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

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Feng-Mei Lu

Full Text Available Conduct disorder (CD is characterized by a persistent pattern of antisocial behavior and aggression in childhood and adolescence. Previous task-based and resting-state functional magnetic resonance imaging (fMRI studies have revealed widespread brain regional abnormalities in adolescents with CD. However, whether the resting-state networks (RSNs are altered in adolescents with CD remains unknown. In this study, resting-state fMRI data were first acquired from eighteen male adolescents with pure CD and eighteen age- and gender-matched typically developing (TD individuals. Independent component analysis (ICA was implemented to extract nine representative RSNs, and the generated RSNs were then compared to show the differences between the CD and TD groups. Interestingly, it was observed from the brain mapping results that compared with the TD group, the CD group manifested decreased functional connectivity in four representative RSNs: the anterior default mode network (left middle frontal gyrus, which is considered to be correlated with impaired social cognition, the somatosensory network (bilateral supplementary motor area and right postcentral gyrus, the lateral visual network (left superior occipital gyrus, and the medial visual network (right fusiform, left lingual gyrus and right calcarine, which are expected to be relevant to the perceptual systems responsible for perceptual dysfunction in male adolescents with CD. Importantly, the novel findings suggested that male adolescents with pure CD were identified to have dysfunctions in both low-level perceptual networks (the somatosensory network and visual network and a high-order cognitive network (the default mode network. Revealing the changes in the functional connectivity of these RSNs enhances our understanding of the neural mechanisms underlying the modulation of emotion and social cognition and the regulation of perception in adolescents with CD.

Combining fMRI and behavioral measures to examine the process of human learning.

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Karuza, Elisabeth A; Emberson, Lauren L; Aslin, Richard N

2014-03-01

Prior to the advent of fMRI, the primary means of examining the mechanisms underlying learning were restricted to studying human behavior and non-human neural systems. However, recent advances in neuroimaging technology have enabled the concurrent study of human behavior and neural activity. We propose that the integration of behavioral response with brain activity provides a powerful method of investigating the process through which internal representations are formed or changed. Nevertheless, a review of the literature reveals that many fMRI studies of learning either (1) focus on outcome rather than process or (2) are built on the untested assumption that learning unfolds uniformly over time. We discuss here various challenges faced by the field and highlight studies that have begun to address them. In doing so, we aim to encourage more research that examines the process of learning by considering the interrelation of behavioral measures and fMRI recording during learning. Copyright © 2013 Elsevier Inc. All rights reserved.

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

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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

Bilateral frontal activation associated with cutaneous stimulation of elixir field: an FMRI study.

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Chan, Agnes S; Cheung, Mei-Chun; Chan, Yu Leung; Yeung, David K W; Lam, Wan

2006-01-01

Elixir Field, or Dan Tian, is the area where energy is stored and nourished in the body according to traditional Chinese medicine (TCM). Although Dan Tian stimulation is a major concept in Qigong healing and has been practiced for thousands of years, and while there are some recent empirical evidence of its effect, its neurophysiological basis remains unknown. We used functional magnetic resonance imaging (fMRI) to study brain activations associated with external stimulation of the lower Elixir Field in ten normal subjects, and compared the results with the stimulation of their right hands. While right-hand stimulation resulted in left postcentral gyrus activation, stimulation of the lower Elixir Field resulted in bilateral activations including the medial and superior frontal gyrus, middle and superior temporal gyrus, thalamus, insula, and cingulate gyrus. These findings suggest that stimulation of the Elixir Field is not only associated with activation of the sensory motor cortex but also with cortical regions that mediate planning, attention, and memory.

Feature-space-based FMRI analysis using the optimal linear transformation.

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Sun, Fengrong; Morris, Drew; Lee, Wayne; Taylor, Margot J; Mills, Travis; Babyn, Paul S

2010-09-01

The optimal linear transformation (OLT), an image analysis technique of feature space, was first presented in the field of MRI. This paper proposes a method of extending OLT from MRI to functional MRI (fMRI) to improve the activation-detection performance over conventional approaches of fMRI analysis. In this method, first, ideal hemodynamic response time series for different stimuli were generated by convolving the theoretical hemodynamic response model with the stimulus timing. Second, constructing hypothetical signature vectors for different activity patterns of interest by virtue of the ideal hemodynamic responses, OLT was used to extract features of fMRI data. The resultant feature space had particular geometric clustering properties. It was then classified into different groups, each pertaining to an activity pattern of interest; the applied signature vector for each group was obtained by averaging. Third, using the applied signature vectors, OLT was applied again to generate fMRI composite images with high SNRs for the desired activity patterns. Simulations and a blocked fMRI experiment were employed for the method to be verified and compared with the general linear model (GLM)-based analysis. The simulation studies and the experimental results indicated the superiority of the proposed method over the GLM-based analysis in detecting brain activities.

Resting State fMRI in the moving fetus: a robust framework for motion, bias field and spin history correction.

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Ferrazzi, Giulio; Kuklisova Murgasova, Maria; Arichi, Tomoki; Malamateniou, Christina; Fox, Matthew J; Makropoulos, Antonios; Allsop, Joanna; Rutherford, Mary; Malik, Shaihan; Aljabar, Paul; Hajnal, Joseph V

2014-11-01

There is growing interest in exploring fetal functional brain development, particularly with Resting State fMRI. However, during a typical fMRI acquisition, the womb moves due to maternal respiration and the fetus may perform large-scale and unpredictable movements. Conventional fMRI processing pipelines, which assume that brain movements are infrequent or at least small, are not suitable. Previous published studies have tackled this problem by adopting conventional methods and discarding as much as 40% or more of the acquired data. In this work, we developed and tested a processing framework for fetal Resting State fMRI, capable of correcting gross motion. The method comprises bias field and spin history corrections in the scanner frame of reference, combined with slice to volume registration and scattered data interpolation to place all data into a consistent anatomical space. The aim is to recover an ordered set of samples suitable for further analysis using standard tools such as Group Independent Component Analysis (Group ICA). We have tested the approach using simulations and in vivo data acquired at 1.5 T. After full motion correction, Group ICA performed on a population of 8 fetuses extracted 20 networks, 6 of which were identified as matching those previously observed in preterm babies. Copyright © 2014 Elsevier Inc. All rights reserved.

fMRI. Basics and clinical applications. 2. ed.

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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.

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

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

2018-07-01

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

Decoding Overlapping Memories in the Medial Temporal Lobes Using High-Resolution fMRI

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Chadwick, Martin J.; Hassabis, Demis; Maguire, Eleanor A.

2011-01-01

The hippocampus is proposed to process overlapping episodes as discrete memory traces, although direct evidence for this in human episodic memory is scarce. Using green-screen technology we created four highly overlapping movies of everyday events. Participants were scanned using high-resolution fMRI while recalling the movies. Multivariate…

Optogenetic activation of CA1 pyramidal neurons at the dorsal and ventral hippocampus evokes distinct brain-wide responses revealed by mouse fMRI.

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Norio Takata

Full Text Available The dorsal and ventral hippocampal regions (dHP and vHP are proposed to have distinct functions. Electrophysiological studies have revealed intra-hippocampal variances along the dorsoventral axis. Nevertheless, the extra-hippocampal influences of dHP and vHP activities remain unclear. In this study, we compared the spatial distribution of brain-wide responses upon dHP or vHP activation and further estimate connection strengths between the dHP and the vHP with corresponding extra-hippocampal areas. To achieve this, we first investigated responses of local field potential (LFP and multi unit activities (MUA upon light stimulation in the hippocampus of an anesthetized transgenic mouse, whose CA1 pyramidal neurons expressed a step-function opsin variant of channelrhodopsin-2 (ChR2. Optogenetic stimulation increased hippocampal LFP power at theta, gamma, and ultra-fast frequency bands, and augmented MUA, indicating light-induced activation of CA1 pyramidal neurons. Brain-wide responses examined using fMRI revealed that optogenetic activation at the dHP or vHP caused blood oxygenation level-dependent (BOLD fMRI signals in situ. Although activation at the dHP induced BOLD responses at the vHP, the opposite was not observed. Outside the hippocampal formation, activation at the dHP, but not the vHP, evoked BOLD responses at the retrosplenial cortex (RSP, which is in line with anatomical evidence. In contrast, BOLD responses at the lateral septum (LS were induced only upon vHP activation, even though both dHP and vHP send axonal fibers to the LS. Our findings suggest that the primary targets of dHP and vHP activation are distinct, which concurs with attributed functions of the dHP and RSP in spatial memory, as well as of the vHP and LS in emotional responses.

Applying independent component analysis to clinical fMRI at 7 T

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Simon Daniel Robinson

2013-09-01

Full Text Available Increased BOLD sensitivity at 7 T offers the possibility to increase the reliability of fMRI, but ultra-high field is also associated with an increase in artifacts related to head motion, Nyquist ghosting and parallel imaging reconstruction errors. In this study, the ability of Independent Component Analysis (ICA to separate activation from these artifacts was assessed in a 7 T study of neurological patients performing chin and hand motor tasks. ICA was able to isolate primary motor activation with negligible contamination by motion effects. The results of General Linear Model (GLM analysis of these data were, in contrast, heavily contaminated by motion. Secondary motor areas, basal ganglia and thalamus involvement were apparent in ICA results, but there was low capability to isolate activation in the same brain regions in the GLM analysis, indicating that ICA was more sensitive as well as more specific. A method was developed to simplify the assessment of the large number of independent components. Task-related activation components could be automatically identified via intuitive and effective features. These findings demonstrate that ICA is a practical and sensitive analysis approach in high field fMRI studies, particularly where motion is evoked. Promising applications of ICA in clinical fMRI include presurgical planning and the study of pathologies affecting subcortical brain areas.

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

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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)

Short- and long-term reliability of language fMRI.

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

2018-08-01

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

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

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

2018-06-13

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

Concurrent tACS-fMRI Reveals Causal Influence of Power Synchronized Neural Activity on Resting State fMRI Connectivity.

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Bächinger, Marc; Zerbi, Valerio; Moisa, Marius; Polania, Rafael; Liu, Quanying; Mantini, Dante; Ruff, Christian; Wenderoth, Nicole

2017-05-03

Resting state fMRI (rs-fMRI) is commonly used to study the brain's intrinsic neural coupling, which reveals specific spatiotemporal patterns in the form of resting state networks (RSNs). It has been hypothesized that slow rs-fMRI oscillations (5 Hz); however, causal evidence for this relationship is currently lacking. Here we measured rs-fMRI in humans while applying transcranial alternating current stimulation (tACS) to entrain brain rhythms in left and right sensorimotor cortices. The two driving tACS signals were tailored to the individual's α rhythm (8-12 Hz) and fluctuated in amplitude according to a 1 Hz power envelope. We entrained the left versus right hemisphere in accordance to two different coupling modes where either α oscillations were synchronized between hemispheres (phase-synchronized tACS) or the slower oscillating power envelopes (power-synchronized tACS). Power-synchronized tACS significantly increased rs-fMRI connectivity within the stimulated RSN compared with phase-synchronized or no tACS. This effect outlasted the stimulation period and tended to be more effective in individuals who exhibited a naturally weak interhemispheric coupling. Using this novel approach, our data provide causal evidence that synchronized power fluctuations contribute to the formation of fMRI-based RSNs. Moreover, our findings demonstrate that the brain's intrinsic coupling at rest can be selectively modulated by choosing appropriate tACS signals, which could lead to new interventions for patients with altered rs-fMRI connectivity. SIGNIFICANCE STATEMENT Resting state fMRI (rs-fMRI) has become an important tool to estimate brain connectivity. However, relatively little is known about how slow hemodynamic oscillations measured with fMRI relate to electrophysiological processes. It was suggested that slowly fluctuating power envelopes of electrophysiological signals synchronize across brain areas and that the topography of this activity is spatially correlated to

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

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

2017-06-15

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

Task-Related Edge Density (TED)-A New Method for Revealing Dynamic Network Formation in fMRI Data of the Human Brain.

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Lohmann, Gabriele; Stelzer, Johannes; Zuber, Verena; Buschmann, Tilo; Margulies, Daniel; Bartels, Andreas; Scheffler, Klaus

2016-01-01

The formation of transient networks in response to external stimuli or as a reflection of internal cognitive processes is a hallmark of human brain function. However, its identification in fMRI data of the human brain is notoriously difficult. Here we propose a new method of fMRI data analysis that tackles this problem by considering large-scale, task-related synchronisation networks. Networks consist of nodes and edges connecting them, where nodes correspond to voxels in fMRI data, and the weight of an edge is determined via task-related changes in dynamic synchronisation between their respective times series. Based on these definitions, we developed a new data analysis algorithm that identifies edges that show differing levels of synchrony between two distinct task conditions and that occur in dense packs with similar characteristics. Hence, we call this approach "Task-related Edge Density" (TED). TED proved to be a very strong marker for dynamic network formation that easily lends itself to statistical analysis using large scale statistical inference. A major advantage of TED compared to other methods is that it does not depend on any specific hemodynamic response model, and it also does not require a presegmentation of the data for dimensionality reduction as it can handle large networks consisting of tens of thousands of voxels. We applied TED to fMRI data of a fingertapping and an emotion processing task provided by the Human Connectome Project. TED revealed network-based involvement of a large number of brain areas that evaded detection using traditional GLM-based analysis. We show that our proposed method provides an entirely new window into the immense complexity of human brain function.

Task-Related Edge Density (TED-A New Method for Revealing Dynamic Network Formation in fMRI Data of the Human Brain.

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Gabriele Lohmann

Full Text Available The formation of transient networks in response to external stimuli or as a reflection of internal cognitive processes is a hallmark of human brain function. However, its identification in fMRI data of the human brain is notoriously difficult. Here we propose a new method of fMRI data analysis that tackles this problem by considering large-scale, task-related synchronisation networks. Networks consist of nodes and edges connecting them, where nodes correspond to voxels in fMRI data, and the weight of an edge is determined via task-related changes in dynamic synchronisation between their respective times series. Based on these definitions, we developed a new data analysis algorithm that identifies edges that show differing levels of synchrony between two distinct task conditions and that occur in dense packs with similar characteristics. Hence, we call this approach "Task-related Edge Density" (TED. TED proved to be a very strong marker for dynamic network formation that easily lends itself to statistical analysis using large scale statistical inference. A major advantage of TED compared to other methods is that it does not depend on any specific hemodynamic response model, and it also does not require a presegmentation of the data for dimensionality reduction as it can handle large networks consisting of tens of thousands of voxels. We applied TED to fMRI data of a fingertapping and an emotion processing task provided by the Human Connectome Project. TED revealed network-based involvement of a large number of brain areas that evaded detection using traditional GLM-based analysis. We show that our proposed method provides an entirely new window into the immense complexity of human brain function.

High spatial correspondence at a columnar level between activation and resting state fMRI signals and local field potentials.

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Shi, Zhaoyue; Wu, Ruiqi; Yang, Pai-Feng; Wang, Feng; Wu, Tung-Lin; Mishra, Arabinda; Chen, Li Min; Gore, John C

2017-05-16

Although blood oxygenation level-dependent (BOLD) fMRI has been widely used to map brain responses to external stimuli and to delineate functional circuits at rest, the extent to which BOLD signals correlate spatially with underlying neuronal activity, the spatial relationships between stimulus-evoked BOLD activations and local correlations of BOLD signals in a resting state, and whether these spatial relationships vary across functionally distinct cortical areas are not known. To address these critical questions, we directly compared the spatial extents of stimulated activations and the local profiles of intervoxel resting state correlations for both high-resolution BOLD at 9.4 T and local field potentials (LFPs), using 98-channel microelectrode arrays, in functionally distinct primary somatosensory areas 3b and 1 in nonhuman primates. Anatomic images of LFP and BOLD were coregistered within 0.10 mm accuracy. We found that the point spread functions (PSFs) of BOLD and LFP responses were comparable in the stimulus condition, and both estimates of activations were slightly more spatially constrained than local correlations at rest. The magnitudes of stimulus responses in area 3b were stronger than those in area 1 and extended in a medial to lateral direction. In addition, the reproducibility and stability of stimulus-evoked activation locations within and across both modalities were robust. Our work suggests that the intrinsic resolution of BOLD is not a limiting feature in practice and approaches the intrinsic precision achievable by multielectrode electrophysiology.

Selective attention modulates neural substrates of repetition priming and "implicit" visual memory: suppressions and enhancements revealed by FMRI.

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Vuilleumier, Patrik; Schwartz, Sophie; Duhoux, Stéphanie; Dolan, Raymond J; Driver, Jon

2005-08-01

Attention can enhance processing for relevant information and suppress this for ignored stimuli. However, some residual processing may still arise without attention. Here we presented overlapping outline objects at study, with subjects attending to those in one color but not the other. Attended objects were subsequently recognized on a surprise memory test, whereas there was complete amnesia for ignored items on such direct explicit testing; yet reliable behavioral priming effects were found on indirect testing. Event-related fMRI examined neural responses to previously attended or ignored objects, now shown alone in the same or mirror-reversed orientation as before, intermixed with new items. Repetition-related decreases in fMRI responses for objects previously attended and repeated in the same orientation were found in the right posterior fusiform, lateral occipital, and left inferior frontal cortex. More anterior fusiform regions also showed some repetition decreases for ignored objects, irrespective of orientation. View-specific repetition decreases were found in the striate cortex, particularly for previously attended items. In addition, previously ignored objects produced some fMRI response increases in the bilateral lingual gyri, relative to new objects. Selective attention at exposure can thus produce several distinct long-term effects on processing of stimuli repeated later, with neural response suppression stronger for previously attended objects, and some response enhancement for previously ignored objects, with these effects arising in different brain areas. Although repetition decreases may relate to positive priming phenomena, the repetition increases for ignored objects shown here for the first time might relate to processes that can produce "negative priming" in some behavioral studies. These results reveal quantitative and qualitative differences between neural substrates of long-term repetition effects for attended versus unattended objects.

Human fMRI Reveals That Delayed Action Re-Recruits Visual Perception

OpenAIRE

Singhal, Anthony; Monaco, Simona; Kaufman, Liam D.; Culham, Jody C.

2013-01-01

Behavioral and neuropsychological research suggests that delayed actions rely on different neural substrates than immediate actions; however, the specific brain areas implicated in the two types of actions remain unknown. We used functional magnetic resonance imaging (fMRI) to measure human brain activation during delayed grasping and reaching. Specifically, we examined activation during visual stimulation and action execution separated by a 18-s delay interval in which subjects had to rememb...

Task-Related Edge Density (TED)—A New Method for Revealing Dynamic Network Formation in fMRI Data of the Human Brain

Science.gov (United States)

Lohmann, Gabriele; Stelzer, Johannes; Zuber, Verena; Buschmann, Tilo; Margulies, Daniel; Bartels, Andreas; Scheffler, Klaus

2016-01-01

The formation of transient networks in response to external stimuli or as a reflection of internal cognitive processes is a hallmark of human brain function. However, its identification in fMRI data of the human brain is notoriously difficult. Here we propose a new method of fMRI data analysis that tackles this problem by considering large-scale, task-related synchronisation networks. Networks consist of nodes and edges connecting them, where nodes correspond to voxels in fMRI data, and the weight of an edge is determined via task-related changes in dynamic synchronisation between their respective times series. Based on these definitions, we developed a new data analysis algorithm that identifies edges that show differing levels of synchrony between two distinct task conditions and that occur in dense packs with similar characteristics. Hence, we call this approach “Task-related Edge Density” (TED). TED proved to be a very strong marker for dynamic network formation that easily lends itself to statistical analysis using large scale statistical inference. A major advantage of TED compared to other methods is that it does not depend on any specific hemodynamic response model, and it also does not require a presegmentation of the data for dimensionality reduction as it can handle large networks consisting of tens of thousands of voxels. We applied TED to fMRI data of a fingertapping and an emotion processing task provided by the Human Connectome Project. TED revealed network-based involvement of a large number of brain areas that evaded detection using traditional GLM-based analysis. We show that our proposed method provides an entirely new window into the immense complexity of human brain function. PMID:27341204

Motor function deficits in schizophrenia: an fMRI and VBM study

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

2014-05-15

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

Motor function deficits in schizophrenia: an fMRI and VBM study

International Nuclear Information System (INIS)

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

2014-01-01

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

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

Science.gov (United States)

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

2018-04-01

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

Pre-surgical integration of FMRI and DTI of the sensorimotor system in transcortical resection of a high-grade insular astrocytoma

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Chelsea eEkstrand

2016-03-01

Full Text Available Herein we report on a patient with a WHO Grade III astrocytoma in the right insular region in close proximity to the internal capsule who underwent a right frontotemporal craniotomy. Total gross resection of insular gliomas remains surgically challenging based on the possibility of damage to the corticospinal tracts. However, maximizing the extent of resection has been shown to decrease future adverse outcomes. Thus, the goal of such surgeries should focus on maximizing extent of resection while minimizing possible adverse outcomes. In this case, pre-surgical planning included integration of functional magnetic resonance imaging (fMRI and diffusion tensor imaging (DTI, to localize motor and sensory pathways. Novel fMRI tasks were individually developed for the patient to maximize both somatosensory and motor activation simultaneously in areas in close proximity to the tumor. Information obtained was used to optimize resection trajectory and extent, facilitating gross total resection of the astrocytoma. Across all three motor-sensory tasks administered, fMRI revealed an area of interest just superior and lateral to the astrocytoma. Further, DTI analyses showed displacement of the corona radiata around the superior dorsal surface of the astrocytoma, extending in the direction of the activation found using fMRI. Taking into account these results, a transcortical superior temporal gyrus surgical approach was chosen in order to avoid the area of interest identified by fMRI and DTI. Total gross resection was achieved and minor post-surgical motor and sensory deficits were temporary. This case highlights the utility of comprehensive pre-surgical planning, including fMRI and DTI, to maximize surgical outcomes on a case-by-case basis.

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

NARCIS (Netherlands)

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

2018-01-01

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

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

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Klaudius eKalcher

2015-12-01

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

Multivariate linear regression of high-dimensional fMRI data with multiple target variables.

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Valente, Giancarlo; Castellanos, Agustin Lage; Vanacore, Gianluca; Formisano, Elia

2014-05-01

Multivariate regression is increasingly used to study the relation between fMRI spatial activation patterns and experimental stimuli or behavioral ratings. With linear models, informative brain locations are identified by mapping the model coefficients. This is a central aspect in neuroimaging, as it provides the sought-after link between the activity of neuronal populations and subject's perception, cognition or behavior. Here, we show that mapping of informative brain locations using multivariate linear regression (MLR) may lead to incorrect conclusions and interpretations. MLR algorithms for high dimensional data are designed to deal with targets (stimuli or behavioral ratings, in fMRI) separately, and the predictive map of a model integrates information deriving from both neural activity patterns and experimental design. Not accounting explicitly for the presence of other targets whose associated activity spatially overlaps with the one of interest may lead to predictive maps of troublesome interpretation. We propose a new model that can correctly identify the spatial patterns associated with a target while achieving good generalization. For each target, the training is based on an augmented dataset, which includes all remaining targets. The estimation on such datasets produces both maps and interaction coefficients, which are then used to generalize. The proposed formulation is independent of the regression algorithm employed. We validate this model on simulated fMRI data and on a publicly available dataset. Results indicate that our method achieves high spatial sensitivity and good generalization and that it helps disentangle specific neural effects from interaction with predictive maps associated with other targets. Copyright © 2013 Wiley Periodicals, Inc.

Specific default mode subnetworks support mentalizing as revealed through opposing network recruitment by social and semantic FMRI tasks.

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Hyatt, Christopher J; Calhoun, Vince D; Pearlson, Godfrey D; Assaf, Michal

2015-08-01

The ability to attribute mental states to others, or "mentalizing," is posited to involve specific subnetworks within the overall default mode network (DMN), but this question needs clarification. To determine which default mode (DM) subnetworks are engaged by mentalizing processes, we assessed task-related recruitment of DM subnetworks. Spatial independent component analysis (sICA) applied to fMRI data using relatively high-order model (75 components). Healthy participants (n = 53, ages 17-60) performed two fMRI tasks: an interactive game involving mentalizing (Domino), a semantic memory task (SORT), and a resting state fMRI scan. sICA of the two tasks split the DMN into 10 subnetworks located in three core regions: medial prefrontal cortex (mPFC; five subnetworks), posterior cingulate/precuneus (PCC/PrC; three subnetworks), and bilateral temporoparietal junction (TPJ). Mentalizing events increased recruitment in five of 10 DM subnetworks, located in all three core DMN regions. In addition, three of these five DM subnetworks, one dmPFC subnetwork, one PCC/PrC subnetwork, and the right TPJ subnetwork, showed reduced recruitment by semantic memory task events. The opposing modulation by the two tasks suggests that these three DM subnetworks are specifically engaged in mentalizing. Our findings, therefore, suggest the unique involvement of mentalizing processes in only three of 10 DM subnetworks, and support the importance of the dmPFC, PCC/PrC, and right TPJ in mentalizing as described in prior studies. © 2015 Wiley Periodicals, Inc.

Automatic physiological waveform processing for FMRI noise correction and analysis.

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Daniel J Kelley

2008-03-01

Full Text Available Functional MRI resting state and connectivity studies of brain focus on neural fluctuations at low frequencies which share power with physiological fluctuations originating from lung and heart. Due to the lack of automated software to process physiological signals collected at high magnetic fields, a gap exists in the processing pathway between the acquisition of physiological data and its use in fMRI software for both physiological noise correction and functional analyses of brain activation and connectivity. To fill this gap, we developed an open source, physiological signal processing program, called PhysioNoise, in the python language. We tested its automated processing algorithms and dynamic signal visualization on resting monkey cardiac and respiratory waveforms. PhysioNoise consistently identifies physiological fluctuations for fMRI noise correction and also generates covariates for subsequent analyses of brain activation and connectivity.

Somatosensory BOLD fMRI reveals close link between salient blood pressure changes and the murine neuromatrix.

Science.gov (United States)

Reimann, Henning Matthias; Todiras, Mihail; Hodge, Russ; Huelnhagen, Till; Millward, Jason Michael; Turner, Robert; Seeliger, Erdmann; Bader, Michael; Pohlmann, Andreas; Niendorf, Thoralf

2018-05-15

The neuromatrix, or "pain matrix", is a network of cortical brain areas which is activated by noxious as well as salient somatosensory stimulation. This has been studied in mice and humans using blood oxygenation level-dependent (BOLD) fMRI. Here we demonstrate that BOLD effects observed in the murine neuromatrix in response to salient somatosensory stimuli are prone to reflect mean arterial blood pressure (MABP) changes, rather than neural activity. We show that a standard electrostimulus typically used in murine somatosensory fMRI can induce substantial elevations in MABP. Equivalent drug-induced MABP changes - without somatosensory stimulation - evoked BOLD patterns in the neuromatrix strikingly similar to those evoked by electrostimulation. This constitutes a serious caveat for murine fMRI. The regional specificity of these BOLD patterns can be attributed to the co-localization of the neuromatrix with large draining veins. Based on these findings we propose a cardiovascular support mechanism whereby abrupt elevations in MABP provide additional energy supply to the neuromatrix and other essential brain areas in fight-or-flight situations. Copyright © 2018 Elsevier Inc. All rights reserved.

Distinct BOLD fMRI Responses of Capsaicin-Induced Thermal Sensation Reveal Pain-Related Brain Activation in Nonhuman Primates.

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Abu Bakar Ali Asad

Full Text Available Approximately 20% of the adult population suffer from chronic pain that is not adequately treated by current therapies, highlighting a great need for improved treatment options. To develop effective analgesics, experimental human and animal models of pain are critical. Topically/intra-dermally applied capsaicin induces hyperalgesia and allodynia to thermal and tactile stimuli that mimics chronic pain and is a useful translation from preclinical research to clinical investigation. Many behavioral and self-report studies of pain have exploited the use of the capsaicin pain model, but objective biomarker correlates of the capsaicin augmented nociceptive response in nonhuman primates remains to be explored.Here we establish an aversive capsaicin-induced fMRI model using non-noxious heat stimuli in Cynomolgus monkeys (n = 8. BOLD fMRI data were collected during thermal challenge (ON:20 s/42°C; OFF:40 s/35°C, 4-cycle at baseline and 30 min post-capsaicin (0.1 mg, topical, forearm application. Tail withdrawal behavioral studies were also conducted in the same animals using 42°C or 48°C water bath pre- and post- capsaicin application (0.1 mg, subcutaneous, tail.Group comparisons between pre- and post-capsaicin application revealed significant BOLD signal increases in brain regions associated with the 'pain matrix', including somatosensory, frontal, and cingulate cortices, as well as the cerebellum (paired t-test, p<0.02, n = 8, while no significant change was found after the vehicle application. The tail withdrawal behavioral study demonstrated a significant main effect of temperature and a trend towards capsaicin induced reduction of latency at both temperatures.These findings provide insights into the specific brain regions involved with aversive, 'pain-like', responses in a nonhuman primate model. Future studies may employ both behavioral and fMRI measures as translational biomarkers to gain deeper understanding of pain processing and evaluate

Gaze-related mimic word activates the frontal eye field and related network in the human brain: an fMRI study.

Science.gov (United States)

Osaka, Naoyuki; Osaka, Mariko

2009-09-18

This is an fMRI study demonstrating new evidence that a mimic word highly suggestive of an eye gaze, heard by the ear, significantly activates the frontal eye field (FEF), inferior frontal gyrus (IFG), dorsolateral premotor area (PMdr) and superior parietal lobule (SPL) connected with the frontal-parietal network. However, hearing a non-sense words that did not imply gaze under the same task does not activate this area in humans. We concluded that the FEF would be a critical area for generating/processing an active gaze, evoked by an onomatopoeia word that implied gaze closely associated with social skill. We suggest that the implied active gaze may depend on prefrontal-parietal interactions that modify cognitive gaze led by spatial visual attention associated with the SPL.

fMRI in Parkinson’s Disease

DEFF Research Database (Denmark)

Siebner, Hartwig R.; Herz, Damian

2013-01-01

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

An FMRI-compatible Symbol Search task.

Science.gov (United States)

Liebel, Spencer W; Clark, Uraina S; Xu, Xiaomeng; Riskin-Jones, Hannah H; Hawkshead, Brittany E; Schwarz, Nicolette F; Labbe, Donald; Jerskey, Beth A; Sweet, Lawrence H

2015-03-01

Our objective was to determine whether a Symbol Search paradigm developed for functional magnetic resonance imaging (FMRI) is a reliable and valid measure of cognitive processing speed (CPS) in healthy older adults. As all older adults are expected to experience cognitive declines due to aging, and CPS is one of the domains most affected by age, establishing a reliable and valid measure of CPS that can be administered inside an MR scanner may prove invaluable in future clinical and research settings. We evaluated the reliability and construct validity of a newly developed FMRI Symbol Search task by comparing participants' performance in and outside of the scanner and to the widely used and standardized Symbol Search subtest of the Wechsler Adult Intelligence Scale (WAIS). A brief battery of neuropsychological measures was also administered to assess the convergent and discriminant validity of the FMRI Symbol Search task. The FMRI Symbol Search task demonstrated high test-retest reliability when compared to performance on the same task administered out of the scanner (r=.791; pSymbol Search (r=.717; pSymbol Search task were also observed. The FMRI Symbol Search task is a reliable and valid measure of CPS in healthy older adults and exhibits expected sensitivity to the effects of age on CPS performance.

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

Directory of Open Access Journals (Sweden)

Russell A Poldrack

2013-07-01

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

fMRI investigation of response inhibition, emotion, impulsivity, and clinical high-risk behaviour in adolescents

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Matthew R G Brown

2015-09-01

Full Text Available High-risk behaviour in adolescents is associated with injury, mental health problems, and poor outcomes in later life. Improved understanding of the neurobiology of high-risk behaviour and impulsivity shows promise for informing clinical treatment and prevention as well as policy to better address high-risk behaviour. We recruited 21 adolescents (age 14-17 with a wide range of high-risk behaviour tendencies, including medically high-risk participants recruited from psychiatric clinics. Risk tendencies were assessed using the Adolescent Risk Behaviour Screen (ARBS. ARBS risk scores correlated highly (0.78 with impulsivity scores from the Barratt Impulsivity scale (BIS. Participants underwent 4.7 Tesla functional magnetic resonance imaging (fMRI while performing an emotional Go/NoGo task. This task presented an aversive or neutral distractor image simultaneously with each Go or NoGo stimulus. Risk behaviour and impulsivity tendencies exhibited similar but not identical associations with fMRI activation patterns in prefrontal brain regions. We interpret these results as reflecting differences in response inhibition, emotional stimulus processing, and emotion regulation in relation to participant risk behaviour tendencies and impulsivity levels. The results are consistent with high impulsivity playing an important role in determining high risk tendencies in this sample containing clinically high-risk adolescents.

fMRI investigation of response inhibition, emotion, impulsivity, and clinical high-risk behavior in adolescents.

Science.gov (United States)

Brown, Matthew R G; Benoit, James R A; Juhás, Michal; Dametto, Ericson; Tse, Tiffanie T; MacKay, Marnie; Sen, Bhaskar; Carroll, Alan M; Hodlevskyy, Oleksandr; Silverstone, Peter H; Dolcos, Florin; Dursun, Serdar M; Greenshaw, Andrew J

2015-01-01

High-risk behavior in adolescents is associated with injury, mental health problems, and poor outcomes in later life. Improved understanding of the neurobiology of high-risk behavior and impulsivity shows promise for informing clinical treatment and prevention as well as policy to better address high-risk behavior. We recruited 21 adolescents (age 14-17) with a wide range of high-risk behavior tendencies, including medically high-risk participants recruited from psychiatric clinics. Risk tendencies were assessed using the Adolescent Risk Behavior Screen (ARBS). ARBS risk scores correlated highly (0.78) with impulsivity scores from the Barratt Impulsivity scale (BIS). Participants underwent 4.7 Tesla functional magnetic resonance imaging (fMRI) while performing an emotional Go/NoGo task. This task presented an aversive or neutral distractor image simultaneously with each Go or NoGo stimulus. Risk behavior and impulsivity tendencies exhibited similar but not identical associations with fMRI activation patterns in prefrontal brain regions. We interpret these results as reflecting differences in response inhibition, emotional stimulus processing, and emotion regulation in relation to participant risk behavior tendencies and impulsivity levels. The results are consistent with high impulsivity playing an important role in determining high risk tendencies in this sample containing clinically high-risk adolescents.

A high-resolution 7-Tesla fMRI dataset from complex natural stimulation with an audio movie.

Science.gov (United States)

Hanke, Michael; Baumgartner, Florian J; Ibe, Pierre; Kaule, Falko R; Pollmann, Stefan; Speck, Oliver; Zinke, Wolf; Stadler, Jörg

2014-01-01

Here we present a high-resolution functional magnetic resonance (fMRI) dataset - 20 participants recorded at high field strength (7 Tesla) during prolonged stimulation with an auditory feature film ("Forrest Gump"). In addition, a comprehensive set of auxiliary data (T1w, T2w, DTI, susceptibility-weighted image, angiography) as well as measurements to assess technical and physiological noise components have been acquired. An initial analysis confirms that these data can be used to study common and idiosyncratic brain response patterns to complex auditory stimulation. Among the potential uses of this dataset are the study of auditory attention and cognition, language and music perception, and social perception. The auxiliary measurements enable a large variety of additional analysis strategies that relate functional response patterns to structural properties of the brain. Alongside the acquired data, we provide source code and detailed information on all employed procedures - from stimulus creation to data analysis. In order to facilitate replicative and derived works, only free and open-source software was utilized.

The inferior, anterior temporal lobes and semantic memory clarified: novel evidence from distortion-corrected fMRI.

Science.gov (United States)

Visser, M; Embleton, K V; Jefferies, E; Parker, G J; Ralph, M A Lambon

2010-05-01

The neural basis of semantic memory generates considerable debate. Semantic dementia results from bilateral anterior temporal lobe (ATL) atrophy and gives rise to a highly specific impairment of semantic memory, suggesting that this region is a critical neural substrate for semantic processing. Recent rTMS experiments with neurologically-intact participants also indicate that the ATL are a necessary substrate for semantic memory. Exactly which regions within the ATL are important for semantic memory are difficult to detect from these methods (because the damage in SD covers a large part of the ATL). Functional neuroimaging might provide important clues about which specific areas exhibit activation that correlates with normal semantic performance. Neuroimaging studies, however, have not consistently found anterior temporal lobe activation in semantic tasks. A recent meta-analysis indicates that this inconsistency may be due to a collection of technical limitations associated with previous studies, including a reduced field-of-view and magnetic susceptibility artefacts associated with standard gradient echo fMRI. We conducted an fMRI study of semantic memory using a combination of techniques which improve sensitivity to ATL activations whilst preserving whole-brain coverage. As expected from SD patients and ATL rTMS experiments, this method revealed bilateral temporal activation extending from the inferior temporal lobe along the fusiform gyrus to the anterior temporal regions, bilaterally. We suggest that the inferior, anterior temporal lobe region makes a crucial contribution to semantic cognition and utilising this version of fMRI will enable further research on the semantic role of the ATL. 2010 Elsevier Ltd. All rights reserved.

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....

Simulating fiction: individual differences in literature comprehension revealed with FMRI.

Science.gov (United States)

Nijhof, Annabel D; Willems, Roel M

2015-01-01

When we read literary fiction, we are transported to fictional places, and we feel and think along with the characters. Despite the importance of narrative in adult life and during development, the neurocognitive mechanisms underlying fiction comprehension are unclear. We used functional magnetic resonance imaging (fMRI) to investigate how individuals differently employ neural networks important for understanding others' beliefs and intentions (mentalizing), and for sensori-motor simulation while listening to excerpts from literary novels. Localizer tasks were used to localize both the cortical motor network and the mentalizing network in participants after they listened to excerpts from literary novels. Results show that participants who had high activation in anterior medial prefrontal cortex (aMPFC; part of the mentalizing network) when listening to mentalizing content of literary fiction, had lower motor cortex activity when they listened to action-related content of the story, and vice versa. This qualifies how people differ in their engagement with fiction: some people are mostly drawn into a story by mentalizing about the thoughts and beliefs of others, whereas others engage in literature by simulating more concrete events such as actions. This study provides on-line neural evidence for the existence of qualitatively different styles of moving into literary worlds, and adds to a growing body of literature showing the potential to study narrative comprehension with neuroimaging methods.

Analytic programming with FMRI data: a quick-start guide for statisticians using R.

Science.gov (United States)

Eloyan, Ani; Li, Shanshan; Muschelli, John; Pekar, Jim J; Mostofsky, Stewart H; Caffo, Brian S

2014-01-01

Functional magnetic resonance imaging (fMRI) is a thriving field that plays an important role in medical imaging analysis, biological and neuroscience research and practice. This manuscript gives a didactic introduction to the statistical analysis of fMRI data using the R project, along with the relevant R code. The goal is to give statisticians who would like to pursue research in this area a quick tutorial for programming with fMRI data. References of relevant packages and papers are provided for those interested in more advanced analysis.

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

Directory of Open Access Journals (Sweden)

Hendrik eMandelkow

2016-03-01

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

A Specialized Multi-Transmit Head Coil for High Resolution fMRI of the Human Visual Cortex at 7T.

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Sengupta, Shubharthi; Roebroeck, Alard; Kemper, Valentin G; Poser, Benedikt A; Zimmermann, Jan; Goebel, Rainer; Adriany, Gregor

2016-01-01

To design, construct and validate radiofrequency (RF) transmit and receive phased array coils for high-resolution visual cortex imaging at 7 Tesla. A 4 channel transmit and 16 channel receive array was constructed on a conformal polycarbonate former. Transmit field efficiency and homogeneity were simulated and validated, along with the Specific Absorption Rate, using [Formula: see text] mapping techniques and electromagnetic simulations. Receiver signal-to-noise ratio (SNR), temporal SNR (tSNR) across EPI time series, g-factors for accelerated imaging and noise correlations were evaluated and compared with a commercial 32 channel whole head coil. The performance of the coil was further evaluated with human subjects through functional MRI (fMRI) studies at standard and submillimeter resolutions of upto 0.8mm isotropic. The transmit and receive sections were characterized using bench tests and showed good interelement decoupling, preamplifier decoupling and sample loading. SNR for the 16 channel coil was ∼ 1.5 times that of the commercial coil in the human occipital lobe, and showed better g-factor values for accelerated imaging. fMRI tests conducted showed better response to Blood Oxygen Level Dependent (BOLD) activation, at resolutions of 1.2mm and 0.8mm isotropic. The 4 channel phased array transmit coil provides homogeneous excitation across the visual cortex, which, in combination with the dual row 16 channel receive array, makes for a valuable research tool for high resolution anatomical and functional imaging of the visual cortex at 7T.

On application of kernel PCA for generating stimulus features for fMRI during continuous music listening.

Science.gov (United States)

Tsatsishvili, Valeri; Burunat, Iballa; Cong, Fengyu; Toiviainen, Petri; Alluri, Vinoo; Ristaniemi, Tapani

2018-06-01

There has been growing interest towards naturalistic neuroimaging experiments, which deepen our understanding of how human brain processes and integrates incoming streams of multifaceted sensory information, as commonly occurs in real world. Music is a good example of such complex continuous phenomenon. In a few recent fMRI studies examining neural correlates of music in continuous listening settings, multiple perceptual attributes of music stimulus were represented by a set of high-level features, produced as the linear combination of the acoustic descriptors computationally extracted from the stimulus audio. NEW METHOD: fMRI data from naturalistic music listening experiment were employed here. Kernel principal component analysis (KPCA) was applied to acoustic descriptors extracted from the stimulus audio to generate a set of nonlinear stimulus features. Subsequently, perceptual and neural correlates of the generated high-level features were examined. The generated features captured musical percepts that were hidden from the linear PCA features, namely Rhythmic Complexity and Event Synchronicity. Neural correlates of the new features revealed activations associated to processing of complex rhythms, including auditory, motor, and frontal areas. Results were compared with the findings in the previously published study, which analyzed the same fMRI data but applied linear PCA for generating stimulus features. To enable comparison of the results, methodology for finding stimulus-driven functional maps was adopted from the previous study. Exploiting nonlinear relationships among acoustic descriptors can lead to the novel high-level stimulus features, which can in turn reveal new brain structures involved in music processing. Copyright © 2018 Elsevier B.V. All rights reserved.

Neurofunctional MRI at high magnetic fields; Neurofunktionelle MRT bei hohen Feldern

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Speck, O. [Fakultaet fuer Naturwissenschaften, Otto-von-Guericke Universitaet Magdeburg, Abteilung Biomedizinische Magnetresonanz, Institut fuer Experimentelle Physik, Magdeburg (Germany); Leibniz Institut fuer Neurobiologie, Magdeburg (Germany); Deutsches Zentrum fuer Neurodegenerative Erkrankungen (DZNE), Magdeburg (Germany); Center for Behavioral Brain Sciences (CBBS), Magdeburg (Germany); Turner, R. [MPI fuer Kognitions- und Neurowissenschaften, Abteilung Neurophysik, Leipzig (Germany)

2013-05-15

Functional magnetic resonance imaging (fMRI) examinations are limited in their sensitivity due to the low activation-induced signal change. Within short tolerable scan times the spatial resolution is thus limited. fMRI is a reliable tool in neuroscience as well as for clinical applications such as presurgical mapping of brain function. The fMRI sensitivity improves greatly (more than linearly) with increasing magnetic field strengths. For many years this was the main driving force in the push towards higher field strengths, such as 7 T. The sensitivity gain is greatest for high spatial resolution and fMRI with very high sub-millimeter resolution becomes feasible. Current results demonstrate that the localization of the blood oxygenation level dependent (BOLD) signal is better than previously assumed. High-field fMRI not only allows quantitative improvements but also opens the way to new information content, such as columnar and layer-dependent functional structures of the cortex. This may pave the way for further information, e.g. the directionality of cortico-cortical connections; however, these possibilities also pose new challenges. New methods for processing such high resolution data are required which do not require spatial smoothing and preserve the high information content. Common spatial resolutions of 2-3 mm are still very well suited for examinations at 3 T where they benefit from the low signal void, lower geometrical distortion and reduced acoustic noise. To achieve higher resolution at 7 T parallel imaging and geometric distortion correction are essential and permit the best congruence with structural data. The echo time at 7 T should be adjusted to about 20-25 ms. Data processing for single subjects or patients should be performed with little or no smoothing to retain resolution. Group studies could achieve good correlation with local normalization. New methods for information extraction, such as multivariate pattern analysis may allow combination of

Sub-Millimeter T2 Weighted fMRI at 7 T: Comparison of 3D-GRASE and 2D SE-EPI

Directory of Open Access Journals (Sweden)

Valentin G. Kemper

2015-05-01

Full Text Available Functional magnetic resonance imaging (fMRI allows studying human brain function non-invasively up to the spatial resolution of cortical columns and layers. Most fMRI acquisitions rely on the blood oxygenation level dependent (BOLD contrast employing T2* weighted 2D multi-slice echo-planar imaging (EPI. At ultra-high magnetic field (i.e. 7 T and above, it has been shown experimentally and by simulation, that T2 weighted acquisitions yield a signal that is spatially more specific to the site of neuronal activity at the cost of functional sensitivity. This study compared two T2 weighted imaging sequences, inner-volume 3D Gradient-and-Spin-Echo (3D-GRASE and 2D Spin-Echo EPI (SE-EPI, with evaluation of their imaging point-spread function, functional specificity, and functional sensitivity at sub-millimeter resolution. Simulations and measurements of the imaging point-spread function revealed that the strongest anisotropic blurring in 3D-GRASE (along the second phase-encoding direction was about 60 % higher than the strongest anisotropic blurring in 2D SE-EPI (along the phase-encoding direction In a visual paradigm, the BOLD sensitivity of 3D-GRASE was found to be superior due to its higher temporal signal-to-noise ratio. High resolution cortical depth profiles suggested that the contrast mechanisms are similar between the two sequences, however, 2D SE-EPI had a higher surface bias owing to the higher T2* contribution of the longer in-plane EPI echo-train for full field of view compared to the reduced field of view of zoomed 3D-GRASE.

Applying independent component analysis to clinical fMRI at 7 T

OpenAIRE

Simon Daniel Robinson; Veronika eSchöpf; Pedro eCardoso; Alexander eGeissler; Alexander eGeissler; Florian Ph.S Fischmeister; Florian Ph.S Fischmeister; Moritz eWurnig; Moritz eWurnig; Siegfried eTrattnig; Roland eBeisteiner; Roland eBeisteiner

2013-01-01

Increased BOLD sensitivity at 7 T offers the possibility to increase the reliability of fMRI, but ultra-high field is also associated with an increase in artifacts related to head motion, Nyquist ghosting and parallel imaging reconstruction errors. In this study, the ability of Independent Component Analysis (ICA) to separate activation from these artifacts was assessed in a 7 T study of neurological patients performing chin and hand motor tasks. ICA was able to isolate primary motor activati...

Multivoxel Pattern Analysis for fMRI Data: A Review

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Abdelhak Mahmoudi

2012-01-01

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

Multivoxel Pattern Analysis for fMRI Data: A Review

Science.gov (United States)

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

2012-01-01

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

Network modelling methods for FMRI.

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Smith, Stephen M; Miller, Karla L; Salimi-Khorshidi, Gholamreza; Webster, Matthew; Beckmann, Christian F; Nichols, Thomas E; Ramsey, Joseph D; Woolrich, Mark W

2011-01-15

There is great interest in estimating brain "networks" from FMRI data. This is often attempted by identifying a set of functional "nodes" (e.g., spatial ROIs or ICA maps) and then conducting a connectivity analysis between the nodes, based on the FMRI timeseries associated with the nodes. Analysis methods range from very simple measures that consider just two nodes at a time (e.g., correlation between two nodes' timeseries) to sophisticated approaches that consider all nodes simultaneously and estimate one global network model (e.g., Bayes net models). Many different methods are being used in the literature, but almost none has been carefully validated or compared for use on FMRI timeseries data. In this work we generate rich, realistic simulated FMRI data for a wide range of underlying networks, experimental protocols and problematic confounds in the data, in order to compare different connectivity estimation approaches. Our results show that in general correlation-based approaches can be quite successful, methods based on higher-order statistics are less sensitive, and lag-based approaches perform very poorly. More specifically: there are several methods that can give high sensitivity to network connection detection on good quality FMRI data, in particular, partial correlation, regularised inverse covariance estimation and several Bayes net methods; however, accurate estimation of connection directionality is more difficult to achieve, though Patel's τ can be reasonably successful. With respect to the various confounds added to the data, the most striking result was that the use of functionally inaccurate ROIs (when defining the network nodes and extracting their associated timeseries) is extremely damaging to network estimation; hence, results derived from inappropriate ROI definition (such as via structural atlases) should be regarded with great caution. Copyright © 2010 Elsevier Inc. All rights reserved.

fMRI of Simultaneous Interpretation Reveals the Neural Basis of Extreme Language Control.

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Hervais-Adelman, Alexis; Moser-Mercer, Barbara; Michel, Christoph M; Golestani, Narly

2015-12-01

We used functional magnetic resonance imaging (fMRI) to examine the neural basis of extreme multilingual language control in a group of 50 multilingual participants. Comparing brain responses arising during simultaneous interpretation (SI) with those arising during simultaneous repetition revealed activation of regions known to be involved in speech perception and production, alongside a network incorporating the caudate nucleus that is known to be implicated in domain-general cognitive control. The similarity between the networks underlying bilingual language control and general executive control supports the notion that the frequently reported bilingual advantage on executive tasks stems from the day-to-day demands of language control in the multilingual brain. We examined neural correlates of the management of simultaneity by correlating brain activity during interpretation with the duration of simultaneous speaking and hearing. This analysis showed significant modulation of the putamen by the duration of simultaneity. Our findings suggest that, during SI, the caudate nucleus is implicated in the overarching selection and control of the lexico-semantic system, while the putamen is implicated in ongoing control of language output. These findings provide the first clear dissociation of specific dorsal striatum structures in polyglot language control, roles that are consistent with previously described involvement of these regions in nonlinguistic executive control. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Cerebral somatic pain modulation during autogenic training in fMRI.

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Naglatzki, R P; Schlamann, M; Gasser, T; Ladd, M E; Sure, U; Forsting, M; Gizewski, E R

2012-10-01

Functional magnetic resonance imaging (fMRI) studies are increasingly employed in different conscious states. Autogenic training (AT) is a common clinically used relaxation method. The purpose of this study was to investigate the cerebral modulation of pain activity patterns due to AT and to correlate the effects to the degree of experience with AT and strength of stimuli. Thirteen volunteers familiar with AT were studied with fMRI during painful electrical stimulation in a block design alternating between resting state and electrical stimulation, both without AT and while employing the same paradigm when utilizing their AT abilities. The subjective rating of painful stimulation and success in modulation during AT was assessed. During painful electrical stimulation without AT, fMRI revealed activation of midcingulate, right secondary sensory, right supplementary motor, and insular cortices, the right thalamus and left caudate nucleus. In contrast, utilizing AT only activation of left insular and supplementary motor cortices was revealed. The paired t-test revealed pain-related activation in the midcingulate, posterior cingulate and left anterior insular cortices for the condition without AT, and activation in the left ventrolateral prefrontal cortex under AT. Activation of the posterior cingulate cortex and thalamus correlated with the amplitude of electrical stimulation. This study revealed an effect on cerebral pain processing while performing AT. This might represent the cerebral correlate of different painful stimulus processing by subjects who are trained in performing relaxation techniques. However, due to the absence of a control group, further studies are needed to confirm this theory. © 2012 European Federation of International Association for the Study of Pain Chapters.

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

An intra-neural microstimulation system for ultra-high field magnetic resonance imaging and magnetoencephalography.

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Glover, Paul M; Watkins, Roger H; O'Neill, George C; Ackerley, Rochelle; Sanchez-Panchuelo, Rosa; McGlone, Francis; Brookes, Matthew J; Wessberg, Johan; Francis, Susan T

2017-10-01

Intra-neural microstimulation (INMS) is a technique that allows the precise delivery of low-current electrical pulses into human peripheral nerves. Single unit INMS can be used to stimulate individual afferent nerve fibres during microneurography. Combining this with neuroimaging allows the unique monitoring of central nervous system activation in response to unitary, controlled tactile input, with functional magnetic resonance imaging (fMRI) providing exquisite spatial localisation of brain activity and magnetoencephalography (MEG) high temporal resolution. INMS systems suitable for use within electrophysiology laboratories have been available for many years. We describe an INMS system specifically designed to provide compatibility with both ultra-high field (7T) fMRI and MEG. Numerous technical and safety issues are addressed. The system is fully analogue, allowing for arbitrary frequency and amplitude INMS stimulation. Unitary recordings obtained within both the MRI and MEG screened-room environments are comparable with those obtained in 'clean' electrophysiology recording environments. Single unit INMS (current met. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

Applying independent component analysis to clinical FMRI at 7 t

OpenAIRE

Robinson, Simon Daniel; Schöpf, Veronika; Cardoso, Pedro; Geissler, Alexander; Fischmeister, Florian P S; Wurnig, Moritz; Trattnig, Siegfried; Beisteiner, Roland

2013-01-01

Increased BOLD sensitivity at 7 T offers the possibility to increase the reliability of fMRI, but ultra-high field is also associated with an increase in artifacts related to head motion, Nyquist ghosting, and parallel imaging reconstruction errors. In this study, the ability of independent component analysis (ICA) to separate activation from these artifacts was assessed in a 7 T study of neurological patients performing chin and hand motor tasks. ICA was able to isolate primary motor activat...

Whole brain, high resolution spin-echo resting state fMRI using PINS multiplexing at 7 T

NARCIS (Netherlands)

Koopmans, P.J.; Boyacioglu, R.; Barth, M.; Norris, David Gordon

2012-01-01

This article demonstrates the application of spin-echo EPI for resting state fMRI at 7 T. A short repetition time of 1860 ms was made possible by the use of slice multiplexing which permitted whole brain coverage at high spatial resolution (84 slices of 1.6 mm thickness). Radiofrequency power

Toward relating the subthalamic nucleus spiking activity to the local field potentials acquired intranuclearly

International Nuclear Information System (INIS)

Michmizos, K P; Nikita, K S; Sakas, D

2011-01-01

Studies on neurophysiological correlates of the functional magnetic resonance imaging (fMRI) signals reveal a strong relationship between the local field potential (LFP) acquired invasively and metabolic signal changes in fMRI experiments. Most of these studies failed to reveal an analogous relationship between metabolic signals and the spiking activity. That would allow for the prediction of the neural activity exclusively from the fMRI signals. However, the relationship between fMRI signals and spiking activity can be inferred indirectly provided that the LFPs can be used to predict the spiking activity of the area. Until now, only the LFP–spike relationship in cortical areas has been examined. Herein, we show that the spiking activity can be predicted by the LFPs acquired in a deep nucleus, namely the subthalamic nucleus (STN), using a nonlinear cascade model. The model can reproduce the spike patterns inside the motor area of the STN that represent information about the motor plans. Our findings expand the possibility of further recruiting non-invasive neuroimaging techniques to understand the activity of the STN and predict or even control movement

The neural substrates of musical memory revealed by fMRI and two semantic tasks.

Science.gov (United States)

Groussard, M; Rauchs, G; Landeau, B; Viader, F; Desgranges, B; Eustache, F; Platel, H

2010-12-01

Recognizing a musical excerpt without necessarily retrieving its title typically reflects the existence of a memory system dedicated to the retrieval of musical knowledge. The functional distinction between musical and verbal semantic memory has seldom been investigated. In this fMRI study, we directly compared the musical and verbal memory of 20 nonmusicians, using a congruence task involving automatic semantic retrieval and a familiarity task requiring more thorough semantic retrieval. In the former, participants had to access their semantic store to retrieve musical or verbal representations of melodies or expressions they heard, in order to decide whether these were then given the right ending or not. In the latter, they had to judge the level of familiarity of musical excerpts and expressions. Both tasks revealed activation of the left inferior frontal and posterior middle temporal cortices, suggesting that executive and selection processes are common to both verbal and musical retrievals. Distinct patterns of activation were observed within the left temporal cortex, with musical material mainly activating the superior temporal gyrus and verbal material the middle and inferior gyri. This cortical organization of musical and verbal semantic representations could explain clinical dissociations featuring selective disturbances for musical or verbal material. Copyright © 2010 Elsevier Inc. All rights reserved.

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

Science.gov (United States)

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

2013-01-01

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

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.

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

Reducing task-based fMRI scanning time using simultaneous multislice echo planar imaging

Energy Technology Data Exchange (ETDEWEB)

Kiss, Mate [Hungarian Academy of Sciences, Brain Imaging Centre, Research Centre for Natural Sciences, Budapest (Hungary); Janos Szentagothai PhD School, MR Research Centre, Budapest (Hungary); National Institute of Clinical Neuroscience, Department of Neuroradiology, Budapest (Hungary); Hermann, Petra; Vidnyanszky, Zoltan; Gal, Viktor [Hungarian Academy of Sciences, Brain Imaging Centre, Research Centre for Natural Sciences, Budapest (Hungary)

2018-03-15

To maintain alertness and to remain motionless during scanning represent a substantial challenge for patients/subjects involved in both clinical and research functional magnetic resonance imaging (fMRI) examinations. Therefore, availability and application of new data acquisition protocols allowing the shortening of scan time without compromising the data quality and statistical power are of major importance. Higher order category-selective visual cortical areas were identified individually, and rapid event-related fMRI design was used to compare three different sampling rates (TR = 2000, 1000, and 410 ms, using state-of-the-art simultaneous multislice imaging) and four different scanning lengths to match the statistical power of the traditional scanning methods to high sampling-rate design. The results revealed that ∝ 4 min of the scan time with 1 Hz (TR = 1000 ms) sampling rate and ∝ 2 min scanning at ∝ 2.5 Hz (TR = 410 ms) sampling rate provide similar localization sensitivity and selectivity to that obtained with 11-min session at conventional, 0.5 Hz (TR = 2000 ms) sampling rate. Our findings suggest that task-based fMRI examination of clinical population prone to distress such as presurgical mapping experiments might substantially benefit from the reduced (20-40%) scanning time that can be achieved by the application of simultaneous multislice sequences. (orig.)

Cortico-Cortical Receptive Field Estimates in Human Visual Cortex

Directory of Open Access Journals (Sweden)

Koen V Haak

2012-05-01

Full Text Available Human visual cortex comprises many visual areas that contain a map of the visual field (Wandell et al 2007, Neuron 56, 366–383. These visual field maps can be identified readily in individual subjects with functional magnetic resonance imaging (fMRI during experimental sessions that last less than an hour (Wandell and Winawer 2011, Vis Res 718–737. Hence, visual field mapping with fMRI has been, and still is, a heavily used technique to examine the organisation of both normal and abnormal human visual cortex (Haak et al 2011, ACNR, 11(3, 20–21. However, visual field mapping cannot reveal every aspect of human visual cortex organisation. For example, the information processed within a visual field map arrives from somewhere and is sent to somewhere, and visual field mapping does not derive these input/output relationships. Here, we describe a new, model-based analysis for estimating the dependence between signals in distinct cortical regions using functional magnetic resonance imaging (fMRI data. Just as a stimulus-referred receptive field predicts the neural response as a function of the stimulus contrast, the neural-referred receptive field predicts the neural response as a function of responses elsewhere in the nervous system. When applied to two cortical regions, this function can be called the cortico-cortical receptive field (CCRF. We model the CCRF as a Gaussian-weighted region on the cortical surface and apply the model to data from both stimulus-driven and resting-state experimental conditions in visual cortex.

Min-max Extrapolation Scheme for Fast Estimation of 3D Potts Field Partition Functions. Application to the Joint Detection-Estimation of Brain Activity in fMRI

International Nuclear Information System (INIS)

Risser, L.; Vincent, T.; Ciuciu, P.; Risser, L.; Idier, J.; Risser, L.; Forbes, F.

2011-01-01

In this paper, we propose a fast numerical scheme to estimate Partition Functions (PF) of symmetric Potts fields. Our strategy is first validated on 2D two-color Potts fields and then on 3D two- and three-color Potts fields. It is then applied to the joint detection-estimation of brain activity from functional Magnetic Resonance Imaging (fMRI) data, where the goal is to automatically recover activated, deactivated and inactivated brain regions and to estimate region dependent hemodynamic filters. For any brain region, a specific 3D Potts field indeed embodies the spatial correlation over the hidden states of the voxels by modeling whether they are activated, deactivated or inactive. To make spatial regularization adaptive, the PFs of the Potts fields over all brain regions are computed prior to the brain activity estimation. Our approach is first based upon a classical path-sampling method to approximate a small subset of reference PFs corresponding to pre-specified regions. Then, we propose an extrapolation method that allows us to approximate the PFs associated to the Potts fields defined over the remaining brain regions. In comparison with preexisting methods either based on a path sampling strategy or mean-field approximations, our contribution strongly alleviates the computational cost and makes spatially adaptive regularization of whole brain fMRI datasets feasible. It is also robust against grid inhomogeneities and efficient irrespective of the topological configurations of the brain regions. (authors)

Autogenic training alters cerebral activation patterns in fMRI.

Science.gov (United States)

Schlamann, Marc; Naglatzki, Ryan; de Greiff, Armin; Forsting, Michael; Gizewski, Elke R

2010-10-01

Cerebral activation patterns during the first three auto-suggestive phases of autogenic training (AT) were investigated in relation to perceived experiences. Nineteen volunteers trained in AT and 19 controls were studied with fMRI during the first steps of autogenic training. FMRI revealed activation of the left postcentral areas during AT in those with experience in AT, which also correlated with the level of AT experience. Activation of prefrontal and insular cortex was significantly higher in the group with experience in AT while insular activation was correlated with number years of simple relaxation exercises. Specific activation in subjects experienced in AT may represent a training effect. Furthermore, the correlation of insular activation suggests that these subjects are different from untrained subjects in emotional processing or self-awareness.

Sparse dictionary learning of resting state fMRI networks.

Science.gov (United States)

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

2012-07-02

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

Acquisition and analysis strategies in functional MRI at high fields

International Nuclear Information System (INIS)

Windischberger, C.

2001-08-01

Functional magnetic resonance imaging represents a non-invasive technique to examine neuronal activity in the brain. It applies radio waves to excite nuclear spins, using the emitted signal during relaxation for image generation. Signal modulations from local blood flow and oxygenation level changes caused by neuronal activity are the basis for calculating functional brain maps with high spatial resolution. The present work discusses concepts for improving the spatial and temporal resolution, as well as sophisticated analysis approaches. Besides an exhaustive description of image reconstruction algorithms, computational simulations on echo-shifting in echo-planar imaging are presented and effects on spatial resolution are quantified. The results demonstrate that echo-shifting causes only minimal resolution losses for high signal-to-noise data, but leads to severe resolution degradation (up to 30 %) in images with low signal-to-noise ratios. After an overview of the mechanisms that cause fMRI signal changes subsequent to neuronal activity, explorative analysis algorithms like Fuzzy Cluster Analysis, as well as parametric approaches are described and discussed. In the context of fMRI artifacts, effects of respiratory motion are examined. For the first time, well-defined breathing patterns are used to quantify the influences on fMRI signal intensity. Also, the variability of fMRI activation in a mental rotation paradigm are investigated, using single-trial analysis. Such, intra-subject activation consistency was determined successfully. Finally, in a second study on mental rotation explorative data analysis was applied to retrieve neuro-functional hypotheses. (author)

The mean-variance relationship reveals two possible strategies for dynamic brain connectivity analysis in fMRI.

Science.gov (United States)

Thompson, William H; Fransson, Peter

2015-01-01

When studying brain connectivity using fMRI, signal intensity time-series are typically correlated with each other in time to compute estimates of the degree of interaction between different brain regions and/or networks. In the static connectivity case, the problem of defining which connections that should be considered significant in the analysis can be addressed in a rather straightforward manner by a statistical thresholding that is based on the magnitude of the correlation coefficients. More recently, interest has come to focus on the dynamical aspects of brain connectivity and the problem of deciding which brain connections that are to be considered relevant in the context of dynamical changes in connectivity provides further options. Since we, in the dynamical case, are interested in changes in connectivity over time, the variance of the correlation time-series becomes a relevant parameter. In this study, we discuss the relationship between the mean and variance of brain connectivity time-series and show that by studying the relation between them, two conceptually different strategies to analyze dynamic functional brain connectivity become available. Using resting-state fMRI data from a cohort of 46 subjects, we show that the mean of fMRI connectivity time-series scales negatively with its variance. This finding leads to the suggestion that magnitude- versus variance-based thresholding strategies will induce different results in studies of dynamic functional brain connectivity. Our assertion is exemplified by showing that the magnitude-based strategy is more sensitive to within-resting-state network (RSN) connectivity compared to between-RSN connectivity whereas the opposite holds true for a variance-based analysis strategy. The implications of our findings for dynamical functional brain connectivity studies are discussed.

Intrusive Memories of Distressing Information: An fMRI Study.

Directory of Open Access Journals (Sweden)

Eva Battaglini

Full Text Available Although intrusive memories are characteristic of many psychological disorders, the neurobiological underpinning of these involuntary recollections are largely unknown. In this study we used functional magentic resonance imaging (fMRI to identify the neural networks associated with encoding of negative stimuli that are subsequently experienced as intrusive memories. Healthy partipants (N = 42 viewed negative and neutral images during a visual/verbal processing task in an fMRI context. Two days later they were assessed on the Impact of Event Scale for occurrence of intrusive memories of the encoded images. A sub-group of participants who reported significant intrusions (n = 13 demonstrated stronger activation in the amygdala, bilateral ACC and parahippocampal gyrus during verbal encoding relative to a group who reported no intrusions (n = 13. Within-group analyses also revealed that the high intrusion group showed greater activity in the dorsomedial (dmPFC and dorsolateral prefrontal cortex (dlPFC, inferior frontal gyrus and occipital regions during negative verbal processing compared to neutral verbal processing. These results do not accord with models of intrusions that emphasise visual processing of information at encoding but are consistent with models that highlight the role of inhibitory and suppression processes in the formation of subsequent intrusive memories.

Saturn's Internal Magnetic Field Revealed by Cassini Grand Finale

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Cao, H.; Dougherty, M. K.; Khurana, K. K.; Hunt, G. J.; Provan, G.; Kellock, S.; Burton, M. E.; Burk, T. A.

2017-12-01

Saturn's internal magnetic field has been puzzling since the first in-situ measurements during the Pioneer 11 Saturn flyby. Cassini magnetometer measurements prior to the Grand Finale phase established 1) the highly axisymmetric nature of Saturn's internal magnetic field with a dipole tilt smaller than 0.06 degrees, 2) at least an order of magnitude slower secular variation rate compared to that of the current geomagnetic field, and 3) expulsion of magnetic fluxes from the equatorial region towards high latitude. The highly axisymmetric nature of Saturn's intrinsic magnetic field not only challenges dynamo theory but also makes an accurate determination of the interior rotation rate of Saturn extremely difficult. The Cassini spacecraft entered the Grand Finale phase in April 2017, during which time the spacecraft dived through the gap between Saturn's atmosphere and the inner edge of the D-ring 22 times before descending into the deep atmosphere of Saturn. The unprecedented proximity to Saturn (reaching 2500 km above the cloud deck) and the highly inclined nature of the Grand Finale orbits provided an ideal opportunity to decode Saturn's internal magnetic field. The fluxgate magnetometer onboard Cassini made precise vector measurements during the Grand Finale phase. Magnetic signals from the interior of the planet, the magnetospheric ring current, the high-latitude field-aligned current (FAC) modulated by the 10.7 hour planetary period oscillation, and low-latitude FACs were observed during the Grand Finale phase. Here we report the magnetometer measurements during the Cassini Grand Finale phase, new features of Saturn's internal magnetic field revealed by these measurements (e.g., the high degree magnetic moments of Saturn, the level of axisymmetry beyond dipole), and implications for the deep interior of Saturn.

From Mahan excitons to Landau levels at high magnetic fields: 2DFT spectroscopy reveals hidden quantum correlations (Conference Presentation)

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Karaiskaj, Denis

2017-02-01

Two-dimensional electron gases have been the subject of research for decades. Modulation doped GaAs quantum wells in the absence of magnetic fields exhibit interesting many-body physics such as the Fermi edge singularity or Mahan exciton and can be regarded as a collective excitation of the system. Under high magnetic fields Landau levels form which have been studied using transport and optical measurements. Nonlinear coherent two-dimensional Fourier transform (2DFT) spectroscopy however provides new insights into these systems. We present the 2DFT spectra of Mahan Excitons associated with the heavy-hole and light-hole resonances observed in a modulation doped GaAs/AlGaAs single quantum well [1]. These resonances are observed to be strongly coupled through many-body interactions. The 2DFT spectra were measured using co-linear, cross-linear, and co-circular polarizations and reveal striking differences. Furthermore, 2DFT spectra at high magnetic fields performed at the National High Magnetic Field Lab (NHMFL) in Tallahassee, Florida will be discussed. The spectra exhibit new features and peculiar line shapes suggesting interesting underlying physics. [1] J. Paul, C. E. Stevens, C. Liu, P. Dey, C. McIntyre, V. Turkowski, J. L. Reno, D. J. Hilton, and D. Karaiskaj, Phys. Rev. Lett.116, 157401 (2016).

Physiologic noise regression, motion regression, and TOAST dynamic field correction in complex-valued fMRI time series.

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Hahn, Andrew D; Rowe, Daniel B

2012-02-01

As more evidence is presented suggesting that the phase, as well as the magnitude, of functional MRI (fMRI) time series may contain important information and that there are theoretical drawbacks to modeling functional response in the magnitude alone, removing noise in the phase is becoming more important. Previous studies have shown that retrospective correction of noise from physiologic sources can remove significant phase variance and that dynamic main magnetic field correction and regression of estimated motion parameters also remove significant phase fluctuations. In this work, we investigate the performance of physiologic noise regression in a framework along with correction for dynamic main field fluctuations and motion regression. Our findings suggest that including physiologic regressors provides some benefit in terms of reduction in phase noise power, but it is small compared to the benefit of dynamic field corrections and use of estimated motion parameters as nuisance regressors. Additionally, we show that the use of all three techniques reduces phase variance substantially, removes undesirable spatial phase correlations and improves detection of the functional response in magnitude and phase. Copyright © 2011 Elsevier Inc. All rights reserved.

fMRI reveals reciprocal inhibition between social and physical cognitive domains

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Jack, Anthony I.; Dawson, Abigail; Begany, Katelyn; Leckie, Regina L.; Barry, Kevin; Ciccia, Angela; Snyder, Abraham

2012-01-01

Two lines of evidence indicate that there exists a reciprocal inhibitory relationship between opposed brain networks. First, most attention-demanding cognitive tasks activate a stereotypical set of brain areas, known as the task-positive network and simultaneously deactivate a different set of brain regions, commonly referred to as the task negative or default mode network. Second, functional connectivity analyses show that these same opposed networks are anti-correlated in the resting state. We hypothesize that these reciprocally inhibitory effects reflect two incompatible cognitive modes, each of which is directed towards understanding the external world. Thus, engaging one mode activates one set of regions and suppresses activity in the other. We test this hypothesis by identifying two types of problem-solving task which, on the basis of prior work, have been consistently associated with the task positive and task negative regions: tasks requiring social cognition, i.e., reasoning about the mental states of other persons, and tasks requiring physical cognition, i.e., reasoning about the causal/mechanical properties of inanimate objects. Social and mechanical reasoning tasks were presented to neurologically normal participants during fMRI. Each task type was presented using both text and video clips. Regardless of presentation modality, we observed clear evidence of reciprocal suppression: social tasks deactivated regions associated with mechanical reasoning and mechanical tasks deactivated regions associated with social reasoning. These findings are not explained by self-referential processes, task engagement, mental simulation, mental time travel or external vs. internal attention, all factors previously hypothesized to explain default mode network activity. Analyses of resting state data revealed a close match between the regions our tasks identified as reciprocally inhibitory and regions of maximal anti-correlation in the resting state. These results indicate

fMRI reveals reciprocal inhibition between social and physical cognitive domains.

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Jack, Anthony I; Dawson, Abigail J; Begany, Katelyn L; Leckie, Regina L; Barry, Kevin P; Ciccia, Angela H; Snyder, Abraham Z

2013-02-01

Two lines of evidence indicate that there exists a reciprocal inhibitory relationship between opposed brain networks. First, most attention-demanding cognitive tasks activate a stereotypical set of brain areas, known as the task-positive network and simultaneously deactivate a different set of brain regions, commonly referred to as the task negative or default mode network. Second, functional connectivity analyses show that these same opposed networks are anti-correlated in the resting state. We hypothesize that these reciprocally inhibitory effects reflect two incompatible cognitive modes, each of which may be directed towards understanding the external world. Thus, engaging one mode activates one set of regions and suppresses activity in the other. We test this hypothesis by identifying two types of problem-solving task which, on the basis of prior work, have been consistently associated with the task positive and task negative regions: tasks requiring social cognition, i.e., reasoning about the mental states of other persons, and tasks requiring physical cognition, i.e., reasoning about the causal/mechanical properties of inanimate objects. Social and mechanical reasoning tasks were presented to neurologically normal participants during fMRI. Each task type was presented using both text and video clips. Regardless of presentation modality, we observed clear evidence of reciprocal suppression: social tasks deactivated regions associated with mechanical reasoning and mechanical tasks deactivated regions associated with social reasoning. These findings are not explained by self-referential processes, task engagement, mental simulation, mental time travel or external vs. internal attention, all factors previously hypothesized to explain default mode network activity. Analyses of resting state data revealed a close match between the regions our tasks identified as reciprocally inhibitory and regions of maximal anti-correlation in the resting state. These results

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

The mean–variance relationship reveals two possible strategies for dynamic brain connectivity analysis in fMRI

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Thompson, William H.; Fransson, Peter

2015-01-01

When studying brain connectivity using fMRI, signal intensity time-series are typically correlated with each other in time to compute estimates of the degree of interaction between different brain regions and/or networks. In the static connectivity case, the problem of defining which connections that should be considered significant in the analysis can be addressed in a rather straightforward manner by a statistical thresholding that is based on the magnitude of the correlation coefficients. More recently, interest has come to focus on the dynamical aspects of brain connectivity and the problem of deciding which brain connections that are to be considered relevant in the context of dynamical changes in connectivity provides further options. Since we, in the dynamical case, are interested in changes in connectivity over time, the variance of the correlation time-series becomes a relevant parameter. In this study, we discuss the relationship between the mean and variance of brain connectivity time-series and show that by studying the relation between them, two conceptually different strategies to analyze dynamic functional brain connectivity become available. Using resting-state fMRI data from a cohort of 46 subjects, we show that the mean of fMRI connectivity time-series scales negatively with its variance. This finding leads to the suggestion that magnitude- versus variance-based thresholding strategies will induce different results in studies of dynamic functional brain connectivity. Our assertion is exemplified by showing that the magnitude-based strategy is more sensitive to within-resting-state network (RSN) connectivity compared to between-RSN connectivity whereas the opposite holds true for a variance-based analysis strategy. The implications of our findings for dynamical functional brain connectivity studies are discussed. PMID:26236216

Bayesian spatiotemporal model of fMRI data using transfer functions.

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

2010-09-01

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

Age differences in the motor control of speech: An fMRI study of healthy aging.

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Tremblay, Pascale; Sato, Marc; Deschamps, Isabelle

2017-05-01

Healthy aging is associated with a decline in cognitive, executive, and motor processes that are concomitant with changes in brain activation patterns, particularly at high complexity levels. While speech production relies on all these processes, and is known to decline with age, the mechanisms that underlie these changes remain poorly understood, despite the importance of communication on everyday life. In this cross-sectional group study, we investigated age differences in the neuromotor control of speech production by combining behavioral and functional magnetic resonance imaging (fMRI) data. Twenty-seven healthy adults underwent fMRI while performing a speech production task consisting in the articulation of nonwords of different sequential and motor complexity. Results demonstrate strong age differences in movement time (MT), with longer and more variable MT in older adults. The fMRI results revealed extensive age differences in the relationship between BOLD signal and MT, within and outside the sensorimotor system. Moreover, age differences were also found in relation to sequential complexity within the motor and attentional systems, reflecting both compensatory and de-differentiation mechanisms. At very high complexity level (high motor complexity and high sequence complexity), age differences were found in both MT data and BOLD response, which increased in several sensorimotor and executive control areas. Together, these results suggest that aging of motor and executive control mechanisms may contribute to age differences in speech production. These findings highlight the importance of studying functionally relevant behavior such as speech to understand the mechanisms of human brain aging. Hum Brain Mapp 38:2751-2771, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

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

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

2017-07-01

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

Analysis strategies for high-resolution UHF-fMRI data.

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Polimeni, Jonathan R; Renvall, Ville; Zaretskaya, Natalia; Fischl, Bruce

2018-03-01

Functional MRI (fMRI) benefits from both increased sensitivity and specificity with increasing magnetic field strength, making it a key application for Ultra-High Field (UHF) MRI scanners. Most UHF-fMRI studies utilize the dramatic increases in sensitivity and specificity to acquire high-resolution data reaching sub-millimeter scales, which enable new classes of experiments to probe the functional organization of the human brain. This review article surveys advanced data analysis strategies developed for high-resolution fMRI at UHF. These include strategies designed to mitigate distortion and artifacts associated with higher fields in ways that attempt to preserve spatial resolution of the fMRI data, as well as recently introduced analysis techniques that are enabled by these extremely high-resolution data. Particular focus is placed on anatomically-informed analyses, including cortical surface-based analysis, which are powerful techniques that can guide each step of the analysis from preprocessing to statistical analysis to interpretation and visualization. New intracortical analysis techniques for laminar and columnar fMRI are also reviewed and discussed. Prospects for single-subject individualized analyses are also presented and discussed. Altogether, there are both specific challenges and opportunities presented by UHF-fMRI, and the use of proper analysis strategies can help these valuable data reach their full potential. Copyright © 2017 Elsevier Inc. All rights reserved.

Resting state FMRI research in child psychiatric disorders

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Oldehinkel, Marianne; Francx, Winke; Beckmann, Christian; Buitelaar, Jan K.; Mennes, Maarten

2013-01-01

Concurring with the shift from linking functions to specific brain areas towards studying network integration, resting state FMRI (R-FMRI) has become an important tool for delineating the functional network architecture of the brain. Fueled by straightforward data collection, R-FMRI analysis methods

Imaging gait analysis: An fMRI dual task study.

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

2017-08-01

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

Decoding Complex Cognitive States Online by Manifold Regularization in Real-Time fMRI

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Hansen, Toke Jansen; Hansen, Lars Kai; Madsen, Kristoffer Hougaard

2011-01-01

Human decision making is complex and influenced by many factors on multiple time scales, reflected in the numerous brain networks and connectivity patterns involved as revealed by fMRI. We address mislabeling issues in paradigms involving complex cognition, by considering a manifold regularizing...

Visibility graphs for fMRI data: Multiplex temporal graphs and their modulations across resting-state networks

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Speranza Sannino

2017-10-01

Full Text Available Visibility algorithms are a family of methods that map time series into graphs, such that the tools of graph theory and network science can be used for the characterization of time series. This approach has proved a convenient tool, and visibility graphs have found applications across several disciplines. Recently, an approach has been proposed to extend this framework to multivariate time series, allowing a novel way to describe collective dynamics. Here we test their application to fMRI time series, following two main motivations, namely that (a this approach allows vs to simultaneously capture and process relevant aspects of both local and global dynamics in an easy and intuitive way, and (b this provides a suggestive bridge between time series and network theory that nicely fits the consolidating field of network neuroscience. Our application to a large open dataset reveals differences in the similarities of temporal networks (and thus in correlated dynamics across resting-state networks, and gives indications that some differences in brain activity connected to psychiatric disorders could be picked up by this approach. Here we present the first application of multivariate visibility graphs to fMRI data. Visibility graphs are a way to represent a time series as a temporal network, evidencing specific aspects of its dynamics, such as extreme events. Multivariate time series, as those encountered in neuroscience, and in fMRI in particular, can be seen as a multiplex network, in which each layer represents a time series (a region of interest in the brain in our case. Here we report the method, we describe some relevant aspects of its application to BOLD time series, and we discuss the analogies and differences with existing methods. Finally, we present an application to a high-quality, publicly available dataset, containing healthy subjects and psychotic patients, and we discuss our findings. All the code to reproduce the analyses and the

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

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

2017-07-01

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

Amygdala fMRI Signal as a Predictor of Reaction Time

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Philipp Riedel

2016-10-01

Full Text Available Reaction times (RT are a valuable measure for assessing cognitive processes. However, RTs are susceptible to confounds and therefore variable. Exposure to threat, for example, speeds up or slows down responses. Distinct task types to some extent account for differential effects of threat on RTs. But also do inter-individual differences like trait anxiety. In this functional magnetic resonance imaging study, we investigated whether activation within the amygdala, a brain region closely linked to the processing of threat, may also function as a predictor of RTs, similar to trait anxiety scores. After threat conditioning by means of aversive electric shocks, 45 participants performed a choice RT task during alternating 30s blocks in the presence of the threat conditioned stimulus CS+ or of the safe control stimulus CS-. Trait anxiety was assessed with the State-Trait-Anxiety-Inventory and participants were median split into a high- and a low-anxiety subgroup. We tested three hypotheses: 1 RTs will be faster during the exposure to threat compared to the safe condition in individuals with high trait anxiety. 2 The amygdala fMRI signal will be higher in the threat condition compared to the safe condition. 3 Amygdala fMRI signal prior to a RT trial will be correlated with the corresponding RT. We found that, the high-anxious subgroup showed faster responses in the threat condition compared to the safe condition, while the low-anxious subgroup showed no significant difference in RTs in the threat condition compared to the safe condition. Though the fMRI analysis did not reveal an effect of condition on amygdala activity, we found a trial-by-trial correlation between blood-oxygen-level-dependent signal within the right amygdala prior to the CRT task and the subsequent RT. Taken together, the results of this study showed that: Exposure to threat modulates task performance. This modulation is influenced by personality trait. Additionally and most

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

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

2017-02-01

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

Combination of DTI and fMRI reveals the white matter changes correlating with the decline of default-mode network activity in Alzheimer's disease

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Wu, Xianjun; Di, Qian; Li, Yao; Zhao, Xiaojie

2009-02-01

Recently, evidences from fMRI studies have shown that there was decreased activity among the default-mode network in Alzheimer's disease (AD), and DTI researches also demonstrated that demyelinations exist in white matter of AD patients. Therefore, combining these two MRI methods may help to reveal the relationship between white matter damages and alterations of the resting state functional connectivity network. In the present study, we tried to address this issue by means of correlation analysis between DTI and resting state fMRI images. The default-mode networks of AD and normal control groups were compared to find the areas with significantly declined activity firstly. Then, the white matter regions whose fractional anisotropy (FA) value correlated with this decline were located through multiple regressions between the FA values and the BOLD response of the default networks. Among these correlating white matter regions, those whose FA values also declined were found by a group comparison between AD patients and healthy elderly control subjects. Our results showed that the areas with decreased activity among default-mode network included left posterior cingulated cortex (PCC), left medial temporal gyrus et al. And the damaged white matter areas correlated with the default-mode network alterations were located around left sub-gyral temporal lobe. These changes may relate to the decreased connectivity between PCC and medial temporal lobe (MTL), and thus correlate with the deficiency of default-mode network activity.

Extensive cochleotopic mapping of human auditory cortical fields obtained with phase-encoding FMRI.

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Ella Striem-Amit

Full Text Available The primary sensory cortices are characterized by a topographical mapping of basic sensory features which is considered to deteriorate in higher-order areas in favor of complex sensory features. Recently, however, retinotopic maps were also discovered in the higher-order visual, parietal and prefrontal cortices. The discovery of these maps enabled the distinction between visual regions, clarified their function and hierarchical processing. Could such extension of topographical mapping to high-order processing regions apply to the auditory modality as well? This question has been studied previously in animal models but only sporadically in humans, whose anatomical and functional organization may differ from that of animals (e.g. unique verbal functions and Heschl's gyrus curvature. Here we applied fMRI spectral analysis to investigate the cochleotopic organization of the human cerebral cortex. We found multiple mirror-symmetric novel cochleotopic maps covering most of the core and high-order human auditory cortex, including regions considered non-cochleotopic, stretching all the way to the superior temporal sulcus. These maps suggest that topographical mapping persists well beyond the auditory core and belt, and that the mirror-symmetry of topographical preferences may be a fundamental principle across sensory modalities.

Resting-state FMRI confounds and cleanup

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Murphy, Kevin; Birn, Rasmus M.; Bandettini, Peter A.

2013-01-01

The goal of resting-state functional magnetic resonance imaging (FMRI) is to investigate the brain’s functional connections by using the temporal similarity between blood oxygenation level dependent (BOLD) signals in different regions of the brain “at rest” as an indicator of synchronous neural activity. Since this measure relies on the temporal correlation of FMRI signal changes between different parts of the brain, any non-neural activity-related process that affects the signals will influence the measure of functional connectivity, yielding spurious results. To understand the sources of these resting-state FMRI confounds, this article describes the origins of the BOLD signal in terms of MR physics and cerebral physiology. Potential confounds arising from motion, cardiac and respiratory cycles, arterial CO2 concentration, blood pressure/cerebral autoregulation, and vasomotion are discussed. Two classes of techniques to remove confounds from resting-state BOLD time series are reviewed: 1) those utilising external recordings of physiology and 2) data-based cleanup methods that only use the resting-state FMRI data itself. Further methods that remove noise from functional connectivity measures at a group level are also discussed. For successful interpretation of resting-state FMRI comparisons and results, noise cleanup is an often over-looked but essential step in the analysis pipeline. PMID:23571418

A receptor-based model for dopamine-induced fMRI signal

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

2013-01-01

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

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

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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

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

DEFF Research Database (Denmark)

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

2010-01-01

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

An fMRI study of Agency

DEFF Research Database (Denmark)

Charalampaki, Angeliki

2017-01-01

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

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

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

2014-11-07

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

Right and left amygdalae activation in patients with major depression receiving antidepressant treatment, as revealed by fMRI.

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Chen, Yen-Ting; Huang, Min-Wei; Hung, I-Chung; Lane, Hsien-Yuan; Hou, Chun-Ju

2014-10-08

treatment for each emotion tested. In the future, changes in BOLD signals as revealed by fMRI might be useful in evaluating the clinical manifestation of major depression.

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

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

2015-01-01

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

Comparison of PET and fMRI activation patterns during declarative memory processes

International Nuclear Information System (INIS)

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

2000-01-01

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

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

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

2014-01-01

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

Intersession reliability of fMRI activation for heat pain and motor tasks

Science.gov (United States)

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

2014-01-01

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

Signal Sampling for Efficient Sparse Representation of Resting State FMRI Data

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Ge, Bao; Makkie, Milad; Wang, Jin; Zhao, Shijie; Jiang, Xi; Li, Xiang; Lv, Jinglei; Zhang, Shu; Zhang, Wei; Han, Junwei; Guo, Lei; Liu, Tianming

2015-01-01

As the size of brain imaging data such as fMRI grows explosively, it provides us with unprecedented and abundant information about the brain. How to reduce the size of fMRI data but not lose much information becomes a more and more pressing issue. Recent literature studies tried to deal with it by dictionary learning and sparse representation methods, however, their computation complexities are still high, which hampers the wider application of sparse representation method to large scale fMRI datasets. To effectively address this problem, this work proposes to represent resting state fMRI (rs-fMRI) signals of a whole brain via a statistical sampling based sparse representation. First we sampled the whole brain’s signals via different sampling methods, then the sampled signals were aggregate into an input data matrix to learn a dictionary, finally this dictionary was used to sparsely represent the whole brain’s signals and identify the resting state networks. Comparative experiments demonstrate that the proposed signal sampling framework can speed-up by ten times in reconstructing concurrent brain networks without losing much information. The experiments on the 1000 Functional Connectomes Project further demonstrate its effectiveness and superiority. PMID:26646924

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.

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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.

Atlas-based head modeling and spatial normalization for high-density diffuse optical tomography: in vivo validation against fMRI.

Science.gov (United States)

Ferradal, Silvina L; Eggebrecht, Adam T; Hassanpour, Mahlega; Snyder, Abraham Z; Culver, Joseph P

2014-01-15

Diffuse optical imaging (DOI) is increasingly becoming a valuable neuroimaging tool when fMRI is precluded. Recent developments in high-density diffuse optical tomography (HD-DOT) overcome previous limitations of sparse DOI systems, providing improved image quality and brain specificity. These improvements in instrumentation prompt the need for advancements in both i) realistic forward light modeling for accurate HD-DOT image reconstruction, and ii) spatial normalization for voxel-wise comparisons across subjects. Individualized forward light models derived from subject-specific anatomical images provide the optimal inverse solutions, but such modeling may not be feasible in all situations. In the absence of subject-specific anatomical images, atlas-based head models registered to the subject's head using cranial fiducials provide an alternative solution. In addition, a standard atlas is attractive because it defines a common coordinate space in which to compare results across subjects. The question therefore arises as to whether atlas-based forward light modeling ensures adequate HD-DOT image quality at the individual and group level. Herein, we demonstrate the feasibility of using atlas-based forward light modeling and spatial normalization methods. Both techniques are validated using subject-matched HD-DOT and fMRI data sets for visual evoked responses measured in five healthy adult subjects. HD-DOT reconstructions obtained with the registered atlas anatomy (i.e. atlas DOT) had an average localization error of 2.7mm relative to reconstructions obtained with the subject-specific anatomical images (i.e. subject-MRI DOT), and 6.6mm relative to fMRI data. At the group level, the localization error of atlas DOT reconstruction was 4.2mm relative to subject-MRI DOT reconstruction, and 6.1mm relative to fMRI. These results show that atlas-based image reconstruction provides a viable approach to individual head modeling for HD-DOT when anatomical imaging is not available

Ultrafast bold fMRI using single-shot spin-echo echo planar imaging

Directory of Open Access Journals (Sweden)

Boujraf Said

2009-01-01

Full Text Available The choice of imaging parameters for functional MRI can have an impact on the accuracy of functional localization by affecting the image quality and the degree of blood oxygenation-dependent (BOLD contrast achieved. By improving sampling efficiency, parallel acquisition techniques such as sensitivity encoding (SENSE have been used to shorten readout trains in single-shot (SS echo planar imaging (EPI. This has been applied to susceptibility artifact reduction and improving spatial resolution. SENSE together with single-shot spin-echo (SS-SE imaging may also reduce off-resonance artifacts. The goal of this work was to investigate the BOLD response of a SENSE-adapted SE-EPI on a three Tesla scanner. Whole-brain fMRI studies of seven healthy right hand-dominant volunteers were carried out in a three Tesla scanner. fMRI was performed using an SS-SE EPI sequence with SENSE. The data was processed using statistical parametric mapping. Both, group and individual subject data analyses were performed. Individual average percentage and maximal percentage signal changes attributed to the BOLD effect in M1 were calculated for all the subjects as a function of echo time. Corresponding activation maps and the sizes of the activated clusters were also calculated. Our results show that susceptibility artifacts were reduced with the use of SENSE; and the acquired BOLD images were free of the typical quadrature artifacts of SS-EPI. Such measures are crucial at high field strengths. SS SE-EPI with SENSE offers further benefits in this regard and is more specific for oxygenation changes in the microvasculature bed. Functional brain activity can be investigated with the help of single-shot spin echo EPI using SENSE at high magnetic fields.

Resting-state fMRI revealed different brain activities responding to valproic acid and levetiracetam in benign epilepsy with central-temporal spikes

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Zhang, Qirui; Zhang, Zhiqiang; Xu, Qiang; Wu, Han; Li, Zhipeng; Lu, Guangming [Nanjing University School of Medicine, Department of Medical Imaging, Jinling Hospital, Nanjing (China); Yang, Fang; Li, Qian [Nanjing University School of Medicine, Department of Neurology, Jinling Hospital, Nanjing (China); Hu, Zheng [Nanjing Children' s Hospital, Department of Neurology, Nanjing (China); Dante, Mantini [Faculty of Kinesiology and Rehabilitation Sciences, KU Leuven (Belgium); Li, Kai [Suzhou University, Laboratory of Molecular Medicine, Suzhou (China)

2017-05-15

Our aim was to investigate regional difference in brain activities in response to antiepileptic drug (AED) medications in benign epilepsy with central-temporal spikes (BECTS) using resting-state functional magnetic resonance imaging (fMRI). Fifty-seven patients with BECTS underwent resting-state fMRI scans after receiving either valproic acid (VPA) (n = 15), levetiracetam (LEV) (n = 21), or no medication (n = 21). fMRI regional homogeneity (ReHo) parameter among the three groups of patients were compared and were correlated with total doses of AED in the two medicated groups. Compared with patients on no-medication, patients receiving either VPA or LEV showed decreased ReHo in the central-temporal region, frontal cortex, and thalamus. In particular, the VPA group showed greater ReHo decrease in the thalamus and milder in cortices and caudate heads compared with the LEV group. In addition, the VPA group demonstrated a negative correlation between ReHo values in the central-temporal region and medication dose. Both VPA and LEV inhibit resting-state neural activity in the central-temporal region, which is the main epileptogenic focus of BECTS. VPA reduced brain activity in the cortical epileptogenic regions and thalamus evenly, whereas LEV reduced brain activity predominantly in the cortices. Interestingly, VPA showed a cumulative effect on inhibiting brain activity in the epileptogenic regions in BECTS. (orig.)

Resting-state fMRI revealed different brain activities responding to valproic acid and levetiracetam in benign epilepsy with central-temporal spikes

International Nuclear Information System (INIS)

Zhang, Qirui; Zhang, Zhiqiang; Xu, Qiang; Wu, Han; Li, Zhipeng; Lu, Guangming; Yang, Fang; Li, Qian; Hu, Zheng; Dante, Mantini; Li, Kai

2017-01-01

Our aim was to investigate regional difference in brain activities in response to antiepileptic drug (AED) medications in benign epilepsy with central-temporal spikes (BECTS) using resting-state functional magnetic resonance imaging (fMRI). Fifty-seven patients with BECTS underwent resting-state fMRI scans after receiving either valproic acid (VPA) (n = 15), levetiracetam (LEV) (n = 21), or no medication (n = 21). fMRI regional homogeneity (ReHo) parameter among the three groups of patients were compared and were correlated with total doses of AED in the two medicated groups. Compared with patients on no-medication, patients receiving either VPA or LEV showed decreased ReHo in the central-temporal region, frontal cortex, and thalamus. In particular, the VPA group showed greater ReHo decrease in the thalamus and milder in cortices and caudate heads compared with the LEV group. In addition, the VPA group demonstrated a negative correlation between ReHo values in the central-temporal region and medication dose. Both VPA and LEV inhibit resting-state neural activity in the central-temporal region, which is the main epileptogenic focus of BECTS. VPA reduced brain activity in the cortical epileptogenic regions and thalamus evenly, whereas LEV reduced brain activity predominantly in the cortices. Interestingly, VPA showed a cumulative effect on inhibiting brain activity in the epileptogenic regions in BECTS. (orig.)

Archetypal Analysis for Modeling Multisubject fMRI Data

DEFF Research Database (Denmark)

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

2016-01-01

are assumed to be generated by a set of 'prototype' time series. Archetypal analysis (AA) provides a promising alternative, combining the advantages of component-model flexibility with highly interpretable latent 'archetypes' (similar to cluster-model prototypes). To date, AA has not been applied to group......-level fMRI; a major limitation is that it does not generalize to multi-subject datasets, which may have significant variations in blood oxygenation-level-dependent signal and heteroscedastic noise. We develop multi-subject AA (MS-AA), which accounts for group-level data by assuming that archetypal...... performance when modelling archetypes for a motor task experiment. The procedure extracts a 'seed map' across subjects, used to provide brain parcellations with subject-specific temporal profiles. Our approach thus decomposes multisubject fMRI data into distinct interpretable component archetypes that may...

Individual differences in decision making competence revealed by multivariate fMRI.

Science.gov (United States)

Talukdar, Tanveer; Román, Francisco J; Operskalski, Joachim T; Zwilling, Christopher E; Barbey, Aron K

2018-06-01

While an extensive literature in decision neuroscience has elucidated the neurobiological foundations of decision making, prior research has focused primarily on group-level effects in a sample population. Due to the presence of inherent differences between individuals' cognitive abilities, it is also important to examine the neural correlates of decision making that explain interindividual variability in cognitive performance. This study therefore investigated how individual differences in decision making competence, as measured by the Adult Decision Making Competence (A-DMC) battery, are related to functional brain connectivity patterns derived from resting-state fMRI data in a sample of 304 healthy participants. We examined connectome-wide associations, identifying regions within frontal, parietal, temporal, and occipital cortex that demonstrated significant associations with decision making competence. We then assessed whether the functional interactions between brain regions sensitive to decision making competence and seven intrinsic connectivity networks (ICNs) were predictive of specific facets of decision making assessed by subtests of the A-DMC battery. Our findings suggest that individual differences in specific facets of decision making competence are mediated by ICNs that support executive, social, and perceptual processes, and motivate an integrative framework for understanding the neural basis of individual differences in decision making competence. © 2018 Wiley Periodicals, Inc.

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

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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.

Dominance of layer-specific microvessel dilation in contrast-enhanced high-resolution fMRI: Comparison between hemodynamic spread and vascular architecture with CLARITY.

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Poplawsky, Alexander John; Fukuda, Mitsuhiro; Kang, Bok-Man; Kim, Jae Hwan; Suh, Minah; Kim, Seong-Gi

2017-08-16

Contrast-enhanced cerebral blood volume-weighted (CBVw) fMRI response peaks are specific to the layer of evoked synaptic activity (Poplawsky et al., 2015), but the spatial resolution limit of CBVw fMRI is unknown. In this study, we measured the laminar spread of the CBVw fMRI evoked response in the external plexiform layer (EPL, 265 ± 65 μm anatomical thickness, mean ± SD, n = 30 locations from 5 rats) of the rat olfactory bulb during electrical stimulation of the lateral olfactory tract and examined its potential vascular source. First, we obtained the evoked CBVw fMRI responses with a 55 × 55 μm 2 in-plane resolution and a 500-μm thickness at 9.4 T, and found that the fMRI signal peaked predominantly in the inner half of EPL (136 ± 54 μm anatomical thickness). The mean full-width at half-maximum of these fMRI peaks was 347 ± 102 μm and the functional spread was approximately 100 or 200 μm when the effects of the laminar thicknesses of EPL or inner EPL were removed, respectively. Second, we visualized the vascular architecture of EPL from a different rat using a Clear Lipid-exchanged Anatomically Rigid Imaging/immunostaining-compatible Tissue hYdrogel (CLARITY)-based tissue preparation method and confocal microscopy. Microvascular segments with an outer diameter of limit of the fMRI spatial resolution is approximately the average length of 1-2 microvessel segments, which may be sufficient for examining sublaminar circuits. Copyright © 2017 Elsevier Inc. All rights reserved.

Behavior, neuropsychology and fMRI.

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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.

Safety and EEG data quality of concurrent high-density EEG and high-speed fMRI at 3 Tesla

DEFF Research Database (Denmark)

Foged, Mette Thrane; Lindberg, Ulrich; Vakamudi, Kishore

2017-01-01

) related heating, the effect of EEG on cortical signal-to-noise ratio (SNR) in fMRI, and assess EEG data quality. MATERIALS AND METHODS: The study compared EPI, multi-echo EPI, multi-band EPI and multi-slab echo-volumar imaging pulse sequences, using clinical 3 Tesla MR scanners from two different vendors...

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.

Framing effects reveal discrete lexical-semantic and sublexical procedures in reading: an fMRI study.

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Danelli, Laura; Marelli, Marco; Berlingeri, Manuela; Tettamanti, Marco; Sberna, Maurizio; Paulesu, Eraldo; Luzzatti, Claudio

2015-01-01

According to the dual-route model, a printed string of letters can be processed by either a grapheme-to-phoneme conversion (GPC) route or a lexical-semantic route. Although meta-analyses of the imaging literature support the existence of distinct but interacting reading procedures, individual neuroimaging studies that explored neural correlates of reading yielded inconclusive results. We used a list-manipulation paradigm to provide a fresh empirical look at this issue and to isolate specific areas that underlie the two reading procedures. In a lexical condition, we embedded disyllabic Italian words (target stimuli) in lists of either loanwords or trisyllabic Italian words with unpredictable stress position. In a GPC condition, similar target stimuli were included within lists of pseudowords. The procedure was designed to induce participants to emphasize either the lexical-semantic or the GPC reading procedure, while controlling for possible linguistic confounds and keeping the reading task requirements stable across the two conditions. Thirty-three adults participated in the behavioral study, and 20 further adult participants were included in the fMRI study. At the behavioral level, we found sizeable effects of the framing manipulations that included slower voice onset times for stimuli in the pseudoword frames. At the functional anatomical level, the occipital and temporal regions, and the intraparietal sulcus were specifically activated when subjects were reading target words in a lexical frame. The inferior parietal and anterior fusiform cortex were specifically activated in the GPC condition. These patterns of activation represented a valid classifying model of fMRI images associated with target reading in both frames in the multi-voxel pattern analyses. Further activations were shared by the two procedures in the occipital and inferior parietal areas, in the premotor cortex, in the frontal regions and the left supplementary motor area. These regions are most

Estimating Dynamic Connectivity States in fMRI Using Regime-Switching Factor Models

KAUST Repository

Ting, Chee-Ming

2017-12-06

We consider the challenges in estimating state-related changes in brain connectivity networks with a large number of nodes. Existing studies use sliding-window analysis or time-varying coefficient models which are unable to capture both smooth and abrupt changes simultaneously, and rely on ad-hoc approaches to the high-dimensional estimation. To overcome these limitations, we propose a Markov-switching dynamic factor model which allows the dynamic connectivity states in functional magnetic resonance imaging (fMRI) data to be driven by lower-dimensional latent factors. We specify a regime-switching vector autoregressive (SVAR) factor process to quantity the time-varying directed connectivity. The model enables a reliable, data-adaptive estimation of change-points of connectivity regimes and the massive dependencies associated with each regime. We develop a three-step estimation procedure: 1) extracting the factors using principal component analysis, 2) identifying connectivity regimes in a low-dimensional subspace based on the factor-based SVAR model, 3) constructing high-dimensional state connectivity metrics based on the subspace estimates. Simulation results show that our estimator outperforms K-means clustering of time-windowed coefficients, providing more accurate estimate of time-evolving connectivity. It achieves percentage of reduction in mean squared error by 60% when the network dimension is comparable to the sample size. When applied to resting-state fMRI data, our method successfully identifies modular organization in resting-state networks in consistency with other studies. It further reveals changes in brain states with variations across subjects and distinct large-scale directed connectivity patterns across states.

Cortical processing of pitch: Model-based encoding and decoding of auditory fMRI responses to real-life sounds.

Science.gov (United States)

De Angelis, Vittoria; De Martino, Federico; Moerel, Michelle; Santoro, Roberta; Hausfeld, Lars; Formisano, Elia

2017-11-13

Pitch is a perceptual attribute related to the fundamental frequency (or periodicity) of a sound. So far, the cortical processing of pitch has been investigated mostly using synthetic sounds. However, the complex harmonic structure of natural sounds may require different mechanisms for the extraction and analysis of pitch. This study investigated the neural representation of pitch in human auditory cortex using model-based encoding and decoding analyses of high field (7 T) functional magnetic resonance imaging (fMRI) data collected while participants listened to a wide range of real-life sounds. Specifically, we modeled the fMRI responses as a function of the sounds' perceived pitch height and salience (related to the fundamental frequency and the harmonic structure respectively), which we estimated with a computational algorithm of pitch extraction (de Cheveigné and Kawahara, 2002). First, using single-voxel fMRI encoding, we identified a pitch-coding region in the antero-lateral Heschl's gyrus (HG) and adjacent superior temporal gyrus (STG). In these regions, the pitch representation model combining height and salience predicted the fMRI responses comparatively better than other models of acoustic processing and, in the right hemisphere, better than pitch representations based on height/salience alone. Second, we assessed with model-based decoding that multi-voxel response patterns of the identified regions are more informative of perceived pitch than the remainder of the auditory cortex. Further multivariate analyses showed that complementing a multi-resolution spectro-temporal sound representation with pitch produces a small but significant improvement to the decoding of complex sounds from fMRI response patterns. In sum, this work extends model-based fMRI encoding and decoding methods - previously employed to examine the representation and processing of acoustic sound features in the human auditory system - to the representation and processing of a relevant

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

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Sutterer, Matthew J; Tranel, Daniel

2017-11-01

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

Improving language mapping in clinical fMRI through assessment of grammar.

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

2017-01-01

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

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

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

2016-01-01

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

An fMRI study

Indian Academy of Sciences (India)

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

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

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

2012-01-01

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

fMRI study of language activation in schizophrenia, schizoaffective disorder and in individuals genetically at high risk.

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Li, Xiaobo; Branch, Craig A; Ardekani, Babak A; Bertisch, Hilary; Hicks, Chindo; DeLisi, Lynn E

2007-11-01

Structural and functional abnormalities have been found in language-related brain regions in patients with schizophrenia. We previously reported findings pointing to differences in word processing between people with schizophrenia and individuals who are at high-risk for schizophrenia using a voxel-based (whole brain) fMRI approach. We now extend this finding to specifically examine functional activity in three language related cortical regions using a larger cohort of individuals. A visual lexical discrimination task was performed by 36 controls, 21 subjects at high genetic-risk for schizophrenia, and 20 patients with schizophrenia during blood oxygenation level dependent (BOLD) fMRI scanning. Activation in bilateral inferior frontal gyri (Brodmann's area 44-45), bilateral inferior parietal lobe (Brodmann's area 39-40), and bilateral superior temporal gyri (Brodmann's area 22) was investigated. For all subjects, two-tailed Pearson correlations were calculated between the computed laterality index and a series of cognitive test scores determining language functioning. Regional activation in Brodmann's area 44-45 was left lateralized in normal controls, while high-risk subjects and patients with schizophrenia or schizoaffective disorder showed more bilateral activation. No significant differences among the three diagnostic groups in the other two regions of interest (Brodmann's area 22 or areas 39-40) were found. Furthermore, the apparent reasons for loss of leftward language lateralization differed between groups. In high-risk subjects, the loss of lateralization was based on reduced left hemisphere activation, while in the patient group, it was due to increased right side activation. Language ability related cognitive scores were positively correlations with the laterality indices obtained from Brodmann's areas 44-45 in the high-risk group, and with the laterality indices from Brodmann's areas 22 and 44-45 in the patient group. This study reinforces previous

High-field proton MRS of human brain

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Di Costanzo, Alfonso E-mail: alfonso.dicostanzo@unina2.it; Trojsi, F.; Tosetti, M.; Giannatempo, G.M.; Nemore, F.; Piccirillo, M.; Bonavita, S.; Tedeschi, G.; Scarabino, T

2003-11-01

Proton magnetic resonance spectroscopy ({sup 1}H-MRS) of the brain reveals specific biochemical information about cerebral metabolites, which may support clinical diagnoses and enhance the understanding of neurological disorders. The advantages of performing {sup 1}H-MRS at higher field strengths include better signal to noise ratio (SNR) and increased spectral, spatial and temporal resolution, allowing the acquisition of high quality, easily quantifiable spectra in acceptable imaging times. In addition to improved measurement precision of N-acetylaspartate, choline, creatine and myo-inositol, high-field systems allow the high-resolution measurement of other metabolites, such as glutamate, glutamine, {gamma}-aminobutyric acid, scyllo-inositol, aspartate, taurine, N-acetylaspartylglutamate, glucose and branched amino acids, thus extending the range of metabolic information. However, these advantages may be hampered by intrinsic field-dependent technical difficulties, such as decreased T2 signal, chemical shift dispersion errors, J-modulation anomalies, increased magnetic susceptibility, eddy current artifacts, limitations in the design of homogeneous and sensitive radiofrequency (RF) coils, magnetic field instability and safety issues. Several studies demonstrated that these limitations could be overcome, suggesting that the appropriate optimization of high-field {sup 1}H-MRS would expand the application in the fields of clinical research and diagnostic routine.

Advances in fMRI Real-Time Neurofeedback.

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

2017-12-01

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

Impaired risk evaluation in people with Internet gaming disorder: fMRI evidence from a probability discounting task.

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Lin, Xiao; Zhou, Hongli; Dong, Guangheng; Du, Xiaoxia

2015-01-02

This study examined how Internet gaming disorder (IGD) subjects modulating reward and risk at a neural level under a probability-discounting task with functional magnetic resonance imaging (fMRI). Behavioral and imaging data were collected from 19 IGD subjects (22.2 ± 3.08 years) and 21 healthy controls (HC, 22.8 ± 3.5 years). Behavior results showed that IGD subjects prefer the probabilistic options to fixed ones and were associated with shorter reaction time, when comparing to HC. The fMRI results revealed that IGD subjects show decreased activation in the inferior frontal gyrus and the precentral gyrus when choosing the probabilistic options than HC. Correlations were also calculated between behavioral performances and brain activities in relevant brain regions. Both of the behavioral performance and fMRI results indicate that people with IGD show impaired risk evaluation, which might be the reason why IGD subjects continue playing online games despite the risks of widely known negative consequence. Copyright © 2014 Elsevier Inc. All rights reserved.

EEG-Informed fMRI: A Review of Data Analysis Methods

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Abreu, Rodolfo; Leal, Alberto; Figueiredo, Patrícia

2018-01-01

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

EEG-Informed fMRI: A Review of Data Analysis Methods

Directory of Open Access Journals (Sweden)

Rodolfo Abreu

2018-02-01

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

fMRI activation patterns in an analytic reasoning task: consistency with EEG source localization

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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.

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.

Modality Specific Cerebro-Cerebellar Activations in Verbal Working Memory: An fMRI Study

Science.gov (United States)

Kirschen, Matthew P.; Chen, S. H. Annabel; Desmond, John E.

2010-01-01

Verbal working memory (VWM) engages frontal and temporal/parietal circuits subserving the phonological loop, as well as, superior and inferior cerebellar regions which have projections from these neocortical areas. Different cerebro-cerebellar circuits may be engaged for integrating aurally- and visually-presented information for VWM. The present fMRI study investigated load (2, 4, or 6 letters) and modality (auditory and visual) dependent cerebro-cerebellar VWM activation using a Sternberg task. FMRI revealed modality-independent activations in left frontal (BA 6/9/44), insular, cingulate (BA 32), and bilateral inferior parietal/supramarginal (BA 40) regions, as well as in bilateral superior (HVI) and right inferior (HVIII) cerebellar regions. Visual presentation evoked prominent activations in right superior (HVI/CrusI) cerebellum, bilateral occipital (BA19) and left parietal (BA7/40) cortex while auditory presentation showed robust activations predominately in bilateral temporal regions (BA21/22). In the cerebellum, we noted a visual to auditory emphasis of function progressing from superior to inferior and from lateral to medial regions. These results extend our previous findings of fMRI activation in cerebro-cerebellar networks during VWM, and demonstrate both modality dependent commonalities and differences in activations with increasing memory load. PMID:20714061

Monkey cortex through fMRI glasses.

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

2014-08-06

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

Improving fMRI reliability in presurgical mapping for brain tumours.

Science.gov (United States)

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

2016-03-01

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

Diversity of sharp-wave–ripple LFP signatures reveals differentiated brain-wide dynamical events

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Ramirez-Villegas, Juan F.; Logothetis, Nikos K.; Besserve, Michel

2015-01-01

Sharp-wave–ripple (SPW-R) complexes are believed to mediate memory reactivation, transfer, and consolidation. However, their underlying neuronal dynamics at multiple scales remains poorly understood. Using concurrent hippocampal local field potential (LFP) recordings and functional MRI (fMRI), we study local changes in neuronal activity during SPW-R episodes and their brain-wide correlates. Analysis of the temporal alignment between SPW and ripple components reveals well-differentiated SPW-R subtypes in the CA1 LFP. SPW-R–triggered fMRI maps show that ripples aligned to the positive peak of their SPWs have enhanced neocortical metabolic up-regulation. In contrast, ripples occurring at the trough of their SPWs relate to weaker neocortical up-regulation and absent subcortical down-regulation, indicating differentiated involvement of neuromodulatory pathways in the ripple phenomenon mediated by long-range interactions. To our knowledge, this study provides the first evidence for the existence of SPW-R subtypes with differentiated CA1 activity and metabolic correlates in related brain areas, possibly serving different memory functions. PMID:26540729

Diversity of sharp-wave-ripple LFP signatures reveals differentiated brain-wide dynamical events.

Science.gov (United States)

Ramirez-Villegas, Juan F; Logothetis, Nikos K; Besserve, Michel

2015-11-17

Sharp-wave-ripple (SPW-R) complexes are believed to mediate memory reactivation, transfer, and consolidation. However, their underlying neuronal dynamics at multiple scales remains poorly understood. Using concurrent hippocampal local field potential (LFP) recordings and functional MRI (fMRI), we study local changes in neuronal activity during SPW-R episodes and their brain-wide correlates. Analysis of the temporal alignment between SPW and ripple components reveals well-differentiated SPW-R subtypes in the CA1 LFP. SPW-R-triggered fMRI maps show that ripples aligned to the positive peak of their SPWs have enhanced neocortical metabolic up-regulation. In contrast, ripples occurring at the trough of their SPWs relate to weaker neocortical up-regulation and absent subcortical down-regulation, indicating differentiated involvement of neuromodulatory pathways in the ripple phenomenon mediated by long-range interactions. To our knowledge, this study provides the first evidence for the existence of SPW-R subtypes with differentiated CA1 activity and metabolic correlates in related brain areas, possibly serving different memory functions.

Spatially adaptive mixture modeling for analysis of FMRI time series.

Science.gov (United States)

Vincent, Thomas; Risser, Laurent; Ciuciu, Philippe

2010-04-01

Within-subject analysis in fMRI essentially addresses two problems, the detection of brain regions eliciting evoked activity and the estimation of the underlying dynamics. In Makni et aL, 2005 and Makni et aL, 2008, a detection-estimation framework has been proposed to tackle these problems jointly, since they are connected to one another. In the Bayesian formalism, detection is achieved by modeling activating and nonactivating voxels through independent mixture models (IMM) within each region while hemodynamic response estimation is performed at a regional scale in a nonparametric way. Instead of IMMs, in this paper we take advantage of spatial mixture models (SMM) for their nonlinear spatial regularizing properties. The proposed method is unsupervised and spatially adaptive in the sense that the amount of spatial correlation is automatically tuned from the data and this setting automatically varies across brain regions. In addition, the level of regularization is specific to each experimental condition since both the signal-to-noise ratio and the activation pattern may vary across stimulus types in a given brain region. These aspects require the precise estimation of multiple partition functions of underlying Ising fields. This is addressed efficiently using first path sampling for a small subset of fields and then using a recently developed fast extrapolation technique for the large remaining set. Simulation results emphasize that detection relying on supervised SMM outperforms its IMM counterpart and that unsupervised spatial mixture models achieve similar results without any hand-tuning of the correlation parameter. On real datasets, the gain is illustrated in a localizer fMRI experiment: brain activations appear more spatially resolved using SMM in comparison with classical general linear model (GLM)-based approaches, while estimating a specific parcel-based HRF shape. Our approach therefore validates the treatment of unsmoothed fMRI data without fixed GLM

Recording visual evoked potentials and auditory evoked P300 at 9.4T static magnetic field.

Science.gov (United States)

Arrubla, Jorge; Neuner, Irene; Hahn, David; Boers, Frank; Shah, N Jon

2013-01-01

Simultaneous recording of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) has shown a number of advantages that make this multimodal technique superior to fMRI alone. The feasibility of recording EEG at ultra-high static magnetic field up to 9.4 T was recently demonstrated and promises to be implemented soon in fMRI studies at ultra high magnetic fields. Recording visual evoked potentials are expected to be amongst the most simple for simultaneous EEG/fMRI at ultra-high magnetic field due to the easy assessment of the visual cortex. Auditory evoked P300 measurements are of interest since it is believed that they represent the earliest stage of cognitive processing. In this study, we investigate the feasibility of recording visual evoked potentials and auditory evoked P300 in a 9.4 T static magnetic field. For this purpose, EEG data were recorded from 26 healthy volunteers inside a 9.4 T MR scanner using a 32-channel MR compatible EEG system. Visual stimulation and auditory oddball paradigm were presented in order to elicit evoked related potentials (ERP). Recordings made outside the scanner were performed using the same stimuli and EEG system for comparison purposes. We were able to retrieve visual P100 and auditory P300 evoked potentials at 9.4 T static magnetic field after correction of the ballistocardiogram artefact using independent component analysis. The latencies of the ERPs recorded at 9.4 T were not different from those recorded at 0 T. The amplitudes of ERPs were higher at 9.4 T when compared to recordings at 0 T. Nevertheless, it seems that the increased amplitudes of the ERPs are due to the effect of the ultra-high field on the EEG recording system rather than alteration in the intrinsic processes that generate the electrophysiological responses.

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

Directory of Open Access Journals (Sweden)

Sarah E. Morgan

2018-06-01

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

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

International Nuclear Information System (INIS)

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

2007-01-01

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

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.)

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

Science.gov (United States)

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

2015-08-30

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

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

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Wen, Haiguang; Liu, Zhongming

2016-06-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2007-10-15

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

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

International Nuclear Information System (INIS)

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

2007-01-01

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

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

International Nuclear Information System (INIS)

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

2009-01-01

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

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

Science.gov (United States)

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

2017-12-01

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

Activation Detection in fMRI Using Jeffrey Divergence

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Seghouane, Abd-Krim

2009-12-01

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

Statistical Analysis Methods for the fMRI Data

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Huseyin Boyaci

2011-08-01

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

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

Science.gov (United States)

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

2013-01-01

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

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

Directory of Open Access Journals (Sweden)

João R Sato

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

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

Science.gov (United States)

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

2013-01-01

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

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.

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

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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.

Acoustic fMRI noise : Linear time-invariant system model

NARCIS (Netherlands)

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

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

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

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

2011-01-01

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

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.

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.

Generative embedding for model-based classification of fMRI data.

Directory of Open Access Journals (Sweden)

Kay H Brodersen

2011-06-01

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

Coping with Self-Threat and the Evaluation of Self-Related Traits: An fMRI Study.

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Andreas Hoefler

Full Text Available A positive view of oneself is important for a healthy lifestyle. Self-protection mechanisms such as suppressing negative self-related information help us to maintain a positive view of ourselves. This is of special relevance when, for instance, a negative test result threatens our positive self-view. To date, it is not clear which brain areas support self-protective mechanisms under self-threat. In the present functional magnetic resonance imaging (fMRI study the participants (N = 46 received a (negative vs. positive performance test feedback before entering the scanner. In the scanner, the participants were instructed to ascribe personality traits either to themselves or to a famous other. Our results showed that participants responded slower to negative self-related traits compared to positive self-related traits. High self-esteem individuals responded slower to negative traits compared to low self-esteem individuals following a self-threat. This indicates that high self-esteem individuals engage more in self-enhancing strategies after a threat by inhibiting negative self-related information more successfully than low self-esteem individuals. This behavioral pattern was mirrored in the fMRI data as dACC correlated positively with trait self-esteem. Generally, ACC activation was attenuated under threat when participants evaluated self-relevant traits and even more for negative self-related traits. We also found that activation in the ACC was negatively correlated with response times, indicating that greater activation of the ACC is linked to better access (faster response to positive self-related traits and to impaired access (slower response to negative self-related traits. These results confirm the ACC function as important in managing threatened self-worth but indicate differences in trait self-esteem levels. The fMRI analyses also revealed a decrease in activation within the left Hippocampus and the right thalamus under threat. This

Coping with Self-Threat and the Evaluation of Self-Related Traits: An fMRI Study

Science.gov (United States)

Corcoran, Katja; Ebner, Franz

2015-01-01

A positive view of oneself is important for a healthy lifestyle. Self-protection mechanisms such as suppressing negative self-related information help us to maintain a positive view of ourselves. This is of special relevance when, for instance, a negative test result threatens our positive self-view. To date, it is not clear which brain areas support self-protective mechanisms under self-threat. In the present functional magnetic resonance imaging (fMRI) study the participants (N = 46) received a (negative vs. positive) performance test feedback before entering the scanner. In the scanner, the participants were instructed to ascribe personality traits either to themselves or to a famous other. Our results showed that participants responded slower to negative self-related traits compared to positive self-related traits. High self-esteem individuals responded slower to negative traits compared to low self-esteem individuals following a self-threat. This indicates that high self-esteem individuals engage more in self-enhancing strategies after a threat by inhibiting negative self-related information more successfully than low self-esteem individuals. This behavioral pattern was mirrored in the fMRI data as dACC correlated positively with trait self-esteem. Generally, ACC activation was attenuated under threat when participants evaluated self-relevant traits and even more for negative self-related traits. We also found that activation in the ACC was negatively correlated with response times, indicating that greater activation of the ACC is linked to better access (faster response) to positive self-related traits and to impaired access (slower response) to negative self-related traits. These results confirm the ACC function as important in managing threatened self-worth but indicate differences in trait self-esteem levels. The fMRI analyses also revealed a decrease in activation within the left Hippocampus and the right thalamus under threat. This indicates that a down

Investigating Inhibitory Control in Children with Epilepsy: An fMRI Study

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

2014-01-01

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

Neural mechanisms of the mind, Aristotle, Zadeh, and fMRI.

Science.gov (United States)

Perlovsky, Leonid I

2010-05-01

Processes in the mind: perception, cognition, concepts, instincts, emotions, and higher cognitive abilities for abstract thinking, beautiful music are considered here within a neural modeling fields (NMFs) paradigm. Its fundamental mathematical mechanism is a process "from vague-fuzzy to crisp," called dynamic logic (DL). This paper discusses why this paradigm is necessary mathematically, and relates it to a psychological description of the mind. Surprisingly, the process from "vague to crisp" corresponds to Aristotelian understanding of mental functioning. Recent functional magnetic resonance imaging (fMRI) measurements confirmed this process in neural mechanisms of perception.

The compensatory dynamic of inter-hemispheric interactions in visuospatial attention revealed using rTMS and fMRI

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Ela B Plow

2014-04-01

Full Text Available A balance of mutual tonic inhibition between bi-hemispheric posterior parietal cortices is believed to play an important role in bilateral visual attention. However, experimental support for this notion has been mainly drawn from clinical models of unilateral damage. We have previously shown that low-frequency repetitive TMS (rTMS over the intraparietal sulcus (IPS generates a contralateral attentional deficit in bilateral visual tracking. Here, we used functional Magnetic Resonance Imaging (fMRI to study whether rTMS temporarily disrupts the inter-hemispheric balance between bilateral IPS in visual attention. Following application of 1 Hz rTMS over the left IPS, subjects performed a bilateral visual tracking task while their brain activity was recorded using fMRI. Behaviorally, tracking accuracy was reduced immediately following rTMS. Areas ventro-lateral to left IPS, including inferior parietal lobule (IPL, lateral IPS (LIPS, and middle occipital gyrus (MoG, showed decreased activity following rTMS, while dorsomedial areas, such as Superior Parietal Lobule (SPL, Superior occipital gyrus (SoG, and lingual gyrus, as well as middle temporal areas (MT+, showed higher activity. The brain activity of the homologues of these regions in the un-stimulated, right hemisphere was reversed. Interestingly, the evolution of network-wide activation related to attentional behavior following rTMS showed that activation of most occipital synergists adaptively compensated for contralateral and ipsilateral decrement after rTMS, but that of parietal synergists, and SoG remained competing. This pattern of ipsilateral and contralateral activations empirically supports the hypothesized loss of inter-hemispheric balance that underlies clinical manifestation of visual attentional extinction.

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

International Nuclear Information System (INIS)

Hayashi, Toshihiro

2011-01-01

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

Spatial and object-based attention modulates broadband high-frequency responses across the human visual cortical hierarchy.

Science.gov (United States)

Davidesco, Ido; Harel, Michal; Ramot, Michal; Kramer, Uri; Kipervasser, Svetlana; Andelman, Fani; Neufeld, Miri Y; Goelman, Gadi; Fried, Itzhak; Malach, Rafael

2013-01-16

One of the puzzling aspects in the visual attention literature is the discrepancy between electrophysiological and fMRI findings: whereas fMRI studies reveal strong attentional modulation in the earliest visual areas, single-unit and local field potential studies yielded mixed results. In addition, it is not clear to what extent spatial attention effects extend from early to high-order visual areas. Here we addressed these issues using electrocorticography recordings in epileptic patients. The patients performed a task that allowed simultaneous manipulation of both spatial and object-based attention. They were presented with composite stimuli, consisting of a small object (face or house) superimposed on a large one, and in separate blocks, were instructed to attend one of the objects. We found a consistent increase in broadband high-frequency (30-90 Hz) power, but not in visual evoked potentials, associated with spatial attention starting with V1/V2 and continuing throughout the visual hierarchy. The magnitude of the attentional modulation was correlated with the spatial selectivity of each electrode and its distance from the occipital pole. Interestingly, the latency of the attentional modulation showed a significant decrease along the visual hierarchy. In addition, electrodes placed over high-order visual areas (e.g., fusiform gyrus) showed both effects of spatial and object-based attention. Overall, our results help to reconcile previous observations of discrepancy between fMRI and electrophysiology. They also imply that spatial attention effects can be found both in early and high-order visual cortical areas, in parallel with their stimulus tuning properties.

Functional brain segmentation using inter-subject correlation in fMRI.

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

2017-05-01

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

Orchestrating Proactive and Reactive Mechanisms for Filtering Distracting Information: Brain-Behavior Relationships Revealed by a Mixed-Design fMRI Study

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Marini, Francesco; Demeter, Elise; Roberts, Kenneth C.; Chelazzi, Leonardo

2016-01-01

Given the information overload often imparted to human cognitive-processing systems, suppression of irrelevant and distracting information is essential for successful behavior. Using a hybrid block/event-related fMRI design, we characterized proactive and reactive brain mechanisms for filtering distracting stimuli. Participants performed a flanker task, discriminating the direction of a target arrow in the presence versus absence of congruent or incongruent flanking distracting arrows during either Pure blocks (distracters always absent) or Mixed blocks (distracters on 80% of trials). Each Mixed block had either 20% or 60% incongruent trials. Activations in the dorsal frontoparietal attention network during Mixed versus Pure blocks evidenced proactive (blockwise) recruitment of a distraction-filtering mechanism. Sustained activations in right middle frontal gyrus during 60% Incongruent blocks correlated positively with behavioral indices of distraction-filtering (slowing when distracters might occur) and negatively with distraction-related behavioral costs (incongruent vs congruent trials), suggesting a role in coordinating proactive filtering of potential distracters. Event-related analyses showed that incongruent trials elicited greater reactive activations in 20% (vs 60%) Incongruent blocks for counteracting distraction and conflict, including in the insula and anterior cingulate. Context-related effects in occipitoparietal cortex consisted of greater target-evoked activations for distracter-absent trials (central-target-only) in Mixed versus Pure blocks, suggesting enhanced attentional engagement. Functional-localizer analyses in V1/V2/V3 revealed less distracter-processing activity in 60% (vs 20%) Incongruent blocks, presumably reflecting tonic suppression by proactive filtering mechanisms. These results delineate brain mechanisms underlying proactive and reactive filtering of distraction and conflict, and how they are orchestrated depending on distraction

Functional magnetic resonance imaging with ultra-high fields; Funktionelle Magnetresonanztomographie bei ultrahohen Feldern

Energy Technology Data Exchange (ETDEWEB)

Windischberger, C.; Schoepf, V.; Sladky, R.; Moser, E. [Medizinische Universitaet Wien, Exzellenzzentrum Hochfeld-MR, Wien (Austria); Medizinische Universitaet Wien, Zentrum fuer Medizinische Physik und Biomedizinische Technik, Wien (Austria); Fischmeister, F.P.S. [Medizinische Universitaet Wien, Exzellenzzentrum Hochfeld-MR, Wien (Austria); Universitaet Wien, Fakultaet fuer Psychologie, Wien (Austria)

2010-02-15

Functional magnetic resonance imaging (fMRI) is currently the primary method for non-invasive functional localization in the brain. With the emergence of MR systems with field strengths of 4 Tesla and above, neuronal activation may be studied with unprecedented accuracy. In this article we present different approaches to use the improved sensitivity and specificity for expanding current fMRT resolution limits in space and time based on several 7 Tesla studies. In addition to the challenges that arise with ultra-high magnetic fields possible solutions will be discussed. (orig.) [German] Die funktionelle Magnetresonanztomographie (fMRT) stellt zurzeit die wichtigste Methode zur nichtinvasiven Funktionslokalisation im Gehirn dar. Mit der Verfuegbarkeit von MRT-Geraeten mit Magnetfeldstaerken von 4 Tesla (T) und darueber ergeben sich neue Moeglichkeiten, mittels fMRT die neuronale Aktivitaet in bislang unerreichter Genauigkeit zu untersuchen. In diesem Artikel zeigen wir anhand mehrerer Studien bei 7 T, in wieweit die Zugewinne an Sensitivitaet und Spezifitaet verwendet werden koennen, um die bisherigen Grenzen der fMRT-Aufloesung in raeumlicher und zeitlicher Hinsicht auszuweiten. Die neuen Herausforderungen, die mit dem Schritt zu ultrahohen Magnetfeldern einhergehen, werden dabei ebenso diskutiert wie moegliche Ansaetze zu deren Loesung. (orig.)

FMRI activity during associative encoding is correlated with cardiorespiratory fitness and source memory performance in older adults

Science.gov (United States)

Hayes, Scott M.; Hayes, Jasmeet P.; Williams, Victoria J.; Liu, Huiting; Verfaellie, Mieke

2017-01-01

Older adults (OA), relative to young adults (YA), exhibit age-related alterations in functional Magnetic Resonance Imaging (fMRI) activity during associative encoding, which contributes to deficits in source memory. Yet, there are remarkable individual differences in brain health and memory performance among OA. Cardiorespiratory fitness (CRF) is one individual difference factor that may attenuate brain aging, and thereby contribute to enhanced source memory in OA. To examine this possibility, 26 OA and 31 YA completed a treadmill-based exercise test to evaluate CRF (peak VO2) and fMRI to examine brain activation during a face-name associative encoding task. Our results indicated that in OA, peak VO2 was positively associated with fMRI activity during associative encoding in multiple regions including bilateral prefrontal cortex, medial frontal cortex, bilateral thalamus and left hippocampus. Next, a conjunction analysis was conducted to assess whether CRF influenced age-related differences in fMRI activation. We classified OA as high or low CRF and compared their activation to YA. High fit OA (HFOA) showed fMRI activation more similar to YA than low fit OA (LFOA) (i.e., reduced age-related differences) in multiple regions including thalamus, posterior and prefrontal cortex. Conversely, in other regions, primarily in prefrontal cortex, HFOA, but not LFOA, demonstrated greater activation than YA (i.e., increased age-related differences). Further, fMRI activity in these brain regions was positively associated with source memory among OA, with a mediation model demonstrating that associative encoding activation in medial frontal cortex indirectly influenced the relationship between peak VO2 and subsequent source memory performance. These results indicate that CRF may contribute to neuroplasticity among OA, reducing age-related differences in some brain regions, consistent with the brain maintenance hypothesis, but accentuating age-differences in other regions

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

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

2018-02-27

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

Human fMRI reveals that delayed action re-recruits visual perception.

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Singhal, Anthony; Monaco, Simona; Kaufman, Liam D; Culham, Jody C

2013-01-01

Behavioral and neuropsychological research suggests that delayed actions rely on different neural substrates than immediate actions; however, the specific brain areas implicated in the two types of actions remain unknown. We used functional magnetic resonance imaging (fMRI) to measure human brain activation during delayed grasping and reaching. Specifically, we examined activation during visual stimulation and action execution separated by a 18-s delay interval in which subjects had to remember an intended action toward the remembered object. The long delay interval enabled us to unambiguously distinguish visual, memory-related, and action responses. Most strikingly, we observed reactivation of the lateral occipital complex (LOC), a ventral-stream area implicated in visual object recognition, and early visual cortex (EVC) at the time of action. Importantly this reactivation was observed even though participants remained in complete darkness with no visual stimulation at the time of the action. Moreover, within EVC, higher activation was observed for grasping than reaching during both vision and action execution. Areas in the dorsal visual stream were activated during action execution as expected and, for some, also during vision. Several areas, including the anterior intraparietal sulcus (aIPS), dorsal premotor cortex (PMd), primary motor cortex (M1) and the supplementary motor area (SMA), showed sustained activation during the delay phase. We propose that during delayed actions, dorsal-stream areas plan and maintain coarse action goals; however, at the time of execution, motor programming requires re-recruitment of detailed visual information about the object through reactivation of (1) ventral-stream areas involved in object perception and (2) early visual areas that contain richly detailed visual representations, particularly for grasping.

Human fMRI reveals that delayed action re-recruits visual perception.

Directory of Open Access Journals (Sweden)

Anthony Singhal

Full Text Available Behavioral and neuropsychological research suggests that delayed actions rely on different neural substrates than immediate actions; however, the specific brain areas implicated in the two types of actions remain unknown. We used functional magnetic resonance imaging (fMRI to measure human brain activation during delayed grasping and reaching. Specifically, we examined activation during visual stimulation and action execution separated by a 18-s delay interval in which subjects had to remember an intended action toward the remembered object. The long delay interval enabled us to unambiguously distinguish visual, memory-related, and action responses. Most strikingly, we observed reactivation of the lateral occipital complex (LOC, a ventral-stream area implicated in visual object recognition, and early visual cortex (EVC at the time of action. Importantly this reactivation was observed even though participants remained in complete darkness with no visual stimulation at the time of the action. Moreover, within EVC, higher activation was observed for grasping than reaching during both vision and action execution. Areas in the dorsal visual stream were activated during action execution as expected and, for some, also during vision. Several areas, including the anterior intraparietal sulcus (aIPS, dorsal premotor cortex (PMd, primary motor cortex (M1 and the supplementary motor area (SMA, showed sustained activation during the delay phase. We propose that during delayed actions, dorsal-stream areas plan and maintain coarse action goals; however, at the time of execution, motor programming requires re-recruitment of detailed visual information about the object through reactivation of (1 ventral-stream areas involved in object perception and (2 early visual areas that contain richly detailed visual representations, particularly for grasping.

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.

Toward brain correlates of natural behavior: fMRI during violent video games.

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Mathiak, Klaus; Weber, René

2006-12-01

Modern video games represent highly advanced virtual reality simulations and often contain virtual violence. In a significant amount of young males, playing video games is a quotidian activity, making it an almost natural behavior. Recordings of brain activation with functional magnetic resonance imaging (fMRI) during gameplay may reflect neuronal correlates of real-life behavior. We recorded 13 experienced gamers (18-26 years; average 14 hrs/week playing) while playing a violent first-person shooter game (a violent computer game played in self-perspective) by means of distortion and dephasing reduced fMRI (3 T; single-shot triple-echo echo-planar imaging [EPI]). Content analysis of the video and sound with 100 ms time resolution achieved relevant behavioral variables. These variables explained significant signal variance across large distributed networks. Occurrence of violent scenes revealed significant neuronal correlates in an event-related design. Activation of dorsal and deactivation of rostral anterior cingulate and amygdala characterized the mid-frontal pattern related to virtual violence. Statistics and effect sizes can be considered large at these areas. Optimized imaging strategies allowed for single-subject and for single-trial analysis with good image quality at basal brain structures. We propose that virtual environments can be used to study neuronal processes involved in semi-naturalistic behavior as determined by content analysis. Importantly, the activation pattern reflects brain-environment interactions rather than stimulus responses as observed in classical experimental designs. We relate our findings to the general discussion on social effects of playing first-person shooter games. (c) 2006 Wiley-Liss, Inc.

Mapping, Learning, Visualization, Classification, and Understanding of fMRI Data in the NeuCube Evolving Spatiotemporal Data Machine of Spiking Neural Networks.

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Kasabov, Nikola K; Doborjeh, Maryam Gholami; Doborjeh, Zohreh Gholami

2017-04-01

This paper introduces a new methodology for dynamic learning, visualization, and classification of functional magnetic resonance imaging (fMRI) as spatiotemporal brain data. The method is based on an evolving spatiotemporal data machine of evolving spiking neural networks (SNNs) exemplified by the NeuCube architecture [1]. The method consists of several steps: mapping spatial coordinates of fMRI data into a 3-D SNN cube (SNNc) that represents a brain template; input data transformation into trains of spikes; deep, unsupervised learning in the 3-D SNNc of spatiotemporal patterns from data; supervised learning in an evolving SNN classifier; parameter optimization; and 3-D visualization and model interpretation. Two benchmark case study problems and data are used to illustrate the proposed methodology-fMRI data collected from subjects when reading affirmative or negative sentences and another one-on reading a sentence or seeing a picture. The learned connections in the SNNc represent dynamic spatiotemporal relationships derived from the fMRI data. They can reveal new information about the brain functions under different conditions. The proposed methodology allows for the first time to analyze dynamic functional and structural connectivity of a learned SNN model from fMRI data. This can be used for a better understanding of brain activities and also for online generation of appropriate neurofeedback to subjects for improved brain functions. For example, in this paper, tracing the 3-D SNN model connectivity enabled us for the first time to capture prominent brain functional pathways evoked in language comprehension. We found stronger spatiotemporal interaction between left dorsolateral prefrontal cortex and left temporal while reading a negated sentence. This observation is obviously distinguishable from the patterns generated by either reading affirmative sentences or seeing pictures. The proposed NeuCube-based methodology offers also a superior classification accuracy

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

Science.gov (United States)

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

2008-01-01

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

Specificity of Esthetic Experience for Artworks: An fMRI Study

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Di Dio, Cinzia; Canessa, Nicola; Cappa, Stefano F.; Rizzolatti, Giacomo

2011-01-01

In a previous functional magnetic resonance imaging (fMRI) study, where we investigated the neural correlates of esthetic experience, we found that observing canonical sculptures, relative to sculptures whose proportions had been modified, produced the activation of a network that included the lateral occipital gyrus, precuneus, prefrontal areas, and, most interestingly, the right anterior insula. We interpreted this latter activation as the neural signature underpinning hedonic response during esthetic experience. With the aim of exploring whether this specific hedonic response is also present during the observation of non-art biological stimuli, in the present fMRI study we compared the activations associated with viewing masterpieces of classical sculpture with those produced by the observation of pictures of young athletes. The two stimulus-categories were matched on various factors, including body postures, proportion, and expressed dynamism. The stimuli were presented in two conditions: observation and esthetic judgment. The two stimulus-categories produced a rather similar global activation pattern. Direct comparisons between sculpture and real-body images revealed, however, relevant differences, among which the activation of right antero-dorsal insula during sculptures viewing only. Along with our previous data, this finding suggests that the hedonic state associated with activation of right dorsal anterior insula underpins esthetic experience for artworks. PMID:22121344

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

DEFF Research Database (Denmark)

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

2017-01-01

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

Effects of Field-Map Distortion Correction on Resting State Functional Connectivity MRI

Directory of Open Access Journals (Sweden)

Hiroki Togo

2017-12-01

Full Text Available Magnetic field inhomogeneities cause geometric distortions of echo planar images used for functional magnetic resonance imaging (fMRI. To reduce this problem, distortion correction (DC with field map is widely used for both task and resting-state fMRI (rs-fMRI. Although DC with field map has been reported to improve the quality of task fMRI, little is known about its effects on rs-fMRI. Here, we tested the influence of field-map DC on rs-fMRI results using two rs-fMRI datasets derived from 40 healthy subjects: one with DC (DC+ and the other without correction (DC−. Independent component analysis followed by the dual regression approach was used for evaluation of resting-state functional connectivity networks (RSN. We also obtained the ratio of low-frequency to high-frequency signal power (0.01–0.1 Hz and above 0.1 Hz, respectively; LFHF ratio to assess the quality of rs-fMRI signals. For comparison of RSN between DC+ and DC− datasets, the default mode network showed more robust functional connectivity in the DC+ dataset than the DC− dataset. Basal ganglia RSN showed some decreases in functional connectivity primarily in white matter, indicating imperfect registration/normalization without DC. Supplementary seed-based and simulation analyses supported the utility of DC. Furthermore, we found a higher LFHF ratio after field map correction in the anterior cingulate cortex, posterior cingulate cortex, ventral striatum, and cerebellum. In conclusion, field map DC improved detection of functional connectivity derived from low-frequency rs-fMRI signals. We encourage researchers to include a DC step in the preprocessing pipeline of rs-fMRI analysis.

Analysing E-Services and Mobile Applications with Companied Conjoint Analysis and fMRI Technique

OpenAIRE

Heinonen, Jarmo

2015-01-01

Previous research has shown that neuromarketing and conjoint analysis have been used in many areas of consumer research, and to provide for further understanding of consumer behaviour. Together these two methods may reveal more information about hidden desires, expectations and restrains of consumers’ brain. This paper attempts to examine these two research methods together as a companied analysis. More specifically this study utilizes fMRI and conjoint analysis is a tool for analysing consum...

Exploring neural dysfunction in 'clinical high risk' for psychosis: a quantitative review of fMRI studies.

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Dutt, Anirban; Tseng, Huai-Hsuan; Fonville, Leon; Drakesmith, Mark; Su, Liang; Evans, John; Zammit, Stanley; Jones, Derek; Lewis, Glyn; David, Anthony S

2015-02-01

Individuals at clinical high risk (CHR) of developing psychosis present with widespread functional abnormalities in the brain. Cognitive deficits, including working memory (WM) problems, as commonly elicited by n-back tasks, are observed in CHR individuals. However, functional MRI (fMRI) studies, comprising a heterogeneous cluster of general and social cognition paradigms, have not necessarily demonstrated consistent and conclusive results in this population. Hence, a comprehensive review of fMRI studies, spanning almost one decade, was carried out to observe for general trends with respect to brain regions and cognitive systems most likely to be dysfunctional in CHR individuals. 32 studies were included for this review, out of which 22 met the criteria for quantitative analysis using activation likelihood estimation (ALE). Task related contrast activations were firstly analysed by comparing CHR and healthy control participants in the total pooled sample, followed by a comparison of general cognitive function studies (excluding social cognition paradigms), and finally by only looking at n-back working memory task based studies. Findings from the ALE implicated four key dysfunctional and distinct neural regions in the CHR group, namely the right inferior parietal lobule (rIPL), the left medial frontal gyrus (lmFG), the left superior temporal gyrus (lSTG) and the right fronto-polar cortex (rFPC) of the superior frontal gyrus (SFG). Narrowing down to relatively few significant dysfunctional neural regions is a step forward in reducing the apparent ambiguity of overall findings, which would help to target specific neural regions and pathways of interest for future research in CHR populations. Copyright © 2014. Published by Elsevier Ltd.

High field MRI in the diagnosis of multiple sclerosis: high field-high yield?

International Nuclear Information System (INIS)

Wattjes, Mike P.; Barkhof, Frederik

2009-01-01

Following the approval of the U.S. Food and Drug Administration (FDA), high field magnetic resonance imaging (MRI) has been increasingly incorporated into the clinical setting. Especially in the field of neuroimaging, the number of high field MRI applications has been increased dramatically. Taking advantage on increased signal-to-noise ratio (SNR) and chemical shift, higher magnetic field strengths offer new perspectives particularly in brain imaging and also challenges in terms of several technical and physical consequences. Over the past few years, many applications of high field MRI in patients with suspected and definite multiple sclerosis (MS) have been reported including conventional and quantitative MRI methods. Conventional pulse sequences at 3 T offers higher lesion detection rates when compared to 1.5 T, particularly in anatomic regions which are important for the diagnosis of patients with MS. MR spectroscopy at 3 T is characterized by an improved spectral resolution due to increased chemical shift allowing a better quantification of metabolites. It detects significant axonal damage already in patients presenting with clinically isolated syndromes and can quantify metabolites of special interest such as glutamate which is technically difficult to quantify at lower field strengths. Furthermore, the higher susceptibility and SNR offer advantages in the field of functional MRI and diffusion tensor imaging. The recently introduced new generation of ultra-high field systems beyond 3 T allows scanning in submillimeter resolution and gives new insights into in vivo MS pathology on MRI. The objectives of this article are to review the current knowledge and level of evidence concerning the application of high field MRI in MS and to give some ideas of research perspectives in the future. (orig.)

Electrophysiological correlates of the BOLD signal for EEG-informed fMRI

Science.gov (United States)

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

2015-01-01

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

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

International Nuclear Information System (INIS)

Salagierska-Barwinska, A.; Goraj, B.

2004-01-01

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

Magnetoresistance peculiarities of bismuth wires in high magnetic field

Energy Technology Data Exchange (ETDEWEB)

Condrea, E., E-mail: condrea@nano.asm.md [Institute of Electronic Engineering and Nanotechnologies, Academy of Science of Moldova, 2028 Chisinau, Republic of Moldova (Moldova, Republic of); International Laboratory of High Magnetic Fields and Low Temperatures, Gajowicka 95, 51-421 Wroclaw (Poland); Gilewski, A. [International Laboratory of High Magnetic Fields and Low Temperatures, Gajowicka 95, 51-421 Wroclaw (Poland); MagNet, 50-421 Wroclaw (Poland); Nicorici, A. [Institute of Electronic Engineering and Nanotechnologies, Academy of Science of Moldova, 2028 Chisinau, Republic of Moldova (Moldova, Republic of)

2016-03-11

Magnetoresistance measurements of Bi wires performed in the magnetic field oriented along the bisector axis revealed unexpected anomalous peaks in a high magnetic field far above the quantum limit of the electrons. By combining a magnetic field and an uniaxial strain, we obtained a modification of the electronic structure; as a result, the quantum limit for light and heavy electrons is changed in a different way. For the case where heavy electrons are in the quantum limit, a correlation between the exit of the lowest Landau level of light electrons and the Lifshitz transition was found. - Highlights: • Glass-coated single-crystalline Bi wires attain high limit of elastic strain of up to 3.0%. • Selective modification of the electronic structure of Bi wires is obtained by combining a high magnetic field and uniaxial strain. • The correlation between the exit of the lowest Landau level of electrons and Lifshitz transition was found.

Magnetoresistance peculiarities of bismuth wires in high magnetic field

International Nuclear Information System (INIS)

Condrea, E.; Gilewski, A.; Nicorici, A.

2016-01-01

Magnetoresistance measurements of Bi wires performed in the magnetic field oriented along the bisector axis revealed unexpected anomalous peaks in a high magnetic field far above the quantum limit of the electrons. By combining a magnetic field and an uniaxial strain, we obtained a modification of the electronic structure; as a result, the quantum limit for light and heavy electrons is changed in a different way. For the case where heavy electrons are in the quantum limit, a correlation between the exit of the lowest Landau level of light electrons and the Lifshitz transition was found. - Highlights: • Glass-coated single-crystalline Bi wires attain high limit of elastic strain of up to 3.0%. • Selective modification of the electronic structure of Bi wires is obtained by combining a high magnetic field and uniaxial strain. • The correlation between the exit of the lowest Landau level of electrons and Lifshitz transition was found.

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

OpenAIRE

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

2015-01-01

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

Classification of autistic individuals and controls using cross-task characterization of fMRI activity

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Guillaume Chanel

2016-01-01

Full Text Available Multivariate pattern analysis (MVPA has been applied successfully to task-based and resting-based fMRI recordings to investigate which neural markers distinguish individuals with autistic spectrum disorders (ASD from controls. While most studies have focused on brain connectivity during resting state episodes and regions of interest approaches (ROI, a wealth of task-based fMRI datasets have been acquired in these populations in the last decade. This calls for techniques that can leverage information not only from a single dataset, but from several existing datasets that might share some common features and biomarkers. We propose a fully data-driven (voxel-based approach that we apply to two different fMRI experiments with social stimuli (faces and bodies. The method, based on Support Vector Machines (SVMs and Recursive Feature Elimination (RFE, is first trained for each experiment independently and each output is then combined to obtain a final classification output. Second, this RFE output is used to determine which voxels are most often selected for classification to generate maps of significant discriminative activity. Finally, to further explore the clinical validity of the approach, we correlate phenotypic information with obtained classifier scores. The results reveal good classification accuracy (range between 69% and 92.3%. Moreover, we were able to identify discriminative activity patterns pertaining to the social brain without relying on a priori ROI definitions. Finally, social motivation was the only dimension which correlated with classifier scores, suggesting that it is the main dimension captured by the classifiers. Altogether, we believe that the present RFE method proves to be efficient and may help identifying relevant biomarkers by taking advantage of acquired task-based fMRI datasets in psychiatric populations.

Classification of autistic individuals and controls using cross-task characterization of fMRI activity

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Chanel, Guillaume; Pichon, Swann; Conty, Laurence; Berthoz, Sylvie; Chevallier, Coralie; Grèzes, Julie

2015-01-01

Multivariate pattern analysis (MVPA) has been applied successfully to task-based and resting-based fMRI recordings to investigate which neural markers distinguish individuals with autistic spectrum disorders (ASD) from controls. While most studies have focused on brain connectivity during resting state episodes and regions of interest approaches (ROI), a wealth of task-based fMRI datasets have been acquired in these populations in the last decade. This calls for techniques that can leverage information not only from a single dataset, but from several existing datasets that might share some common features and biomarkers. We propose a fully data-driven (voxel-based) approach that we apply to two different fMRI experiments with social stimuli (faces and bodies). The method, based on Support Vector Machines (SVMs) and Recursive Feature Elimination (RFE), is first trained for each experiment independently and each output is then combined to obtain a final classification output. Second, this RFE output is used to determine which voxels are most often selected for classification to generate maps of significant discriminative activity. Finally, to further explore the clinical validity of the approach, we correlate phenotypic information with obtained classifier scores. The results reveal good classification accuracy (range between 69% and 92.3%). Moreover, we were able to identify discriminative activity patterns pertaining to the social brain without relying on a priori ROI definitions. Finally, social motivation was the only dimension which correlated with classifier scores, suggesting that it is the main dimension captured by the classifiers. Altogether, we believe that the present RFE method proves to be efficient and may help identifying relevant biomarkers by taking advantage of acquired task-based fMRI datasets in psychiatric populations. PMID:26793434

RETROSPECTIVE DETECTION OF INTERLEAVED SLICE ACQUISITION PARAMETERS FROM FMRI DATA

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Parker, David; Rotival, Georges; Laine, Andrew; Razlighi, Qolamreza R.

2015-01-01

To minimize slice excitation leakage to adjacent slices, interleaved slice acquisition is nowadays performed regularly in fMRI scanners. In interleaved slice acquisition, the number of slices skipped between two consecutive slice acquisitions is often referred to as the ‘interleave parameter’; the loss of this parameter can be catastrophic for the analysis of fMRI data. In this article we present a method to retrospectively detect the interleave parameter and the axis in which it is applied. Our method relies on the smoothness of the temporal-distance correlation function, which becomes disrupted along the axis on which interleaved slice acquisition is applied. We examined this method on simulated and real data in the presence of fMRI artifacts such as physiological noise, motion, etc. We also examined the reliability of this method in detecting different types of interleave parameters and demonstrated an accuracy of about 94% in more than 1000 real fMRI scans. PMID:26161244

Arterial Spin Labeling (ASL) fMRI: advantages, theoretical constrains, and experimental challenges in neurosciences.

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Borogovac, Ajna; Asllani, Iris

2012-01-01

Cerebral blood flow (CBF) is a well-established correlate of brain function and therefore an essential parameter for studying the brain at both normal and diseased states. Arterial spin labeling (ASL) is a noninvasive fMRI technique that uses arterial water as an endogenous tracer to measure CBF. ASL provides reliable absolute quantification of CBF with higher spatial and temporal resolution than other techniques. And yet, the routine application of ASL has been somewhat limited. In this review, we start by highlighting theoretical complexities and technical challenges of ASL fMRI for basic and clinical research. While underscoring the main advantages of ASL versus other techniques such as BOLD, we also expound on inherent challenges and confounds in ASL perfusion imaging. In closing, we expound on several exciting developments in the field that we believe will make ASL reach its full potential in neuroscience research.

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

OpenAIRE

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

2016-01-01

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

Real-Time Correction By Optical Tracking with Integrated Geometric Distortion Correction for Reducing Motion Artifacts in fMRI

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Rotenberg, David J.

Artifacts caused by head motion are a substantial source of error in fMRI that limits its use in neuroscience research and clinical settings. Real-time scan-plane correction by optical tracking has been shown to correct slice misalignment and non-linear spin-history artifacts, however residual artifacts due to dynamic magnetic field non-uniformity may remain in the data. A recently developed correction technique, PLACE, can correct for absolute geometric distortion using the complex image data from two EPI images, with slightly shifted k-space trajectories. We present a correction approach that integrates PLACE into a real-time scan-plane update system by optical tracking, applied to a tissue-equivalent phantom undergoing complex motion and an fMRI finger tapping experiment with overt head motion to induce dynamic field non-uniformity. Experiments suggest that including volume by volume geometric distortion correction by PLACE can suppress dynamic geometric distortion artifacts in a phantom and in vivo and provide more robust activation maps.

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

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

2018-06-08

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

Effects of anesthetic agents on brain blood oxygenation level revealed with ultra-high field MRI

International Nuclear Information System (INIS)

Ciobanu, Luisa; Reynaud, Olivier; Le Bihan, Denis; Uhrig, Lynn; Jarraya, Bechir

2012-01-01

During general anesthesia it is crucial to control systemic hemodynamics and oxygenation levels. However, anesthetic agents can affect cerebral hemodynamics and metabolism in a drug-dependent manner, while systemic hemodynamics is stable. Brain-wide monitoring of this effect remains highly challenging. Because T2'*-weighted imaging at ultra-high magnetic field strengths benefits from a dramatic increase in contrast to noise ratio, we hypothesized that it could monitor anesthesia effects on brain blood oxygenation. We scanned rat brains at 7 T and 17.2 T under general anesthesia using different anesthetics (isoflurane, ketamine-xylazine, medetomidine). We showed that the brain/vessels contrast in T2'*- weighted images at 17.2 T varied directly according to the applied pharmacological anesthetic agent, a phenomenon that was visible, but to a much smaller extent at 7 T. This variation is in agreement with the mechanism of action of these agents. These data demonstrate that preclinical ultra-high field MRI can monitor the effects of a given drug on brain blood oxygenation level in the absence of systemic blood oxygenation changes and of any neural stimulation. (authors)

Symmetry of fMRI activation in the primary sensorimotor cortex during unilateral chewing.

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Lotze, M; Domin, M; Kordass, B

2017-05-01

Functional magnetic resonance imaging (fMRI) is one of the most advanced techniques to analyze the cerebral effects on many behavior aspects of the oral system such as chewing and mastication. Studies on imaging of the cerebral representation of chewing demonstrated differential results with respect to cortical lateralization during unilateral chewing. The aim of our study is to clarify the effects of cerebral responses during unilateral chewing. We used fMRI to compare brain activities during occlusal function in centric occlusion on natural teeth and chewing on a gum located on the right or the left teeth in 15 healthy subjects. Group data were performed by Talairach normalization and in addition by an assignment of activation maxima to individual anatomical landmarks in order to avoid possible loss of spatial preciseness of activation sites by normalization procedures. Evaluation of group data by Talairach normalization revealed representation sites for occlusal movements in bilateral primary (S1) and secondary (S2) somatosensory cortices, primary motor (M1) and premotor cortices, supplementary motor area (SMA) and medial cingulate gyrus, bilateral anterior cerebellar hemispheres and vermis, insula, orbitofrontal cortex, thalamus, and left pallidum. Right-sided chewing showed no differential activation to left-sided chewing, and both showed activation in areas also involved in bilateral occlusion. Both techniques, the one based on group normalization and the one based on an individual evaluation method, revealed remarkable low differences in activation maximum location in the primary motor, the primary and secondary somatosensory cortices, and the anterior cerebellar lobe. All chewing movements tested involved bilateral sensorimotor activation without a significant lateralization of activation intensities. Overall, a general lateralization of occlusion movements to the dominant side could not be verified in the present study. Chewing on the left or on the right

Nonlinear complexity analysis of brain FMRI signals in schizophrenia.

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Moses O Sokunbi

Full Text Available We investigated the differences in brain fMRI signal complexity in patients with schizophrenia while performing the Cyberball social exclusion task, using measures of Sample entropy and Hurst exponent (H. 13 patients meeting diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM IV criteria for schizophrenia and 16 healthy controls underwent fMRI scanning at 1.5 T. The fMRI data of both groups of participants were pre-processed, the entropy characterized and the Hurst exponent extracted. Whole brain entropy and H maps of the groups were generated and analysed. The results after adjusting for age and sex differences together show that patients with schizophrenia exhibited higher complexity than healthy controls, at mean whole brain and regional levels. Also, both Sample entropy and Hurst exponent agree that patients with schizophrenia have more complex fMRI signals than healthy controls. These results suggest that schizophrenia is associated with more complex signal patterns when compared to healthy controls, supporting the increase in complexity hypothesis, where system complexity increases with age or disease, and also consistent with the notion that schizophrenia is characterised by a dysregulation of the nonlinear dynamics of underlying neuronal systems.

Ageing differentially affects neural processing of different conflict types-an fMRI study.

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Korsch, Margarethe; Frühholz, Sascha; Herrmann, Manfred

2014-01-01

Interference control and conflict resolution is affected by ageing. There is increasing evidence that ageing does not compromise interference control in general but rather shows distinctive effects on different components of interference control. Different conflict types, [e.g., stimulus-stimulus (S-S) or stimulus-response (S-R) conflicts] trigger different cognitive processes and thus activate different neural networks. In the present functional magnetic resonance imaging (fMRI) study, we used a combined Flanker and Stimulus Response Conflict (SRC) task to investigate the effect of ageing on S-S and S-R conflicts. Behavioral data analysis revealed larger SRC effects in elderly. fMRI Results show that both age groups recruited similar regions [caudate nucleus, cingulate gyrus and middle occipital gyrus (MOG)] during Flanker conflict processing. Furthermore, elderly show an additional activation pattern in parietal and frontal areas. In contrast, no common activation of both age groups was found in response to the SRC. These data suggest that ageing has distinctive effects on S-S and S-R conflicts.

Application of fMRI to obesity research: differences in reward pathway activation measured with fMRI BOLD during visual presentation of high and low calorie foods

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Tsao, Sinchai; Adam, Tanja C.; Goran, Michael I.; Singh, Manbir

2012-03-01

The factors behind the neural mechanisms that motivate food choice and obesity are not well known. Furthermore, it is not known when these neural mechanisms develop and how they are influenced by both genetic and environmental factors. This study uses fMRI together with clinical data to shed light on the aforementioned questions by investigating how appetite-related activation in the brain changes with low versus high caloric foods in pre-pubescent girls. Previous studies have shown that obese adults have less striatal D2 receptors and thus reduced Dopamine (DA) signaling leading to the reward-deficit theory of obesity. However, overeating in itself reduces D2 receptor density, D2 sensitivity and thus reward sensitivity. The results of this study will show how early these neural mechanisms develop and what effect the drastic endocrinological changes during puberty has on these mechanisms. Our preliminary results showed increased activations in the Putamen, Insula, Thalamus and Hippocampus when looking at activations where High Calorie > Low Calorie. When comparing High Calorie > Control and Low Calorie > Control, the High > Control test showed increased significant activation in the frontal lobe. The Low > Control also yielded significant activation in the Left and Right Fusiform Gyrus, which did not appear in the High > Control test. These results indicate that the reward pathway activations previously shown in post-puberty and adults are present in pre-pubescent teens. These results may suggest that some of the preferential neural mechanisms of reward are already present pre-puberty.

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

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

2014-01-01

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

Magnetoresistance peculiarities of bismuth wires in high magnetic field

Science.gov (United States)

Condrea, E.; Gilewski, A.; Nicorici, A.

2016-03-01

Magnetoresistance measurements of Bi wires performed in the magnetic field oriented along the bisector axis revealed unexpected anomalous peaks in a high magnetic field far above the quantum limit of the electrons. By combining a magnetic field and an uniaxial strain, we obtained a modification of the electronic structure; as a result, the quantum limit for light and heavy electrons is changed in a different way. For the case where heavy electrons are in the quantum limit, a correlation between the exit of the lowest Landau level of light electrons and the Lifshitz transition was found.

Spatio-temporal models of mental processes from fMRI.

Science.gov (United States)

Janoos, Firdaus; Machiraju, Raghu; Singh, Shantanu; Morocz, Istvan Ákos

2011-07-15

Understanding the highly complex, spatially distributed and temporally organized phenomena entailed by mental processes using functional MRI is an important research problem in cognitive and clinical neuroscience. Conventional analysis methods focus on the spatial dimension of the data discarding the information about brain function contained in the temporal dimension. This paper presents a fully spatio-temporal multivariate analysis method using a state-space model (SSM) for brain function that yields not only spatial maps of activity but also its temporal structure along with spatially varying estimates of the hemodynamic response. Efficient algorithms for estimating the parameters along with quantitative validations are given. A novel low-dimensional feature-space for representing the data, based on a formal definition of functional similarity, is derived. Quantitative validation of the model and the estimation algorithms is provided with a simulation study. Using a real fMRI study for mental arithmetic, the ability of this neurophysiologically inspired model to represent the spatio-temporal information corresponding to mental processes is demonstrated. Moreover, by comparing the models across multiple subjects, natural patterns in mental processes organized according to different mental abilities are revealed. Copyright © 2011 Elsevier Inc. All rights reserved.

cudaBayesreg: Parallel Implementation of a Bayesian Multilevel Model for fMRI Data Analysis

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Adelino R. Ferreira da Silva

2011-10-01

Full Text Available Graphic processing units (GPUs are rapidly gaining maturity as powerful general parallel computing devices. A key feature in the development of modern GPUs has been the advancement of the programming model and programming tools. Compute Unified Device Architecture (CUDA is a software platform for massively parallel high-performance computing on Nvidia many-core GPUs. In functional magnetic resonance imaging (fMRI, the volume of the data to be processed, and the type of statistical analysis to perform call for high-performance computing strategies. In this work, we present the main features of the R-CUDA package cudaBayesreg which implements in CUDA the core of a Bayesian multilevel model for the analysis of brain fMRI data. The statistical model implements a Gibbs sampler for multilevel/hierarchical linear models with a normal prior. The main contribution for the increased performance comes from the use of separate threads for fitting the linear regression model at each voxel in parallel. The R-CUDA implementation of the Bayesian model proposed here has been able to reduce significantly the run-time processing of Markov chain Monte Carlo (MCMC simulations used in Bayesian fMRI data analyses. Presently, cudaBayesreg is only configured for Linux systems with Nvidia CUDA support.

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

Science.gov (United States)

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

2018-05-01

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

Enhanced sympathetic arousal in response to FMRI scanning correlates with task induced activations and deactivations.

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Markus Muehlhan

Full Text Available It has been repeatedly shown that functional magnetic resonance imaging (fMRI triggers distress and neuroendocrine response systems. Prior studies have revealed that sympathetic arousal increases, particularly at the beginning of the examination. Against this background it appears likely that those stress reactions during the scanning procedure may influence task performance and neural correlates. However, the question how sympathetic arousal elicited by the scanning procedure itself may act as a potential confounder of fMRI data remains unresolved today. Thirty-seven scanner naive healthy subjects performed a simple cued target detection task. Levels of salivary alpha amylase (sAA, as a biomarker for sympathetic activity, were assessed in samples obtained at several time points during the lab visit. SAA increased two times, immediately prior to scanning and at the end of the scanning procedure. Neural activation related to motor preparation and timing as well as task performance was positively correlated with the first increase. Furthermore, the first sAA increase was associated with task induced deactivation (TID in frontal and parietal regions. However, these effects were restricted to the first part of the experiment. Consequently, this bias of scanner related sympathetic activation should be considered in future fMRI investigations. It is of particular importance for pharmacological investigations studying adrenergic agents and the comparison of groups with different stress vulnerabilities like patients and controls or adolescents and adults.

Effects of anesthetic agents on brain blood oxygenation level revealed with ultra-high field MRI.

Directory of Open Access Journals (Sweden)

Luisa Ciobanu

Full Text Available During general anesthesia it is crucial to control systemic hemodynamics and oxygenation levels. However, anesthetic agents can affect cerebral hemodynamics and metabolism in a drug-dependent manner, while systemic hemodynamics is stable. Brain-wide monitoring of this effect remains highly challenging. Because T(2*-weighted imaging at ultra-high magnetic field strengths benefits from a dramatic increase in contrast to noise ratio, we hypothesized that it could monitor anesthesia effects on brain blood oxygenation. We scanned rat brains at 7T and 17.2T under general anesthesia using different anesthetics (isoflurane, ketamine-xylazine, medetomidine. We showed that the brain/vessels contrast in T(2*-weighted images at 17.2T varied directly according to the applied pharmacological anesthetic agent, a phenomenon that was visible, but to a much smaller extent at 7T. This variation is in agreement with the mechanism of action of these agents. These data demonstrate that preclinical ultra-high field MRI can monitor the effects of a given drug on brain blood oxygenation level in the absence of systemic blood oxygenation changes and of any neural stimulation.

A Human Open Field Test Reveals Thigmotaxis Related to Agoraphobic Fear.

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Walz, Nora; Mühlberger, Andreas; Pauli, Paul

2016-09-01

Thigmotaxis refers to a specific behavior of animals (i.e., to stay close to walls when exploring an open space). Such behavior can be assessed with the open field test (OFT), which is a well-established indicator of animal fear. The detection of similar open field behavior in humans may verify the translational validity of this paradigm. Enhanced thigmotaxis related to anxiety may suggest the relevance of such behavior for anxiety disorders, especially agoraphobia. A global positioning system was used to analyze the behavior of 16 patients with agoraphobia and 18 healthy individuals with a risk for agoraphobia (i.e., high anxiety sensitivity) during a human OFT and compare it with appropriate control groups (n = 16 and n = 19). We also tracked 17 patients with agoraphobia and 17 control participants during a city walk that involved walking through an open market square. Our human OFT triggered thigmotaxis in participants; patients with agoraphobia and participants with high anxiety sensitivity exhibited enhanced thigmotaxis. This behavior was evident in increased movement lengths along the wall of the natural open field and fewer entries into the center of the field despite normal movement speed and length. Furthermore, participants avoided passing through the market square during the city walk, indicating again that thigmotaxis is related to agoraphobia. This study is the first to our knowledge to verify the translational validity of the OFT and to reveal that thigmotaxis, an evolutionarily adaptive behavior shown by most species, is related to agoraphobia, a pathologic fear of open spaces, and anxiety sensitivity, a risk factor for agoraphobia. Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

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

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

2016-03-01

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

Age-Dependent Mesial Temporal Lobe Lateralization in Language FMRI

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Sepeta, Leigh N.; Berl, Madison M.; Wilke, Marko; You, Xiaozhen; Mehta, Meera; Xu, Benjamin; Inati, Sara; Dustin, Irene; Khan, Omar; Austermuehle, Alison; Theodore, William H.; Gaillard, William D.

2015-01-01

Objective FMRI activation of the mesial temporal lobe (MTL) may be important for epilepsy surgical planning. We examined MTL activation and lateralization during language fMRI in children and adults with focal epilepsy. Methods 142 controls and patients with left hemisphere focal epilepsy (Pediatric: epilepsy, n = 17, mean age = 9.9 ± 2.0; controls, n = 48; mean age = 9.1 ± 2.6; Adult: epilepsy, n = 20, mean age = 26.7 ± 5.8; controls, n = 57, mean age = 26.2 ± 7.5) underwent 3T fMRI using a language task (auditory description decision task). Image processing and analyses were conducted in SPM8; ROIs included MTL, Broca’s area, and Wernicke’s area. We assessed group and individual MTL activation, and examined degree of lateralization. Results Patients and controls (pediatric and adult) demonstrated group and individual MTL activation during language fMRI. MTL activation was left lateralized for adults but less so in children (p’s < 0.005). Patients did not differ from controls in either age group. Stronger left-lateralized MTL activation was related to older age (p = 0.02). Language lateralization (Broca’s and Wernicke’s) predicted 19% of the variance in MTL lateralization for adults (p = 0.001), but not children. Significance Language fMRI may be used to elicit group and individual MTL activation. The developmental difference in MTL lateralization and its association with language lateralization suggests a developmental shift in lateralization of MTL function, with increased left lateralization across the age span. This shift may help explain why children have better memory outcomes following resection compared to adults. PMID:26696589

Further fMRI Validation of the Visual Half Field Technique as an Indicator of Language Laterality: A Large-Group Analysis

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Van der Haegen, Lise; Cai, Qing; Seurinck, Ruth; Brysbaert, Marc

2011-01-01

The best established lateralized cerebral function is speech production, with the majority of the population having left hemisphere dominance. An important question is how to best assess the laterality of this function. Neuroimaging techniques such as functional Magnetic Resonance Imaging (fMRI) are increasingly used in clinical settings to…

Voxel-Based Morphometry and fMRI Revealed Differences in Brain Gray Matter in Breastfed and Milk Formula-Fed Children.

Science.gov (United States)

Ou, X; Andres, A; Pivik, R T; Cleves, M A; Snow, J H; Ding, Z; Badger, T M

2016-04-01

Infant diets may have significant impact on brain development in children. The aim of this study was to evaluate brain gray matter structure and function in 8-year-old children who were predominantly breastfed or fed cow's milk formula as infants. Forty-two healthy children (breastfed: n = 22, 10 boys and 12 girls; cow's milk formula: n = 20, 10 boys and 10 girls) were studied by using structural MR imaging (3D T1-weighted imaging) and blood oxygen level-dependent fMRI (while performing tasks involving visual perception and language functions). They were also administered standardized tests evaluating intelligence (Reynolds Intellectual Assessment Scales) and language skills (Clinical Evaluation of Language Fundamentals). Total brain gray matter volume did not differ between the breastfed and cow's milk formula groups. However, breastfed children had significantly higher (P left inferior temporal lobe and left superior parietal lobe compared with cow's milk formula-fed children. Breastfed children showed significantly more brain activation in the right frontal and left/right temporal lobes on fMRI when processing the perception task and in the left temporal/occipital lobe when processing the visual language task than cow's milk formula-fed children. The imaging findings were associated with significantly better performance for breastfed than cow's milk formula-fed children on both tasks. Our findings indicated greater regional gray matter development and better regional gray matter function in breastfed than cow's milk formula-fed children at 8 years of age and suggested that infant diets may have long-term influences on brain development in children. © 2016 by American Journal of Neuroradiology.

Learning Computational Models of Video Memorability from fMRI Brain Imaging.

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

2015-08-01

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

High-resolution functional MRI of the human amygdala at 7 T

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Sladky, Ronald, E-mail: ronald.sladky@meduniwien.ac.at [MR Centre of Excellence, Medical University of Vienna, Lazarettgasse 14, 1090 Vienna (Austria); Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Währinger Gürtel 18-20, 1090 Vienna (Austria); Baldinger, Pia; Kranz, Georg S. [Department of Psychiatry and Psychotherapy, Medical University of Vienna, Währinger Gürtel 18-20, 1090 Vienna (Austria); Tröstl, Jasmin [MR Centre of Excellence, Medical University of Vienna, Lazarettgasse 14, 1090 Vienna (Austria); Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Währinger Gürtel 18-20, 1090 Vienna (Austria); Höflich, Anna; Lanzenberger, Rupert [Department of Psychiatry and Psychotherapy, Medical University of Vienna, Währinger Gürtel 18-20, 1090 Vienna (Austria); Moser, Ewald [MR Centre of Excellence, Medical University of Vienna, Lazarettgasse 14, 1090 Vienna (Austria); Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Währinger Gürtel 18-20, 1090 Vienna (Austria); Windischberger, Christian, E-mail: christian.windischberger@meduniwien.ac.at [MR Centre of Excellence, Medical University of Vienna, Lazarettgasse 14, 1090 Vienna (Austria); Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Währinger Gürtel 18-20, 1090 Vienna (Austria)

2013-05-15

Functional magnetic resonance imaging (fMRI) has become the primary non-invasive method for investigating the human brain function. With an increasing number of ultra-high field MR systems worldwide possibilities of higher spatial and temporal resolution in combination with increased sensitivity and specificity are expected to advance detailed imaging of distinct cortical brain areas and subcortical structures. One target region of particular importance to applications in psychiatry and psychology is the amygdala. However, ultra-high field magnetic resonance imaging of these ventral brain regions is a challenging endeavor that requires particular methodological considerations. Ventral brain areas are particularly prone to signal losses arising from strong magnetic field inhomogeneities along susceptibility borders. In addition, physiological artifacts from respiration and cardiac action cause considerable fluctuations in the MR signal. Here we show that, despite these challenges, fMRI data from the amygdala may be obtained with high temporal and spatial resolution combined with increased signal-to-noise ratio. Maps of neural activation during a facial emotion discrimination paradigm at 7 T are presented and clearly show the gain in percental signal change compared to 3 T results, demonstrating the potential benefits of ultra-high field functional MR imaging also in ventral brain areas.

High-resolution functional MRI of the human amygdala at 7 T

International Nuclear Information System (INIS)

Sladky, Ronald; Baldinger, Pia; Kranz, Georg S.; Tröstl, Jasmin; Höflich, Anna; Lanzenberger, Rupert; Moser, Ewald; Windischberger, Christian

2013-01-01

Functional magnetic resonance imaging (fMRI) has become the primary non-invasive method for investigating the human brain function. With an increasing number of ultra-high field MR systems worldwide possibilities of higher spatial and temporal resolution in combination with increased sensitivity and specificity are expected to advance detailed imaging of distinct cortical brain areas and subcortical structures. One target region of particular importance to applications in psychiatry and psychology is the amygdala. However, ultra-high field magnetic resonance imaging of these ventral brain regions is a challenging endeavor that requires particular methodological considerations. Ventral brain areas are particularly prone to signal losses arising from strong magnetic field inhomogeneities along susceptibility borders. In addition, physiological artifacts from respiration and cardiac action cause considerable fluctuations in the MR signal. Here we show that, despite these challenges, fMRI data from the amygdala may be obtained with high temporal and spatial resolution combined with increased signal-to-noise ratio. Maps of neural activation during a facial emotion discrimination paradigm at 7 T are presented and clearly show the gain in percental signal change compared to 3 T results, demonstrating the potential benefits of ultra-high field functional MR imaging also in ventral brain areas

Steering Electromagnetic Fields in MRI: Investigating Radiofrequency Field Interactions with Endogenous and External Dielectric Materials for Improved Coil Performance at High Field

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Vaidya, Manushka

inferior regions of the brain, where the specific coil's imaging efficiency was inherently poor. Results showed a gain in SNR, while the maximum local and head SAR values remained below the prescribed limits. We showed that increasing coil performance with HPM could improve detection of functional MR activation during a motor-based task for whole brain fMRI. Finally, to gain an intuitive understanding of how HPM improves coil performance, we investigated how HPM separately affects signal and noise sensitivity to improve SNR. For this purpose, we employed a theoretical model based on dyadic Green's functions to compare the characteristics of current patterns, i.e. the optimal spatial distribution of coil conductors, that would either maximize SNR (ideal current patterns), maximize signal reception (signal-only optimal current patterns), or minimize sample noise (dark mode current patterns). Our results demonstrated that the presence of a lossless HPM changed the relative balance of signal-only optimal and dark mode current patterns. For a given relative permittivity, increasing the thickness of the HPM altered the magnitude of the currents required to optimize signal sensitivity at the voxel of interest as well as decreased the net electric field in the sample, which is associated, via reciprocity, to the noise received from the sample. Our results also suggested that signal-only current patterns could be used to identify HPM configurations that lead to high SNR gain for RF coil arrays. We anticipate that physical insights from this work could be utilized to build the next generation of high performing RF coils integrated with HPM.

Intrasubject reproducibility of presurgical language lateralization and mapping using fMRI.

NARCIS (Netherlands)

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

2003-01-01

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

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

International Nuclear Information System (INIS)

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

2014-01-01

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

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

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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.

FMRI activity during associative encoding is correlated with cardiorespiratory fitness and source memory performance in older adults.

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Hayes, Scott M; Hayes, Jasmeet P; Williams, Victoria J; Liu, Huiting; Verfaellie, Mieke

2017-06-01

Older adults (OA), relative to young adults (YA), exhibit age-related alterations in functional Magnetic Resonance Imaging (fMRI) activity during associative encoding, which contributes to deficits in source memory. Yet, there are remarkable individual differences in brain health and memory performance among OA. Cardiorespiratory fitness (CRF) is one individual difference factor that may attenuate brain aging, and thereby contribute to enhanced source memory in OA. To examine this possibility, 26 OA and 31 YA completed a treadmill-based exercise test to evaluate CRF (peak VO 2 ) and fMRI to examine brain activation during a face-name associative encoding task. Our results indicated that in OA, peak VO 2 was positively associated with fMRI activity during associative encoding in multiple regions including bilateral prefrontal cortex, medial frontal cortex, bilateral thalamus and left hippocampus. Next, a conjunction analysis was conducted to assess whether CRF influenced age-related differences in fMRI activation. We classified OA as high or low CRF and compared their activation to YA. High fit OA (HFOA) showed fMRI activation more similar to YA than low fit OA (LFOA) (i.e., reduced age-related differences) in multiple regions including thalamus, posterior and prefrontal cortex. Conversely, in other regions, primarily in prefrontal cortex, HFOA, but not LFOA, demonstrated greater activation than YA (i.e., increased age-related differences). Further, fMRI activity in these brain regions was positively associated with source memory among OA, with a mediation model demonstrating that associative encoding activation in medial frontal cortex indirectly influenced the relationship between peak VO 2 and subsequent source memory performance. These results indicate that CRF may contribute to neuroplasticity among OA, reducing age-related differences in some brain regions, consistent with the brain maintenance hypothesis, but accentuating age-differences in other regions

The continuing challenge of understanding and modeling hemodynamic variation in fMRI

OpenAIRE

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

2012-01-01

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

Multiple fMRI system-level baseline connectivity is disrupted in patients with consciousness alterations.

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Demertzi, Athena; Gómez, Francisco; Crone, Julia Sophia; Vanhaudenhuyse, Audrey; Tshibanda, Luaba; Noirhomme, Quentin; Thonnard, Marie; Charland-Verville, Vanessa; Kirsch, Murielle; Laureys, Steven; Soddu, Andrea

2014-03-01

In healthy conditions, group-level fMRI resting state analyses identify ten resting state networks (RSNs) of cognitive relevance. Here, we aim to assess the ten-network model in severely brain-injured patients suffering from disorders of consciousness and to identify those networks which will be most relevant to discriminate between patients and healthy subjects. 300 fMRI volumes were obtained in 27 healthy controls and 53 patients in minimally conscious state (MCS), vegetative state/unresponsive wakefulness syndrome (VS/UWS) and coma. Independent component analysis (ICA) reduced data dimensionality. The ten networks were identified by means of a multiple template-matching procedure and were tested on neuronality properties (neuronal vs non-neuronal) in a data-driven way. Univariate analyses detected between-group differences in networks' neuronal properties and estimated voxel-wise functional connectivity in the networks, which were significantly less identifiable in patients. A nearest-neighbor "clinical" classifier was used to determine the networks with high between-group discriminative accuracy. Healthy controls were characterized by more neuronal components compared to patients in VS/UWS and in coma. Compared to healthy controls, fewer patients in MCS and VS/UWS showed components of neuronal origin for the left executive control network, default mode network (DMN), auditory, and right executive control network. The "clinical" classifier indicated the DMN and auditory network with the highest accuracy (85.3%) in discriminating patients from healthy subjects. FMRI multiple-network resting state connectivity is disrupted in severely brain-injured patients suffering from disorders of consciousness. When performing ICA, multiple-network testing and control for neuronal properties of the identified RSNs can advance fMRI system-level characterization. Automatic data-driven patient classification is the first step towards future single-subject objective diagnostics

The insula is not specifically involved in disgust processing: an fMRI study.

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Schienle, A; Stark, R; Walter, B; Blecker, C; Ott, U; Kirsch, P; Sammer, G; Vaitl, D

2002-11-15

fMRI studies have shown that the perception of facial disgust expressions specifically activates the insula. The present fMRI study investigated whether this structure is also involved in the processing of visual stimuli depicting non-mimic disgust elicitors compared to fear-inducing and neutral scenes. Twelve female subjects were scanned while viewing alternating blocks of 40 disgust-inducing, 40 fear-inducing and 40 affectively neutral pictures, shown for 1.5 s each. Afterwards, affective ratings were assessed. The disgust pictures, rated as highly repulsive, induced activation in the insula, the amygdala, the orbitofrontal and occipito-temporal cortex. Since during the fear condition the insula was also involved, our findings do not fit the idea of the insula as a specific disgust processor.

Ageing differentially affects neural processing of different conflict types – an fMRI study

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Margarethe eKorsch

2014-04-01

Full Text Available Interference control and conflict resolution is affected by ageing. There is increasing evidence that ageing does not compromise interference control in general but rather shows distinctive effects on different components of interference control. Different conflict types, (e.g. stimulus-stimulus (S-S or stimulus-response (S-R conflicts trigger different cognitive processes and thus activate different neural networks. In the present functional magnetic resonance imaging (fMRI study, we used a combined Flanker and Stimulus Response Conflict (SRC task to investigate the effect of ageing on S-S and S-R conflicts. Behavioral data analysis revealed larger SRC effects in elderly. fMRI Results show that both age groups recruited similar regions (caudate nucleus, cingulate gyrus and middle occipital gyrus during Flanker conflict processing. Furthermore, elderly show an additional activation pattern in parietal and frontal areas. In contrast, no common activation of both age groups was found in response to the SRC. These data suggest that ageing has distinctive effects on S-S and S-R conflicts.

Metabolic connectivity mapping reveals effective connectivity in the resting human brain.

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Riedl, Valentin; Utz, Lukas; Castrillón, Gabriel; Grimmer, Timo; Rauschecker, Josef P; Ploner, Markus; Friston, Karl J; Drzezga, Alexander; Sorg, Christian

2016-01-12

Directionality of signaling among brain regions provides essential information about human cognition and disease states. Assessing such effective connectivity (EC) across brain states using functional magnetic resonance imaging (fMRI) alone has proven difficult, however. We propose a novel measure of EC, termed metabolic connectivity mapping (MCM), that integrates undirected functional connectivity (FC) with local energy metabolism from fMRI and positron emission tomography (PET) data acquired simultaneously. This method is based on the concept that most energy required for neuronal communication is consumed postsynaptically, i.e., at the target neurons. We investigated MCM and possible changes in EC within the physiological range using "eyes open" versus "eyes closed" conditions in healthy subjects. Independent of condition, MCM reliably detected stable and bidirectional communication between early and higher visual regions. Moreover, we found stable top-down signaling from a frontoparietal network including frontal eye fields. In contrast, we found additional top-down signaling from all major clusters of the salience network to early visual cortex only in the eyes open condition. MCM revealed consistent bidirectional and unidirectional signaling across the entire cortex, along with prominent changes in network interactions across two simple brain states. We propose MCM as a novel approach for inferring EC from neuronal energy metabolism that is ideally suited to study signaling hierarchies in the brain and their defects in brain disorders.

Reading positional codes with fMRI: Problems and solutions.

Directory of Open Access Journals (Sweden)

Kristjan Kalm

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

Bayesian Inference for Functional Dynamics Exploring in fMRI Data

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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.

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

Science.gov (United States)

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

1998-04-01

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

Test-retest reliability of evoked BOLD signals from a cognitive-emotive fMRI test battery.

Science.gov (United States)

Plichta, Michael M; Schwarz, Adam J; Grimm, Oliver; Morgen, Katrin; Mier, Daniela; Haddad, Leila; Gerdes, Antje B M; Sauer, Carina; Tost, Heike; Esslinger, Christine; Colman, Peter; Wilson, Frederick; Kirsch, Peter; Meyer-Lindenberg, Andreas

2012-04-15

Even more than in cognitive research applications, moving fMRI to the clinic and the drug development process requires the generation of stable and reliable signal changes. The performance characteristics of the fMRI paradigm constrain experimental power and may require different study designs (e.g., crossover vs. parallel groups), yet fMRI reliability characteristics can be strongly dependent on the nature of the fMRI task. The present study investigated both within-subject and group-level reliability of a combined three-task fMRI battery targeting three systems of wide applicability in clinical and cognitive neuroscience: an emotional (face matching), a motivational (monetary reward anticipation) and a cognitive (n-back working memory) task. A group of 25 young, healthy volunteers were scanned twice on a 3T MRI scanner with a mean test-retest interval of 14.6 days. FMRI reliability was quantified using the intraclass correlation coefficient (ICC) applied at three different levels ranging from a global to a localized and fine spatial scale: (1) reliability of group-level activation maps over the whole brain and within targeted regions of interest (ROIs); (2) within-subject reliability of ROI-mean amplitudes and (3) within-subject reliability of individual voxels in the target ROIs. Results showed robust evoked activation of all three tasks in their respective target regions (emotional task=amygdala; motivational task=ventral striatum; cognitive task=right dorsolateral prefrontal cortex and parietal cortices) with high effect sizes (ES) of ROI-mean summary values (ES=1.11-1.44 for the faces task, 0.96-1.43 for the reward task, 0.83-2.58 for the n-back task). Reliability of group level activation was excellent for all three tasks with ICCs of 0.89-0.98 at the whole brain level and 0.66-0.97 within target ROIs. Within-subject reliability of ROI-mean amplitudes across sessions was fair to good for the reward task (ICCs=0.56-0.62) and, dependent on the particular ROI

Considering sex differences clarifies the effects of depression on facial emotion processing during fMRI.

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Jenkins, L M; Kendall, A D; Kassel, M T; Patrón, V G; Gowins, J R; Dion, C; Shankman, S A; Weisenbach, S L; Maki, P; Langenecker, S A

2018-01-01

Sex differences in emotion processing may play a role in women's increased risk for Major Depressive Disorder (MDD). However, studies of sex differences in brain mechanisms involved in emotion processing in MDD (or interactions of sex and diagnosis) are sparse. We conducted an event-related fMRI study examining the interactive and distinct effects of sex and MDD on neural activity during a facial emotion perception task. To minimize effects of current affective state and cumulative disease burden, we studied participants with remitted MDD (rMDD) who were early in the course of the illness. In total, 88 individuals aged 18-23 participated, including 48 with rMDD (32 female) and 40 healthy controls (HC; 25 female). fMRI revealed an interaction between sex and diagnosis for sad and neutral facial expressions in the superior frontal gyrus and left middle temporal gyrus. Results also revealed an interaction of sex with diagnosis in the amygdala. Data was from two sites, which might increase variability, but it also increases power to examine sex by diagnosis interactions. This study demonstrates the importance of taking sex differences into account when examining potential trait (or scar) mechanisms that could be useful in identifying individuals at-risk for MDD as well as for evaluating potential therapeutic innovations. Copyright © 2017 Elsevier B.V. All rights reserved.

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

NARCIS (Netherlands)

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

2002-01-01

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

Convergence of human brain mapping tools: neuronavigated TMS parameters and fMRI activity in the hand motor area.

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Sarfeld, Anna-Sophia; Diekhoff, Svenja; Wang, Ling E; Liuzzi, Gianpiero; Uludağ, Kamil; Eickhoff, Simon B; Fink, Gereon R; Grefkes, Christian

2012-05-01

Functional magnetic resonance imaging (fMRI) and transcranial magnetic stimulation (TMS) are well-established tools for investigating the human motor system in-vivo. We here studied the relationship between movement-related fMRI signal changes in the primary motor cortex (M1) and electrophysiological properties of the hand motor area assessed with neuronavigated TMS in 17 healthy subjects. The voxel showing the highest task-related BOLD response in the left hand motor area during right hand movements was identified for each individual subject. This fMRI peak voxel in M1 served as spatial target for coil positioning during neuronavigated TMS. We performed correlation analyses between TMS parameters, BOLD signal estimates and effective connectivity parameters of M1 assessed with dynamic causal modeling (DCM). The results showed a negative correlation between the movement-related BOLD signal in left M1 and resting as well as active motor threshold (MT) obtained for left M1. The DCM analysis revealed that higher excitability of left M1 was associated with a stronger coupling between left supplementary motor area (SMA) and M1. Furthermore, BOLD activity in left M1 correlated with ipsilateral silent period (ISP), i.e. the stronger the task-related BOLD response in left M1, the higher interhemispheric inhibition effects targeting right M1. DCM analyses revealed a positive correlation between the coupling of left SMA with left M1 and the duration of ISP. The data show that TMS parameters assessed for the hand area of M1 do not only reflect the intrinsic properties at the stimulation site but also interactions with remote areas in the human motor system. Copyright © 2011 Wiley-Liss, Inc.

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

Science.gov (United States)

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

2017-06-01

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

Magnetic resonance imaging of hindfoot involvement in patients with spondyloarthritides: Comparison of low-field and high-field strength units

Energy Technology Data Exchange (ETDEWEB)

Eshed, Iris; Althoff, Christian E. [Department of Radiology, Charite Medical School, Berlin (Germany); Feist, Eugen [Department of Rheumatology and Clinical Immunology, Charite Medical School, Berlin (Germany); Minden, Kirsten [Helios Clinics, 2nd Children' s Hospital Berlin-Buch, Rheumatology Unit, Berlin (Germany); German Rheumatology Research Center, Berlin (Germany); Schink, Tania [Department of Medical Biometry, Charite Medical School, Berlin (Germany); Hamm, Bernd [Department of Radiology, Charite Medical School, Berlin (Germany); Hermann, Kay-Geert A. [Department of Radiology, Charite Medical School, Berlin (Germany)], E-mail: kgh@charite.de

2008-01-15

Objective: To compare MRI evaluation of a painful hindfoot of patients with spondyloarthritides (SpA) on low-field (0.2 T) versus high-field (1.5 T) MRI. Materials and methods: Patients with SpA and hindfoot pain were randomly referred to either high-field or low-field MRI. Twenty-seven patients were evaluated (male/female: 17:10; mean age: 39 {+-} 1.4 years). Fifteen patients were examined by low-field and 12 by high-field MRI. Two patients (evaluated by high-field MRI) were excluded. Images were separately read by two radiologists who later reached a consensus. In each patient the prevalence of erosions, fluid, synovitis or bone marrow edema of the hindfoot joints, tendinosis or tenosynovitis of tendons, enthesitis of the plantar fascia and Achilles tendon and retrocalcaneal bursitis were recorded. Clinical and demographic parameters were comparable between both groups. Results: MRI evaluation of joints and tendons of the hindfoot revealed no significant differences in patients with SpA groups for all parameters. Analyzing all joints or tendons together, there was no statistically significant difference between the two groups. Conclusion: Low-field and high-field MRI provide comparable information for evaluation of inflammatory hindfoot involvement. Thus, low-field MRI can be considered as a reliable diagnostic tool for the detection of hindfoot abnormalities in SpA patients.

Magnetic resonance imaging of hindfoot involvement in patients with spondyloarthritides: Comparison of low-field and high-field strength units

International Nuclear Information System (INIS)

Eshed, Iris; Althoff, Christian E.; Feist, Eugen; Minden, Kirsten; Schink, Tania; Hamm, Bernd; Hermann, Kay-Geert A.

2008-01-01

Objective: To compare MRI evaluation of a painful hindfoot of patients with spondyloarthritides (SpA) on low-field (0.2 T) versus high-field (1.5 T) MRI. Materials and methods: Patients with SpA and hindfoot pain were randomly referred to either high-field or low-field MRI. Twenty-seven patients were evaluated (male/female: 17:10; mean age: 39 ± 1.4 years). Fifteen patients were examined by low-field and 12 by high-field MRI. Two patients (evaluated by high-field MRI) were excluded. Images were separately read by two radiologists who later reached a consensus. In each patient the prevalence of erosions, fluid, synovitis or bone marrow edema of the hindfoot joints, tendinosis or tenosynovitis of tendons, enthesitis of the plantar fascia and Achilles tendon and retrocalcaneal bursitis were recorded. Clinical and demographic parameters were comparable between both groups. Results: MRI evaluation of joints and tendons of the hindfoot revealed no significant differences in patients with SpA groups for all parameters. Analyzing all joints or tendons together, there was no statistically significant difference between the two groups. Conclusion: Low-field and high-field MRI provide comparable information for evaluation of inflammatory hindfoot involvement. Thus, low-field MRI can be considered as a reliable diagnostic tool for the detection of hindfoot abnormalities in SpA patients

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...

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

Science.gov (United States)

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

2014-07-15

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

Decoding subjective mental states from fMRI activity patterns

International Nuclear Information System (INIS)

Tamaki, Masako; Kamitani, Yukiyasu

2011-01-01

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

The influence of FMRI lie detection evidence on juror decision-making.

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McCabe, David P; Castel, Alan D; Rhodes, Matthew G

2011-01-01

In the current study, we report on an experiment examining whether functional magnetic resonance imaging (fMRI) lie detection evidence would influence potential jurors' assessment of guilt in a criminal trial. Potential jurors (N = 330) read a vignette summarizing a trial, with some versions of the vignette including lie detection evidence indicating that the defendant was lying about having committed the crime. Lie detector evidence was based on evidence from the polygraph, fMRI (functional brain imaging), or thermal facial imaging. Results showed that fMRI lie detection evidence led to more guilty verdicts than lie detection evidence based on polygraph evidence, thermal facial imaging, or a control condition that did not include lie detection evidence. However, when the validity of the fMRI lie detection evidence was called into question on cross-examination, guilty verdicts were reduced to the level of the control condition. These results provide important information about the influence of lie detection evidence in legal settings. Copyright © 2011 John Wiley & Sons, Ltd.

Cortical control of gait in healthy humans: an fMRI study

International Nuclear Information System (INIS)

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

2008-01-01

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

Single Voxel Proton Spectroscopy for Neurofeedback at 7 Tesla

OpenAIRE

Koush, Yury; Elliott, Mark A.; Mathiak, Klaus

2011-01-01

Echo-planar imaging (EPI) in fMRI is regularly used to reveal BOLD activation in presubscribed regions of interest (ROI). The response is mediated by relative changes in T2* which appear as changes in the image pixel intensities. We have proposed an application of functional single-voxel proton spectroscopy (fSVPS) for real-time studies at ultra-high MR field which can be comparable to the EPI BOLD fMRI technique. A spin-echo SVPS protocol without water suppression was acquired with 310 repet...

High magnetic field quantum transport in Au nanoparticle–cellulose films

International Nuclear Information System (INIS)

Turyanska, L; Makarovsky, O; Patanè, A; Kozlova, N V; Liu, Z; Li, M; Mann, S

2012-01-01

We report the magneto-transport properties of cellulose films comprising interconnected networks of gold nanoparticles (Au NPs). Cellulose is a biopolymer that can be made electrically conducting by cellulose regeneration in Au NP dispersions. The mechanism of electronic conduction in the Au–cellulose films changes from variable range hopping to metallic-like conduction with decreasing resistivity. Our experiments in high magnetic fields (up to 45 T) reveal negative magnetoresistance in the highly resistive films. This is attributed to the spin polarization of the Au NPs and the magnetic field induced suppression of electron spin flips during spin-polarized tunneling in the NP network. (paper)

Increasing fMRI sampling rate improves Granger causality estimates.

Directory of Open Access Journals (Sweden)

Fa-Hsuan Lin

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

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

Science.gov (United States)

Sokunbi, Moses O

2018-05-15

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

Field trip method as an effort to reveal student environmental literacy on biodiversity issue and context

Science.gov (United States)

Rijal, M.; Saefudin; Amprasto

2018-05-01

Field trip method through investigation of local biodiversity cases can give educational experiences for students. This learning activity was efforts to reveal students environmental literacy on biodiversity. The aim of study were (1) to describe the activities of students get information about the biodiversity issue and its context through field trip, (2) to describe the students findings during field trip, and (3) to reveal students environmental literacy based on pre test and post test. The research method used weak-experiment and involved 34 participants at senior high school students in Bandung-Indonesia. The research instruments for collecting data were environmental literacy test, observation sheets and questionnaire sheets for students. The analysis of data was quantitative descriptive. The results show that more than 79% of the students gave positive view for each field trip activity, i.e students activity during work (97%-100%); students activity during gather information (79%- 100%); students activity during exchange information with friend (82%-100%); and students interested to Biodiversity after field trip activity (85%-100%). Students gain knowledge about the diversity of animal vertebrate and its characteristics, the status and condition of animals, and the source of animal with the cases of animal diversity. The students environmental literacy tends to be moderate level based on test. Meanwhile, the average of the attitudes and action greater than the components of knowledge and cognitive skills.

Lying about the valence of affective pictures: an fMRI study.

Directory of Open Access Journals (Sweden)

Tatia M C Lee

Full Text Available The neural correlates of lying about affective information were studied using a functional magnetic resonance imaging (fMRI methodology. Specifically, 13 healthy right-handed Chinese men were instructed to lie about the valence, positive or negative, of pictures selected from the International Affective Picture System (IAPS while their brain activity was scanned by a 3T Philip Achieva scanner. The key finding is that the neural activity associated with deception is valence-related. Comparing to telling the truth, deception about the valence of the affectively positive pictures was associated with activity in the inferior frontal, cingulate, inferior parietal, precuneus, and middle temporal regions. Lying about the valence of the affectively negative pictures, on the other hand, was associated with activity in the orbital and medial frontal regions. While a clear valence-related effect on deception was observed, common neural regions were also recruited for the process of deception about the valence of the affective pictures. These regions included the lateral prefrontal and inferior parietal regions. Activity in these regions has been widely reported in fMRI studies on deception using affectively-neutral stimuli. The findings of this study reveal the effect of valence on the neural activity associated with deception. Furthermore, the data also help to illustrate the complexity of the neural mechanisms underlying deception.

Vocal Tract Images Reveal Neural Representations of Sensorimotor Transformation During Speech Imitation

Science.gov (United States)

Carey, Daniel; Miquel, Marc E.; Evans, Bronwen G.; Adank, Patti; McGettigan, Carolyn

2017-01-01

Abstract Imitating speech necessitates the transformation from sensory targets to vocal tract motor output, yet little is known about the representational basis of this process in the human brain. Here, we address this question by using real-time MR imaging (rtMRI) of the vocal tract and functional MRI (fMRI) of the brain in a speech imitation paradigm. Participants trained on imitating a native vowel and a similar nonnative vowel that required lip rounding. Later, participants imitated these vowels and an untrained vowel pair during separate fMRI and rtMRI runs. Univariate fMRI analyses revealed that regions including left inferior frontal gyrus were more active during sensorimotor transformation (ST) and production of nonnative vowels, compared with native vowels; further, ST for nonnative vowels activated somatomotor cortex bilaterally, compared with ST of native vowels. Using test representational similarity analysis (RSA) models constructed from participants’ vocal tract images and from stimulus formant distances, we found that RSA searchlight analyses of fMRI data showed either type of model could be represented in somatomotor, temporal, cerebellar, and hippocampal neural activation patterns during ST. We thus provide the first evidence of widespread and robust cortical and subcortical neural representation of vocal tract and/or formant parameters, during prearticulatory ST. PMID:28334401

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.

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

Science.gov (United States)

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

2008-08-01

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

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

Science.gov (United States)

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

2013-04-01

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

Decomposition of BOLD Activity into Tuned and Untuned Components Reveals Cohabitation of Stimulus and Choice Information in V1

Directory of Open Access Journals (Sweden)

Kyoung Whan Choe

2012-10-01

Full Text Available Recent studies on V1 report top-down modulation of input-driven responses of sensory neurons, implying that exogenous sensory drives and endogenous top-down drives jointly determine V1 responses. By measuring fMRI responses in conjunction with a classification task on ambiguous ring stimuli, we sought to understand how V1 carries out its encoding operation on afferent currents while being adaptively modulated by top-down currents associated with perceptual tasks. Population activity of V1, as in its raw eccentricity profiles, failed to resolve the threshold differences between the ring stimuli due to large moment-to-moment fluctuations. The analysis of variance indicated that stimulus-evoked responses explain only one-fifth of the total variance and fMRI responses were highly correlated among eccentricity-bins, implying that a substantial fraction of V1 responses fluctuate as a whole. This led us to decompose the raw fMRI responses into untuned and tuned components: average response across eccentricity-bins and residual responses from the average, respectively, the former varying only in time and the latter varying in both space and time. The tuned responses revealed the veridical encoding operation of V1 by readily distinguishing between the ring stimuli, which was impossible with the raw fMRI responses. In contrast, the untuned were correlated with two major aspects of choice behavior—inter-trial variability in response time and inter-subject variability in response bias. We propose that this cohabitation of stimulus and choice information in V1 indicates the presence of top-down exertion of gain modulation on the early processing stage by the high-tier stage that accumulates evidence for perceptual choices.

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

Science.gov (United States)

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

2018-01-01

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

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

Science.gov (United States)

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

2018-01-01

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

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.

Voluntary Enhancement of Neural Signatures of Affiliative Emotion Using fMRI Neurofeedback

Science.gov (United States)

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

2014-01-01

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

Feature-Space Clustering for fMRI Meta-Analysis

DEFF Research Database (Denmark)

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

2001-01-01

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

Cross-cultural reading the mind in the eyes: an fMRI investigation.

Science.gov (United States)

Adams, Reginald B; Rule, Nicholas O; Franklin, Robert G; Wang, Elsie; Stevenson, Michael T; Yoshikawa, Sakiko; Nomura, Mitsue; Sato, Wataru; Kveraga, Kestutis; Ambady, Nalini

2010-01-01

The ability to infer others' thoughts, intentions, and feelings is regarded as uniquely human. Over the last few decades, this remarkable ability has captivated the attention of philosophers, primatologists, clinical and developmental psychologists, anthropologists, social psychologists, and cognitive neuroscientists. Most would agree that the capacity to reason about others' mental states is innately prepared, essential for successful human social interaction. Whether this ability is culturally tuned, however, remains entirely uncharted on both the behavioral and neural levels. Here we provide the first behavioral and neural evidence for an intracultural advantage (better performance for same- vs. other-culture) in mental state decoding in a sample of native Japanese and white American participants. We examined the neural correlates of this intracultural advantage using fMRI, revealing greater bilateral posterior superior temporal sulci recruitment during same- versus other-culture mental state decoding in both cultural groups. These findings offer preliminary support for cultural consistency in the neurological architecture subserving high-level mental state reasoning, as well as its differential recruitment based on cultural group membership.

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...

Characterization of dynamic changes of current source localization based on spatiotemporal fMRI constrained EEG source imaging

Science.gov (United States)

Nguyen, Thinh; Potter, Thomas; Grossman, Robert; Zhang, Yingchun

2018-06-01

Objective. Neuroimaging has been employed as a promising approach to advance our understanding of brain networks in both basic and clinical neuroscience. Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) represent two neuroimaging modalities with complementary features; EEG has high temporal resolution and low spatial resolution while fMRI has high spatial resolution and low temporal resolution. Multimodal EEG inverse methods have attempted to capitalize on these properties but have been subjected to localization error. The dynamic brain transition network (DBTN) approach, a spatiotemporal fMRI constrained EEG source imaging method, has recently been developed to address these issues by solving the EEG inverse problem in a Bayesian framework, utilizing fMRI priors in a spatial and temporal variant manner. This paper presents a computer simulation study to provide a detailed characterization of the spatial and temporal accuracy of the DBTN method. Approach. Synthetic EEG data were generated in a series of computer simulations, designed to represent realistic and complex brain activity at superficial and deep sources with highly dynamical activity time-courses. The source reconstruction performance of the DBTN method was tested against the fMRI-constrained minimum norm estimates algorithm (fMRIMNE). The performances of the two inverse methods were evaluated both in terms of spatial and temporal accuracy. Main results. In comparison with the commonly used fMRIMNE method, results showed that the DBTN method produces results with increased spatial and temporal accuracy. The DBTN method also demonstrated the capability to reduce crosstalk in the reconstructed cortical time-course(s) induced by neighboring regions, mitigate depth bias and improve overall localization accuracy. Significance. The improved spatiotemporal accuracy of the reconstruction allows for an improved characterization of complex neural activity. This improvement can be

From Blame to Punishment: Disrupting Prefrontal Cortex Activity Reveals Norm Enforcement Mechanisms.

Science.gov (United States)

Buckholtz, Joshua W; Martin, Justin W; Treadway, Michael T; Jan, Katherine; Zald, David H; Jones, Owen; Marois, René

2015-09-23

The social welfare provided by cooperation depends on the enforcement of social norms. Determining blameworthiness and assigning a deserved punishment are two cognitive cornerstones of norm enforcement. Although prior work has implicated the dorsolateral prefrontal cortex (DLPFC) in norm-based judgments, the relative contribution of this region to blameworthiness and punishment decisions remains poorly understood. Here, we used repetitive transcranial magnetic stimulation (rTMS) and fMRI to determine the specific role of DLPFC function in norm-enforcement behavior. DLPFC rTMS reduced punishment for wrongful acts without affecting blameworthiness ratings, and fMRI revealed punishment-selective DLPFC recruitment, suggesting that these two facets of norm-based decision making are neurobiologically dissociable. Finally, we show that DLPFC rTMS affects punishment decision making by altering the integration of information about culpability and harm. Together, these findings reveal a selective, causal role for DLPFC in norm enforcement: representational integration of the distinct information streams used to make punishment decisions. Copyright © 2015 Elsevier Inc. All rights reserved.

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

Science.gov (United States)

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

2015-08-01

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

Nonparametric trend estimation in the presence of fractal noise: application to fMRI time-series analysis.

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Afshinpour, Babak; Hossein-Zadeh, Gholam-Ali; Soltanian-Zadeh, Hamid

2008-06-30

Unknown low frequency fluctuations called "trend" are observed in noisy time-series measured for different applications. In some disciplines, they carry primary information while in other fields such as functional magnetic resonance imaging (fMRI) they carry nuisance effects. In all cases, however, it is necessary to estimate them accurately. In this paper, a method for estimating trend in the presence of fractal noise is proposed and applied to fMRI time-series. To this end, a partly linear model (PLM) is fitted to each time-series. The parametric and nonparametric parts of PLM are considered as contributions of hemodynamic response and trend, respectively. Using the whitening property of wavelet transform, the unknown components of the model are estimated in the wavelet domain. The results of the proposed method are compared to those of other parametric trend-removal approaches such as spline and polynomial models. It is shown that the proposed method improves activation detection and decreases variance of the estimated parameters relative to the other methods.

Probing the brain with molecular fMRI.

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

2018-04-09

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

A novel approach to calibrate the Hemodynamic Model using functional Magnetic Resonance Imaging (fMRI) measurements

KAUST Repository

Khoram, Nafiseh; Zayane, Chadia; Djellouli, Rabia; Laleg-Kirati, Taous-Meriem

2016-01-01

We have designed an iterative numerical technique, called the TNM-CKF algorithm, for calibrating the mathematical model that describes the single-event related brain response when fMRI measurements are given. The method appears to be highly accurate and effective in reconstructing the BOLD signal even when the measurements are tainted with high noise level (as high as 30%).

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

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

2017-09-01

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

Cerebrovascular reactivity among native-raised high altitude residents: an fMRI study

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Zhang Jiaxing

2011-09-01

Full Text Available Abstract Background The impact of long term residence on high altitude (HA on human brain has raised concern among researchers in recent years. This study investigated the cerebrovascular reactivity among native-born high altitude (HA residents as compared to native sea level (SL residents. The two groups were matched on the ancestral line, ages, gender ratios, and education levels. A visual cue guided maximum inspiration task with brief breath holding was performed by all the subjects while Blood-Oxygenation-Level-Dependent (BOLD functional Magnetic Resonance Imaging (fMRI data were acquired from them. Results Compared to SL controls, the HA group showed generally decreased cerebrovascular reactivity and longer delay in hemodynamic response. Clusters showing significant differences in the former aspect were located at the bilateral primary motor cortex, the right somatosensory association cortex, the right thalamus and the right caudate, the bilateral precuneus, the right cingulate gyrus and the right posterior cingulate cortex, as well as the left fusiform gyrus and the right lingual cortex; clusters showing significant differences in the latter aspect were located at the precuneus, the insula, the superior frontal and temporal gyrus, the somatosensory cortex (the postcentral gyrus and the cerebellar tonsil. Inspiratory reserve volume (IRV, which is an important aspect of pulmonary function, demonstrated significant correlation with the amount of BOLD signal change in multiple brain regions, particularly at the bilateral insula among the HA group. Conclusions Native-born HA residents generally showed reduced cerebrovascular reactivity as demonstrated in the hemodynamic response during a visual cue guided maximum inspiration task conducted with BOLD-fMRI. This effect was particularly manifested among brain regions that are typically involved in cerebral modulation of respiration.

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

International Nuclear Information System (INIS)

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

2011-01-01

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

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

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

2011-11-15

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

Application of calibrated fMRI in Alzheimer's disease.

Science.gov (United States)

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

2017-01-01

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

Application of calibrated fMRI in Alzheimer's disease

Directory of Open Access Journals (Sweden)

Isabelle Lajoie

2017-01-01

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

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%).

High-field magnetic resonance imaging of the human temporal lobe

Directory of Open Access Journals (Sweden)

Luis M. Colon-Perez

2015-01-01

Conclusions: Fresh ex vivo MR imaging, along with tractography, revealed complex intra-temporal structural variation corresponding to neuronal cell body layers, dendritic fields, and axonal projection systems evident histologically. This is the first study to describe in detail the human temporal lobe structural organization using high-field MR imaging and tractography. By preserving the 3-dimensional structures of the hippocampus and surrounding structures, specific changes in anatomy may inform us about the changes that occur in TLE in relation to the disease process and structural underpinnings in epilepsy-related memory dysfunction.

Functional magnetic resonance imaging in a low-field intraoperative scanner.

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Schulder, Michael; Azmi, Hooman; Biswal, Bharat

2003-01-01

Functional magnetic resonance imaging (fMRI) has been used for preoperative planning and intraoperative surgical navigation. However, most experience to date has been with preoperative images acquired on high-field echoplanar MRI units. We explored the feasibility of acquiring fMRI of the motor cortex with a dedicated low-field intraoperative MRI (iMRI). Five healthy volunteers were scanned with the 0.12-tesla PoleStar N-10 iMRI (Odin Medical Technologies, Israel). A finger-tapping motor paradigm was performed with sequential scans, acquired alternately at rest and during activity. In addition, scans were obtained during breath holding alternating with normal breathing. The same paradigms were repeated using a 3-tesla MRI (Siemens Corp., Allandale, N.J., USA). Statistical analysis was performed offline using cross-correlation and cluster techniques. Data were resampled using the 'jackknife' process. The location, number of activated voxels and degrees of statistical significance between the two scanners were compared. With both the 0.12- and 3-tesla imagers, motor cortex activation was seen in all subjects to a significance of p < 0.02 or greater. No clustered pixels were seen outside the sensorimotor cortex. The resampled correlation coefficients were normally distributed, with a mean of 0.56 for both the 0.12- and 3-tesla scanners (standard deviations 0.11 and 0.08, respectively). The breath holding paradigm confirmed that the expected diffuse activation was seen on 0.12- and 3-tesla scans. Accurate fMRI with a low-field iMRI is feasible. Such data could be acquired immediately before or even during surgery. This would increase the utility of iMRI and allow for updated intraoperative functional imaging, free of the limitations of brain shift. Copyright 2003 S. Karger AG, Basel

fMRI paradigm designing and post-processing tools

International Nuclear Information System (INIS)

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

2014-01-01

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

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

Science.gov (United States)

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

2012-07-01

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

A pooling-LiNGAM algorithm for effective connectivity analysis of fMRI data

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Lele eXu

2014-10-01

Full Text Available The Independent Component Analysis - linear non-Gaussian acyclic model (LiNGAM, an algorithm that can be used to estimate the causal relationship among non-Gaussian distributed data, has the potential value to detect the effective connectivity of human brain areas. Under the assumptions that (a: the data generating process is linear, (b there are no unobserved confounders, and (c data have non-Gaussian distributions, LiNGAM can be used to discover the complete causal structure of data. Previous studies reveal that the algorithm could perform well when the data points being analyzed is relatively long. However, there are too few data points in most neuroimaging recordings, especially functional magnetic resonance imaging (fMRI, to allow the algorithm to converge. Smith’s study speculates a method by pooling data points across subjects may be useful to address this issue (Smith et al., 2011. Thus this study focus on validating Smith’s proposal of pooling data points across subjects for the use of LiNGAM, and this method is named as pooling-LiNGAM (pLiNGAM. Using both simulated and real fMRI data, our current study demonstrates the feasibility and efficiency of the pLiNGAM on the effective connectivity estimation.

High performance field emission of silicon carbide nanowires and their applications in flexible field emission displays

Science.gov (United States)

Cui, Yunkang; Chen, Jing; Di, Yunsong; Zhang, Xiaobing; Lei, Wei

2017-12-01

In this paper, a facile method to fabricate the flexible field emission devices (FEDs) based on SiC nanostructure emitters by a thermal evaporation method has been demonstrated. The composition characteristics of SiC nanowires was characterized by X-ray diffraction (XRD), selected area electron diffraction (SAED) and energy dispersive X-ray spectrometer (EDX), while the morphology was revealed by field emission scanning electron microscopy (SEM) and high resolution transmission electron microscopy (HRTEM). The results showed that the SiC nanowires grew along the [111] direction with the diameter of ˜110 nm and length of˜30 μm. The flexible FEDs have been fabricated by transferring and screen-printing the SiC nanowires onto the flexible substrates exhibited excellent field emission properties, such as the low turn-on field (˜0.95 V/μm) and threshold field (˜3.26 V/μm), and the high field enhancement factor (β=4670). It is worth noting the current density degradation can be controlled lower than 2% per hour during the stability tests. In addition, the flexible FEDs based on SiC nanowire emitters exhibit uniform bright emission modes under bending test conditions. As a result, this strategy is very useful for its potential application in the commercial flexible FEDs.

High performance field emission of silicon carbide nanowires and their applications in flexible field emission displays

Directory of Open Access Journals (Sweden)

Yunkang Cui

2017-12-01

Full Text Available In this paper, a facile method to fabricate the flexible field emission devices (FEDs based on SiC nanostructure emitters by a thermal evaporation method has been demonstrated. The composition characteristics of SiC nanowires was characterized by X-ray diffraction (XRD, selected area electron diffraction (SAED and energy dispersive X-ray spectrometer (EDX, while the morphology was revealed by field emission scanning electron microscopy (SEM and high resolution transmission electron microscopy (HRTEM. The results showed that the SiC nanowires grew along the [111] direction with the diameter of ∼110 nm and length of∼30 μm. The flexible FEDs have been fabricated by transferring and screen-printing the SiC nanowires onto the flexible substrates exhibited excellent field emission properties, such as the low turn-on field (∼0.95 V/μm and threshold field (∼3.26 V/μm, and the high field enhancement factor (β=4670. It is worth noting the current density degradation can be controlled lower than 2% per hour during the stability tests. In addition, the flexible FEDs based on SiC nanowire emitters exhibit uniform bright emission modes under bending test conditions. As a result, this strategy is very useful for its potential application in the commercial flexible FEDs.

Presurgical motor, somatosensory and language fMRI: Technical feasibility and limitations in 491 patients over 13 years

International Nuclear Information System (INIS)

Tyndall, Anthony J.; Reinhardt, Julia; Stippich, Christoph; Tronnier, Volker; Mariani, Luigi

2017-01-01

To analyse the long-term feasibility and limitations of presurgical fMRI in a cohort of tumour and epilepsy patients with different MR-scanners at 1.5 and 3.0 T. Four hundred and ninety-one consecutive patients undergoing presurgical fMRI between 2000 and 2012 on five different MR-scanners using established paradigms and semi-automated data processing were included. Success rates of task performance and BOLD-activation were determined for motor and somatosensory somatotopic mapping and language localisation. Procedural success, failures and imaging artifacts were analysed. MR-field strengths were compared. Two thousand three hundred fifteen of 2348 (98.6 %) attempted paradigms (1033 motor, 1220 speech, 95 somatosensory) were successfully performed. 100 paradigms (4.3 %) were repetition runs. 23 speech, 6 motor and 2 sensory paradigms failed for non-compliance and technical issues. Most language paradigm failures were noted in overt sentence generation. Average significant BOLD-activation was higher for motor than language paradigms (95.8 vs. 81.6 %). Most language paradigms showed significantly higher activation rates at 3 T compared to 1.5 T, whereas no significant difference was found for motor paradigms. fMRI proved very robust for the presurgical localisation of the different motor and somatosensory body representations, as well as Broca's and Wernicke's language areas across different MR-scanners at 1.5 and 3.0 T over 13 years. (orig.)

Presurgical motor, somatosensory and language fMRI: Technical feasibility and limitations in 491 patients over 13 years

Energy Technology Data Exchange (ETDEWEB)

Tyndall, Anthony J.; Reinhardt, Julia; Stippich, Christoph [University Hospital Basel, Division of Diagnostic and Interventional Neuroradiology, Basel (Switzerland); Tronnier, Volker [University Hospital Schleswig-Holstein, Luebeck Campus, Department of Neurosurgery, Luebeck (Germany); Mariani, Luigi [University Hospitals Basel, Department of Neurosurgery, Basel (Switzerland)

2017-01-15

To analyse the long-term feasibility and limitations of presurgical fMRI in a cohort of tumour and epilepsy patients with different MR-scanners at 1.5 and 3.0 T. Four hundred and ninety-one consecutive patients undergoing presurgical fMRI between 2000 and 2012 on five different MR-scanners using established paradigms and semi-automated data processing were included. Success rates of task performance and BOLD-activation were determined for motor and somatosensory somatotopic mapping and language localisation. Procedural success, failures and imaging artifacts were analysed. MR-field strengths were compared. Two thousand three hundred fifteen of 2348 (98.6 %) attempted paradigms (1033 motor, 1220 speech, 95 somatosensory) were successfully performed. 100 paradigms (4.3 %) were repetition runs. 23 speech, 6 motor and 2 sensory paradigms failed for non-compliance and technical issues. Most language paradigm failures were noted in overt sentence generation. Average significant BOLD-activation was higher for motor than language paradigms (95.8 vs. 81.6 %). Most language paradigms showed significantly higher activation rates at 3 T compared to 1.5 T, whereas no significant difference was found for motor paradigms. fMRI proved very robust for the presurgical localisation of the different motor and somatosensory body representations, as well as Broca's and Wernicke's language areas across different MR-scanners at 1.5 and 3.0 T over 13 years. (orig.)

Decrease in fMRI brain activation during working memory performed after sleeping under 10 lux light.

Science.gov (United States)

Kang, Seung-Gul; Yoon, Ho-Kyoung; Cho, Chul-Hyun; Kwon, Soonwook; Kang, June; Park, Young-Min; Lee, Eunil; Kim, Leen; Lee, Heon-Jeong

2016-11-09

The aim of this study was to investigate the effect of exposure to dim light at night (dLAN) when sleeping on functional brain activation during a working-memory tasks. We conducted the brain functional magnetic resonance imaging (fMRI) analysis on 20 healthy male subjects. All participants slept in a polysomnography laboratory without light exposure on the first and second nights and under a dim-light condition of either 5 or 10 lux on the third night. The fMRI scanning was conducted during n-back tasks after second and third nights. Statistical parametric maps revealed less activation in the right inferior frontal gyrus (IFG) after exposure to 10-lux light. The brain activity in the right and left IFG areas decreased more during the 2-back task than during the 1- or 0-back task in the 10-lux group. The exposure to 5-lux light had no significant effect on brain activities. The exposure to dLAN might influence the brain function which is related to the cognition.

The role of the DLPFC in inductive reasoning of MCI patients and normal agings: an fMRI study.

Science.gov (United States)

Yang, YanHui; Liang, PeiPeng; Lu, ShengFu; Li, KunCheng; Zhong, Ning

2009-08-01

Previous studies of young people have revealed that the left dorsolateral prefrontal cortex (DLPFC) plays an important role in inductive reasoning. An fMRI experiment was performed in this study to examine whether the left DLPFC was involved in inductive reasoning of MCI patients and normal aging, and whether the activation pattern of this region was different between MCI patients and normal aging. The fMRI results indicated that MCI patients had no difference from normal aging in behavior performance (reaction time and accuracy) and the activation pattern of DLPFC. However, the BOLD response of the DLPFC region for MCI patients was weaker than that for normal aging, and the functional connectivity between the bilateral DLPFC regions for MCI patients was significantly higher than for normal aging. Taken together, these results indicated that DLPFC plays an important role in inductive reasoning of aging, and the functional abnormity of DLPFC may be an earlier marker of MCI before structural alterations.

Log wavelet leaders cumulant based multifractal analysis of EVI fMRI time series: evidence of scaling in ongoing and evoked brain activity

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Ciuciu, P.; Rabrait, C. [CEA, Neuro Spin, Gif Sur Yvette (France); Abry, P.; Wendt, H. [Ecole Normale Super Lyon, Phys Lab, CNRS, UMR 5672, Lyon (France)

2008-07-01

Classical within-subject analysis in functional magnetic resonance imaging (fMRI) relies on a detection step to localize which parts of the brain are activated by a given stimulus type. This is usually achieved using model-based approaches. Here, we propose an alternative exploratory analysis. The originality of this contribution is twofold. First, we propose a synthetic, consistent, and comparative overview of the various stochastic processes and estimation procedures used to model and analyze scale invariance. Notably, it is explained how multifractal models are more versatile to adjust the scaling properties of fMRI data but require more elaborated analysis procedures. Second, we bring evidence of the existence of actual scaling in fMRI time series that are clearly disentangled from putative superimposed non-stationarities. By nature, scaling analysis requires the use of long enough signals with high frequency sampling rate. To this end, we make use of a localized 3-D echo volume imaging (EVI) technique, which has recently emerged in fMRI because it allows very fast acquisitions of successive brain volumes. High temporal resolution EVI fMRI data have been acquired both in resting state and during a slow event-related visual paradigm. A voxel-based systematic multifractal analysis has been performed over both kinds of data. Combining multifractal attribute estimates together with paired statistical tests, we observe significant scaling parameter changes between ongoing and evoked brain activity, which clearly validate an increase in long memory and suggest a global multi-fractality decrease effect under activation. (authors)

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

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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.

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

International Nuclear Information System (INIS)

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

2014-01-01

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

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

Science.gov (United States)

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

2014-10-01

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

Hamstring Muscle Use in Females During Hip-Extension and the Nordic Hamstring Exercise: An fMRI Study.

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Messer, Daniel J; Bourne, Matthew N; Williams, Morgan D; Al Najjar, Aiman; Shield, Anthony J

2018-04-23

Study Design Cross-sectional study. Background Understanding hamstring muscle activation patterns in resistance training exercises may have implications for the design of strength training and injury prevention programs. Unfortunately, surface electromyography studies have reported conflicting results with regard to hamstring muscle activation patterns in women. Objectives To determine the spatial patterns of hamstring muscle activity during the 45º hip-extension and Nordic hamstring exercises, in females using functional magnetic resonance imaging. Methods Six recreationally active females with no history of lower limb injury underwent functional magnetic resonance imaging (fMRI) on both thighs before and immediately after 5 sets of 6 bilateral eccentric contractions of the 45º hip-extension or Nordic exercises. Using fMRI, the transverse (T2) relaxation times were measured from pre- and post- exercise scans and the percentage increase in T2 was used as an index of muscle activation. Results fMRI revealed a significantly higher biceps femoris long head (BF LongHead ) to semitendinosus ratio during the 45° hip-extension than the Nordic exercise (P = .028). The T2 increase after 45° hip-extension was greater for BF LongHead (P Nordic exercise, the T2 increase for semitendinosus was greater than that of BF ShortHead (P Nordic exercise preferentially recruits that muscle while the hip extension more evenly activates all of the biarticular hamstrings. J Orthop Sports Phys Ther, Epub 23 Apr 2018. doi:10.2519/jospt.2018.7748.

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

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

2011-01-01

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

Valence Scaling of Dynamic Facial Expressions Is Altered in High-Functioning Subjects with Autism Spectrum Disorders: An FMRI Study

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Rahko, Jukka S.; Paakki, Jyri-Johan; Starck, Tuomo H.; Nikkinen, Juha; Pauls, David L.; Katsyri, Jari V.; Jansson-Verkasalo, Eira M.; Carter, Alice S.; Hurtig, Tuula M.; Mattila, Marja-Leena; Jussila, Katja K.; Remes, Jukka J.; Kuusikko-Gauffin, Sanna A.; Sams, Mikko E.; Bolte, Sven; Ebeling, Hanna E.; Moilanen, Irma K.; Tervonen, Osmo; Kiviniemi, Vesa

2012-01-01

FMRI was performed with the dynamic facial expressions fear and happiness. This was done to detect differences in valence processing between 25 subjects with autism spectrum disorders (ASDs) and 27 typically developing controls. Valence scaling was abnormal in ASDs. Positive valence induces lower deactivation and abnormally strong activity in ASD…

High-field, high-density tokamak power reactor

International Nuclear Information System (INIS)

Cohn, D.R.; Cook, D.L.; Hay, R.D.; Kaplan, D.; Kreischer, K.; Lidskii, L.M.; Stephany, W.; Williams, J.E.C.; Jassby, D.L.; Okabayashi, M.

1977-11-01

A conceptual design of a compact (R 0 = 6.0 m) high power density (average P/sub f/ = 7.7 MW/m 3 ) tokamak demonstration power reactor has been developed. High magnetic field (B/sub t/ = 7.4 T) and moderate elongation (b/a = 1.6) permit operation at the high density (n(0) approximately 5 x 10 14 cm -3 ) needed for ignition in a relatively small plasma, with a spatially-averaged toroidal beta of only 4%. A unique design for the Nb 3 Sn toroidal-field magnet system reduces the stress in the high-field trunk region, and allows modularization for simpler disassembly. The modest value of toroidal beta permits a simple, modularized plasma-shaping coil system, located inside the TF coil trunk. Heating of the dense central plasma is attained by the use of ripple-assisted injection of 120-keV D 0 beams. The ripple-coil system also affords dynamic control of the plasma temperature during the burn period. A FLIBE-lithium blanket is designed especially for high-power-density operation in a high-field environment, and gives an overall tritium breeding ratio of 1.05 in the slowly pumped lithium

Extending Local Canonical Correlation Analysis to Handle General Linear Contrasts for fMRI Data

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Mingwu Jin

2012-01-01

Full Text Available Local canonical correlation analysis (CCA is a multivariate method that has been proposed to more accurately determine activation patterns in fMRI data. In its conventional formulation, CCA has several drawbacks that limit its usefulness in fMRI. A major drawback is that, unlike the general linear model (GLM, a test of general linear contrasts of the temporal regressors has not been incorporated into the CCA formalism. To overcome this drawback, a novel directional test statistic was derived using the equivalence of multivariate multiple regression (MVMR and CCA. This extension will allow CCA to be used for inference of general linear contrasts in more complicated fMRI designs without reparameterization of the design matrix and without reestimating the CCA solutions for each particular contrast of interest. With the proper constraints on the spatial coefficients of CCA, this test statistic can yield a more powerful test on the inference of evoked brain regional activations from noisy fMRI data than the conventional t-test in the GLM. The quantitative results from simulated and pseudoreal data and activation maps from fMRI data were used to demonstrate the advantage of this novel test statistic.

Identifying musical pieces from fMRI data using encoding and decoding models.

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Hoefle, Sebastian; Engel, Annerose; Basilio, Rodrigo; Alluri, Vinoo; Toiviainen, Petri; Cagy, Maurício; Moll, Jorge

2018-02-02

Encoding models can reveal and decode neural representations in the visual and semantic domains. However, a thorough understanding of how distributed information in auditory cortices and temporal evolution of music contribute to model performance is still lacking in the musical domain. We measured fMRI responses during naturalistic music listening and constructed a two-stage approach that first mapped musical features in auditory cortices and then decoded novel musical pieces. We then probed the influence of stimuli duration (number of time points) and spatial extent (number of voxels) on decoding accuracy. Our approach revealed a linear increase in accuracy with duration and a point of optimal model performance for the spatial extent. We further showed that Shannon entropy is a driving factor, boosting accuracy up to 95% for music with highest information content. These findings provide key insights for future decoding and reconstruction algorithms and open new venues for possible clinical applications.

fMRI evidence of improved visual function in patients with progressive retinitis pigmentosa by eye-movement training.

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Yoshida, Masako; Origuchi, Maki; Urayama, Shin-Ichi; Takatsuki, Akira; Kan, Shigeyuki; Aso, Toshihiko; Shiose, Takayuki; Sawamoto, Nobukatsu; Miyauchi, Satoru; Fukuyama, Hidenao; Seiyama, Akitoshi

2014-01-01

To evaluate changes in the visual processing of patients with progressive retinitis pigmentosa (RP) who acquired improved reading capability by eye-movement training (EMT), we performed functional magnetic resonance imaging (fMRI) before and after EMT. Six patients with bilateral concentric contraction caused by pigmentary degeneration of the retina and 6 normal volunteers were recruited. Patients were given EMT for 5 min every day for 8-10 months. fMRI data were acquired on a 3.0-Tesla scanner while subjects were performing reading tasks. In separate experiments (before fMRI scanning), visual performances for readings were measured by the number of letters read correctly in 5 min. Before EMT, activation areas of the primary visual cortex of patients were 48.8% of those of the controls. The number of letters read correctly in 5 min was 36.6% of those by the normal volunteers. After EMT, the activation areas of patients were not changed or slightly decreased; however, reading performance increased in 5 of 6 patients, which was 46.6% of that of the normal volunteers (p< 0.05). After EMT, increased activity was observed in the frontal eye fields (FEFs) of all patients; however, increases in the activity of the parietal eye fields (PEFs) were observed only in patients who showed greater improvement in reading capability. The improvement in reading ability of the patients after EMT is regarded as an effect of the increased activity of FEF and PEF, which play important roles in attention and working memory as well as the regulation of eye movements.

fMRI evidence of improved visual function in patients with progressive retinitis pigmentosa by eye-movement training

Directory of Open Access Journals (Sweden)

Masako Yoshida

2014-01-01

Full Text Available To evaluate changes in the visual processing of patients with progressive retinitis pigmentosa (RP who acquired improved reading capability by eye-movement training (EMT, we performed functional magnetic resonance imaging (fMRI before and after EMT. Six patients with bilateral concentric contraction caused by pigmentary degeneration of the retina and 6 normal volunteers were recruited. Patients were given EMT for 5 min every day for 8–10 months. fMRI data were acquired on a 3.0-Tesla scanner while subjects were performing reading tasks. In separate experiments (before fMRI scanning, visual performances for readings were measured by the number of letters read correctly in 5 min. Before EMT, activation areas of the primary visual cortex of patients were 48.8% of those of the controls. The number of letters read correctly in 5 min was 36.6% of those by the normal volunteers. After EMT, the activation areas of patients were not changed or slightly decreased; however, reading performance increased in 5 of 6 patients, which was 46.6% of that of the normal volunteers (p< 0.05. After EMT, increased activity was observed in the frontal eye fields (FEFs of all patients; however, increases in the activity of the parietal eye fields (PEFs were observed only in patients who showed greater improvement in reading capability. The improvement in reading ability of the patients after EMT is regarded as an effect of the increased activity of FEF and PEF, which play important roles in attention and working memory as well as the regulation of eye movements.

Neuroimaging of love: fMRI meta-analysis evidence toward new perspectives in sexual medicine.

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Ortigue, Stephanie; Bianchi-Demicheli, Francesco; Patel, Nisa; Frum, Chris; Lewis, James W

2010-11-01

Brain imaging is becoming a powerful tool in the study of human cerebral functions related to close personal relationships. Outside of subcortical structures traditionally thought to be involved in reward-related systems, a wide range of neuroimaging studies in relationship science indicate a prominent role for different cortical networks and cognitive factors. Thus, the field needs a better anatomical/network/whole-brain model to help translate scientific knowledge from lab bench to clinical models and ultimately to the patients suffering from disorders associated with love and couple relationships. The aim of the present review is to provide a review across wide range of functional magnetic resonance imaging (fMRI) studies to critically identify the cortical networks associated with passionate love, and to compare and contrast it with other types of love (such as maternal love and unconditional love for persons with intellectual disabilities). Retrospective review of pertinent neuroimaging literature. Review of published literature on fMRI studies of love illustrating brain regions associated with different forms of love. Although all fMRI studies of love point to the subcortical dopaminergic reward-related brain systems (involving dopamine and oxytocin receptors) for motivating individuals in pair-bonding, the present meta-analysis newly demonstrated that different types of love involve distinct cerebral networks, including those for higher cognitive functions such as social cognition and bodily self-representation. These metaresults provide the first stages of a global neuroanatomical model of cortical networks involved in emotions related to different aspects of love. Developing this model in future studies should be helpful for advancing clinical approaches helpful in sexual medicine and couple therapy. © 2010 International Society for Sexual Medicine.

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

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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.)

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

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

2016-03-01

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

On the plurality of (methodological worlds: Estimating the analytic flexibility of fMRI experiments.

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Joshua eCarp

2012-10-01

Full Text Available How likely are published findings in the functional neuroimaging literature to be false? According to a recent mathematical model, the potential for false positives increases with the flexibility of analysis methods. Functional MRI (fMRI experiments can be analyzed using a large number of commonly used tools, with little consensus on how, when, or whether to apply each one. This situation may lead to substantial variability in analysis outcomes. Thus, the present study sought to estimate the flexibility of neuroimaging analysis by submitting a single event-related fMRI experiment to a large number of unique analysis procedures. Ten analysis steps for which multiple strategies appear in the literature were identified, and two to four strategies were enumerated for each step. Considering all possible combinations of these strategies yielded 6,912 unique analysis pipelines. Activation maps from each pipeline were corrected for multiple comparisons using five thresholding approaches, yielding 34,560 significance maps. While some outcomes were relatively consistent across pipelines, others showed substantial methods-related variability in activation strength, location, and extent. Some analysis decisions contributed to this variability more than others, and different decisions were associated with distinct patterns of variability across the brain. Qualitative outcomes also varied with analysis parameters: many contrasts yielded significant activation under some pipelines but not others. Altogether, these results reveal considerable flexibility in the analysis of fMRI experiments. This observation, when combined with mathematical simulations linking analytic flexibility with elevated false positive rates, suggests that false positive results may be more prevalent than expected in the literature. This risk of inflated false positive rates may be mitigated by constraining the flexibility of analytic choices or by abstaining from selective analysis

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...

Functional Topography of Human Corpus Callosum: An fMRI Mapping Study

OpenAIRE

Fabri, Mara; Polonara, Gabriele

2013-01-01

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

fMRI orientation decoding in V1 does not require global maps or globally coherent orientation stimuli.

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Alink, Arjen; Krugliak, Alexandra; Walther, Alexander; Kriegeskorte, Nikolaus

2013-01-01

The orientation of a large grating can be decoded from V1 functional magnetic resonance imaging (fMRI) data, even at low resolution (3-mm isotropic voxels). This finding has suggested that columnar-level neuronal information might be accessible to fMRI at 3T. However, orientation decodability might alternatively arise from global orientation-preference maps. Such global maps across V1 could result from bottom-up processing, if the preferences of V1 neurons were biased toward particular orientations (e.g., radial from fixation, or cardinal, i.e., vertical or horizontal). Global maps could also arise from local recurrent or top-down processing, reflecting pre-attentive perceptual grouping, attention spreading, or predictive coding of global form. Here we investigate whether fMRI orientation decoding with 2-mm voxels requires (a) globally coherent orientation stimuli and/or (b) global-scale patterns of V1 activity. We used opposite-orientation gratings (balanced about the cardinal orientations) and spirals (balanced about the radial orientation), along with novel patch-swapped variants of these stimuli. The two stimuli of a patch-swapped pair have opposite orientations everywhere (like their globally coherent parent stimuli). However, the two stimuli appear globally similar, a patchwork of opposite orientations. We find that all stimulus pairs are robustly decodable, demonstrating that fMRI orientation decoding does not require globally coherent orientation stimuli. Furthermore, decoding remained robust after spatial high-pass filtering for all stimuli, showing that fine-grained components of the fMRI patterns reflect visual orientations. Consistent with previous studies, we found evidence for global radial and vertical preference maps in V1. However, these were weak or absent for patch-swapped stimuli, suggesting that global preference maps depend on globally coherent orientations and might arise through recurrent or top-down processes related to the perception of

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

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

2009-01-01

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

LLNL high-field coil program

International Nuclear Information System (INIS)

Miller, J.R.

1986-01-01

An overview is presented of the LLNL High-Field Superconducting Magnet Development Program wherein the technology is being developed for producing fields in the range of 15 T and higher for both mirror and tokamak applications. Applications requiring less field will also benefit from this program. In addition, recent results on the thermomechanical performance of cable-in-conduit conductor systems are presented and their importance to high-field coil design discussed

Correlation between MEG and BOLD fMRI signals induced by visual flicker stimuli

Institute of Scientific and Technical Information of China (English)

Chu Renxin; Holroyd Tom; Duyn Jeff

2007-01-01

The goal of this work was to investigate how the MEG signal amplitude correlates with that of BOLD fMRI.To investigate the correlation between fMRI and macroscopic electrical activity, BOLD fMRI and MEG was performed on the same subjects (n =5). A visual flicker stimulus of varying temporal frequency was used to elicit neural responses in early visual areas. A strong similarity was observed in frequency tuning curves between both modalities.Although, averaged over subjects, the BOLD tuning curve was somewhat broader than MEG, both BOLD and MEG had maxima at a flicker frequency of 10 Hz. Also, we measured the first and second harmonic components as the stimuli frequency by MEG. In the low stimuli frequency (less than 6 Hz), the second harmonic has comparable amplitude with the first harmonic, which implies that neural frequency response is nonlinear and has more nonlinear components in low frequency than in high frequency.

fMRI of the motor speech center using EPI

International Nuclear Information System (INIS)

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

1998-01-01

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

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

International Nuclear Information System (INIS)

Feng Jieying; Huang Biao

2013-01-01

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

Self-reflection and the psychosis-prone brain: an fMRI study.

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Modinos, Gemma; Renken, Remco; Ormel, Johan; Aleman, André

2011-05-01

The Cortical Midline Structures (CMS) play a critical role in self-reflection, together with the insula. Abnormalities in self-referential processing and its neural underpinnings have been reported in schizophrenia and at-risk populations, suggesting they might be markers of psychotic vulnerability. Psychometric measures of schizotypal traits may be used to index psychosis proneness (PP) in nonclinical samples. It remains an unresolved question whether differences in self-reflective processing are associated with PP. Six hundred students completed the Community Assessment of Psychic Experiences Questionnaire, positive subscale. Two groups were formed from the extremes of the distribution (total N = 36). fMRI was used to examine CMS/insula function during a self-reflection task. Participants judged personality trait sentences about self and about an acquaintance. High PP subjects attributed less positive traits to others (i.e., acquaintances) than subjects with low PP. Across groups, the contrasts self > semantic and self > other induced activation in CMS and insula, whereas other > semantic did not produce insula activation. Other > self induced posterior cingulate cortex activation in low PP but not in high PP. In addition, high PP subjects showed stronger activation than low PP in left insula during self > semantic. Examining valence effects revealed that high PP individuals showed increased activation in left insula, right dMPFC, and left vMPFC for positive self-related traits, and in bilateral insula, ACC, and right dMPFC for negative self-related traits. The findings suggest that aspects of self-referential processing and underlying brain mechanisms are similar in clinical and subclinical (high PP) forms of psychosis, suggesting that these may be associated with vulnerability to psychosis.

Integrating fMRI with psychophysiological measurements in the study of decision-making

OpenAIRE

Wong, Savio W.H.; Xue, Gui; Bechara, Antoine

2011-01-01

Neuroimaging techniques have recently been used to examine the neural mechanism of decision-making. Nevertheless, most of the neuroimaging studies overlook the importance of emotion and autonomic response in modulating the process of decision-making. In this paper, we discussed how to integrating fMRI with psychophysiological measurements in studying decision-making. We suggested that psychophysiological data would complement with fMRI findings in providing a more comprehensive understanding ...

fMRI for mapping language networks in neurosurgical cases

International Nuclear Information System (INIS)

Gupta, Santosh S

2014-01-01

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

Replicability of time-varying connectivity patterns in large resting state fMRI samples.

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Abrol, Anees; Damaraju, Eswar; Miller, Robyn L; Stephen, Julia M; Claus, Eric D; Mayer, Andrew R; Calhoun, Vince D

2017-12-01

The past few years have seen an emergence of approaches that leverage temporal changes in whole-brain patterns of functional connectivity (the chronnectome). In this chronnectome study, we investigate the replicability of the human brain's inter-regional coupling dynamics during rest by evaluating two different dynamic functional network connectivity (dFNC) analysis frameworks using 7 500 functional magnetic resonance imaging (fMRI) datasets. To quantify the extent to which the emergent functional connectivity (FC) patterns are reproducible, we characterize the temporal dynamics by deriving several summary measures across multiple large, independent age-matched samples. Reproducibility was demonstrated through the existence of basic connectivity patterns (FC states) amidst an ensemble of inter-regional connections. Furthermore, application of the methods to conservatively configured (statistically stationary, linear and Gaussian) surrogate datasets revealed that some of the studied state summary measures were indeed statistically significant and also suggested that this class of null model did not explain the fMRI data fully. This extensive testing of reproducibility of similarity statistics also suggests that the estimated FC states are robust against variation in data quality, analysis, grouping, and decomposition methods. We conclude that future investigations probing the functional and neurophysiological relevance of time-varying connectivity assume critical importance. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

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

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Song, Xiaomu; Chen, Nan-kuei

2014-09-01

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

Classification of fMRI independent components using IC-fingerprints and support vector machine classifiers.

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De Martino, Federico; Gentile, Francesco; Esposito, Fabrizio; Balsi, Marco; Di Salle, Francesco; Goebel, Rainer; Formisano, Elia

2007-01-01

We present a general method for the classification of independent components (ICs) extracted from functional MRI (fMRI) data sets. The method consists of two steps. In the first step, each fMRI-IC is associated with an IC-fingerprint, i.e., a representation of the component in a multidimensional space of parameters. These parameters are post hoc estimates of global properties of the ICs and are largely independent of a specific experimental design and stimulus timing. In the second step a machine learning algorithm automatically separates the IC-fingerprints into six general classes after preliminary training performed on a small subset of expert-labeled components. We illustrate this approach in a multisubject fMRI study employing visual structure-from-motion stimuli encoding faces and control random shapes. We show that: (1) IC-fingerprints are a valuable tool for the inspection, characterization and selection of fMRI-ICs and (2) automatic classifications of fMRI-ICs in new subjects present a high correspondence with those obtained by expert visual inspection of the components. Importantly, our classification procedure highlights several neurophysiologically interesting processes. The most intriguing of which is reflected, with high intra- and inter-subject reproducibility, in one IC exhibiting a transiently task-related activation in the 'face' region of the primary sensorimotor cortex. This suggests that in addition to or as part of the mirror system, somatotopic regions of the sensorimotor cortex are involved in disambiguating the perception of a moving body part. Finally, we show that the same classification algorithm can be successfully applied, without re-training, to fMRI collected using acquisition parameters, stimulation modality and timing considerably different from those used for training.

Simple Fully Automated Group Classification on Brain fMRI

International Nuclear Information System (INIS)

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

2010-01-01

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.

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.

High magnetic field MRI system

International Nuclear Information System (INIS)

Maeda, Hideaki; Urata, Masami; Satoh, Kozo

1990-01-01

A high field superconducting magnet, 4-5 T in central magnetic field, is required for magnetic resonance spectroscopic imaging (MRSI) on 31 P, essential nuclei for energy metabolism of human body. This paper reviews superconducting magnets for high field MRSI systems. Examples of the cross-sectional image and the spectrum of living animals are shown in the paper. (author)

Gender differences in the cognitive control of emotion: An fMRI study.

Science.gov (United States)

Koch, Kathrin; Pauly, Katharina; Kellermann, Thilo; Seiferth, Nina Y; Reske, Martina; Backes, Volker; Stöcker, Tony; Shah, N Jon; Amunts, Katrin; Kircher, Tilo; Schneider, Frank; Habel, Ute

2007-09-20

The interaction of emotion and cognition has become a topic of major interest. However, the influence of gender on the interplay between the two processes, along with its neural correlates have not been fully analysed so far. In this functional magnetic resonance imaging (fMRI) study we induced negative emotion using negative olfactory stimulation while male (n=21) and female (n=19) participants performed an n-back verbal working memory task. Based on findings indicating increased emotional reactivity in women, we expected the female participants to exhibit stronger activation in characteristically emotion-associated areas during the interaction of emotional and cognitive processing in comparison to the male participants. Both groups were found to be significantly impaired in their working memory performance by negative emotion induction. However, fMRI analysis revealed distinct differences in neuronal activation between groups. In men, cognitive performance under negative emotion induction was associated with extended activation patterns in mainly prefrontal and superior parietal regions. In women, the interaction between emotion and working memory yielded a significantly stronger response in the amygdala and the orbitofrontal cortex (OFC) compared to their male counterparts. Our data suggest that in women the interaction of verbal working memory and negative emotion is associated with relative hyperactivation in more emotion-associated areas whereas in men regions commonly regarded as important for cognition and cognitive control are activated. These results provide new insights in gender-specific cerebral mechanisms.

Residual fMRI sensitivity for identity changes in acquired prosopagnosia.

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Fox, Christopher J; Iaria, Giuseppe; Duchaine, Bradley C; Barton, Jason J S

2013-01-01

While a network of cortical regions contribute to face processing, the lesions in acquired prosopagnosia are highly variable, and likely result in different combinations of spared and affected regions of this network. To assess the residual functional sensitivities of spared regions in prosopagnosia, we designed a rapid event-related functional magnetic resonance imaging (fMRI) experiment that included pairs of faces with same or different identities and same or different expressions. By measuring the release from adaptation to these facial changes we determined the residual sensitivity of face-selective regions-of-interest. We tested three patients with acquired prosopagnosia, and all three of these patients demonstrated residual sensitivity for facial identity changes in surviving fusiform and occipital face areas of either the right or left hemisphere, but not in the right posterior superior temporal sulcus. The patients also showed some residual capabilities for facial discrimination with normal performance on the Benton Facial Recognition Test, but impaired performance on more complex tasks of facial discrimination. We conclude that fMRI can demonstrate residual processing of facial identity in acquired prosopagnosia, that this adaptation can occur in the same structures that show similar processing in healthy subjects, and further, that this adaptation may be related to behavioral indices of face perception.

Residual fMRI sensitivity for identity changes in acquired prosopagnosia

Directory of Open Access Journals (Sweden)

Christopher J Fox

2013-10-01

Full Text Available While a network of cortical regions contribute to face processing, the lesions in acquired prosopagnosia are highly variable, and likely result in different combinations of spared and affected regions of this network. To assess the residual functional sensitivities of spared regions in prosopagnosia, we designed a rapid event-related functional magnetic resonance imaging (fMRI experiment that included pairs of faces with same or different identities and same or different expressions. By measuring the release from adaptation to these facial changes we determined the residual sensitivity of face-selective regions-of-interest. We tested three patients with acquired prosopagnosia, and all three of these patients demonstrated residual sensitivity for facial identity changes in surviving fusiform and occipital face areas of either the right or left hemisphere, but not in the right posterior superior temporal sulcus. The patients also showed some residual capabilities for facial discrimination with normal performance on the Benton Facial Recognition Test, but impaired performance on more complex tasks of facial discrimination. We conclude that fMRI can demonstrate residual processing of facial identity in acquired prosopagnosia, that this adaptation can occur in the same structures that show similar processing in healthy subjects, and further, that this adaptation may be related to behavioral indices of face perception.

Effects of hypoglycemia on human brain activation measured with fMRI.

Science.gov (United States)

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

2006-07-01

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

Calibrated fMRI for mapping absolute CMRO2: Practicalities and prospects.

Science.gov (United States)

Germuska, M; Wise, R G

2018-03-29

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

Single Trial Decoding of Belief Decision Making from EEG and fMRI Data Using ICA Features

Directory of Open Access Journals (Sweden)

Pamela eDouglas

2013-07-01

Full Text Available The complex task of assessing the veracity of a statement is thought to activate uniquely distributed brain regions based on whether a subject believes or disbelieves a given assertion. In the current work, we present parallel machine learning methods for predicting a subject’s decision response to a given propositional statement based on independent component (IC features derived from EEG and fMRI data. Our results demonstrate that IC features outperformed features derived from event related spectral perturbations derived from any single spectral band, yet were similar to accuracy across all spectral bands combined. We compared our diagnostic IC spatial maps with our conventional general linear model (GLM results, and found that informative ICs had significant spatial overlap with our GLM results, yet also revealed unique regions like amygdala that were not statistically significant in GLM analyses. Overall, these results suggest that ICs may yield a parsimonious feature set that can be used along with a decision tree structure for interpretation of features used in classifying complex cognitive processes such as belief and disbelief across both fMRI and EEG neuroimaging modalities.

Relational complexity modulates activity in the prefrontal cortex during numerical inductive reasoning: an fMRI study.

Science.gov (United States)

Feng, Xiao; Peng, Li; Chang-Quan, Long; Yi, Lei; Hong, Li

2014-09-01

Most previous studies investigating relational reasoning have used visuo-spatial materials. This fMRI study aimed to determine how relational complexity affects brain activity during inductive reasoning, using numerical materials. Three numerical relational levels of the number series completion task were adopted for use: 0-relational (e.g., "23 23 23"), 1-relational ("32 30 28") and 2-relational ("12 13 15") problems. The fMRI results revealed that the bilateral dorsolateral prefrontal cortex (DLPFC) showed enhanced activity associated with relational complexity. Bilateral inferior parietal lobule (IPL) activity was greater during the 1- and 2-relational level problems than during the 0-relational level problems. In addition, the left fronto-polar cortex (FPC) showed selective activity during the 2-relational level problems. The bilateral DLPFC may be involved in the process of hypothesis generation, whereas the bilateral IPL may be sensitive to calculation demands. Moreover, the sensitivity of the left FPC to the multiple relational problems may be related to the integration of numerical relations. The present study extends our knowledge of the prefrontal activity pattern underlying numerical relational processing. Copyright © 2014 Elsevier B.V. All rights reserved.

An open-source hardware and software system for acquisition and real-time processing of electrophysiology during high field MRI.

Science.gov (United States)

Purdon, Patrick L; Millan, Hernan; Fuller, Peter L; Bonmassar, Giorgio

2008-11-15

Simultaneous recording of electrophysiology and functional magnetic resonance imaging (fMRI) is a technique of growing importance in neuroscience. Rapidly evolving clinical and scientific requirements have created a need for hardware and software that can be customized for specific applications. Hardware may require customization to enable a variety of recording types (e.g., electroencephalogram, local field potentials, or multi-unit activity) while meeting the stringent and costly requirements of MRI safety and compatibility. Real-time signal processing tools are an enabling technology for studies of learning, attention, sleep, epilepsy, neurofeedback, and neuropharmacology, yet real-time signal processing tools are difficult to develop. We describe an open-source system for simultaneous electrophysiology and fMRI featuring low-noise (tested up to 7T), and user-programmable real-time signal processing. The hardware distribution provides the complete specifications required to build an MRI-compatible electrophysiological data acquisition system, including circuit schematics, print circuit board (PCB) layouts, Gerber files for PCB fabrication and robotic assembly, a bill of materials with part numbers, data sheets, and vendor information, and test procedures. The software facilitates rapid implementation of real-time signal processing algorithms. This system has been used in human EEG/fMRI studies at 3 and 7T examining the auditory system, visual system, sleep physiology, and anesthesia, as well as in intracranial electrophysiological studies of the non-human primate visual system during 3T fMRI, and in human hyperbaric physiology studies at depths of up to 300 feet below sea level.

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

Science.gov (United States)

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

2016-01-01

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

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

Directory of Open Access Journals (Sweden)

Tingting Xu

2016-01-01

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

Is negative self-referent bias an endophenotype for depression? An fMRI study of emotional self-referent words in twins at high vs. low risk of depression.

Science.gov (United States)

Miskowiak, K W; Larsen, J E; Harmer, C J; Siebner, H R; Kessing, L V; Macoveanu, J; Vinberg, M

2018-01-15

Negative cognitive bias and aberrant neural processing of self-referent emotional words seem to be trait-marks of depression. However, it is unclear whether these neurocognitive changes are present in unaffected first-degree relatives and constitute an illness endophenotype. Fifty-three healthy, never-depressed monozygotic or dizygotic twins with a co-twin history of depression (high-risk group: n = 26) or no first-degree family history of depression (low-risk group: n = 27) underwent neurocognitive testing and functional magnetic imaging (fMRI) as part of a follow-up cohort study. Participants performed a self-referent emotional word categorisation task and free word recall task followed by a recognition task during fMRI. Participants also completed questionnaires assessing mood, personality traits and coping strategies. High-risk and low-risk twins (age, mean ± SD: 40 ± 11) were well-balanced for demographic variables, mood, coping and neuroticism. High-risk twins showed lower accuracy during self-referent categorisation of emotional words independent of valence and more false recollections of negative words than low-risk twins during free recall. Functional MRI yielded no differences between high-risk and low-risk twins in retrieval-specific neural activity for positive or negative words or during the recognition of negative versus positive words within the hippocampus or prefrontal cortex. The subtle display of negative recall bias is consistent with the hypothesis that self-referent negative memory bias is an endophenotype for depression. High-risk twins' lower categorisation accuracy adds to the evidence for valence-independent cognitive deficits in individuals at familial risk for depression. Copyright © 2017 Elsevier B.V. All rights reserved.

Highly flexible and robust N-doped SiC nanoneedle field emitters

KAUST Repository

Chen, Shanliang

2015-01-23

Flexible field emission (FE) emitters, whose unique advantages are lightweight and conformable, promise to enable a wide range of technologies, such as roll-up flexible FE displays, e-papers and flexible light-emitting diodes. In this work, we demonstrate for the first time highly flexible SiC field emitters with low turn-on fields and excellent emission stabilities. n-Type SiC nanoneedles with ultra-sharp tips and tailored N-doping levels were synthesized via a catalyst-assisted pyrolysis process on carbon fabrics by controlling the gas mixture and cooling rate. The turn-on field, threshold field and current emission fluctuation of SiC nanoneedle emitters with an N-doping level of 7.58 at.% are 1.11 V μm-1, 1.55 V μm-1 and 8.1%, respectively, suggesting the best overall performance for such flexible field emitters. Furthermore, characterization of the FE properties under repeated bending cycles and different bending states reveal that the SiC field emitters are mechanically and electrically robust with unprecedentedly high flexibility and stabilities. These findings underscore the importance of concurrent morphology and composition controls in nanomaterial synthesis and establish SiC nanoneedles as the most promising candidate for flexible FE applications. © 2015 Nature Publishing Group All rights reserved.

Highly flexible and robust N-doped SiC nanoneedle field emitters

KAUST Repository

Chen, Shanliang; Ying, Pengzhan; Wang, Lin; Wei, Guodong; Gao, Fengmei; Zheng, Jinju; Shang, Minhui; Yang, Zuobao; Yang, Weiyou; Wu, Tao

2015-01-01

Flexible field emission (FE) emitters, whose unique advantages are lightweight and conformable, promise to enable a wide range of technologies, such as roll-up flexible FE displays, e-papers and flexible light-emitting diodes. In this work, we demonstrate for the first time highly flexible SiC field emitters with low turn-on fields and excellent emission stabilities. n-Type SiC nanoneedles with ultra-sharp tips and tailored N-doping levels were synthesized via a catalyst-assisted pyrolysis process on carbon fabrics by controlling the gas mixture and cooling rate. The turn-on field, threshold field and current emission fluctuation of SiC nanoneedle emitters with an N-doping level of 7.58 at.% are 1.11 V μm-1, 1.55 V μm-1 and 8.1%, respectively, suggesting the best overall performance for such flexible field emitters. Furthermore, characterization of the FE properties under repeated bending cycles and different bending states reveal that the SiC field emitters are mechanically and electrically robust with unprecedentedly high flexibility and stabilities. These findings underscore the importance of concurrent morphology and composition controls in nanomaterial synthesis and establish SiC nanoneedles as the most promising candidate for flexible FE applications. © 2015 Nature Publishing Group All rights reserved.

Altered fractional amplitude of low frequency fluctuation in premenstrual syndrome: A resting state fMRI study.

Science.gov (United States)

Liao, Hai; Duan, Gaoxiong; Liu, Peng; Liu, Yanfei; Pang, Yong; Liu, Huimei; Tang, Lijun; Tao, Jien; Wen, Danhong; Li, Shasha; Liang, Lingyan; Deng, Demao

2017-08-15

Premenstrual syndrome (PMS) is becoming highly prevalent among female and is characterized by emotional, physical and behavior symptoms. Previous evidence suggested functional dysregulation of female brain was expected to be involved in the etiology of PMS. The aim of present study was to evaluate the alterations of spontaneous brain activity in PMS patients based on functional magnetic resonance imaging (fMRI). 20 PMS patients and 21 healthy controls underwent resting-state fMRI scanning during luteal phase. All participants were asked to complete a prospective daily record of severity of problems (DRSP) questionnaire. Compared with healthy controls, the results showed that PMS patients had increased fALFF in bilateral precuneus, left hippocampus and left inferior temporal cortex, and decreased fALFF in bilateral anterior cingulate cortex (ACC) and cerebellum at luteal phase. Moreover, the DRSP scores of PMS patients were negatively correlated with the mean fALFF in ACC and positively correlated with the fALFF in precuneus. (1) the study did not investigate whether or not abnormal brain activity differences between groups in mid-follicular phase, and within-group changes. between phases.(2) it was relatively limited sample size and the participants were young; (3) fALFF could not provide us with more holistic information of brain network;(4) the comparisons of PMS and premenstrual dysphoric disorder (PMDD) were not involved in the study. The present study shows abnormal spontaneous brain activity in PMS patients revealed by fALFF, which could provide neuroimaging evidence to further improve our understanding of the underlying neural mechanism of PMS. Copyright © 2017. Published by Elsevier B.V.

Specific cerebral activation due to visual erotic stimuli in male-to-female transsexuals compared with male and female controls: an fMRI study.

Science.gov (United States)

Gizewski, Elke R; Krause, Eva; Schlamann, Marc; Happich, Friederike; Ladd, Mark E; Forsting, Michael; Senf, Wolfgang

2009-02-01

Transsexuals harbor the strong feeling of having been born to the wrong sex. There is a continuing controversial discussion of whether or not transsexualism has a biological representation. Differences between males and females in terms of functional imaging during erotic stimuli have been previously described, revealing gender-specific results. Therefore, we postulated that male-to-female (MTF) transsexuals may show specific cerebral activation differing from their biological gender. Cerebral activation patterns during viewing of erotic film excerpts in functional magnetic resonance imaging (fMRI). Twelve male and 12 female heterosexual volunteers and 12 MTF transsexuals before any treatment viewed erotic film excerpts during fMRI. Additionally, subjective rating of sexual arousal was assessed. Statistics were performed using the Statistical Parametric Mapping software. Significantly enhanced activation for men compared with women was revealed in brain areas involved in erotic processing, i.e., the thalamus, the amygdala, and the orbitofrontal and insular cortex, whereas no specific activation for women was found. When comparing MTF transsexuals with male volunteers, activation patterns similar to female volunteers being compared with male volunteers were revealed. Sexual arousal was assessed using standard rating scales and did not differ significantly for the three groups. We revealed a cerebral activation pattern in MTF transsexuals compared with male controls similar to female controls compared with male controls during viewing of erotic stimuli, indicating a tendency of female-like cerebral processing in transsexualism.

Neural reactivity to visual food stimuli is reduced in some areas of the brain during evening hours compared to morning hours: an fMRI study in women.

Science.gov (United States)

Masterson, Travis D; Kirwan, C Brock; Davidson, Lance E; LeCheminant, James D

2016-03-01

The extent that neural responsiveness to visual food stimuli is influenced by time of day is not well examined. Using a crossover design, 15 healthy women were scanned using fMRI while presented with low- and high-energy pictures of food, once in the morning (6:30-8:30 am) and once in the evening (5:00-7:00 pm). Diets were identical on both days of the fMRI scans and were verified using weighed food records. Visual analog scales were used to record subjective perception of hunger and preoccupation with food prior to each fMRI scan. Six areas of the brain showed lower activation in the evening to both high- and low-energy foods, including structures in reward pathways (P foods compared to low-energy foods (P food stimuli tended to produce greater fMRI responses than low-energy food stimuli in specific areas of the brain, regardless of time of day. However, evening scans showed a lower response to both low- and high-energy food pictures in some areas of the brain. Subjectively, participants reported no difference in hunger by time of day (F = 1.84, P = 0.19), but reported they could eat more (F = 4.83, P = 0.04) and were more preoccupied with thoughts of food (F = 5.51, P = 0.03) in the evening compared to the morning. These data underscore the role that time of day may have on neural responses to food stimuli. These results may also have clinical implications for fMRI measurement in order to prevent a time of day bias.

P300 amplitude variation is related to ventral striatum BOLD response during gain and loss anticipation: an EEG and fMRI experiment.

Science.gov (United States)

Pfabigan, Daniela M; Seidel, Eva-Maria; Sladky, Ronald; Hahn, Andreas; Paul, Katharina; Grahl, Arvina; Küblböck, Martin; Kraus, Christoph; Hummer, Allan; Kranz, Georg S; Windischberger, Christian; Lanzenberger, Rupert; Lamm, Claus

2014-08-01

The anticipation of favourable or unfavourable events is a key component in our daily life. However, the temporal dynamics of anticipation processes in relation to brain activation are still not fully understood. A modified version of the monetary incentive delay task was administered during separate functional magnetic resonance imaging (fMRI) and electroencephalogram (EEG) sessions in the same 25 participants to assess anticipatory processes with a multi-modal neuroimaging set-up. During fMRI, gain and loss anticipation were both associated with heightened activation in ventral striatum and reward-related areas. EEG revealed most pronounced P300 amplitudes for gain anticipation, whereas CNV amplitudes distinguished neutral from gain and loss anticipation. Importantly, P300, but not CNV amplitudes, were correlated to neural activation in the ventral striatum for both gain and loss anticipation. Larger P300 amplitudes indicated higher ventral striatum blood oxygen level dependent (BOLD) response. Early stimulus evaluation processes indexed by EEG seem to be positively related to higher activation levels in the ventral striatum, indexed by fMRI, which are usually associated with reward processing. The current results, however, point towards a more general motivational mechanism processing salient stimuli during anticipation. Copyright © 2014. Published by Elsevier Inc.

An Emotional Go/No-Go fMRI study in adolescents with depressive symptoms following concussion.

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Ho, Rachelle A; Hall, Geoffrey B; Noseworthy, Michael D; DeMatteo, Carol

2017-10-03

Following concussion, adolescents may experience both poor inhibitory control and increased depressive symptoms. fMRI research suggests that adolescents with major depressive disorder have abnormal physiological responses in the frontostriatal pathway, and exhibit poorer inhibitory control in the presence of negatively-aroused images. The scarcity of information surrounding depression following concussion in adolescents makes it difficult to identify patients at risk of depression after injury. This is the first study to examine neural activity patterns in adolescents with post-concussive depressive symptoms. To explore the effect of depressive symptoms on inhibitory control in adolescents with concussion in the presence of emotional stimuli using fMRI. Using a prospective cohort design, 30 adolescents diagnosed with concussion between 10 and 17years were recruited. The Children's Depression Inventory questionnaire was used to divide participants into two groups: average or elevated levels of depressive symptoms. Participants completed an Emotional Go/No-Go task involving angry or neutral faces in a 3Telsa MRI scanner. Eleven participants had elevated depressive symptoms, of which 72% were hit in the occipital region of the head at the time of injury. fMRI results from the Emotional Go/No-Go task revealed activity patterns in the overall sample. Faces activated regions associated with both facial and cognitive processing. However, frontal regions that are usually associated with inhibitory control were not activated. Adolescents with elevated levels of depressive symptoms engaged more frontal lobe regions during the task than the average group. They also showed a trend towards worse symptoms following MRI scanning. Adolescents with elevated depressive symptoms engaged brain regions subserving evaluative processing of social interactions. This finding provides insight into the role the environment plays in contributing to the cognitive demands placed on adolescents

Key issues in decomposing fMRI during naturalistic and continuous music experience with independent component analysis.

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Cong, Fengyu; Puoliväli, Tuomas; Alluri, Vinoo; Sipola, Tuomo; Burunat, Iballa; Toiviainen, Petri; Nandi, Asoke K; Brattico, Elvira; Ristaniemi, Tapani

2014-02-15

Independent component analysis (ICA) has been often used to decompose fMRI data mostly for the resting-state, block and event-related designs due to its outstanding advantage. For fMRI data during free-listening experiences, only a few exploratory studies applied ICA. For processing the fMRI data elicited by 512-s modern tango, a FFT based band-pass filter was used to further pre-process the fMRI data to remove sources of no interest and noise. Then, a fast model order selection method was applied to estimate the number of sources. Next, both individual ICA and group ICA were performed. Subsequently, ICA components whose temporal courses were significantly correlated with musical features were selected. Finally, for individual ICA, common components across majority of participants were found by diffusion map and spectral clustering. The extracted spatial maps (by the new ICA approach) common across most participants evidenced slightly right-lateralized activity within and surrounding the auditory cortices. Meanwhile, they were found associated with the musical features. Compared with the conventional ICA approach, more participants were found to have the common spatial maps extracted by the new ICA approach. Conventional model order selection methods underestimated the true number of sources in the conventionally pre-processed fMRI data for the individual ICA. Pre-processing the fMRI data by using a reasonable band-pass digital filter can greatly benefit the following model order selection and ICA with fMRI data by naturalistic paradigms. Diffusion map and spectral clustering are straightforward tools to find common ICA spatial maps. Copyright © 2013 Elsevier B.V. All rights reserved.

Magnetic quantum tunneling: key insights from multi-dimensional high-field EPR.

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Lawrence, J; Yang, E-C; Hendrickson, D N; Hill, S

2009-08-21

Multi-dimensional high-field/frequency electron paramagnetic resonance (HFEPR) spectroscopy is performed on single-crystals of the high-symmetry spin S = 4 tetranuclear single-molecule magnet (SMM) [Ni(hmp)(dmb)Cl](4), where hmp(-) is the anion of 2-hydroxymethylpyridine and dmb is 3,3-dimethyl-1-butanol. Measurements performed as a function of the applied magnetic field strength and its orientation within the hard-plane reveal the four-fold behavior associated with the fourth order transverse zero-field splitting (ZFS) interaction, (1/2)B(S + S), within the framework of a rigid spin approximation (with S = 4). This ZFS interaction mixes the m(s) = +/-4 ground states in second order of perturbation, generating a sizeable (12 MHz) tunnel splitting, which explains the fast magnetic quantum tunneling in this SMM. Meanwhile, multi-frequency measurements performed with the field parallel to the easy-axis reveal HFEPR transitions associated with excited spin multiplets (S spin s = 1 Ni(II) ions within the cluster, as well as a characterization of the ZFS within excited states. The combined experimental studies support recent work indicating that the fourth order anisotropy associated with the S = 4 state originates from second order ZFS interactions associated with the individual Ni(II) centers, but only as a result of higher-order processes that occur via S-mixing between the ground state and higher-lying (S spin multiplets. We argue that this S-mixing plays an important role in the low-temperature quantum dynamics associated with many other well known SMMs.

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...

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...

Brain activity changes in cognitive networks in relapsing-remitting multiple sclerosis - insights from a longitudinal FMRI study.

Directory of Open Access Journals (Sweden)

Marisa Loitfelder

Full Text Available BACKGROUND: Extrapolations from previous cross-sectional fMRI studies suggest cerebral functional changes with progression of Multiple Sclerosis (MS, but longitudinal studies are scarce. We assessed brain activation changes over time in MS patients using a cognitive fMRI paradigm and examined correlations with clinical and cognitive status and brain morphology. METHODS: 13 MS patients and 15 healthy controls (HC underwent MRI including fMRI (go/no-go task, neurological and neuropsychological exams at baseline (BL and follow-up (FU; minimum 12, median 20 months. We assessed estimates of and changes in fMRI activation, total brain and subcortical grey matter volumes, cortical thickness, and T2-lesion load. Bland-Altman (BA plots served to assess fMRI signal variability. RESULTS: Cognitive and disability levels remained largely stable in the patients. With the fMRI task, both at BL and FU, patients compared to HC showed increased activation in the insular cortex, precuneus, cerebellum, posterior cingulate cortex, and occipital cortex. At BL, patients vs. HC also had lower caudate nucleus, thalamus and putamen volumes. Over time, patients (but not HC demonstrated fMRI activity increments in the left inferior parietal lobule. These correlated with worse single-digit-modality test (SDMT performance. BA-plots attested to reproducibility of the fMRI task. In the patients, the right caudate nucleus decreased in volume which again correlated with worsening SDMT performance. CONCLUSIONS: Given preserved cognitive performance, the increased activation at BL in the patients may be viewed as largely adaptive. In contrast, the negative correlation with SDMT performance suggests increasing parietal activation over time to be maladaptive. Several areas with purported relevance for cognition showed decreased volumes at BL and right caudate nucleus volume decline correlated with decreasing SDMT performance. This highlights the dynamics of functional changes and

Brain activity changes in cognitive networks in relapsing-remitting multiple sclerosis - insights from a longitudinal FMRI study.

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Loitfelder, Marisa; Fazekas, Franz; Koschutnig, Karl; Fuchs, Siegrid; Petrovic, Katja; Ropele, Stefan; Pichler, Alexander; Jehna, Margit; Langkammer, Christian; Schmidt, Reinhold; Neuper, Christa; Enzinger, Christian

2014-01-01

Extrapolations from previous cross-sectional fMRI studies suggest cerebral functional changes with progression of Multiple Sclerosis (MS), but longitudinal studies are scarce. We assessed brain activation changes over time in MS patients using a cognitive fMRI paradigm and examined correlations with clinical and cognitive status and brain morphology. 13 MS patients and 15 healthy controls (HC) underwent MRI including fMRI (go/no-go task), neurological and neuropsychological exams at baseline (BL) and follow-up (FU; minimum 12, median 20 months). We assessed estimates of and changes in fMRI activation, total brain and subcortical grey matter volumes, cortical thickness, and T2-lesion load. Bland-Altman (BA) plots served to assess fMRI signal variability. Cognitive and disability levels remained largely stable in the patients. With the fMRI task, both at BL and FU, patients compared to HC showed increased activation in the insular cortex, precuneus, cerebellum, posterior cingulate cortex, and occipital cortex. At BL, patients vs. HC also had lower caudate nucleus, thalamus and putamen volumes. Over time, patients (but not HC) demonstrated fMRI activity increments in the left inferior parietal lobule. These correlated with worse single-digit-modality test (SDMT) performance. BA-plots attested to reproducibility of the fMRI task. In the patients, the right caudate nucleus decreased in volume which again correlated with worsening SDMT performance. Given preserved cognitive performance, the increased activation at BL in the patients may be viewed as largely adaptive. In contrast, the negative correlation with SDMT performance suggests increasing parietal activation over time to be maladaptive. Several areas with purported relevance for cognition showed decreased volumes at BL and right caudate nucleus volume decline correlated with decreasing SDMT performance. This highlights the dynamics of functional changes and the strategic importance of specific brain areas for

Tokamak-like confinement at high beta and low field in the reversed field pinch

International Nuclear Information System (INIS)

Sarff, J S; Anderson, J K; Biewer, T M; Brower, D L; Chapman, B E; Chattopadhyay, P K; Craig, D; Deng, B; Hartog, D J Den; Ding, W X; Fiksel, G; Forest, C B; Goetz, J A; O'Connell, R; Prager, S C; Thomas, M A

2003-01-01

For several reasons, improved-confinement achieved in the reversed field pinch (RFP) during the last few years can be characterized as 'tokamak-like'. Historically, RFP plasmas have had relatively poor confinement due to tearing instability which causes magnetic stochasticity and enhanced transport. Tearing reduction is achieved through modification of the inductive current drive, which dramatically improves confinement. The electron temperature increases to >1 keV and the electron heat diffusivity decreases to approx. 5 m 2 s -1 , comparable with the transport level expected in a tokamak plasma of the same size and current. This corresponds to a 10-fold increase in global energy confinement. Runaway electrons are confined, and Fokker-Planck modelling of the electron distribution reveals that the diffusion at high energy is independent of the parallel velocity, uncharacteristic of stochastic transport. Improved-confinement occurs simultaneously with increased beta approx. 15%, while maintaining a magnetic field strength ten times weaker than a comparable tokamak. Measurements of the current, magnetic, and electric field profiles show that a simple Ohm's Law applies to this RFP sustained without dynamo relaxation

Resting-State fMRI in MS: General Concepts and Brief Overview of Its Application

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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.

Auditory-motor interaction revealed by fMRI: speech, music, and working memory in area Spt.

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Hickok, Gregory; Buchsbaum, Bradley; Humphries, Colin; Muftuler, Tugan

2003-07-01

The concept of auditory-motor interaction pervades speech science research, yet the cortical systems supporting this interface have not been elucidated. Drawing on experimental designs used in recent work in sensory-motor integration in the cortical visual system, we used fMRI in an effort to identify human auditory regions with both sensory and motor response properties, analogous to single-unit responses in known visuomotor integration areas. The sensory phase of the task involved listening to speech (nonsense sentences) or music (novel piano melodies); the "motor" phase of the task involved covert rehearsal/humming of the auditory stimuli. A small set of areas in the superior temporal and temporal-parietal cortex responded both during the listening phase and the rehearsal/humming phase. A left lateralized region in the posterior Sylvian fissure at the parietal-temporal boundary, area Spt, showed particularly robust responses to both phases of the task. Frontal areas also showed combined auditory + rehearsal responsivity consistent with the claim that the posterior activations are part of a larger auditory-motor integration circuit. We hypothesize that this circuit plays an important role in speech development as part of the network that enables acoustic-phonetic input to guide the acquisition of language-specific articulatory-phonetic gestures; this circuit may play a role in analogous musical abilities. In the adult, this system continues to support aspects of speech production, and, we suggest, supports verbal working memory.

Music Therapy Using Singing Training Improves Psychomotor Speed in Patients with Alzheimer's Disease: A Neuropsychological and fMRI Study

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Satoh, Masayuki; Yuba, Toru; Tabei, Ken-ichi; Okubo, Yukari; Kida, Hirotaka; Sakuma, Hajime; Tomimoto, Hidekazu

2015-01-01

Background/Aims To investigate the effect of singing training on the cognitive function in Alzheimer's disease (AD) patients. Methods Ten AD patients (mean age 78.1 years) participated in music therapy using singing training once a week for 6 months (music therapy group). Each session was performed with professional musicians using karaoke and a unique voice training method (the YUBA Method). Before and after the intervention period, each patient was assessed by neuropsychological batteries, and functional magnetic resonance imaging (fMRI) was performed while the patients sang familiar songs with a karaoke device. As the control group, another 10 AD patients were recruited (mean age 77.0 years), and neuropsychological assessments were performed twice with an interval of 6 months. Results In the music therapy group, the time for completion of the Japanese Raven's Colored Progressive Matrices was significantly reduced (p = 0.026), and the results obtained from interviewing the patients' caregivers revealed a significant decrease in the Neuropsychiatric Inventory score (p = 0.042) and a prolongation of the patients' sleep time (p = 0.039). The fMRI study revealed increased activity in the right angular gyrus and the left lingual gyrus in the before-minus-after subtraction analysis of the music therapy intervention. Conclusion Music therapy intervention using singing training may be useful for dementia patients by improving the neural efficacy of cognitive processing. PMID:26483829

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

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

2005-11-01

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

High-Field Accelerator Magnets

International Nuclear Information System (INIS)

Rijk, G de

2014-01-01

In this lecture an overview is given of the present technology for high field accelerator magnets. We indicate how to get high fields and what are the most important parameters. The available conductors and their limitations are presented followed by the most relevant types of coils and support structures. We conclude by showing a number of recent examples of development magnets which are either pure R&D objects or models for the LHC luminosity upgrade

Can Harry Potter still put a spell on us in a second language? An fMRI study on reading emotion-laden literature in late bilinguals.

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Hsu, Chun-Ting; Jacobs, Arthur M; Conrad, Markus

2015-02-01

In this fMRI study we contrasted emotional responses to literary reading in late bilinguals' first or second language. German participants with adequate English proficiency in their second language (L2) English read short text passages from Harry Potter books characterized by a "negative" or "positive" versus "neutral" emotional valence manipulation. Previous studies have suggested that given sufficient L2 proficiency, neural substrates involved in L1 versus L2 do not differ (Fabbro, 2001). On the other hand, the question of attenuated emotionality of L2 language processing is still an open debate (see Conrad, Recio, & Jacobs, 2011). Our results revealed a set of neural structures involved in the processing of emotion-laden literature, including emotion-related amygdala and a set of lateral prefrontal, anterior temporal, and temporo-parietal regions associated with discourse comprehension, high-level semantic integration, and Theory-of-Mind processing. Yet, consistent with post-scan emotion ratings of text passages, factorial fMRI analyses revealed stronger hemodynamic responses to "happy" than to "neutral" in bilateral amygdala and the left precentral cortex that were restricted to L1 reading. Furthermore, multivariate pattern analyses (MVPA) demonstrated better classifiability of differential patterns of brain activity elicited by passages of different emotional content in L1 than in L2 for the whole brain level. Overall, our results suggest that reading emotion-laden texts in our native language provides a stronger and more differentiated emotional experience than reading in a second language. Copyright © 2014 Elsevier Ltd. All rights reserved.

Ultra high field magnetic resonance imaging

International Nuclear Information System (INIS)

Lethimonnier, F.; Vedrine, P.

2007-01-01

Understanding human brain function, brain development and brain dysfunction is one of the great challenges of the twenty first century. Biomedical imaging has now run up against a number of technical constraints that are exposing limits to its potential. In order to overcome the current limits to high-field magnetic resonance cerebral imaging (MRI) and unleash its fullest potential, the Cea has built NeuroSpin, an ultra-high-field neuroimaging facility at its Saclay centre (in the Essonne). NeuroSpin already boasts three fully operational MRI systems. The first is a 3-tesla high-field system and the second is a very-high-field 7-tesla system, both of which are dedicated to clinical studies and investigations in humans, while the third is an ultra-high-field 17.65-tesla system designed for studies on small animals. In 2011, NeuroSpin will be commissioning an 11.7-tesla ultra-high-field system of unprecedented power that is designed for research on human subjects. The level of the magnetic field and the scale required will make this joint French-German project to build the magnet a breakthrough in the international arena. (authors)

Further dissociating the processes involved in recognition memory: an FMRI study.

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Henson, Richard N A; Hornberger, Michael; Rugg, Michael D

2005-07-01

Based on an event-related potential study by Rugg et al. [Dissociation of the neural correlates of implicit and explicit memory. Nature, 392, 595-598, 1998], we attempted to isolate the hemodynamic correlates of recollection, familiarity, and implicit memory within a single verbal recognition memory task using event-related fMRI. Words were randomly cued for either deep or shallow processing, and then intermixed with new words for yes/no recognition. The number of studied words was such that, whereas most were recognized ("hits"), an appreciable number of shallow-studied words were not ("misses"). Comparison of deep hits versus shallow hits at test revealed activations in regions including the left inferior parietal gyrus. Comparison of shallow hits versus shallow misses revealed activations in regions including the bilateral intraparietal sulci, the left posterior middle frontal gyrus, and the left frontopolar cortex. Comparison of hits versus correct rejections revealed a relative deactivation in an anterior left medial-temporal region (most likely the perirhinal cortex). Comparison of shallow misses versus correct rejections did not reveal response decreases in any regions expected on the basis of previous imaging studies of priming. Given these and previous data, we associate the left inferior parietal activation with recollection, the left anterior medial-temporal deactivation with familiarity, and the intraparietal and prefrontal responses with target detection. The absence of differences between shallow misses and correct rejections means that the hemodynamic correlates of implicit memory remain unclear.

Three-dimensional brain mapping using fMRI

International Nuclear Information System (INIS)

Fukunaga, Masaki; Tanaka, Chuzo; Umeda, Masahiro; Ebisu, Toshihiko; Aoki, Ichio; Higuchi, Toshihiro; Naruse, Shoji.

1997-01-01

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)

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

International Nuclear Information System (INIS)

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

2002-01-01

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

Testing competing hypotheses about single trial fMRI

DEFF Research Database (Denmark)

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

2002-01-01

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

High-field EPR on membrane proteins - crossing the gap to NMR.

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Möbius, Klaus; Lubitz, Wolfgang; Savitsky, Anton

2013-11-01

In this review on advanced EPR spectroscopy, which addresses both the EPR and NMR communities, considerable emphasis is put on delineating the complementarity of NMR and EPR concerning the measurement of molecular interactions in large biomolecules. From these interactions, detailed information can be revealed on structure and dynamics of macromolecules embedded in solution- or solid-state environments. New developments in pulsed microwave and sweepable cryomagnet technology as well as ultrafast electronics for signal data handling and processing have pushed to new horizons the limits of EPR spectroscopy and its multifrequency extensions concerning the sensitivity of detection, the selectivity with respect to interactions, and the resolution in frequency and time domains. One of the most important advances has been the extension of EPR to high magnetic fields and microwave frequencies, very much in analogy to what happens in NMR. This is exemplified by referring to ongoing efforts for signal enhancement in both NMR and EPR double-resonance techniques by exploiting dynamic nuclear or electron spin polarization via unpaired electron spins and their electron-nuclear or electron-electron interactions. Signal and resolution enhancements are particularly spectacular for double-resonance techniques such as ENDOR and PELDOR at high magnetic fields. They provide greatly improved orientational selection for disordered samples that approaches single-crystal resolution at canonical g-tensor orientations - even for molecules with small g-anisotropies. Exchange of experience between the EPR and NMR communities allows for handling polarization and resolution improvement strategies in an optimal manner. Consequently, a dramatic improvement of EPR detection sensitivity could be achieved, even for short-lived paramagnetic reaction intermediates. Unique structural and dynamic information is thus revealed that can hardly be obtained by any other analytical techniques. Micromolar

fMRI and brain activation after sport concussion: a tale of two cases

Directory of Open Access Journals (Sweden)

Michael G Hutchison

2014-04-01

Full Text Available Sport-related concussions are now recognized as a major public health concern: The number of participants in sport and recreation is growing, possibly playing their games faster, and there is heightened public awareness of injuries to some high-profile athletes. However, many clinicians still rely on subjective symptom reports for the clinical determination of recovery. Relying on subjective symptom reports can be dangerous, as it has been shown that some concussed athletes may downplay their symptoms. The use of neuropsychological (NP testing tools has enabled clinicians to measure the effects and extent of impairment following concussion more precisely, providing more objective metrics for determining recovery after concussion. Nevertheless, there is a remaining concern that brain abnormalities may exist beyond the point at which individuals achieve recovery in self-reported symptoms and cognition measured by NP testing. Our understanding of brain recovery after concussion is important not only from a neuroscience perspective, but also from the perspective of clinical decision making for safe return-to-play (RTP. A number of advanced neuroimaging tools, including blood oxygen level dependent (BOLD functional magnetic resonance imaging (fMRI, have independently yielded early information on these abnormal brain functions. In the two cases presented in this article, we report contrasting brain activation patterns and recovery profiles using fMRI. Importantly, fMRI was conducted using adapted versions of the most sensitive computerized NP tests administered in current clinical practice to determine impairments and recovery after sport-related concussion. One of the cases is consistent with the concept of lagging brain recovery.

Integration of EEG source imaging and fMRI during continuous viewing of natural movies.

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Whittingstall, Kevin; Bartels, Andreas; Singh, Vanessa; Kwon, Soyoung; Logothetis, Nikos K

2010-10-01

estimate of the current density at every time point. We then carried out a correlation between the time series of visual contrast changes in the movie with that of EEG voxels. We found the most significant correlations in visual area V1, just as seen in previous fMRI studies (Bartels A, Zeki, S, Logothetis NK. Natural vision reveals regional specialization to local motion and to contrast-invariant, global flow in the human brain. Cereb Cortex 2008;18(3):705-717), but on the time scale of milliseconds rather than of seconds. To obtain an estimate of how the EEG signal relates to the BOLD signal, we calculated the IRF between the BOLD signal and the estimated current density in area V1. We found that this IRF was very similar to that observed using combined intracortical recordings and fMRI experiments in nonhuman primates. Taken together, these findings open a new approach to noninvasive mapping of the brain. It allows, firstly, the localization of feature-selective brain areas during natural viewing conditions with the temporal resolution of EEG. Secondly, it provides a tool to assess EEG/BOLD transfer functions during processing of more natural stimuli. This is especially useful in combined EEG/fMRI experiments, where one can now potentially study neural-hemodynamic relationships across the whole brain volume in a noninvasive manner. Copyright © 2010 Elsevier Inc. All rights reserved.

A spatio-temporal nonparametric Bayesian variable selection model of fMRI data for clustering correlated time courses.

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Zhang, Linlin; Guindani, Michele; Versace, Francesco; Vannucci, Marina

2014-07-15

In this paper we present a novel wavelet-based Bayesian nonparametric regression model for the analysis of functional magnetic resonance imaging (fMRI) data. Our goal is to provide a joint analytical framework that allows to detect regions of the brain which exhibit neuronal activity in response to a stimulus and, simultaneously, infer the association, or clustering, of spatially remote voxels that exhibit fMRI time series with similar characteristics. We start by modeling the data with a hemodynamic response function (HRF) with a voxel-dependent shape parameter. We detect regions of the brain activated in response to a given stimulus by using mixture priors with a spike at zero on the coefficients of the regression model. We account for the complex spatial correlation structure of the brain by using a Markov random field (MRF) prior on the parameters guiding the selection of the activated voxels, therefore capturing correlation among nearby voxels. In order to infer association of the voxel time courses, we assume correlated errors, in particular long memory, and exploit the whitening properties of discrete wavelet transforms. Furthermore, we achieve clustering of the voxels by imposing a Dirichlet process (DP) prior on the parameters of the long memory process. For inference, we use Markov Chain Monte Carlo (MCMC) sampling techniques that combine Metropolis-Hastings schemes employed in Bayesian variable selection with sampling algorithms for nonparametric DP models. We explore the performance of the proposed model on simulated data, with both block- and event-related design, and on real fMRI data. Copyright © 2014 Elsevier Inc. All rights reserved.

Reorganization of Language Areas in Patient with a Frontal Lobe Low Grade Glioma – fMRI Case Study

International Nuclear Information System (INIS)

Kośla, Katarzyna; Bryszewski, Bartosz; Jaskólski, Dariusz; Błasiak-Kołacińska, Nina; Stefańczyk, Ludomir; Majos, Agata

2015-01-01

Functional magnetic resonance (fMRI) studies results in case of an adult patient with low grade glioma (LGG) in dominant hemisphere suggest brain plasticity process with acquisition of language functions by the non-dominant hemisphere speech regions. A 36-years old right-handed woman was admitted to the Department of Neurosurgery for surgical treatment of brain tumor. An MRI examination revealed a pathological mass in the left frontal lobe, in close topographical relationship to the Broca’s area. A left fronto-parietal craniotomy was performed, with an intraoperative awake language mapping procedure. A total resection of the pathological mass was achieved. The tumor was examined histologically as LGG. In the follow-up MRI exam 32 months after the operation a tumor recurrence was suggested. The fMRI exams performed preoperative and 3, 32 and 41 months after the operation showed changes in language regions activation patterns, with a progressive right-sided activation of Broca’s and Wernicke’s areas. Pre- and postoperative cognitive evaluation by a neuropsychologist did not detect any language impairment. We present a running process of reorganization of language areas in a patient after brain tumor resection, from strong left-sided to symmetrical lateralization. 1. FMRI results in comparison with the psychological status of the patient proved contribution of functional reorganization to the preservation of language performance. 2. A slow growing LGG as well as the recurrence of the tumor near the left Broca’s area might be the factors leading to reorganization of language-related areas by recruiting the right hemisphe

Single-trial EEG-informed fMRI reveals spatial dependency of BOLD signal on early and late IC-ERP amplitudes during face recognition.

Science.gov (United States)

Wirsich, Jonathan; Bénar, Christian; Ranjeva, Jean-Philippe; Descoins, Médéric; Soulier, Elisabeth; Le Troter, Arnaud; Confort-Gouny, Sylviane; Liégeois-Chauvel, Catherine; Guye, Maxime

2014-10-15

Simultaneous EEG-fMRI has opened up new avenues for improving the spatio-temporal resolution of functional brain studies. However, this method usually suffers from poor EEG quality, especially for evoked potentials (ERPs), due to specific artifacts. As such, the use of EEG-informed fMRI analysis in the context of cognitive studies has particularly focused on optimizing narrow ERP time windows of interest, which ignores the rich diverse temporal information of the EEG signal. Here, we propose to use simultaneous EEG-fMRI to investigate the neural cascade occurring during face recognition in 14 healthy volunteers by using the successive ERP peaks recorded during the cognitive part of this process. N170, N400 and P600 peaks, commonly associated with face recognition, were successfully and reproducibly identified for each trial and each subject by using a group independent component analysis (ICA). For the first time we use this group ICA to extract several independent components (IC) corresponding to the sequence of activation and used single-trial peaks as modulation parameters in a general linear model (GLM) of fMRI data. We obtained an occipital-temporal-frontal stream of BOLD signal modulation, in accordance with the three successive IC-ERPs providing an unprecedented spatio-temporal characterization of the whole cognitive process as defined by BOLD signal modulation. By using this approach, the pattern of EEG-informed BOLD modulation provided improved characterization of the network involved than the fMRI-only analysis or the source reconstruction of the three ERPs; the latter techniques showing only two regions in common localized in the occipital lobe. Copyright © 2014 Elsevier Inc. All rights reserved.

High-magnetic field atomic physics

International Nuclear Information System (INIS)

Gay, J.C.

1984-01-01

This chapter discusses both the traditional developments of Zeeman techniques at strong fields and the fundamental concepts of diamagnetism. Topics considered include historical aspects, the production of high fields, the atom in a magnetic field (Hamiltonian and symmetries, the various magnetic regimes in atomic spectra), applications of the Zeeman effect at strong B fields, the Landau regime for loosely bound particles, theoretical concepts of atomic diamagnetism, and the ultra-high-field regime and quantum electrodynamics. It is concluded that the wide implications of the problem of the strongly magnetized hydrogen atom in various domains of physics and its conceptual importance concerning theoretical methods of classical and quantum mechanics justify the experimental and theoretical efforts in atomic physics

Pulsed-High Field/High-Frequency EPR Spectroscopy

Science.gov (United States)

Fuhs, Michael; Moebius, Klaus

Pulsed high-field/high-frequency electron paramagnetic resonance (EPR) spectroscopy is used to disentangle many kinds of different effects often obscured in continuous wave (cw) EPR spectra at lower magnetic fields/microwave frequencies. While the high magnetic field increases the resolution of G tensors and of nuclear Larmor frequencies, the high frequencies allow for higher time resolution for molecular dynamics as well as for transient paramagnetic intermediates studied with time-resolved EPR. Pulsed EPR methods are used for example for relaxation-time studies, and pulsed Electron Nuclear DOuble Resonance (ENDOR) is used to resolve unresolved hyperfine structure hidden in inhomogeneous linewidths. In the present article we introduce the basic concepts and selected applications to structure and mobility studies on electron transfer systems, reaction centers of photosynthesis as well as biomimetic models. The article concludes with an introduction to stochastic EPR which makes use of an other concept for investigating resonance systems in order to increase the excitation bandwidth of pulsed EPR. The limited excitation bandwidth of pulses at high frequency is one of the main limitations which, so far, made Fourier transform methods hardly feasible.

Large-scale DCMs for resting-state fMRI

Directory of Open Access Journals (Sweden)

Adeel Razi

2017-01-01

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

Assessment of lexical semantic judgment abilities in alcohol-dependent subjects: an fMRI study.

Science.gov (United States)

Bagga, D; Singh, N; Modi, S; Kumar, P; Bhattacharya, D; Garg, M L; Khushu, S

2013-12-01

Neuropsychological studies have shown that alcohol dependence is associated with neurocognitive deficits in tasks requiring memory, perceptual motor skills, abstraction and problem solving, whereas language skills are relatively spared in alcoholics despite structural abnormalities in the language-related brain regions. To investigate the preserved mechanisms of language processing in alcohol-dependents, functional brain imaging was undertaken in healthy controls (n=18) and alcohol-dependents (n=16) while completing a lexical semantic judgment task in a 3 T MR scanner. Behavioural data indicated that alcohol-dependents took more time than controls for performing the task but there was no significant difference in their response accuracy. fMRI data analysis revealed that while performing the task, the alcoholics showed enhanced activations in left supramarginal gyrus, precuneus bilaterally, left angular gyrus, and left middle temporal gyrus as compared to control subjects. The extensive activations observed in alcoholics as compared to controls suggest that alcoholics recruit additional brain areas to meet the behavioural demands for equivalent task performance. The results are consistent with previous fMRI studies suggesting compensatory mechanisms for the execution of task for showing an equivalent performance or decreased neural efficiency of relevant brain networks. However, on direct comparison of the two groups, the results did not survive correction for multiple comparisons; therefore, the present findings need further exploration.

Aging affects the interaction between attentional control and source memory: an fMRI study.

Science.gov (United States)

Dulas, Michael R; Duarte, Audrey

2014-12-01

Age-related source memory impairments may be due, at least in part, to deficits in executive processes mediated by the PFC at both study and test. Behavioral work suggests that providing environmental support at encoding, such as directing attention toward item-source associations, may improve source memory and reduce age-related deficits in the recruitment of these executive processes. The present fMRI study investigated the effects of directed attention and aging on source memory encoding and retrieval. At study, participants were shown pictures of objects. They were either asked to attend to the objects and their color (source) or to their size. At test, participants determined if objects were seen before, and if so, whether they were the same color as previously. Behavioral results showed that direction of attention improved source memory for both groups; however, age-related deficits persisted. fMRI results revealed that, across groups, direction of attention facilitated medial temporal lobe-mediated contextual binding processes during study and attenuated right PFC postretrieval monitoring effects at test. However, persistent age-related source memory deficits may be related to increased recruitment of medial anterior PFC during encoding, indicative of self-referential processing, as well as underrecruitment of lateral anterior PFC-mediated relational processes. Taken together, this study suggests that, even when supported, older adults may fail to selectively encode goal-relevant contextual details supporting source memory performance.

Mapping cerebrovascular reactivity using concurrent fMRI and near infrared spectroscopy

Science.gov (United States)

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

2011-02-01

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

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

Directory of Open Access Journals (Sweden)

Nicoletta Cera

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

Neuroethics and fMRI: Mapping a fledgling relationship

DEFF Research Database (Denmark)

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

2011-01-01

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

Neural effects of environmental advertising: An fMRI analysis of voice age and temporal framing.

Science.gov (United States)

Casado-Aranda, Luis-Alberto; Martínez-Fiestas, Myriam; Sánchez-Fernández, Juan

2018-01-15

Ecological information offered to society through advertising enhances awareness of environmental issues, encourages development of sustainable attitudes and intentions, and can even alter behavior. This paper, by means of functional Magnetic Resonance Imaging (fMRI) and self-reports, explores the underlying mechanisms of processing ecological messages. The study specifically examines brain and behavioral responses to persuasive ecological messages that differ in temporal framing and in the age of the voice pronouncing them. The findings reveal that attitudes are more positive toward future-framed messages presented by young voices. The whole-brain analysis reveals that future-framed (FF) ecological messages trigger activation in brain areas related to imagery, prospective memories and episodic events, thus reflecting the involvement of past behaviors in future ecological actions. Past-framed messages (PF), in turn, elicit brain activations within the episodic system. Young voices (YV), in addition to triggering stronger activation in areas involved with the processing of high-timbre, high-pitched and high-intensity voices, are perceived as more emotional and motivational than old voices (OV) as activations in anterior cingulate cortex and amygdala. Messages expressed by older voices, in turn, exhibit stronger activation in areas formerly linked to low-pitched voices and voice gender perception. Interestingly, a link is identified between neural and self-report responses indicating that certain brain activations in response to future-framed messages and young voices predicted higher attitudes toward future-framed and young voice advertisements, respectively. The results of this study provide invaluable insight into the unconscious origin of attitudes toward environmental messages and indicate which voice and temporal frame of a message generate the greatest subconscious value. Copyright © 2017 Elsevier Ltd. All rights reserved.

How restful is it with all that noise? Comparison of Interleaved silent steady state (ISSS) and conventional imaging in resting-state fMRI.

Science.gov (United States)

Andoh, J; Ferreira, M; Leppert, I R; Matsushita, R; Pike, B; Zatorre, R J

2017-02-15

Resting-state fMRI studies have become very important in cognitive neuroscience because they are able to identify BOLD fluctuations in brain circuits involved in motor, cognitive, or perceptual processes without the use of an explicit task. Such approaches have been fruitful when applied to various disordered populations, or to children or the elderly. However, insufficient attention has been paid to the consequences of the loud acoustic scanner noise associated with conventional fMRI acquisition, which could be an important confounding factor affecting auditory and/or cognitive networks in resting-state fMRI. Several approaches have been developed to mitigate the effects of acoustic noise on fMRI signals, including sparse sampling protocols and interleaved silent steady state (ISSS) acquisition methods, the latter being used only for task-based fMRI. Here, we developed an ISSS protocol for resting-state fMRI (rs-ISSS) consisting of rapid acquisition of a set of echo planar imaging volumes following each silent period, during which the steady state longitudinal magnetization was maintained with a train of relatively silent slice-selective excitation pulses. We evaluated the test-retest reliability of intensity and spatial extent of connectivity networks of fMRI BOLD signal across three different days for rs-ISSS and compared it with a standard resting-state fMRI (rs-STD). We also compared the strength and distribution of connectivity networks between rs-ISSS and rs-STD. We found that both rs-ISSS and rs-STD showed high reproducibility of fMRI signal across days. In addition, rs-ISSS showed a more robust pattern of functional connectivity within the somatosensory and motor networks, as well as an auditory network compared with rs-STD. An increased connectivity between the default mode network and the language network and with the anterior cingulate cortex (ACC) network was also found for rs-ISSS compared with rs-STD. Finally, region of interest analysis showed

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/.

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

Science.gov (United States)

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

2010-03-01

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

The Perception of Dynamic and Static Facial Expressions of Happiness and Disgust Investigated by ERPs and fMRI Constrained Source Analysis

Science.gov (United States)

Trautmann-Lengsfeld, Sina Alexa; Domínguez-Borràs, Judith; Escera, Carles; Herrmann, Manfred; Fehr, Thorsten

2013-01-01

A recent functional magnetic resonance imaging (fMRI) study by our group demonstrated that dynamic emotional faces are more accurately recognized and evoked more widespread patterns of hemodynamic brain responses than static emotional faces. Based on this experimental design, the present study aimed at investigating the spatio-temporal processing of static and dynamic emotional facial expressions in 19 healthy women by means of multi-channel electroencephalography (EEG), event-related potentials (ERP) and fMRI-constrained regional source analyses. ERP analysis showed an increased amplitude of the LPP (late posterior positivity) over centro-parietal regions for static facial expressions of disgust compared to neutral faces. In addition, the LPP was more widespread and temporally prolonged for dynamic compared to static faces of disgust and happiness. fMRI constrained source analysis on static emotional face stimuli indicated the spatio-temporal modulation of predominantly posterior regional brain activation related to the visual processing stream for both emotional valences when compared to the neutral condition in the fusiform gyrus. The spatio-temporal processing of dynamic stimuli yielded enhanced source activity for emotional compared to neutral conditions in temporal (e.g., fusiform gyrus), and frontal regions (e.g., ventromedial prefrontal cortex, medial and inferior frontal cortex) in early and again in later time windows. The present data support the view that dynamic facial displays trigger more information reflected in complex neural networks, in particular because of their changing features potentially triggering sustained activation related to a continuing evaluation of those faces. A combined fMRI and EEG approach thus provides an advanced insight to the spatio-temporal characteristics of emotional face processing, by also revealing additional neural generators, not identifiable by the only use of an fMRI approach. PMID:23818974

High-field superferric MR magnet

International Nuclear Information System (INIS)

Huson, F.R.; Carcagno, R.; Colvin, J.

1987-01-01

Current large-bore (>20 cm), high-field (2-T) MR magnets have major implementation disadvantages, mostly related to the extensive stray field of traditional air-core superconducting magnets. To circumvent this problem, the authors designed, constructed, and tested a 30-cm prototype superconducting, self-shielded, high field magnet. This unshimmed superferric magnet can operate between 0.5 and 4 T with a field quality of about one part per million over one quarter of its aperture. The magnet can be ramped from one field strength to another in approximately 10 minutes. The 5-Gauss line extends less than 1 meter outside the magnet structure. Further details, including MR measurements and images, are demonstrated, as well as 1-meter bore scale-up projections

Development of high field superconducting magnet

International Nuclear Information System (INIS)

Irie, Fujio; Takeo, Masakatsu.

1986-01-01

Recently, in connection with nuclear fusion research, the development of high field superconducting magnets showed rapid progress. The development of high field magnets of 15 T class by the techniques of winding after heat treatment has been continued in various places, as these techniques are suitable to make large magnets. In 1985, Kyushu University attained the record of 15.5 T. However in high field magnets, there are many problems peculiar to them, and the basic research related to those is demanded. In this report, these general problems, the experience of the design and manufacture in Kyushu University and the related problems are described. The superconducting magnet installed in the Superconducting Magnet Research Center of Kyushu University attained the record of 15.5 T for the first time in March, 1985. In superconducting magnets, very difficult problem must be solved since superconductivity, heat and mechanical force are inter related. The problems of the wire materials for high field, the scale of high field magnets, the condition limiting mean current density, and the development of high field magnets in Kyushu University are described. (Kako, I.)

Differences in cortical coding of heat evoked pain beyond the perceived intensity: an fMRI and EEG study.

Science.gov (United States)

Haefeli, Jenny; Freund, Patrick; Kramer, John L K; Blum, Julia; Luechinger, Roger; Curt, Armin

2014-04-01

Imaging studies have identified a wide network of brain areas activated by nociceptive stimuli and revealed differences in somatotopic representation of highly distinct stimulation sites (foot vs. hand) in the primary (S1) and secondary (S2) somatosensory cortices. Somatotopic organization between adjacent dermatomes and differences in cortical coding of similarly perceived nociceptive stimulation are less well studied. Here, cortical processing following contact heat nociceptive stimulation of cervical (C4, C6, and C8) and trunk (T10) dermatomes were recorded in 20 healthy subjects using functional magnetic resonance imaging (fMRI) and electroencephalography (EEG). Stimulation of T10 compared with the C6 and C8 revealed significant higher response intensity in the left S1 (contralateral) and the right S2 (ipsilateral) even when the perceived pain was equal between stimulation sites. Accordingly, contact heat evoked potentials following stimulation of T10 showed significantly higher N2P2 amplitudes compared to C6 and C8. Adjacent dermatomes did not reveal a distinct somatotopical representation. Within the assessed cervical and trunk dermatomes, nociceptive cortical processing to heat differs significantly in magnitude even when controlling for pain perception. This study provides evidence that controlling for pain perception is not sufficient to compare directly the magnitude of cortical processing [blood oxygen level dependence (BOLD) response and amplitude of evoked potentials] between body sites. Copyright © 2013 Wiley Periodicals, Inc.

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.

The potential of infant fMRI research and the study of early life stress as a promising exemplar

Directory of Open Access Journals (Sweden)

Alice M. Graham

2015-04-01

Full Text Available Functional magnetic resonance imaging (fMRI research with infants and toddlers has increased rapidly over the past decade, and provided a unique window into early brain development. In the current report, we review the state of the literature, which has established the feasibility and utility of task-based fMRI and resting state functional connectivity MRI (rs-fcMRI during early periods of brain maturation. These methodologies have been successfully applied beginning in the neonatal period to increase understanding of how the brain both responds to environmental stimuli, and becomes organized into large-scale functional systems that support complex behaviors. We discuss the methodological challenges posed by this promising area of research. We also highlight that despite these challenges, early work indicates a strong potential for these methods to influence multiple research domains. As an example, we focus on the study of early life stress and its influence on brain development and mental health outcomes. We illustrate the promise of these methodologies for building on, and making important contributions to, the existing literature in this field.

Implicit Structured Sequence Learning: An FMRI Study of the Structural Mere-Exposure Effect

OpenAIRE

Vasiliki eFolia; Vasiliki eFolia; Karl Magnus ePetersson; Karl Magnus ePetersson; Karl Magnus ePetersson

2014-01-01

In this event-related FMRI study we investigated the effect of five days of implicit acquisition on preference classification by means of an artificial grammar learning (AGL) paradigm based on the structural mere-exposure effect and preference classification using a simple right-linear unification grammar. This allowed us to investigate implicit AGL in a proper learning design by including baseline measurements prior to grammar exposure. After 5 days of implicit acquisition, the FMRI results ...

Generalized INverse imaging (GIN): ultrafast fMRI with physiological noise correction.

Science.gov (United States)

Boyacioğlu, Rasim; Barth, Markus

2013-10-01

An ultrafast functional magnetic resonance imaging (fMRI) technique, called generalized inverse imaging (GIN), is proposed, which combines inverse imaging with a phase constraint-leading to a less underdetermined reconstruction-and physiological noise correction. A single 3D echo planar imaging (EPI) prescan is sufficient to obtain the necessary coil sensitivity information and reference images that are used to reconstruct standard images, so that standard analysis methods are applicable. A moving dots stimulus paradigm was chosen to assess the performance of GIN. We find that the spatial localization of activation for GIN is comparable to an EPI protocol and that maximum z-scores increase significantly. The high temporal resolution of GIN (50 ms) and the acquisition of the phase information enable unaliased sampling and regression of physiological signals. Using the phase time courses obtained from the 32 channels of the receiver coils as nuisance regressors in a general linear model results in significant improvement of the functional activation, rendering the acquisition of external physiological signals unnecessary. The proposed physiological noise correction can in principle be used for other fMRI protocols, such as simultaneous multislice acquisitions, which acquire the phase information sufficiently fast and sample physiological signals unaliased. Copyright © 2012 Wiley Periodicals, Inc.

MR equipment acquisition strategies: low-field or high-field scanners

International Nuclear Information System (INIS)

Marti-Bonmati, L.; Kormano, M.

1997-01-01

Magnetic resonance (MR) field strength is one of the key aspects to consider when purchasing MR equipment. Other aspects include the gradient system, coil design, computer and pulse sequence availability, purchase cost, local reimbursement policies, and current opinion within the medical community. Our objective here is to evaluate the decision-influencing aspects of the MR market, with a focus on some specific areas such as high resolution studies, examination times, special techniques, instrumentation, open design magnets, costs and reimbursement policies, academic and industrial interests, contrast media, clinical efficacy, and finally, clinicians' preferences. Certainly the advantage of high-field is a higher signal-to-noise ratio and improved resolution. With a high-field unit, higher spatial resolution images and higher temporal resolution images can be obtained. Typical imaging times needed to produce clinically diagnostic images are about 3 times longer at 0.1 T than at 1.0 or 1.5 T. High-field-related advanced techniques, such as functional imaging, spectroscopy and microscopy, may become clinically useful in the near future. As long as there is an unlimited demand for MR examinations, it appears financially profitable to run a high-field system, despite the associated higher costs. However, if demand for MR becomes saturated, low-field systems will cause less financial strain on the reimbursement organisation and service provider. Recent emphasis on cost containment, the development of interventional techniques, the increased use of MR for patients in intensive care and operating suites, the deployment of magnets in office suites, and the development of new magnet configurations, all favour the supplementary use of low-field systems. Hence, MR units of all field strengths have a role in radiology. (orig.)

Influence of emotional expression on memory recognition bias in schizophrenia as revealed by fMRI.

Science.gov (United States)

Sergerie, Karine; Armony, Jorge L; Menear, Matthew; Sutton, Hazel; Lepage, Martin

2010-07-01

We recently showed that, in healthy individuals, emotional expression influences memory for faces both in terms of accuracy and, critically, in memory response bias (tendency to classify stimuli as previously seen or not, regardless of whether this was the case). Although schizophrenia has been shown to be associated with deficit in episodic memory and emotional processing, the relation between these processes in this population remains unclear. Here, we used our previously validated paradigm to directly investigate the modulation of emotion on memory recognition. Twenty patients with schizophrenia and matched healthy controls completed functional magnetic resonance imaging (fMRI) study of recognition memory of happy, sad, and neutral faces. Brain activity associated with the response bias was obtained by correlating this measure with the contrast subjective old (ie, hits and false alarms) minus subjective new (misses and correct rejections) for sad and happy expressions. Although patients exhibited an overall lower memory performance than controls, they showed the same effects of emotion on memory, both in terms of accuracy and bias. For sad faces, the similar behavioral pattern between groups was mirrored by a largely overlapping neural network, mostly involved in familiarity-based judgments (eg, parahippocampal gyrus). In contrast, controls activated a much larger set of regions for happy faces, including areas thought to underlie recollection-based memory retrieval (eg, superior frontal gyrus and hippocampus) and in novelty detection (eg, amygdala). This study demonstrates that, despite an overall lower memory accuracy, emotional memory is intact in schizophrenia, although emotion-specific differences in brain activation exist, possibly reflecting different strategies.

The implicit effect of texturizing field on the elastic properties of magnetic elastomers revealed by SANS

Energy Technology Data Exchange (ETDEWEB)

Balasoiu, M., E-mail: balas@jinr.ru [Joint Institute of Nuclear Research, Dubna (Russian Federation); Horia Hulubei National Institute for Physics and Nuclear Engineering, Bucharest (Romania); Lebedev, V.T. [St.Petersburg Nuclear Physics Institute NRC KI, Gatchina (Russian Federation); Raikher, Yu.L. [Institute of Continuous Media Mechanics, Russian Academy of Sciences, Ural Branch, Perm (Russian Federation); Bica, I.; Bunoiu, M. [West University of Timisoara, Department of Physics (Romania)

2017-06-01

Small angle neutron scattering method (SANS) is used to characterize the structure properties of the polymer matrix of magnetic elastomers (MEs) of the same material content but with different magnetic textures. For that, series of silicone-rubber elastomers mixed with a ferrofluid and polymerized with/without external magnetic field were studied. In the species of pure rubber and the ME samples synthesized without field, SANS reveals a substantial number of large polymer coils (blobs) which are vertically prolate. The case of MEs polymerized under the magnetic field that is also vertically directed, is different. SANS data indicates that there the blobs are preferably elongated in the direction normal to the field. - Highlights: • SANS method is used to determine the structure of SR elastomers polymerized with ferrofluid in/no external magnetic field. • In the rubber and ME samples synthesized without field, SANS reveals a substantial number of vertically prolate blobs. • For MEs polymerized in vertical magnetic field, results that the blobs are elongated in the direction normal to the field. • Isotropic and texturized MEs differ by the filler structure and by intrinsic elastic properties of the matrix as well.

Tinnitus- related distress: evidence from fMRI of an emotional stroop task

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Dennis Golm

2016-08-01

Full Text Available Abstract Background Chronic tinnitus affects 5 % of the population, 17 % suffer under the condition. This distress seems mainly to be dependent on negative cognitive-emotional evaluation of the tinnitus and selective attention to the tinnitus. A well-established paradigm to examine selective attention and emotional processing is the Emotional Stroop Task (EST. Recent models of tinnitus distress propose limbic, frontal and parietal regions to be more active in highly distressed tinnitus patients. Only a few studies have compared high and low distressed tinnitus patients. Thus, this study aimed to explore neural correlates of tinnitus-related distress. Methods Highly distressed tinnitus patients (HDT, n = 16, low distressed tinnitus patients (LDT, n = 16 and healthy controls (HC, n = 16 underwent functional magnetic resonance imaging (fMRI during an EST, that used tinnitus-related words and neutral words as stimuli. A random effects analysis of the fMRI data was conducted on the basis of the general linear model. Furthermore correlational analyses between the blood oxygen level dependent response and tinnitus distress, loudness, depression, anxiety, vocabulary and hypersensitivity to sound were performed. Results Contradictory to the hypothesis, highly distressed patients showed no Stroop effect in their reaction times. As hypothesized HDT and LDT differed in the activation of the right insula and the orbitofrontal cortex. There were no hypothesized differences between HDT and HC. Activation of the orbitofrontal cortex and the right insula were found to correlate with tinnitus distress. Conclusions The results are partially supported by earlier resting-state studies and corroborate the role of the insula and the orbitofrontal cortex in tinnitus distress.

Studies on the reliability of high-field intra-operative MRI in brain glioma resection

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Zhi-jun SONG

2011-07-01

Full Text Available Objective To evaluate the reliability of high-field intra-operative magnetic resonance imaging(iMRI in detecting the residual tumors during glioma resection.Method One hundred and thirty-one cases of brain glioma(69 males and 62 females,aged from 7 to 79 years with mean of 39.6 years hospitalized from Nov.2009 to Aug.2010 were involved in present study.All the patients were evaluated using magnetic resonance imaging(MRI before the operation.The tumors were resected under conventional navigation microscope,and the high-field iMRI was used for all the patients when the operators considered the tumor was satisfactorily resected,while the residual tumor was difficult to detect under the microscope,but resected after being revealed by high-field iMRI.Histopathological examination was performed.The patients without residual tumors recieved high-field MRI scan at day 4 or 5 after operation to evaluate the accuracy of high-field iMRI during operation.Results High quality intra-operative images were obtained by using high-field iMRI.Twenty-eight cases were excluded because their residual tumors were not resected due to their location too close to functional area.Combined with the results of intra-operative histopathological examination and post-operative MRI at the early recovery stage,the sensitivity of high-field iMRI in residual tumor diagnosis was 98.0%(49/50,the specificity was 94.3%(50/53,and the accuracy was 96.1%(99/103.Conclusion High-quality intra-operative imaging could be acquired by high-field iMRI,which maybe used as a safe and reliable method in detecting the residual tumors during glioma resection.

Exploring fMRI Data for Periodic Signal Components

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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...

Adaptive smoothing based on Gaussian processes regression increases the sensitivity and specificity of fMRI data.

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Strappini, Francesca; Gilboa, Elad; Pitzalis, Sabrina; Kay, Kendrick; McAvoy, Mark; Nehorai, Arye; Snyder, Abraham Z

2017-03-01

Temporal and spatial filtering of fMRI data is often used to improve statistical power. However, conventional methods, such as smoothing with fixed-width Gaussian filters, remove fine-scale structure in the data, necessitating a tradeoff between sensitivity and specificity. Specifically, smoothing may increase sensitivity (reduce noise and increase statistical power) but at the cost loss of specificity in that fine-scale structure in neural activity patterns is lost. Here, we propose an alternative smoothing method based on Gaussian processes (GP) regression for single subjects fMRI experiments. This method adapts the level of smoothing on a voxel by voxel basis according to the characteristics of the local neural activity patterns. GP-based fMRI analysis has been heretofore impractical owing to computational demands. Here, we demonstrate a new implementation of GP that makes it possible to handle the massive data dimensionality of the typical fMRI experiment. We demonstrate how GP can be used as a drop-in replacement to conventional preprocessing steps for temporal and spatial smoothing in a standard fMRI pipeline. We present simulated and experimental results that show the increased sensitivity and specificity compared to conventional smoothing strategies. Hum Brain Mapp 38:1438-1459, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

A field-sweep/field-lock system for superconducting magnets--Application to high-field EPR.

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Maly, Thorsten; Bryant, Jeff; Ruben, David; Griffin, Robert G

2006-12-01

We describe a field-lock/field-sweep system for the use in superconducting magnets. The system is based on a commercially available field mapping unit and a custom designed broad-band 1H NMR probe. The NMR signal of a small water sample is used in a feedback loop to set and control the magnetic field to high accuracy. The current instrumental configuration allows field sweeps of +/-0.4 T and a resolution of up to 10(-5) T (0.1 G) and the performance of the system is demonstrated in a high-field electron paramagnetic resonance (EPR) application. The system should also be of utility in other experiments requiring precise and reproducible sweeps of the magnetic field such as DNP, ENDOR or PELDOR.

A Field-Sweep/Field-Lock System for Superconducting Magnets-Application to High-Field EPR

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Maly, Thorsten; Bryant, Jeff; Ruben, David; Griffin, Robert G.

2007-01-01

We describe a field-lock/field-sweep system for the use in superconducting magnets. The system is based on a commercially available field mapping unit and a custom designed broad-band 1H-NMR probe. The NMR signal of a small water sample is used in a feedback loop to set and control the magnetic field to high accuracy. The current instrumental configuration allows field sweeps of ± 0.4 T and a resolution of up to 10-5 T (0.1 G) and the performance of the system is demonstrated in a high-field electron paramagnetic resonance (EPR) application. The system should also be of utility in other experiments requiring precise and reproducible sweeps of the magnetic field such as DNP, ENDOR or PELDOR. PMID:17027306

Gaussian process based independent analysis for temporal source separation in fMRI

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

2017-01-01

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

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

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

1999-01-01

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

Language changes coincide with motor and fMRI changes following upper extremity motor therapy for hemiparesis: a brief report.

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Harnish, Stacy; Meinzer, Marcus; Trinastic, Jonathan; Fitzgerald, David; Page, Stephen

2014-09-01

To formally assess changes in language, affected UE movement, and motor functional activation changes via functional magnetic resonance imaging (fMRI) following participation in motor therapy without any accompanying language intervention. Pre-post case series. Five subjects with stroke exhibiting chronic, stable UE hemiparesis. The upper extremity section of the Fugl-Meyer (FM), the Western Aphasia Battery (WAB), and functional magnetic resonance imaging (fMRI), administered during performance of an affected UE motor task. All subjects were administered six weeks of repetitive task specific training (RTP), performed for approximately 2.5 hours per day, split into two sessions. For the first four weeks of the intervention period, RTP was administered every weekday, whereas, for the subsequent two weeks, RTP was administered 3 days/week. Epidural cortical stimulation was co-administered with the RTP via an electrode array and implanted pulse generator. For all sessions, one subject worked with a single therapist. Four weeks before and four weeks after the intervention period, all subjects were administered the FM, WAB, and fMRI. Three of the subjects exhibited clinically significant language changes on the WAB. These individuals exhibited the largest motor changes as measured by the FM. Functional MRI revealed distinct motor activation patterns in these subjects, characterized by more strongly right lateralized focal BOLD activity or a shift in activation toward the right hemisphere. Language changes appear to co-occur with motor changes after UE RTP. Understanding the underlying mechanisms of these findings may lead to more efficient and synergistic rehabilitative therapy delivery.

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

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Jukka-Pekka eKauppi

2014-01-01

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

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

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

2014-01-01

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

Distinct prediction errors in mesostriatal circuits of the human brain mediate learning about the values of both states and actions: evidence from high-resolution fMRI.

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Colas, Jaron T; Pauli, Wolfgang M; Larsen, Tobias; Tyszka, J Michael; O'Doherty, John P

2017-10-01

Prediction-error signals consistent with formal models of "reinforcement learning" (RL) have repeatedly been found within dopaminergic nuclei of the midbrain and dopaminoceptive areas of the striatum. However, the precise form of the RL algorithms implemented in the human brain is not yet well determined. Here, we created a novel paradigm optimized to dissociate the subtypes of reward-prediction errors that function as the key computational signatures of two distinct classes of RL models-namely, "actor/critic" models and action-value-learning models (e.g., the Q-learning model). The state-value-prediction error (SVPE), which is independent of actions, is a hallmark of the actor/critic architecture, whereas the action-value-prediction error (AVPE) is the distinguishing feature of action-value-learning algorithms. To test for the presence of these prediction-error signals in the brain, we scanned human participants with a high-resolution functional magnetic-resonance imaging (fMRI) protocol optimized to enable measurement of neural activity in the dopaminergic midbrain as well as the striatal areas to which it projects. In keeping with the actor/critic model, the SVPE signal was detected in the substantia nigra. The SVPE was also clearly present in both the ventral striatum and the dorsal striatum. However, alongside these purely state-value-based computations we also found evidence for AVPE signals throughout the striatum. These high-resolution fMRI findings suggest that model-free aspects of reward learning in humans can be explained algorithmically with RL in terms of an actor/critic mechanism operating in parallel with a system for more direct action-value learning.

Language Lateralization in Children Aged 10 to 11 Years: A Combined fMRI and Dichotic Listening Study

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Norrelgen, Fritjof; Lilja, Anders; Ingvar, Martin; Gisselgård, Jens; Fransson, Peter

2012-01-01

Objective The aims of this study were to develop and assess a method to map language networks in children with two auditory fMRI protocols in combination with a dichotic listening task (DL). The method is intended for pediatric patients prior to epilepsy surgery. To evaluate the potential clinical usefulness of the method we first wanted to assess data from a group of healthy children. Methods In a first step language test materials were developed, intended for subsequent implementation in fMRI protocols. An evaluation of this material was done in 30 children with typical development, 10 from the 1st, 4th and the 7th grade, respectively. The language test material was then adapted and implemented in two fMRI protocols intended to target frontal and posterior language networks. In a second step language lateralization was assessed in 17 typical 10–11 year olds with fMRI and DL. To reach a conclusion about language lateralization, firstly, quantitative analyses of the index data from the two fMRI tasks and the index data from the DL task were done separately. In a second step a set of criteria were applied to these results to reach a conclusion about language lateralization. The steps of these analyses are described in detail. Results The behavioral assessment of the language test material showed that it was well suited for typical children. The results of the language lateralization assessments, based on fMRI data and DL data, showed that for 15 of the 17 subjects (88%) a conclusion could be reached about hemispheric language dominance. In 2 cases (12%) DL provided critical data. Conclusions The employment of DL combined with language mapping using fMRI for assessing hemispheric language dominance is novel and it was deemed valuable since it provided additional information compared to the results gained from each method individually. PMID:23284796

Language lateralization in children aged 10 to 11 years: a combined fMRI and dichotic listening study.

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Fritjof Norrelgen

Full Text Available OBJECTIVE: The aims of this study were to develop and assess a method to map language networks in children with two auditory fMRI protocols in combination with a dichotic listening task (DL. The method is intended for pediatric patients prior to epilepsy surgery. To evaluate the potential clinical usefulness of the method we first wanted to assess data from a group of healthy children. METHODS: In a first step language test materials were developed, intended for subsequent implementation in fMRI protocols. An evaluation of this material was done in 30 children with typical development, 10 from the 1(st, 4(th and the 7(th grade, respectively. The language test material was then adapted and implemented in two fMRI protocols intended to target frontal and posterior language networks. In a second step language lateralization was assessed in 17 typical 10-11 year olds with fMRI and DL. To reach a conclusion about language lateralization, firstly, quantitative analyses of the index data from the two fMRI tasks and the index data from the DL task were done separately. In a second step a set of criteria were applied to these results to reach a conclusion about language lateralization. The steps of these analyses are described in detail. RESULTS: The behavioral assessment of the language test material showed that it was well suited for typical children. The results of the language lateralization assessments, based on fMRI data and DL data, showed that for 15 of the 17 subjects (88% a conclusion could be reached about hemispheric language dominance. In 2 cases (12% DL provided critical data. CONCLUSIONS: The employment of DL combined with language mapping using fMRI for assessing hemispheric language dominance is novel and it was deemed valuable since it provided additional information compared to the results gained from each method individually.

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

International Nuclear Information System (INIS)

Wurm, Gabriele; Schnizer, Mathilde; Fellner, Claudia

2008-01-01

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

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

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

2010-01-01

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

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

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Seghouane, Abd-Krim; Iqbal, Asif

2017-09-01

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

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

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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.

Children’s head motion during fMRI tasks is heritable and stable over time

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Laura E. Engelhardt

2017-06-01

Full Text Available Head motion during fMRI scans negatively impacts data quality, and as post-acquisition techniques for addressing motion become increasingly stringent, data retention decreases. Studies conducted with adult participants suggest that movement acts as a relatively stable, heritable phenotype that serves as a marker for other genetically influenced phenotypes. Whether these patterns extend downward to childhood has critical implications for the interpretation and generalizability of fMRI data acquired from children. We examined factors affecting scanner motion in two samples: a population-based twin sample of 73 participants (ages 7–12 years and a case-control sample of 32 non-struggling and 78 struggling readers (ages 8–11 years, 30 of whom were scanned multiple times. Age, but not ADHD symptoms, was significantly related to scanner movement. Movement also varied as a function of task type, run length, and session length. Twin pair concordance for head motion was high for monozygotic twins and moderate for dizygotic twins. Cross-session test-retest reliability was high. Together, these findings suggest that children’s head motion is a genetically influenced trait that has the potential to systematically affect individual differences in BOLD changes within and across groups. We discuss recommendations for future work and best practices for pediatric neuroimaging.

Near field plasmonic gradient effects on high vacuum tip-enhanced Raman spectroscopy.

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Fang, Yurui; Zhang, Zhenglong; Chen, Li; Sun, Mengtao

2015-01-14

Near field gradient effects in high vacuum tip-enhanced Raman spectroscopy (HV-TERS) are a recent developing ultra-sensitive optical and spectral analysis technology on the nanoscale, based on the plasmons and plasmonic gradient enhancement in the near field and under high vacuum. HV-TERS can not only be used to detect ultra-sensitive Raman spectra enhanced by surface plasmon, but also to detect clear molecular IR-active modes enhanced by strongly plasmonic gradient. Furthermore, the molecular overtone modes and combinational modes can also be experimentally measured, where the Fermi resonance and Darling-Dennison resonance were successfully observed in HV-TERS. Theoretical calculations using electromagnetic field theory firmly supported experimental observation. The intensity ratio of the plasmon gradient term over the linear plasmon term can reach values greater than 1. Theoretical calculations also revealed that with the increase in gap distance between tip and substrate, the decrease in the plasmon gradient was more significant than the decrease in plasmon intensity, which is the reason that the gradient Raman can be only observed in the near field. Recent experimental results of near field gradient effects on HV-TERS were summarized, following the section of the theoretical analysis.

Overlay control methodology comparison: field-by-field and high-order methods

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Huang, Chun-Yen; Chiu, Chui-Fu; Wu, Wen-Bin; Shih, Chiang-Lin; Huang, Chin-Chou Kevin; Huang, Healthy; Choi, DongSub; Pierson, Bill; Robinson, John C.

2012-03-01

Overlay control in advanced integrated circuit (IC) manufacturing is becoming one of the leading lithographic challenges in the 3x and 2x nm process nodes. Production overlay control can no longer meet the stringent emerging requirements based on linear composite wafer and field models with sampling of 10 to 20 fields and 4 to 5 sites per field, which was the industry standard for many years. Methods that have emerged include overlay metrology in many or all fields, including the high order field model method called high order control (HOC), and field by field control (FxFc) methods also called correction per exposure. The HOC and FxFc methods were initially introduced as relatively infrequent scanner qualification activities meant to supplement linear production schemes. More recently, however, it is clear that production control is also requiring intense sampling, similar high order and FxFc methods. The added control benefits of high order and FxFc overlay methods need to be balanced with the increased metrology requirements, however, without putting material at risk. Of critical importance is the proper control of edge fields, which requires intensive sampling in order to minimize signatures. In this study we compare various methods of overlay control including the performance levels that can be achieved.

Ready...go: Amplitude of the FMRI signal encodes expectation of cue arrival time.

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Xu Cui

2009-08-01

Full Text Available What happens when the brain awaits a signal of uncertain arrival time, as when a sprinter waits for the starting pistol? And what happens just after the starting pistol fires? Using functional magnetic resonance imaging (fMRI, we have discovered a novel correlate of temporal expectations in several brain regions, most prominently in the supplementary motor area (SMA. Contrary to expectations, we found little fMRI activity during the waiting period; however, a large signal appears after the "go" signal, the amplitude of which reflects learned expectations about the distribution of possible waiting times. Specifically, the amplitude of the fMRI signal appears to encode a cumulative conditional probability, also known as the cumulative hazard function. The fMRI signal loses its dependence on waiting time in a "countdown" condition in which the arrival time of the go cue is known in advance, suggesting that the signal encodes temporal probabilities rather than simply elapsed time. The dependence of the signal on temporal expectation is present in "no-go" conditions, demonstrating that the effect is not a consequence of motor output. Finally, the encoding is not dependent on modality, operating in the same manner with auditory or visual signals. This finding extends our understanding of the relationship between temporal expectancy and measurable neural signals.

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

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

2014-01-01

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

Implicit Structured Sequence Learning: An FMRI Study of the Structural Mere-Exposure Effect

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Vasiliki eFolia

2014-02-01

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

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

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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

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

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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.)

Whole-globe biomechanics using high-field MRI.

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Voorhees, Andrew P; Ho, Leon C; Jan, Ning-Jiun; Tran, Huong; van der Merwe, Yolandi; Chan, Kevin; Sigal, Ian A

2017-07-01

The eye is a complex structure composed of several interconnected tissues acting together, across the whole globe, to resist deformation due to intraocular pressure (IOP). However, most work in the ocular biomechanics field only examines the response to IOP over smaller regions of the eye. We used high-field MRI to measure IOP induced ocular displacements and deformations over the whole globe. Seven sheep eyes were obtained from a local abattoir and imaged within 48 h using MRI at multiple levels of IOP. IOP was controlled with a gravity perfusion system and a cannula inserted into the anterior chamber. T2-weighted imaging was performed to the eyes serially at 0 mmHg, 10 mmHg, 20 mmHg and 40 mmHg of IOP using a 9.4 T MRI scanner. Manual morphometry was conducted using 3D visualization software to quantify IOP-induced effects at the globe scale (e.g. axial length and equatorial diameters) or optic nerve head scale (e.g. canal diameter, peripapillary sclera bowing). Measurement sensitivity analysis was conducted to determine measurement precision. High-field MRI revealed an outward bowing of the posterior sclera and anterior bulging of the cornea due to IOP elevation. Increments in IOP from 10 to 40 mmHg caused measurable increases in axial length in 6 of 7 eyes of 7.9 ± 5.7% (mean ± SD). Changes in equatorial diameter were minimal, 0.4 ± 1.2% between 10 and 40 mmHg, and in all cases less than the measurement sensitivity. The effects were nonlinear, with larger deformations at normal IOPs (10-20 mmHg) than at elevated IOPs (20-40 mmHg). IOP also caused measurable increases in the nasal-temporal scleral canal diameter of 13.4 ± 9.7% between 0 and 20 mmHg, but not in the superior-inferior diameter. This study demonstrates that high-field MRI can be used to visualize and measure simultaneously the effects of IOP over the whole globe, including the effects on axial length and equatorial diameter, posterior sclera displacement and bowing, and even

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

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

1999-01-01

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

Synchrotron Applications of High Magnetic Fields

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NONE

2006-07-01

This workshop aims at discussing the scientific potential of X-ray diffraction and spectroscopy in magnetic fields above 30 T. Pulsed magnetic fields in the range of 30 to 40 T have recently become available at Spring-8 and the ESRF (European synchrotron radiation facility). This document gathers the transparencies of the 6 following presentations: 1) pulsed magnetic fields at ESRF: first results; 2) X-ray spectroscopy and diffraction experiments by using mini-coils: applications to valence state transition and frustrated magnet; 3) R{sub 5}(Si{sub x}Ge{sub 1-x}){sub 4}: an ideal system to be studied in X-ray under high magnetic field?; 4) high field studies at the Advanced Photon Source: present status and future plans; 5) synchrotron X-ray diffraction studies under extreme conditions; and 6) projects for pulsed and steady high magnetic fields at the ESRF.

Quantitative evaluation of fMRI retinotopic maps, from V1 to V4, for cognitive experiments

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Cecile eBordier

2015-05-01

Full Text Available FMRI retinotopic mapping is a non-invasive technique for the delineation of low-level visual areas in individual subjects. It generally relies upon the analysis of functional responses to periodic visual stimuli that encode eccentricity or polar angle in the visual field. This technique is used in vision research when the precise assignation of brain activation to retinotopic areas is an issue. It involves processing steps computed with different algorithms and embedded in various software suites. Manual intervention may be needed for some steps. Although the diversity of the available processing suites and manual interventions may potentially introduce some differences in the final delineation of visual areas, no documented comparison between maps obtained with different procedures has been reported in the literature. To explore the effect of the processing steps on the quality of the maps obtained, we used two tools, BALC, which relies on a fully automated procedure, and BrainVoyager, where areas are delineated by hand on the brain surface. To focus on the mapping procedures specifically, we used the same SPM pipeline for pretreatment and the same tissue segmentation tool. We document the consistency and differences of the fMRI retinotopic maps obtained from routine retinotopy experiments on ten subjects. The maps obtained by skilled users are never fully identical. However, the agreement between the maps, around 80% for low-level areas, is probably sufficient for most applications. Our results also indicate that assigning cognitive activations, following a specific experiment (here, color perception, to individual retinotopic maps is not free of errors. We provide measurements of this error, that may help for the cautious interpretation of cognitive activation projection onto fMRI retinotopic maps. On average, the magnitude of the error is about 20%, with much larger differences in a few subjects.

The neural correlates of perceptual load induced attentional selection: an fMRI study.

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Wei, P; Szameitat, A J; Müller, H J; Schubert, T; Zhou, X

2013-10-10

The neural correlates of perceptual load induced attentional selection were investigated in an functional magnetic resonance imaging (fMRI) experiment in which attentional selection was manipulated through the variation of perceptual load in target search. Participants searched for a vertically or horizontally oriented bar among heterogeneously (the high load condition) or homogeneously (the low load condition) oriented distractor bars in the central display, which was flanked by a vertical or horizontal bar presented at the left or the right periphery. The search reaction times were longer when the central display was of high load than of low load, and were longer when the flanker was incongruent than congruent with the target. Importantly, the flanker congruency effect was manifested only in the low load condition, not in the high load condition, indicating that the perceptual load in target search determined whether the task-irrelevant flanker was processed. Imaging analyses revealed a set of fronto-parietal regions having higher activations in the high than in the low load condition. Anterior cingulate cortex (ACC) was more activated for the incongruent than for the congruent trials. Moreover, ACC and bilateral anterior insula were sensitive to the interaction between perceptual load and flanker congruency such that the activation differences between the incongruent and congruent conditions were significant in the low, but not in the high load condition. These results are consistent with the claim that ACC and bilateral anterior insula may exert executive control by selectively biasing processing in favor of task-relevant information and this biasing depends on the resources currently available to the control system. Copyright © 2013 IBRO. Published by Elsevier Ltd. All rights reserved.

Altered affective response in marijuana smokers: an FMRI study.

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Gruber, Staci A; Rogowska, Jadwiga; Yurgelun-Todd, Deborah A

2009-11-01

More than 94 million Americans have tried marijuana, and it remains the most widely used illicit drug in the nation. Investigations of the cognitive effects of marijuana report alterations in brain function during tasks requiring executive control, including inhibition and decision-making. Endogenous cannabinoids regulate a variety of emotional responses, including anxiety, mood control, and aggression; nevertheless, little is known about smokers' responses to affective stimuli. The anterior cingulate and amygdala play key roles in the inhibition of impulsive behavior and affective regulation, and studies using PET and fMRI have demonstrated changes within these regions in marijuana smokers. Given alterations in mood and perception often observed in smokers, we hypothesized altered fMRI patterns of response in 15 chronic heavy marijuana smokers relative to 15 non-marijuana smoking control subjects during the viewing of masked happy and fearful faces. Despite no between-group differences on clinical or demographic measures, smokers demonstrated a relative decrease in both anterior cingulate and amygdalar activity during masked affective stimuli compared to controls, who showed relative increases in activation within these regions during the viewing of masked faces. Findings indicate that chronic heavy marijuana smokers demonstrate altered activation of frontal and limbic systems while viewing masked faces, consistent with autoradiographic studies reporting high CB-1 receptor density in these regions. These data suggest differences in affective processing in chronic smokers, even when stimuli are presented below the level of conscious processing, and underscore the likelihood that marijuana smokers process emotional information differently from those who do not smoke, which may result in negative consequences.

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

Science.gov (United States)

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

2015-01-01

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

Neutron Scattering and High Magnetic Fields

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Winn, Barry L. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Stone, Matthew B. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

2014-11-01

The workshop “Neutron Scattering and High Magnetic Fields” was held September 4-5, 2014 at the Oak Ridge National Laboratory (ORNL). The workshop was held in response to a recent report by the National Research Council of the National Academy of Sciences entitled “High Magnetic Field Science and Its Application in the United States: Current Status and Future Directions.”1 This report highlights the fact that neutron scattering measurements carried out in high magnetic fields provide important opportunities for new science. The workshop explored the range of the scientific discoveries that could be enabled with neutron scattering measurements at high fields (25 Tesla or larger), the various technologies that might be utilized to build specialized instruments and sample environment equipment to enable this research at ORNL, and possible routes to funding and constructing these facilities and portable high field sample environments.

Convergence of EEG and fMRI measures of reward anticipation.

Science.gov (United States)

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

2015-12-01

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

High Field Workshop

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Anon.

1984-12-15

A Workshop was held in Frascati at the end of September under the title 'Generation of High Fields for Particle Acceleration to Very High Energies'. It was organized by the CERN Accelerator School, the European Committee for Future Accelerators (ECFA) and the Italian INFN and was a further stage in the exploratory moves towards new techniques of acceleration. Such techniques might become necessary to respond to the needs of high energy physics some decades from now when the application of conventional techniques will probably have reached their limits.

Occurrence of dsRNA Mycovirus (LeV-FMRI0339 in the Edible Mushroom Lentinula edodes and Meiotic Stability of LeV-FMRI0339 among Monokaryotic Progeny

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Jung-Mi Kim

2013-12-01

Full Text Available dsRNA was found in malformed cultures of Lentinula edodes strain FMRI0339, one of the three most popular sawdust cultivated commercial strains of shiitake, and was also found in healthy-looking fruiting bodies and actively growing mycelia. Cloning of the partial genome of the dsRNA revealed the presence of the RdRp sequence of a novel L. edodes mycovirus (LeV, and sequence comparison of the cloned amplicon showed identical sequences sequence to known RNA-dependent RNA polymerase genes of LeV found in strain HKA. The meiotic stability of dsRNA was examined by measuring the ratio of the presence of dsRNA among sexual monokaryotic progeny. More than 40% of the monokaryotic progeny still contained the dsRNA, indicating the persistence of dsRNA during sexual reproduction. Comparing the mycelia growth of monokaryotic progeny suggested that there appeared to be a tendency toward a lower frequency of virus incidence in actively growing progeny.

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

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

2006-05-01

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

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

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

2017-02-15

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

Readers select a comprehension mode independent of pronoun: Evidence from fMRI during narrative comprehension.

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Hartung, Franziska; Hagoort, Peter; Willems, Roel M

2017-07-01

Perspective is a crucial feature for communicating about events. Yet it is unclear how linguistically encoded perspective relates to cognitive perspective taking. Here, we tested the effect of perspective taking with short literary stories. Participants listened to stories with 1st or 3rd person pronouns referring to the protagonist, while undergoing fMRI. When comparing action events with 1st and 3rd person pronouns, we found no evidence for a neural dissociation depending on the pronoun. A split sample approach based on the self-reported experience of perspective taking revealed 3 comprehension preferences. One group showed a strong 1st person preference, another a strong 3rd person preference, while a third group engaged in 1st and 3rd person perspective taking simultaneously. Comparing brain activations of the groups revealed different neural networks. Our results suggest that comprehension is perspective dependent, but not on the perspective suggested by the text, but on the reader's (situational) preference. Copyright © 2017 Elsevier Inc. All rights reserved.

Meta-analysis of real-time fMRI neurofeedback studies using individual participant data: How is brain regulation mediated?

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Emmert, Kirsten; Kopel, Rotem; Sulzer, James; Brühl, Annette B; Berman, Brian D; Linden, David E J; Horovitz, Silvina G; Breimhorst, Markus; Caria, Andrea; Frank, Sabine; Johnston, Stephen; Long, Zhiying; Paret, Christian; Robineau, Fabien; Veit, Ralf; Bartsch, Andreas; Beckmann, Christian F; Van De Ville, Dimitri; Haller, Sven

2016-01-01

An increasing number of studies using real-time fMRI neurofeedback have demonstrated that successful regulation of neural activity is possible in various brain regions. Since these studies focused on the regulated region(s), little is known about the target-independent mechanisms associated with neurofeedback-guided control of brain activation, i.e. the regulating network. While the specificity of the activation during self-regulation is an important factor, no study has effectively determined the network involved in self-regulation in general. In an effort to detect regions that are responsible for the act of brain regulation, we performed a post-hoc analysis of data involving different target regions based on studies from different research groups. We included twelve suitable studies that examined nine different target regions amounting to a total of 175 subjects and 899 neurofeedback runs. Data analysis included a standard first- (single subject, extracting main paradigm) and second-level (single subject, all runs) general linear model (GLM) analysis of all participants taking into account the individual timing. Subsequently, at the third level, a random effects model GLM included all subjects of all studies, resulting in an overall mixed effects model. Since four of the twelve studies had a reduced field of view (FoV), we repeated the same analysis in a subsample of eight studies that had a well-overlapping FoV to obtain a more global picture of self-regulation. The GLM analysis revealed that the anterior insula as well as the basal ganglia, notably the striatum, were consistently active during the regulation of brain activation across the studies. The anterior insula has been implicated in interoceptive awareness of the body and cognitive control. Basal ganglia are involved in procedural learning, visuomotor integration and other higher cognitive processes including motivation. The larger FoV analysis yielded additional activations in the anterior cingulate

Music of the 7Ts: Predicting and Decoding Multivoxel fMRI Responses with Acoustic, Schematic, and Categorical Music Features.

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Casey, Michael A

2017-01-01

Underlying the experience of listening to music are parallel streams of auditory, categorical, and schematic qualia, whose representations and cortical organization remain largely unresolved. We collected high-field (7T) fMRI data in a music listening task, and analyzed the data using multivariate decoding and stimulus-encoding models. Twenty subjects participated in the experiment, which measured BOLD responses evoked by naturalistic listening to twenty-five music clips from five genres. Our first analysis applied machine classification to the multivoxel patterns that were evoked in temporal cortex. Results yielded above-chance levels for both stimulus identification and genre classification-cross-validated by holding out data from multiple of the stimuli during model training and then testing decoding performance on the held-out data. Genre model misclassifications were significantly correlated with those in a corresponding behavioral music categorization task, supporting the hypothesis that geometric properties of multivoxel pattern spaces underlie observed musical behavior. A second analysis employed a spherical searchlight regression analysis which predicted multivoxel pattern responses to music features representing melody and harmony across a large area of cortex. The resulting prediction-accuracy maps yielded significant clusters in the temporal, frontal, parietal, and occipital lobes, as well as in the parahippocampal gyrus and the cerebellum. These maps provide evidence in support of our hypothesis that geometric properties of music cognition are neurally encoded as multivoxel representational spaces. The maps also reveal a cortical topography that differentially encodes categorical and absolute-pitch information in distributed and overlapping networks, with smaller specialized regions that encode tonal music information in relative-pitch representations.

Music of the 7Ts: Predicting and Decoding Multivoxel fMRI Responses with Acoustic, Schematic, and Categorical Music Features

Science.gov (United States)

Casey, Michael A.

2017-01-01

Underlying the experience of listening to music are parallel streams of auditory, categorical, and schematic qualia, whose representations and cortical organization remain largely unresolved. We collected high-field (7T) fMRI data in a music listening task, and analyzed the data using multivariate decoding and stimulus-encoding models. Twenty subjects participated in the experiment, which measured BOLD responses evoked by naturalistic listening to twenty-five music clips from five genres. Our first analysis applied machine classification to the multivoxel patterns that were evoked in temporal cortex. Results yielded above-chance levels for both stimulus identification and genre classification–cross-validated by holding out data from multiple of the stimuli during model training and then testing decoding performance on the held-out data. Genre model misclassifications were significantly correlated with those in a corresponding behavioral music categorization task, supporting the hypothesis that geometric properties of multivoxel pattern spaces underlie observed musical behavior. A second analysis employed a spherical searchlight regression analysis which predicted multivoxel pattern responses to music features representing melody and harmony across a large area of cortex. The resulting prediction-accuracy maps yielded significant clusters in the temporal, frontal, parietal, and occipital lobes, as well as in the parahippocampal gyrus and the cerebellum. These maps provide evidence in support of our hypothesis that geometric properties of music cognition are neurally encoded as multivoxel representational spaces. The maps also reveal a cortical topography that differentially encodes categorical and absolute-pitch information in distributed and overlapping networks, with smaller specialized regions that encode tonal music information in relative-pitch representations. PMID:28769835

Advances in high field laser physics

CERN Document Server

Sheng, Zhengming; Chen, Liming; Lu, Wei; Shen, Baifei

2019-01-01

High field laser physics emerged with the advent of ultrashort intense lasers about 25 years ago. It has developed into a frontier of cross-disciplinary studies, covering attosecond X-ray physics, particle accelerator physics, and physics of inertial confined fusion, etc., with prospects of wide applications. Because this is a new and rapidly developing field, so far there are only 2-3 related books available. There are a few review articles in some journals, which are limited to specific topics in high field physics. There are quite a few conference proceedings in this field, which are the collections of papers presented at conferences. In this book, a few leading experts working on different subjects in this field are invited to introduce the key topics in high field laser physics, which cover the involved fundamental physics, the recent advances, as well as the prospects of future applications. It shall be very useful to graduate students, young researchers, and people who want to have an overview of thi...

Functional magnetic resonance imaging of the frontal eye fields during saccadic eye movements

International Nuclear Information System (INIS)

Miki, Atsushi; Takagi, Mineo; Abe, Haruki; Nakajima, Takashi; Miyauchi, Satoru.

1996-01-01

We evaluated activity-induced signal intensity changes in the human cerebral cortex during horizontal saccadic eye movements using functional magnetic resonance imaging (fMRI) based on the blood-oxygenation-level-dependent (BOLD) contrast method. Compared with central fixation, significant signal increases were observed bilaterally in the middle frontal gyrus (Brodmann area 8) during saccadic conditions. The location of the activated area was consistent with that of previously reported frontal eye fields (FEF). These results suggest that fMRI has potential merit for the study of cortical control of eye movements in humans. (author)

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

Science.gov (United States)

Gaberova, Katerina; Pacheva, Iliyana; Ivanov, Ivan

2018-04-27

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

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.

Progress with High-Field Superconducting Magnets for High-Energy Colliders

Science.gov (United States)

Apollinari, Giorgio; Prestemon, Soren; Zlobin, Alexander V.

2015-10-01

One of the possible next steps for high-energy physics research relies on a high-energy hadron or muon collider. The energy of a circular collider is limited by the strength of bending dipoles, and its maximum luminosity is determined by the strength of final focus quadrupoles. For this reason, the high-energy physics and accelerator communities have shown much interest in higher-field and higher-gradient superconducting accelerator magnets. The maximum field of NbTi magnets used in all present high-energy machines, including the LHC, is limited to ˜10 T at 1.9 K. Fields above 10 T became possible with the use of Nb3Sn superconductors. Nb3Sn accelerator magnets can provide operating fields up to ˜15 T and can significantly increase the coil temperature margin. Accelerator magnets with operating fields above 15 T require high-temperature superconductors. This review discusses the status and main results of Nb3Sn accelerator magnet research and development and work toward 20-T magnets.

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

OpenAIRE

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

2009-01-01

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

Comparative study of SVM methods combined with voxel selection for object category classification on fMRI data.

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Song, Sutao; Zhan, Zhichao; Long, Zhiying; Zhang, Jiacai; Yao, Li

2011-02-16

Support vector machine (SVM) has been widely used as accurate and reliable method to decipher brain patterns from functional MRI (fMRI) data. Previous studies have not found a clear benefit for non-linear (polynomial kernel) SVM versus linear one. Here, a more effective non-linear SVM using radial basis function (RBF) kernel is compared with linear SVM. Different from traditional studies which focused either merely on the evaluation of different types of SVM or the voxel selection methods, we aimed to investigate the overall performance of linear and RBF SVM for fMRI classification together with voxel selection schemes on classification accuracy and time-consuming. Six different voxel selection methods were employed to decide which voxels of fMRI data would be included in SVM classifiers with linear and RBF kernels in classifying 4-category objects. Then the overall performances of voxel selection and classification methods were compared. Results showed that: (1) Voxel selection had an important impact on the classification accuracy of the classifiers: in a relative low dimensional feature space, RBF SVM outperformed linear SVM significantly; in a relative high dimensional space, linear SVM performed better than its counterpart; (2) Considering the classification accuracy and time-consuming holistically, linear SVM with relative more voxels as features and RBF SVM with small set of voxels (after PCA) could achieve the better accuracy and cost shorter time. The present work provides the first empirical result of linear and RBF SVM in classification of fMRI data, combined with voxel selection methods. Based on the findings, if only classification accuracy was concerned, RBF SVM with appropriate small voxels and linear SVM with relative more voxels were two suggested solutions; if users concerned more about the computational time, RBF SVM with relative small set of voxels when part of the principal components were kept as features was a better choice.

The supraspinal neural correlate of bladder cold sensation--an fMRI study.

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Mehnert, Ulrich; Michels, Lars; Zempleni, Monika-Zita; Schurch, Brigitte; Kollias, Spyros

2011-06-01

In recent years, functional imaging studies have revealed a supraspinal network, which is involved in perception and processing of bladder distention. Very little information exists on the cortical representation of C-fiber transmitted temperature sensation of the human bladder, although C-fibers seem to be involved in the pathomechanisms of bladder dysfunctions. Our aim was, therefore, to evaluate the outcome of bladder cold stimulation on supraspinal activity using functional magnetic resonance imaging (fMRI). A block design fMRI study was performed in 14 healthy females at the MR-center of the University of Zurich. After catheterization, all subjects were investigated in a 3.0-Tesla Scanner. The scanning consisted of 10 repetitive cycles. Each cycle consisted of five conditions: REST, INFUSION, SENSATION, DRAIN 1, and DRAIN 2. Cold saline was passively infused at 4-8°C during scanning. Not more than 100 ml were infused per cycle. Blood-oxygen-level-dependent (BOLD) signal analysis of the different conditions was compared to REST. All activations were evaluated on a random effects level at P = 0.001. Activation of brain regions for bladder cold stimulation (DRAIN 1 period) was found bilaterally in the inferior parietal lobe [Brodmann area (BA) 40], the right insula (BA 13), the right cerebellar posterior lobe, the right middle temporal gyrus (BA 20), and the right postcentral gyrus (BA 3). In conclusion, bladder cooling caused a different supraspinal activation pattern compared to what is known to occur during bladder distention. This supports our hypothesis that cold sensation is processed differently from bladder distension at the supraspinal level. Copyright © 2010 Wiley-Liss, Inc.

Droplet size characteristics and energy input requirements of emulsions formed using high-intensity-pulsed electric fields

International Nuclear Information System (INIS)

Scott, T.C.; Sisson, W.G.

1987-01-01

Experimental methods have been developed to measure droplet size characteristics and energy inputs associated with the rupture of aqueous droplets by high-intensity-pulsed electric fields. The combination of in situ microscope optics and high-speed video cameras allows reliable observation of liquid droplets down to 0.5 μm in size. Videotapes of electric-field-created emulsions reveal that average droplet sizes of less than 5 μm are easily obtained in such systems. Analysis of the energy inputs into the fluids indicates that the electric field method requires less than 1% of the energy required from mechanical agitation to create comparable droplet sizes. 11 refs., 3 figs., 2 tabs

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

International Nuclear Information System (INIS)

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

1995-01-01

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

High-performance field emission device utilizing vertically aligned carbon nanotubes-based pillar architectures

Science.gov (United States)

Gupta, Bipin Kumar; Kedawat, Garima; Gangwar, Amit Kumar; Nagpal, Kanika; Kashyap, Pradeep Kumar; Srivastava, Shubhda; Singh, Satbir; Kumar, Pawan; Suryawanshi, Sachin R.; Seo, Deok Min; Tripathi, Prashant; More, Mahendra A.; Srivastava, O. N.; Hahm, Myung Gwan; Late, Dattatray J.

2018-01-01

The vertical aligned carbon nanotubes (CNTs)-based pillar architectures were created on laminated silicon oxide/silicon (SiO2/Si) wafer substrate at 775 °C by using water-assisted chemical vapor deposition under low pressure process condition. The lamination was carried out by aluminum (Al, 10.0 nm thickness) as a barrier layer and iron (Fe, 1.5 nm thickness) as a catalyst precursor layer sequentially on a silicon wafer substrate. Scanning electron microscope (SEM) images show that synthesized CNTs are vertically aligned and uniformly distributed with a high density. The CNTs have approximately 2-30 walls with an inner diameter of 3-8 nm. Raman spectrum analysis shows G-band at 1580 cm-1 and D-band at 1340 cm-1. The G-band is higher than D-band, which indicates that CNTs are highly graphitized. The field emission analysis of the CNTs revealed high field emission current density (4mA/cm2 at 1.2V/μm), low turn-on field (0.6 V/μm) and field enhancement factor (6917) with better stability and longer lifetime. Emitter morphology resulting in improved promising field emission performances, which is a crucial factor for the fabrication of pillared shaped vertical aligned CNTs bundles as practical electron sources.

High-performance field emission device utilizing vertically aligned carbon nanotubes-based pillar architectures

Directory of Open Access Journals (Sweden)

Bipin Kumar Gupta

2018-01-01

Full Text Available The vertical aligned carbon nanotubes (CNTs-based pillar architectures were created on laminated silicon oxide/silicon (SiO2/Si wafer substrate at 775 °C by using water-assisted chemical vapor deposition under low pressure process condition. The lamination was carried out by aluminum (Al, 10.0 nm thickness as a barrier layer and iron (Fe, 1.5 nm thickness as a catalyst precursor layer sequentially on a silicon wafer substrate. Scanning electron microscope (SEM images show that synthesized CNTs are vertically aligned and uniformly distributed with a high density. The CNTs have approximately 2–30 walls with an inner diameter of 3–8 nm. Raman spectrum analysis shows G-band at 1580 cm−1 and D-band at 1340 cm−1. The G-band is higher than D-band, which indicates that CNTs are highly graphitized. The field emission analysis of the CNTs revealed high field emission current density (4mA/cm2 at 1.2V/μm, low turn-on field (0.6 V/μm and field enhancement factor (6917 with better stability and longer lifetime. Emitter morphology resulting in improved promising field emission performances, which is a crucial factor for the fabrication of pillared shaped vertical aligned CNTs bundles as practical electron sources.

Effect of Phase-Encoding Reduction on Geometric Distortion and BOLD Signal Changes in fMRI

Directory of Open Access Journals (Sweden)

Golestan karami

2013-03-01

Full Text Available Introduction Echo-planar imaging (EPI is a group of fast data acquisition methods commonly used in fMRI studies. It acquires multiple image lines in k-space after a single excitation, which leads to a very short scan time. A well-known problem with EPI is that it is more sensitive to distortions due to the used encoding scheme. Source of distortion is inhomogeneity in the static B0 field that causes more geometric distortion in phase encoding direction. This inhomogeneity is induced mainly by the magnetic susceptibility differences between various structures within the object placed inside the scanner, often at air-tissue or bone-tissue interfaces. Methods of reducing EPI distortion are mainly based on decreasing steps of the phase encoding. Reducing steps of phase encoding can be applied by reducing field of view, slice thickness, and/or the use of parallel acquisition technique. Materials and Methods We obtained three data acquisitions with different FOVs including: conventional low resolution, conventional high resolution, and zoomed high resolution EPIs. Moreover we used SENSE technique for phase encoding reduction. All experiments were carried out on three Tesla scanners (Siemens, TIM, and Germany equipped with 12 channel head coil. Ten subjects participated in the experiments. Results The data were processed by FSL software and were evaluated by ANOVA. Distortion was assessed by obtaining low displacement voxels map, and calculated from a field map image. Conclusion We showed that image distortion can be reduced by decreasing slice thickness and phase encoding steps. Distortion reduction in zoomed technique resulted the lowest level, but at the cost of signal-to-noise loss. Moreover, the SENSE technique was shown to decrease the amount of image distortion, efficiently.

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

International Nuclear Information System (INIS)

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

2003-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2003-05-21

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

Brain-to-brain hyperclassification reveals action-specific motor mapping of observed actions in humans.

Science.gov (United States)

Smirnov, Dmitry; Lachat, Fanny; Peltola, Tomi; Lahnakoski, Juha M; Koistinen, Olli-Pekka; Glerean, Enrico; Vehtari, Aki; Hari, Riitta; Sams, Mikko; Nummenmaa, Lauri

2017-01-01

Seeing an action may activate the corresponding action motor code in the observer. It remains unresolved whether seeing and performing an action activates similar action-specific motor codes in the observer and the actor. We used novel hyperclassification approach to reveal shared brain activation signatures of action execution and observation in interacting human subjects. In the first experiment, two "actors" performed four types of hand actions while their haemodynamic brain activations were measured with 3-T functional magnetic resonance imaging (fMRI). The actions were videotaped and shown to 15 "observers" during a second fMRI experiment. Eleven observers saw the videos of one actor, and the remaining four observers saw the videos of the other actor. In a control fMRI experiment, one of the actors performed actions with closed eyes, and five new observers viewed these actions. Bayesian canonical correlation analysis was applied to functionally realign observers' and actors' fMRI data. Hyperclassification of the seen actions was performed with Bayesian logistic regression trained on actors' data and tested with observers' data. Without the functional realignment, between-subjects accuracy was at chance level. With the realignment, the accuracy increased on average by 15 percentage points, exceeding both the chance level and the accuracy without functional realignment. The highest accuracies were observed in occipital, parietal and premotor cortices. Hyperclassification exceeded chance level also when the actor did not see her own actions. We conclude that the functional brain activation signatures underlying action execution and observation are partly shared, yet these activation signatures may be anatomically misaligned across individuals.