns derived from functional magnetic resonance imaging (fMRI) protocol. The method was applied to correlation matrices of 106 regions of interest (ROIs) in 29 individuals with autism spectrum disorders (ASD), and 29 individuals with typical development (TD) while they completed a cognitive control task. Connectivity clustering geometry was examined at both "fine" and "coarse" scales. At the coarse scale, the connectivity clustering geometry produced 10 valid clusters with a coherent relationship to neural anatomy. A supervised learning algorithm employed fine scale information about clustering motif configurations and prevalence, and coarse scale information about intra- and inter-regional connectivity; the algorithm correctly classified ASD and TD participants with sensitivity of 82.8% and specificity of 82.8%. Most of the predictive power of the logistic regression model resided at the level of the fine-scale clustering geometry, suggesting that cellular versus systems level disturbances are more prominent in individuals with ASD. This article provides validation for this multi-scale geometric approach to extracting brain functional connectivity pattern information and for its use in classification of ASD.

  9. Sex-Related Hemispheric Lateralization of Amygdala Function in Emotionally Influenced Memory: An fMRI Investigation

    Science.gov (United States)

    Cahill, Larry; Uncapher, Melina; Kilpatrick, Lisa; Alkire, Mike T.; Turner, Jessica

    2004-01-01

    The amygdala appears necessary for enhanced long-term memory associated with emotionally arousing events. Recent brain imaging investigations support this view and indicate a sex-related hemispheric lateralization exists in the amygdala relationship to memory for emotional material. This study confirms and further explores this finding. Healthy men and women underwent functional Magnetic Resonance Imaging (fMRI) while viewing a series of standardized slides that were rated by the subjects as ranging from emotionally neutral to highly arousing. Two weeks later, memory for the slides was assessed in an incidental recognition test. The results demonstrate a significantly stronger relationship in men than in women between activity of the right hemisphere amygdala and memory for those slides judged as arousing, and a significantly stronger relationship in women than in men between activity of the left hemisphere amygdala and memory for arousing slides. An ANOVA confirmed a significant interaction between sex and hemisphere regarding amygdala function in memory. These results provide the strongest evidence to date of a sex-related hemispheric lateralization of amygdala function in memory for emotional material. Furthermore, they underscore the view that investigations of neural mechanisms underlying emotionally influenced memory must anticipate, and begin to account for, the apparently substantial influence of sex. PMID:15169855

  10. 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%).

  11. Thoughts turned into high-level commands: Proof-of-concept study of a vision-guided robot arm driven by functional MRI (fMRI) signals.

    Science.gov (United States)

    Minati, Ludovico; Nigri, Anna; Rosazza, Cristina; Bruzzone, Maria Grazia

    2012-06-01

    Previous studies have demonstrated the possibility of using functional MRI to control a robot arm through a brain-machine interface by directly coupling haemodynamic activity in the sensory-motor cortex to the position of two axes. Here, we extend this work by implementing interaction at a more abstract level, whereby imagined actions deliver structured commands to a robot arm guided by a machine vision system. Rather than extracting signals from a small number of pre-selected regions, the proposed system adaptively determines at individual level how to map representative brain areas to the input nodes of a classifier network. In this initial study, a median action recognition accuracy of 90% was attained on five volunteers performing a game consisting of collecting randomly positioned coloured pawns and placing them into cups. The "pawn" and "cup" instructions were imparted through four mental imaginery tasks, linked to robot arm actions by a state machine. With the current implementation in MatLab language the median action recognition time was 24.3s and the robot execution time was 17.7s. We demonstrate the notion of combining haemodynamic brain-machine interfacing with computer vision to implement interaction at the level of high-level commands rather than individual movements, which may find application in future fMRI approaches relevant to brain-lesioned patients, and provide source code supporting further work on larger command sets and real-time processing.

  12. fMRI in Parkinson’s Disease

    DEFF Research Database (Denmark)

    Siebner, Hartwig R.; Herz, Damian

    2013-01-01

    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...

  13. 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.

  14. ORIGINAL ARTICLE CASE REPORT Functional MRI in pre-surgical ...

    African Journals Online (AJOL)

    CASE REPORT. Functional magnetic resonance imaging (fMRI) is an MRI technique ... most promising direct clinical application is in pre-surgical planning, where fMRI is ... robust and established, although it is interesting to note that recent.

  15. Effect of Integrated Cognitive Therapy on Hippocampal Functional Connectivity Patterns in Stroke Patients with Cognitive Dysfunction: A Resting-State fMRI Study

    OpenAIRE

    Shanli Yang; Cai Jiang; Haicheng Ye; Jing Tao; Jia Huang; Yanling Gao; Zhicheng Lin; Lidian Chen

    2014-01-01

    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 baseli...

  16. Assessing language and visuospatial functions with one task: a "dual use" approach to performing fMRI in children.

    Science.gov (United States)

    Ebner, Kathina; Lidzba, Karen; Hauser, Till-Karsten; Wilke, Marko

    2011-10-01

    In order to increase the rate of successful functional MR studies in children it is helpful to shorten the time spent in the scanner. To this effect, assessing two cognitive functions with one task seems to be a promising approach. The hypothesis of this study was that the control condition of an established language task (vowel identification task, VIT) requires visuospatial processing and that the control condition (VIT(CC)) therefore may also be applicable to localize visuospatial functions. As a reference task, a visual search task (VST, previously established for use in children) was employed. To test this hypothesis, 43 children (19 f, 24 m; 12.0±2.6, range 7.9 to 17.8 years) were recruited and scanned using both tasks. Second-level random effects group analyses showed activation of left inferior-frontal cortex in the active condition of the VIT, as in previous studies. Additionally, analysis of the VIT(CC) demonstrated activation in right-dominant superior parietal and high-frontal brain regions, classically associated with visuospatial functions; activation seen in the VST was similar with a substantial overlap. However, lateralization in the parietal lobe was significantly more bilateral in the VST than in the VIT(CC). This suggests that the VIT can not only be applied to assess language functions (using the active>control contrast), but also that the control>active condition is useful for assessing visuospatial functions. Future task design may benefit from such a "dual use" approach to performing fMRI not only, but also particularly in children.

  17. Altered interhemispheric functional connectivity in patients with anisometropic and strabismic amblyopia: a resting-state fMRI study

    Energy Technology Data Exchange (ETDEWEB)

    Liang, Minglong; Xie, Bing; Yin, Xuntao; Wang, Jian [Third Military Medical University, Department of Radiology, Southwest Hospital, 30 Gaotanyan Street, Shapingba District, Chongqing (China); Yang, Hong; Wang, Hao [Third Military Medical University, Ophthalmology Research Center, Southwest Eye Hospital/Southwest Hospital, Chongqing (China); Yu, Longhua [Third Military Medical University, Department of Radiology, Southwest Hospital, 30 Gaotanyan Street, Shapingba District, Chongqing (China); 401st Hospital of PLA, Department of Radiology, Qingdao (China); He, Sheng [University of Minnesota Twin Cities, Department of Psychology, Minneapolis, MN (United States)

    2017-05-15

    Altered brain functional connectivity has been reported in patients with amblyopia by recent neuroimaging studies. However, relatively little is known about the alterations in interhemispheric functional connectivity in amblyopia. The present study aimed to investigate the functional connectivity patterns between homotopic regions across hemispheres in patients with anisometropic and strabismic amblyopia under resting state. Nineteen monocular anisometropic amblyopia (AA), 18 strabismic amblyopia (SA), and 20 normal-sight controls (NC) were enrolled in this study. After a comprehensive ophthalmologic examination, resting-state fMRI scanning was performed in all participants. The pattern of the interhemispheric functional connectivity was measured with the voxel-mirrored homotopic connectivity (VMHC) approach. VMHC values differences within and between three groups were compared, and correlations between VMHC values and each the clinical variable were also analyzed. Altered VMHC was observed in AA and SA patients in lingual gyrus and fusiform gyrus compared with NC subjects. The altered VMHC of lingual gyrus showed a pattern of AA > SA > NC, while the altered VMHC of fusiform gyrus showed a pattern of AA > NC > SA. Moreover, the VMHC values of lingual gyrus were positively correlated with the stereoacuity both in AA and SA patients, and the VMHC values of fusiform gyrus were positively correlated with the amount of anisometropia just in AA patients. These findings suggest that interhemispheric functional coordination between several homotopic visual-related brain regions is impaired both in AA and SA patients under resting state and revealed the similarities and differences in interhemispheric functional connectivity between the anisometropic and strabismic amblyopia. (orig.)

  18. Adult age differences in the functional neuroanatomy of visual attention: A combined fMRI and DTI study

    Science.gov (United States)

    Madden, David J.; Spaniol, Julia; Whiting, Wythe L.; Bucur, Barbara; Provenzale, James M.; Cabeza, Roberto; White, Leonard E.; Huettel, Scott A.

    2007-01-01

    We combined measures from event-related functional magnetic resonance imaging (fMRI), diffusion tensor imaging (DTI), and cognitive performance (visual search response time) to test the hypotheses that differences between younger and older adults in top-down (goal-directed) attention would be related to cortical activation, and that white matter integrity as measured by DTI (fractional anisotropy, FA) would be a mediator of this age-related effect. Activation in frontal and parietal cortical regions was overall greater for older adults than for younger adults. The relation between activation and search performance supported the hypothesis of age differences in top-down attention. When the task involved top-down control (increased target predictability), performance was associated with frontoparietal activation for older adults, but with occipital (fusiform) activation for younger adults. White matter integrity (FA) exhibited an age-related decline that was more pronounced for anterior brain regions than for posterior regions, but white matter integrity did not specifically mediate the age-related increase in activation of the frontoparietal attentional network. PMID:16500004

  19. Conference Report: Functional Magnetic Resonance Imaging for Beginners – A Review of the fMRI Experience IV, 13–14 May 2002, Natcher Conference Center, National Institutes of Health, Bethesda, MD

    Directory of Open Access Journals (Sweden)

    Daniel Caggiano

    2002-01-01

    Full Text Available The fourth fMRI Experience meeting was held at the Bethesda, Maryland campus of the National Institutes of Health on May 13th and 14th, 2002. The purpose of the meeting was to provide a platform for students working with functional magnetic resonance imaging (fMRI to present their research to an international audience of peers. This year’s meeting featured special lectures from Dr. Leslie Ungerleider (“Imaging Mechanisms of Visual Attention” and Dr. Daniel Weinberger (“Genetic Variation and fMRI Response”.

  20. 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...... and population inference. NeuroImage 7, S754) that has been adopted widely for analyses of fMRI data at the group level. We describe a simple procedure, based on restricted maximum likelihood (ReML) estimates of covariance components, that enables full mixed-effects analyses in the context of statistical...

  1. Interhemispheric functional connectivity and its relationships with clinical characteristics in major depressive disorder: a resting state fMRI study.

    Directory of Open Access Journals (Sweden)

    Li Wang

    Full Text Available BACKGROUND: Abnormalities in large-scale, structural and functional brain connectivity have been increasingly reported in patients with major depressive disorder (MDD. However, MDD-related alterations in functional interaction between the cerebral hemispheres are still not well understood. Resting state fMRI, which reveals spontaneous neural fluctuations in blood oxygen level dependent signals, provides a means to detect interhemispheric functional coherence. We examined the resting state functional connectivity (RSFC between the two hemispheres and its relationships with clinical characteristics in MDD patients using a recently proposed measurement named "voxel-mirrored homotopic connectivity (VMHC". METHODOLOGY/PRINCIPAL FINDINGS: We compared the interhemispheric RSFC, computed using the VMHC approach, of seventeen first-episode drug-naive patients with MDD and seventeen healthy controls. Compared to the controls, MDD patients showed significant VMHC decreases in the medial orbitofrontal gyrus, parahippocampal gyrus, fusiform gyrus, and occipital regions including the middle occipital gyrus and cuneus. In MDD patients, a negative correlation was found between VMHC of the fusiform gyrus and illness duration. Moreover, there were several regions whose VMHC showed significant negative correlations with the severity of cognitive disturbance, including the prefrontal regions, such as middle and inferior frontal gyri, and two regions in the cereballar crus. CONCLUSIONS/SIGNIFICANCE: These findings suggest that the functional coordination between homotopic brain regions is impaired in MDD patients, thereby providing new evidence supporting the interhemispheric connectivity deficits of MDD. The significant correlations between the VMHC and clinical characteristics in MDD patients suggest potential clinical implication of VMHC measures for MDD. Interhemispheric RSFC may serve as a useful screening method for evaluating MDD where neural connectivity is

  2. Pharmacological fMRI; a clinical exploration

    OpenAIRE

    Goekoop, R.

    2006-01-01

    Dit proefschrift beschrijft de resultaten van een verkennend onderzoek naar een nieuwe techniek die gebruikt kan worden om de effecten van geneesmiddelen op hersenaktiviteit af te beelden: pharmacologische functionele magnetic resonance imaging (farmacologische fMRI of phMRI). Met behulp van deze techniek werden de effecten onderzocht van drie verschillende medicijnen (de bètablokker propranolol, de selectieve oestrogeen-receptor modulator (SERM) raloxifene en de cholinesteraseremmer galantam...

  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. Distant functional connectivity for bimanual finger coordination declines with aging: An fMRI and SEM exploration

    Directory of Open Access Journals (Sweden)

    Sachiko eKiyama

    2014-04-01

    Full Text Available Although bimanual finger coordination is known to decline with aging, it still remains unclear how exactly the neural substrates underlying the coordination differ between young and elderly adults. The present study focused on: (1 characterization of the functional connectivity within the motor association cortex which is required for successful bimanual finger coordination, and (2 to elucidate upon its age-related decline. To address these objectives, we utilized functional magnetic resonance imaging (fMRI in combination with structural equation modeling (SEM. This allowed us to compare functional connectivity models between young and elderly age groups during a visually guided bimanual finger movement task using both stable in-phase and complex anti-phase modes. Our SEM exploration of functional connectivity revealed significant age-related differences in connections surrounding the PMd in the dominant hemisphere. In the young group who generally displayed accurate behavior, the SEM model for the anti-phase mode exhibited significant connections from the dominant PMd to the non-dominant SPL, and from the dominant PMd to the dominant S1. However, the model for the elderly group’s anti-phase mode in which task performance dropped, did not exhibit significant connections within the aforementioned regions. These results suggest that: (1 the dominant PMd acts as an intermediary to invoke intense intra- and inter-hemispheric connectivity with distant regions among the higher motor areas including the dominant S1 and the non-dominant SPL in order to achieve successful bimanual finger coordination, and (2 the distant connectivity among the higher motor areas declines with aging, whereas the local connectivity within the bilateral M1 is enhanced for the complex anti-phase mode. The latter may underlie the elderly’s decreased performance in the complex anti-phase mode of the bimanual finger movement task.

  5. Distant functional connectivity for bimanual finger coordination declines with aging: an fMRI and SEM exploration.

    Science.gov (United States)

    Kiyama, Sachiko; Kunimi, Mitsunobu; Iidaka, Tetsuya; Nakai, Toshiharu

    2014-01-01

    Although bimanual finger coordination is known to decline with aging, it still remains unclear how exactly the neural substrates underlying the coordination differ between young and elderly adults. The present study focused on: (1) characterization of the functional connectivity within the motor association cortex which is required for successful bimanual finger coordination, and (2) to elucidate upon its age-related decline. To address these objectives, we utilized functional magnetic resonance imaging (fMRI) in combination with structural equation modeling (SEM). This allowed us to compare functional connectivity models between young and elderly age groups during a visually guided bimanual finger movement task using both stable in-phase and complex anti-phase modes. Our SEM exploration of functional connectivity revealed significant age-related differences in connections surrounding the PMd in the dominant hemisphere. In the young group who generally displayed accurate behavior, the SEM model for the anti-phase mode exhibited significant connections from the dominant PMd to the non-dominant SPL, and from the dominant PMd to the dominant S1. However, the model for the elderly group's anti-phase mode in which task performance dropped, did not exhibit significant connections within the aforementioned regions. These results suggest that: (1) the dominant PMd acts as an intermediary to invoke intense intra- and inter-hemispheric connectivity with distant regions among the higher motor areas including the dominant S1 and the non-dominant SPL in order to achieve successful bimanual finger coordination, and (2) the distant connectivity among the higher motor areas declines with aging, whereas the local connectivity within the bilateral M1 is enhanced for the complex anti-phase mode. The latter may underlie the elderly's decreased performance in the complex anti-phase mode of the bimanual finger movement task.

  6. Clinical functional MRI. Presurgical functional neuroimaging

    Energy Technology Data Exchange (ETDEWEB)

    Stippich, C. (ed.) [Heidelberg Univ. (Germany). Div. of Neuroradiology

    2007-07-01

    Functional magnetic resonance imaging (fMRI) permits noninvasive imaging of the ''human brain at work'' under physiological conditions. This is the first textbook on clinical fMRI. It is devoted to preoperative fMRI in patients with brain tumors and epilepsies, which are the most well-established clinical applications. By localizing and lateralizing specific brain functions, as well as epileptogenic zones, fMRI facilitates the selection of a safe treatment and the planning and performance of function-preserving neurosurgery. State of the art fMRI procedures are presented, with detailed consideration of the physiological and methodological background, imaging and data processing, normal and pathological findings, diagnostic possibilities and limitations, and other related techniques. All chapters are written by recognized experts in their fields, and the book is designed to be of value to beginners, trained clinicians and experts alike. (orig.)

  7. 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)

    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.; Boecker, Henning

    2017-01-01

    Background 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. Patients / methods 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. PMID:28076368

  8. Realignment strategies for awake-monkey fMRI data.

    Science.gov (United States)

    Stoewer, Steffen; Goense, Jozien; Keliris, Georgios A; Bartels, Andreas; Logothetis, Nikos K; Duncan, John; Sigala, Natasha

    2011-12-01

    Functional magnetic resonance imaging (fMRI) experiments with awake nonhuman primates (NHPs) have recently seen a surge of applications. However, the standard fMRI analysis tools designed for human experiments are not optimal for NHP data collected at high fields. One major difference is the experimental setup. Although real head movement is impossible for NHPs, MRI image series often contain visible motion artifacts. Animal body movement results in image position changes and geometric distortions. Since conventional realignment methods are not appropriate to address such differences, algorithms tailored specifically for animal scanning become essential. We have implemented a series of high-field NHP specific methods in a software toolbox, fMRI Sandbox (http://kyb.tuebingen.mpg.de/~stoewer/), which allows us to use different realignment strategies. Here we demonstrate the effect of different realignment strategies on the analysis of awake-monkey fMRI data acquired at high field (7 T). We show that the advantage of using a nonstandard realignment algorithm depends on the amount of distortion in the dataset. While the benefits for less distorted datasets are minor, the improvement of statistical maps for heavily distorted datasets is significant.

  9. Action processing and mirror neuron function in patients with amyotrophic lateral sclerosis: an fMRI study.

    Directory of Open Access Journals (Sweden)

    Laura Jelsone-Swain

    Full Text Available Amyotrophic lateral sclerosis (ALS is a highly debilitating and rapidly fatal neurodegenerative disease. It has been suggested that social cognition may be affected, such as impairment in theory of mind (ToM ability. Despite these findings, research in this area is scarce and the investigation of neural mechanisms behind such impairment is absent. Nineteen patients with ALS and eighteen healthy controls participated in this study. Because the mirror neuron system (MNS is thought to be involved in theory of mind, we first implemented a straightforward action-execution and observation task to assess basic MNS function. Second, we examined the social-cognitive ability to understand actions of others, which is a component of ToM. We used fMRI to assess BOLD activity differences between groups during both experiments. Theory of mind was also measured behaviorally using the Reading the Mind in the Eyes test (RME. ALS patients displayed greater BOLD activity during the action-execution and observation task, especially throughout right anterior cortical regions. These areas included the right inferior operculum, premotor and primary motor regions, and left inferior parietal lobe. A conjunction analysis showed significantly more co-activated voxels during both the observation and action-execution conditions in the patient group throughout MNS regions. These results support a compensatory response in the MNS during action processing. In the action understanding experiment, healthy controls performed better behaviorally and subsequently recruited greater regions of activity throughout the prefrontal cortex and middle temporal gyrus. Lastly, action understanding performance was able to cluster patients with ALS into high and lower performing groups, which then differentiated RME performance. Collectively, these data suggest that social cognition, particularly theory of mind, may be affected in a subset of patients with ALS. This impairment may be related to

  10. Functionally integrated neural processing of linguistic and talker information: An event-related fMRI and ERP study.

    Science.gov (United States)

    Zhang, Caicai; Pugh, Kenneth R; Mencl, W Einar; Molfese, Peter J; Frost, Stephen J; Magnuson, James S; Peng, Gang; Wang, William S-Y

    2016-01-01

    Speech signals contain information of both linguistic content and a talker's voice. Conventionally, linguistic and talker processing are thought to be mediated by distinct neural systems in the left and right hemispheres respectively, but there is growing evidence that linguistic and talker processing interact in many ways. Previous studies suggest that talker-related vocal tract changes are processed integrally with phonetic changes in the bilateral posterior superior temporal gyrus/superior temporal sulcus (STG/STS), because the vocal tract parameter influences the perception of phonetic information. It is yet unclear whether the bilateral STG is also activated by the integral processing of another parameter - pitch, which influences the perception of lexical tone information and is related to talker differences in tone languages. In this study, we conducted separate functional magnetic resonance imaging (fMRI) and event-related potential (ERP) experiments to examine the spatial and temporal loci of interactions of lexical tone and talker-related pitch processing in Cantonese. We found that the STG was activated bilaterally during the processing of talker changes when listeners attended to lexical tone changes in the stimuli and during the processing of lexical tone changes when listeners attended to talker changes, suggesting that lexical tone and talker processing are functionally integrated in the bilateral STG. It extends the previous study, providing evidence for a general neural mechanism of integral phonetic and talker processing in the bilateral STG. The ERP results show interactions of lexical tone and talker processing 500-800ms after auditory word onset (a simultaneous posterior P3b and a frontal negativity). Moreover, there is some asymmetry in the interaction, such that unattended talker changes affect linguistic processing more than vice versa, which may be related to the ambiguity that talker changes cause in speech perception and/or attention bias

  11. Action processing and mirror neuron function in patients with amyotrophic lateral sclerosis: an fMRI study.

    Science.gov (United States)

    Jelsone-Swain, Laura; Persad, Carol; Burkard, David; Welsh, Robert C

    2015-01-01

    Amyotrophic lateral sclerosis (ALS) is a highly debilitating and rapidly fatal neurodegenerative disease. It has been suggested that social cognition may be affected, such as impairment in theory of mind (ToM) ability. Despite these findings, research in this area is scarce and the investigation of neural mechanisms behind such impairment is absent. Nineteen patients with ALS and eighteen healthy controls participated in this study. Because the mirror neuron system (MNS) is thought to be involved in theory of mind, we first implemented a straightforward action-execution and observation task to assess basic MNS function. Second, we examined the social-cognitive ability to understand actions of others, which is a component of ToM. We used fMRI to assess BOLD activity differences between groups during both experiments. Theory of mind was also measured behaviorally using the Reading the Mind in the Eyes test (RME). ALS patients displayed greater BOLD activity during the action-execution and observation task, especially throughout right anterior cortical regions. These areas included the right inferior operculum, premotor and primary motor regions, and left inferior parietal lobe. A conjunction analysis showed significantly more co-activated voxels during both the observation and action-execution conditions in the patient group throughout MNS regions. These results support a compensatory response in the MNS during action processing. In the action understanding experiment, healthy controls performed better behaviorally and subsequently recruited greater regions of activity throughout the prefrontal cortex and middle temporal gyrus. Lastly, action understanding performance was able to cluster patients with ALS into high and lower performing groups, which then differentiated RME performance. Collectively, these data suggest that social cognition, particularly theory of mind, may be affected in a subset of patients with ALS. This impairment may be related to functioning of

  12. Optimization of anesthesia protocol for resting-state fMRI in mice based on differential effects of anesthetics on functional connectivity patterns.

    Science.gov (United States)

    Grandjean, Joanes; Schroeter, Aileen; Batata, Imene; Rudin, Markus

    2014-11-15

    Resting state-fMRI (rs-fMRI) in mice allows studying mechanisms underlying functional connectivity (FC) as well as alterations of FC occurring in murine models of neurological diseases. Mouse fMRI experiments are typically carried out under anesthesia to minimize animal movement and potential distress during examination. Yet, anesthesia inevitably affects FC patterns. Such effects have to be understood for proper interpretation of data. We have compared the influence of four commonly used anesthetics on rs-fMRI. Rs-fMRI data acquired under isoflurane, propofol, and urethane presented similar patterns when accounting for anesthesia depth. FC maps displayed bilateral correlation with respect to cortical seeds, but no significant inter-hemispheric striatal connectivity. In contrast, for medetomidine, we detected bilateral striatal but compromised inter-hemispheric cortical connectivity. The spatiotemporal patterns of the rs-fMRI signal have been rationalized considering anesthesia depth and pharmacodynamic properties of the anesthetics. Our results bridge the results from different studies from the burgeoning field of mouse rs-fMRI and offer a framework for understanding the influences of anesthetics on FC patterns. Utilizing this information, we suggest the combined use of medetomidine and isoflurane representing the two proposed classes of anesthetics; the combination of low doses of the two anesthetics retained strong correlations both within cortical and subcortical structures, without the potential seizure-inducing effects of medetomidine, rendering this regimen an attractive anesthesia for rs-fMRI in mice.

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

    Science.gov (United States)

    Churchill, Nathan W; Madsen, Kristoffer; Mørup, Morten

    2016-10-01

    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 these functional relationships, although it is an ongoing challenge to develop robust, interpretable models for high-dimensional fMRI data. Gaussian mixture models (GMMs) are a powerful tool for parcellating the brain, based on the similarity of voxel time series. However, conventional GMMs have limited parametric 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 of the GMM framework simultaneously estimates spatial clustering and the most consistent group functional connectivity structure. It also explicitly models network variability, based on voxel- and subject-specific network scaling profiles. We compared the FSIM to standard GMM in a predictive cross-validation framework and examined the importance of different model parameters, using both simulated and experimental resting-state data. The reliability of parcellations is not significantly altered by flexibility of the FSIM, whereas voxel- and subject-specific network scaling profiles significantly improve the ability to predict functional connectivity in independent test data. Moreover, the FSIM provides a set of interpretable parameters to characterize both consistent and variable aspects functional connectivity structure. As an example of its utility, we use subject-specific network profiles to identify brain regions where network expression predicts subject age in the experimental data. Thus, the FSIM is effective at summarizing functional connectivity structure in group

  14. Neuroethics and fMRI: mapping a fledgling relationship.

    Science.gov (United States)

    Garnett, Alex; Whiteley, Louise; Piwowar, Heather; Rasmussen, Edie; Illes, Judy

    2011-04-22

    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 moral judgments. It is at the centre of debate surrounding the importance of neuroscience findings for concepts such as personhood and free will, and the extent of their practical consequences. Here, we map the landscape of fMRI and neuroethics, using citation analysis to uncover salient topics. We find that this landscape is sparsely populated: despite previous calls for debate, there are few articles that discuss both fMRI and ethical, legal, or social implications (ELSI), and even fewer direct citations between the two literatures. Recognizing that practical barriers exist to integrating ELSI discussion into the research literature, we argue nonetheless that the ethical challenges of fMRI, and controversy over its conceptual and practical implications, make this essential.

  15. Neuroethics and fMRI: mapping a fledgling relationship.

    Directory of Open Access Journals (Sweden)

    Alex Garnett

    Full Text Available 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 moral judgments. It is at the centre of debate surrounding the importance of neuroscience findings for concepts such as personhood and free will, and the extent of their practical consequences. Here, we map the landscape of fMRI and neuroethics, using citation analysis to uncover salient topics. We find that this landscape is sparsely populated: despite previous calls for debate, there are few articles that discuss both fMRI and ethical, legal, or social implications (ELSI, and even fewer direct citations between the two literatures. Recognizing that practical barriers exist to integrating ELSI discussion into the research literature, we argue nonetheless that the ethical challenges of fMRI, and controversy over its conceptual and practical implications, make this essential.

  16. 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.; Hamalainen, Matti S.; Rosen, Bruce R.; Wald, Lawrence L.

    2016-01-01

    Object 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. Materials and Methods 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 utilized the increased contrast-to-noise ratio of 7 Tesla fMRI compared to 3 Tesla and the 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). Results 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. Conclusion 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. PMID:27126248

  17. 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.

  18. The interactive effect of social pain and executive functioning on aggression: an fMRI experiment.

    Science.gov (United States)

    Chester, David S; Eisenberger, Naomi I; Pond, Richard S; Richman, Stephanie B; Bushman, Brad J; Dewall, C Nathan

    2014-05-01

    Social rejection often increases aggression, but the neural mechanisms underlying this effect remain unclear. This experiment tested whether neural activity in the dorsal anterior cingulate cortex (dACC) and anterior insula in response to social rejection predicted greater subsequent aggression. Additionally, it tested whether executive functioning moderated this relationship. Participants completed a behavioral measure of executive functioning, experienced social rejection while undergoing functional magnetic resonance imaging and then completed a task in which they could aggress against a person who rejected them using noise blasts . We found that dACC activation and executive functioning interacted to predict aggression. Specifically, participants with low executive functioning showed a positive association between dACC activation and aggression, whereas individuals with high executive functioning showed a negative association. Similar results were found for the left anterior insula. These findings suggest that social pain can increase or decrease aggression, depending on an individual's regulatory capability.

  19. 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 cons

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

    NARCIS (Netherlands)

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

    2008-01-01

    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 noi

  1. Primary Visual Cortex Scales Individual's Perceived Brightness with Power Function: Inner Psychophysics with fMRI

    Science.gov (United States)

    Tsubomi, Hiroyuki; Ikeda, Takashi; Osaka, Naoyuki

    2012-01-01

    Perceived brightness is well described by Stevens' power function (S. S. Stevens, 1957, On the psychophysical law, "Psychological Review", Vol. 64, pp. 153-181), with a power exponent of 0.33 (the cubic-root function of luminance). The power exponent actually varies across individuals, yet little is known about neural substrates underlying this…

  2. Primary Visual Cortex Scales Individual's Perceived Brightness with Power Function: Inner Psychophysics with fMRI

    Science.gov (United States)

    Tsubomi, Hiroyuki; Ikeda, Takashi; Osaka, Naoyuki

    2012-01-01

    Perceived brightness is well described by Stevens' power function (S. S. Stevens, 1957, On the psychophysical law, "Psychological Review", Vol. 64, pp. 153-181), with a power exponent of 0.33 (the cubic-root function of luminance). The power exponent actually varies across individuals, yet little is known about neural substrates underlying this…

  3. Alternations of functional connectivity in amblyopia patients: a resting-state fMRI study

    Science.gov (United States)

    Wang, Jieqiong; Hu, Ling; Li, Wenjing; Xian, Junfang; Ai, Likun; He, Huiguang

    2014-03-01

    Amblyopia is a common yet hard-to-cure disease in children and results in poor or blurred vision. Some efforts such as voxel-based analysis, cortical thickness analysis have been tried to reveal the pathogenesis of amblyopia. However, few studies focused on alterations of the functional connectivity (FC) in amblyopia. In this study, we analyzed the abnormalities of amblyopia patients by both the seed-based FC with the left/right primary visual cortex and the network constructed throughout the whole brain. Experiments showed the following results: (1)As for the seed-based FC analysis, FC between superior occipital gyrus and the primary visual cortex was found to significantly decrease in both sides. The abnormalities were also found in lingual gyrus. The results may reflect functional deficits both in dorsal stream and ventral stream. (2)Two increased functional connectivities and 64 decreased functional connectivities were found in the whole brain network analysis. The decreased functional connectivities most concentrate in the temporal cortex. The results suggest that amblyopia may be caused by the deficits in the visual information transmission.

  4. Brain Function and Upper Limb Outcome in Stroke : A Cross-Sectional fMRI Study

    NARCIS (Netherlands)

    Buma, Floor E; Raemaekers, Mathijs; Kwakkel, Gert; Ramsey, Nick F

    2015-01-01

    OBJECTIVE: The nature of changes in brain activation related to good recovery of arm function after stroke is still unclear. While the notion that this is a reflection of neuronal plasticity has gained much support, confounding by compensatory strategies cannot be ruled out. We address this issue by

  5. fMRI functional connectivity of the periaqueductal gray in PTSD and its dissociative subtype.

    Science.gov (United States)

    Harricharan, Sherain; Rabellino, Daniela; Frewen, Paul A; Densmore, Maria; Théberge, Jean; McKinnon, Margaret C; Schore, Allan N; Lanius, Ruth A

    2016-12-01

    Posttraumatic stress disorder (PTSD) is associated with hyperarousal and active fight or flight defensive responses. By contrast, the dissociative subtype of PTSD, characterized by depersonalization and derealization symptoms, is frequently accompanied by additional passive or submissive defensive responses associated with autonomic blunting. Here, the periaqueductal gray (PAG) plays a central role in defensive responses, where the dorsolateral (DL-PAG) and ventrolateral PAG (VL-PAG) are thought to mediate active and passive defensive responses, respectively. We examined PAG subregion (dorsolateral and ventrolateral) resting-state functional connectivity in three groups: PTSD patients without the dissociative subtype (n = 60); PTSD patients with the dissociative subtype (n = 37); and healthy controls (n = 40) using a seed-based approach via PickAtlas and SPM12. All PTSD patients showed extensive DL- and VL-PAG functional connectivity at rest with areas associated with emotional reactivity and defensive action as compared to controls (n = 40). Although all PTSD patients demonstrated DL-PAG functional connectivity with areas associated with initiation of active coping strategies and hyperarousal (e.g., dorsal anterior cingulate; anterior insula), only dissociative PTSD patients exhibited greater VL-PAG functional connectivity with brain regions linked to passive coping strategies and increased levels of depersonalization (e.g., temporoparietal junction; rolandic operculum). These findings suggest greater defensive posturing in PTSD patients even at rest and demonstrate that those with the dissociative subtype show unique patterns of PAG functional connectivity when compared to those without the subtype. Taken together, these findings represent an important first step toward identifying neural and behavioral targets for therapeutic interventions that address defensive strategies in trauma-related disorders.

  6. Functional Asymmetries Revealed in Visually Guided Saccades: An fMRI Study

    Energy Technology Data Exchange (ETDEWEB)

    Petit, L.; Zago, L.; Vigneau, M.; Crivello, F.; Mazoyer, B.; Mellet, E.; Tzourio-Mazoyer, N. [Centre for Imaging, Neurosciences and Applications to Pathologies, UMR6232 CNRS CEA (France); Mazoyer, B. [Centre Hospitalier Universitaire, Caen (France); Andersson, F. [Institut Federatif de Recherche 135, Imagerie fonctionnelle, Tours (France); Mazoyer, B. [Institut Universitaire de France, Paris (France)

    2009-07-01

    Because eye movements are a fundamental tool for spatial exploration, we hypothesized that the neural bases of these movements in humans should be under right cerebral dominance, as already described for spatial attention. We used functional magnetic resonance imaging in 27 right-handed participants who alternated central fixation with either large or small visually guided saccades (VGS), equally performed in both directions. Hemispheric functional asymmetry was analyzed to identify whether brain regions showing VGS activation elicited hemispheric asymmetries. Hemispheric anatomical asymmetry was also estimated to assess its influence on the VGS functional lateralization. Right asymmetrical activations of a saccadic/attentional system were observed in the lateral frontal eye fields (FEF), the anterior part of the intra-parietal sulcus (aIPS), the posterior third of the superior temporal sulcus (STS), the occipito-temporal junction (MT/V5 area), the middle occipital gyrus, and medially along the calcarine fissure (V1). The present rightward functional asymmetries were not related to differences in gray matter (GM) density/sulci positions between right and left hemispheres in the pre-central, intra-parietal, superior temporal, and extrastriate regions. Only V1 asymmetries were explained for almost 20% of the variance by a difference in the position of the right and left calcarine fissures. Left asymmetrical activations of a saccadic motor system were observed in the medial FEF and in the motor strip eye field along the Rolando sulcus. They were not explained by GM asymmetries. We suggest that the leftward saccadic motor asymmetry is part of a general dominance of the left motor cortex in right-handers, which must include an effect of sighting dominance. Our results demonstrate that, although bilateral by nature, the brain network involved in the execution of VGSs, irrespective of their direction, presented specific right and left asymmetries that were not related to

  7. The effect of topiramate on cognitive fMRI

    Science.gov (United States)

    Yasuda, Clarissa Lin; Centeno, Maria; Vollmar, Christian; Stretton, Jason; Symms, Mark; Cendes, Fernando; Mehta, Mitul A.; Thompson, Pamela; Duncan, John S.; Koepp, Matthias J.

    2013-01-01

    Summary Purpose Topiramate (TPM) is known to cause language impairment in healthy volunteers and patients with epilepsy. We assessed the effects of TPM on functional language networks in both patients with focal epilepsies and healthy controls using functional magnetic resonance imaging (fMRI). Methods We obtained fMRI data in 24 controls and 35 patients with frontal lobe epilepsy using a simple verbal fluency (VF) paradigm. Eight of the 35 patients were treated with TPM in polytherapy. We compared cognitive task related activations and de-activations in patients taking TPM with patients taking other AEDs and healthy controls. In a longitudinal pilot study with VF-fMRI paradigm, we studied two patients with focal epilepsies twice, prior to starting and on stable doses of TPM, two patients twice, before and after tapering TPM completely and two healthy controls twice, before and after single doses of 200 mg TPM. Key findings Cross sectional analyses of VF-fMRI showed a reduction in the task-related deactivation of the default mode network (DMN) in patients taking TPM. The longitudinal study corroborated these findings as both chronic administration and a single dose of TPM were associated with impaired categorical verbal fluency and disruption of task-related deactivations. Significance Similar neuropsychological and fMRI findings in patients and healthy controls indicate a specific effect of TPM in default mode network areas that may be essential components of the language network. Our preliminary data suggest a mechanism by which TPM impairs cognitive processing during language function and highlights the sensitivity of fMRI to detect the effects of AEDs on cognitive brain networks. PMID:23333471

  8. Spinal cord stimulation modulates cerebral function: an fMRI study

    Energy Technology Data Exchange (ETDEWEB)

    Moens, M. [Universitair Ziekenhuis Brussel, Department of Neurosurgery and Center for Neuroscience, Brussels (Belgium); Sunaert, S.; Peeters, R. [UZ Leuven, Katholieke Universiteit Leuven, Department of Radiology, Leuven (Belgium); Marien, P. [ZNA Middelheim General Hospital, Department of Neurology, Antwerp (Belgium); Vrije Universiteit Brussel, Department of Clinical and Experimental Neurolinguistics, Brussels (Belgium); Brouns, R.; Smedt, A. de [Universitair Ziekenhuis Brussel, Department of Neurology and Center for Neuroscience, Brussels (Belgium); Droogmans, S. [Universitair Ziekenhuis Brussel, Department of Cardiology, Brussels (Belgium); Schuerbeek, P. van [Universitair Ziekenhuis Brussel, Department of Radiology, Brussels (Belgium); Poelaert, J. [Universitair Ziekenhuis Brussel, Department of Anesthesiology, Brussels (Belgium); Nuttin, B. [UZ Leuven, Katholieke Universiteit Leuven, Department of Neurosurgery, Leuven (Belgium)

    2012-12-15

    Although spinal cord stimulation (SCS) is widely used for chronic neuropathic pain after failed spinal surgery, little is known about the underlying physiological mechanisms. This study aims to investigate the neural substrate underlying short-term (30 s) SCS by means of functional magnetic resonance imaging in 20 patients with failed back surgery syndrome (FBSS). Twenty patients with FBSS, treated with externalized SCS, participated in a blocked functional magnetic resonance imaging design with stimulation and rest phases of 30 s each, repeated eight times in a row. During scanning, patients rated pain intensity over time using an 11-point numerical rating scale with verbal anchors (0 = no pain at all to 10 = worst pain imaginable) by pushing buttons (left hand, lesser pain; right hand, more pain). This scale was back projected to the patients on a flat screen allowing them to manually direct the pain indicator. To increase the signal-to-noise ratio, the 8-min block measurements were repeated three times. Marked deactivation of the bilateral medial thalamus and its connections to the rostral and caudal cingulate cortex and the insula was found; the study also showed immediate pain relief obtained by short-term SCS correlated negatively with activity in the inferior olivary nucleus, the cerebellum, and the rostral anterior cingulate cortex. Results indicate the key role of the medial thalamus as a mediator and the involvement of a corticocerebellar network implicating the modulation and regulation of averse and negative affect related to pain. The observation of a deactivation of the ipsilateral antero-medial thalamus might be used as a region of interest for further response SCS studies. (orig.)

  9. Prospective multiaxial motion correction for fMRI.

    Science.gov (United States)

    Ward, H A; Riederer, S J; Grimm, R C; Ehman, R L; Felmlee, J P; Jack, C R

    2000-03-01

    Corruption of the image time series due to interimage head motion limits the clinical utility of functional MRI. This paper presents a method for real-time prospective correction of rotation and translation in all six degrees of rigid body motion. By incorporating an orbital navigator (ONAV) echo for each of the sagittal, axial, and coronal planes into the fMRI pulse sequence, rotation and translation can be measured and the spatial orientation of the image acquisition sequence that follows can be corrected prospectively in as little as 160 msec. Testing of the method using a computerized motion phantom capable of performing complex multiaxial motion showed subdegree rotational and submillimeter translational accuracy over a range of +/-8 degrees and +/-8 mm of motion. In vivo images demonstrate correction of simultaneous through-plane and in-plane motion and improved detection of fMRI activation in the presence of head motion.

  10. Neurophysiology of motor function following cannabis discontinuation in chronic cannabis smokers: an fMRI study.

    Science.gov (United States)

    Pillay, Srinivasan S; Rogowska, Jadwiga; Kanayama, Gen; Jon, Duk-In; Gruber, Staci; Simpson, Norah; Cherayil, Monisha; Pope, Harrison G; Yurgelun-Todd, Deborah A

    2004-12-07

    The objective of this study was to identify the differences in cerebral activation between chronic cannabis smokers and controls in response to finger sequencing. We hypothesized that attentional areas related to motor function as well as primary and supplementary motor cortices would show diminished activation in chronic cannabis smokers. Nine cannabis smokers and 16 controls were included in these analyses. Scanning was performed on a GE 1.5T scanner. Echo planar images and high-resolution MR images were acquired. The challenge paradigm included left and right finger sequencing. Group differences in cerebral activation were examined for Brodmann areas (BA) 4, 6, 24, and 32 using ROI analyses in SPM. Cannabis users, tested within 4-36 h of discontinuation, exhibited significantly less activation than controls in BA 24 and 32 bilaterally during right- and left-sided sequencing and for BA 6 in all tasks except for left-sided sequencing in the left hemisphere. There were no statistically significant differences for BA 4. None of these regional activations correlated with urinary cannabis concentration and verbal IQ for smokers. These results suggest that recently abstinent chronic cannabis smokers produce reduced activation in motor cortical areas in response to finger sequencing compared to controls.

  11. Modeling Task fMRI Data via Deep Convolutional Autoencoder.

    Science.gov (United States)

    Huang, Heng; Hu, Xintao; Zhao, Yu; Makkie, Milad; Dong, Qinglin; Zhao, Shijie; Guo, Lei; Liu, Tianming

    2017-06-15

    Task-based fMRI (tfMRI) has been widely used to study functional brain networks under task performance. Modeling tfMRI data is challenging due to at least two problems: the lack of the ground truth of underlying neural activity and the highly complex intrinsic structure of tfMRI data. To better understand brain networks based on fMRI data, data-driven approaches have been proposed, for instance, Independent Component Analysis (ICA) and Sparse Dictionary Learning (SDL). However, both ICA and SDL only build shallow models, and they are under the strong assumption that original fMRI signal could be linearly decomposed into time series components with their corresponding spatial maps. As growing evidence shows that human brain function is hierarchically organized, new approaches that can infer and model the hierarchical structure of brain networks are widely called for. Recently, deep convolutional neural network (CNN) has drawn much attention, in that deep CNN has proven to be a powerful method for learning high-level and mid-level abstractions from low-level raw data. Inspired by the power of deep CNN, in this study, we developed a new neural network structure based on CNN, called Deep Convolutional Auto-Encoder (DCAE), in order to take the advantages of both data-driven approach and CNN's hierarchical feature abstraction ability for the purpose of learning mid-level and high-level features from complex, large-scale tfMRI time series in an unsupervised manner. The DCAE has been applied and tested on the publicly available human connectome project (HCP) tfMRI datasets, and promising results are achieved.

  12. Does Chronic Tinnitus Alter the Emotional Response Function of the Amygdala?: A Sound-Evoked fMRI Study

    Science.gov (United States)

    Davies, Jeff E.; Gander, Phillip E.; Hall, Deborah A.

    2017-01-01

    Tinnitus is often associated with strong negative thoughts and emotions which can contribute to a distressing and chronic long-term condition. The amygdala, the “feeling and reacting” part of the brain, may play a key role in this process. Although implicated in several theoretical models of tinnitus, quantification of activity in the human amygdala has only been made possible more recently through neuroimaging methods such as functional magnetic resonance imaging (fMRI) but benefits from modified scanning parameters using a double-echo acquisition for improved BOLD sensitivity. This study thus examined the role of the amygdala in emotional sound processing in people with tinnitus using a novel double-echo imaging sequence for optimal detectability of subcortical activity. Our hypotheses were: (1) emotionally evocative sound clips rated as pleasant or unpleasant would elicit stronger amygdalar activation than sound clips rated as neutral, (2) people with tinnitus have greater amygdalar activation in response to emotionally evocative sounds (relative to neutral sounds) compared to controls. Methods: Twelve participants all with chronic, constant tinnitus took part. We also recruited 11 age and hearing-matched controls. Participants listened to a range of emotionally evocative sound clips; rated as pleasant, unpleasant or neutral. A region-of-interest analysis was chosen to test our a priori hypotheses. Results: Both groups displayed a robust and similar overall response to sounds vs. silence in the following ascending auditory pathways; inferior colliculus, medial geniculate body and the primary auditory cortex. In support of our first hypothesis, the amygdala's response to pleasant and unpleasant sound clips was significantly greater than neutral sounds. Opposing our second hypothesis, we found that the amygdala's overall response to pleasant and unpleasant sounds (compared to neutral sounds) was actually lower in the tinnitus group as compared to the controls

  13. fMRI at High Spatial Resolution: Implications for BOLD-Models.

    Science.gov (United States)

    Goense, Jozien; Bohraus, Yvette; Logothetis, Nikos K

    2016-01-01

    As high-resolution functional magnetic resonance imaging (fMRI) and fMRI of cortical layers become more widely used, the question how well high-resolution fMRI signals reflect the underlying neural processing, and how to interpret laminar fMRI data becomes more and more relevant. High-resolution fMRI has shown laminar differences in cerebral blood flow (CBF), volume (CBV), and neurovascular coupling. Features and processes that were previously lumped into a single voxel become spatially distinct at high resolution. These features can be vascular compartments such as veins, arteries, and capillaries, or cortical layers and columns, which can have differences in metabolism. Mesoscopic models of the blood oxygenation level dependent (BOLD) response therefore need to be expanded, for instance, to incorporate laminar differences in the coupling between neural activity, metabolism and the hemodynamic response. Here we discuss biological and methodological factors that affect the modeling and interpretation of high-resolution fMRI data. We also illustrate with examples from neuropharmacology and the negative BOLD response how combining BOLD with CBF- and CBV-based fMRI methods can provide additional information about neurovascular coupling, and can aid modeling and interpretation of high-resolution fMRI.

  14. Functional magnetic resonance imaging (fMRI) of motor deficits in schizophrenia; Funktionelle Magnetresonanztomographie (fMRT) bei Bewegungsstoerungen von Patienten mit Schizophrenie

    Energy Technology Data Exchange (ETDEWEB)

    Wenz, F. [Radiologische Universitaetsklinik, Heidelberg (Germany). Abt. Klinische Radiologie; Baudendistel, K. [Deutsches Krebsforschungszentrum, Heidelberg (Germany). Forschungsschwerpunkt Radiologische Diagnostik und Therapie; Knopp, M.V. [Deutsches Krebsforschungszentrum, Heidelberg (Germany). Forschungsschwerpunkt Radiologische Diagnostik und Therapie; Schad, L.R. J. [Deutsches Krebsforschungszentrum, Heidelberg (Germany). Forschungsschwerpunkt Radiologische Diagnostik und Therapie; Schroeder, J. [Psychiatrische Universitaetsklinik, Heidelberg (Germany); Floemer, F. [Deutsches Krebsforschungszentrum, Heidelberg (Germany). Forschungsschwerpunkt Radiologische Diagnostik und Therapie; Kaick, G. van [Deutsches Krebsforschungszentrum, Heidelberg (Germany). Forschungsschwerpunkt Radiologische Diagnostik und Therapie

    1995-04-01

    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/{alpha}=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.) [Deutsch] In dieser Studie sollten Veraenderungen im zerebralen Aktivierungsmuster bei 10 schizophrenen Patienten im Vergleich zu 10 gesunden Probanden mit der fMRT untersucht werden. Wir benutzten eine modifizierte FLASH-Sequenz (TR/TE/{alpha}=100/60/40 ) und einen konventionellen 1,5-T-MR-Tomographen. Farbkodierte t-Testbilder wurden berechnet und mit Hilfe eines ueberlagerten 5x6-Gitters quantitativ ausgewertet. Bei den Probanden induzierte die Bewegung der linken Hand eine hoehere Aktivierung als die Bewegung der rechten Hand. Dieses Lateralisationsverhalten war bei den Patienten, die eine insgesamt verminderte Aktivierungsstaerke zeigten, umgekehrt. Bei schizophrenen Patienten konnte mittels fMRT eine veraenderte Interhemisphaeren-Balance gezeigt werden. (orig.)

  15. fMRI paradigm designing and post-processing tools

    Directory of Open Access Journals (Sweden)

    Jija S James

    2014-01-01

    Full Text Available 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.

  16. Investigation of fMRI activation in the internal capsule

    Directory of Open Access Journals (Sweden)

    Brewer Kimberley D

    2011-06-01

    Full Text Available Abstract Background Functional magnetic resonance imaging (fMRI in white matter has long been considered controversial. Recently, this viewpoint has been challenged by an emerging body of evidence demonstrating white matter activation in the corpus callosum. The current study aimed to determine whether white matter activation could be detected outside of the corpus callosum, in the internal capsule. Data were acquired from a 4 T MRI using a specialized asymmetric spin echo spiral sequence. A motor task was selected to elicit activation in the posterior limb of the internal capsule. Results White matter fMRI activation was examined at the individual and group levels. Analyses revealed that activation was present in the posterior limb of the internal capsule in 80% of participants. These results provide further support for white matter fMRI activation. Conclusions The ability to visualize functionally active tracts has strong implications for the basic scientific study of connectivity and the clinical assessment of white matter disease.

  17. Physiological measurements using ultra-high field fMRI: a review.

    Science.gov (United States)

    Francis, Sue; Panchuelo, Rosa Sanchez

    2014-09-01

    Functional MRI (fMRI) has grown to be the neuroimaging technique of choice for investigating brain function. This topical review provides an outline of fMRI methods and applications, with a particular emphasis on the recent advances provided by ultra-high field (UHF) scanners to allow functional mapping with greater sensitivity and improved spatial specificity. A short outline of the origin of the blood oxygenation level dependent (BOLD) contrast is provided, followed by a review of BOLD fMRI methods based on gradient-echo (GE) and spin-echo (SE) contrast. Phase based fMRI measures, as well as perfusion contrast obtained with the technique of arterial spin labelling (ASL), are also discussed. An overview of 7 T based functional neuroimaging is provided, outlining the potential advances to be made and technical challenges to be addressed.

  18. Memory fMRI predicts verbal memory decline after anterior temporal lobe resection

    OpenAIRE

    Sidhu, Meneka K; Stretton, Jason; Winston, Gavin P.; Symms, Mark; Thompson, Pamela J; Koepp, Matthias J; Duncan, John S.

    2015-01-01

    Objective: To develop a clinically applicable memory functional MRI (fMRI) method of predicting postsurgical memory outcome in individual patients. Methods: In this prospective cohort study, 50 patients with temporal lobe epilepsy (23 left) and 26 controls underwent an fMRI memory encoding paradigm of words with a subsequent out-of-scanner recognition assessment. Neuropsychological assessment was performed preoperatively and 4 months after anterior temporal lobe resection, and at equal time i...

  19. Plasticity of motor function and surgical outcomes in patients with cerebral arteriovenous malformation involving primary motor area:insight from fMRI and DTI

    Institute of Scientific and Technical Information of China (English)

    Lijun Wang; Fuxin Lin; Jun Wu; Yuming Jiao; Yong Cao; Yuanli Zhao; Shuo Wang

    2016-01-01

    Background:Patients who have a cerebral arteriovenous malformation (cAVMs) in the motor cortex can have displaced function. The finding and its relationship to recovery from surgery is not known. Methods:We present the five cases with cAVMs involving precentral knob and/or paracentral lobule and without preoperative motor deficits. We used motor activation areas derived from Functional functional MRI (fMRI) as a region of interesting (ROI) to launch the plasticity of cerebrospinal tracts (CST). All the results were incorporated into the neuronavigation platform for surgical treatment. Intraoperative electric cortical stimulation (ECS) was used to map motor areas. Modified Rankin Scale (mRS) of hands and feets were performed on postoperative day 2, 7 and at month 3, 6 during follow-up period. All the patients suffered from motor deficits regardless of cortical activation patterns. Results:Three patients showed functionally seeded CST in or around the AVM, and were validated by intraoperative electrical stimulation (ECS). Patient 4 had two aberrant functionally seeded fiber tracts away from the lesion, but were proved to be non-functional by postoperative motor deficits. Patient 3 with motor cortex and fiber tract within a diffuse AVMs nidus, complete paralysis of upper extremity after operation and has a persistent motor deficit during 6-month follow-up period. Conclusions:The plasticity of motor cortex on fMRI doesn’t prevent post-operative motor deficits. Functionally mapped fiber tract within or abutting AVM nidus predicts transient and persistent motor deficit.

  20. Functional connectivity of motor cortical network in patients with brachial plexus avulsion injury after contralateral cervical nerve transfer: a resting-state fMRI study

    Energy Technology Data Exchange (ETDEWEB)

    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.)

  1. Joint sparse representation of brain activity patterns in multi-task fMRI data.

    Science.gov (United States)

    Ramezani, M; Marble, K; Trang, H; Johnsrude, I S; Abolmaesumi, P

    2015-01-01

    A single-task functional magnetic resonance imaging (fMRI) experiment may only partially highlight alterations to functional brain networks affected by a particular disorder. Multivariate analysis across multiple fMRI tasks may increase the sensitivity of fMRI-based diagnosis. Prior research using multi-task analysis in fMRI, such as those that use joint independent component analysis (jICA), has mainly assumed that brain activity patterns evoked by different tasks are independent. This may not be valid in practice. Here, we use sparsity, which is a natural characteristic of fMRI data in the spatial domain, and propose a joint sparse representation analysis (jSRA) method to identify common information across different functional subtraction (contrast) images in data from a multi-task fMRI experiment. Sparse representation methods do not require independence, or that the brain activity patterns be nonoverlapping. We use functional subtraction images within the joint sparse representation analysis to generate joint activation sources and their corresponding sparse modulation profiles. We evaluate the use of sparse representation analysis to capture individual differences with simulated fMRI data and with experimental fMRI data. The experimental fMRI data was acquired from 16 young (age: 19-26) and 16 older (age: 57-73) adults obtained from multiple speech comprehension tasks within subjects, where an independent measure (namely, age in years) can be used to differentiate between groups. Simulation results show that this method yields greater sensitivity, precision, and higher Jaccard indexes (which measures similarity and diversity of the true and estimated brain activation sources) than does the jICA method. Moreover, superiority of the jSRA method in capturing individual differences was successfully demonstrated using experimental fMRI data.

  2. Contradictory Reasoning Network: An EEG and fMRI Study

    OpenAIRE

    Porcaro, Camillo; Medaglia, Maria Teresa; Thai, Ngoc Jade; Seri, Stefano; Rotshtein, Pia; Tecchio, Franca

    2014-01-01

    Contradiction is a cornerstone of human rationality, essential for everyday life and communication. We investigated electroencephalographic (EEG) and functional magnetic resonance imaging (fMRI) in separate recording sessions during contradictory judgments, using a logical structure based on categorical propositions of the Aristotelian Square of Opposition (ASoO). The use of ASoO propositions, while controlling for potential linguistic or semantic confounds, enabled us to observe the spatial ...

  3. Decoding the encoding of functional brain networks: An fMRI classification comparison of non-negative matrix factorization (NMF), independent component analysis (ICA), and sparse coding algorithms.

    Science.gov (United States)

    Xie, Jianwen; Douglas, Pamela K; Wu, Ying Nian; Brody, Arthur L; Anderson, Ariana E

    2017-04-15

    Brain networks in fMRI are typically identified using spatial independent component analysis (ICA), yet other mathematical constraints provide alternate biologically-plausible frameworks for generating brain networks. Non-negative matrix factorization (NMF) would suppress negative BOLD signal by enforcing positivity. Spatial sparse coding algorithms (L1 Regularized Learning and K-SVD) would impose local specialization and a discouragement of multitasking, where the total observed activity in a single voxel originates from a restricted number of possible brain networks. The assumptions of independence, positivity, and sparsity to encode task-related brain networks are compared; the resulting brain networks within scan for different constraints are used as basis functions to encode observed functional activity. These encodings are then decoded using machine learning, by using the time series weights to predict within scan whether a subject is viewing a video, listening to an audio cue, or at rest, in 304 fMRI scans from 51 subjects. The sparse coding algorithm of L1 Regularized Learning outperformed 4 variations of ICA (pcoding algorithms. Holding constant the effect of the extraction algorithm, encodings using sparser spatial networks (containing more zero-valued voxels) had higher classification accuracy (pcoding algorithms suggests that algorithms which enforce sparsity, discourage multitasking, and promote local specialization may capture better the underlying source processes than those which allow inexhaustible local processes such as ICA. Negative BOLD signal may capture task-related activations. Copyright © 2017 Elsevier B.V. All rights reserved.

  4. 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.

  5. Robust extrapolation scheme for fast estimation of 3D ising field partition functions: application to within-subject fMRI data analysis.

    Science.gov (United States)

    Risser, Laurent; Vincent, Thomas; Ciuciu, Philippe; Idier, Jérôme

    2009-01-01

    In this paper, we present a fast 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 a classical path-sampling method to approximate a small subset of reference PFs corresponding to prespecified regions. Then, the proposed extrapolation method allows us 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.

  6. 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)

  7. Altered Brain Functional Connectivity in Small-Cell Lung Cancer Patients after Chemotherapy Treatment: A Resting-State fMRI Study

    Directory of Open Access Journals (Sweden)

    Konstantinos Bromis

    2017-01-01

    Full Text Available Previous studies in small-cell lung cancer (SCLC patients have mainly focused on exploring neurocognitive deficits associated with prophylactic cranial irradiation (PCI. Little is known about functional brain alterations that might occur due to chemotherapy treatment in this population before PCI is administered. For this reason, we used resting-state functional Magnetic Resonance Imaging (fMRI to examine potential functional connectivity disruptions in brain networks, including the Default Mode Network (DMN, the Sensorimotor Network, and the Task-Positive Network (TPN. Nineteen SCLC patients after platinum-based chemotherapy treatment and thirteen controls were recruited in the current study. ROI-to-ROI and Seed-to-Voxel analyses were carried out and revealed functional connectivity deficits in patients within all the networks investigated demonstrating the possible negative effect of chemotherapy in cognitive functions in SCLC populations.

  8. 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

  9. Resting-State fMRI Functional Connectivity Is Associated with Sleepiness, Imagery, and Discontinuity of Mind

    NARCIS (Netherlands)

    Stoffers, D.; Diaz, B Alexander; Chen, Gang; den Braber, Anouk; van 't Ent, Dennis; Boomsma, Dorret I; Mansvelder, Huibert D; de Geus, Eco; Van Someren, Eus J W; Linkenkaer-Hansen, Klaus

    2015-01-01

    Resting-state functional magnetic resonance imaging (rs-fMRI) is widely used to investigate the functional architecture of the healthy human brain and how it is affected by learning, lifelong development, brain disorders or pharmacological intervention. Non-sensory experiences are prevalent during

  10. Lateralisation of cerebral response to active acupuncture in patients with unilateral ischaemic stroke: an fMRI study

    National Research Council Canada - National Science Library

    Huang, Yong; Chen, Jun-Qi; Lai, Xin-Sheng; Tang, Chun-Zhi; Yang, Jun-Jun; Chen, Hua; Wu, Jun-Xian; Xiao, Hui-Ling; Qu, Shan-Shan; Zhang, Yi-Dan; Zhang, Zhang-Jin

    2013-01-01

    Acupuncture is beneficial in treating stroke neuropsychiatric symptoms. The present study aimed to identify functional brain response to active acupuncture in patients with unilateral ischaemic stroke using functional MRI (fMRI...

  11. State-space model with deep learning for functional dynamics estimation in resting-state fMRI.

    Science.gov (United States)

    Suk, Heung-Il; Wee, Chong-Yaw; Lee, Seong-Whan; Shen, Dinggang

    2016-04-01

    Studies on resting-state functional Magnetic Resonance Imaging (rs-fMRI) have shown that different brain regions still actively interact with each other while a subject is at rest, and such functional interaction is not stationary but changes over time. In terms of a large-scale brain network, in this paper, we focus on time-varying patterns of functional networks, i.e., functional dynamics, inherent in rs-fMRI, which is one of the emerging issues along with the network modelling. Specifically, we propose a novel methodological architecture that combines deep learning and state-space modelling, and apply it to rs-fMRI based Mild Cognitive Impairment (MCI) diagnosis. We first devise a Deep Auto-Encoder (DAE) to discover hierarchical non-linear functional relations among regions, by which we transform the regional features into an embedding space, whose bases are complex functional networks. Given the embedded functional features, we then use a Hidden Markov Model (HMM) to estimate dynamic characteristics of functional networks inherent in rs-fMRI via internal states, which are unobservable but can be inferred from observations statistically. By building a generative model with an HMM, we estimate the likelihood of the input features of rs-fMRI as belonging to the corresponding status, i.e., MCI or normal healthy control, based on which we identify the clinical label of a testing subject. In order to validate the effectiveness of the proposed method, we performed experiments on two different datasets and compared with state-of-the-art methods in the literature. We also analyzed the functional networks learned by DAE, estimated the functional connectivities by decoding hidden states in HMM, and investigated the estimated functional connectivities by means of a graph-theoretic approach. Copyright © 2016 Elsevier Inc. All rights reserved.

  12. 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.

  13. Neurophysiologic correlates of fMRI in human motor cortex.

    Science.gov (United States)

    Hermes, Dora; Miller, Kai J; Vansteensel, Mariska J; Aarnoutse, Erik J; Leijten, Frans S S; Ramsey, Nick F

    2012-07-01

    The neurophysiological underpinnings of functional magnetic resonance imaging (fMRI) are not well understood. To understand the relationship between the fMRI blood oxygen level dependent (BOLD) signal and neurophysiology across large areas of cortex, we compared task related BOLD change during simple finger movement to brain surface electric potentials measured on a similar spatial scale using electrocorticography (ECoG). We found that spectral power increases in high frequencies (65-95 Hz), which have been related to local neuronal activity, colocalized with spatially focal BOLD peaks on primary sensorimotor areas. Independent of high frequencies, decreases in low frequency rhythms (neurophysiological mechanisms, one being spatially focal neuronal processing and the other spatially distributed low frequency rhythms. Copyright © 2011 Wiley-Liss, Inc.

  14. Compressed Sensing for fMRI: Feasibility Study on the Acceleration of Non-EPI fMRI at 9.4T

    Directory of Open Access Journals (Sweden)

    Paul Kyu Han

    2015-01-01

    Full Text Available Conventional functional magnetic resonance imaging (fMRI technique known as gradient-recalled echo (GRE echo-planar imaging (EPI is sensitive to image distortion and degradation caused by local magnetic field inhomogeneity at high magnetic fields. Non-EPI sequences such as spoiled gradient echo and balanced steady-state free precession (bSSFP have been proposed as an alternative high-resolution fMRI technique; however, the temporal resolution of these sequences is lower than the typically used GRE-EPI fMRI. One potential approach to improve the temporal resolution is to use compressed sensing (CS. In this study, we tested the feasibility of k-t FOCUSS—one of the high performance CS algorithms for dynamic MRI—for non-EPI fMRI at 9.4T using the model of rat somatosensory stimulation. To optimize the performance of CS reconstruction, different sampling patterns and k-t FOCUSS variations were investigated. Experimental results show that an optimized k-t FOCUSS algorithm with acceleration by a factor of 4 works well for non-EPI fMRI at high field under various statistical criteria, which confirms that a combination of CS and a non-EPI sequence may be a good solution for high-resolution fMRI at high fields.

  15. fMRI reliability in subjects with stroke.

    Science.gov (United States)

    Kimberley, Teresa Jacobson; Khandekar, Gauri; Borich, Michael

    2008-03-01

    Functional MRI (fMRI) has become one of the most commonly used neuroimaging tools to assess the cortical effects associated with rehabilitation, learning, or disease recovery in subjects with stroke. Despite this, there has been no systematic study of the reliability of the fMR signal in this population. The purpose of this study was to examine the within- and between-session reliability of fMRI in cortical and cerebellar structures in subjects with stroke during a complex, continuous visual motor task performed with the less affected hand. Nine subjects with stroke underwent four testing trials during two sessions separated by three weeks. Subjects performed a drawing task using an MRI compatible joystick while in the MRI. Methods of analysis evaluated included: percent signal intensity change, active voxel count and a voxel by voxel stat value analysis within and between testing sessions. Reliability was determined with Interclass correlation coefficients (ICC) in the following regions of interest: primary motor (M1), primary sensory (S1), premotor cortex (PMC), medial cerebellum (MCB), and lateral cerebellum (LCB). Results indicate that intensity change has superior reliability to the other methods of analysis (Average ICC across brain regions and trials: intensity change: 0.73, voxel count: 0.58, voxel by voxel: 0.67) and that generally with any analysis method, within-session reliability was higher than between-session, as indicated by higher ICC values across brain regions. Overall, when comparing between-session results, moderate to good reliability was obtained with intensity change (ICC: M1: 0.52, S1: 0.80, SMA: 0.78, PMC: 0.94, MCB: 0.86, and LCB: 0.59). These results show good reliability in subjects with stroke when performing a continuous motor task. These findings give confidence for interpreting fMRI test/retest research in subjects with stroke.

  16. A fMRI Data Processing Method Using a New Composite ICA Algorithm

    Institute of Scientific and Technical Information of China (English)

    CHENHuafu; ZHOUQun; YAODezhong; ZENGMin

    2004-01-01

    One of the reasons Independent component analysis (ICA) becoming so popular is that ICA is a promising tool for signal process application, such as Functional magnetic resonance imaging (fMRI) data processing. However, there are still some problems to be solved. Most ICA algorithms are not stable in fMRI data processing. This paper presents a novel composite ICA algorithm integrating fixed-point algorithm and natural gradient algorithm for brain activity localization in Functional magnetic resonance imaging (fMRI) data. The new composite ICA algorithm has overcome the drawbacks of the both algorithms, providing more accurate and fast detection of weak fMRI functional signals. Simulations show great performance improvement compared with correlation analysis and Automated functional neuro imaging (AfNI) software.

  17. Resting-State fMRI Functional Connectivity Is Associated with Sleepiness, Imagery, and Discontinuity of Mind

    Science.gov (United States)

    Chen, Gang; den Braber, Anouk; van ‘t Ent, Dennis; Boomsma, Dorret I.; Mansvelder, Huibert D.; de Geus, Eco; Van Someren, Eus J. W.; Linkenkaer-Hansen, Klaus

    2015-01-01

    Resting-state functional magnetic resonance imaging (rs-fMRI) is widely used to investigate the functional architecture of the healthy human brain and how it is affected by learning, lifelong development, brain disorders or pharmacological intervention. Non-sensory experiences are prevalent during rest and must arise from ongoing brain activity, yet little is known about this relationship. Here, we used two runs of rs-fMRI both immediately followed by the Amsterdam Resting-State Questionnaire (ARSQ) to investigate the relationship between functional connectivity within ten large-scale functional brain networks and ten dimensions of thoughts and feelings experienced during the scan in 106 healthy participants. We identified 11 positive associations between brain-network functional connectivity and ARSQ dimensions. ‘Sleepiness’ exhibited significant associations with functional connectivity within Visual, Sensorimotor and Default Mode networks. Similar associations were observed for ‘Visual Thought’ and ‘Discontinuity of Mind’, which may relate to variation in imagery and thought control mediated by arousal fluctuations. Our findings show that self-reports of thoughts and feelings experienced during a rs-fMRI scan help understand the functional significance of variations in functional connectivity, which should be of special relevance to clinical studies. PMID:26540239

  18. Matched-filter acquisition for BOLD fMRI.

    Science.gov (United States)

    Kasper, Lars; Haeberlin, Maximilian; Dietrich, Benjamin E; Gross, Simon; Barmet, Christoph; Wilm, Bertram J; Vannesjo, S Johanna; Brunner, David O; Ruff, Christian C; Stephan, Klaas E; Pruessmann, Klaas P

    2014-10-15

    We introduce matched-filter fMRI, which improves BOLD (blood oxygen level dependent) sensitivity by variable-density image acquisition tailored to subsequent image smoothing. Image smoothing is an established post-processing technique used in the vast majority of fMRI studies. Here we show that the signal-to-noise ratio of the resulting smoothed data can be substantially increased by acquisition weighting with a weighting function that matches the k-space filter imposed by the smoothing operation. We derive the theoretical SNR advantage of this strategy and propose a practical implementation of 2D echo-planar acquisition matched to common Gaussian smoothing. To reliably perform the involved variable-speed trajectories, concurrent magnetic field monitoring with NMR probes is used. Using this technique, phantom and in vivo measurements confirm reliable SNR improvement in the order of 30% in a "resting-state" condition and prove robust in different regimes of physiological noise. Furthermore, a preliminary task-based visual fMRI experiment equally suggests a consistent BOLD sensitivity increase in terms of statistical sensitivity (average t-value increase of about 35%). In summary, our study suggests that matched-filter acquisition is an effective means of improving BOLD SNR in studies that rely on image smoothing at the post-processing level. Copyright © 2014 Elsevier Inc. All rights reserved.

  19. Assessment of biofeedback rehabilitation in post-stroke patients combining fMRI and gait analysis: a case study

    OpenAIRE

    Del Din, Silvia; Bertoldo, Alessandra; Sawacha, Zimi; Jonsdottir, Johanna; Rabuffetti, Marco; Cobelli, Claudio; Ferrarin, Maurizio

    2014-01-01

    Background The ability to walk independently is a primary goal for rehabilitation after stroke. Gait analysis provides a great amount of valuable information, while functional magnetic resonance imaging (fMRI) offers a powerful approach to define networks involved in motor control. The present study reports a new methodology based on both fMRI and gait analysis outcomes in order to investigate the ability of fMRI to reflect the phases of motor learning before/after electromyographic biofeedba...

  20. 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...... 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...... have been described. Still, to take full advantage of simultaneously recorded VEP-fMRI one would ideally want to track single-trial changes in the VEP and use this information in the fMRI analysis. In order to do this we examined 10 healthy volunteers with simultaneous VEP-fMRI. Different measures...

  1. Sequential Dictionary Learning From Correlated Data: Application to fMRI Data Analysis.

    Science.gov (United States)

    Seghouane, Abd-Krim; Iqbal, Asif

    2017-03-22

    Sequential dictionary learning via the K-SVD algorithm has been revealed as a successful alternative to conventional data driven methods such as independent component analysis (ICA) for functional magnetic resonance imaging (fMRI) data analysis. fMRI datasets are however structured data matrices with notions of spatio-temporal correlation and temporal smoothness. This prior information has not been included in the K-SVD algorithm when applied to fMRI data analysis. In this paper we propose three variants of the K-SVD algorithm dedicated to fMRI data analysis by accounting for this prior information. The proposed algorithms differ from the K-SVD in their sparse coding and dictionary update stages. The first two algorithms account for the known correlation structure in the fMRI data by using the squared Q, R-norm instead of the Frobenius norm for matrix approximation. The third and last algorithm account for both the known correlation structure in the fMRI data and the temporal smoothness. The temporal smoothness is incorporated in the dictionary update stage via regularization of the dictionary atoms obtained with penalization. The performance of the proposed dictionary learning algorithms are illustrated through simulations and applications on real fMRI data.

  2. [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.

  3. 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.

  4. Independent Component Analysis for fMRI: What is Signal and What is Noise?

    DEFF Research Database (Denmark)

    McKeown, Martin; Hansen, Lars Kai; Sejnowski, Terrence J.

    2003-01-01

    Many sources of fluctuation contribute to the functional magnetic resonance imaging (fMRI) signal, complicating attempts to infer those changes that are truly related to brain activation. Unlike methods of analysis of fMRI data that test the time course of each voxel against a hypothesized waveform...... that are not time-locked to an easily specified sensory or motor event. These methods can be further improved by incorporating prior knowledge regarding the temporal and spatial extent of brain activation....

  5. 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...

  6. Assessing the function of the fronto-parietal attention network: insights from resting-state fMRI and the attentional network test.

    Science.gov (United States)

    Markett, Sebastian; Reuter, Martin; Montag, Christian; Voigt, Gesine; Lachmann, Bernd; Rudorf, Sarah; Elger, Christian E; Weber, Bernd

    2014-04-01

    In the recent past, various intrinsic connectivity networks (ICN) have been identified in the resting brain. It has been hypothesized that the fronto-parietal ICN is involved in attentional processes. Evidence for this claim stems from task-related activation studies that show a joint activation of the implicated brain regions during tasks that require sustained attention. In this study, we used functional magnetic resonance imaging (fMRI) to demonstrate that functional connectivity within the fronto-parietal network at rest directly relates to attention. We applied graph theory to functional connectivity data from multiple regions of interest and tested for associations with behavioral measures of attention as provided by the attentional network test (ANT), which we acquired in a separate session outside the MRI environment. We found robust statistical associations with centrality measures of global and local connectivity of nodes within the network with the alerting and executive control subfunctions of attention. The results provide further evidence for the functional significance of ICN and the hypothesized role of the fronto-parietal attention network.

  7. Mapping the functional network of medial prefrontal cortex by combining optogenetics and fMRI in awake rats.

    Science.gov (United States)

    Liang, Zhifeng; Watson, Glenn D R; Alloway, Kevin D; Lee, Gangchea; Neuberger, Thomas; Zhang, Nanyin

    2015-08-15

    The medial prefrontal cortex (mPFC) plays a critical role in multiple cognitive and limbic functions. Given its vital importance, investigating the function of individual mPFC circuits in animal models has provided critical insight into the neural basis underlying different behaviors and psychiatric conditions. However, our knowledge regarding the mPFC whole-brain network stays largely at the anatomical level, while the functional network of mPFC, which can be dynamic in different conditions or following manipulations, remains elusive especially in awake rodents. Here we combined optogenetic stimulation and functional magnetic resonance imaging (opto-fMRI) to reveal the network of brain regions functionally activated by mPFC outputs in awake rodents. Our data showed significant increases in blood-oxygenation-level dependent (BOLD) signals in prefrontal, striatal and limbic regions when mPFC was optically stimulated. This activation pattern was robust, reproducible, and did not depend on the stimulation period in awake rats. BOLD signals, however, were substantially reduced when animals were anesthetized. In addition, regional brain activation showing increased BOLD signals during mPFC stimulation was corroborated by electrophysiological recordings. These results expand the applicability of the opto-fMRI approach from sensorimotor processing to cognition-related networks in awake rodents. Importantly, it may help elucidate the circuit mechanisms underlying numerous mPFC-related functions and behaviors that need to be assessed in the awake state.

  8. 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

    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...... by a global hypercapnia-induced BOLD signal. To demonstrate the effectiveness of the BOLD normalization approach, gradient-echo BOLD fMRI at 1.5, 4, and 7 T and spin-echo BOLD fMRI at 4 T were performed in human subjects. For neural stimulation, subjects performed sequential finger movements at 2 Hz, while...... 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...

  9. 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.

  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. Bayesian networks for fMRI: a primer.

    Science.gov (United States)

    Mumford, Jeanette A; Ramsey, Joseph D

    2014-02-01

    Bayesian network analysis is an attractive approach for studying the functional integration of brain networks, as it includes both the locations of connections between regions of the brain (functional connectivity) and more importantly the direction of the causal relationship between the regions (directed functional connectivity). Further, these approaches are more attractive than other functional connectivity analyses in that they can often operate on larger sets of nodes and run searches over a wide range of candidate networks. An important study by Smith et al. (2011) illustrated that many Bayesian network approaches did not perform well in identifying the directionality of connections in simulated single-subject data. Since then, new Bayesian network approaches have been developed that have overcome the failures in the Smith work. Additionally, an important discovery was made that shows a preprocessing step used in the Smith data puts some of the Bayesian network methods at a disadvantage. This work provides a review of Bayesian network analyses, focusing on the methods used in the Smith work as well as methods developed since 2011 that have improved estimation performance. Importantly, only approaches that have been specifically designed for fMRI data perform well, as they have been tailored to meet the challenges of fMRI data. Although this work does not suggest a single best model, it describes the class of models that perform best and highlights the features of these models that allow them to perform well on fMRI data. Specifically, methods that rely on non-Gaussianity to direct causal relationships in the network perform well.

  12. Sexually dimorphic functional connectivity in response to high vs. low energy-dense food cues in obese humans: an fMRI study.

    Science.gov (United States)

    Atalayer, Deniz; Pantazatos, Spiro P; Gibson, Charlisa D; McOuatt, Haley; Puma, Lauren; Astbury, Nerys M; Geliebter, Allan

    2014-10-15

    Sexually-dimorphic behavioral and biological aspects of human eating have been described. Using psychophysiological interaction (PPI) analysis, we investigated sex-based differences in functional connectivity with a key emotion-processing region (amygdala, AMG) and a key reward-processing area (ventral striatum, VS) in response to high vs. low energy-dense (ED) food images using blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) in obese persons in fasted and fed states. When fed, in response to high vs. low-ED food cues, obese men (vs. women) had greater functional connectivity with AMG in right subgenual anterior cingulate, whereas obese women had greater functional connectivity with AMG in left angular gyrus and right primary motor areas. In addition, when fed, AMG functional connectivity with pre/post-central gyrus was more associated with BMI in women (vs. men). When fasted, obese men (vs. women) had greater functional connectivity with AMG in bilateral supplementary frontal and primary motor areas, left precuneus, and right cuneus, whereas obese women had greater functional connectivity with AMG in left inferior frontal gyrus, right thalamus, and dorsomedial prefrontal cortex. When fed, greater functional connectivity with VS was observed in men in bilateral supplementary and primary motor areas, left postcentral gyrus, and left precuneus. These sex-based differences in functional connectivity in response to visual food cues may help partly explain differential eating behavior, pathology prevalence, and outcomes in men and women.

  13. Multi-echo fMRI: A review of applications in fMRI denoising and analysis of BOLD signals.

    Science.gov (United States)

    Kundu, Prantik; Voon, Valerie; Balchandani, Priti; Lombardo, Michael V; Poser, Benedikt A; Bandettini, Peter A

    2017-07-01

    In recent years the field of fMRI research has enjoyed expanded technical abilities related to resolution, as well as use across many fields of brain research. At the same time, the field has also dealt with uncertainty related to many known and unknown effects of artifact in fMRI data. In this review we discuss an emerging fMRI technology, called multi-echo (ME)-fMRI, which focuses on improving the fidelity and interpretability of fMRI. Where the essential problem of standard single-echo fMRI is the indeterminacy of sources of signals, whether BOLD or artifact, this is not the case for ME-fMRI. By acquiring multiple echo images per slice, the ME approach allows T2* decay to be modeled at every voxel at every time point. Since BOLD signals arise by changes in T2* over time, an fMRI experiment sampling the T2* signal decay can be analyzed to distinguish BOLD from artifact signal constituents. While the ME approach has a long history of use in theoretical and validation studies, modern MRI systems enable whole-brain multi-echo fMRI at high resolution. This review covers recent multi-echo fMRI acquisition methods, and the analysis steps for this data to make fMRI at once more principled, straightforward, and powerful. After a brief overview of history and theory, T2* modeling and applications will be discussed. These applications include T2* mapping and combining echoes from ME data to increase BOLD contrast and mitigate dropout artifacts. Next, the modeling of fMRI signal changes to detect signal origins in BOLD-related T2* versus artifact-related S0 changes will be reviewed. A focus is on the use of ME-fMRI data to extract and classify components from spatial ICA, called multi-echo ICA (ME-ICA). After describing how ME-fMRI and ME-ICA lead to a general model for analysis of fMRI signals, applications in animal and human imaging will be discussed. Applications include removing motion artifacts in resting state data at subject and group level. New imaging methods such

  14. 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).

  15. A multifunctional method (ERP and fMRI of analysis on facial expression. Three pilot studies

    Directory of Open Access Journals (Sweden)

    Galit Yovel

    2007-04-01

    Full Text Available As social primates, one of the most important cognitive tasks we conduct, dozens of times a day, is to look at a face and extract the person's identity. During the last decade, the neural basis of face processing has been extensively investigated in humans with event-related potential (ERP and functional MRI (fMRI. These two methods provide complementary information about the temporal and spatial aspects of the neural response, with ERPs allowing high temporal resolution of milliseconds but low spatial resolution of the neural generator and fMRI displaying a slow hemodynamic response but better spatial localization of the activated regions. Despite the extensive fMRI and ERP research of faces, only a few studies have assessed the relationship between the two methods and no study to date have collected simultaneous ERP and fMRI responses to face stimuli. In the current paper we will try to assess the spatial and temporal aspects of the neural response to faces by simultaneously collecting functional MRI and event-related potentials (ERP to face stimuli. Our goals are twofold: 1 ERP and fMRI show a robust selective response to faces. In particular, two well-established face-specific phenomena, the RH superiority and the inversion effect are robustly found with both ERP and fMRI. Despite the extensive research of these effects with ERP and fMRI, it is still unknown to what extent their spatial (fMRI and temporal (ERP aspects are associated. In Study 1 we will employ an individual differences approach, to assess the relationship between these ERP and fMRI face-specific responses. 2 Face processing involves several stages starting from structural encoding of the face image through identity processing to storage for later retrieval. This representation undergoes several manipulations that take place at different time points and in different brain regions before the final percept is generated. By simultaneously recording ERP and fMRI we hope to gain a

  16. Depletion of brain functional connectivity enhancement leads to disability progression in multiple sclerosis: A longitudinal resting-state fMRI study.

    Science.gov (United States)

    Faivre, Anthony; Robinet, Emmanuelle; Guye, Maxime; Rousseau, Celia; Maarouf, Adil; Le Troter, Arnaud; Zaaraoui, Wafaa; Rico, Audrey; Crespy, Lydie; Soulier, Elisabeth; Confort-Gouny, Sylviane; Pelletier, Jean; Achard, Sophie; Ranjeva, Jean-Philippe; Audoin, Bertrand

    2016-11-01

    The compensatory effect of brain functional connectivity enhancement in relapsing-remitting multiple sclerosis (RRMS) remains controversial. To characterize the relationships between brain functional connectivity changes and disability progression in RRMS. Long-range connectivity, short-range connectivity, and density of connections were assessed using graph theoretical analysis of resting-state functional magnetic resonance imaging (fMRI) data acquired in 38 RRMS patients (disease duration: 120 ± 32 months) and 24 controls. All subjects were explored at baseline and all patients and six controls 2 years later. At baseline, levels of long-range and short-range brain functional connectivity were higher in patients compared to controls. During the follow-up, decrease in connections' density was inversely correlated with disability progression. Post-hoc analysis evidenced differential evolution of brain functional connectivity metrics in patients according to their level of disability at baseline: while patients with lowest disability at baseline experienced an increase in all connectivity metrics during the follow-up, patients with higher disability at baseline showed a decrease in the connectivity metrics. In these patients, decrease in the connectivity metrics was associated with disability progression. The study provides two main findings: (1) brain functional connectivity enhancement decreases during the disease course after reaching a maximal level, and (2) decrease in brain functional connectivity enhancement participates in disability progression. © The Author(s), 2016.

  17. 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.

    Science.gov (United States)

    Hou, Bob L; Bhatia, Sanjay; Carpenter, Jeffrey S

    2016-01-01

    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.

  18. 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.

  19. Paradigm-free mapping with morphological component analysis: getting most out of fMRI data

    Science.gov (United States)

    Caballero Gaudes, César; Van De Ville, Dimitri; Petridou, Natalia; Lazeyras, François; Gowland, Penny

    2011-09-01

    Functional magnetic resonance imaging (fMRI) is a non-invasive imaging technique that maps the brain's response to neuronal activity based on the blood oxygenation level dependent (BOLD) effect. This work proposes a novel method for fMRI data analysis that enables the decomposition of the fMRI signal in its sources based on morphological descriptors. Beyond traditional fMRI hypothesis-based or blind data-driven exploratory approaches, this method allows the detection of BOLD responses without prior timing information. It is based on the deconvolution of the neuronal-related haemodynamic component of the fMRI signal with paradigm free mapping and also furnishes estimates of the movement-related effects, instrumental drifts and physiological fluctuations. Our algorithm is based on an overcomplete representation of the fMRI voxel time series with an additive linear model that is recovered by means of a L1-norm regularized least-squares estimators and an adapted block coordinate relaxation procedure. The performance of the technique is evaluated with simulated data and real experimental data acquired at 3T.

  20. The neuroscience of investing: fMRI of the reward system.

    Science.gov (United States)

    Peterson, Richard L

    2005-11-15

    Functional magnetic resonance imaging (fMRI) has proven a useful tool for observing neural BOLD signal changes during complex cognitive and emotional tasks. Yet the meaning and applicability of the fMRI data being gathered is still largely unknown. The brain's reward system underlies the fundamental neural processes of goal evaluation, preference formation, positive motivation, and choice behavior. fMRI technology allows researchers to dynamically visualize reward system processes. Experimenters can then correlate reward system BOLD activations with experimental behavior from carefully controlled experiments. In the SPAN lab at Stanford University, directed by Brian Knutson Ph.D., researchers have been using financial tasks during fMRI scanning to correlate emotion, behavior, and cognition with the reward system's fundamental neural activations. One goal of the SPAN lab is the development of predictive models of behavior. In this paper we extrapolate our fMRI results toward understanding and predicting individual behavior in the uncertain and high-risk environment of the financial markets. The financial market price anomalies of "value versus glamour" and "momentum" may be real-world examples of reward system activation biasing collective behavior. On the individual level, the investor's bias of overconfidence may similarly be related to reward system activation. We attempt to understand selected "irrational" investor behaviors and anomalous financial market price patterns through correlations with findings from fMRI research of the reward system.

  1. An fMRI study of visual attention and sensorimotor function before and after antipsychotic treatment in first-episode schizophrenia.

    Science.gov (United States)

    Keedy, Sarah K; Rosen, Cherise; Khine, Tin; Rajarethinam, Rajaprabhakaran; Janicak, Philip G; Sweeney, John A

    2009-04-30

    While much is known about receptor affinity profiles of antipsychotic medications, less is known about their impact on functional brain systems in patients with schizophrenia. We conducted functional magnetic resonance imaging (fMRI) studies with first-episode schizophrenia patients as they made saccades to unpredictable visual targets before and after 4-6 weeks of antipsychotic treatment. Matched healthy individuals were scanned at similar time intervals. Pretreatment, patients had less activation in frontal and parietal eye fields and cerebellum. After treatment these disturbances were not present, suggesting improved function in attentional and sensorimotor systems. Other pretreatment abnormalities were noted in sensory and ventromedial prefrontal cortex, but after treatment these abnormalities were absent or less prominent, in line with improved function in attentional systems. In addition, although not abnormal at baseline, there was reduced activity after treatment in dorsal prefrontal cortex, dorsal striatum, and dorsomedial thalamus, suggesting a potential adverse effect of treatment on frontostriatal systems, perhaps related to dopamine blockade in the caudate. These findings provide evidence for a complex impact of antipsychotic medication on functional brain systems in schizophrenia and illustrate the potential of neuroimaging biomarkers for both adverse and beneficial drug effects on functional brain systems.

  2. A study-specific fMRI normalization approach that operates directly on high resolution functional EPI data at 7 Tesla.

    Science.gov (United States)

    Grabner, Günther; Poser, Benedikt A; Fujimoto, Kyoko; Polimeni, Jonathan R; Wald, Lawrence L; Trattnig, Siegfried; Toni, Ivan; Barth, Markus

    2014-10-15

    Due to the availability of ultra-high field scanners and novel imaging methods, high resolution, whole brain functional MR imaging (fMRI) has become increasingly feasible. However, it is common to use extensive spatial smoothing to account for inter-subject anatomical variation when pooling over subjects. This reduces the spatial details of group level functional activation considerably, even when the original data was acquired with high resolution. In our study we used an accelerated 3D EPI sequence at 7 Tesla to acquire whole brain fMRI data with an isotropic spatial resolution of 1.1mm which shows clear gray/white matter contrast due to the stronger T1 weighting of 3D EPI. To benefit from the high spatial resolution on the group level, we develop a study specific, high resolution anatomical template which is facilitated by the good anatomical contrast that is present in the average functional EPI images. Different template generations with increasing accuracy were created by using a hierarchical linear and stepwise non-linear registration approach. As the template is based on the functional data themselves no additional co-registration step with the usual T1-weighted anatomical data is necessary which eliminates a potential source of misalignment. To test the improvement of functional localization and spatial details we performed a group level analysis of a finger tapping experiment in eight subjects. The most accurate template shows better spatial localization--such as a separation of somatosensory and motor areas and of single digit activation--compared to the simple linear registration. The number of activated voxels is increased by a factor of 1.2, 2.5, and 3.1 for somatosensory, supplementary motor area, and dentate nucleus, respectively, for the functional contrast between left versus right hand. Similarly, the number of activated voxels is increased 1.4- and 2.4-fold for right little versus right index finger and left little versus left index finger

  3. Motion or activity: their role in intra- and inter-subject variation in fMRI

    DEFF Research Database (Denmark)

    Lund, Torben E; Nørgaard, Minna D; Rostrup, Egill

    2005-01-01

    Functional MRI (fMRI) carries the potential for non-invasive measurements of brain activity. Typically, what are referred to as activation images are actually thresholded statistical parametric maps. These maps possess large inter-session variability. This is especially problematic when applying ...

  4. Novelty increases the mesolimbic functional connectivity of the substantia nigra/ventral tegmental area (SN/VTA) during reward anticipation: Evidence from high-resolution fMRI.

    Science.gov (United States)

    Krebs, R M; Heipertz, D; Schuetze, H; Duzel, E

    2011-09-15

    Reward and novelty are potent learning signals that critically rely on dopaminergic midbrain responses. Recent findings suggest that although reward and novelty are likely to interact, both functions may be subserved by distinct neuronal clusters. We used high-resolution functional magnetic resonance imaging (fMRI) to isolate neural responses to reward and novelty within the human substantia nigra/ventral tegmental area (SN/VTA) complex to investigate the spatial delineation and integration of reward- and novelty-related activity clusters. We demonstrate that distinct clusters within the caudal portion of the medial SN/VTA and the lateral portion of the right SN are predominantly modulated by the anticipation of reward, while a more rostral part of the medial SN/VTA was exclusively modulated by novelty. In addition, the caudal medial SN/VTA cluster embodied an interaction between novelty and reward where novelty selectively increased reward-anticipation responses. This interaction, in turn, was paralleled by differences in the functional-connectivity patterns of these SN/VTA regions. Specifically, novel as compared to familiar reward-predictive stimuli increased the functional connectivity of the medial SN/VTA with mesolimbic regions, including the nucleus accumbens and the hippocampus, as well as with the primary visual cortex. This functional correlation may highlight how afferents of the medial SN/VTA provide integrative information about novelty and reward, or, alternatively, how medial SN/VTA activity may modulate memory processes for novel events associated with rewards.

  5. A comparison of brain activity evoked by single content and function words: an fMRI investigation of implicit word processing.

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    Diaz, Michele T; McCarthy, Gregory

    2009-07-28

    Content and function words have different roles in language and differ greatly in their semantic content. Although previous research has suggested that these different roles may be mediated by different neural substrates, the neuroimaging literature on this topic is particularly scant. Moreover, fMRI studies that have investigated differences between content and function words have utilized tasks that focus the subjects' attention on the differences between these word types. It is possible, then, that task-related differences in attention, working memory, and decision-making contribute to the differential patterns of activation observed. Here, subjects were engaged in a continuous working memory cover task while single, task-irrelevant content and function words were infrequently and irregularly presented. Nonword letter strings were displayed in black font at a fast rate (2/s). Subjects were required to either remember or retrieve occasional nonwords that were presented in colored fonts. Incidental and irrelevant to the memory task, content and function words were interspersed among nonwords at intervals of 12 to 15 s. Both word types strongly activated temporal-parietal cortex, middle and anterior temporal cortex, inferior frontal gyrus, parahippocampal gyrus, and orbital frontal cortex. Activations were more extensive in the left hemisphere. Content words elicited greater activation than function words in middle and anterior temporal cortex, a sub-region of orbital frontal cortex, and the parahippocampal region. Words also evoked extensive deactivation, most notably in brain regions previously associated with working memory and attention.

  6. Recovery of directed intracortical connectivity from fMRI data

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    Gilson, Matthieu; Ritter, Petra; Deco, Gustavo

    2016-06-01

    The brain exhibits complex spatio-temporal patterns of activity. In particular, its baseline activity at rest has a specific structure: imaging techniques (e.g., fMRI, EEG and MEG) show that cortical areas experience correlated fluctuations, which is referred to as functional connectivity (FC). The present study relies on our recently developed model in which intracortical white-matter connections shape noise-driven fluctuations to reproduce FC observed in experimental data (here fMRI BOLD signal). Here noise has a functional role and represents the variability of neural activity. The model also incorporates anatomical information obtained using diffusion tensor imaging (DTI), which estimates the density of white-matter fibers (structural connectivity, SC). After optimization to match empirical FC, the model provides an estimation of the efficacies of these fibers, which we call effective connectivity (EC). EC differs from SC, as EC not only accounts for the density of neural fibers, but also the concentration of synapses formed at their end, the type of neurotransmitters associated and the excitability of target neural populations. In summary, the model combines anatomical SC and activity FC to evaluate what drives the neural dynamics, embodied in EC. EC can then be analyzed using graph theory to understand how it generates FC and to seek for functional communities among cortical areas (parcellation of 68 areas). We find that intracortical connections are not symmetric, which affects the dynamic range of cortical activity (i.e., variety of states it can exhibit).

  7. Is the center of mass (COM) a reliable parameter for the localization of brain function in fMRI?

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    Fesl, G; Braun, B; Rau, S; Wiesmann, M; Ruge, M; Bruhns, P; Linn, J; Stephan, T; Ilmberger, J; Tonn, J-C; Brückmann, H

    2008-05-01

    The center of mass (COM) in functional MRI studies is defined as the center of a cerebral activation cluster. Although the COM is a well-accepted parameter for exactly localizing brain function, the reliability of COMs has not received much attention until now. Our goal was to investigate COM reliability as a function of the thresholding technique, the threshold level, and the type of COM calculation. Therefore 15 subjects were examined repeatedly using simple hand and tongue movement paradigms. Postprocessing was performed with uncorrected, corrected, and proportional thresholding as well as different threshold levels. Geometric and T-weighted COMs of left-hemispheric primary hand and tongue motor clusters were calculated. The COM variation was evaluated within and between repeated sessions depending on the different postprocessing setups. Mean COM variations over three repeated sessions varied between 1.6 mm and 9.8 mm for the hand paradigm and between 7.0 mm and 14.4 mm for the tongue task. Stringent thresholding techniques and high threshold levels were required to assess reliable results, whereas the kind of COM calculation was of lesser relevance. Thus, COM reliability cannot be presupposed; it depends strongly on the individual postprocessing techniques. This should be considered when using COMs for localizing brain function.

  8. Optimized design and analysis of sparse-sampling fMRI experiments

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    Tyler K Perrachione

    2013-04-01

    Full Text Available Sparse-sampling is an important methodological advance in functional magnetic resonance imaging (fMRI, in which silent delays are introduced between MR volume acquisitions, allowing for the presentation of auditory stimuli without contamination by acoustic scanner noise and for overt vocal responses without motion-induced artifacts in the functional timeseries. As such, the sparse-sampling technique has become a mainstay of principled fMRI research into the cognitive and systems neuroscience of speech, language, hearing, and music. Despite being in use for over a decade, there has been little systematic investigation of the acquisition parameters, experimental design considerations, and statistical analysis approaches that bear on the results and interpretation of sparse-sampling fMRI experiments. In this report, we examined how design and analysis choices related to the duration of repetition time (TR delay (an acquisition parameter, stimulation rate (an experimental design parameter and model basis function (an analysis parameter act independently and interactively to affect the neural activation profiles observed in fMRI. First, we conducted a series of computational simulations to explore the parameter space of sparse design and analysis with respect to these variables; second, we validated the results of these simulations in a series of sparse-sampling fMRI experiments. Overall, these experiments suggest three methodological approaches that can, in many situations, substantially improve the detection of neurophysiological response in sparse fMRI: (1 Sparse analyses should utilize a physiologically-informed model that incorporates hemodynamic response convolution to reduce model error. (2 The design of sparse fMRI experiments should maintain a high rate of stimulus presentation to maximize effect size. (3 TR delays of short to intermediate length can be used between acquisitions of sparse-sampled functional image volumes to improve

  9. How skill expertise shapes the brain functional architecture: an fMRI study of visuo-spatial and motor processing in professional racing-car and naive drivers.

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    Giulio Bernardi

    Full Text Available The present study was designed to investigate the brain functional architecture that subserves visuo-spatial and motor processing in highly skilled individuals. By using functional magnetic resonance imaging (fMRI, we measured brain activity while eleven Formula racing-car drivers and eleven 'naïve' volunteers performed a motor reaction and a visuo-spatial task. Tasks were set at a relatively low level of difficulty such to ensure a similar performance in the two groups and thus avoid any potential confounding effects on brain activity due to discrepancies in task execution. The brain functional organization was analyzed in terms of regional brain response, inter-regional interactions and blood oxygen level dependent (BOLD signal variability. While performance levels were equal in the two groups, as compared to naïve drivers, professional drivers showed a smaller volume recruitment of task-related regions, stronger connections among task-related areas, and an increased information integration as reflected by a higher signal temporal variability. In conclusion, our results demonstrate that, as compared to naïve subjects, the brain functional architecture sustaining visuo-motor processing in professional racing-car drivers, trained to perform at the highest levels under extremely demanding conditions, undergoes both 'quantitative' and 'qualitative' modifications that are evident even when the brain is engaged in relatively simple, non-demanding tasks. These results provide novel evidence in favor of an increased 'neural efficiency' in the brain of highly skilled individuals.

  10. Increasing fMRI sampling rate improves Granger causality estimates.

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    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.

  11. Human memory retention and recall processes. A review of EEG and fMRI studies.

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    Amin, Hafeezullah; Malik, Aamir S

    2013-10-01

    Human memory is an important concept in cognitive psychology and neuroscience. Our brain is actively engaged in functions of learning and memorization. Generally, human memory has been classified into 2 groups: short-term/working memory, and long-term memory. Using different memory paradigms and brain mapping techniques, psychologists and neuroscientists have identified 3 memory processes: encoding, retention, and recall. These processes have been studied using EEG and functional MRI (fMRI) in cognitive and neuroscience research. This study reviews previous research reported for human memory processes, particularly brain behavior in memory retention and recall processes with the use of EEG and fMRI. We discuss issues and challenges related to memory research with EEG and fMRI techniques.

  12. The functional organization of the left STS: a large scale meta-analysis of PET and fMRI studies of healthy adults

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    Einat eLiebenthal

    2014-09-01

    Full Text Available The superior temporal sulcus (STS in the left hemisphere is functionally diverse, with sub-areas implicated in both linguistic and non-linguistic functions. However, the number and boundaries of distinct functional regions remain to be determined. Here, we present new evidence, from meta-analysis of a large number of positron emission tomography (PET and functional magnetic resonance imaging (fMRI studies, of different functional specificity in the left STS supporting a division of its middle to terminal extent into at least three functional areas. The middle portion of the left STS stem (fmSTS is highly specialized for speech perception and the processing of language material. The posterior portion of the left STS stem (fpSTS is highly versatile and involved in multiple functions supporting semantic memory and associative thinking. The fpSTS responds to both language and non-language stimuli but the sensitivity to non-language material is greater. The horizontal portion of the left STS stem and terminal ascending branches (ftSTS display intermediate functional specificity, with the anterior ascending branch adjoining the supramarginal gyrus (fatSTS supporting executive functions and motor planning and showing greater sensitivity to language material, and the horizontal stem and posterior ascending branch adjoining the angular gyrus (fptSTS supporting primarily semantic processing and displaying greater sensitivity to non-language material. We suggest that the high functional specificity of the left fmSTS for speech is an important means by which the human brain achieves exquisite affinity and efficiency for native speech perception. In contrast, the extreme multi-functionality of the left fpSTS reflects the role of this area as a cortical hub for semantic processing and the extraction of meaning from multiple sources of information. Finally, in the left ftSTS, further functional differentiation between the dorsal and ventral aspect is warranted.

  13. A new vibrator to stimulate muscle proprioceptors in fMRI.

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    Montant, Marie; Romaiguère, Patricia; Roll, Jean-Pierre

    2009-03-01

    Studying cognitive brain functions by functional magnetic resonance imaging (fMRI) requires appropriate stimulation devices that do not interfere with the magnetic fields. Since the emergence of fMRI in the 90s, a number of stimulation devices have been developed for the visual and auditory modalities. Only few devices, however, have been developed for the somesthesic modality. Here, we present a vibration device for studying somesthesia that is compatible with high magnetic field environments and that can be used in fMRI machines. This device consists of a poly vinyl chloride (PVC) vibrator containing a wind turbine and of a pneumatic apparatus that controls 1-6 vibrators simultaneously. Just like classical electromagnetic vibrators, our device stimulates muscle mechanoreceptors (muscle spindles) and generates reliable illusions of movement. We provide the fMRI compatibility data (phantom test), the calibration curve (vibration frequency as a function of air flow), as well as the results of a kinesthetic test (perceived speed of the illusory movement as a function of vibration frequency). This device was used successfully in several brain imaging studies using both fMRI and magnetoencephalography.

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

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    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.

  15. Large-scale functional brain network changes in taxi drivers: evidence from resting-state fMRI.

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    Wang, Lubin; Liu, Qiang; Shen, Hui; Li, Hong; Hu, Dewen

    2015-03-01

    Driving a car in the environment is a complex behavior that involves cognitive processing of visual information to generate the proper motor outputs and action controls. Previous neuroimaging studies have used virtual simulation to identify the brain areas that are associated with various driving-related tasks. Few studies, however, have focused on the specific patterns of functional organization in the driver's brain. The aim of this study was to assess differences in the resting-state networks (RSNs) of the brains of drivers and nondrivers. Forty healthy subjects (20 licensed taxi drivers, 20 nondrivers) underwent an 8-min resting-state functional MRI acquisition. Using independent component analysis, three sensory (primary and extrastriate visual, sensorimotor) RSNs and four cognitive (anterior and posterior default mode, left and right frontoparietal) RSNs were retrieved from the data. We then examined the group differences in the intrinsic brain activity of each RSN and in the functional network connectivity (FNC) between the RSNs. We found that the drivers had reduced intrinsic brain activity in the visual RSNs and reduced FNC between the sensory RSNs compared with the nondrivers. The major finding of this study, however, was that the FNC between the cognitive and sensory RSNs became more positively or less negatively correlated in the drivers relative to that in the nondrivers. Notably, the strength of the FNC between the left frontoparietal and primary visual RSNs was positively correlated with the number of taxi-driving years. Our findings may provide new insight into how the brain supports driving behavior. © 2014 Wiley Periodicals, Inc.

  16. Explorations of Object and Location Memory using fMRI

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    Antony D Passaro

    2013-08-01

    Full Text Available Content-specific sub-systems of visual working memory (VWM have been explored in many neuroimaging studies with inconsistent findings and procedures across experiments. The present study employed functional magnetic resonance imaging (fMRI and a change detection task using a high number of trials and matched stimulus displays across object and location change ("what" vs "where" conditions. Furthermore, individual task periods were studied independently across conditions to identify period-specific differences. Importantly, this combination of task controls has not previously been described in the fMRI literature. Composite results revealed differential frontoparietal activation during each task period. A separation of object and location conditions yielded a distributed system of dorsal and ventral streams during the encoding of information corresponding to bilateral inferior parietal lobule (IPL and lingual gyrus activation, respectively. Differential activity was also shown during the maintenance of information in middle frontal structures bilaterally for objects and the right IPL and left insula for locations. Together, these results reflect a domain-specific dissociation spanning several cortices and task periods. Furthermore, differential activations suggest a general caudal-rostral separation corresponding to object and location memory, respectively.

  17. Pycortex: an interactive surface visualizer for fMRI

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    James Shuang Gao

    2015-09-01

    Full Text Available Surface visualizations of fMRI provide a comprehensive view of cortical activity. However, surface visualizations are difficult to generate and most common visualization techniques rely on unnecessary interpolation which limits the fidelity of the resulting maps. Furthermore, it is difficult to understand the relationship between flattened cortical surfaces and the underlying 3D anatomy using tools available currently. To address these problems we have developed pycortex, a Python toolbox for interactive surface mapping and visualization. Pycortex exploits the power of modern graphics cards to sample volumetric data on a per-pixel basis, allowing dense and accurate mapping of the voxel grid across the surface. Anatomical, functional and fiduciary information can be projected onto the cortical surface. The surface can be inflated and flattened interactively, aiding interpretation of the correspondence between the anatomical surface and the flattened cortical sheet. The output of pycortex can be viewed using WebGL, a technology compatible with modern web browsers. This allows complex fMRI surface maps to be distributed broadly online without requiring installation of complex software.

  18. Applications of fMRI for Brain Mapping

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    Nivedita Daimiwal

    2012-11-01

    Full Text Available Brain-mapping techniques have proven to be vital in understanding the molecular, cellular, and functional mechanisms of the brain. Normal anatomical imaging can provide structural information on certain abnormalities in the brain. However there are many neurological disorders for which only structure studies are not sufficient. In such cases it is required to investigate the functional organization of the brain. Further it is necessary to study the brain functions under normal as well as diseased conditions. Brain mapping techniques can help in deriving useful and important information on these issues. Brain functions and brain area responsible for the particular activities like motor, sensory speech and memory process could be investigated. The authors provide an overview of various Brain Mapping techniques and fMRI signal processing methods.

  19. A comparison of Gamma and Gaussian dynamic convolution models of the fMRI BOLD response.

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    Chen, Huafu; Yao, Dezhong; Liu, Zuxiang

    2005-01-01

    Blood oxygenation level-dependent (BOLD) contrast-based functional magnetic resonance imaging (fMRI) has been widely utilized to detect brain neural activities and great efforts are now stressed on the hemodynamic processes of different brain regions activated by a stimulus. The focus of this paper is the comparison of Gamma and Gaussian dynamic convolution models of the fMRI BOLD response. The convolutions are between the perfusion function of the neural response to a stimulus and a Gaussian or Gamma function. The parameters of the two models are estimated by a nonlinear least-squares optimal algorithm for the fMRI data of eight subjects collected in a visual stimulus experiment. The results show that the Gaussian model is better than the Gamma model in fitting the data. The model parameters are different in the left and right occipital regions, which indicate that the dynamic processes seem different in various cerebral functional regions.

  20. 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

  1. Peripheral inflammation related to lower fMRI activation during a working memory task and resting functional connectivity among older adults: a preliminary study.

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    Dev, Sheena I; Moore, Raeanne C; Soontornniyomkij, Benchawanna; Achim, Cristian L; Jeste, Dilip V; Eyler, Lisa T

    2017-03-01

    Peripheral inflammation has been associated with adverse effects on cognition and brain structure in late life, a process called 'inflammaging.' Identifying biomarkers of preclinical cognitive decline is critical in the development of preventative therapies, and peripheral inflammation may be able to serve as an indicator of cognitive decline. However, little is known regarding the relationship between peripheral inflammation and brain structure and function among older adults. Twenty-four older adults (mean age = 78) underwent a functional magnetic resonance imaging (fMRI) resting state functional connectivity scan, and a subset (n = 14) completed the n-Back working memory task in the scanner. All participants completed a blood draw, and inflammation was measured with interleukin 6 (IL-6) and C-Reactive Protein (CRP). Surprisingly, age was unrelated to measures of inflammation (IL-6, CRP) or brain function (default mode network (DMN) connectivity; working memory performance; blood oxygenation level dependent (BOLD) activation with higher working memory load). However, lower functional connectivity between the left parietal seed and all other DMN regions was associated with higher levels of IL-6 and CRP. Additionally, greater plasma concentration of IL-6 was associated with lower BOLD activation in the left middle frontal gyrus in response to increased working memory load. These preliminary findings support the importance of IL-6 and CRP in brain function among older adults. Frontal and parietal regions may be particularly sensitive to the effects of inflammation. Additionally, these findings provide preliminary evidence of inflammatory contributions to level of neural activity, even after accounting for vascular risk factors. Copyright © 2016 John Wiley & Sons, Ltd.

  2. Functional specialization and convergence in the occipito-temporal cortex supporting haptic and visual identification of human faces and body parts: an fMRI study.

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    Kitada, Ryo; Johnsrude, Ingrid S; Kochiyama, Takanori; Lederman, Susan J

    2009-10-01

    Humans can recognize common objects by touch extremely well whenever vision is unavailable. Despite its importance to a thorough understanding of human object recognition, the neuroscientific study of this topic has been relatively neglected. To date, the few published studies have addressed the haptic recognition of nonbiological objects. We now focus on haptic recognition of the human body, a particularly salient object category for touch. Neuroimaging studies demonstrate that regions of the occipito-temporal cortex are specialized for visual perception of faces (fusiform face area, FFA) and other body parts (extrastriate body area, EBA). Are the same category-sensitive regions activated when these components of the body are recognized haptically? Here, we use fMRI to compare brain organization for haptic and visual recognition of human body parts. Sixteen subjects identified exemplars of faces, hands, feet, and nonbiological control objects using vision and haptics separately. We identified two discrete regions within the fusiform gyrus (FFA and the haptic face region) that were each sensitive to both haptically and visually presented faces; however, these two regions differed significantly in their response patterns. Similarly, two regions within the lateral occipito-temporal area (EBA and the haptic body region) were each sensitive to body parts in both modalities, although the response patterns differed. Thus, although the fusiform gyrus and the lateral occipito-temporal cortex appear to exhibit modality-independent, category-sensitive activity, our results also indicate a degree of functional specialization related to sensory modality within these structures.

  3. Multimodal classification of schizophrenia patients with MEG and fMRI data using static and dynamic connectivity measures

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    Mustafa Sinan Cetin

    2016-10-01

    Full Text Available Mental disorders like schizophrenia are currently diagnosed by physicians/psychiatrists through clinical assessment and their evaluation of patient’s self-reported experiences as the illness emerges. There is great interest in identifying biological markers of prognosis at the onset of illness, rather than relying on the evolution of symptoms across time. Functional network connectivity, which indicates a subject's overall level of 'synchronicity' of activity between brain regions, demonstrates promise in providing individual subject predictive power. Many previous studies reported functional connectivity changes during resting-state using only functional magnetic resonance imaging (fMRI. Nevertheless, exclusive reliance on fMRI to generate such networks may limit the inference of the underlying dysfunctional connectivity, which is hypothesized to be a factor in patient symptoms, as fMRI measures connectivity via hemodynamics. Therefore, combination of connectivity assessments using fMRI and magnetoencephalography (MEG, which more directly measures neuronal activity, may provide improved classification of schizophrenia than either modality alone. Moreover, recent evidence indicates that metrics of dynamic connectivity may also be critical for understanding pathology in schizophrenia. In this work, we propose a new framework for extraction of important disease related features and classification of patients with schizophrenia based on using both fMRI and MEG to investigate functional network components in the resting state. Results of this study show that the integration of fMRI and MEG provides important information that captures fundamental characteristics of functional network connectivity in schizophrenia and is helpful for prediction of schizophrenia patient group membership. Combined fMRI/MEG methods, using static functional network connectivity analyses, improved classification accuracy relative to use of fMRI or MEG methods alone (by 15

  4. fMRI of retina-originated phosphenes experienced by patients with Leber congenital amaurosis.

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    Manzar Ashtari

    Full Text Available A phenomenon characterized by the experience of seeing light without any light actually entering the eye is called phosphenes or photopsias. Phosphenes can occur spontaneously or via induction by external stimuli. Previous reports regarding phosphenes have primarily focused on externally induced phosphenes such as by applying alternating or direct current to the cortex. A few of these reports used functional magnetic resonance (fMRI to study activations induced by cortical phosphenes. However, there are no fMRI reports on spontaneous phosphenes originating from the retina and the resulting pattern of cortical activations. We performed fMRI during a reversing checkerboard paradigm in three LCA patients who underwent unilateral gene therapy and reported experiencing frequent phosphene on a daily basis. We observed bilateral cortical activation covering the entire visual cortices when patients reported experiencing phosphenes. In contrast, in the absence of phosphenes, activation was regulated by patient's visual ability and demonstrated improved cortical activation due to gene therapy. These fMRI results illustrate the potential impact of phosphene perception on visual function and they may explain some of the variability that clinicians find in visual function testing in retinal degeneration. Although we did not perform correlations between visual function and phosphenes, we hope data presented here raises awareness of this phenomenon and its potential effect on visual function and the implications for clinical testing. We recommend a thorough history for phosphene experiences be taken in patients with retinal disease who are candidates for gene or molecular therapy. Lastly, these data illustrate the potential power of fMRI as an outcome measure of gene therapy and the negative impact phosphenes may have on vision testing. fMRI has proven to be a sensitive, non-invasive, and reproducible test paradigm for these purposes and can complement

  5. Is Granger causality a viable technique for analyzing fMRI data?

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    Xiaotong Wen

    Full Text Available Multivariate neural data provide the basis for assessing interactions in brain networks. Among myriad connectivity measures, Granger causality (GC has proven to be statistically intuitive, easy to implement, and generate meaningful results. Although its application to functional MRI (fMRI data is increasing, several factors have been identified that appear to hinder its neural interpretability: (a latency differences in hemodynamic response function (HRF across different brain regions, (b low-sampling rates, and (c noise. Recognizing that in basic and clinical neuroscience, it is often the change of a dependent variable (e.g., GC between experimental conditions and between normal and pathology that is of interest, we address the question of whether there exist systematic relationships between GC at the fMRI level and that at the neural level. Simulated neural signals were convolved with a canonical HRF, down-sampled, and noise-added to generate simulated fMRI data. As the coupling parameters in the model were varied, fMRI GC and neural GC were calculated, and their relationship examined. Three main results were found: (1 GC following HRF convolution is a monotonically increasing function of neural GC; (2 this monotonicity can be reliably detected as a positive correlation when realistic fMRI temporal resolution and noise level were used; and (3 although the detectability of monotonicity declined due to the presence of HRF latency differences, substantial recovery of detectability occurred after correcting for latency differences. These results suggest that Granger causality is a viable technique for analyzing fMRI data when the questions are appropriately formulated.

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

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    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

  7. Preoperative Evaluation with fMRI of Patients with Intracranial Gliomas

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    Ioannis Z. Kapsalakis

    2012-01-01

    Full Text Available Introduction. Aggressive surgical resection constitutes the optimal treatment for intracranial gliomas. However, the proximity of a tumor to eloquent areas requires exact knowledge of its anatomic relationships to functional cortex. The purpose of our study was to evaluate fMRI’s accuracy by comparing it to intraoperative cortical stimulation (DCS mapping. Material and Methods. Eighty-seven patients, with presumed glioma diagnosis, underwent preoperative fMRI and intraoperative DCS for cortical mapping during tumor resection. Findings of fMRI and DCS were considered concordant if the identified cortical centers were less than 5 mm apart. Pre and postoperative Karnofsky Performance Scale and Spitzer scores were recorded. A postoperative MRI was obtained for assessing the extent of resection. Results. The areas of interest were identified by fMRI and DCS in all participants. The concordance between fMRI and DCS was 91.9% regarding sensory-motor cortex, 100% for visual cortex, and 85.4% for language. Data analysis showed that patients with better functional condition demonstrated higher concordance rates, while there also was a weak association between tumor grade and concordance rate. The mean extent of tumor resection was 96.7%. Conclusions. Functional MRI is a highly accurate preoperative methodology for sensory-motor mapping. However, in language mapping, DCS remains necessary for accurate localization.

  8. Parametric analysis of fMRI data using linear systems methods.

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    Cohen, M S

    1997-08-01

    Using a model of the functional MRI (fMRI) impulse response based on published data, we have demonstrated that the form of the fMRI response to stimuli of freely varied timing can be modeled well by convolution of the impulse response with the behavioral stimulus. The amplitudes of the responses as a function of parametrically varied behavioral conditions are fitted well using a piecewise linear approximation. Use of the combined model, in conjunction with correlation analysis, results in an increase in sensitivity for the MRI study. This approach, based on the well-established methods of linear systems analysis, also allows a quantitative comparison of the response amplitudes across subjects to a broad range of behavioral conditions. Fit parameters, derived from the amplitude data, are relatively insensitive to a variety of MRI-related artifacts and yield results that are compared readily across subjects.

  9. Visual Cortex Plasticity Following Peripheral Damage To The Visual System: fMRI Evidence.

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    Lemos, João; Pereira, Daniela; Castelo-Branco, Miguel

    2016-10-01

    Over the last two decades, functional magnetic resonance imaging (fMRI) has become a powerful research method to investigate cortical visual plasticity. Abnormal fMRI response patterns have been occasionally detected in the visually deprived cortex of patients with bilateral retinal diseases. Controversy remains whether these observations indicate structural reorganization of the visual cortex or unmasking of previously silent cortico-cortical connections. In optic nerve diseases, there is weak evidence showing that early visual cortex seems to lack reorganization, while higher-order visual areas undergo plastic changes which may contribute to optimise visual function. There is however accumulating imaging evidence demonstrating trans-synaptic degeneration of the visual cortex in patients with disease of the anterior visual pathways. This may preclude the use of restorative treatments in these patients. Here, we review and update the body of fMRI evidence on visual cortical plasticity.

  10. Modelling the neurovascular habituation effect on fMRI time series

    Energy Technology Data Exchange (ETDEWEB)

    Ciuciu, Ph.; Sockeel, S.; Vincent, T. [NeuroSpin/CEA, F-91191 Gif-sur-Yvette (France); Idier, J. [IRCCyN/CNRS, 1 rue de la Noe 44300 Nantes (France)

    2009-07-01

    In this paper, a novel non-stationary model of functional Magnetic Resonance Imaging (fMRI) time series is proposed. It allows us to account for some putative habituation effect arising in event-related fMRI paradigms that involves the so-called repetition-suppression phenomenon and induces decreasing magnitude responses over successive trials. Akin, this model is defined over functionally homogeneous regions-of-interest (ROIs) and embedded in a joint detection-estimation approach of brain activity. Importantly, its non-stationarity character is embodied in the trial-varying nature of the BOLD response magnitude. Habituation and activation maps are then estimated within the Bayesian framework in a fully unsupervised MCMC procedure. On artificial fMRI datasets, we show that habituation effects can be accurately recovered in activating voxels. (authors)

  11. Distinct functional properties of the vertical and horizontal saccadic network in Health and Parkinson's disease: An eye-tracking and fMRI study.

    Science.gov (United States)

    Lemos, J; Pereira, D; Almendra, L; Rebelo, D; Patrício, M; Castelhano, J; Cunha, G; Januário, C; Cunha, L; Freire, A; Castelo-Branco, M

    2016-10-01

    Saccadic behaviour ranges from reflexive (e.g., prosaccade) to goal oriented voluntary movements (e.g., antisaccade). Behavioural asymmetries between vertical and horizontal saccades have been described both in normal individuals (greater delay of vertical prosaccades) and in disease states such as Parkinson's disease (PD) (prosaccades are short and antisaccades are delayed, especially in the vertical plane, possibly due to a frontostriatal deficit). Importantly, the cortical mechanisms for the generation of vertical saccades are largely unknown, both in health and disease, when compared with their horizontal counterpart. Moreover, studies exploring saccadic neural correlates and putative compensatory mechanisms at a functional level in PD are scarce. We investigated horizontal and vertical prosaccades and antisaccades in an eye tracking paradigm in 19 PD patients off medication and 22 healthy controls, followed by a block-design functional Magnetic Resonance Imaging (fMRI) study, consisting of two runs (prosaccade, antisaccade) of 6 blocks each (3 vertical, 3 horizontal). While saccade metrics were not significantly different between groups, PD showed left frontal underactivation during horizontal prosaccades and right parietal overactivation during horizontal and vertical prosaccades and horizontal antisaccades. Moreover, controls showed greater deactivation of the default-mode network (DMN) during antisaccades. Vertical prosaccades were associated with greater right frontal and cerebellar activity in controls, and cuneus hypoactivity in PD. Vertical antisaccades were associated with greater DMN deactivation in both groups and left frontal hypoactivity in PD. Putative functional compensatory changes in the right parietal cortex in PD patients may help to keep saccadic behaviour at the same level as the healthy controls. We provide first time evidence showing that functional cortical asymmetries between vertical and horizontal saccades occur distinctively in PD

  12. Functional Network Overlap as Revealed by fMRI Using sICA and Its Potential Relationships with Functional Heterogeneity, Balanced Excitation and Inhibition, and Sparseness of Neuron Activity

    Science.gov (United States)

    Xu, Jiansong; Calhoun, Vince D.; Worhunsky, Patrick D.; Xiang, Hui; Li, Jian; Wall, John T.; Pearlson, Godfrey D.; Potenza, Marc N.

    2015-01-01

    Functional magnetic resonance imaging (fMRI) studies traditionally use general linear model-based analysis (GLM-BA) and regularly report task-related activation, deactivation, or no change in activation in separate brain regions. However, several recent fMRI studies using spatial independent component analysis (sICA) find extensive overlap of functional networks (FNs), each exhibiting different task-related modulation (e.g., activation vs. deactivation), different from the dominant findings of GLM-BA. This study used sICA to assess overlap of FNs extracted from four datasets, each related to a different cognitive task. FNs extracted from each dataset overlapped with each other extensively across most or all brain regions and showed task-related concurrent increases, decreases, or no changes in activity. These findings indicate that neural substrates showing task-related concurrent but different modulations in activity intermix with each other and distribute across most of the brain. Furthermore, spatial correlation analyses found that most FNs were highly consistent in spatial patterns across different datasets. This finding indicates that these FNs probably reflect large-scale patterns of task-related brain activity. We hypothesize that FN overlaps as revealed by sICA might relate to functional heterogeneity, balanced excitation and inhibition, and population sparseness of neuron activity, three fundamental properties of the brain. These possibilities deserve further investigation. PMID:25714362

  13. Functional network overlap as revealed by fMRI using sICA and its potential relationships with functional heterogeneity, balanced excitation and inhibition, and sparseness of neuron activity.

    Science.gov (United States)

    Xu, Jiansong; Calhoun, Vince D; Worhunsky, Patrick D; Xiang, Hui; Li, Jian; Wall, John T; Pearlson, Godfrey D; Potenza, Marc N

    2015-01-01

    Functional magnetic resonance imaging (fMRI) studies traditionally use general linear model-based analysis (GLM-BA) and regularly report task-related activation, deactivation, or no change in activation in separate brain regions. However, several recent fMRI studies using spatial independent component analysis (sICA) find extensive overlap of functional networks (FNs), each exhibiting different task-related modulation (e.g., activation vs. deactivation), different from the dominant findings of GLM-BA. This study used sICA to assess overlap of FNs extracted from four datasets, each related to a different cognitive task. FNs extracted from each dataset overlapped with each other extensively across most or all brain regions and showed task-related concurrent increases, decreases, or no changes in activity. These findings indicate that neural substrates showing task-related concurrent but different modulations in activity intermix with each other and distribute across most of the brain. Furthermore, spatial correlation analyses found that most FNs were highly consistent in spatial patterns across different datasets. This finding indicates that these FNs probably reflect large-scale patterns of task-related brain activity. We hypothesize that FN overlaps as revealed by sICA might relate to functional heterogeneity, balanced excitation and inhibition, and population sparseness of neuron activity, three fundamental properties of the brain. These possibilities deserve further investigation.

  14. Language dominance in children with epilepsy: concordance of fMRI with intracarotid amytal testing and cortical stimulation.

    Science.gov (United States)

    Rodin, Danielle; Bar-Yosef, Omer; Smith, Mary Lou; Kerr, Elizabeth; Morris, Drew; Donner, Elizabeth J

    2013-10-01

    Accurate localization of language function is critical in children undergoing epilepsy surgery. Functional magnetic resonance imaging (fMRI) is a noninvasive mapping method that has begun to replace electrocortical stimulation mapping (ESM) and the intracarotid amytal test (IAT). We used both quantitative and qualitative methods to evaluate the concordance of fMRI with ESM and IAT in 20 children using a panel of language tasks. In no cases did fMRI assessment of language hemisphere dominance identify the opposite hemisphere from assessment by IAT or ESM. Concordance with IAT and ESM was higher using fMRI visual inspection than an fMRI laterality index, which failed to lateralize language in a number of the subjects. We have demonstrated that fMRI has good concordance with more traditional methods of language mapping. When fMRI demonstrates bilateral language activations, however, we continue to recommend confirmatory testing by either IAT or ESM prior to resection in classic language regions.

  15. Neuroethics and fMRI: Mapping a fledgling relationship

    DEFF Research Database (Denmark)

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

    2011-01-01

    of moral judgments. It is at the centre of debate surrounding the importance of neuroscience findings for concepts such as personhood and free will, and the extent of their practical consequences. Here, we map the landscape of fMRI and neuroethics, using citation analysis to uncover salient topics. We find...... that this landscape is sparsely populated: despite previous calls for debate, there are few articles that discuss both fMRI and ethical, legal, or social implications (ELSI), and even fewer direct citations between the two literatures. Recognizing that practical barriers exist to integrating ELSI discussion...

  16. Regional Coherence Alterations Revealed by Resting-State fMRI in Post-Stroke Patients with Cognitive Dysfunction

    National Research Council Canada - National Science Library

    Peng, Cheng-Yu; Chen, Yu-Chen; Cui, Ying; Zhao, Deng-Ling; Jiao, Yun; Tang, Tian-Yu; Ju, Shenghong; Teng, Gao-Jun

    2016-01-01

    ...) to investigate the alterations in regional coherence in patients after subcortical stroke. Resting-state fMRI measurements were acquired from 16 post-stroke patients with poor cognitive function (PSPC...

  17. Altered Dynamics of the fMRI Response to Faces in Individuals with Autism

    Science.gov (United States)

    Kleinhans, Natalia M.; Richards, Todd; Greenson, Jessica; Dawson, Geraldine; Aylward, Elizabeth

    2016-01-01

    Abnormal fMRI habituation in autism spectrum disorders (ASDs) has been proposed as a critical component in social impairment. This study investigated habituation to fearful faces and houses in ASD and whether fMRI measures of brain activity discriminate between ASD and typically developing (TD) controls. Two identical fMRI runs presenting masked…

  18. Bootstrapping GEE models for fMRI regional connectivity.

    Science.gov (United States)

    D'Angelo, Gina M; Lazar, Nicole A; Zhou, Gongfu; Eddy, William F; Morris, John C; Sheline, Yvette I

    2012-12-01

    An Alzheimer's fMRI study has motivated us to evaluate inter-regional correlations during rest between groups. We apply generalized estimating equation (GEE) models to test for differences in regional correlations across groups. Both the GEE marginal model and GEE transition model are evaluated and compared to the standard pooling Fisher-z approach using simulation studies. Standard errors of all methods are estimated both theoretically (model-based) and empirically (bootstrap). Of all the methods, we find that the transition models have the best statistical properties. Overall, the model-based standard errors and bootstrap standard errors perform about the same. We also demonstrate the methods with a functional connectivity study in a healthy cognitively normal population of ApoE4+ participants and ApoE4- participants who are recruited from the Adult Children's Study conducted at the Washington University Knight Alzheimer's Disease Research Center.

  19. An fMRI study on sunk cost effect.

    Science.gov (United States)

    Zeng, Jianmin; Zhang, Qinglin; Chen, Changming; Yu, Rongjun; Gong, Qiyong

    2013-06-26

    Sunk cost effect (also called escalation of commitment, etc) is a pervasive, interesting and famous decision bias, which has been intensively discussed in psychology, economics, management, political science, zoology, etc. To date, little has been known about the neural basis of this phenomenon. We investigated it by using functional magnetic resonance imaging (fMRI) to monitor healthy subjects' brain activities when they made decisions in a task wherein sunk cost and incremental cost were systematically manipulated. Higher sunk cost only increased activity of some brain areas (mainly lateral frontal and parietal cortices, which are involved in risk-taking), whereas lower incremental cost mainly increased activity of some brain areas (including striatum and medial prefrontal cortex, which are sensitive to rewards). No overlapping brain areas were found to respond to both sunk cost and incremental cost. These results favor certainty effect over self-justification or diminishing sensitivity as account of sunk cost effect.

  20. Simple Fully Automated Group Classification on Brain fMRI

    Energy Technology Data Exchange (ETDEWEB)

    Honorio, J.; Goldstein, R.; Honorio, J.; Samaras, D.; Tomasi, D.; Goldstein, R.Z.

    2010-04-14

    We propose a simple, well grounded classification technique which is suited for group classification on brain fMRI data sets that have high dimensionality, small number of subjects, high noise level, high subject variability, imperfect registration and capture subtle cognitive effects. We propose threshold-split region as a new feature selection method and majority voteas the classification technique. Our method does not require a predefined set of regions of interest. We use average acros ssessions, only one feature perexperimental condition, feature independence assumption, and simple classifiers. The seeming counter-intuitive approach of using a simple design is supported by signal processing and statistical theory. Experimental results in two block design data sets that capture brain function under distinct monetary rewards for cocaine addicted and control subjects, show that our method exhibits increased generalization accuracy compared to commonly used feature selection and classification techniques.

  1. Application of functional MRI in epilepsy

    Institute of Scientific and Technical Information of China (English)

    YU Ai-hong; LI Kun-cheng; PIAO Chang-fu; LI Hong-li

    2005-01-01

    Objective To review the recent development of functional MRI application in epilepsy. Data sources Both Chinese and English language literatures were researched using MEDLINE/ CD ROM (1996-2005) and the Chinese Biomedical Literature Disk (1996-2005). Study selection Published articles about functional MRI application and epilepsy were selected.Data extraction Data were mainly extracted from 38 articles which are listed in the reference section of this review.Results fMRI can be used to localize seizure foci through detecting these cerebral hemodynamic changes produced by epileptiform discharges. EEG-triggered fMRI, which has higher spatial and temporal resolution, helps to detect the spatiotemporal pattern of spike origin and propagation, and define localization of the epileptogenic focus. fMRI is also useful in language and memory cognitive function assessment and presurgical assessment of refractory epilepsy. Atypically distributed cognitive function areas can be detected by fMRI, because of cortical language and memory areas reorganization during long-term epileptic activity in patients with epilepsy. Conclusions fMRI technique plays a very important role in cognitive function and presurgical assessment of patients with epilepsy. It is meaningful for understanding pathogenesis of epilepsy.

  2. Feature-space clustering for fMRI meta-analysis

    DEFF Research Database (Denmark)

    Goutte, C.; Hansen, L.K.; Liptrot, Matthew George

    2001-01-01

    Clustering functional magnetic resonance imaging (fMRI) time series has emerged in recent years as a possible alternative to parametric modeling approaches. Most of the work so far has been concerned with clustering raw time series. In this contribution we investigate the applicability...... of a clustering method applied to features extracted from the data. This approach is extremely versatile and encompasses previously published results [Goutte et al., 1999] as special cases. A typical application is in data reduction: as the increase in temporal resolution of fMRI experiments routinely yields f......-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...

  3. Feature-space clustering for fMRI meta-analysis

    DEFF Research Database (Denmark)

    Goutte, C.; Hansen, L.K.; Liptrot, Matthew George

    2001-01-01

    Clustering functional magnetic resonance imaging (fMRI) time series has emerged in recent years as a possible alternative to parametric modeling approaches. Most of the work so far has been concerned with clustering raw time series. In this contribution we investigate the applicability...... of a clustering method applied to features extracted from the data. This approach is extremely versatile and encompasses previously published results [Goutte et al., 1999] as special cases. A typical application is in data reduction: as the increase in temporal resolution of fMRI experiments routinely yields f......-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...

  4. Embedded sparse representation of fMRI data via group-wise dictionary optimization

    Science.gov (United States)

    Zhu, Dajiang; Lin, Binbin; Faskowitz, Joshua; Ye, Jieping; Thompson, Paul M.

    2016-03-01

    Sparse learning enables dimension reduction and efficient modeling of high dimensional signals and images, but it may need to be tailored to best suit specific applications and datasets. Here we used sparse learning to efficiently represent functional magnetic resonance imaging (fMRI) data from the human brain. We propose a novel embedded sparse representation (ESR), to identify the most consistent dictionary atoms across different brain datasets via an iterative group-wise dictionary optimization procedure. In this framework, we introduced additional criteria to make the learned dictionary atoms more consistent across different subjects. We successfully identified four common dictionary atoms that follow the external task stimuli with very high accuracy. After projecting the corresponding coefficient vectors back into the 3-D brain volume space, the spatial patterns are also consistent with traditional fMRI analysis results. Our framework reveals common features of brain activation in a population, as a new, efficient fMRI analysis method.

  5. ICA if fMRI based on a convolutive mixture model

    DEFF Research Database (Denmark)

    Hansen, Lars Kai

    2003-01-01

    mixing relevant for spatial ICA. Convolutive ICA has many computational problems and no standard solution is available. In this study a new predictive estimation method is used for finding the mixing coefficients and the source signals of a convolutive mixture and it is applied in temporal mode...... challenge with previous independent component analyses is the convolutive nature of the mixing process in fMRI. In temporal ICA we assume that the measured fMRI response is an instantaneous, spatially varying, mixture of independent time functions. However, the convolutive structure of the hemodynamic....... The mixing is represented by “mixture coefficient images” quantifying the local response to a given source at a certain time lag. This is the first communication to address this important issue in the context of fMRI ICA. Data: A single slice holding 128x128 pixels and passing through primary visual cortex...

  6. Language lateralization of a bilingual person with epilepsy using a combination of fMRI and neuropsychological assessment findings.

    Science.gov (United States)

    O'Grady, Christopher; Omisade, Antonina; Sadler, R Mark

    2016-10-01

    This report describes the findings of language functional magnetic resonance imaging (fMRI) in a left-handed Urdu and English speaker with right hemisphere-originating epilepsy and unclear language dominance. fMRI is a reliable method for determining hemispheric language dominance in presurgical planning. However, the effects of bilingualism on language activation depend on many factors including age of acquisition and proficiency in the tested language, and morphological properties of the language itself. This case demonstrates that completing fMRI in both spoken languages and interpreting the results within the context of a neuropsychological assessment are essential in arriving at accurate conclusions about language distribution in bilingual patients.

  7. On the Relationship Between fMRI and Theories of Cognition: The Arrow Points in Both Directions.

    Science.gov (United States)

    Wixted, John T; Mickes, Laura

    2013-01-01

    In this article, we ask about the contribution of fMRI data to our understanding of theories of cognition and about the contribution of theories of cognition to our understanding of fMRI data. Experiments using fMRI can contribute to our understanding of cognition when they are designed to test the predictions of a particular cognitive theory. Although not all cognitive theories make clear predictions about patterns of activity in the brain fMRI experiments are often well suited to testing the predictions of those that do. However, many fMRI studies that are concerned with cognitive functional neuroanatomy are not designed to test predictions of cognitive theories but are instead designed to investigate the role played by different regions of the brain in cognitive activity. These fMRI studies do not shed light on cognitive theories but instead depend on cognitive theories to interpret the data-an interpretation that is only as valid as the cognitive theory on which it is based. These considerations suggest that the relationship between fMRI and theories of cognition is a two-way street.

  8. 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...

  9. 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...... and reproducible delivery of visual stimuli in fMRI as well as neurophysiology environments. It has the advantage of allowing variation of the stimulus source (e.g. colour of LED) without the need for manipulating the subject in the bore....

  10. Motor area localization using fMRI-constrained cortical current density reconstruction of movement-related cortical potentials, a comparison with fMRI and TMS mapping.

    Science.gov (United States)

    Inuggi, Alberto; Filippi, Massimo; Chieffo, Raffaella; Agosta, Federica; Rocca, Maria A; González-Rosa, Javier J; Cursi, Marco; Comi, Giancarlo; Leocani, Letizia

    2010-01-13

    The localization of human hand primary motor area (M1) has been the object of several studies during the last decades. EEG source analysis, functional magnetic resonance imaging (fMRI) and focal transcranial magnetic stimulation (TMS) are non-invasive methods for localizing M1 with good accuracy compared to direct electrocorticography (ECoG) results. EEG sources were reconstructed with Cortical Current Density (CCD) method, allowing to evaluate simultaneous and distributed patterns of activation and to increase accuracy by constraining on information derived from fMRI (fMRI-CCD). The aim of this study was to compare the M1 contribution of movement-related cortical potentials (MRCP) with TMS and fMRI results and to test the effect of constraints strength, algorithm norm and localization methods over CCD reconstruction. Seven right-handed healthy subjects underwent 64-channel EEG recording of MRCP to right thumb movement, focal TMS mapping of the right abductor pollicis brevis muscle and fMRI during right hand movement. We found fMRI activations, EEG sources and TMS mapping corresponding to the anatomical landmark of the hand area in all subjects with fMRI and TMS center-of-gravity and in almost all subjects using fMRI-CCD with moderate constraint. A significant improvement was found using fMRI-CCD compared to CCD alone. This study confirms the usefulness of multimodal integration of fMRI, EEG and TMS in localizing M1 and the possibility to increase EEG spatial resolution using fMRI information.

  11. Relating resting-state fMRI and EEG whole-brain connectomes across frequency bands

    Science.gov (United States)

    Deligianni, Fani; Centeno, Maria; Carmichael, David W.; Clayden, Jonathan D.

    2014-01-01

    Whole brain functional connectomes hold promise for understanding human brain activity across a range of cognitive, developmental and pathological states. So called resting-state (rs) functional MRI studies have contributed to the brain being considered at a macroscopic scale as a set of interacting regions. Interactions are defined as correlation-based signal measurements driven by blood oxygenation level dependent (BOLD) contrast. Understanding the neurophysiological basis of these measurements is important in conveying useful information about brain function. Local coupling between BOLD fMRI and neurophysiological measurements is relatively well defined, with evidence that gamma (range) frequency EEG signals are the closest correlate of BOLD fMRI changes during cognitive processing. However, it is less clear how whole-brain network interactions relate during rest where lower frequency signals have been suggested to play a key role. Simultaneous EEG-fMRI offers the opportunity to observe brain network dynamics with high spatio-temporal resolution. We utilize these measurements to compare the connectomes derived from rs-fMRI and EEG band limited power (BLP). Merging this multi-modal information requires the development of an appropriate statistical framework. We relate the covariance matrices of the Hilbert envelope of the source localized EEG signal across bands to the covariance matrices derived from rs-fMRI with the means of statistical prediction based on sparse Canonical Correlation Analysis (sCCA). Subsequently, we identify the most prominent connections that contribute to this relationship. We compare whole-brain functional connectomes based on their geodesic distance to reliably estimate the performance of the prediction. The performance of predicting fMRI from EEG connectomes is considerably better than predicting EEG from fMRI across all bands, whereas the connectomes derived in low frequency EEG bands resemble best rs-fMRI connectivity. PMID:25221467

  12. Relating resting-state fMRI and EEG whole-brain connectomes across frequency bands

    Directory of Open Access Journals (Sweden)

    Fani eDeligianni

    2014-08-01

    Full Text Available Whole brain functional connectomes hold promise for understanding human brain activity across a range of cognitive, developmental and pathological states. So called ‘resting-state’ (rs functional MRI studies have contributed to the brain being considered at a macroscopic scale as a set of interacting regions. Interactions are defined as correlation-based signal measurements driven by blood oxygenation level dependent (BOLD contrast. Understanding the neurophysiological basis of these measurements is important in conveying useful information about brain function. Local coupling between BOLD fMRI and neurophysiological measurements is relatively well defined, with evidence that gamma (range frequency EEG signals are the closest correlate of BOLD fMRI changes during cognitive processing. However, it is less clear how whole-brain network interactions relate during rest where lower frequency signals have been suggested to play a key role. Simultaneous EEG-fMRI offers the opportunity to observe brain network dynamics with high spatio-temporal resolution. We utilize these measurements to compare the connectomes derived from rs-fMRI and EEG band limited power (BLP. Merging this multi-modal information requires the development of an appropriate statistical framework. We relate the covariance matrices of the Hilbert envelope of the source localised EEG signal across bands to the covariance matrices derived from rs-fMRI with the means of statistical prediction based on sparse Canonical Correlation Analysis (sCCA. Subsequently, we identify the most prominent connections that contribute to this relationship. We compare whole-brain functional connectomes based on their geodesic distance to reliably estimate the performance of the prediction. The performance of predicting fMRI from EEG connectomes is considerably better than predicting EEG from fMRI across all bands, whereas the connectomes derived in low frequency EEG bands resemble best rs-fMRI

  13. Presurgical language mapping in epilepsy: Using fMRI of reading to identify functional reorganization in a patient with long-standing temporal lobe epilepsy

    Directory of Open Access Journals (Sweden)

    Layla Gould

    2016-01-01

    Full Text Available We report a 55-year-old, right-handed patient with intractable left temporal lobe epilepsy, who previously had a partial left temporal lobectomy. The patient could talk during seizures, suggesting that he might have language dominance in the right hemisphere. Presurgical fMRI localization of language processing including reading of exception and regular words, pseudohomophones, and dual meaning words confirmed the clinical hypothesis of right language dominance, with only small amounts of activation near the planned surgical resection and, thus, minimal eloquent cortex to avoid during surgery. Postoperatively, the patient was rendered seizure-free without speech deficits.

  14. Understanding the Pathophysiology of Alzheimer's Disease and Mild Cognitive Impairment: A Mini Review on fMRI and ERP Studies

    Directory of Open Access Journals (Sweden)

    Takao Yamasaki

    2012-01-01

    Full Text Available The prevalence of Alzheimer's disease (AD is predicted to increase rapidly in the coming decade, highlighting the importance of early detection and intervention in patients with AD and mild cognitive impairment (MCI. Recently, remarkable advances have been made in the application of neuroimaging techniques in investigations of AD and MCI. Among the various neuroimaging techniques, functional magnetic resonance imaging (fMRI has many potential advantages, noninvasively detecting alterations in brain function that may be present very early in the course of AD and MCI. In this paper, we first review task-related and resting-state fMRI studies on AD and MCI. We then present our recent fMRI studies with additional event-related potential (ERP experiments during a motion perception task in MCI. Our results indicate that fMRI, especially when combined with ERP recording, can be useful for detecting spatiotemporal functional changes in AD and MCI patients.

  15. Impact of Global Normalization in fMRI Acupuncture Studies

    Directory of Open Access Journals (Sweden)

    Jinbo Sun

    2012-01-01

    Full Text Available Global normalization is often used as a preprocessing step for dispelling the “nuisance effects.” However, it has been shown in cognitive and emotion tasks that this preprocessing step might greatly distort statistical results when the orthogonality assumption of global normalization is violated. The present study examines this issue in fMRI acupuncture studies. Thirty healthy subjects were recruited to evaluate the impacts of the global normalization on the BOLD responses evoked by acupuncture stimulation during De-qi sensation and tactile stimulation during nonpainful sensations. To this end, we compared results by conducting global normalization (PSGS and not conducting global normalization (NO PSGS based on a proportional scaling model. The orthogonality assumption of global normalization was violated, and significant changes between BOLD responses for NO PSGS and PSGS were shown in most subjects. Extensive deactivations of acupuncture in fMRI were the non-specifically pernicious consequences of global normalization. The central responses of acupuncture during De-qi are non-specifically activation-dominant at the somatosensory-related brain network, whose statistical power is specifically enhanced by PSGS. In conclusion, PSGS should be unjustified for acupuncture studies in fMRI. The differences including the global normalization or not may partly contribute to conflicting results and interpretations in previous fMRI acupuncture studies.

  16. Bayesian Modelling of fMRI Time Series

    DEFF Research Database (Denmark)

    Højen-Sørensen, Pedro; Hansen, Lars Kai; Rasmussen, Carl Edward

    2000-01-01

    We present a Hidden Markov Model (HMM) for inferring the hidden psychological state (or neural activity) during single trial fMRI activation experiments with blocked task paradigms. Inference is based on Bayesian methodology, using a combination of analytical and a variety of Markov Chain Monte...

  17. Linear systems analysis of the fMRI signal.

    Science.gov (United States)

    Boynton, Geoffrey M; Engel, Stephen A; Heeger, David J

    2012-08-15

    In 1995 when we began our investigations of the human visual system using fMRI, little was known about the temporal properties of the fMRI signal. Before we felt comfortable making quantitative estimates of neuronal responses with this new technique, we decided to first conduct a basic study of how the time-course of the fMRI response varied with stimulus timing and strength. The results ended up showing strong evidence that to a first approximation the hemodynamic transformation was linear in time. This was both important and remarkable: important because nearly all fMRI data analysis techniques assume or require linearity, and remarkable because the physiological basis of the hemodynamic transformation is so complex that we still have a far from complete understanding of it. In this paper, we provide highlights of the results of our original paper supporting the linear transform hypothesis. A reanalysis of the original data provides some interesting new insights into the published results. We also provide a detailed appendix describing of the properties and predictions of a linear system in time in the context of the transformation between neuronal responses and the BOLD signal.

  18. The Effect of fMRI (Noise) on Cognitive Control

    Science.gov (United States)

    Hommel, Bernhard; Fischer, Rico; Colzato, Lorenza S.; van den Wildenberg, Wery P. M.; Cellini, Cristiano

    2012-01-01

    Stressful situations, the aversiveness of events, or increases in task difficulty (e.g., conflict) have repeatedly been shown to be capable of triggering attentional control adjustments. In the present study we tested whether the particularity of an fMRI testing environment (i.e., EPI noise) might result in such increases of the cognitive control…

  19. Functional and anatomical dissociation between the orthographic lexicon and the orthographic buffer revealed in reading and writing Chinese characters by fMRI.

    Science.gov (United States)

    Chen, Hsiang-Yu; Chang, Erik C; Chen, Sinead H Y; Lin, Yi-Chen; Wu, Denise H

    2016-04-01

    The contribution of orthographic representations to reading and writing has been intensively investigated in the literature. However, the distinction between neuronal correlates of the orthographic lexicon and the orthographic (graphemic) buffer has rarely been examined in alphabetic languages and never been explored in non-alphabetic languages. To determine whether the neural networks associated with the orthographic lexicon and buffer of logographic materials are comparable to those reported in the literature, the present fMRI experiment manipulated frequency and the stroke number of Chinese characters in the tasks of form judgment and stroke judgment, which emphasized the processing of character recognition and writing, respectively. It was found that the left fusiform gyrus exhibited higher activation when encountering low-frequency than high-frequency characters in both tasks, which suggested this region to be the locus of the orthographic lexicon that represents the knowledge of character forms. On the other hand, the activations in the posterior part of the left middle frontal gyrus and in the left angular gyrus were parametrically modulated by the stroke number of target characters only in the stroke judgment task, which suggested these regions to be the locus of the orthographic buffer that represents the processing of stroke sequence in writing. These results provide the first evidence for the functional and anatomical dissociation between the orthographic lexicon and buffer in reading and writing Chinese characters. They also demonstrate the critical roles of the left fusiform area and the frontoparietal network to the long-term and short-term representations of orthographic knowledge, respectively, across different orthographies.

  20. Diffusion fMRI detects white-matter dysfunction in mice with acute optic neuritis.

    Science.gov (United States)

    Lin, Tsen-Hsuan; Spees, William M; Chiang, Chia-Wen; Trinkaus, Kathryn; Cross, Anne H; Song, Sheng-Kwei

    2014-07-01

    Optic neuritis is a frequent and early symptom of multiple sclerosis (MS). Conventional magnetic resonance (MR) techniques provide means to assess multiple MS-related pathologies, including axonal injury, demyelination, and inflammation. A method to directly and non-invasively probe white-matter function could further elucidate the interplay of underlying pathologies and functional impairments. Previously, we demonstrated a significant 27% activation-associated decrease in the apparent diffusion coefficient of water perpendicular to the axonal fibers (ADC⊥) in normal C57BL/6 mouse optic nerve with visual stimulation using diffusion fMRI. Here we apply this approach to explore the relationship between visual acuity, optic nerve pathology, and diffusion fMRI in the experimental autoimmune encephalomyelitis (EAE) mouse model of optic neuritis. Visual stimulation produced a significant 25% (vs. baseline) ADC⊥ decrease in sham EAE optic nerves, while only a 7% (vs. baseline) ADC⊥ decrease was seen in EAE mice with acute optic neuritis. The reduced activation-associated ADC⊥ response correlated with post-MRI immunohistochemistry determined pathologies (including inflammation, demyelination, and axonal injury). The negative correlation between activation-associated ADC⊥ response and visual acuity was also found when pooling EAE-affected and sham groups under our experimental criteria. Results suggest that reduction in diffusion fMRI directly reflects impaired axonal-activation in EAE mice with optic neuritis. Diffusion fMRI holds promise for directly gauging in vivo white-matter dysfunction or therapeutic responses in MS patients.

  1. Three-dimensional brain mapping using fMRI

    Energy Technology Data Exchange (ETDEWEB)

    Fukunaga, Masaki; Tanaka, Chuzo; Umeda, Masahiro; Ebisu, Toshihiko; Aoki, Ichio [Meiji Univ. of Oriental Medicine, Hiyoshi, Kyoto (Japan); Higuchi, Toshihiro; Naruse, Shoji

    1997-10-01

    Functional mapping of the activated brain, the location and extent of the activated area were determined, during motor tasks and sensory stimulation using fMRI superimposed on 3D anatomical MRI. Twelve volunteers were studied. The fMR images were acquired using a 2D gradient echo echo planar imaging sequence. The 3D anatomical MR images of the whole brain were acquired using a conventional 3D gradient echo sequence. Motor tasks were sequential opposition of fingers, clenching a hand and elbow flexion. Somatosensory stimulation were administered by scrubbing the palm and sole with a washing sponge. Visual stimulation consisted of full visual field stimulation. Data were analyzed by the cross-correlation method. Transversal fMR images and anatomical images were reconstructed using both volume-, surface-rendering methods, and reconstructed for coronal and sagittal sections. Activated areas were expressed using the three primary colors. Motor tasks activated the contralateral primary motor area (M1), the primary somatosensory area (S1) and the supplementary motor area (SMA). Somatosensory tasks activated the contralateral S1, M1 and secondary sensory area (S2). Activated areas during full visual field stimulation was observed in the bilateral occipital lobe, including both the primary cortex. Three-dimensional brain mapping allowed visualization of the anatomical location and extent of the activated brain during both motor task and sensory stimulation. Using this method we could obtain a functional map similar to the Penfield`s schema. (author)

  2. Utility of functional MRI in pediatric neurology.

    Science.gov (United States)

    Freilich, Emily R; Gaillard, William D

    2010-01-01

    Functional MRI (fMRI), a tool increasingly used to study cognitive function, is also an important tool for understanding not only normal development in healthy children, but also abnormal development, as seen in children with epilepsy, attention-deficit/hyperactivity disorder, and autism. Since its inception almost 15 years ago, fMRI has seen an explosion in its use and applications in the adult literature. However, only recently has it found a home in pediatric neurology. New adaptations in study design and technologic advances, especially the study of resting state functional connectivity as well as the use of passive task design in sedated children, have increased the utility of functional imaging in pediatrics to help us gain understanding into the developing brain at work. This article reviews the background of fMRI in pediatrics and highlights the most recent literature and clinical applications.

  3. Energetics of neuronal signaling and fMRI activity.

    Science.gov (United States)

    Maandag, Natasja J G; Coman, Daniel; Sanganahalli, Basavaraju G; Herman, Peter; Smith, Arien J; Blumenfeld, Hal; Shulman, Robert G; Hyder, Fahmeed

    2007-12-18

    Energetics of resting and evoked fMRI signals were related to localized ensemble firing rates (nu) measured by electrophysiology in rats. Two different unstimulated, or baseline, states were established by anesthesia. Halothane and alpha-chloralose established baseline states of high and low energy, respectively, in which forepaw stimulation excited the contralateral primary somatosensory cortex (S1). With alpha-chloralose, forepaw stimulation induced strong and reproducible fMRI activations in the contralateral S1, where the ensemble firing was dominated by slow signaling neurons (SSN; nu range of 1-13 Hz). Under halothane, weaker and less reproducible fMRI activations were observed in the contralateral S1 and elsewhere in the cortex, but ensemble activity in S1 was dominated by rapid signaling neurons (RSN; nu range of 13-40 Hz). For both baseline states, the RSN activity (i.e., higher frequencies, including the gamma band) did not vary upon stimulation, whereas the SSN activity (i.e., alpha band and lower frequencies) did change. In the high energy baseline state, a large majority of total oxidative energy [cerebral metabolic rate of oxygen consumption (CMR(O2))] was devoted to RSN activity, whereas in the low energy baseline state, it was roughly divided between SSN and RSN activities. We hypothesize that in the high energy baseline state, the evoked changes in fMRI activation in areas beyond S1 are supported by rich intracortical interactions represented by RSN. We discuss implications for interpreting fMRI data where stimulus-specific DeltaCMR(O2) is generally small compared with baseline CMR(O2).

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

    Energy Technology Data Exchange (ETDEWEB)

    Wurm, Gabriele [Landesnervenklinik Wagner Jauregg, Neurosurgical Department, Linz (Austria); Schnizer, Mathilde [Landesnervenklinik Wagner Jauregg, Neurological Department, Linz (Austria); Landesnervenklinik Wagner Jauregg, Neuroradiological Department, Linz (Austria); Fellner, Claudia [Landesnervenklinik Wagner Jauregg, Neuroradiological Department, Linz (Austria); University of Regensburg, Institute of Radiology, Regensburg (Germany)

    2008-09-15

    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.)

  5. 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…

  6. Seeing Chinese Characters in Action: An fMRI Study of the Perception of Writing Sequences

    Science.gov (United States)

    Yu, Hongbo; Gong, Lanyun; Qiu, Yinchen; Zhou, Xiaolin

    2011-01-01

    The Chinese character is composed of a finite set of strokes whose order in writing follows consensual principles and is learnt through school education. Using functional magnetic resonance imaging (fMRI), this study investigates the neural activity associated with the perception of writing sequences by asking participants to observe…

  7. Neural Changes after Phonological Treatment for Anomia: An fMRI Study

    Science.gov (United States)

    Rochon, Elizabeth; Leonard, Carol; Burianova, Hana; Laird, Laura; Soros, Peter; Graham, Simon; Grady, Cheryl

    2010-01-01

    Functional magnetic resonance imaging (fMRI) was used to investigate the neural processing characteristics associated with word retrieval abilities after a phonologically-based treatment for anomia in two stroke patients with aphasia. Neural activity associated with a phonological and a semantic task was compared before and after treatment with…

  8. How mood challenges emotional memory formation: An fMRI investigation

    NARCIS (Netherlands)

    Fitzgerald, D.A.; Arnold, J.F.; Becker, E.S.; Speckens, A.E.M.; Rinck, M.; Rijpkema, M.J.P.; Fernandez, G.S.E.; Tendolkar, I.

    2011-01-01

    Experimental mood manipulations and functional magnetic resonance imaging (fMRI) provide a unique opportunity for examining the neural correlates of mood-congruent memory formation. While prior studies in mood-disorder patients point to the medial temporal lobe in the genesis of mood-congruent memor

  9. How mood challenges emotional memory formation: an fMRI investigation

    NARCIS (Netherlands)

    Fitzgerald, D.A.; Arnold, J.F.; Becker, E.S.; Speckens, A.E.M.; Rinck, M.; Rijpkema, M.J.P.; Fernandez, G.S.E.; Tendolkar, I.

    2011-01-01

    Experimental mood manipulations and functional magnetic resonance imaging (fMRI) provide a unique opportunity for examining the neural correlates of mood-congruent memory formation. While prior studies in mood-disorder patients point to the medial temporal lobe in the genesis of mood-congruent memor

  10. Puzzlingly High Correlations in fMRI Studies of Emotion, Personality, and Social Cognition

    Science.gov (United States)

    Vul, Edward; Harris, Christine; Winkielman, Piotr; Pashler, Harold

    2009-01-01

    Functional Magnetic Resonance Imaging (fMRI) studies of emotion, personality, and social cognition have drawn much attention in recent years, with high-profile studies frequently reporting extremely high (e.g., > 8) correlations between behavioral and self-report measures of personality or emotion and measures of brain activation. We show that…

  11. 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…

  12. 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

    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...

  13. 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…

  14. Blind source separation of fMRI data by means of factor analytic transformations

    NARCIS (Netherlands)

    Langers, Dave R. M.

    2009-01-01

    In this study, the application of factor analytic (FA) rotation methods in the context of neuroimaging data analysis was explored. Three FA algorithms (ProMax, QuartiMax, and VariMax) were employed to carry out blind source separation in a functional magnetic resonance imaging (fMRI) experiment that

  15. Auditory Verb Perception Recruits Motor Systems in the Developing Brain: An fMRI Investigation

    Science.gov (United States)

    James, Karin Harman; Maouene, Josita

    2009-01-01

    This study investigated neural activation patterns during verb processing in children, using fMRI (functional Magnetic Resonance Imaging). Preschool children (aged 4-6) passively listened to lists of verbs and adjectives while neural activation was measured. Findings indicated that verbs were processed differently than adjectives, as the verbs…

  16. Are Errors Differentiable from Deceptive Responses when Feigning Memory Impairment? An fMRI Study

    Science.gov (United States)

    Lee, Tatia M. C.; Au, Ricky K. C.; Liu, Ho-Ling; Ting, K. H.; Huang, Chih-Mao; Chan, Chetwyn C. H.

    2009-01-01

    Previous neuroimaging studies have suggested that the neural activity associated with truthful recall, with false memory, and with feigned memory impairment are different from one another. Here, we report a functional magnetic resonance imaging (fMRI) study that addressed an important but yet unanswered question: Is the neural activity associated…

  17. Using fMRI to Study Conceptual Change: Why and How?

    Science.gov (United States)

    Masson, Steve; Potvin, Patrice; Riopel, Martin; Foisy, Lorie-Marlene Brault; Lafortune, Stephanie

    2012-01-01

    Although the use of brain imaging techniques, such as functional magnetic resonance imaging (fMRI) is increasingly common in educational research, only a few studies regarding science learning have so far taken advantage of this technology. This paper aims to facilitate the design and implementation of brain imaging studies relating to science…

  18. Non-white noise in fMRI: does modelling have an impact?

    DEFF Research Database (Denmark)

    Lund, Torben E; Madsen, Kristoffer H; Sidaros, Karam

    2006-01-01

    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 ...

  19. Neural Changes after Phonological Treatment for Anomia: An fMRI Study

    Science.gov (United States)

    Rochon, Elizabeth; Leonard, Carol; Burianova, Hana; Laird, Laura; Soros, Peter; Graham, Simon; Grady, Cheryl

    2010-01-01

    Functional magnetic resonance imaging (fMRI) was used to investigate the neural processing characteristics associated with word retrieval abilities after a phonologically-based treatment for anomia in two stroke patients with aphasia. Neural activity associated with a phonological and a semantic task was compared before and after treatment with…

  20. Blind source separation of fMRI data by means of factor analytic transformations

    NARCIS (Netherlands)

    Langers, Dave R. M.

    2009-01-01

    In this study, the application of factor analytic (FA) rotation methods in the context of neuroimaging data analysis was explored. Three FA algorithms (ProMax, QuartiMax, and VariMax) were employed to carry out blind source separation in a functional magnetic resonance imaging (fMRI) experiment that

  1. Effects of ¿9-Tetrahydrocannabinol Administration on human encoding and recall memory function: a pharmacological fMRI study

    NARCIS (Netherlands)

    Bossong, M.G.; Jager, G.; Hell, van H.H.; Zuurman, L.; Jansma, J.M.; Mehta, M.A.; Gerven, van J.; Kahn, R.S.; Ramsey, N.F.

    2012-01-01

    Deficits in memory function are an incapacitating aspect of various psychiatric and neurological disorders. Animal studies have recently provided strong evidence for involvement of the endocannabinoid (eCB) system in memory function. Neuropsychological studies in humans have shown less convincing

  2. Effects of ¿9-Tetrahydrocannabinol Administration on human encoding and recall memory function: a pharmacological fMRI study

    NARCIS (Netherlands)

    Bossong, M.G.; Jager, G.; Hell, van H.H.; Zuurman, L.; Jansma, J.M.; Mehta, M.A.; Gerven, van J.; Kahn, R.S.; Ramsey, N.F.

    2012-01-01

    Deficits in memory function are an incapacitating aspect of various psychiatric and neurological disorders. Animal studies have recently provided strong evidence for involvement of the endocannabinoid (eCB) system in memory function. Neuropsychological studies in humans have shown less convincing ev

  3. Effects of ¿9-Tetrahydrocannabinol Administration on human encoding and recall memory function: a pharmacological fMRI study

    NARCIS (Netherlands)

    Bossong, M.G.; Jager, G.; Hell, van H.H.; Zuurman, L.; Jansma, J.M.; Mehta, M.A.; Gerven, van J.; Kahn, R.S.; Ramsey, N.F.

    2012-01-01

    Deficits in memory function are an incapacitating aspect of various psychiatric and neurological disorders. Animal studies have recently provided strong evidence for involvement of the endocannabinoid (eCB) system in memory function. Neuropsychological studies in humans have shown less convincing ev

  4. Decreased functional connectivity of the amygdala in Alzheimer's disease revealed by resting-state fMRI

    Energy Technology Data Exchange (ETDEWEB)

    Yao, Hongxiang [Department of Radiology, Chinese PLA General Hospital, Beijing, 100853 (China); Liu, Yong, E-mail: yliu@nlpr.ia.ac.cn [Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190 (China); National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190 (China); Zhou, Bo; Zhang, Zengqiang [Department of Neurology, Institute of Geriatrics and Gerontology, Chinese PLA General Hospital, Beijing, 100853 (China); An, Ningyu [Department of Radiology, Chinese PLA General Hospital, Beijing, 100853 (China); Wang, Pan; Wang, Luning [Department of Neurology, Institute of Geriatrics and Gerontology, Chinese PLA General Hospital, Beijing, 100853 (China); Zhang, Xi, E-mail: zhangxi@301hospital.com.cn [Department of Neurology, Institute of Geriatrics and Gerontology, Chinese PLA General Hospital, Beijing, 100853 (China); Jiang, Tianzi [Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190 (China); National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190 (China); Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054 (China); The Queensland Brain Institute, The University of Queensland, Brisbane, QLD 4072 (Australia)

    2013-09-15

    Alzheimer's disease (AD), the most common cause of dementia, is thought to be a progressive neurodegenerative disease that is clinically characterised by a decline of memory and other cognitive functions. Mild cognitive impairment (MCI) is considered to be the prodromal stage of AD. However, the relationship between AD and MCI and the development process remains unclear. The amygdala is one of the most vulnerable structures in the early stages of AD. To our knowledge, this is the first report on the alteration of the functional connectivity of the amygdala in AD and MCI subjects. We hypothesised that the amygdala-cortical loop is impaired in AD and that these alterations relate to the disease severity. In our study, we used resting-state functional MRIs to investigate the altered amygdala connectivity patterns in 35 AD patients, 27 MCI patients and 27 age- and gender-matched normal controls (NC). Compared with the NC, the decreased functional connectivity found in the AD patients was mainly located between the amygdala and the regions that are included in the default mode, context conditioning and extinction networks. Importantly, the decreased functional connectivity between the amygdala and some of the identified regions was positively correlated with MMSE, which indicated that the cognitive function impairment is related to an altered functional connectivity pattern.

  5. Functionally Brain Network Connected to the Retrosplenial Cortex of Rats Revealed by 7T fMRI.

    Science.gov (United States)

    Wang, Jingjuan; Nie, Binbin; Duan, Shaofeng; Zhu, Haitao; Liu, Hua; Shan, Baoci

    2016-01-01

    Functional networks are regarded as important mechanisms for increasing our understanding of brain function in healthy and diseased states, and increased interest has been focused on extending the study of functional networks to animal models because such models provide a functional understanding of disease progression, therapy and repair. In rodents, the retrosplenial cortex (RSC) is an important cortical region because it has a large size and presents transitional patterns of lamination between the neocortex and archicortex. In addition, a number of invasive studies have highlighted the importance of the RSC for many functions. However, the network based on the RSC in rodents remains unclear. Based on the critical importance of the RSC, we defined the bilateral RSCs as two regions of interest and estimated the network based on the RSC. The results showed that the related regions include the parietal association cortex, hippocampus, thalamus nucleus, midbrain structures, and hypothalamic mammillary bodies. Our findings indicate two possible major networks: a sensory-cognitive network that has a hub in the RSCs and processes sensory information, spatial learning, and episodic memory; and a second network that is involved in the regulation of visceral functions and arousal. In addition, functional asymmetry between the bilateral RSCs was observed.

  6. Distant functional connectivity for bimanual finger coordination declines with aging: an fMRI and SEM exploration

    OpenAIRE

    2014-01-01

    Although bimanual finger coordination is known to decline with aging, it still remains unclear how exactly the neural substrates underlying the coordination differ between young and elderly adults. The present study focused on: (1) characterization of the functional connectivity within the motor association cortex which is required for successful bimanual finger coordination, and (2) to elucidate upon its age-related decline. To address these objectives, we utilized functional magnetic resona...

  7. Functional Neuronavigation: Comparison of spatial congruence between fMRI and electrocortical stimulation in central region tumor surgery

    OpenAIRE

    Wachter, Dorothee

    2010-01-01

    Background: The surgical treatment of lesions in or around the central region confronts the neurosurgeon with a great challenge. Radical tumor resection leads to a better outcome but it also bears the risk of postoperative neurological deficit due to the functional importance of the central region. Throughout the last couple of years different techniques made it possible to identify the patient’s specific functional and anatomical topography. The central sulcus and the adjacent gyri...

  8. Altered brain functional networks in people with Internet gaming disorder: Evidence from resting-state fMRI.

    Science.gov (United States)

    Wang, Lingxiao; Wu, Lingdan; Lin, Xiao; Zhang, Yifen; Zhou, Hongli; Du, Xiaoxia; Dong, Guangheng

    2016-08-30

    Although numerous neuroimaging studies have detected structural and functional abnormality in specific brain regions and connections in subjects with Internet gaming disorder (IGD), the topological organization of the whole-brain network in IGD remain unclear. In this study, we applied graph theoretical analysis to explore the intrinsic topological properties of brain networks in Internet gaming disorder (IGD). 37 IGD subjects and 35 matched healthy control (HC) subjects underwent a resting-state functional magnetic resonance imaging scan. The functional networks were constructed by thresholding partial correlation matrices of 90 brain regions. Then we applied graph-based approaches to analysis their topological attributes, including small-worldness, nodal metrics, and efficiency. Both IGD and HC subjects show efficient and economic brain network, and small-world topology. Although there was no significant group difference in global topology metrics, the IGD subjects showed reduced regional centralities in the prefrontal cortex, left posterior cingulate cortex, right amygdala, and bilateral lingual gyrus, and increased functional connectivity in sensory-motor-related brain networks compared to the HC subjects. These results imply that people with IGD may be associated with functional network dysfunction, including impaired executive control and emotional management, but enhanced coordination among visual, sensorimotor, auditory and visuospatial systems.

  9. Analysis of group ICA-based connectivity measures from fMRI: application to Alzheimer's disease.

    Directory of Open Access Journals (Sweden)

    Shanshan Li

    Full Text Available Functional magnetic resonance imaging (fMRI is a powerful tool for the in vivo study of the pathophysiology of brain disorders and disease. In this manuscript, we propose an analysis stream for fMRI functional connectivity data and apply it to a novel study of Alzheimer's disease. In the first stage, spatial independent component analysis is applied to group fMRI data to obtain common brain networks (spatial maps and subject-specific mixing matrices (time courses. In the second stage, functional principal component analysis is utilized to decompose the mixing matrices into population-level eigenvectors and subject-specific loadings. Inference is performed using permutation-based exact logistic regression for matched pairs data. The method is applied to a novel fMRI study of Alzheimer's disease risk under a verbal paired associates task. We found empirical evidence of alternative ICA-based metrics of connectivity when comparing subjects evidencing mild cognitive impairment relative to carefully matched controls.

  10. 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.

  11. Incidental use of ecstasy: no evidence for harmful effects on cognitive brain function in a prospective fMRI study

    NARCIS (Netherlands)

    Jager, G.; Win, M.M. de; Vervaeke, H.K.; Schilt, T.; Kahn, R.S.; Brink, W. van den; Ree, J.M. van; Ramsey, M.F.

    2007-01-01

    Rationale Heavy ecstasy use in humans has been associated with cognitive impairments and changes in cognitive brain function supposedly due to damage to the serotonin system. There is concern that even a single dose of 3,4-methylenedioxymethamphetamine may be neurotoxic, but very little is known ab

  12. 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.

  13. Influence of ROI selection on Resting Functional Connectivity: An Individualized Approach for Resting fMRI Analysis

    Directory of Open Access Journals (Sweden)

    William Seunghyun Sohn

    2015-08-01

    Full Text Available The differences in how our brain is connected are often thought to reflect the differences in our individual personalities and cognitive abilities. Individual differences in brain connectivity has long been recognized in the neuroscience community however it has yet to manifest itself in the methodology of resting state analysis. This is evident as previous studies use the same region of interest (ROIs for all subjects. In this paper we demonstrate that the use of ROIs which are standardized across individuals leads to inaccurate calculations of functional connectivity. We also show that this problem can be addressed by taking an individualized approach by using subject-specific ROIs. Finally we show that ROI selection can affect the way we interpret our data by showing different changes in functional connectivity with ageing.

  14. Altered brain function in new onset childhood acute lymphoblastic leukemia before chemotherapy: A resting-state fMRI study.

    Science.gov (United States)

    Hu, Zhanqi; Zou, Dongfang; Mai, Huirong; Yuan, Xiuli; Wang, Lihong; Li, Yue; Liao, Jianxiang; Liu, Liwei; Liu, Guosheng; Zeng, Hongwu; Wen, Feiqiu

    2017-10-01

    Cognitive impairments had been reported in childhood acute lymphoblastic leukemia, what caused the impairments needed to be demonstrated, chemotherapy-related or the disease itself. The primary aim of this exploratory investigation was to determine if there were changes in brain function of children with acute lymphoblastic leukemia before chemotherapy. In this study, we advanced a measure named regional homogeneity to evaluate the resting-state brain activities, intelligence quotient test was performed at same time. Using regional homogeneity, we first investigated the resting state brain function in patients with new onset childhood acute lymphoblastic leukemia before chemotherapy, healthy children as control. The decreased ReHo values were mainly founded in the default mode network and left frontal lobe, bilateral inferior parietal lobule, bilateral temporal lobe, bilateral occipital lobe, precentral gyrus, bilateral cerebellum in the newly diagnosed acute lymphoblastic leukemia patients compared with the healthy control. While in contrast, increased ReHo values were mainly shown in the right frontal lobe (language area), superior frontal gyrus-R, middle frontal gyrus-R and inferior parietal lobule-R for acute lymphoblastic leukemia patients group. There were no significant differences for intelligence quotient measurements between the acute lymphoblastic leukemia patient group and the healthy control in performance intelligence quotient, verbal intelligence quotient, total intelligence quotient. The altered brain functions are associated with cognitive change and language, it is suggested that there may be cognition impairment before the chemotherapy. Regional homogeneity by functional magnetic resonance image is a sensitive way for early detection on brain damage in childhood acute lymphoblastic leukemia. Copyright © 2017 The Japanese Society of Child Neurology. Published by Elsevier B.V. All rights reserved.

  15. Using concurrent EEG and fMRI to probe the state of the brain in schizophrenia.

    Science.gov (United States)

    Ford, Judith M; Roach, Brian J; Palzes, Vanessa A; Mathalon, Daniel H

    2016-01-01

    Perceptional abnormalities in schizophrenia are associated with hallucinations and delusions, but also with negative symptoms and poor functional outcome. Perception can be studied using EEG-derived event related potentials (ERPs). Because of their excellent temporal resolution, ERPs have been used to ask when perception is affected by schizophrenia. Because of its excellent spatial resolution, functional magnetic resonance imaging (fMRI) has been used to ask where in the brain these effects are seen. We acquired EEG and fMRI data simultaneously to explore when and where auditory perception is affected by schizophrenia. Thirty schizophrenia (SZ) patients and 23 healthy comparison subjects (HC) listened to 1000 Hz tones occurring about every second. We used joint independent components analysis (jICA) to combine EEG-based event-related potential (ERP) and fMRI responses to tones. Five ERP-fMRI joint independent components (JIC) were extracted. The "N100" JIC had temporal weights during N100 (peaking at 100 ms post-tone onset) and fMRI spatial weights in superior and middle temporal gyri (STG/MTG); however, it did not differ between groups. The "P200" JIC had temporal weights during P200 and positive fMRI spatial weights in STG/MTG and frontal areas, and negative spatial weights in the nodes of the default mode network (DMN) and visual cortex. Groups differed on the "P200" JIC: SZ had smaller "P200" JIC, especially those with more severe avolition/apathy. This is consistent with negative symptoms being related to perceptual deficits, and suggests patients with avolition/apathy may allocate too few resources to processing external auditory events and too many to processing internal events.

  16. 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 (pfunctional 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.

  17. Hemispheric preference in visuospatial processing: a complementary approach with fMRI and lesion studies.

    Science.gov (United States)

    Ng, V W; Eslinger, P J; Williams, S C; Brammer, M J; Bullmore, E T; Andrew, C M; Suckling, J; Morris, R G; Benton, A L

    2000-06-01

    Historically, the left cerebral hemisphere has been considered specialized for language, whereas the right cerebral hemisphere is aligned with spatial processes. However, studies have called into question adherence to this model and suggested that both hemispheres participate in language and spatial cognition. Using functional Magnetic Resonance Imaging (fMRI) and human brain lesion studies, we determined whether these complementary techniques could clarify issues of hemispheric dominance. Using a modified Benton Judgement of Line Orientation (JLO) test, considered a relatively pure spatial processing task, we found robust and significant (p < 0.0005) bilateral superior parietal lobe activation on fMRI in ten right-handed male adult volunteers. This was corroborated by lesion data in a cohort of 17 patients who showed significant JLO impairments after either right or left parietal lobe damage, with right parietal damage associated with somewhat more severe deficit. Detailed wavelet analysis of the fMRI time-series did, however, reveal a more dominant role of the right parietal lobe in "kick-starting" the task. To our knowledge, this is a novel way of using fMRI to address functional hemispheric differences in a cognitive task that is known to have bilateral representation.

  18. 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.)

  19. Adolescent development of inhibition as a function of SES and gender: Converging evidence from behavior and fMRI.

    Science.gov (United States)

    Spielberg, Jeffrey M; Galarce, Ezequiel M; Ladouceur, Cecile D; McMakin, Dana L; Olino, Thomas M; Forbes, Erika E; Silk, Jennifer S; Ryan, Neal D; Dahl, Ronald E

    2015-08-01

    The ability to adaptively inhibit responses to tempting/distracting stimuli in the pursuit of goals is an essential set of skills necessary for adult competence and wellbeing. These inhibitory capacities develop throughout childhood, with growing evidence of important maturational changes occurring in adolescence. There also has been intense interest in the role of social adversity on the development of executive function, including inhibitory control. We hypothesized that the onset of adolescence could be a time of particular opportunity/vulnerability in the development of inhibition due to the large degree of maturational changes in neural systems involved in regulatory control. We investigated this hypothesis in a longitudinal study of adolescents by examining the impact of socioeconomic status (SES) on the maturation of inhibition and concurrent brain function. Furthermore, we examined gender as a potential moderator of this relationship, given evidence of gender-specificity in the developmental pathways of inhibition as well as sex differences in adolescent development. Results reveal that lower SES is associated with worse behavioral inhibition over time and a concurrent increase in anterior cingulate (ACC) activation, but only in girls. We also found that lower SES girls exhibited decreased ACC ↔ dorsolateral prefrontal cortex (dlPFC) coupling over time. Our findings suggest that female adolescents with lower SES appear to develop less efficient inhibitory processing in dlPFC, requiring greater and relatively unsuccessful compensatory recruitment of ACC. In summary, the present study provides a novel window into the neural mechanisms by which the influence of SES on inhibition may be transmitted during adolescence.

  20. 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.)

  1. A hierarchical model for probabilistic independent component analysis of multi-subject fMRI studies.

    Science.gov (United States)

    Guo, Ying; Tang, Li

    2013-12-01

    An important goal in fMRI studies is to decompose the observed series of brain images to identify and characterize underlying brain functional networks. Independent component analysis (ICA) has been shown to be a powerful computational tool for this purpose. Classic ICA has been successfully applied to single-subject fMRI data. The extension of ICA to group inferences in neuroimaging studies, however, is challenging due to the unavailability of a pre-specified group design matrix. Existing group ICA methods generally concatenate observed fMRI data across subjects on the temporal domain and then decompose multi-subject data in a similar manner to single-subject ICA. The major limitation of existing methods is that they ignore between-subject variability in spatial distributions of brain functional networks in group ICA. In this article, we propose a new hierarchical probabilistic group ICA method to formally model subject-specific effects in both temporal and spatial domains when decomposing multi-subject fMRI data. The proposed method provides model-based estimation of brain functional networks at both the population and subject level. An important advantage of the hierarchical model is that it provides a formal statistical framework to investigate similarities and differences in brain functional networks across subjects, for example, subjects with mental disorders or neurodegenerative diseases such as Parkinson's as compared to normal subjects. We develop an EM algorithm for model estimation where both the E-step and M-step have explicit forms. We compare the performance of the proposed hierarchical model with that of two popular group ICA methods via simulation studies. We illustrate our method with application to an fMRI study of Zen meditation.

  2. fMRI mapping of the visual system in the mouse brain with interleaved snapshot GE-EPI.

    Science.gov (United States)

    Niranjan, Arun; Christie, Isabel N; Solomon, Samuel G; Wells, Jack A; Lythgoe, Mark F

    2016-06-10

    The use of functional magnetic resonance imaging (fMRI) in mice is increasingly prevalent, providing a means to non-invasively characterise functional abnormalities associated with genetic models of human diseases. The predominant stimulus used in task-based fMRI in the mouse is electrical stimulation of the paw. Task-based fMRI in mice using visual stimuli remains underexplored, despite visual stimuli being common in human fMRI studies. In this study, we map the mouse brain visual system with BOLD measurements at 9.4T using flashing light stimuli with medetomidine anaesthesia. BOLD responses were observed in the lateral geniculate nucleus, the superior colliculus and the primary visual area of the cortex, and were modulated by the flashing frequency, diffuse vs focussed light and stimulus context. Negative BOLD responses were measured in the visual cortex at 10Hz flashing frequency; but turned positive below 5Hz. In addition, the use of interleaved snapshot GE-EPI improved fMRI image quality without diminishing the temporal contrast-noise-ratio. Taken together, this work demonstrates a novel methodological protocol in which the mouse brain visual system can be non-invasively investigated using BOLD fMRI.

  3. Functional cortical changes in relapsing-remitting multiple sclerosis at amplitude configuration: a resting-state fMRI study

    Directory of Open Access Journals (Sweden)

    Liu H

    2016-11-01

    showed high degrees of sensitivity and specificity for distinguishing patients with RRMS from HCs. The EDSS score showed a significant negative Pearson correlation with the beta value of the caudate head (r=-0.474, P=0.047. Conclusion: RRMS is associated with disturbances in spontaneous regional brain activity in specific areas, and these specific abnormalities may provide important information about the neural mechanisms underlying behavioral impairment in RRMS. Keywords: multiple sclerosis, amplitude of low-frequency fluctuation, receiver operating characteristic, functional magnetic resonance imaging, blood oxygen level dependent, resting state

  4. A prosocial online game for social cognition training in adolescents with high-functioning autism: an fMRI study

    Directory of Open Access Journals (Sweden)

    Chung US

    2016-03-01

    helped participants more accurately consider associated environments in response to facial emotional stimulation. However, the online CBT was less effective than the offline-CBT at evoking emotions in response to emotional words. Keywords: autism, online games, sociality, cognitive behavior therapy, functional magnetic resonance image

  5. 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

  6. 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.

  7. A Study of Long-Term fMRI Reproducibility Using Data-Driven Analysis Methods.

    Science.gov (United States)

    Song, Xiaomu; Panych, Lawrence P; Chou, Ying-Hui; Chen, Nan-Kuei

    2014-12-01

    The reproducibility of functional magnetic resonance imaging (fMRI) is important for fMRI-based neuroscience research and clinical applications. Previous studies show considerable variation in amplitude and spatial extent of fMRI activation across repeated sessions on individual subjects even using identical experimental paradigms and imaging conditions. Most existing fMRI reproducibility studies were typically limited by time duration and data analysis techniques. Particularly, the assessment of reproducibility is complicated by a fact that fMRI results may depend on data analysis techniques used in reproducibility studies. In this work, the long-term fMRI reproducibility was investigated with a focus on the data analysis methods. Two spatial smoothing techniques, including a wavelet-domain Bayesian method and the Gaussian smoothing, were evaluated in terms of their effects on the long-term reproducibility. A multivariate support vector machine (SVM)-based method was used to identify active voxels, and compared to a widely used general linear model (GLM)-based method at the group level. The reproducibility study was performed using multisession fMRI data acquired from eight healthy adults over 1.5 years' period of time. Three regions-of-interest (ROI) related to a motor task were defined based upon which the long-term reproducibility were examined. Experimental results indicate that different spatial smoothing techniques may lead to different reproducibility measures, and the wavelet-based spatial smoothing and SVM-based activation detection is a good combination for reproducibility studies. On the basis of the ROIs and multiple numerical criteria, we observed a moderate to substantial within-subject long-term reproducibility. A reasonable long-term reproducibility was also observed from the inter-subject study. It was found that the short-term reproducibility is usually higher than the long-term reproducibility. Furthermore, the results indicate that brain

  8. Characteristics of the default mode functional connectivity in normal ageing and Alzheimer's disease using resting state fMRI with a combined approach of entropy-based and graph theoretical measurements.

    Science.gov (United States)

    Toussaint, Paule-Joanne; Maiz, Sofiane; Coynel, David; Doyon, Julien; Messé, Arnaud; de Souza, Leonardo Cruz; Sarazin, Marie; Perlbarg, Vincent; Habert, Marie-Odile; Benali, Habib

    2014-11-01

    Cognitive decline in normal ageing and Alzheimer's disease (AD) emerges from functional disruption in the coordination of large-scale brain systems sustaining cognition. Integrity of these systems can be examined by correlation methods based on analysis of resting state functional magnetic resonance imaging (fMRI). Here we investigate functional connectivity within the default mode network (DMN) in normal ageing and AD using resting state fMRI. Images from young and elderly controls, and patients with AD were processed using spatial independent component analysis to identify the DMN. Functional connectivity was quantified using integration and indices derived from graph theory. Four DMN sub-systems were identified: Frontal (medial and superior), parietal (precuneus-posterior cingulate, lateral parietal), temporal (medial temporal), and hippocampal (bilateral). There was a decrease in antero-posterior interactions (lower global efficiency), but increased interactions within the frontal and parietal sub-systems (higher local clustering) in elderly compared to young controls. This decreased antero-posterior integration was more pronounced in AD patients compared to elderly controls, particularly in the precuneus-posterior cingulate region. Conjoint knowledge of integration measures and graph indices in the same data helps in the interpretation of functional connectivity results, as comprehension of one measure improves with understanding of the other. The approach allows for complete characterisation of connectivity changes and could be applied to other resting state networks and different pathologies. Copyright © 2014 Elsevier Inc. All rights reserved.

  9. Investigating emotion with music: an fMRI study.

    Science.gov (United States)

    Koelsch, Stefan; Fritz, Thomas; V Cramon, D Yves; Müller, Karsten; Friederici, Angela D

    2006-03-01

    The present study used pleasant and unpleasant music to evoke emotion and functional magnetic resonance imaging (fMRI) to determine neural correlates of emotion processing. Unpleasant (permanently dissonant) music contrasted with pleasant (consonant) music showed activations of amygdala, hippocampus, parahippocampal gyrus, and temporal poles. These structures have previously been implicated in the emotional processing of stimuli with (negative) emotional valence; the present data show that a cerebral network comprising these structures can be activated during the perception of auditory (musical) information. Pleasant (contrasted to unpleasant) music showed activations of the inferior frontal gyrus (IFG, inferior Brodmann's area (BA) 44, BA 45, and BA 46), the anterior superior insula, the ventral striatum, Heschl's gyrus, and the Rolandic operculum. IFG activations appear to reflect processes of music-syntactic analysis and working memory operations. Activations of Rolandic opercular areas possibly reflect the activation of mirror-function mechanisms during the perception of the pleasant tunes. Rolandic operculum, anterior superior insula, and ventral striatum may form a motor-related circuitry that serves the formation of (premotor) representations for vocal sound production during the perception of pleasant auditory information. In all of the mentioned structures, except the hippocampus, activations increased over time during the presentation of the musical stimuli, indicating that the effects of emotion processing have temporal dynamics; the temporal dynamics of emotion have so far mainly been neglected in the functional imaging literature. Copyright 2005 Wiley-Liss, Inc.

  10. Finding multivariate outliers in fMRI time-series data.

    Science.gov (United States)

    Magnotti, John F; Billor, Nedret

    2014-10-01

    A fundamental challenge for researchers studying the brain is to explain how distributed patterns of brain activity relate to a specific representation or computation. Multivariate techniques are therefore becoming increasingly popular for pattern localization of functional magnetic resonance imaging (fMRI) data. The increased power of these techniques can be offset by their susceptibility to multivariate outliers, a problem not directly encountered when fMRI data are analyzed in more common univariate analysis techniques. We test how two algorithms, High Dimensional Blocked Adaptive Computationally Efficient Outlier Nominators (HD BACON) and Principal Component based Outlier detection (PCOut), can detect multivariate outliers in high-dimensional fMRI data, in which the number of variables is larger than the number of observations. We show how these methods can be applied to individual, voxel time-series to identify outlying voxels within a region of interest. Finally, we compare these methods with simulated data to identify which aspects of the data each method is most sensitive to. Voxels identified by both algorithms were primarily on the edges of univariate activation clusters and near the boundaries between different tissue types. Simulation results showed the PCOut outperformed HD BACON, maintaining both high sensitivity and specificity across a wide range of outlier contamination percentages. Our results suggest that multivariate analysis of fMRI can benefit from including multivariate outlier detection as a routine data quality check prior to model fitting. Copyright © 2014 Elsevier Ltd. All rights reserved.

  11. Utility of resting fMRI and connectivity in patients with brain tumor

    Directory of Open Access Journals (Sweden)

    Sandhya Manglore

    2013-01-01

    Full Text Available Background: Resting state (task independent Functional Magnetic Resonance Imaging (fMRI has opened a new avenue in cognitive studies and has found practical clinical applications. Materials and Methods: Resting fMRI analysis was performed in six patients with brain tumor in the motor cortex. For comparison, task-related mapping of the motor cortex was done. Connectivity analysis to study the connections and strength of the connections between the primary motor cortex, premotor cortex, and primary somatosensory cortex on the affected side was also performed and compared with the contralateral normal side and the controls. Results: Resting fMRI in patients with brain tumor in the motor cortex mapped the motor cortex in a task-free state and the results were comparable to the motor task paradigm. Decreased connectivity on the tumor-affected side was observed, as compared to the unaffected side. Conclusion: Resting fMRI and connectivity analysis are useful in the presurgical evaluation of patients with brain tumors and may help in uncooperative or pediatric patients. They can also prognosticate the postoperative outcome. This method also has significant applications due to the ease of image acquisition.

  12. Clustering of Dependent Components: A New Paradigm for fMRI Signal Detection

    Directory of Open Access Journals (Sweden)

    Hurdal Monica K

    2005-01-01

    Full Text Available Exploratory data-driven methods such as unsupervised clustering and independent component analysis (ICA are considered to be hypothesis-generating procedures and are complementary to the hypothesis-led statistical inferential methods in functional magnetic resonance imaging (fMRI. Recently, a new paradigm in ICA emerged, that of finding "clusters" of dependent components. This intriguing idea found its implementation into two new ICA algorithms: tree-dependent and topographic ICA. For fMRI, this represents the unifying paradigm of combining two powerful exploratory data analysis methods, ICA and unsupervised clustering techniques. For the fMRI data, a comparative quantitative evaluation between the two methods, tree-dependent and topographic ICA, was performed. The comparative results were evaluated by (1 task-related activation maps, (2 associated time courses, and (3 ROC study. The most important findings in this paper are that (1 both tree-dependent and topographic ICA are able to identify signal components with high correlation to the fMRI stimulus, and that (2 topographic ICA outperforms all other ICA methods including tree-dependent ICA for 8 and 9 ICs. However for 16 ICs, topographic ICA is outperformed by tree-dependent ICA (KGV using as an approximation of the mutual information the kernel generalized variance. The applicability of the new algorithm is demonstrated on experimental data.

  13. Combining EEG Microstates with fMRI Structural Features for Modeling Brain Activity.

    Science.gov (United States)

    Michalopoulos, Kostas; Bourbakis, Nikolaos

    2015-12-01

    Combining information from Electroencephalography (EEG) and Functional Magnetic Resonance Imaging (fMRI) has been a topic of increased interest recently. The main advantage of the EEG is its high temporal resolution, in the scale of milliseconds, while the main advantage of fMRI is the detection of functional activity with good spatial resolution. The advantages of each modality seem to complement each other, providing better insight in the neuronal activity of the brain. The main goal of combining information from both modalities is to increase the spatial and the temporal localization of the underlying neuronal activity captured by each modality. This paper presents a novel technique based on the combination of these two modalities (EEG, fMRI) that allow a better representation and understanding of brain activities in time. EEG is modeled as a sequence of topographies, based on the notion of microstates. Hidden Markov Models (HMMs) were used to model the temporal evolution of the topography of the average Event Related Potential (ERP). For each model the Fisher score of the sequence is calculated by taking the gradient of the trained model parameters. The Fisher score describes how this sequence deviates from the learned HMM. Canonical Partial Least Squares (CPLS) were used to decompose the two datasets and fuse the EEG and fMRI features. In order to test the effectiveness of this method, the results of this methodology were compared with the results of CPLS using the average ERP signal of a single channel. The presented methodology was able to derive components that co-vary between EEG and fMRI and present significant differences between the two tasks.

  14. Language dominance assessment in a bilingual population: validity of fMRI in the second language.

    Science.gov (United States)

    Centeno, Maria; Koepp, Matthias J; Vollmar, Christian; Stretton, Jason; Sidhu, Meneka; Michallef, Caroline; Symms, Mark R; Thompson, Pamela J; Duncan, John S

    2014-10-01

    Assessment of language dominance using functional magnetic resonance imaging (fMRI) is a standard tool to estimate the risk of language function decline after epilepsy surgery. Although there has been considerable research in the characterization of language networks in bilingual individuals; little is known about the clinical usefulness of language mapping in a secondary language in patients with epilepsy, and how language lateralization assessed by fMRI may differ by the use of native or a secondary language paradigms. In this study we investigate language representation in a population of nonnative English speakers to assess differences in fMRI language lateralization between the first (native) and second language (English). Sixteen nonnative English-speaking patients with focal drug-resistant epilepsy underwent language fMRI in their first (native) language (L1) and in English (L2). Differences between language maps using L1 and L2 paradigms were examined at the single subject level by comparing within-subject lateralization indexes obtained for each language. Differences at the group level were examined for each of the tasks and languages. Group maps for the second language (English) showed overlapping areas of activation with the native language, but with larger clusters, and more bilaterally distributed than for the first language. However, at the individual level, lateralization indexes were concordant between the two languages, except for one patient with bilateral hippocampal sclerosis who was left dominant in English and showed bilateral dominance for verb generation and right dominance for verbal fluency in his native tongue. Language lateralization can generally be reliably derived from fMRI tasks in a second language provided that the subject can follow the task. Subjects with greater likelihood of atypical language representation should be evaluated more carefully, using more than one language paradigm. Wiley Periodicals, Inc. © 2014 International

  15. Bayesian Modelling of fMRI Time Series

    DEFF Research Database (Denmark)

    Højen-Sørensen, Pedro; Hansen, Lars Kai; Rasmussen, Carl Edward

    2000-01-01

    We present a Hidden Markov Model (HMM) for inferring the hidden psychological state (or neural activity) during single trial fMRI activation experiments with blocked task paradigms. Inference is based on Bayesian methodology, using a combination of analytical and a variety of Markov Chain Monte C...... Carlo (MCMC) sampling techniques. The advantage of this method is that detection of short time learning effects between repeated trials is possible since inference is based only on single trial experiments....

  16. 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...... signals even if the fundamental frequency is beyond the Nyquist frequency. We apply the signal detector to locate regions that are highly affected by periodic physiological artifacts, such as cardiac pulsation....

  17. 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.

  18. Topiramate and its effect on fMRI of language in patients with right or left temporal lobe epilepsy.

    Science.gov (United States)

    Szaflarski, Jerzy P; Allendorfer, Jane B

    2012-05-01

    Topiramate (TPM) is well recognized for its negative effects on cognition, language performance and lateralization results on the intracarotid amobarbital procedure (IAP). But, the effects of TPM on functional MRI (fMRI) of language and the fMRI signals are less clear. Functional MRI is increasingly used for presurgical evaluation of epilepsy patients in place of IAP for language lateralization. Thus, the goal of this study was to assess the effects of TPM on fMRI signals. In this study, we included 8 patients with right temporal lobe epilepsy (RTLE) and 8 with left temporal lobe epilepsy (LTLE) taking TPM (+TPM). Matched to them for age, handedness and side of seizure onset were 8 patients with RTLE and 8 with LTLE not taking TPM (-TPM). Matched for age and handedness to the patients with TLE were 32 healthy controls. The fMRI paradigm involved semantic decision/tone decision task (in-scanner behavioral data were collected). All epilepsy patients received a standard neuropsychological language battery. One sample t-tests were performed within each group to assess task-specific activations. Functional MRI data random-effects analysis was performed to determine significant group activation differences and to assess the effect of TPM dose on task activation. Direct group comparisons of fMRI, language and demographic data between patients with R/L TLE +TPM vs. -TPM and the analysis of the effects of TPM on blood oxygenation level-dependent (BOLD) signal were performed. Groups were matched for age, handedness and, within the R/L TLE groups, for the age of epilepsy onset/duration and the number of AEDs/TPM dose. The in-scanner language performance of patients was worse when compared to healthy controls - all pTPM vs. -TPM showed significant fMRI signal differences between groups (increases in left cingulate gyrus and decreases in left superior temporal gyrus in the patients with LTLE +TPM; increases in the right BA 10 and left visual cortex and decreases in the left BA

  19. 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/.

  20. BROCCOLI: Software for fast fMRI analysis on many-core CPUs and GPUs.

    Science.gov (United States)

    Eklund, Anders; Dufort, Paul; Villani, Mattias; Laconte, Stephen

    2014-01-01

    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 mm(3) brain template in 4-6 s, 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/).

  1. Electrodermal Recording and fMRI to Inform Sensorimotor Recovery in Stroke Patients

    Science.gov (United States)

    MacIntosh, Bradley J.; McIlroy, William E.; Mraz, Richard; Staines, W. Richard; Black, Sandra E.; Graham, Simon J.

    2016-01-01

    Background Functional magnetic resonance imaging (fMRI) appears to be useful for investigating motor recovery after stroke. Some of the potential confounders of brain activation studies, however, could be mitigated through complementary physiological monitoring. Objective To investigate a sensorimotor fMRI battery that included simultaneous measurement of electrodermal activity in subjects with hemiparetic stroke to provide a measure related to the sense of effort during motor performance. Methods Bilateral hand and ankle tasks were performed by 6 patients with stroke (2 subacute, 4 chronic) during imaging with blood oxygen level-dependent (BOLD) fMRI using an event-related design. BOLD percent changes, peak activation, and laterality index values were calculated in the sensorimotor cortex. Electrodermal recordings were made concurrently and used as a regressor. Results Sensorimotor BOLD time series and percent change values provided evidence of an intact motor network in each of these well-recovered patients. During tasks involving the hemiparetic limb, electrodermal activity changes were variable in amplitude, and electrodermal activity time-series data showed significant correlations with fMRI in 3 of 6 patients. No such correlations were observed for control tasks involving the unaffected lower limb. Conclusions Electrodermal activity activation maps implicated the contralesional over the ipsilesional hemisphere, supporting the notion that stroke patients may require higher order motor processing to perform simple tasks. Electrodermal activity recordings may be useful as a physiological marker of differences in effort required during movements of a subject’s hemiparetic compared with the unaffected limb during fMRI studies. PMID:18784267

  2. 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.)

  3. BROCCOLI: Software for fast fMRI analysis on many-core CPUs and GPUs

    Science.gov (United States)

    Eklund, Anders; Dufort, Paul; Villani, Mattias; LaConte, Stephen

    2014-01-01

    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 s, 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/). PMID:24672471

  4. fMRI and MEG in the study of typical and atypical cognitive development.

    Science.gov (United States)

    Taylor, M J; Donner, E J; Pang, E W

    2012-01-01

    The tremendous changes in brain structure over childhood are critical to the development of cognitive functions. Neuroimaging provides a means of linking these brain-behaviour relations, as task protocols can be adapted for use with young children to assess the development of cognitive functions in both typical and atypical populations. This paper reviews some of our research using magnetoencephalography (MEG) and functional MRI (fMRI) in the study of cognitive development, with a focus on frontal lobe functions. Working memory for complex abstract patterns showed clear development in terms of the recruitment of frontal regions, seen with fMRI, with indications of strategy differences across the age range, from 6 to 35 years of age. Right hippocampal involvement was also evident in these n-back tasks, demonstrating its involvement in recognition in simple working memory protocols. Children born very preterm (7 to 9 years of age) showed reduced fMRI activation particularly in the precuneus and right hippocampal regions relative to control children. In a large normative n-back study (n=90) with upright and inverted faces, MEG data also showed right hippocampal activation that was present across the age range; frontal sources were evident only from 10 years of age. Other studies have investigated the development of set shifting, an executive function that is often deficit in atypical populations. fMRI showed recruitment of frontal areas, including the insula, that have significantly different patterns in children (7 to 14 years of age) with autism spectrum disorder compared to typically developing children, indicating that successful performance implicated differing strategies in these two groups of children. These types of studies will help our understanding of both normal brain-behaviour development and cognitive dysfunction in atypically developing populations. Copyright © 2011 Elsevier Masson SAS. All rights reserved.

  5. Imaging artifacts induced by electrical stimulation during conventional fMRI of the brain.

    Science.gov (United States)

    Antal, Andrea; Bikson, Marom; Datta, Abhishek; Lafon, Belen; Dechent, Peter; Parra, Lucas C; Paulus, Walter

    2014-01-15

    Functional magnetic resonance imaging (fMRI) of brain activation during transcranial electrical stimulation is used to provide insight into the mechanisms of neuromodulation and targeting of particular brain structures. However, the passage of current through the body may interfere with the concurrent detection of blood oxygen level-dependent (BOLD) signal, which is sensitive to local magnetic fields. To test whether these currents can affect concurrent fMRI recordings we performed conventional gradient echo-planar imaging (EPI) during transcranial direct current (tDCS) and alternating current stimulation (tACS) on two post-mortem subjects. tDCS induced signals in both superficial and deep structures. The signal was specific to the electrode montage, with the strongest signal near cerebrospinal fluid (CSF) and scalp. The direction of change relative to non-stimulation reversed with tDCS stimulation polarity. For tACS there was no net effect of the MRI signal. High-resolution individualized modeling of current flow and induced static magnetic fields suggested a strong coincidence of the change EPI signal with regions of large current density and magnetic fields. These initial results indicate that (1) fMRI studies of tDCS must consider this potentially confounding interference from current flow and (2) conventional MRI imaging protocols can be potentially used to measure current flow during transcranial electrical stimulation. The optimization of current measurement and artifact correction techniques, including consideration of the underlying physics, remains to be addressed.

  6. A Sensitivity Analysis of fMRI Balloon Model

    KAUST Repository

    Zayane, Chadia

    2015-04-22

    Functional magnetic resonance imaging (fMRI) allows the mapping of the brain activation through measurements of the Blood Oxygenation Level Dependent (BOLD) contrast. The characterization of the pathway from the input stimulus to the output BOLD signal requires the selection of an adequate hemodynamic model and the satisfaction of some specific conditions while conducting the experiment and calibrating the model. This paper, focuses on the identifiability of the Balloon hemodynamic model. By identifiability, we mean the ability to estimate accurately the model parameters given the input and the output measurement. Previous studies of the Balloon model have somehow added knowledge either by choosing prior distributions for the parameters, freezing some of them, or looking for the solution as a projection on a natural basis of some vector space. In these studies, the identification was generally assessed using event-related paradigms. This paper justifies the reasons behind the need of adding knowledge, choosing certain paradigms, and completing the few existing identifiability studies through a global sensitivity analysis of the Balloon model in the case of blocked design experiment.

  7. Brain imaging correlates of recovered swallowing after dysphagic stroke: A fMRI and DWI study

    OpenAIRE

    Paul Glad Mihai; Mareile Otto; Martin Domin; Thomas Platz; Shaheen Hamdy; Martin Lotze

    2016-01-01

    Neurogenic dysphagia frequently occurs after stroke and deglutitive aspiration is one of the main reasons for subacute death after stroke. Although promising therapeutic interventions for neurogenic dysphagia are being developed, the functional neuroanatomy of recovered swallowing in this population remains uncertain. Here, we investigated 18 patients post-stroke who recovered from dysphagia using an event related functional magnetic resonance imaging (fMRI) study of swallowing. Patients were...

  8. Residual fMRI sensitivity for identity changes in acquired prosopagnosia

    OpenAIRE

    Fox, Christopher J; Giuseppe eIaria; 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 meas...

  9. Population Receptive Field Properties from fMRI and Electrocorticography in Striate and Extrastriate Cortex of the Same Subject

    Directory of Open Access Journals (Sweden)

    Ben Mark Harvey

    2012-05-01

    Full Text Available Population receptive field (pRF modelling reconstructs the properties of visually responsive neuronal populations, typically using fMRI in humans. However, fMRI is an indirect measure of neural activity. Electrocorticography (ECoG measures electrical activity directly in humans using subdural electrodes. Here, we model pRF properties using both fMRI and ECoG data from the same subject. Prior to clinical intervention, we recorded fMRI responses to visual field mapping stimuli to determine pRF properties and visual area layout. The same subject subsequently underwent surgery to implant subdural ECoG electrodes and was shown the same visual field mapping stimuli while recording ECoG signals. ECoG data were filtered into different spectral bands, which were analysed separately. ECoG electrodes were localised to V1, MT, LO2, and IPS visual areas. Gamma-band responses allowed pRF modelling in all electrodes, and beta-band responses could also be fit in V1. pRF sizes were similar between ECoG and fMRI models. V1 alpha-band amplitude was highest when the stimulus was in the inhibitory surround of the neural population, although this did not reduce the gamma signal below baseline. IPS, MT, and LO2 alpha amplitude was highest when a blank screen was displayed, which was also found in the IPS beta-band. ECoG recording produces comparable results to fMRI for pRF modelling, providing useful validation and extension of fMRI-based reconstruction of neural pRF properties. The fMRI signal cannot be explained by one ECoG spectral density band alone. Alpha band amplitudes reflect inhibitory signals in V1 and resting-state in extra-striate cortex. The same spectral band can reflect different functional processing depending on cortical location.

  10. Functional dissociation of transient and sustained fMRI BOLD components in human auditory cortex revealed with a streaming paradigm based on interaural time differences.

    Science.gov (United States)

    Schadwinkel, Stefan; Gutschalk, Alexander

    2010-12-01

    A number of physiological studies suggest that feature-selective adaptation is relevant to the pre-processing for auditory streaming, the perceptual separation of overlapping sound sources. Most of these studies are focused on spectral differences between streams, which are considered most important for streaming. However, spatial cues also support streaming, alone or in combination with spectral cues, but physiological studies of spatial cues for streaming remain scarce. Here, we investigate whether the tuning of selective adaptation for interaural time differences (ITD) coincides with the range where streaming perception is observed. FMRI activation that has been shown to adapt depending on the repetition rate was studied with a streaming paradigm where two tones were differently lateralized by ITD. Listeners were presented with five different ΔITD conditions (62.5, 125, 187.5, 343.75, or 687.5 μs) out of an active baseline with no ΔITD during fMRI. The results showed reduced adaptation for conditions with ΔITD ≥ 125 μs, reflected by enhanced sustained BOLD activity. The percentage of streaming perception for these stimuli increased from approximately 20% for ΔITD = 62.5 μs to > 60% for ΔITD = 125 μs. No further sustained BOLD enhancement was observed when the ΔITD was increased beyond ΔITD = 125 μs, whereas the streaming probability continued to increase up to 90% for ΔITD = 687.5 μs. Conversely, the transient BOLD response, at the transition from baseline to ΔITD blocks, increased most prominently as ΔITD was increased from 187.5 to 343.75 μs. These results demonstrate a clear dissociation of transient and sustained components of the BOLD activity in auditory cortex.

  11. A New General Linear Convolution Model for fMRI Data Process

    Institute of Scientific and Technical Information of China (English)

    YUAN Hong; CHEN Hua-fu; YAO De-zhong

    2005-01-01

    General linear model (GLM) is the most popular method for functional magnetic resource imaging (fMRI) data analysis. However, its theory is imperfect. The key of this model is how to constitute the design-matrix to model the interesting effects better and separate noises better. For the purpose of detecting brain function activation, according to the principle of GLM, a new convolution model is presented by a new dynamic function convolving with design-matrix, which combining with t-test can be used to detect brain active signal. The fMRI imaging result of visual stimulus experiment indicates that brain activities mainly concentrate among vland v2 areas of visual cortex, and also verified the validity of this technique.

  12. Evaluation of Multiband EPI Acquisitions for Resting State fMRI.

    Directory of Open Access Journals (Sweden)

    Christine Preibisch

    Full Text Available Functional magnetic resonance imaging (fMRI and particularly resting state fMRI (rs-fMRI is widely used to investigate resting state brain networks (RSNs on the systems level. Echo planar imaging (EPI is the state-of-the-art imaging technique for most fMRI studies. Therefore, improvements of EPI might lead to increased sensitivity for a large amount of studies performed every day. A number of developments to shorten acquisition time have been recently proposed and the multiband technique, allowing the simultaneous acquisition of multiple slices yielding an equivalent reduction of measurement time, is the most promising among them. While the prospect to significantly reduce acquisition time by means of high multiband acceleration factors (M appears tempting, signal quality parameters and the sensitivity to detect common RSNs with increasing M-factor have only been partially investigated up to now. In this study, we therefore acquired rs-fMRI data from 20 healthy volunteers to systematically investigate signal characteristics and sensitivity for brain network activity in datasets with increasing M-factor, M = 2 - 4. Combined with an inplane, sensitivity encoding (SENSE, acceleration factor, S = 2, we applied a maximal acceleration factor of 8 (S2×M4. Our results suggest that an M-factor of 2 (total acceleration of 4 only causes negligible SNR decrease but reveals common RSN with increased sensitivity and stability. Further M-factor increase produced random artifacts as revealed by signal quality measures that may affect interpretation of RSNs under common scanning conditions. Given appropriate hardware, a mb-EPI sequence with a total acceleration of 4 significantly reduces overall scanning time and clearly increases sensitivity to detect common RSNs. Together, our results suggest mb-EPI at moderate acceleration factors as a novel standard for fMRI that might increase our understanding of network dynamics in healthy and diseased brains.

  13. Brain imaging correlates of recovered swallowing after dysphagic stroke: A fMRI and DWI study

    Directory of Open Access Journals (Sweden)

    Paul Glad Mihai

    2016-01-01

    Full Text Available Neurogenic dysphagia frequently occurs after stroke and deglutitive aspiration is one of the main reasons for subacute death after stroke. Although promising therapeutic interventions for neurogenic dysphagia are being developed, the functional neuroanatomy of recovered swallowing in this population remains uncertain. Here, we investigated 18 patients post-stroke who recovered from dysphagia using an event related functional magnetic resonance imaging (fMRI study of swallowing. Patients were characterized by initial dysphagia score (mild to severe, lesion mapping, white matter fractional anisotropy (FA of the pyramidal tracts, and swallowing performance measurement during fMRI scanning. Eighteen age matched healthy participants served as a control group. Overall, patients showed decreased fMRI-activation in the entire swallowing network apart from an increase of activation in the contralesional primary somatosensory cortex (S1. Moreover, fMRI activation in contralesional S1 correlated with initial dysphagia score. Finally, when lesions of the pyramidal tract were more severe, recovered swallowing appeared to be associated with asymmetric activation of the ipsilesional anterior cerebellum. Taken together, our data support a role for increased contralesional somatosensory resources and ipsilesional anterior cerebellum feed forward loops for recovered swallowing after dysphagia following stroke.

  14. Mapping the MRI voxel volume in which thermal noise matches physiological noise--implications for fMRI.

    Science.gov (United States)

    Bodurka, J; Ye, F; Petridou, N; Murphy, K; Bandettini, P A

    2007-01-15

    This work addresses the choice of the imaging voxel volume in blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI). Noise of physiological origin that is present in the voxel time course is a prohibitive factor in the detection of small activation-induced BOLD signal changes. If the physiological noise contribution dominates over the temporal fluctuation contribution in the imaging voxel, further increases in the voxel signal-to-noise ratio (SNR) will have diminished corresponding increases in temporal signal-to-noise (TSNR), resulting in reduced corresponding increases in the ability to detect activation induced signal changes. On the other hand, if the thermal and system noise dominate (suggesting a relatively low SNR) further decreases in SNR can prohibit detection of activation-induced signal changes. Here we have proposed and called the "suggested" voxel volume for fMRI the volume where thermal plus system-related and physiological noise variances are equal. Based on this condition we have created maps of fMRI suggested voxel volume from our experimental data at 3T, since this value will spatially vary depending on the contribution of physiologic noise in each voxel. Based on our fast EPI segmentation technique we have found that for gray matter (GM), white matter (WM), and cerebral spinal fluid (CSF) brain compartments the mean suggested cubical voxel volume is: (1.8 mm)3, (2.1 mm)3 and (1.4 mm)3, respectively. Serendipitously, (1.8 mm)3 cubical voxel volume for GM approximately matches the cortical thickness, thus optimizing BOLD contrast by minimizing partial volume averaging. The introduced suggested fMRI voxel volume can be a useful parameter for choice of imaging volume for functional studies.

  15. A Hybrid LDA+gCCA Model for fMRI Data Classification and Visualization.

    Science.gov (United States)

    Afshin-Pour, Babak; Shams, Seyed-Mohammad; Strother, Stephen

    2015-05-01

    Linear predictive models are applied to functional MRI (fMRI) data to estimate boundaries that predict experimental task states for scans. These boundaries are visualized as statistical parametric maps (SPMs) and range from low to high spatial reproducibility across subjects (e.g., Strother , 2004; LaConte , 2003). Such inter-subject pattern reproducibility is an essential characteristic of interpretable SPMs that generalize across subjects. Therefore, we introduce a flexible hybrid model that optimizes reproducibility by simultaneously enhancing the prediction power and reproducibility. This hybrid model is formed by a weighted summation of the optimization functions of a linear discriminate analysis (LDA) model and a generalized canonical correlation (gCCA) model (Afshin-Pour , 2012). LDA preserves the model's ability to discriminate the fMRI scans of multiple brain states while gCCA finds a linear combination for each subject's scans such that the estimated boundary map is reproducible. The hybrid model is implemented in a split-half resampling framework (Strother , 2010) which provides reproducibility (r) and prediction (p) quality metrics. Then the model was compared with LDA, and Gaussian Naive Bayes (GNB). For simulated fMRI data, the hybrid model outperforms the other two techniques in terms of receiver operating characteristic (ROC) curves, particularly for detecting less predictable but spatially reproducible networks. These techniques were applied to real fMRI data to estimate the maps for two task contrasts. Our results indicate that compared to LDA and GNB, the hybrid model can provide maps with large increases in reproducibility for small reductions in prediction, which are jointly closer to the ideal performance point of (p=1, r=1).

  16. Multivariate analysis of fMRI time series: classification and regression of brain responses using machine learning.

    Science.gov (United States)

    Formisano, Elia; De Martino, Federico; Valente, Giancarlo

    2008-09-01

    Machine learning and pattern recognition techniques are being increasingly employed in functional magnetic resonance imaging (fMRI) data analysis. By taking into account the full spatial pattern of brain activity measured simultaneously at many locations, these methods allow detecting subtle, non-strictly localized effects that may remain invisible to the conventional analysis with univariate statistical methods. In typical fMRI applications, pattern recognition algorithms "learn" a functional relationship between brain response patterns and a perceptual, cognitive or behavioral state of a subject expressed in terms of a label, which may assume discrete (classification) or continuous (regression) values. This learned functional relationship is then used to predict the unseen labels from a new data set ("brain reading"). In this article, we describe the mathematical foundations of machine learning applications in fMRI. We focus on two methods, support vector machines and relevance vector machines, which are respectively suited for the classification and regression of fMRI patterns. Furthermore, by means of several examples and applications, we illustrate and discuss the methodological challenges of using machine learning algorithms in the context of fMRI data analysis.

  17. 美沙酮对海洛因成瘾者伏隔核功能连接影响的 fMRI 研究%The effects of methadone in functional connectivity of nucleus accumbens on heroin addicts:a resting state fMRI study

    Institute of Scientific and Technical Information of China (English)

    李永斌; 陈佳杰; 王玮; 王亚蓉; 李玮; 李强; 张东升; 朱佳; 叶建军; 常海峰; 严雪娇

    2015-01-01

    Objective To explore the effect of methadone maintenace treatment (MMT)in functional connectivity (FC)of nucleus accumbens (Nacc)on heroin addicts,and to identify the potential neuromechanism of MMT performing on heroin craving.Methods Craving scores and resting-state fMRI (rs-fMRI)were performed in 37 heroin addicts under MMT and 26 matched heroin addicts (HA) without any treatment.The rs-fMRI data preprocessing was performed by data processing assistant for rs-fMRI (DPARSF)soft-ware based on Matlab 2009a.Bilateral Naccs were set as regions of interesting (ROIs)respectively,and then the mean time series and other voxels within whole brain were analyzed by the rs-fMRI data analysis toolkit (REST).Intra-and inter-group analysis was performed with a single sample t-test and two sample t-test respectively.The partial correlation between the intensity of FC in brain regions showed abnormal FC and the duration/doses of methadone consumption was further investigated by SPSS.Craving scores were tested with two sample t-test.Results Inter-group analysis showed the FC of the right Nacc with left dorsal medial/lateral prefrontal cortex and right dorsal anterior cingulate was significantly increased in the MMT group in comparisonwith HA group,how-ever,it was decreased with right medial orbitofrontal cortex.The FC between the left Nacc and left dorsal medial/lateral prefrontal cortex,right dorsal lateral prefrontal cortex,right dorsal anterior cingulate and left insular cortex was also significantly increased in the MMT group (P 26,t=2.91).There were no regions with induced FC.The craving scores of MMT were signifi-cantly lower than those of HA (t = - 2.03,P 26,t=2.91);MMT 组主观渴求评分显著小于 HA 组(t=-2.03,P 0.05)。结论MMT 可能通过认知控制环路与动机驱动环路的共同作用来影响奖赏环路伏隔核的功能,从而降低海洛因成瘾者的毒品渴求。

  18. 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.

  19. Regional homogeneity on resting state fMRI in patients with tinnitus

    Institute of Scientific and Technical Information of China (English)

    Haidi Yang; Yiqing Zheng; Yongkang Ou; Xiayin Huang

    2014-01-01

    Objective:To study central functional network connections and their alterations in tinnitus patients using fMRI. Methods: Regional homogeneity (ReHo) values on fMRI were obtained from 18 tinnitus patients and 20 age and gender-matched control subjects. ReHo values were compared between tinnitus patients and control subjects to evaluate functional network connection differences. Results:Tinnitus patients showed increased ReHo values in gyrus frontalis inferior and decreased ReHo values in the anterior lobe of cerebellum in comparison with the controls. Analysis of functional network connection from the gyrus frontalis interior shows stronger connections to the middle brain (FWE, P<0.001) and right ventral striatum (FEW, P<0.05, small volume correction). Conclusions: The fMRI results indicate that both auditory and non-auditory centers play important roles in tinnitus. Functional connections among the auditory cortex, thalamus, medial temporal gyrus, parahippocampal gyrus and insula may be an underlying cause for the development of tinnitus.

  20. 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.

  1. Cortical reorganization in children with connatal spastic hemiparesis - a functional magnetic resonance imaging (fMRI) study; Kortikale Reorganisation bei Kindern mit konnataler spastischer Hemiparese - eine funktionelle Magnetresonanztomographie-(fMRT-)Studie

    Energy Technology Data Exchange (ETDEWEB)

    Moeller, F. [Universitaetsklinikum Schleswig-Holstein, Campus Kiel (Germany). Sektion fuer Neuroradiologie; Universitaetsklinikum Schleswig-Holstein, Campus Kiel (Germany). Klinik fuer Neuropaediatrie; Ulmer, S. [Universitaetsklinikum Schleswig-Holstein, Campus Kiel (Germany). Sektion fuer Neuroradiologie; Universitaetsklinikum Schleswig-Holstein, Campus Kiel (Germany). Klinik fuer Neurochirurgie; Wolff, S.; Jansen, O. [Universitaetsklinikum Schleswig-Holstein, Campus Kiel (Germany). Sektion fuer Neuroradiologie; Stephani, U. [Universitaetsklinikum Schleswig-Holstein, Campus Kiel (Germany). Klinik fuer Neuropaediatrie

    2005-11-15

    Purpose: We applied fMRI to investigate atypical cortical activation in patients with connatal spastic hemiparesis using voluntary movements of the hand, foot, and tongue. The relation between the findings from fMRI and the motor dysfunction was examined. Materials and Methods: 11 patients with connatal spastic hemiparesis were studied. Eight of these patients had periventricular leukomalacia (PVL), and three patients had cortical-subcortical lesions. To evaluate the severity of motor impairment tests for the upper and lower limb were performed. fMRI data were obtained in a block design using hand, foot, and tongue movements. As a control group, 14 healthy volunteers were examined with the fMRI protocol. Results: A laterally cortical representation of the paretic foot was found in three patients with PVL. In patients with cortical-subcortical lesions, tongue movements were associated with cortical activation restricted to the unaffected hemisphere. Movements of the paretic limb showed more ipsilateral activation in patients with PVL than in patients with cortical-subcortical lesions. Conclusion: Different types of structural damage such as PVL and cortical-subcortical lesions show differences in fMRI examination. (orig.)

  2. Knowing Who’s Boss: fMRI and ERP Investigations of Social Dominance Perception

    OpenAIRE

    Chiao, Joan Y.; Adams, Reginald B.; Tse, Peter U.; Lowenthal, Lowenthal; Richeson, Jennifer A.; Ambady, Nalini

    2008-01-01

    Humans use facial cues to convey social dominance and submission. Despite the evolutionary importance of this social ability, how the brain recognizes social dominance from the face is unknown. We used event-related brain potentials (ERP) and functional magnetic resonance imaging (fMRI) to examine the neural mechanisms underlying social dominance perception from facial cues. Participants made gender judgments while viewing aggression-related facial expressions as well as facial postures conve...

  3. Enhanced emotional reactivity after selective REM sleep deprivation in humans: an fMRI study

    OpenAIRE

    Rosales-Lagarde, Alejandra; Jorge L Armony; del Río-Portilla, Yolanda; Trejo-Martínez, David; Conde, Ruben; Corsi-Cabrera, Maria

    2012-01-01

    Converging evidence from animal and human studies suggest that rapid eye movement (REM) sleep modulates emotional processing. The aim of the present study was to explore the effects of selective REM sleep deprivation (REM-D) on emotional responses to threatening visual stimuli and their brain correlates using functional magnetic resonance imaging (fMRI). Twenty healthy subjects were randomly assigned to two groups: selective REM-D, by awakening them at each REM sleep onset, or non-rapid eye m...

  4. Enhanced emotional reactivity after selective REM sleep deprivation in humans: an fMRI study

    OpenAIRE

    Alejandra eRosales-Lagarde; Jorge L Armony; Yolanda edel Río-Portilla; David eTrejo-Martínez; Ruben eConde; Maria eCorsi-Cabrera

    2012-01-01

    Converging evidence from animal and human studies suggest that REM sleep modulates emotional processing. The aim of the present study was to explore the effects of selective REM sleep deprivation on emotional responses to threatening visual stimuli and their brain correlates using functional magnetic resonance imaging (fMRI). Twenty healthy subjects were randomly assigned to two groups: selective REM sleep deprivation (REM-D), by awakening them at each REM sleep onset, or NREM sleep interrupt...

  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. PMID:19184561

  6. Area summation in human visual system: psychophysics, fMRI, and modeling.

    Science.gov (United States)

    Nurminen, Lauri; Kilpeläinen, Markku; Laurinen, Pentti; Vanni, Simo

    2009-11-01

    Contextual modulation is a fundamental feature of sensory processing, both on perceptual and on single-neuron level. When the diameter of a visual stimulus is increased, the firing rate of a cell typically first increases (summation field) and then decreases (surround field). Such an area summation function draws a comprehensive profile of the receptive field structure of a neuron, including areas outside the classical receptive field. We investigated area summation in human vision with psychophysics and functional magnetic resonance imaging (fMRI). The stimuli were drifting sine wave gratings similar to those used in previous macaque single-cell area summation studies [corrected]. A model was developed to facilitate comparison of area summation in fMRI to area summation in psychophysics and single cells. The model consisted of units with an antagonistic receptive field structure found in single cells in the primary visual cortex. The receptive field centers of the model neurons were distributed in the region of the visual field covered by a single voxel. The measured area summation functions were qualitatively similar to earlier single-cell data. The model with parameters derived from psychophysics captured the spatial structure of the summation field in the primary visual cortex as measured with fMRI. The model also generalized to a novel situation in which the neural population was displaced from the stimulus center. The current study shows that contextual modulation arises from similar spatially antagonistic and overlapping excitatory and inhibitory mechanisms, both in single cells and in human vision.

  7. 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.

  8. Gaussian Process Based Independent Analysis for Temporal Source Separation in fMRI.

    Science.gov (United States)

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

    2017-02-26

    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 temporal nature. fMRI source signals, biological stimuli and non-stimuli-related artifacts are all smooth over a time-scale compatible with the sampling time (TR). We therefore propose Gaussian process ICA (GPICA), which facilitates temporal dependency by the use of Gaussian process source priors. On two fMRI data sets with different sampling frequency, we show that the GPICA-inferred temporal components and associated spatial maps allow for a more definite interpretation than standard temporal ICA methods. The temporal structures of the sources are controlled by the covariance of the Gaussian process, specified by a kernel function with an interpretable and controllable temporal length scale parameter. We propose a hierarchical model specification, considering both instantaneous and convolutive mixing, and we infer source spatial maps, temporal patterns and temporal length scale parameters by Markov Chain Monte Carlo. A companion implementation made as a plug-in for SPM can be downloaded from https://github.com/dittehald/GPICA.

  9. Decreased sleep duration is associated with increased fMRI responses to emotional faces in children.

    Science.gov (United States)

    Reidy, Brooke L; Hamann, Stephan; Inman, Cory; Johnson, Katrina C; Brennan, Patricia A

    2016-04-01

    In adults and children, sleep loss is associated with affective dysregulation and increased responsivity to negative stimuli. Adult functional neuroimaging (fMRI) studies have demonstrated associations between restricted sleep and neural alterations in the amygdala and reward circuitry when viewing emotional picture and face stimuli. Despite this, few studies have examined the associations between short sleep duration and emotional responsivity in typically developing children, and no studies have investigated this relationship using fMRI. The current study examined the relationship between sleep duration and fMRI activation to emotional facial expressions in 15 male children (ages 7-11 years). During fMRI scanning, subjects viewed and made perceptual judgments regarding negative, neutral, and positive emotional faces. Maternal reported child sleep duration was negatively associated with (a) activation in the bilateral amygdala, left insula, and left temporal pole activation when viewing negative (i.e., fearful, disgust) vs. neutral faces, (b) right orbitofrontal and bilateral prefrontal activation when viewing disgust vs. neutral faces, and (c) bilateral orbitofrontal, right anterior cingulate, and left amygdala activation when viewing happy vs. neutral faces. Consistent with our prediction, we also noted that emotion-dependent functional connectivity between the bilateral amygdala and prefrontal cortex, cingulate, fusiform, and occipital cortex was positively associated with sleep duration. Paralleling similar studies in adults, these findings collectively suggest that decreased sleep duration in school-aged children may contribute to enhanced reactivity of brain regions involved in emotion and reward processing, as well as decreased emotion-dependent functional connectivity between the amygdala and brain regions associated with emotion regulation.

  10. Stability of fMRI striatal response to alcohol cues: a hierarchical linear modeling approach.

    Science.gov (United States)

    Schacht, Joseph P; Anton, Raymond F; Randall, Patrick K; Li, Xingbao; Henderson, Scott; Myrick, Hugh

    2011-05-01

    In functional magnetic resonance imaging (fMRI) studies of alcohol-dependent individuals, alcohol cues elicit activation of the ventral and dorsal aspects of the striatum (VS and DS), which are believed to underlie aspects of reward learning critical to the initiation and maintenance of alcohol dependence. Cue-elicited striatal activation may represent a biological substrate through which treatment efficacy may be measured. However, to be useful for this purpose, VS or DS activation must first demonstrate stability across time. Using hierarchical linear modeling (HLM), this study tested the stability of cue-elicited activation in anatomically and functionally defined regions of interest in bilateral VS and DS. Nine non-treatment-seeking alcohol-dependent participants twice completed an alcohol cue reactivity task during two fMRI scans separated by 14 days. HLM analyses demonstrated that, across all participants, alcohol cues elicited significant activation in each of the regions of interest. At the group level, these activations attenuated slightly between scans, but session-wise differences were not significant. Within-participants stability was best in the anatomically defined right VS and DS and in a functionally defined region that encompassed right caudate and putamen (intraclass correlation coefficients of .75, .81, and .76, respectively). Thus, within this small sample, alcohol cue-elicited fMRI activation had good reliability in the right striatum, though a larger sample is necessary to ensure generalizability and further evaluate stability. This study also demonstrates the utility of HLM analytic techniques for serial fMRI studies, in which separating within-participants variance (individual changes in activation) from between-participants factors (time or treatment) is critical. Copyright © 2011 Elsevier Inc. All rights reserved.

  11. 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.

  12. 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...

  13. Relationship between saccadic eye movements and cortical activity as measured by fMRI

    DEFF Research Database (Denmark)

    Kimmig, H.; Greenlee, M.W.; Gondan, Matthias;

    2001-01-01

    quantitative changes in cortical activity associated with qualitative changes in the saccade task for comparable levels of saccadic activity. All experiments required the simultaneous acquisition of eye movement and fMRI data. For this purpose we used a new high-resolution limbus-tracking technique......We investigated the quantitative relationship between saccadic activity (as reflected in frequency of occurrence and amplitude of saccades) and blood oxygenation level dependent (BOLD) changes in the cerebral cortex using functional magnetic resonance imaging (fMRI). Furthermore, we investigated....... The latter finding is taken to indicate a more demanding cortical processing in the "anti" task than the "pro" task, which could explain the observed difference in BOLD activation. We hold that a quantitative analysis of saccade parameters (especially saccade frequency and latency) is important...

  14. 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.

  15. Pooling fMRI data: meta-analysis, mega-analysis and multi-center studies

    Directory of Open Access Journals (Sweden)

    Sergi G Costafreda

    2009-09-01

    Full Text Available The quantitative analysis of pooled data from related fMRI experiments has the potential to significantly accelerate progress in brain mapping. Such data-pooling can be achieved through meta-analysis (the pooled analysis of published results, mega-analysis (the pooled analysis of raw data or multi-site studies which can be seen as designed mega-analyses. Current limitations in function-location brain mapping and how data-pooling can be used to remediate them are reviewed, with particular attention to power aggregation and mitigation of false positive results. Some recently developed analysis tools for meta- and mega-analysis are also presented, and recommendations for the conduct of valid fMRI data pooling are formulated.

  16. 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.

  17. 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.

  18. 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....... Experimental setups in an imaging spectrometer are not ideally suited for studying the visual pathway of the rodent due to stringent physical constraints imposed by the imaging bore size and strong magnetic field. Here we report a method, applicable to both data acquisition scenarios, for specific...... and reproducible delivery of visual stimuli in fMRI as well as neurophysiology environments. It has the advantage of allowing variation of the stimulus source (e.g. colour of LED) without the need for manipulating the subject in the bore....

  19. 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

  20. Meta-Analysis of fMRI Studies of Disruptive Behavior Disorders.

    Science.gov (United States)

    Alegria, Analucia A; Radua, Joaquim; Rubia, Katya

    2016-11-01

    Functional magnetic resonance imaging (fMRI) studies in conduct disorder and in oppositional defiant disorder have shown inconsistencies. The aim of this meta-analysis of fMRI studies in disruptive behavior disorders was to establish the most consistent brain dysfunctions and to address task- and subtype-related heterogeneity. Web-based publication databases were searched to conduct a meta-analysis of all whole-brain fMRI studies of youths with disruptive behavior disorder or conduct problems up to August 2015. Sub-meta-analyses were conducted in functional subdomains of emotion processing; in cool and hot executive functions, which refer to goal-directed higher cognitive functions with and without motivational and affective significance; and in a subgroup of youths with additional psychopathic traits. The authors performed a meta-analysis of voxel-based group differences in functional activation using the anisotropic effect-size version of seed-based d mapping. Across 24 studies, 338 youths with disruptive behavior disorder or conduct problems relative to 298 typically developing youths had consistent underactivation in the rostral and dorsal anterior cingulate and in the medial prefrontal cortex and ventral caudate. Sub-meta-analyses of fMRI studies showed that medial fronto-cingulate dysfunction was driven by hot executive function. The sub-meta-analysis of emotion processing fMRI studies showed the most consistent underactivation in the dorsolateral prefrontal cortex and temporal pole, while cool executive functions were associated with temporal abnormalities. Youths with disruptive behavior disorder with psychopathic traits showed reduced ventromedial prefrontal-hypothalamic-limbic activation, but they also showed hyperactivation in cognitive control mediating dorsolateral prefrontal-dorsal and striatal regions. The findings show that the most consistent dysfunction in youths with disruptive behavior disorder is in the rostro-dorsomedial, fronto-cingulate, and

  1. Physiological and technical limitations of functional magnetic resonance imaging (fMRI) - consequences for clinical use; Physiologische und technische Grenzen der funktionellen Magnetresonanztomographie und die damit verbundenen Konsequenzen fuer die klinische Anwendung

    Energy Technology Data Exchange (ETDEWEB)

    Wuestenberg, T. [Neurologische Klinik der Charite, Humboldt-Universitaet Berlin (Germany); Neurologische Klinik der Charite, Humboldt-Universitaet Berlin, Schumannstrasse 20/21, 10117, Berlin (Germany); Jordan, K. [Institut fuer Psychologie II, Otto-von-Guericke-Universitaet Magdeburg (Germany); Giesel, F.L. [Abteilung fuer onkologische Diagnostik und Therapie, Deutsches Krebsforschungszentrum Heidelberg (Germany); Villringer, A. [Neurologische Klinik der Charite, Humboldt-Universitaet Berlin (Germany)

    2003-07-01

    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.) [German] Die funktionelle Magnetresonanztomographie (fMRT) ist eines der wichtigsten Verfahren der funktionellen Neuroanatomie. Aufbauend auf einer kurzen Darstellung des aktuellen Wissensstands bzgl. des Zusammenhangs zwischen lokaler neuronaler Aktivitaet und haemodynamischer Reaktion werden ausgewaehlte Moeglichkeiten und Grenzen des Verfahrens fuer die klinische Anwendung diskutiert. Der Schwerpunkt liegt dabei auf der Darstellung der derzeitigen methodischen und technischen Einschraenkungen hinsichtlich einer fMRT-basierten Detektion und Lokalisierung neuronaler Aktivitaet. Es werden die Hauptfehlerquellen und ihre Auswirkungen auf die Reliabilitaet und Validitaet des Verfahrens erlaeutert und aktuelle Loesungsansaetze diskutiert. Abschliessend erfolgt eine Bewertung der aktuellen klinischen Relevanz funktioneller MR-Diagnosemethoden. (orig.)

  2. Classification of mouth movements using 7 T fMRI

    Science.gov (United States)

    Bleichner, M. G.; Jansma, J. M.; Salari, E.; Freudenburg, Z. V.; Raemaekers, M.; Ramsey, N. F.

    2015-12-01

    Objective. A brain-computer interface (BCI) is an interface that uses signals from the brain to control a computer. BCIs will likely become important tools for severely paralyzed patients to restore interaction with the environment. The sensorimotor cortex is a promising target brain region for a BCI due to the detailed topography and minimal functional interference with other important brain processes. Previous studies have shown that attempted movements in paralyzed people generate neural activity that strongly resembles actual movements. Hence decodability for BCI applications can be studied in able-bodied volunteers with actual movements. Approach. In this study we tested whether mouth movements provide adequate signals in the sensorimotor cortex for a BCI. The study was executed using fMRI at 7 T to ensure relevance for BCI with cortical electrodes, as 7 T measurements have been shown to correlate well with electrocortical measurements. Twelve healthy volunteers executed four mouth movements (lip protrusion, tongue movement, teeth clenching, and the production of a larynx activating sound) while in the scanner. Subjects performed a training and a test run. Single trials were classified based on the Pearson correlation values between the activation patterns per trial type in the training run and single trials in the test run in a ‘winner-takes-all’ design. Main results. Single trial mouth movements could be classified with 90% accuracy. The classification was based on an area with a volume of about 0.5 cc, located on the sensorimotor cortex. If voxels were limited to the surface, which is accessible for electrode grids, classification accuracy was still very high (82%). Voxels located on the precentral cortex performed better (87%) than the postcentral cortex (72%). Significance. The high reliability of decoding mouth movements suggests that attempted mouth movements are a promising candidate for BCI in paralyzed people.

  3. fMRI characterization of visual working memory recognition.

    Science.gov (United States)

    Rahm, Benjamin; Kaiser, Jochen; Unterrainer, Josef M; Simon, Juliane; Bledowski, Christoph

    2014-04-15

    Encoding and maintenance of information in visual working memory have been extensively studied, highlighting the crucial and capacity-limiting role of fronto-parietal regions. In contrast, the neural basis of recognition in visual working memory has remained largely unspecified. Cognitive models suggest that recognition relies on a matching process that compares sensory information with the mental representations held in memory. To characterize the neural basis of recognition we varied both the need for recognition and the degree of similarity between the probe item and the memory contents, while independently manipulating memory load to produce load-related fronto-parietal activations. fMRI revealed a fractionation of working memory functions across four distributed networks. First, fronto-parietal regions were activated independent of the need for recognition. Second, anterior parts of load-related parietal regions contributed to recognition but their activations were independent of the difficulty of matching in terms of sample-probe similarity. These results argue against a key role of the fronto-parietal attention network in recognition. Rather the third group of regions including bilateral temporo-parietal junction, posterior cingulate cortex and superior frontal sulcus reflected demands on matching both in terms of sample-probe-similarity and the number of items to be compared. Also, fourth, bilateral motor regions and right superior parietal cortex showed higher activation when matching provided clear evidence for a decision. Together, the segregation between the well-known fronto-parietal activations attributed to attentional operations in working memory from those regions involved in matching supports the theoretical view of separable attentional and mnemonic contributions to working memory. Yet, the close theoretical and empirical correspondence to perceptual decision making may call for an explicit consideration of decision making mechanisms in

  4. Reproducibility of graph metrics in fMRI networks

    Directory of Open Access Journals (Sweden)

    Qawi K Telesford

    2010-12-01

    Full Text Available The reliability of graph metrics calculated in network analysis is essential to the interpretation of complex network organization. These graph metrics are used to deduce the small-world properties in networks. In this study, we investigated the test-retest reliability of graph metrics from functional magnetic resonance imaging (fMRI data collected for two runs in 45 healthy older adults. Graph metrics were calculated on data for both runs and compared using intraclass correlation coefficient (ICC statistics and Bland-Altman (BA plots. ICC scores describe the level of absolute agreement between two measurements and provide a measure of reproducibility. For mean graph metrics, ICC scores were high for clustering coefficient (ICC=0.86, global efficiency (ICC=0.83, path length (ICC=0.79, and local efficiency (ICC=0.75; the ICC score for degree was found to be low (ICC=0.29. ICC scores were also used to generate reproducibility maps in brain space to test voxel-wise reproducibility for unsmoothed and smoothed data. Reproducibility was uniform across the brain for global efficiency and path length, but was only high in network hubs for clustering coefficient, local efficiency and degree. BA plots were used to test the measurement repeatability of all graph metrics. All graph metrics fell within the limits for repeatability. Together, these results suggest that with exception of degree, mean graph metrics are reproducible and suitable for clinical studies. Further exploration is warranted to better understand reproducibility across the brain on a voxel-wise basis.

  5. 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.

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

    Science.gov (United States)

    Kleint, Nina I; Wittchen, Hans-Ulrich; Lueken, Ulrike

    2015-01-01

    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.

  7. Four-dimensional compression of fMRI using JPEG2000

    Science.gov (United States)

    Lalgudi, Hariharan G.; Bilgin, Ali; Marcellin, Michael W.; Tabesh, Ali; Nadar, Mariappan S.; Trouard, Theodore P.

    2005-04-01

    Many medical imaging techniques available today generate 4D data sets. One such technique is functional magnetic resonance imaging (fMRI) which aims to determine regions of the brain that are activated due to various cognitive and/or motor functions or sensory stimuli. These data sets often require substantial resources for storage and transmission and hence call for efficient compression algorithms. fMRI data can be seen as a time-series of 3D images of the brain. Many different strategies can be employed for compressing such data. One possibility is to treat each 2D slice independently. Alternatively, it is also possible to compress each 3D image independently. Such methods do not fully exploit the redundancy present in 4D data. In this work, methods using 4D wavelet transforms are proposed. They are compared to different 2D and 3D methods. The proposed schemes are based on JPEG2000, which is included in the DICOM standard as a transfer syntax. Methodologies to test the effects of lossy compression on the end result of fMRI analysis are introduced and used to compare different compression algorithms.

  8. Parcellation of fMRI Datasets with ICA and PLS-A Data Driven Approach

    CERN Document Server

    Ji, Yongnan; Aickelin, Uwe; Pitiot, Alain

    2010-01-01

    Inter-subject parcellation of functional Magnetic Resonance Imaging (fMRI) data based on a standard General Linear Model (GLM)and spectral clustering was recently proposed as a means to alleviate the issues associated with spatial normalization in fMRI. However, for all its appeal, a GLM-based parcellation approach introduces its own biases, in the form of a priori knowledge about the shape of Hemodynamic Response Function (HRF) and task-related signal changes, or about the subject behaviour during the task. In this paper, we introduce a data-driven version of the spectral clustering parcellation, based on Independent Component Analysis (ICA) and Partial Least Squares (PLS) instead of the GLM. First, a number of independent components are automatically selected. Seed voxels are then obtained from the associated ICA maps and we compute the PLS latent variables between the fMRI signal of the seed voxels (which covers regional variations of the HRF) and the principal components of the signal across all voxels. F...

  9. Independent component analysis in the presence of noise in fMRI.

    Science.gov (United States)

    Cordes, Dietmar; Nandy, Rajesh

    2007-11-01

    A noisy version of independent component analysis (noisy ICA) is applied to simulated and real functional magnetic resonance imaging (fMRI) data. The noise covariance is explicitly modeled by an autoregressive (AR) model of order 1. The unmixing matrix of the data is determined using a variant of the FastICA algorithm based on Gaussian moments. The sources are estimated using the principle of maximum likelihood by modeling the source densities as asymmetric exponential functions. Effect of dimensionality reduction on the effective noise covariance used, accuracy of the obtained mixing matrix and degree of improvement in estimating fMRI sources are investigated. The primary conclusions after using this method of evaluation are as follows: (a) weighting matrix estimates are similar for noisy and conventional ICA in the realm of typical fMRI data, and (b) source estimates are improved by 5% (as measured by the correlation coefficient) in realistic simulated data by explicitly modeling the source densities and the noise, even when just a simple white noise model is used.

  10. Silent speechreading in the absence of scanner noise: an event-related fMRI study.

    Science.gov (United States)

    MacSweeney, M; Amaro, E; Calvert, G A; Campbell, R; David, A S; McGuire, P; Williams, S C; Woll, B; Brammer, M J

    2000-06-05

    In a previous study we used functional magnetic resonance imaging (fMRI) to demonstrate activation in auditory cortex during silent speechreading. Since image acquisition during fMRI generates acoustic noise, this pattern of activation could have reflected an interaction between background scanner noise and the visual lip-read stimuli. In this study we employed an event-related fMRI design which allowed us to measure activation during speechreading in the absence of acoustic scanner noise. In the experimental condition, hearing subjects were required to speechread random numbers from a silent speaker. In the control condition subjects watched a static image of the same speaker with mouth closed and were required to subvocally count an intermittent visual cue. A single volume of images was collected to coincide with the estimated peak of the blood oxygen level dependent (BOLD) response to these stimuli across multiple baseline and experimental trials. Silent speechreading led to greater activation in lateral temporal cortex relative to the control condition. This indicates that activation of auditory areas during silent speechreading is not a function of acoustic scanner noise and confirms that silent speechreading engages similar regions of auditory cortex as listening to speech.

  11. Probing the mysterious underpinnings of multi-voxel fMRI analyses.

    Science.gov (United States)

    Op de Beeck, Hans P

    2010-04-01

    Various arguments have been proposed for or against sub-voxel sensitivity or hyperacuity in functional magnetic resonance imaging (fMRI) at standard resolution. Sub-voxel sensitivity might exist, but nevertheless the performance of multi-voxel fMRI analyses is very likely to be dominated by a larger-scale organization, even if this organization is very weak. Up to now, most arguments are indirect in nature: they do not in themselves proof or contradict sub-voxel sensitivity, but they are suggestive, seem consistent or not with sub-voxel sensitivity, or show that the principle might or might not work. Here the previously proposed smoothing argument against hyperacuity is extended with simulations that include more realistic signal, noise, and analysis properties than any of the simulations presented before. These simulations confirm the relevance of the smoothing approach to find out the scale of the functional maps that underlie the outcome of multi-voxel analyses, at least in relative terms (differences in the scale of different maps). However, image smoothing, like most other arguments in the literature, is an indirect argument, and at the end of the day such arguments are not sufficient to decide the issue on whether and how much sub-voxel maps contribute. A few suggestions are made about the type of evidence that is needed to help us understand the as yet mysterious underpinnings of multi-voxel fMRI analyses.

  12. 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

  13. Surface EMG measurements during fMRI at 3T : Accurate EMG recordings after artifact correction

    NARCIS (Netherlands)

    van Duinen, Hiske; Zijdewind, Inge; Hoogduin, H; Maurits, N

    2005-01-01

    In this experiment, we have measured surface EMG of the first dorsal interosseus during predefined submaximal isometric contractions (5, 15, 30, 50, and 70% of maximal force) of the index finger simultaneously with fMRI measurements. Since we have used sparse sampling fMRI (3-s scanning; 2-s non-sca

  14. Flexible multivariate hemodynamics fMRI data analyses and simulations with PyHRF

    Directory of Open Access Journals (Sweden)

    Thomas eVincent

    2014-04-01

    Full Text Available As part of fMRI data analysis, the pyhrf package provides a set of tools for addressing the two main issues involved in intra-subject fMRI data analysis: (i the localization of cerebral regions that elicit evoked activity and (ii the estimation of activation dynamics also known as Hemodynamic Response Function (HRF recovery. To tackle these two problems, pyhrf implements the Joint Detection-Estimation framework~(JDE which recovers parcel-level HRFs and embeds an adaptive spatio-temporal regularization scheme of activation maps. With respect to the sole detection issue~(i, the classical voxelwise GLM procedure is also available through nipy, whereas Finite Impulse Response~(FIR and temporally regularized FIR models are concerned with HRF estimation~(ii and are specifically implemented in pyhrf. Several parcellation tools are also integrated such as spatial and functional clustering. Parcellations may be used for spatial averaging prior to FIR/RFIR analysis or to specify the spatial support of the HRF estimates in the JDE approach. These analysis procedures can be applied either to volumic data sets or to data projected onto the cortical surface. For validation purpose, this package is shipped with artificial and real fMRI data sets, which are used in this paper to compare the outcome of the different available approaches. The artificial fMRI data generator is also described to illustrate how to simulate different activation configurations, HRF shapes or nuisance components. To cope with the high computational needs for inference, pyhrf handles distributing computing by exploiting cluster units as well as multi-core machines. Finally, a dedicated viewer is presented, which handles $n$-dimensional images and provides suitable features to explore whole brain hemodynamics~(time series, maps, ROI mask overlay.

  15. A new trigemino-nociceptive stimulation model for event-related fMRI.

    Science.gov (United States)

    Stankewitz, A; Voit, H L; Bingel, U; Peschke, C; May, A

    2010-04-01

    Functional imaging of human trigemino-nociceptive processing provides meaningful insights into altered pain processing in head and face pain diseases. Although functional magnetic resonance imaging (fMRI) offers high temporal and spatial resolution, most studies available were done with radioligand-positron emission tomography, as fMRI requires non-magnetic stimulus equipment and fast on-off conditions. We developed a new approach for painful stimulation of the trigeminal nerve that can be implemented within an event-related design using fMRI and aimed to detect increased blood-oxygen-level-dependent (BOLD) signals as surrogate markers of trigeminal pain processing. Using an olfactometer, 20 healthy volunteers received intranasally standardized trigeminal nociceptive stimuli (ammonia gas) as well as olfactory (rose odour) and odorless control stimuli (air puffs). Imaging revealed robust BOLD responses to the trigeminal nociceptive stimulation in cortical and subcortical brain areas known to be involved in pain processing. Focusing on the trigeminal pain pathway, significant activations were observed bilaterally in brainstem areas at the trigeminal nerve entry zone, which are agreeable with the principal trigeminal nuclei. Furthermore, increased signal changes could be detected ipsilaterally at anatomical localization of the trigeminal ganglion and bilaterally in the rostral medulla, which probably represents the spinal trigeminal nuclei. However, brainstem areas involved in the endogenous pain control system that are close to this anatomical localization, such as raphe nuclei, have to be discussed. Our findings suggest that mapping trigeminal pain processing using fMRI with this non-invasive experimental design is feasible and capable of evoking specific activations in the trigeminal nociceptive system. This method will provide an ideal opportunity to study the trigeminal pain system in both health and pathological conditions such as idiopathic headache disorders.

  16. The application of independent component analysis with projection method to two-task fMRI data over multiple subjects

    Science.gov (United States)

    Li, Rui; Hui, Mingqi; Yao, Li; Chen, Kewei; Long, Zhiying

    2011-03-01

    Spatial Independent component analysis (sICA) has been successfully used to analyze functional magnetic resonance (fMRI) data. However, the application of ICA was limited in multi-task fMRI data due to the potential spatial dependence between task-related components. Long et al. (2009) proposed ICA with linear projection (ICAp) method and demonstrated its capacity to solve the interaction among task-related components in multi-task fMRI data of single subject. However, it's unclear that how to perform ICAp over a group of subjects. In this study, we proposed a group analysis framework on multi-task fMRI data by combining ICAp with the temporal concatenation method reported by Calhoun (2001). The results of real fMRI experiment containing multiple visual processing tasks demonstrated the feasibility and effectiveness of the group ICAp method. Moreover, compared to the GLM method, the group ICAp method is more sensitive to detect the regions specific to each task.

  17. Network Connectivity in Epilepsy: Resting State fMRI and EEG-fMRI Contributions.

    Science.gov (United States)

    Centeno, Maria; Carmichael, David W

    2014-01-01

    There is a growing body of evidence pointing toward large-scale networks underlying the core phenomena in epilepsy, from seizure generation to cognitive dysfunction or response to treatment. The investigation of networks in epilepsy has become a key concept to unlock a deeper understanding of the disease. Functional imaging can provide valuable information to characterize network dysfunction; in particular resting state fMRI (RS-fMRI), which is increasingly being applied to study brain networks in a number of diseases. In patients with epilepsy, network connectivity derived from RS-fMRI has found connectivity abnormalities in a number of networks; these include the epileptogenic, cognitive and sensory processing networks. However, in majority of these studies, the effect of epileptic transients in the connectivity of networks has been neglected. EEG-fMRI has frequently shown networks related to epileptic transients that in many cases are concordant with the abnormalities shown in RS studies. This points toward a relevant role of epileptic transients in the network abnormalities detected in RS-fMRI studies. In this review, we summarize the network abnormalities reported by these two techniques side by side, provide evidence of their overlapping findings, and discuss their significance in the context of the methodology of each technique. A number of clinically relevant factors that have been associated with connectivity changes are in turn associated with changes in the frequency of epileptic transients. These factors include different aspects of epilepsy ranging from treatment effects, cognitive processes, or transition between different alertness states (i.e., awake-sleep transition). For RS-fMRI to become a more effective tool to investigate clinically relevant aspects of epilepsy it is necessary to understand connectivity changes associated with epileptic transients, those associated with other clinically relevant factors and the interaction between them, which

  18. Network Connectivity in Epilepsy: Resting State fMRI and EEG–fMRI Contributions

    Science.gov (United States)

    Centeno, Maria; Carmichael, David W.

    2014-01-01

    There is a growing body of evidence pointing toward large-scale networks underlying the core phenomena in epilepsy, from seizure generation to cognitive dysfunction or response to treatment. The investigation of networks in epilepsy has become a key concept to unlock a deeper understanding of the disease. Functional imaging can provide valuable information to characterize network dysfunction; in particular resting state fMRI (RS-fMRI), which is increasingly being applied to study brain networks in a number of diseases. In patients with epilepsy, network connectivity derived from RS-fMRI has found connectivity abnormalities in a number of networks; these include the epileptogenic, cognitive and sensory processing networks. However, in majority of these studies, the effect of epileptic transients in the connectivity of networks has been neglected. EEG–fMRI has frequently shown networks related to epileptic transients that in many cases are concordant with the abnormalities shown in RS studies. This points toward a relevant role of epileptic transients in the network abnormalities detected in RS-fMRI studies. In this review, we summarize the network abnormalities reported by these two techniques side by side, provide evidence of their overlapping findings, and discuss their significance in the context of the methodology of each technique. A number of clinically relevant factors that have been associated with connectivity changes are in turn associated with changes in the frequency of epileptic transients. These factors include different aspects of epilepsy ranging from treatment effects, cognitive processes, or transition between different alertness states (i.e., awake–sleep transition). For RS-fMRI to become a more effective tool to investigate clinically relevant aspects of epilepsy it is necessary to understand connectivity changes associated with epileptic transients, those associated with other clinically relevant factors and the interaction between them

  19. ICA-fNORM: Spatial normalization of fMRI data using intrinsic group-ICA networks

    Directory of Open Access Journals (Sweden)

    Siddharth eKhullar

    2011-11-01

    Full Text Available A common pre-processing challenge associated with group-level fMRI analysis is spatial registration of multiple subjects to a standard space. Spatial normalization, using a reference image such as the Montreal Neurological Institute (MNI brain template, is the most common technique currently in use to achieve spatial congruence across multiple subjects. This method corrects for global shape differences preserving regional asymmetries, but does not account for functional differences. We propose a novel approach to co-register task-based fMRI data using resting-state group ICA networks. We posit that these intrinsic networks can provide to the spatial normalization process with important information about how each individual’s brain is organized functionally. The algorithm is initiated by the extraction of single-subject representations of intrinsic networks using group level independent component analysis (ICA on resting state fMRI data. In this proof of concept work two of the robust, commonly identified, networks are chosen as functional templates. As an estimation step, the relevant intrinsic networks are utilized to derive a set of normalization parameters for each subject. Finally, the normalization parameters are applied individually to a different set of fMRI data acquired while the subjects performed an auditory oddball task. These normalization parameters, although derived using rest data, generalize successfully to data obtained with a cognitive paradigm for each subject. The improvement in results is verified using two widely applied fMRI analysis methods¬: the general linear model (GLM and ICA. Resulting activation patterns from each analysis method show significant improvements in terms of detection sensitivity and statistical significance at the group level. The results presented in this article provide initial evidence to show that common functional domains from the resting state brain may be used to improve the group statistics

  20. 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; Beeinflusst die individuelle Anpassung standardisierter Sprachparadigmen fuer die klinische funktionelle Magnetresonanztomographie (fMRT) die Lokalisation der sprachdominanten Hemisphaere, des Broca- und des Wernicke-Sprachzentrums?

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    Konrad, F.; Nennig, E.; Kress, B.; Sartor, K.; Stippich, C. [Abteilung Neuroradiologie, Neurologische Klinik, Universitaetsklinikum Heidelberg (Germany); Ochmann, H. [Neurochirurgische Klinik, Universitaetsklinikum Heidelberg (Germany)

    2005-03-01

    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 ({delta}S) 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.)

  1. 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.

  2. Assessing cue-induced brain response as a function of abstinence duration in heroin-dependent individuals: an event-related fMRI study.

    Directory of Open Access Journals (Sweden)

    Qiang Li

    Full Text Available The brain activity induced by heroin-related cues may play a role in the maintenance of heroin dependence. Whether the reinforcement or processing biases construct an everlasting feature of heroin addiction remains to be resolved. We used an event-related fMRI paradigm to measure brain activation in response to heroin cue-related pictures versus neutral pictures as the control condition in heroin-dependent patients undergoing short-term and long-term abstinence. The self-reported craving scores were significantly increased after cue exposure in the short-term abstinent patients (t = 3.000, P = 0.008, but no increase was found in the long-term abstinent patients (t = 1.510, P = 0.149. However, no significant differences in cue-induced craving changes were found between the two groups (t = 1.193, P = 0.850. Comparing between the long-term abstinence and short-term abstinence groups, significant decreases in brain activation were detected in the bilateral anterior cingulated cortex, left medial prefrontal cortex, caudate, middle occipital gyrus, inferior parietal lobule and right precuneus. Among all of the heroin dependent patients, the abstinence duration was negatively correlated with brain activation in the left medial prefrontal cortex and left inferior parietal lobule. These findings suggest that long-term abstinence may be useful for heroin-dependent patients to diminish their saliency value of heroin-related cues and possibly lower the relapse vulnerability to some extent.

  3. 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.

  4. Detection of Brain Reorganization in Pediatric Multiple Sclerosis Using Functional MRI

    Science.gov (United States)

    2015-10-01

    surgical site. 15. SUBJECT TERMS Functional brain mapping using fMRI, functional magnetic resonance imaging (fMRI), pediatric-onset multiple sclerosis (POMS...Fluency, for verbal fluency; DKEFS Trails, for visual motor-sequencing; and a Grooved Pegboard task to assess manipulation dexterity. Results for...epilepsy patients at our institution. We have explored fMRI for improving epilepsy surgical planning in pediatric patients. To that end we acquired

  5. Preserving Subject Variability in Group fMRI Analysis: Performance Evaluation of GICA versus IVA

    Directory of Open Access Journals (Sweden)

    Andrew eMichael

    2014-06-01

    Full Text Available Independent component analysis (ICA is a widely applied technique to derive functionally connected brain networks from fMRI data. Group ICA (GICA and Independent Vector Analysis (IVA are extensions of ICA that enable users to perform group fMRI analyses; however a full comparison of the performance limits of GICA and IVA has not been investigated. Recent interest in resting state fMRI data with potentially higher degree of subject variability makes the evaluation of the above techniques important. In this paper we compare component estimation accuracies of GICA and an improved version of IVA using simulated fMRI datasets. We systematically change the degree of component spatial variability and evaluate estimation accuracy over all spatial maps (SMs and time courses (TCs of the decomposition. Our results indicate the following: (1 at low levels of SM variability or when just one SM is varied, both GICA and IVA perform well, (2 at higher levels of SM variability or when more than one SMs are varied, IVA continues to perform well but GICA yields SM estimates that are composites of other SMs with errors in TCs, (3 both GICA and IVA remove spatial correlations of overlapping SMs and introduce artificial correlations in their TCs, (4 if number of SMs is over estimated, IVA continues to perform well but GICA introduces artifacts in the varying and extra SMs with artificial correlations in the TCs of extra components, and (5 in the absence or presence of SMs unique to one subject, GICA produces errors in TCs and IVA estimates are accurate. In summary, our simulation experiments (both simplistic and realistic and our holistic analyses approach indicate that IVA produces results that are closer to ground truth and thereby better preserves subject variability. The improved version of IVA is now packaged into the GIFT toolbox (http://mialab.mrn.org/software/gift.

  6. 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.

  7. Effective Connectivity Modeling for fMRI: Six Issues and Possible Solutions Using Linear Dynamic Systems

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    Jason Fitzgerald Smith

    2012-01-01

    Full Text Available Analysis of directionally specific or causal interactions between regions in functional magnetic resonance imaging (fMRI data has proliferated. Here we identify six issues with existing effective connectivity methods that need addressed. The issues are discussed within the framework of Linear Dynamic Systems for fMRI (LDSf. The first concerns the use of deterministic models to identify inter-regional effective connectivity. We show that deterministic dynamics are incapable of identifying the trial-to-trial variability typically investigated as the marker of connectivity while stochastic models can capture this variability. The second concerns the simplistic (constant connectivity modeled by most methods. Connectivity parameters of the LDSf model can vary at the same timescale as the input data. Further, extending LDSf to mixtures of multiple models provides more robust connectivity variation. The third concerns the correct identification of the network itself including the number and anatomical origin of the network nodes. Augmentation of the LDSf state space can identify additional nodes of a network. The fourth concerns the locus of the signal used as a node in a network. A novel extension LDSf incorporating sparse canonical correlations can select most relevant voxels from an anatomically defined region based on connectivity. The fifth concerns connection interpretation. Individual parameter differences have received most attention. We present alternative network descriptors of connectivity changes which consider the whole network. The sixth concerns the temporal resolution of fMRI data relative to the timescale of the inter-regional interactions in the brain. LDSf includes an instantaneous connection term to capture connectivity occurring at timescales faster than the data resolution. The LDS framework can also be extended to statistically combine fMRI and EEG data. The LDSf framework is a promising foundation for effective connectivity

  8. Prioritizing spatial accuracy in high-resolution fMRI data using multivariate feature weight mapping

    Directory of Open Access Journals (Sweden)

    Johannes eStelzer

    2014-04-01

    Full Text Available Although ultra-high-field fMRI at field strengths of 7T or above provides substantial gains in BOLD contrast-to-noise ratio, when very high-resolution fMRI is required such gains are inevitably reduced. The improvement in sensitivity provided by multivariate analysis techniques, as compared with univariate methods, then becomes especially welcome. Information mapping approaches are commonly used, such as the searchlight technique, which take into account the spatially distributed patterns of activation in order to predict stimulus conditions. However, the popular searchlight decoding technique, in particular, has been found to be prone to spatial inaccuracies. For instance, the spatial extent of informative areas is generally exaggerated, and their spatial configuration is distorted. We propose the combination of a nonparametric and permutation-based statistical framework with linear classifiers. We term this new combined method Feature Weight Mapping (FWM. The main goal of the proposed method is to map the specific contribution of each voxel to the classification decision while including a correction for the multiple comparisons problem. Next, we compare this new method to the searchlight approach using a simulation and ultra-high-field 7T experimental data. We found that the searchlight method led to spatial inaccuracies that are especially noticeable in high-resolution fMRI data. In contrast, FWM was more spatially precise, revealing both informative anatomical structures as well as the direction by which voxels contribute to the classification. By maximizing the spatial accuracy of ultra-high-field fMRI results, global multivariate methods provide a substantial improvement for characterizing structure-function relationships.

  9. Preserving subject variability in group fMRI analysis: performance evaluation of GICA vs. IVA.

    Science.gov (United States)

    Michael, Andrew M; Anderson, Mathew; Miller, Robyn L; Adalı, Tülay; Calhoun, Vince D

    2014-01-01

    Independent component analysis (ICA) is a widely applied technique to derive functionally connected brain networks from fMRI data. Group ICA (GICA) and Independent Vector Analysis (IVA) are extensions of ICA that enable users to perform group fMRI analyses; however a full comparison of the performance limits of GICA and IVA has not been investigated. Recent interest in resting state fMRI data with potentially higher degree of subject variability makes the evaluation of the above techniques important. In this paper we compare component estimation accuracies of GICA and an improved version of IVA using simulated fMRI datasets. We systematically change the degree of inter-subject spatial variability of components and evaluate estimation accuracy over all spatial maps (SMs) and time courses (TCs) of the decomposition. Our results indicate the following: (1) at low levels of SM variability or when just one SM is varied, both GICA and IVA perform well, (2) at higher levels of SM variability or when more than one SMs are varied, IVA continues to perform well but GICA yields SM estimates that are composites of other SMs with errors in TCs, (3) both GICA and IVA remove spatial correlations of overlapping SMs and introduce artificial correlations in their TCs, (4) if number of SMs is over estimated, IVA continues to perform well but GICA introduces artifacts in the varying and extra SMs with artificial correlations in the TCs of extra components, and (5) in the absence or presence of SMs unique to one subject, GICA produces errors in TCs and IVA estimates are accurate. In summary, our simulation experiments (both simplistic and realistic) and our holistic analyses approach indicate that IVA produces results that are closer to ground truth and thereby better preserves subject variability. The improved version of IVA is now packaged into the GIFT toolbox (http://mialab.mrn.org/software/gift).

  10. 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.

  11. An fMRI study on the neural mechanisms of hyperalgesic nocebo effect

    Science.gov (United States)

    Kong, Jian; Gollub, Randy L.; Polich, Ginger; Kirsch, Irving; LaViolette, Peter; Vangel, Mark; Rosen, Bruce; Kaptchuk, Ted J

    2008-01-01

    Summary Previous studies suggest that nocebo effects, sometimes termed “negative placebo effects,” can contribute appreciably to a variety of medical symptoms and adverse events in clinical trials and medical care. In this study, using a within-subject design, we combined fMRI and an expectation / conditioning manipulation model to investigate the neural substrates of nocebo hyperalgesia using heat pain on the right forearm. Thirteen subjects completed the study. Results showed that after administering inert treatment, subjective pain intensity ratings increased significantly more on nocebo regions as compared with the control regions where no expectancy / conditioning manipulation was performed. fMRI analysis of hyperalgesic nocebo responses to identical calibrated noxious stimuli showed signal increases in brain regions including bilateral dorsal ACC, insula, superior temporal gyrus; left frontal and parietal operculum, medial frontal gyrus, orbital prefrontal cortex, superior parietal lobule and hippocampus; right claustrum / putamen, lateral prefrontal gyrus and middle temporal gyrus. Functional connectivity analysis of spontaneous resting-state fMRI data from the same cohort of subjects showed a correlation between two seed regions (frontal operculum and left hippocampus) pain network including bilateral insula, operculum, ACC, and left S1 / M1. In conclusion, we found evidence that nocebo hyperalgesia may be predominantly produced through an affective-cognitive pain pathway (medial pain system) and the left hippocampus may play an important role in this process. PMID:19052227

  12. 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.

  13. Adaptive thresholding for reliable topological inference in single subject fMRI analysis

    Directory of Open Access Journals (Sweden)

    Krzysztof eGorgolewski

    2012-08-01

    Full Text Available Single subject fMRI has proved to be a useful tool for mapping functional areas in clinical procedures such as tumour resection. Using fMRI data, clinicians assess the risk, plan and execute such procedures based on thresholded statistical maps. However, because current thresholding methods were developed mainly in the context of cognitive neuroscience group studies, most single subject fMRI maps are thresholded manually to satisfy specific criteria related to single subject analyses. Here, we propose a new adaptive thresholding method which combines Gamma-Gaussian mixture modelling with topological thresholding to improve cluster delineation. In a series of simulations we show that by adapting to the signal and noise properties, the new method performs well in terms of the trade-off between false negative and positive cluster error rates as well as in terms of over and underestimation of the true activation border. We also show through simulations and a motor test-retest study on ten volunteer subjects that adaptive thresholding improves reliability, mainly by accounting for the global signal variance. This in turn increases the likelihood that the true activation pattern can be determined.

  14. Optimizing the imaging of the monkey auditory cortex: sparse vs. continuous fMRI.

    Science.gov (United States)

    Petkov, Christopher I; Kayser, Christoph; Augath, Mark; Logothetis, Nikos K

    2009-10-01

    The noninvasive imaging of the monkey auditory system with functional magnetic resonance imaging (fMRI) can bridge the gap between electrophysiological studies in monkeys and imaging studies in humans. Some of the recent imaging of monkey auditory cortical and subcortical structures relies on a technique of "sparse imaging," which was developed in human studies to sidestep the negative influence of scanner noise by adding periods of silence in between volume acquisition. Among the various aspects that have gone into the ongoing optimization of fMRI of the monkey auditory cortex, replacing the more common continuous-imaging paradigm with sparse imaging seemed to us to make the most obvious difference in the amount of activity that we could reliably obtain from awake or anesthetized animals. Here, we directly compare the sparse- and continuous-imaging paradigms in anesthetized animals. We document a strikingly greater auditory response with sparse imaging, both quantitatively and qualitatively, which includes a more expansive and robust tonotopic organization. There were instances where continuous imaging could better reveal organizational properties that sparse imaging missed, such as aspects of the hierarchical organization of auditory cortex. We consider the choice of imaging paradigm as a key component in optimizing the fMRI of the monkey auditory cortex.

  15. Women's clitoris, vagina, and cervix mapped on the sensory cortex: fMRI evidence.

    Science.gov (United States)

    Komisaruk, Barry R; Wise, Nan; Frangos, Eleni; Liu, Wen-Ching; Allen, Kachina; Brody, Stuart

    2011-10-01

    The projection of vagina, uterine cervix, and nipple to the sensory cortex in humans has not been reported. The aim of this study was to map the sensory cortical fields of the clitoris, vagina, cervix, and nipple, toward an elucidation of the neural systems underlying sexual response. Using functional magnetic resonance imaging (fMRI), we mapped sensory cortical responses to clitoral, vaginal, cervical, and nipple self-stimulation. For points of reference on the homunculus, we also mapped responses to the thumb and great toe (hallux) stimulation. The main outcome measures used for this study were the fMRI of brain regions activated by the various sensory stimuli. Clitoral, vaginal, and cervical self-stimulation activated differentiable sensory cortical regions, all clustered in the medial cortex (medial paracentral lobule). Nipple self-stimulation activated the genital sensory cortex (as well as the thoracic) region of the homuncular map. The genital sensory cortex, identified in the classical Penfield homunculus based on electrical stimulation of the brain only in men, was confirmed for the first time in the literature by the present study in women applying clitoral, vaginal, and cervical self-stimulation, and observing their regional brain responses using fMRI. Vaginal, clitoral, and cervical regions of activation were differentiable, consistent with innervation by different afferent nerves and different behavioral correlates. Activation of the genital sensory cortex by nipple self-stimulation was unexpected, but suggests a neurological basis for women's reports of its erotogenic quality. © 2011 International Society for Sexual Medicine.

  16. 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.

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

    Science.gov (United States)

    Monti, Martin M

    2011-01-01

    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.

  18. Preoperative therapeutic neuroscience education for lumbar radiculopathy: a single-case fMRI report.

    Science.gov (United States)

    Louw, Adriaan; Puentedura, Emilio J; Diener, Ina; Peoples, Randal R

    2015-01-01

    Therapeutic neuroscience education (TNE) has been shown to be effective in the treatment of mainly chronic musculoskeletal pain conditions. This case study aims to describe the changes in brain activation on functional magnetic resonance imaging (fMRI) scanning, before and after the application of a newly-designed preoperative TNE program. A 30-year-old female with a current acute episode of low back pain (LBP) and radiculopathy participated in a single preoperative TNE session. She completed pre- and post-education measures including visual analog scale (VAS) for LBP and leg pain; Oswestry Disability Index (ODI); Fear Avoidance Beliefs Questionnaire (FABQ); Pain Catastrophizing Scale (PCS) and a series of Likert-scale questions regarding beliefs and attitudes to lumbar surgery (LS). After a 30-minute TNE session, ODI decreased by 10%, PCS decreased by 10 points and her beliefs and attitudes shifted positively regarding LS. Immediately following TNE straight leg raise increased by 7° and forward flexion by 8 cm. fMRI testing following TNE revealed 3 marked differences compared to pre-education scanning: (1) deactivation of the periaqueductal gray area; (2) deactivation of the cerebellum; and (3) increased activation of the motor cortex. The immediate positive fMRI, psychometric and physical movement changes may indicate a cortical mechanism of TNE for patients scheduled for LS.

  19. A Review of fMRI as a Tool for Enhancing Eeg-Based Brain-Machine Interfaces

    Directory of Open Access Journals (Sweden)

    Luis J. Barrios

    2012-01-01

    Full Text Available Human-robot interaction has been going stronger and stronger, up to find a notorious level on brain-machines interfaces. This assistive technology offers a great hope for patients suffering severe neuromuscular disorders. Starting from the current limitations hindering its extensive application outside the research laboratories, this paper reviews findings and prospects on functional magnetic resonance imaging showing how fMRI can help to overcome those limitations, while playing a key role on improving the development of brain-machine interfaces based on electroencephalography. The different types of derived benefits for this interfaces, as well as the different kinds of impact on their components, are presented under a field classification that reveals the distinctive roles that fMRI can play on the present context. The review concludes that fMRI provides complementary knowledge of immediate application, and that a greater profit could be obtained from the own EEG signal by integrating both neuroimaging modalities.

  20. Cerebral correlates of heart rate variations during a spontaneous panic attack in the fMRI scanner.

    Science.gov (United States)

    Spiegelhalder, Kai; Hornyak, Magdolna; Kyle, Simon David; Paul, Dominik; Blechert, Jens; Seifritz, Erich; Hennig, Jürgen; Tebartz van Elst, Ludger; Riemann, Dieter; Feige, Bernd

    2009-12-01

    We report the first published case study of a suddenly occurring panic attack in a patient with no prior history of panic disorder during combined functional magnetic resonance imaging (fMRI, 1.5 Tesla) and electrocardiogram (ECG) recording. The single case was a 46-year-old woman who developed a panic attack near the planned end of the fMRI acquisition session, which therefore had to be aborted. Correlational analysis of heart rate fluctuations and fMRI data revealed a significant negative association in the left middle temporal gyrus. Additionally, regions-of-interest (ROI) analyses indicated significant positive associations in the left amygdala, and trends towards significance in the right amygdala and left insula.

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

    African Journals Online (AJOL)

    Functional MRI in pre-surgical planning: case study and cautionary notes. ... Since its inception almost 20 years ago, functional magnetic resonance imaging ... Although the clinical applications of fMRI are still limited, there have recently been ...

  2. 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.

  3. Structural and functional changes in subcortical vascular mild cognitive impairment: a combined voxel-based morphometry and resting-state fMRI study.

    Directory of Open Access Journals (Sweden)

    Liye Yi

    Full Text Available The present study aimed to investigate changes in structural gray matter (GM volume and functional amplitude of spontaneous low-frequency oscillations (LFO and functional connectivity density in patients with subcortical vascular mild cognitive impairment (svMCI. Structural MRI and resting-sate functional MRI data were collected from 26 svMCI patients and 28 age- and gender-matched healthy controls. Structurally, widespread GM atrophy was found in the svMCI patients that resided primarily in frontal (e.g., the superior and middle frontal gyri and medial prefrontal cortex and temporal (the superior and inferior temporal gyri brain regions as well as several subcortical brain sites (e.g., the thalamus and the caudate. Functionally, svMCI-related changes were predominantly found in the default mode network (DMN. Compared with the healthy controls, the svMCI patients exhibited decreased LFO amplitudes in the anterior part of the DMN (e.g., the medial prefrontal cortex, whereas increased LFO amplitudes in the posterior part of the DMN (e.g., the posterior cingulate/precuneus. As for functional connectivity density, the DMN regions (e.g., the posterior cingulate/precuneus, the medial prefrontal cortex and the middle temporal gyrus consistently exhibited decreased functional connectivity. Finally, the overall patterns of functional alterations in LFO amplitudes and functional connectivity density remained little changed after controlling for structural GM volume losses, which suggests that functional abnormalities can be only partly explained by morphological GM volume changes. Together, our results indicate that svMCI patients exhibit widespread abnormalities in both structural GM volume and functional intrinsic brain activity, which have important implications in understanding the pathophysiological mechanism of svMCI.

  4. Functional asymmetry and effective connectivity of the auditory system during speech perception is modulated by the place of articulation of the consonant- A 7T fMRI study

    Directory of Open Access Journals (Sweden)

    Karsten eSpecht

    2014-06-01

    Full Text Available To differentiate between stop-consonants, the auditory system has to detect subtle place of articulation (PoA and voice onset time (VOT differences between stop-consonants. How this differential processing is represented on the cortical level remains unclear. The present functional magnetic resonance (fMRI study takes advantage of the superior spatial resolution and high sensitivity of ultra high field 7T MRI. Subjects were attentively listening to consonant-vowel syllables with an alveolar or bilabial stop-consonant and either a short or long voice-onset time. The results showed an overall bilateral activation pattern in the posterior temporal lobe during the processing of the consonant-vowel syllables. This was however modulated strongest by place of articulation such that syllables with an alveolar stop-consonant showed stronger left lateralized activation. In addition, analysis of underlying functional and effective connectivity revealed an inhibitory effect of the left planum temporale onto the right auditory cortex during the processing of alveolar consonant-vowel syllables. Further, the connectivity result indicated also a directed information flow from the right to the left auditory cortex, and further to the left planum temporale for all syllables. These results indicate that auditory speech perception relies on an interplay between the left and right auditory cortex, with the left planum temporale as modulator. Furthermore, the degree of functional asymmetry is determined by the acoustic properties of the consonant-vowel syllables.

  5. A unified framework for group independent component analysis for multi-subject fMRI data.

    Science.gov (United States)

    Guo, Ying; Pagnoni, Giuseppe

    2008-09-01

    Independent component analysis (ICA) is becoming increasingly popular for analyzing functional magnetic resonance imaging (fMRI) data. While ICA has been successfully applied to single-subject analysis, the extension of ICA to group inferences is not straightforward and remains an active topic of research. Current group ICA models, such as the GIFT [Calhoun, V.D., Adali, T., Pearlson, G.D., Pekar, J.J., 2001. A method for making group inferences from functional MRI data using independent component analysis. Hum. Brain Mapp. 14, 140-151.] and tensor PICA [Beckmann, C.F., Smith, S.M., 2005. Tensorial extensions of independent component analysis for multisubject FMRI analysis. Neuroimage 25, 294-311.], make different assumptions about the underlying structure of the group spatio-temporal processes and are thus estimated using algorithms tailored for the assumed structure, potentially leading to diverging results. To our knowledge, there are currently no methods for assessing the validity of different model structures in real fMRI data and selecting the most appropriate one among various choices. In this paper, we propose a unified framework for estimating and comparing group ICA models with varying spatio-temporal structures. We consider a class of group ICA models that can accommodate different group structures and include existing models, such as the GIFT and tensor PICA, as special cases. We propose a maximum likelihood (ML) approach with a modified Expectation-Maximization (EM) algorithm for the estimation of the proposed class of models. Likelihood ratio tests (LRT) are presented to compare between different group ICA models. The LRT can be used to perform model comparison and selection, to assess the goodness-of-fit of a model in a particular data set, and to test group differences in the fMRI signal time courses between subject subgroups. Simulation studies are conducted to evaluate the performance of the proposed method under varying structures of group spatio

  6. 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

    2017-03-31

    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 T2* weighted fMRI dataset, obtained with 2D gradient echo (GE) EPI, to a predominantly T2 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 T2* 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 T2* 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

  7. A least angle regression method for fMRI activation detection in phase-encoded experimental designs.

    Science.gov (United States)

    Li, Xingfeng; Coyle, Damien; Maguire, Liam; McGinnity, Thomas M; Watson, David R; Benali, Habib

    2010-10-01

    This paper presents a new regression method for functional magnetic resonance imaging (fMRI) activation detection. Unlike general linear models (GLM), this method is based on selecting models for activation detection adaptively which overcomes the limitation of requiring a predefined design matrix in GLM. This limitation is because GLM designs assume that the response of the neuron populations will be the same for the same stimuli, which is often not the case. In this work, the fMRI hemodynamic response model is selected from a series of models constructed online by the least angle regression (LARS) method. The slow drift terms in the design matrix for the activation detection are determined adaptively according to the fMRI response in order to achieve the best fit for each fMRI response. The LARS method is then applied along with the Moore-Penrose pseudoinverse (PINV) and fast orthogonal search (FOS) algorithm for implementation of the selected model to include the drift effects in the design matrix. Comparisons with GLM were made using 11 normal subjects to test method superiority. This paper found that GLM with fixed design matrix was inferior compared to the described LARS method for fMRI activation detection in a phased-encoded experimental design. In addition, the proposed method has the advantage of increasing the degrees of freedom in the regression analysis. We conclude that the method described provides a new and novel approach to the detection of fMRI activation which is better than GLM based analyses.

  8. 口腔内冷水刺激反应的功能性磁共振成像研究%Functional activity mapping during intraoral stimuli with cold water: with fMRI

    Institute of Scientific and Technical Information of China (English)

    杨秀文; 刘洪臣; 李科; 金真

    2011-01-01

    目的:探讨口腔冷水刺激时的大脑皮层区定位.方法:选取13名健康志愿者,4℃冷水刺激,并以室温水组作为空白对照.利用水传递装置自上下唇进入口腔黏膜水刺激,并采用水刺激信号减静息信号的组块设计方法,采集冷水刺激时全脑血氧水平依赖对比的fMRI扫描数据,并用SPM99软件包进行结果的数据分析.结果:激活双侧眶额皮层(orbitalfrontal cortex,OFC)(BA11)、BA44、口腔躯体感觉运动皮层、顶叶、前运动皮层PMC(BA6).右侧舌回、扣带回、颞叶和左侧枕叶的楔叶激活.结论:1.口腔冷水刺激可以激活大脑皮层的相关区;2.冷水刺激激活与口腔内水愉快行为评估有关的OFC.%Objective: To evaluate the feasibility of fMRI on the location of brain regions related to stimulation with cold water, and compare the different brain regions under between intra-oral 4°C cold and 23° C water stimulation. Methods: Thirteen healthy volunteers were selected to perform the fMRI study. 4° C (group C-g-L) deionized water stimuli was delivered to the subject's mouth through polythene tubes that were held between the left of lips. Group W-g-L served as control. Block designed fMRI scan covering the whole brain was carried out. The fused cross-sectional map between the two groups C-g-L AV-g-L were compared. Results: Under cold stimulation, the following brain locations were bilateral activated: orbitalfrontal cortex (OFC) (BAH), BA44, pre/post-central gyrus oral sensory/motor, parietal lobule, PMC (BA6) , and the following locations were unilateral activated: right ACC (BA24), lingual gyrus, temporal lobe, midbrain red nucleus and occipital lobe. Compared groups C-g-L/W-g-L, overlapping brain areas included pre/post-central gyrus oral sensory/motor, ACC, insula/operculum. Conclusions: l.The volume of activation was remained significantly when cold water was contrasted with warm water. This indicates that specific functional regions of the

  9. ICA-fNORM: Spatial Normalization of fMRI Data Using Intrinsic Group-ICA Networks.

    Science.gov (United States)

    Khullar, Siddharth; Michael, Andrew M; Cahill, Nathan D; Kiehl, Kent A; Pearlson, Godfrey; Baum, Stefi A; Calhoun, Vince D

    2011-01-01

    A common pre-processing challenge associated with group level fMRI analysis is spatial registration of multiple subjects to a standard space. Spatial normalization, using a reference image such as the Montreal Neurological Institute brain template, is the most common technique currently in use to achieve spatial congruence across multiple subjects. This method corrects for global shape differences preserving regional asymmetries, but does not account for functional differences. We propose a novel approach to co-register task-based fMRI data using resting state group-ICA networks. We posit that these intrinsic networks (INs) can provide to the spatial normalization process with important information about how each individual's brain is organized functionally. The algorithm is initiated by the extraction of single subject representations of INs using group level independent component analysis (ICA) on resting state fMRI data. In this proof-of-concept work two of the robust, commonly identified, networks are chosen as functional templates. As an estimation step, the relevant INs are utilized to derive a set of normalization parameters for each subject. Finally, the normalization parameters are applied individually to a different set of fMRI data acquired while the subjects performed an auditory oddball task. These normalization parameters, although derived using rest data, generalize successfully to data obtained with a cognitive paradigm for each subject. The improvement in results is verified using two widely applied fMRI analysis methods: the general linear model and ICA. Resulting activation patterns from each analysis method show significant improvements in terms of detection sensitivity and statistical significance at the group level. The results presented in this article provide initial evidence to show that common functional domains from the resting state brain may be used to improve the group statistics of task-fMRI data.

  10. High-Resolution fMRI of Auditory Cortical Map Changes in Unilateral Hearing Loss and Tinnitus

    NARCIS (Netherlands)

    Ghazaleh, Naghmeh; Van der Zwaag, W.; Clarke, Stephanie; Ville, Dimitri Van De; Maire, Raphael; Saenz, Melissa

    2017-01-01

    Animal models of hearing loss and tinnitus observe pathological neural activity in the tonotopic frequency maps of the primary auditory cortex. Here, we applied ultra high-field fMRI at 7 T to test whether human patients with unilateral hearing loss and tinnitus also show altered functional activity

  11. Transient brain activity disentangles fMRI resting-state dynamics in terms of spatially and temporally overlapping networks.

    Science.gov (United States)

    Karahanoğlu, Fikret Işik; Van De Ville, Dimitri

    2015-07-16

    Dynamics of resting-state functional magnetic resonance imaging (fMRI) provide a new window onto the organizational principles of brain function. Using state-of-the-art signal processing techniques, we extract innovation-driven co-activation patterns (iCAPs) from resting-state fMRI. The iCAPs' maps are spatially overlapping and their sustained-activity signals temporally overlapping. Decomposing resting-state fMRI using iCAPs reveals the rich spatiotemporal structure of functional components that dynamically assemble known resting-state networks. The temporal overlap between iCAPs is substantial; typically, three to four iCAPs occur simultaneously in combinations that are consistent with their behaviour profiles. In contrast to conventional connectivity analysis, which suggests a negative correlation between fluctuations in the default-mode network (DMN) and task-positive networks, we instead find evidence for two DMN-related iCAPs consisting the posterior cingulate cortex that differentially interact with the attention network. These findings demonstrate how the fMRI resting state can be functionally decomposed into spatially and temporally overlapping building blocks using iCAPs.

  12. 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…

  13. The fMRI Study of Cognitive Function in Patients with First Attack Depression%首次发作抑郁症患者认知功能的fMRI研究

    Institute of Scientific and Technical Information of China (English)

    袁辉; 祁吉

    2011-01-01

    目的 利用功能磁共振成像(fMRI)和汉字Stroop任务,探讨抑郁症患者认知功能障碍的神经机制.资料与方法 12例抑郁症患者及12名正常自愿者,采用组块设计的汉字Stroop任务(包括字色一致和字色不一致的颜色命名任务)行fMRI.检查完毕后,行行为学测试,记录总反应时间及错误数.结果 字色不一致的颜色命名任务中,与正常对照组相比,抑郁组的反应时间延长(P<0.01),错误数增多(P<0.01).字色一致的颜色命名任务时,抑郁组出现扣带回的激活.字色不一致的颜色命名任务时,抑郁组左侧前额叶功能脑区激活增加(P<0.05),顶叶多个功能脑区激活减低(P<0.05).两种任务中,抑郁组左侧前额叶功能脑区激活大于右侧(P<0.05).结论 扣带回-前额叶皮层-顶叶网络异常以及双侧前额叶功能失衡共同构成了抑郁症患者认知障碍的神经基础.%Objective To explore the neural mechanism of cognitive function impairment in patients with depression using fMRI and Stroop task. Materials and Methods Twelve depressive patients and 12 healthy volunteers pedormed Block-design fMRI with Chinese character Stroop task, which were included two kinds of task: congruous color-naming (CCN) task and incongruous color-naming( ICN )task. Images were analysed using AFNI and all the activating voxels in each task were recorded respectively. After fMRI examinations,behavior tests of Stroop interference were pedormed for all subjects. Overall reaction time and error numbers were recorded respectively. Results In the 1CN task, depressive patients need more reaction time( P < 0.01 ) ,and made more errors than health controls( P < 0.O1 ). In CCN task, depressive patients showed activation in cingulated gyrus. In ICN task, depressive patients showed activation increase in left frontal lobe( P <0.05 ),while activation decrease in some parietal lobe( P < O. 05 ). Depressive patients showed larger activated voxels in left

  14. Learning and generalization under ambiguity: an fMRI study.

    Directory of Open Access Journals (Sweden)

    J R Chumbley

    2012-01-01

    Full Text Available Adaptive behavior often exploits generalizations from past experience by applying them judiciously in new situations. This requires a means of quantifying the relative importance of prior experience and current information, so they can be balanced optimally. In this study, we ask whether the brain generalizes in an optimal way. Specifically, we used Bayesian learning theory and fMRI to test whether neuronal responses reflect context-sensitive changes in ambiguity or uncertainty about experience-dependent beliefs. We found that the hippocampus expresses clear ambiguity-dependent responses that are associated with an augmented rate of learning. These findings suggest candidate neuronal systems that may be involved in aberrations of generalization, such as over-confidence.

  15. Hand classification of fMRI ICA noise components.

    Science.gov (United States)

    Griffanti, Ludovica; Douaud, Gwenaëlle; Bijsterbosch, Janine; Evangelisti, Stefania; Alfaro-Almagro, Fidel; Glasser, Matthew F; Duff, Eugene P; Fitzgibbon, Sean; Westphal, Robert; Carone, Davide; Beckmann, Christian F; Smith, Stephen M

    2016-12-16

    We present a practical "how-to" guide to help determine whether single-subject fMRI independent components (ICs) characterise structured noise or not. Manual identification of signal and noise after ICA decomposition is required for efficient data denoising: to train supervised algorithms, to check the results of unsupervised ones or to manually clean the data. In this paper we describe the main spatial and temporal features of ICs and provide general guidelines on how to evaluate these. Examples of signal and noise components are provided from a wide range of datasets (3T data, including examples from the UK Biobank and the Human Connectome Project, and 7T data), together with practical guidelines for their identification. Finally, we discuss how the data quality, data type and preprocessing can influence the characteristics of the ICs and present examples of particularly challenging datasets.

  16. Integral calculus problem solving: an fMRI investigation.

    Science.gov (United States)

    Krueger, Frank; Spampinato, Maria Vittoria; Pardini, Matteo; Pajevic, Sinisa; Wood, Jacqueline N; Weiss, George H; Landgraf, Steffen; Grafman, Jordan

    2008-07-16

    Only a subset of adults acquires specific advanced mathematical skills, such as integral calculus. The representation of more sophisticated mathematical concepts probably evolved from basic number systems; however its neuroanatomical basis is still unknown. Using fMRI, we investigated the neural basis of integral calculus while healthy participants were engaged in an integration verification task. Solving integrals activated a left-lateralized cortical network including the horizontal intraparietal sulcus, posterior superior parietal lobe, posterior cingulate gyrus, and dorsolateral prefrontal cortex. Our results indicate that solving of more abstract and sophisticated mathematical facts, such as calculus integrals, elicits a pattern of brain activation similar to the cortical network engaged in basic numeric comparison, quantity manipulation, and arithmetic problem solving.

  17. EEG-correlated fMRI of P3b component in P300 waves

    Institute of Scientific and Technical Information of China (English)

    LI Yuezhi; WANG Liqun; WANG Mingshi

    2005-01-01

    Electroencephalography-correlated functional magnetic resonance imaging (EEG/fMRI) can be used to identify blood oxygen level-dependent (BOLD) signal changes associated with both physiological and pathological EEG events. Here, we implemented continuous and simultaneous EEG/fMRI to identify BOLD signal changes related to P3b component of P300, and 64 channels of EEG were recorded in 11 subjects during Landot Ring task inside a 1.5 T functional magnet resonance (MR) scanner using an MR-compatible EEG recording system. Functional scanning by echoplanar imaging covered almost the entire cerebrum every 2 s, leaving gaps of 2 s without scanning. Off-line MRI artifact subtraction software was applied to obtain continuous EEG data. Additionally, a P300 wave matched filter was constructed to inspect P300 wave occurrence following every target stimulus, target stimuli inspected to induce P300 were detected and their MRI scan number were then used as input for an event-related fMRI analysis. Finally MRI statistical parametric maps were constructed and corrected for multiple comparisons. By random effect group analysis, activations were detected in the right superior parietal lobule and bilaterally in inferior parietal lobule(p<0.001, uncorrected). The results demonstrated the upper regions were sources of P3b component and involved in target detection in memory comparison task.

  18. Evaluation of statistical inference on empirical resting state fMRI.

    Science.gov (United States)

    Yang, Xue; Kang, Hakmook; Newton, Allen T; Landman, Bennett A

    2014-04-01

    Modern statistical inference techniques may be able to improve the sensitivity and specificity of resting state functional magnetic resonance imaging (rs-fMRI) connectivity analysis through more realistic assumptions. In simulation, the advantages of such methods are readily demonstrable. However, quantitative empirical validation remains elusive in vivo as the true connectivity patterns are unknown and noise distributions are challenging to characterize, especially in ultra-high field (e.g., 7T fMRI). Though the physiological characteristics of the fMRI signal are difficult to replicate in controlled phantom studies, it is critical that the performance of statistical techniques be evaluated. The SIMulation EXtrapolation (SIMEX) method has enabled estimation of bias with asymptotically consistent estimators on empirical finite sample data by adding simulated noise . To avoid the requirement of accurate estimation of noise structure, the proposed quantitative evaluation approach leverages the theoretical core of SIMEX to study the properties of inference methods in the face of diminishing data (in contrast to increasing noise). The performance of ordinary and robust inference methods in simulation and empirical rs-fMRI are compared using the proposed quantitative evaluation approach. This study provides a simple, but powerful method for comparing a proxy for inference accuracy using empirical data.

  19. Music reduces pain and increases resting state fMRI BOLD signal amplitude in the left angular gyrus in fibromyalgia patients

    OpenAIRE

    Garza-Villarreal, Eduardo A.; Zhiguo eJiang; Peter eVuust; Sarael eAlcauter; Lene eVase; Erick ePasaye; Roberto eCavazos-Rodriguez; Elvira eBrattico; Troels Staehelin Jensen; Fernando Alejandro Barrios

    2015-01-01

    Music reduces pain in fibromyalgia (FM), a chronic pain disease, but the functional neural correlates of music-induced analgesia are still largely unknown. We recruited FM patients (n = 22) who listened to their preferred relaxing music and an auditory control (pink noise) for 5 minutes without external noise from fMRI image acquisition. Resting state fMRI was then acquired before and after the music and control conditions. A significant increase in the amplitude of low frequency fluctuations...

  20. High spatial resolution increases the specificity of block-design BOLD fMRI studies of overt vowel production.

    Science.gov (United States)

    Soltysik, David A; Hyde, James S

    2008-06-01

    Functional MRI (fMRI) studies of tasks involving orofacial motion, such as speech, are prone to problems related to motion-induced magnetic field variations. Orofacial motion perturbs the static magnetic field, leading to signal changes that correlate with the task and corrupt activation maps with false positives or signal loss. These motion-induced signal changes represent a contraindication for the implementation of fMRI to study the neurophysiology of orofacial motion. An fMRI experiment of a structured, non-semantic vowel production task was performed using four different voxel volumes and three different slice orientations in an attempt to find a set of acquisition parameters leading to activation maps with maximum specificity. Results indicate that the use of small voxel volumes (2 x 2 x 3 mm(3)) yielded a significantly higher percentage of true positive activation compared to the use of larger voxel volumes. Slice orientation did not have as great an impact as spatial resolution, although coronal slices appeared superior at high spatial resolutions. Furthermore, it was found that combining the strategy of high spatial resolution with an optimum task duration and post-processing methods for separating true and false positives greatly improved the specificity of single-subject, block-design fMRI studies of structured, overt vowel production.

  1. 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.

  2. Mapping Human Brain Function with MRI at 7 Tesla

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    @@ In the past decade, the most significant development in MRI is the introduction of fMRI, which permits the mapping of human brain function with exquisite details noninvasively. Functional mapping can be achieved by measuring changes in the blood oxygenation level (I.e. The BOLD contrast) or cerebral blood flow.

  3. When Learning and Remembering Compete: A Functional MRI Study

    NARCIS (Netherlands)

    Huijbers, W.; Pennartz, C.M.A.; Cabeza, R.; Daselaar, S.M.

    2009-01-01

    Recent functional neuroimaging evidence suggests a bottleneck between learning new information and remembering old information. In two behavioral experiments and one functional MRI (fMRI) experiment, we tested the hypothesis that learning and remembering compete when both processes happen within a b

  4. 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

    The blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) signal response to neural stimulation is influenced by many factors that are unrelated to the stimulus. These factors are physiological, such as the resting venous cerebral blood volume (CBV(v)) and vessel...... 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...

  5. 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.

  6. 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 predominantly 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.

  7. Prediction of individual brain maturity using fMRI.

    Science.gov (United States)

    Dosenbach, Nico U F; Nardos, Binyam; Cohen, Alexander L; Fair, Damien A; Power, Jonathan D; Church, Jessica A; Nelson, Steven M; Wig, Gagan S; Vogel, Alecia C; Lessov-Schlaggar, Christina N; Barnes, Kelly Anne; Dubis, Joseph W; Feczko, Eric; Coalson, Rebecca S; Pruett, John R; Barch, Deanna M; Petersen, Steven E; Schlaggar, Bradley L

    2010-09-10

    Group functional connectivity magnetic resonance imaging (fcMRI) studies have documented reliable changes in human functional brain maturity over development. Here we show that support vector machine-based multivariate pattern analysis extracts sufficient information from fcMRI data to make accurate predictions about individuals' brain maturity across development. The use of only 5 minutes of resting-state fcMRI data from 238 scans of typically developing volunteers (ages 7 to 30 years) allowed prediction of individual brain maturity as a functional connectivity maturation index. The resultant functional maturation curve accounted for 55% of the sample variance and followed a nonlinear asymptotic growth curve shape. The greatest relative contribution to predicting individual brain maturity was made by the weakening of short-range functional connections between the adult brain's major functional networks.

  8. An analysis approach for high-field fMRI data from awake non-human primates.

    Directory of Open Access Journals (Sweden)

    Steffen Stoewer

    Full Text Available fMRI experiments with awake non-human primates (NHP have seen a surge of applications in recent years. However, the standard fMRI analysis tools designed for human experiments are not optimal for analysis of NHP fMRI data collected at high fields. There are several reasons for this, including the trial-based nature of NHP experiments, with inter-trial periods being of no interest, and segmentation artefacts and distortions that may result from field changes due to movement. We demonstrate an approach that allows us to address some of these issues consisting of the following steps: 1 Trial-based experimental design. 2 Careful control of subject movement. 3 Computer-assisted selection of trials devoid of artefacts and animal motion. 4 Nonrigid between-trial and rigid within-trial realignment of concatenated data from temporally separated trials and sessions. 5 Linear interpolation of inter-trial intervals and high-pass filtering of temporally continuous data 6 Removal of interpolated data and reconcatenation of datasets before statistical analysis with SPM. We have implemented a software toolbox, fMRI Sandbox (http://code.google.com/p/fmri-sandbox/, for semi-automated application of these processing steps that interfaces with SPM software. Here, we demonstrate that our methodology provides significant improvements for the analysis of awake monkey fMRI data acquired at high-field. The method may also be useful for clinical applications with subjects that are unwilling or unable to remain motionless for the whole duration of a functional scan.

  9. Resting-state fMRI studies in epilepsy

    Institute of Scientific and Technical Information of China (English)

    Wurina; Yu-Feng Zang; Shi-Gang Zhao

    2012-01-01

    Epilepsy is a disease characterized by abnormal spontaneous activity in the brain.Resting-state functional magnetic resonance imaging (RS-fMRI) is a powerful technique for exploring this activity.With good spatial and temporal resolution,RS-fMRI is a promising approach for accurate localization of the focus of seizure activity.Although simultaneous electroencephalogram-fMR1 has been performed with patients in the resting state,most studies focused on activation.This mini-review focuses on RS-fMRI alone,including its computational methods and its application to epilepsy.

  10. 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.

  11. Pitfalls in fractal time series analysis: fMRI BOLD as an exemplary case

    Directory of Open Access Journals (Sweden)

    Andras eEke

    2012-11-01

    Full Text Available This article will be positioned on our previous work demonstrating the importance of adhering to a carefully selected set of criteria when choosing the suitable method from those available ensuring its adequate performance when applied to real temporal signals, such as fMRI BOLD, to evaluate one important facet of their behavior, fractality.Earlier, we have reviewed on a range of monofractal tools and evaluated their performance. Given the advance in the fractal field, in this article we will discuss the most widely used implementations of multifractal analyses, too.Our recommended flowchart for the fractal characterization of spontaneous, low frequency fluctuations in fMRI BOLD will be used as the framework for this article to make certain that it will provide a hands-on experience for the reader in handling the perplexed issues of fractal analysis. The reason why this particular signal modality and its fractal analysis has been chosen was due to its high impact on today's neuroscience given it had powerfully emerged as a new way of interpreting the complex functioning of the brain (see intrinsic activity.The reader will first be presented with the basic concepts of mono and multifractal time series analyses, followed by some of the most relevant implementations, characterization by numerical approaches. The notion of the dichotomy of fractional Gaussian noise (fGn and fractional Brownian motion (fBm signal classes and their impact on fractal time series analyses will be thoroughly discussed as the central theme of our application strategy. Sources of pitfalls and way how to avoid them will be identified followed by a demonstration on fractal studies of fMRI BOLD taken from the literature and that of our own in an attempt to consolidate the best practice in fractal analysis of empirical fMRI-BOLD signals mapped throughout the brain as an exemplary case of potentially wide interest.

  12. 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.

  13. MB-SWIFT functional MRI during deep brain stimulation in rats.

    Science.gov (United States)

    Lehto, Lauri J; Idiyatullin, Djaudat; Zhang, Jinjin; Utecht, Lynn; Adriany, Gregor; Garwood, Michael; Gröhn, Olli; Michaeli, Shalom; Mangia, Silvia

    2017-08-07

    Recently introduced 3D radial MRI pulse sequence entitled Multi-Band SWeep Imaging with Fourier Transformation (MB-SWIFT) having virtually zero acquisition delay was used to obtain functional MRI (fMRI) contrast in rat's brain at 9.4 T during deep brain stimulation (DBS). The results demonstrate that MB-SWIFT allows functional images free of susceptibility artifacts, and provides an excellent fMRI activation contrast in the brain. Flip angle dependence of the MB-SWIFT fMRI signal and elimination of the fMRI contrast while using saturation bands, indicate a blood flow origin of the observed fMRI contrast. MB-SWIFT fMRI modality permits activation studies in the close proximity to an implanted lead, which is not possible to achieve with conventionally used gradient echo and spin echo - echo planar imaging fMRI techniques. We conclude that MB-SWIFT fMRI is a powerful imaging modality for investigations of functional responses during DBS. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  14. The "mirror-neuron system" in MS: A 3 tesla fMRI study.

    Science.gov (United States)

    Rocca, M A; Tortorella, P; Ceccarelli, A; Falini, A; Tango, D; Scotti, G; Comi, G; Filippi, M

    2008-01-22

    The mirror neuron system (MNS) is an observation-execution matching system activated, in humans, during action observation, motor learning, and imitation of action. We used functional MRI (fMRI) to investigate the properties of the MNS in patients with multiple sclerosis (MS). Using a 3 tesla scanner, we acquired fMRI in 16 right-handed patients with relapsing-remitting MS and 14 controls. Two motor tasks were studied. The first consisted of repetitive flexion-extension of the last four fingers of the right hand (simple task) alternated to epochs of rest; the second (MNS task) consisted of observation of a movie showing the hand of another subject while performing the same task. During the simple task, compared to controls, patients with MS had more significant activations of the contralateral primary sensorimotor cortex and supplementary motor area. During the MNS task, both groups showed the activation of several visual areas, the infraparietal sulcus, and the inferior frontal gyrus (IFG), bilaterally. The IFG and the visual areas were significantly more active in patients than controls. The between-group interaction analysis showed that in patients with MS, part of the regions of the MNS were more active also during the simple task. This study suggests increased activation of the mirror neuron system in patients with multiple sclerosis (MS) with a normal level of function and widespread CNS damage. The potentialities of this system in facilitating clinical recovery in patients with MS and other neurologic conditions should be investigated.

  15. 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......MRI data sets with different sampling frequency, we show that the GPICA-inferred temporal components and associated spatial maps allow for a more definite interpretation than standard temporal ICA methods. The temporal structures of the sources are controlled by the covariance of the Gaussian process......, specified by a kernel function with an interpretable and controllable temporal length scale parameter. We propose a hierarchical model specification, considering both instantaneous and convolutive mixing, and we infer source spatial maps, temporal patterns and temporal length scale parameters by Markov...

  16. Working memory dysfunction in delusional disorders: an fMRI investigation.

    Science.gov (United States)

    Oflaz, Serap; Akyuz, Fatma; Hamamci, Andac; Firat, Zeynep; Keskinkılıç, Cahit; Kilickesmez, Ozgur; Cihangiroglu, Mutlu

    2014-09-01

    Delusional disorder (DD) is a rare and understudied psychiatric disorder. There is limited number of studies concerning cognitive characteristics in DD. Using an established working memory paradigm with variable levels of memory load, we investigated alterations in functional magnetic resonance imaging (fMRI) of brain regions in patients with DD. This case control study included 9 patients with DD and 9 healthy control subjects matched for age, sex, and education level. Diagnosis of DD was confirmed using the Structured Clinical Interview for DSM-IV Axis I. The severity of the symptoms was evaluated using the Positive and Negative Syndrome Scale. All patients were asked to perform 0-back and 2-back tasks during fMRI experiments. Functional imaging was performed using the 3.0 T Philips whole-body scanner using an 8-channel head coil. Participants with DD had less neural activation of the left dorsolateral prefrontal cortex in fMRI scans obtained during performance tasks. On the other hand, neural activation of the left and right superior temporal gyrus, left middle and inferior temporal gyrus, right and left posterior cingulate gyrus, right amygdala, left and right fusiform gyrus was more prominent in patients with DD in comparison with the control group. Patients with DD had dysfunction in the prefrontal, temporal and limbic regions of the brain in particular, during performance tasks of working memory. Our findings were in line with the findings of the early reports on deficient functioning in temporal or limbic regions of the brain. Further, patients with DD displayed prefrontal dysfunction as seen in patients with schizophrenia. Copyright © 2014 Elsevier Ltd. All rights reserved.

  17. 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.)

  18. How skill expertise shapes the brain functional architecture: an fMRI study of visuo-spatial and motor processing in professional racing-car and naïve drivers.

    Science.gov (United States)

    Bernardi, Giulio; Ricciardi, Emiliano; Sani, Lorenzo; Gaglianese, Anna; Papasogli, Alessandra; Ceccarelli, Riccardo; Franzoni, Ferdinando; Galetta, Fabio; Santoro, Gino; Goebel, Rainer; Pietrini, Pietro

    2013-01-01

    The present study was designed to investigate the brain functional architecture that subserves visuo-spatial and motor processing in highly skilled individuals. By using functional magnetic resonance imaging (fMRI), we measured brain activity while eleven Formula racing-car drivers and eleven 'naïve' volunteers performed a motor reaction and a visuo-spatial task. Tasks were set at a relatively low level of difficulty such to ensure a similar performance in the two groups and thus avoid any potential confounding effects on brain activity due to discrepancies in task execution. The brain functional organization was analyzed in terms of regional brain response, inter-regional interactions and blood oxygen level dependent (BOLD) signal variability. While performance levels were equal in the two groups, as compared to naïve drivers, professional drivers showed a smaller volume recruitment of task-related regions, stronger connections among task-related areas, and an increased information integration as reflected by a higher signal temporal variability. In conclusion, our results demonstrate that, as compared to naïve subjects, the brain functional architecture sustaining visuo-motor processing in professional racing-car drivers, trained to perform at the highest levels under extremely demanding conditions, undergoes both 'quantitative' and 'qualitative' modifications that are evident even when the brain is engaged in relatively simple, non-demanding tasks. These results provide novel evidence in favor of an increased 'neural efficiency' in the brain of highly skilled individuals.

  19. ICA if fMRI based on a convolutive mixture model

    DEFF Research Database (Denmark)

    Hansen, Lars Kai

    2003-01-01

    processing strategies. Global linear dependencies can be probed by independent component analysis (ICA) based on higher order statistics or spatio-temporal properties. With ICA we separate the different sources of the fMRI signal. ICA can be performed assuming either spatial or temporal independency. A major....... The mixing is represented by “mixture coefficient images” quantifying the local response to a given source at a certain time lag. This is the first communication to address this important issue in the context of fMRI ICA. Data: A single slice holding 128x128 pixels and passing through primary visual cortex......Modeling & Analysis Abstract The fMRI signal has many sources: Stimulus induced activation, other brain activations, confounds including several physiological signal components, the most prominent being the cardiac pulsation at about 1 Hz, and breathing induced motion (0.2-1 Hz). Most fMRI data...

  20. Functional connectivity-based signatures of schizophrenia revealed by multiclass pattern analysis of resting-state fMRI from schizophrenic patients and their healthy siblings

    Directory of Open Access Journals (Sweden)

    Yu Yang

    2013-02-01

    Full Text Available Abstract Background Recently, a growing number of neuroimaging studies have begun to investigate the brains of schizophrenic patients and their healthy siblings to identify heritable biomarkers of this complex disorder. The objective of this study was to use multiclass pattern analysis to investigate the inheritable characters of schizophrenia at the individual level, by comparing whole-brain resting-state functional connectivity of patients with schizophrenia to their healthy siblings. Methods Twenty-four schizophrenic patients, twenty-five healthy siblings and twenty-two matched healthy controls underwent the resting-state functional Magnetic Resonance Imaging (rs-fMRI scanning. A linear support vector machine along with principal component analysis was used to solve the multi-classification problem. By reconstructing the functional connectivities with high discriminative power, three types of functional connectivity-based signatures were identified: (i state connectivity patterns, which characterize the nature of disruption in the brain network of patients with schizophrenia; (ii trait connectivity patterns, reflecting shared connectivities of dysfunction in patients with schizophrenia and their healthy siblings, thereby providing a possible neuroendophenotype and revealing the genetic vulnerability to develop schizophrenia; and (iii compensatory connectivity patterns, which underlie special brain connectivities by which healthy siblings might compensate for an increased genetic risk for developing schizophrenia. Results Our multiclass pattern analysis achieved 62.0% accuracy via leave-one-out cross-validation (p  Conclusions Based on our experimental results, we saw some indication of differences in functional connectivity patterns in the healthy siblings of schizophrenic patients compared to other healthy individuals who have no relations with the patients. Our preliminary investigation suggested that the use of resting-state functional

  1. Processing of intentional and automatic number magnitudes in children born prematurely: evidence from fMRI.

    Science.gov (United States)

    Klein, Elise; Moeller, Korbinian; Kiechl-Kohlendorfer, Ursula; Kremser, Christian; Starke, Marc; Cohen Kadosh, Roi; Pupp-Peglow, Ulrike; Schocke, Michael; Kaufmann, Liane

    2014-01-01

    This study examined the neural correlates of intentional and automatic number processing (indexed by number comparison and physical Stroop task, respectively) in 6- and 7-year-old children born prematurely. Behavioral results revealed significant numerical distance and size congruity effects. Imaging results disclosed (1) largely overlapping fronto-parietal activation for intentional and automatic number processing, (2) a frontal to parietal shift of activation upon considering the risk factors gestational age and birth weight, and (3) a task-specific link between math proficiency and functional magnetic resonance imaging (fMRI) signal within distinct regions of the parietal lobes-indicating commonalities but also specificities of intentional and automatic number processing.

  2. fMRI assessment of somatotopy in human Brodmann area 3b by electrical finger stimulation.

    Science.gov (United States)

    Kurth, R; Villringer, K; Mackert, B M; Schwiemann, J; Braun, J; Curio, G; Villringer, A; Wolf, K J

    1998-01-26

    Functional magnetic resonance imaging (fMRI) is capable of detecting focal brain activation induced by electrical stimulation of single fingers in human subjects. In eight subjects somatotopic arrangement of the second and fifth finger was found in Brodmann area 3b of the primary somatosensory cortex. In four subjects the representation area of the second finger was located lateral and inferior to the fifth finger; in one subject the somatotopy was reversed. In three subjects representation areas of the two fingers in Brodmann area 3b were found overlapping. Additional activated areas were found on the crown of ipsilateral and contralateral postcentral gyrus (Brodmann areas 1 and 2) and posterior parietal cortex.

  3. Effect of "SOHAM" meditation on the human brain: an fMRI study.

    Science.gov (United States)

    Guleria, Anupam; Kumar, Uttam; Kishan, Sadguru Sri Kunal; Khetrapal, Chunni Lal

    2013-12-30

    The effect of "SOHAM" meditation has been investigated using functional magnetic resonance imaging (fMRI) in long-term meditators while they were meditating and not meditating. The results have revealed activation in left middle prefrontal cortex (MPFC) (Brodmann's area, BA 46), left inferior frontal gyrus (LIFG) (BA 44), left supplementary motor area (SMA) (BA 6) and left precuneus (BA 5) during the meditation period compared to the control period (no-meditation period). The results have been interpreted in terms of regulation of the emotional state, attention and working memory of the meditators.

  4. High resolution fMRI of subcortical regions during visual erotic stimulation at 7 T.

    Science.gov (United States)

    Walter, Martin; Stadler, Joerg; Tempelmann, Claus; Speck, Oliver; Northoff, Georg

    2008-03-01

    Involvement of distinct subcortical structures during sexual arousal was shown in animals and functional imaging studies gave coarse evidence for a similar organisation in humans. In contrast to previous imaging studies at lower field strengths, we tried to investigate activation in distinguishable subcortical structures at high spatial resolution during a short stimulating paradigm to further account for potential effects of attenuation or adaptation. Seven healthy subjects were investigated using functional magnetic resonance imaging (fMRI) on a 7 T scanner. High resolution EPI images of 1.4 x 1.4 mm2 inplane resolution were acquired in a single functional session of 13.6 minutes. During the session erotic and non-erotic pictures were presented in an event-related design. In the unsmoothed data with preserved high spatial resolution significant effects were detected in relevant structures, including anterior caudate and mediodorsal thalamus. These effects were restricted to subcortical target structures and their anatomical boundaries. This study demonstrates that fMRI at high fields provides an ideal tool to investigate functional anatomy of subcortical structures. Due to an increased signal-to-noise ratio, functional scans of short duration can be acquired at high resolution without the need for further spatial smoothing.

  5. 精神分裂症患者基底节功能连接的静息态 fMRI 研究%Resting - state functional magnetic resonance imaging study of functional connectivity of basal ganglia in schizophrenia

    Institute of Scientific and Technical Information of China (English)

    蒋宇超; 陈琳; 段明君; 陈曦; 杨宓; 邓佳燕; 赖永秀; 尧德中; 罗程

    2015-01-01

    Objective To explore the difference of functional connectivity of basal ganglia in schizophrenia during a resting state by functional magnetic resoncance imaging(fMRI). Methods 3. 0T fMRI was used to assess the whole brain activity of 15 schizophrenia patients and 12 health controls. Functional connectivity analysis based on basal ganglia was performed to obtain the significant differ-ence between two groups. Results Compared with the health controls,the patients showed significantly increased functional connectiv-ity between media superior frontal gyrus,posterior cingulate and caudate;increased functional connectivity between left superior frontal gyrus,right anterior cingulate and left pallidum;increased functional connectivity between left medial frontal gyrus and right pallidum;increased functional connectivity between left superior frontal gyrus and left putamen. Conclusion This study discovers increased func-tional connectivity between basal ganglia and crucial regions of Default Model Network(DMN). The results imply that basal ganglia -DMN loop altered aberrantly,which might be associated with the pathological mechanisms of schizophrenia.%目的:通过功能磁共振(fMRI)技术,探讨精神分裂症患者静息状态下与基底节异常连接的脑区。方法采用3.0T 功能磁共振成像技术检测15例精神分裂症患者与12例正常对照组在静息状态下的全脑功能活动。采用功能连接分析对比两组被试的基底节(双侧尾状核、壳核和苍白球共6个区域)与全脑功能连接的差异。结果与对照组相比,精神分裂症患者的内侧额上回、后扣带与尾状核的功能连接上升;左侧额上回、右侧前扣带与左侧苍白球功能连接上升;左内侧额上回与右侧苍白球功能连接上升;左侧额上回与左侧壳核功能连接上升。差异均有统计学意义。结论精神分裂症患者的基底节区域与默认网络的重要节点功能连接上升,提

  6. 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 vari