Functional MRI and intraoperative brain mapping to evaluate brain plasticity in patients with brain tumours and hemiparesis

PubMed Central

Roux, F; Boulanouar, K; Ibarrola, D; Tremoulet, M; Chollet, F; Berry, I

2000-01-01

OBJECTIVE—To support the hypothesis about the potential compensatory role of ipsilateral corticofugal pathways when the contralateral pathways are impaired by brain tumours.
METHODS—Retrospective analysis was carried out on the results of functional MRI (fMRI) of a selected group of five paretic patients with Rolandic brain tumours who exhibited an abnormally high ipsilateral/contralateral ratio of activation—that is, movements of the paretic hand activated predominately the ipsilateral cortex. Brain activation was achieved with a flexion extension of the fingers. Statistical parametric activation was obtained using a t test and a threshold of p<0.001. These patients, candidates for tumour resection, also underwent cortical intraoperative stimulation that was correlated to the fMRI spatial data using three dimensional reconstructions of the brain. Three patients also had postoperative control fMRI.
RESULTS—The absence of fMRI activation of the primary sensorimotor cortex normally innervating the paretic hand for the threshold chosen, was correlated with completely negative cortical responses of the cortical hand area during the operation. The preoperative fMRI activation of these patients predominantly found in the ipsilateral frontal and primary sensorimotor cortices could be related to the residual ipsilateral hand function. Postoperatively, the fMRI activation returned to more classic patterns of activation, reflecting the consequences of therapy.
CONCLUSION—In paretic patients with brain tumours, ipsilateral control could be implicated in the residual hand function, when the normal primary pathways are impaired. The possibility that functional tissue still remains in the peritumorous sensorimotor cortex even when the preoperative fMRI and the cortical intraoperative stimulations are negative, should be taken into account when planning the tumour resection and during the operation.

 PMID:10990503

Optimizing real time fMRI neurofeedback for therapeutic discovery and development

PubMed Central

Stoeckel, L.E.; Garrison, K.A.; Ghosh, S.; Wighton, P.; Hanlon, C.A.; Gilman, J.M.; Greer, S.; Turk-Browne, N.B.; deBettencourt, M.T.; Scheinost, D.; Craddock, C.; Thompson, T.; Calderon, V.; Bauer, C.C.; George, M.; Breiter, H.C.; Whitfield-Gabrieli, S.; Gabrieli, J.D.; LaConte, S.M.; Hirshberg, L.; Brewer, J.A.; Hampson, M.; Van Der Kouwe, A.; Mackey, S.; Evins, A.E.

2014-01-01

While reducing the burden of brain disorders remains a top priority of organizations like the World Health Organization and National Institutes of Health, the development of novel, safe and effective treatments for brain disorders has been slow. In this paper, we describe the state of the science for an emerging technology, real time functional magnetic resonance imaging (rtfMRI) neurofeedback, in clinical neurotherapeutics. We review the scientific potential of rtfMRI and outline research strategies to optimize the development and application of rtfMRI neurofeedback as a next generation therapeutic tool. We propose that rtfMRI can be used to address a broad range of clinical problems by improving our understanding of brain–behavior relationships in order to develop more specific and effective interventions for individuals with brain disorders. We focus on the use of rtfMRI neurofeedback as a clinical neurotherapeutic tool to drive plasticity in brain function, cognition, and behavior. Our overall goal is for rtfMRI to advance personalized assessment and intervention approaches to enhance resilience and reduce morbidity by correcting maladaptive patterns of brain function in those with brain disorders. PMID:25161891

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

PubMed

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

2014-01-01

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

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

PubMed Central

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

2014-01-01

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

Individual differences in intrinsic brain connectivity predict decision strategy.

PubMed

Barnes, Kelly Anne; Anderson, Kevin M; Plitt, Mark; Martin, Alex

2014-10-15

When humans are provided with ample time to make a decision, individual differences in strategy emerge. Using an adaptation of a well-studied decision making paradigm, motion direction discrimination, we probed the neural basis of individual differences in strategy. We tested whether strategies emerged from moment-to-moment reconfiguration of functional brain networks involved in decision making with task-evoked functional MRI (fMRI) and whether intrinsic properties of functional brain networks, measured at rest with functional connectivity MRI (fcMRI), were associated with strategy use. We found that human participants reliably selected one of two strategies across 2 days of task performance, either continuously accumulating evidence or waiting for task difficulty to decrease. Individual differences in decision strategy were predicted both by the degree of task-evoked activation of decision-related brain regions and by the strength of pretask correlated spontaneous brain activity. These results suggest that spontaneous brain activity constrains strategy selection on perceptual decisions.

Pushing spatial and temporal resolution for functional and diffusion MRI in the Human Connectome Project

PubMed Central

Uğurbil, Kamil; Xu, Junqian; Auerbach, Edward J.; Moeller, Steen; Vu, An; Duarte-Carvajalino, Julio M.; Lenglet, Christophe; Wu, Xiaoping; Schmitter, Sebastian; Van de Moortele, Pierre Francois; Strupp, John; Sapiro, Guillermo; De Martino, Federico; Wang, Dingxin; Harel, Noam; Garwood, Michael; Chen, Liyong; Feinberg, David A.; Smith, Stephen M.; Miller, Karla L.; Sotiropoulos, Stamatios N; Jbabdi, Saad; Andersson, Jesper L; Behrens, Timothy EJ; Glasser, Matthew F.; Van Essen, David; Yacoub, Essa

2013-01-01

The human connectome project (HCP) relies primarily on three complementary magnetic resonance (MR) methods. These are: 1) resting state functional MR imaging (rfMRI) which uses correlations in the temporal fluctuations in an fMRI time series to deduce ‘functional connectivity’; 2) diffusion imaging (dMRI), which provides the input for tractography algorithms used for the reconstruction of the complex axonal fiber architecture; and 3) task based fMRI (tfMRI), which is employed to identify functional parcellation in the human brain in order to assist analyses of data obtained with the first two methods. We describe technical improvements and optimization of these methods as well as instrumental choices that impact speed of acquisition of fMRI and dMRI images at 3 Tesla, leading to whole brain coverage with 2 mm isotropic resolution in 0.7 second for fMRI, and 1.25 mm isotropic resolution dMRI data for tractography analysis with three-fold reduction in total data acquisition time. Ongoing technical developments and optimization for acquisition of similar data at 7 Tesla magnetic field are also presented, targeting higher resolution, specificity of functional imaging signals, mitigation of the inhomogeneous radio frequency (RF) fields and power deposition. Results demonstrate that overall, these approaches represent a significant advance in MR imaging of the human brain to investigate brain function and structure. PMID:23702417

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

PubMed

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

2015-02-01

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

Anatomo-clinical overlapping maps (AnaCOM): a new method to create anatomo-functional maps from neuropsychological tests and structural MRI scan of subjects with brain lesions

NASA Astrophysics Data System (ADS)

Kinkingnehun, Serge R. J.; du Boisgueheneuc, Foucaud; Golmard, Jean-Louis; Zhang, Sandy X.; Levy, Richard; Dubois, Bruno

2004-04-01

We have developed a new technique to analyze correlations between brain anatomy and its neurological functions. The technique is based on the anatomic MRI of patients with brain lesions who are administered neuropsychological tests. Brain lesions of the MRI scans are first manually segmented. The MRI volumes are then normalized to a reference map, using the segmented area as a mask. After normalization, the brain lesions of the MRI are segmented again in order to redefine the border of the lesions in the context of the normalized brain. Once the MRI is segmented, the patient's score on the neuropsychological test is assigned to each voxel in the lesioned area, while the rest of the voxels of the image are set to 0. Subsequently, the individual patient's MRI images are superimposed, and each voxel is reassigned the average score of the patients who have a lesion at that voxel. A threshold is applied to remove regions having less than three overlaps. This process leads to an anatomo-functional map that links brain areas to functional loss. Other maps can be created to aid in analyzing the functional maps, such as one that indicates the 95% confidence interval of the averaged scores for each area. This anatomo-clinical overlapping map (AnaCOM) method was used to obtain functional maps from patients with lesions in the superior frontal gyrus. By finding particular subregions more responsible for a particular deficit, this method can generate new hypotheses to be tested by conventional group methods.

MRI with intrathecal MRI gadolinium contrast medium administration: a possible method to assess glymphatic function in human brain.

PubMed

Eide, Per Kristian; Ringstad, Geir

2015-11-01

Recently, the "glymphatic system" of the brain has been discovered in rodents, which is a paravascular, transparenchymal route for clearance of excess brain metabolites and distribution of compounds in the cerebrospinal fluid. It has already been demonstrated that intrathecally administered gadolinium (Gd) contrast medium distributes along this route in rats, but so far not in humans. A 27-year-old woman underwent magnetic resonance imaging (MRI) with intrathecal administration of gadobutrol, which distributed throughout her entire brain after 1 and 4.5 h. MRI with intrathecal Gd may become a tool to study glymphatic function in the human brain.

Laminar fMRI and computational theories of brain function.

PubMed

Stephan, K E; Petzschner, F H; Kasper, L; Bayer, J; Wellstein, K V; Stefanics, G; Pruessmann, K P; Heinzle, J

2017-11-02

Recently developed methods for functional MRI at the resolution of cortical layers (laminar fMRI) offer a novel window into neurophysiological mechanisms of cortical activity. Beyond physiology, laminar fMRI also offers an unprecedented opportunity to test influential theories of brain function. Specifically, hierarchical Bayesian theories of brain function, such as predictive coding, assign specific computational roles to different cortical layers. Combined with computational models, laminar fMRI offers a unique opportunity to test these proposals noninvasively in humans. This review provides a brief overview of predictive coding and related hierarchical Bayesian theories, summarises their predictions with regard to layered cortical computations, examines how these predictions could be tested by laminar fMRI, and considers methodological challenges. We conclude by discussing the potential of laminar fMRI for clinically useful computational assays of layer-specific information processing. Copyright © 2017 Elsevier Inc. All rights reserved.

Functional Brain Activation Differences in Stuttering Identified with a Rapid fMRI Sequence

ERIC Educational Resources Information Center

Loucks, Torrey; 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…

Graph-based network analysis of resting-state functional MRI.

PubMed

Wang, Jinhui; Zuo, Xinian; He, Yong

2010-01-01

In the past decade, resting-state functional MRI (R-fMRI) measures of brain activity have attracted considerable attention. Based on changes in the blood oxygen level-dependent signal, R-fMRI offers a novel way to assess the brain's spontaneous or intrinsic (i.e., task-free) activity with both high spatial and temporal resolutions. The properties of both the intra- and inter-regional connectivity of resting-state brain activity have been well documented, promoting our understanding of the brain as a complex network. Specifically, the topological organization of brain networks has been recently studied with graph theory. In this review, we will summarize the recent advances in graph-based brain network analyses of R-fMRI signals, both in typical and atypical populations. Application of these approaches to R-fMRI data has demonstrated non-trivial topological properties of functional networks in the human brain. Among these is the knowledge that the brain's intrinsic activity is organized as a small-world, highly efficient network, with significant modularity and highly connected hub regions. These network properties have also been found to change throughout normal development, aging, and in various pathological conditions. The literature reviewed here suggests that graph-based network analyses are capable of uncovering system-level changes associated with different processes in the resting brain, which could provide novel insights into the understanding of the underlying physiological mechanisms of brain function. We also highlight several potential research topics in the future.

Development of the brain's functional network architecture.

PubMed

Vogel, Alecia C; Power, Jonathan D; Petersen, Steven E; Schlaggar, Bradley L

2010-12-01

A full understanding of the development of the brain's functional network architecture requires not only an understanding of developmental changes in neural processing in individual brain regions but also an understanding of changes in inter-regional interactions. Resting state functional connectivity MRI (rs-fcMRI) is increasingly being used to study functional interactions between brain regions in both adults and children. We briefly review methods used to study functional interactions and networks with rs-fcMRI and how these methods have been used to define developmental changes in network functional connectivity. The developmental rs-fcMRI studies to date have found two general properties. First, regional interactions change from being predominately anatomically local in children to interactions spanning longer cortical distances in young adults. Second, this developmental change in functional connectivity occurs, in general, via mechanisms of segregation of local regions and integration of distant regions into disparate subnetworks.

Development of the Brain's Functional Network Architecture

PubMed Central

Power, Jonathan D.; Petersen, Steven E.; Schlaggar, Bradley L.

2013-01-01

A full understanding of the development of the brain's functional network architecture requires not only an understanding of developmental changes in neural processing in individual brain regions but also an understanding of changes in inter-regional interactions. Resting state functional connectivity MRI (rs-fcMRI) is increasingly being used to study functional interactions between brain regions in both adults and children. We briefly review methods used to study functional interactions and networks with rs-fcMRI and how these methods have been used to define developmental changes in network functional connectivity. The developmental rs-fcMRI studies to date have found two general properties. First, regional interactions change from being predominately anatomically local in children to interactions spanning longer cortical distances in young adults. Second, this developmental change in functional connectivity occurs, in general, via mechanisms of segregation of local regions and integration of distant regions into disparate subnetworks. PMID:20976563

Neurological soft signs are not "soft" in brain structure and functional networks: evidence from ALE meta-analysis.

PubMed

Zhao, Qing; Li, Zhi; Huang, Jia; Yan, Chao; Dazzan, Paola; Pantelis, Christos; Cheung, Eric F C; Lui, Simon S Y; Chan, Raymond C K

2014-05-01

Neurological soft signs (NSS) are associated with schizophrenia and related psychotic disorders. NSS have been conventionally considered as clinical neurological signs without localized brain regions. However, recent brain imaging studies suggest that NSS are partly localizable and may be associated with deficits in specific brain areas. We conducted an activation likelihood estimation meta-analysis to quantitatively review structural and functional imaging studies that evaluated the brain correlates of NSS in patients with schizophrenia and other psychotic disorders. Six structural magnetic resonance imaging (sMRI) and 15 functional magnetic resonance imaging (fMRI) studies were included. The results from meta-analysis of the sMRI studies indicated that NSS were associated with atrophy of the precentral gyrus, the cerebellum, the inferior frontal gyrus, and the thalamus. The results from meta-analysis of the fMRI studies demonstrated that the NSS-related task was significantly associated with altered brain activation in the inferior frontal gyrus, bilateral putamen, the cerebellum, and the superior temporal gyrus. Our findings from both sMRI and fMRI meta-analyses further support the conceptualization of NSS as a manifestation of the "cerebello-thalamo-prefrontal" brain network model of schizophrenia and related psychotic disorders.

In vivo Visuotopic Brain Mapping with Manganese-Enhanced MRI and Resting-State Functional Connectivity MRI

PubMed Central

Chan, Kevin C.; Fan, Shu-Juan; Chan, Russell W.; Cheng, Joe S.; Zhou, Iris Y.; Wu, Ed X.

2014-01-01

The rodents are an increasingly important model for understanding the mechanisms of development, plasticity, functional specialization and disease in the visual system. However, limited tools have been available for assessing the structural and functional connectivity of the visual brain network globally, in vivo and longitudinally. There are also ongoing debates on whether functional brain connectivity directly reflects structural brain connectivity. In this study, we explored the feasibility of manganese-enhanced MRI (MEMRI) via 3 different routes of Mn2+ administration for visuotopic brain mapping and understanding of physiological transport in normal and visually deprived adult rats. In addition, resting-state functional connectivity MRI (RSfcMRI) was performed to evaluate the intrinsic functional network and structural-functional relationships in the corresponding anatomical visual brain connections traced by MEMRI. Upon intravitreal, subcortical, and intracortical Mn2+ injection, different topographic and layer-specific Mn enhancement patterns could be revealed in the visual cortex and subcortical visual nuclei along retinal, callosal, cortico-subcortical, transsynaptic and intracortical horizontal connections. Loss of visual input upon monocular enucleation to adult rats appeared to reduce interhemispheric polysynaptic Mn2+ transfer but not intra- or inter-hemispheric monosynaptic Mn2+ transport after Mn2+ injection into visual cortex. In normal adults, both structural and functional connectivity by MEMRI and RSfcMRI was stronger interhemispherically between bilateral primary/secondary visual cortex (V1/V2) transition zones (TZ) than between V1/V2 TZ and other cortical nuclei. Intrahemispherically, structural and functional connectivity was stronger between visual cortex and subcortical visual nuclei than between visual cortex and other subcortical nuclei. The current results demonstrated the sensitivity of MEMRI and RSfcMRI for assessing the neuroarchitecture, neurophysiology and structural-functional relationships of the visual brains in vivo. These may possess great potentials for effective monitoring and understanding of the basic anatomical and functional connections in the visual system during development, plasticity, disease, pharmacological interventions and genetic modifications in future studies. PMID:24394694

Resting State Network Topology of the Ferret Brain

PubMed Central

Zhou, Zhe Charles; Salzwedel, Andrew P.; Radtke-Schuller, Susanne; Li, Yuhui; Sellers, Kristin K.; Gilmore, John H.; Shih, Yen-Yu Ian; Fröhlich, Flavio; Gao, Wei

2016-01-01

Resting state functional magnetic resonance imaging (rsfMRI) has emerged as a versatile tool for non-invasive measurement of functional connectivity patterns in the brain. RsfMRI brain dynamics in rodents, non-human primates, and humans share similar properties; however, little is known about the resting state functional connectivity patterns in the ferret, an animal model with high potential for developmental and cognitive translational study. To address this knowledge-gap, we performed rsfMRI on anesthetized ferrets using a 9.4 tesla MRI scanner, and subsequently performed group-level independent component analysis (gICA) to identify functionally connected brain networks. Group-level ICA analysis revealed distributed sensory, motor, and higher-order networks in the ferret brain. Subsequent connectivity analysis showed interconnected higher-order networks that constituted a putative default mode network (DMN), a network that exhibits altered connectivity in neuropsychiatric disorders. Finally, we assessed ferret brain topological efficiency using graph theory analysis and found that the ferret brain exhibits small-world properties. Overall, these results provide additional evidence for pan-species resting-state networks, further supporting ferret-based studies of sensory and cognitive function. PMID:27596024

Individual Brain Charting, a high-resolution fMRI dataset for cognitive mapping.

PubMed

Pinho, Ana Luísa; Amadon, Alexis; Ruest, Torsten; Fabre, Murielle; Dohmatob, Elvis; Denghien, Isabelle; Ginisty, Chantal; Becuwe-Desmidt, Séverine; Roger, Séverine; Laurier, Laurence; Joly-Testault, Véronique; Médiouni-Cloarec, Gaëlle; Doublé, Christine; Martins, Bernadette; Pinel, Philippe; Eger, Evelyn; Varoquaux, Gaël; Pallier, Christophe; Dehaene, Stanislas; Hertz-Pannier, Lucie; Thirion, Bertrand

2018-06-12

Functional Magnetic Resonance Imaging (fMRI) has furthered brain mapping on perceptual, motor, as well as higher-level cognitive functions. However, to date, no data collection has systematically addressed the functional mapping of cognitive mechanisms at a fine spatial scale. The Individual Brain Charting (IBC) project stands for a high-resolution multi-task fMRI dataset that intends to provide the objective basis toward a comprehensive functional atlas of the human brain. The data refer to a cohort of 12 participants performing many different tasks. The large amount of task-fMRI data on the same subjects yields a precise mapping of the underlying functions, free from both inter-subject and inter-site variability. The present article gives a detailed description of the first release of the IBC dataset. It comprises a dozen of tasks, addressing both low- and high- level cognitive functions. This openly available dataset is thus intended to become a reference for cognitive brain mapping.

Functional MR imaging assessment of a non-responsive brain injured patient.

PubMed

Moritz, C H; Rowley, H A; Haughton, V M; Swartz, K R; Jones, J; Badie, B

2001-10-01

Functional magnetic resonance imaging (fMRI) was requested to assist in the evaluation of a comatose 38-year-old woman who had sustained multiple cerebral contusions from a motor vehicle accident. Previous electrophysiologic studies suggested absence of thalamocortical processing in response to median nerve stimulation. Whole-brain fMRI was performed utilizing visual, somatosensory, and auditory stimulation paradigms. Results demonstrated intact task-correlated sensory and cognitive blood oxygen level dependent (BOLD) hemodynamic response to stimuli. Electrodiagnostic studies were repeated and evoked potentials indicated supratentorial recovery in the cerebrum. At 3-months post trauma the patient had recovered many cognitive & sensorimotor functions, accurately reflecting the prognostic fMRI evaluation. These results indicate that fMRI examinations may provide a useful evaluation for brain function in non-responsive brain trauma patients.

Neuroelectrical Decomposition of Spontaneous Brain Activity Measured with Functional Magnetic Resonance Imaging

PubMed Central

Liu, Zhongming; de Zwart, Jacco A.; Chang, Catie; Duan, Qi; van Gelderen, Peter; Duyn, Jeff H.

2014-01-01

Spontaneous activity in the human brain occurs in complex spatiotemporal patterns that may reflect functionally specialized neural networks. Here, we propose a subspace analysis method to elucidate large-scale networks by the joint analysis of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data. The new approach is based on the notion that the neuroelectrical activity underlying the fMRI signal may have EEG spectral features that report on regional neuronal dynamics and interregional interactions. Applying this approach to resting healthy adults, we indeed found characteristic spectral signatures in the EEG correlates of spontaneous fMRI signals at individual brain regions as well as the temporal synchronization among widely distributed regions. These spectral signatures not only allowed us to parcel the brain into clusters that resembled the brain's established functional subdivision, but also offered important clues for disentangling the involvement of individual regions in fMRI network activity. PMID:23796947

A Protocol for the Administration of Real-Time fMRI Neurofeedback Training

PubMed Central

Sherwood, Matthew S.; Diller, Emily E.; Ey, Elizabeth; Ganapathy, Subhashini; Nelson, Jeremy T.; Parker, Jason G.

2017-01-01

Neurologic disorders are characterized by abnormal cellular-, molecular-, and circuit-level functions in the brain. New methods to induce and control neuroplastic processes and correct abnormal function, or even shift functions from damaged tissue to physiologically healthy brain regions, hold the potential to dramatically improve overall health. Of the current neuroplastic interventions in development, neurofeedback training (NFT) from functional Magnetic Resonance Imaging (fMRI) has the advantages of being completely non-invasive, non-pharmacologic, and spatially localized to target brain regions, as well as having no known side effects. Furthermore, NFT techniques, initially developed using fMRI, can often be translated to exercises that can be performed outside of the scanner without the aid of medical professionals or sophisticated medical equipment. In fMRI NFT, the fMRI signal is measured from specific regions of the brain, processed, and presented to the participant in real-time. Through training, self-directed mental processing techniques, that regulate this signal and its underlying neurophysiologic correlates, are developed. FMRI NFT has been used to train volitional control over a wide range of brain regions with implications for several different cognitive, behavioral, and motor systems. Additionally, fMRI NFT has shown promise in a broad range of applications such as the treatment of neurologic disorders and the augmentation of baseline human performance. In this article, we present an fMRI NFT protocol developed at our institution for modulation of both healthy and abnormal brain function, as well as examples of using the method to target both cognitive and auditory regions of the brain. PMID:28872110

A Protocol for the Administration of Real-Time fMRI Neurofeedback Training.

PubMed

Sherwood, Matthew S; Diller, Emily E; Ey, Elizabeth; Ganapathy, Subhashini; Nelson, Jeremy T; Parker, Jason G

2017-08-24

Neurologic disorders are characterized by abnormal cellular-, molecular-, and circuit-level functions in the brain. New methods to induce and control neuroplastic processes and correct abnormal function, or even shift functions from damaged tissue to physiologically healthy brain regions, hold the potential to dramatically improve overall health. Of the current neuroplastic interventions in development, neurofeedback training (NFT) from functional Magnetic Resonance Imaging (fMRI) has the advantages of being completely non-invasive, non-pharmacologic, and spatially localized to target brain regions, as well as having no known side effects. Furthermore, NFT techniques, initially developed using fMRI, can often be translated to exercises that can be performed outside of the scanner without the aid of medical professionals or sophisticated medical equipment. In fMRI NFT, the fMRI signal is measured from specific regions of the brain, processed, and presented to the participant in real-time. Through training, self-directed mental processing techniques, that regulate this signal and its underlying neurophysiologic correlates, are developed. FMRI NFT has been used to train volitional control over a wide range of brain regions with implications for several different cognitive, behavioral, and motor systems. Additionally, fMRI NFT has shown promise in a broad range of applications such as the treatment of neurologic disorders and the augmentation of baseline human performance. In this article, we present an fMRI NFT protocol developed at our institution for modulation of both healthy and abnormal brain function, as well as examples of using the method to target both cognitive and auditory regions of the brain.

Joint brain connectivity estimation from diffusion and functional MRI data

NASA Astrophysics Data System (ADS)

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

2015-03-01

Estimating brain wiring patterns is critical to better understand the brain organization and function. Anatomical brain connectivity models axonal pathways, while the functional brain connectivity characterizes the statistical dependencies and correlation between the activities of various brain regions. The synchronization of brain activity can be inferred through the variation of blood-oxygen-level dependent (BOLD) signal from functional MRI (fMRI) and the neural connections can be estimated using tractography from diffusion MRI (dMRI). Functional connections between brain regions are supported by anatomical connections, and the synchronization of brain activities arises through sharing of information in the form of electro-chemical signals on axon pathways. Jointly modeling fMRI and dMRI data may improve the accuracy in constructing anatomical connectivity as well as functional connectivity. Such an approach may lead to novel multimodal biomarkers potentially able to better capture functional and anatomical connectivity variations. We present a novel brain network model which jointly models the dMRI and fMRI data to improve the anatomical connectivity estimation and extract the anatomical subnetworks associated with specific functional modes by constraining the anatomical connections as structural supports to the functional connections. The key idea is similar to a multi-commodity flow optimization problem that minimizes the cost or maximizes the efficiency for flow configuration and simultaneously fulfills the supply-demand constraint for each commodity. In the proposed network, the nodes represent the grey matter (GM) regions providing brain functionality, and the links represent white matter (WM) fiber bundles connecting those regions and delivering information. The commodities can be thought of as the information corresponding to brain activity patterns as obtained for instance by independent component analysis (ICA) of fMRI data. The concept of information flow is introduced and used to model the propagation of information between GM areas through WM fiber bundles. The link capacity, i.e., ability to transfer information, is characterized by the relative strength of fiber bundles, e.g., fiber count gathered from the tractography of dMRI data. The node information demand is considered to be proportional to the correlation between neural activity at various cortical areas involved in a particular functional mode (e.g. visual, motor, etc.). These two properties lead to the link capacity and node demand constraints in the proposed model. Moreover, the information flow of a link cannot exceed the demand from either end node. This is captured by the feasibility constraints. Two different cost functions are considered in the optimization formulation in this paper. The first cost function, the reciprocal of fiber strength represents the unit cost for information passing through the link. In the second cost function, a min-max (minimizing the maximal link load) approach is used to balance the usage of each link. Optimizing the first cost function selects the pathway with strongest fiber strength for information propagation. In the second case, the optimization procedure finds all the possible propagation pathways and allocates the flow proportionally to their strength. Additionally, a penalty term is incorporated with both the cost functions to capture the possible missing and weak anatomical connections. With this set of constraints and the proposed cost functions, solving the network optimization problem recovers missing and weak anatomical connections supported by the functional information and provides the functional-associated anatomical subnetworks. Feasibility is demonstrated using realistic diffusion and functional MRI phantom data. It is shown that the proposed model recovers the maximum number of true connections, with fewest number of false connections when compared with the connectivity derived from a joint probabilistic model using the expectation-maximization (EM) algorithm presented in a prior work. We also apply the proposed method to data provided by the Human Connectome Project (HCP).

MRI with intrathecal MRI gadolinium contrast medium administration: a possible method to assess glymphatic function in human brain

PubMed Central

Ringstad, Geir

2015-01-01

Recently, the “glymphatic system” of the brain has been discovered in rodents, which is a paravascular, transparenchymal route for clearance of excess brain metabolites and distribution of compounds in the cerebrospinal fluid. It has already been demonstrated that intrathecally administered gadolinium (Gd) contrast medium distributes along this route in rats, but so far not in humans. A 27-year-old woman underwent magnetic resonance imaging (MRI) with intrathecal administration of gadobutrol, which distributed throughout her entire brain after 1 and 4.5 h. MRI with intrathecal Gd may become a tool to study glymphatic function in the human brain. PMID:26634147

Regional Homogeneity

PubMed Central

Jiang, Lili; Zuo, Xi-Nian

2015-01-01

Much effort has been made to understand the organizational principles of human brain function using functional magnetic resonance imaging (fMRI) methods, among which resting-state fMRI (rfMRI) is an increasingly recognized technique for measuring the intrinsic dynamics of the human brain. Functional connectivity (FC) with rfMRI is the most widely used method to describe remote or long-distance relationships in studies of cerebral cortex parcellation, interindividual variability, and brain disorders. In contrast, local or short-distance functional interactions, especially at a scale of millimeters, have rarely been investigated or systematically reviewed like remote FC, although some local FC algorithms have been developed and applied to the discovery of brain-based changes under neuropsychiatric conditions. To fill this gap between remote and local FC studies, this review will (1) briefly survey the history of studies on organizational principles of human brain function; (2) propose local functional homogeneity as a network centrality to characterize multimodal local features of the brain connectome; (3) render a neurobiological perspective on local functional homogeneity by linking its temporal, spatial, and individual variability to information processing, anatomical morphology, and brain development; and (4) discuss its role in performing connectome-wide association studies and identify relevant challenges, and recommend its use in future brain connectomics studies. PMID:26170004

Imaging brain development: the adolescent brain.

PubMed

Blakemore, Sarah-Jayne

2012-06-01

The past 15 years have seen a rapid expansion in the number of studies using neuroimaging techniques to investigate maturational changes in the human brain. In this paper, I review MRI studies on structural changes in the developing brain, and fMRI studies on functional changes in the social brain during adolescence. Both MRI and fMRI studies point to adolescence as a period of continued neural development. In the final section, I discuss a number of areas of research that are just beginning and may be the subject of developmental neuroimaging in the next twenty years. Future studies might focus on complex questions including the development of functional connectivity; how gender and puberty influence adolescent brain development; the effects of genes, environment and culture on the adolescent brain; development of the atypical adolescent brain; and implications for policy of the study of the adolescent brain. Copyright © 2011 Elsevier Inc. All rights reserved.

High-field fMRI unveils orientation columns in humans.

PubMed

Yacoub, Essa; Harel, Noam; Ugurbil, Kâmil

2008-07-29

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

Resting State Functional Connectivity in Mild Traumatic Brain Injury at the Acute Stage: Independent Component and Seed-Based Analyses

PubMed Central

Iraji, Armin; Benson, Randall R.; Welch, Robert D.; O'Neil, Brian J.; Woodard, John L.; Imran Ayaz, Syed; Kulek, Andrew; Mika, Valerie; Medado, Patrick; Soltanian-Zadeh, Hamid; Liu, Tianming; Haacke, E. Mark

2015-01-01

Abstract Mild traumatic brain injury (mTBI) accounts for more than 1 million emergency visits each year. Most of the injured stay in the emergency department for a few hours and are discharged home without a specific follow-up plan because of their negative clinical structural imaging. Advanced magnetic resonance imaging (MRI), particularly functional MRI (fMRI), has been reported as being sensitive to functional disturbances after brain injury. In this study, a cohort of 12 patients with mTBI were prospectively recruited from the emergency department of our local Level-1 trauma center for an advanced MRI scan at the acute stage. Sixteen age- and sex-matched controls were also recruited for comparison. Both group-based and individual-based independent component analysis of resting-state fMRI (rsfMRI) demonstrated reduced functional connectivity in both posterior cingulate cortex (PCC) and precuneus regions in comparison with controls, which is part of the default mode network (DMN). Further seed-based analysis confirmed reduced functional connectivity in these two regions and also demonstrated increased connectivity between these regions and other regions of the brain in mTBI. Seed-based analysis using the thalamus, hippocampus, and amygdala regions further demonstrated increased functional connectivity between these regions and other regions of the brain, particularly in the frontal lobe, in mTBI. Our data demonstrate alterations of multiple brain networks at the resting state, particularly increased functional connectivity in the frontal lobe, in response to brain concussion at the acute stage. Resting-state functional connectivity of the DMN could serve as a potential biomarker for improved detection of mTBI in the acute setting. PMID:25285363

A Window into the Brain: Advances in Psychiatric fMRI

PubMed Central

Zhan, Xiaoyan

2015-01-01

Functional magnetic resonance imaging (fMRI) plays a key role in modern psychiatric research. It provides a means to assay differences in brain systems that underlie psychiatric illness, treatment response, and properties of brain structure and function that convey risk factor for mental diseases. Here we review recent advances in fMRI methods in general use and progress made in understanding the neural basis of mental illness. Drawing on concepts and findings from psychiatric fMRI, we propose that mental illness may not be associated with abnormalities in specific local regions but rather corresponds to variation in the overall organization of functional communication throughout the brain network. Future research may need to integrate neuroimaging information drawn from different analysis methods and delineate spatial and temporal patterns of brain responses that are specific to certain types of psychiatric disorders. PMID:26413531

fMRI during natural sleep as a method to study brain function during early childhood.

PubMed

Redcay, Elizabeth; Kennedy, Daniel P; Courchesne, Eric

2007-12-01

Many techniques to study early functional brain development lack the whole-brain spatial resolution that is available with fMRI. We utilized a relatively novel method in which fMRI data were collected from children during natural sleep. Stimulus-evoked responses to auditory and visual stimuli as well as stimulus-independent functional networks were examined in typically developing 2-4-year-old children. Reliable fMRI data were collected from 13 children during presentation of auditory stimuli (tones, vocal sounds, and nonvocal sounds) in a block design. Twelve children were presented with visual flashing lights at 2.5 Hz. When analyses combined all three types of auditory stimulus conditions as compared to rest, activation included bilateral superior temporal gyri/sulci (STG/S) and right cerebellum. Direct comparisons between conditions revealed significantly greater responses to nonvocal sounds and tones than to vocal sounds in a number of brain regions including superior temporal gyrus/sulcus, medial frontal cortex and right lateral cerebellum. The response to visual stimuli was localized to occipital cortex. Furthermore, stimulus-independent functional connectivity MRI analyses (fcMRI) revealed functional connectivity between STG and other temporal regions (including contralateral STG) and medial and lateral prefrontal regions. Functional connectivity with an occipital seed was localized to occipital and parietal cortex. In sum, 2-4 year olds showed a differential fMRI response both between stimulus modalities and between stimuli in the auditory modality. Furthermore, superior temporal regions showed functional connectivity with numerous higher-order regions during sleep. We conclude that the use of sleep fMRI may be a valuable tool for examining functional brain organization in young children.

Optogenetic Functional MRI

PubMed Central

Lin, Peter; Fang, Zhongnan; Liu, Jia; Lee, Jin Hyung

2016-01-01

The investigation of the functional connectivity of precise neural circuits across the entire intact brain can be achieved through optogenetic functional magnetic resonance imaging (ofMRI), which is a novel technique that combines the relatively high spatial resolution of high-field fMRI with the precision of optogenetic stimulation. Fiber optics that enable delivery of specific wavelengths of light deep into the brain in vivo are implanted into regions of interest in order to specifically stimulate targeted cell types that have been genetically induced to express light-sensitive trans-membrane conductance channels, called opsins. fMRI is used to provide a non-invasive method of determining the brain's global dynamic response to optogenetic stimulation of specific neural circuits through measurement of the blood-oxygen-level-dependent (BOLD) signal, which provides an indirect measurement of neuronal activity. This protocol describes the construction of fiber optic implants, the implantation surgeries, the imaging with photostimulation and the data analysis required to successfully perform ofMRI. In summary, the precise stimulation and whole-brain monitoring ability of ofMRI are crucial factors in making ofMRI a powerful tool for the study of the connectomics of the brain in both healthy and diseased states. PMID:27167840

Toward reliable characterization of functional homogeneity in the human brain: Preprocessing, scan duration, imaging resolution and computational space

PubMed Central

Zuo, Xi-Nian; Xu, Ting; Jiang, Lili; Yang, Zhi; Cao, Xiao-Yan; He, Yong; Zang, Yu-Feng; Castellanos, F. Xavier; Milham, Michael P.

2013-01-01

While researchers have extensively characterized functional connectivity between brain regions, the characterization of functional homogeneity within a region of the brain connectome is in early stages of development. Several functional homogeneity measures were proposed previously, among which regional homogeneity (ReHo) was most widely used as a measure to characterize functional homogeneity of resting state fMRI (R-fMRI) signals within a small region (Zang et al., 2004). Despite a burgeoning literature on ReHo in the field of neuroimaging brain disorders, its test–retest (TRT) reliability remains unestablished. Using two sets of public R-fMRI TRT data, we systematically evaluated the ReHo’s TRT reliability and further investigated the various factors influencing its reliability and found: 1) nuisance (head motion, white matter, and cerebrospinal fluid) correction of R-fMRI time series can significantly improve the TRT reliability of ReHo while additional removal of global brain signal reduces its reliability, 2) spatial smoothing of R-fMRI time series artificially enhances ReHo intensity and influences its reliability, 3) surface-based R-fMRI computation largely improves the TRT reliability of ReHo, 4) a scan duration of 5 min can achieve reliable estimates of ReHo, and 5) fast sampling rates of R-fMRI dramatically increase the reliability of ReHo. Inspired by these findings and seeking a highly reliable approach to exploratory analysis of the human functional connectome, we established an R-fMRI pipeline to conduct ReHo computations in both 3-dimensions (volume) and 2-dimensions (surface). PMID:23085497

Detection of Brain Reorganization in Pediatric Multiple Sclerosis Using Functional MRI

DTIC Science & Technology

2015-10-01

Page | 2 AWARD NUMBER: W81XWH-13-1-0464 TITLE: Detection of Brain Reorganization in Pediatric Multiple Sclerosis Using Functional MRI...Sep 2014 – 29 Sep 2015 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Detection of Brain Reorganization in Pediatric Multiple Sclerosis Using Functional...findings include: 1) detection of brain organization in a cohort of 24 pediatric onset multiple sclerosis patients (POMS) and 25 healthy controls

Spontaneous brain activity predicts learning ability of foreign sounds.

PubMed

Ventura-Campos, Noelia; Sanjuán, Ana; González, Julio; Palomar-García, María-Ángeles; Rodríguez-Pujadas, Aina; Sebastián-Gallés, Núria; Deco, Gustavo; Ávila, César

2013-05-29

Can learning capacity of the human brain be predicted from initial spontaneous functional connectivity (FC) between brain areas involved in a task? We combined task-related functional magnetic resonance imaging (fMRI) and resting-state fMRI (rs-fMRI) before and after training with a Hindi dental-retroflex nonnative contrast. Previous fMRI results were replicated, demonstrating that this learning recruited the left insula/frontal operculum and the left superior parietal lobe, among other areas of the brain. Crucially, resting-state FC (rs-FC) between these two areas at pretraining predicted individual differences in learning outcomes after distributed (Experiment 1) and intensive training (Experiment 2). Furthermore, this rs-FC was reduced at posttraining, a change that may also account for learning. Finally, resting-state network analyses showed that the mechanism underlying this reduction of rs-FC was mainly a transfer in intrinsic activity of the left frontal operculum/anterior insula from the left frontoparietal network to the salience network. Thus, rs-FC may contribute to predict learning ability and to understand how learning modifies the functioning of the brain. The discovery of this correspondence between initial spontaneous brain activity in task-related areas and posttraining performance opens new avenues to find predictors of learning capacities in the brain using task-related fMRI and rs-fMRI combined.

Hemisphere- and gender-related differences in small-world brain networks: a resting-state functional MRI study.

PubMed

Tian, Lixia; Wang, Jinhui; Yan, Chaogan; He, Yong

2011-01-01

We employed resting-state functional MRI (R-fMRI) to investigate hemisphere- and gender-related differences in the topological organization of human brain functional networks. Brain networks were first constructed by measuring inter-regional temporal correlations of R-fMRI data within each hemisphere in 86 young, healthy, right-handed adults (38 males and 48 females) followed by a graph-theory analysis. The hemispheric networks exhibit small-world attributes (high clustering and short paths) that are compatible with previous results in the whole-brain functional networks. Furthermore, we found that compared with females, males have a higher normalized clustering coefficient in the right hemispheric network but a lower clustering coefficient in the left hemispheric network, suggesting a gender-hemisphere interaction. Moreover, we observed significant hemisphere-related differences in the regional nodal characteristics in various brain regions, such as the frontal and occipital regions (leftward asymmetry) and the temporal regions (rightward asymmetry), findings that are consistent with previous studies of brain structural and functional asymmetries. Together, our results suggest that the topological organization of human brain functional networks is associated with gender and hemispheres, and they provide insights into the understanding of functional substrates underlying individual differences in behaviors and cognition. Copyright © 2010 Elsevier Inc. All rights reserved.

Resting state network topology of the ferret brain.

PubMed

Zhou, Zhe Charles; Salzwedel, Andrew P; Radtke-Schuller, Susanne; Li, Yuhui; Sellers, Kristin K; Gilmore, John H; Shih, Yen-Yu Ian; Fröhlich, Flavio; Gao, Wei

2016-12-01

Resting state functional magnetic resonance imaging (rsfMRI) has emerged as a versatile tool for non-invasive measurement of functional connectivity patterns in the brain. RsfMRI brain dynamics in rodents, non-human primates, and humans share similar properties; however, little is known about the resting state functional connectivity patterns in the ferret, an animal model with high potential for developmental and cognitive translational study. To address this knowledge-gap, we performed rsfMRI on anesthetized ferrets using a 9.4T MRI scanner, and subsequently performed group-level independent component analysis (gICA) to identify functionally connected brain networks. Group-level ICA analysis revealed distributed sensory, motor, and higher-order networks in the ferret brain. Subsequent connectivity analysis showed interconnected higher-order networks that constituted a putative default mode network (DMN), a network that exhibits altered connectivity in neuropsychiatric disorders. Finally, we assessed ferret brain topological efficiency using graph theory analysis and found that the ferret brain exhibits small-world properties. Overall, these results provide additional evidence for pan-species resting-state networks, further supporting ferret-based studies of sensory and cognitive function. Copyright © 2016 Elsevier Inc. All rights reserved.

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

PubMed Central

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

2015-01-01

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

Functional connectomics from resting-state fMRI

PubMed Central

Smith, Stephen M; Vidaurre, Diego; Beckmann, Christian F; Glasser, Matthew F; Jenkinson, Mark; Miller, Karla L; Nichols, Thomas E; Robinson, Emma; Salimi-Khorshidi, Gholamreza; Woolrich, Mark W; Barch, Deanna M; Uğurbil, Kamil; Van Essen, David C

2014-01-01

Spontaneous fluctuations in activity in different parts of the brain can be used to study functional brain networks. We review the use of resting-state functional MRI for the purpose of mapping the macroscopic functional connectome. After describing MRI acquisition and image processing methods commonly used to generate data in a form amenable to connectomics network analysis, we discuss different approaches for estimating network structure from that data. Finally, we describe new possibilities resulting from the high-quality rfMRI data being generated by the Human Connectome Project, and highlight some upcoming challenges in functional connectomics. PMID:24238796

Task-evoked brain functional magnetic susceptibility mapping by independent component analysis (χICA).

PubMed

Chen, Zikuan; Calhoun, Vince D

2016-03-01

Conventionally, independent component analysis (ICA) is performed on an fMRI magnitude dataset to analyze brain functional mapping (AICA). By solving the inverse problem of fMRI, we can reconstruct the brain magnetic susceptibility (χ) functional states. Upon the reconstructed χ dataspace, we propose an ICA-based brain functional χ mapping method (χICA) to extract task-evoked brain functional map. A complex division algorithm is applied to a timeseries of fMRI phase images to extract temporal phase changes (relative to an OFF-state snapshot). A computed inverse MRI (CIMRI) model is used to reconstruct a 4D brain χ response dataset. χICA is implemented by applying a spatial InfoMax ICA algorithm to the reconstructed 4D χ dataspace. With finger-tapping experiments on a 7T system, the χICA-extracted χ-depicted functional map is similar to the SPM-inferred functional χ map by a spatial correlation of 0.67 ± 0.05. In comparison, the AICA-extracted magnitude-depicted map is correlated with the SPM magnitude map by 0.81 ± 0.05. The understanding of the inferiority of χICA to AICA for task-evoked functional map is an ongoing research topic. For task-evoked brain functional mapping, we compare the data-driven ICA method with the task-correlated SPM method. In particular, we compare χICA with AICA for extracting task-correlated timecourses and functional maps. χICA can extract a χ-depicted task-evoked brain functional map from a reconstructed χ dataspace without the knowledge about brain hemodynamic responses. The χICA-extracted brain functional χ map reveals a bidirectional BOLD response pattern that is unavailable (or different) from AICA. Copyright © 2016 Elsevier B.V. All rights reserved.

Functional connectivity analysis of resting-state fMRI networks in nicotine dependent patients

NASA Astrophysics Data System (ADS)

Smith, Aria; Ehtemami, Anahid; Fratte, Daniel; Meyer-Baese, Anke; Zavala-Romero, Olmo; Goudriaan, Anna E.; Schmaal, Lianne; Schulte, Mieke H. J.

2016-03-01

Brain imaging studies identified brain networks that play a key role in nicotine dependence-related behavior. Functional connectivity of the brain is dynamic; it changes over time due to different causes such as learning, or quitting a habit. Functional connectivity analysis is useful in discovering and comparing patterns between functional magnetic resonance imaging (fMRI) scans of patients' brains. In the resting state, the patient is asked to remain calm and not do any task to minimize the contribution of external stimuli. The study of resting-state fMRI networks have shown functionally connected brain regions that have a high level of activity during this state. In this project, we are interested in the relationship between these functionally connected brain regions to identify nicotine dependent patients, who underwent a smoking cessation treatment. Our approach is on the comparison of the set of connections between the fMRI scans before and after treatment. We applied support vector machines, a machine learning technique, to classify patients based on receiving the treatment or the placebo. Using the functional connectivity (CONN) toolbox, we were able to form a correlation matrix based on the functional connectivity between different regions of the brain. The experimental results show that there is inadequate predictive information to classify nicotine dependent patients using the SVM classifier. We propose other classification methods be explored to better classify the nicotine dependent patients.

Toward reliable characterization of functional homogeneity in the human brain: preprocessing, scan duration, imaging resolution and computational space.

PubMed

Zuo, Xi-Nian; Xu, Ting; Jiang, Lili; Yang, Zhi; Cao, Xiao-Yan; He, Yong; Zang, Yu-Feng; Castellanos, F Xavier; Milham, Michael P

2013-01-15

While researchers have extensively characterized functional connectivity between brain regions, the characterization of functional homogeneity within a region of the brain connectome is in early stages of development. Several functional homogeneity measures were proposed previously, among which regional homogeneity (ReHo) was most widely used as a measure to characterize functional homogeneity of resting state fMRI (R-fMRI) signals within a small region (Zang et al., 2004). Despite a burgeoning literature on ReHo in the field of neuroimaging brain disorders, its test-retest (TRT) reliability remains unestablished. Using two sets of public R-fMRI TRT data, we systematically evaluated the ReHo's TRT reliability and further investigated the various factors influencing its reliability and found: 1) nuisance (head motion, white matter, and cerebrospinal fluid) correction of R-fMRI time series can significantly improve the TRT reliability of ReHo while additional removal of global brain signal reduces its reliability, 2) spatial smoothing of R-fMRI time series artificially enhances ReHo intensity and influences its reliability, 3) surface-based R-fMRI computation largely improves the TRT reliability of ReHo, 4) a scan duration of 5 min can achieve reliable estimates of ReHo, and 5) fast sampling rates of R-fMRI dramatically increase the reliability of ReHo. Inspired by these findings and seeking a highly reliable approach to exploratory analysis of the human functional connectome, we established an R-fMRI pipeline to conduct ReHo computations in both 3-dimensions (volume) and 2-dimensions (surface). Copyright © 2012 Elsevier Inc. All rights reserved.

Sparse dictionary learning of resting state fMRI networks.

PubMed

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.

Brain Entropy Mapping Using fMRI

PubMed Central

Wang, Ze; Li, Yin; Childress, Anna Rose; Detre, John A.

2014-01-01

Entropy is an important trait for life as well as the human brain. Characterizing brain entropy (BEN) may provide an informative tool to assess brain states and brain functions. Yet little is known about the distribution and regional organization of BEN in normal brain. The purpose of this study was to examine the whole brain entropy patterns using a large cohort of normal subjects. A series of experiments were first performed to validate an approximate entropy measure regarding its sensitivity, specificity, and reliability using synthetic data and fMRI data. Resting state fMRI data from a large cohort of normal subjects (n = 1049) from multi-sites were then used to derive a 3-dimensional BEN map, showing a sharp low-high entropy contrast between the neocortex and the rest of brain. The spatial heterogeneity of resting BEN was further studied using a data-driven clustering method, and the entire brain was found to be organized into 7 hierarchical regional BEN networks that are consistent with known structural and functional brain parcellations. These findings suggest BEN mapping as a physiologically and functionally meaningful measure for studying brain functions. PMID:24657999

Disruption to functional networks in neonates with perinatal brain injury predicts motor skills at 8 months.

PubMed

Linke, Annika C; Wild, Conor; Zubiaurre-Elorza, Leire; Herzmann, Charlotte; Duffy, Hester; Han, Victor K; Lee, David S C; Cusack, Rhodri

2018-01-01

Functional connectivity magnetic resonance imaging (fcMRI) of neonates with perinatal brain injury could improve prediction of motor impairment before symptoms manifest, and establish how early brain organization relates to subsequent development. This cohort study is the first to describe and quantitatively assess functional brain networks and their relation to later motor skills in neonates with a diverse range of perinatal brain injuries. Infants ( n  = 65, included in final analyses: n  = 53) were recruited from the neonatal intensive care unit (NICU) and were stratified based on their age at birth (premature vs. term), and on whether neuropathology was diagnosed from structural MRI. Functional brain networks and a measure of disruption to functional connectivity were obtained from 14 min of fcMRI acquired during natural sleep at term-equivalent age. Disruption to connectivity of the somatomotor and frontoparietal executive networks predicted motor impairment at 4 and 8 months. This disruption in functional connectivity was not found to be driven by differences between clinical groups, or by any of the specific measures we captured to describe the clinical course. fcMRI was predictive over and above other clinical measures available at discharge from the NICU, including structural MRI. Motor learning was affected by disruption to somatomotor networks, but also frontoparietal executive networks, which supports the functional importance of these networks in early development. Disruption to these two networks might be best addressed by distinct intervention strategies.

Synchronized delta oscillations correlate with the resting-state functional MRI signal

PubMed Central

Lu, Hanbing; Zuo, Yantao; Gu, Hong; Waltz, James A.; Zhan, Wang; Scholl, Clara A.; Rea, William; Yang, Yihong; Stein, Elliot A.

2007-01-01

Synchronized low-frequency spontaneous fluctuations of the functional MRI (fMRI) signal have recently been applied to investigate large-scale neuronal networks of the brain in the absence of specific task instructions. However, the underlying neural mechanisms of these fluctuations remain largely unknown. To this end, electrophysiological recordings and resting-state fMRI measurements were conducted in α-chloralose-anesthetized rats. Using a seed-voxel analysis strategy, region-specific, anesthetic dose-dependent fMRI resting-state functional connectivity was detected in bilateral primary somatosensory cortex (S1FL) of the resting brain. Cortical electroencephalographic signals were also recorded from bilateral S1FL; a visual cortex locus served as a control site. Results demonstrate that, unlike the evoked fMRI response that correlates with power changes in the γ bands, the resting-state fMRI signal correlates with the power coherence in low-frequency bands, particularly the δ band. These data indicate that hemodynamic fMRI signal differentially registers specific electrical oscillatory frequency band activity, suggesting that fMRI may be able to distinguish the ongoing from the evoked activity of the brain. PMID:17991778

Functional Imaging and Migraine: New Connections?

PubMed Central

Schwedt, Todd J.; Chong, Catherine D.

2015-01-01

Purpose of Review Over the last several years, a growing number of brain functional imaging studies have provided insights into mechanisms underlying migraine. This manuscript reviews the recent migraine functional neuroimaging literature and provides recommendations for future studies that will help fill knowledge gaps. Recent Findings Positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) studies have identified brain regions that might be responsible for mediating the onset of a migraine attack and those associated with migraine symptoms. Enhanced activation of brain regions that facilitate processing of sensory stimuli suggests a mechanism by which migraineurs are hypersensitive to visual, olfactory, and cutaneous stimuli. Resting state functional connectivity MRI studies have identified numerous brain regions and functional networks with atypical functional connectivity in migraineurs, suggesting that migraine is associated with aberrant brain functional organization. Summary fMRI and PET studies that have identified brain regions and brain networks that are atypical in migraine have helped to describe the neurofunctional basis for migraine symptoms. Future studies should compare functional imaging findings in migraine to other headache and pain disorders and should explore the utility of functional imaging data as biomarkers for diagnostic and treatment purposes. PMID:25887764

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

PubMed

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.

Effects of resting state condition on reliability, trait specificity, and network connectivity of brain function measured with arterial spin labeled perfusion MRI.

PubMed

Li, Zhengjun; Vidorreta, Marta; Katchmar, Natalie; Alsop, David C; Wolf, Daniel H; Detre, John A

2018-06-01

Resting state fMRI (rs-fMRI) provides imaging biomarkers of task-independent brain function that can be associated with clinical variables or modulated by interventions such as behavioral training or pharmacological manipulations. These biomarkers include time-averaged regional brain function as manifested by regional cerebral blood flow (CBF) measured using arterial spin labeled (ASL) perfusion MRI and correlated temporal fluctuations of function across brain networks with either ASL or blood oxygenation level dependent (BOLD) fMRI. Resting-state studies are typically carried out using just one of several prescribed state conditions such as eyes closed (EC), eyes open (EO), or visual fixation on a cross-hair (FIX), which may affect the reliability and specificity of rs-fMRI. In this study, we collected test-retest ASL MRI data during 4 resting-state task conditions: EC, EO, FIX and PVT (low-frequency psychomotor vigilance task), and examined the effects of these task conditions on reliability and reproducibility as well as trait specificity of regional brain function. We also acquired resting-state BOLD fMRI under FIX and compared the network connectivity reliabilities between the four ASL conditions and the BOLD FIX condition. For resting-state ASL data, EC provided the highest CBF reliability, reproducibility, trait specificity, and network connectivity reliability, followed by EO, while FIX was lowest on all of these measures. PVT demonstrated lower CBF reliability, reproducibility and trait specificity than EO and EC. Overall network connectivity reliability was comparable between ASL and BOLD. Our findings confirm ASL CBF as a reliable, stable, and consistent measure of resting-state regional brain function and support the use of EC or EO over FIX and PVT as the resting-state condition. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Functional MRI during Hippocampal Deep Brain Stimulation in the Healthy Rat Brain.

PubMed

Van Den Berge, Nathalie; Vanhove, Christian; Descamps, Benedicte; Dauwe, Ine; van Mierlo, Pieter; Vonck, Kristl; Keereman, Vincent; Raedt, Robrecht; Boon, Paul; Van Holen, Roel

2015-01-01

Deep Brain Stimulation (DBS) is a promising treatment for neurological and psychiatric disorders. The mechanism of action and the effects of electrical fields administered to the brain by means of an electrode remain to be elucidated. The effects of DBS have been investigated primarily by electrophysiological and neurochemical studies, which lack the ability to investigate DBS-related responses on a whole-brain scale. Visualization of whole-brain effects of DBS requires functional imaging techniques such as functional Magnetic Resonance Imaging (fMRI), which reflects changes in blood oxygen level dependent (BOLD) responses throughout the entire brain volume. In order to visualize BOLD responses induced by DBS, we have developed an MRI-compatible electrode and an acquisition protocol to perform DBS during BOLD fMRI. In this study, we investigate whether DBS during fMRI is valuable to study local and whole-brain effects of hippocampal DBS and to investigate the changes induced by different stimulation intensities. Seven rats were stereotactically implanted with a custom-made MRI-compatible DBS-electrode in the right hippocampus. High frequency Poisson distributed stimulation was applied using a block-design paradigm. Data were processed by means of Independent Component Analysis. Clusters were considered significant when p-values were <0.05 after correction for multiple comparisons. Our data indicate that real-time hippocampal DBS evokes a bilateral BOLD response in hippocampal and other mesolimbic structures, depending on the applied stimulation intensity. We conclude that simultaneous DBS and fMRI can be used to detect local and whole-brain responses to circuit activation with different stimulation intensities, making this technique potentially powerful for exploration of cerebral changes in response to DBS for both preclinical and clinical DBS.

Functional MRI during Hippocampal Deep Brain Stimulation in the Healthy Rat Brain

PubMed Central

Van Den Berge, Nathalie; Vanhove, Christian; Descamps, Benedicte; Dauwe, Ine; van Mierlo, Pieter; Vonck, Kristl; Keereman, Vincent; Raedt, Robrecht; Boon, Paul; Van Holen, Roel

2015-01-01

Deep Brain Stimulation (DBS) is a promising treatment for neurological and psychiatric disorders. The mechanism of action and the effects of electrical fields administered to the brain by means of an electrode remain to be elucidated. The effects of DBS have been investigated primarily by electrophysiological and neurochemical studies, which lack the ability to investigate DBS-related responses on a whole-brain scale. Visualization of whole-brain effects of DBS requires functional imaging techniques such as functional Magnetic Resonance Imaging (fMRI), which reflects changes in blood oxygen level dependent (BOLD) responses throughout the entire brain volume. In order to visualize BOLD responses induced by DBS, we have developed an MRI-compatible electrode and an acquisition protocol to perform DBS during BOLD fMRI. In this study, we investigate whether DBS during fMRI is valuable to study local and whole-brain effects of hippocampal DBS and to investigate the changes induced by different stimulation intensities. Seven rats were stereotactically implanted with a custom-made MRI-compatible DBS-electrode in the right hippocampus. High frequency Poisson distributed stimulation was applied using a block-design paradigm. Data were processed by means of Independent Component Analysis. Clusters were considered significant when p-values were <0.05 after correction for multiple comparisons. Our data indicate that real-time hippocampal DBS evokes a bilateral BOLD response in hippocampal and other mesolimbic structures, depending on the applied stimulation intensity. We conclude that simultaneous DBS and fMRI can be used to detect local and whole-brain responses to circuit activation with different stimulation intensities, making this technique potentially powerful for exploration of cerebral changes in response to DBS for both preclinical and clinical DBS. PMID:26193653

Fusing DTI and FMRI Data: A Survey of Methods and Applications

PubMed Central

Zhu, Dajiang; Zhang, Tuo; Jiang, Xi; Hu, Xintao; Chen, Hanbo; Yang, Ning; Lv, Jinglei; Han, Junwei; Guo, Lei; Liu, Tianming

2014-01-01

The relationship between brain structure and function has been one of the centers of research in neuroimaging for decades. In recent years, diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI) techniques have been widely available and popular in cognitive and clinical neurosciences for examining the brain’s white matter (WM) micro-structures and gray matter (GM) functions, respectively. Given the intrinsic integration of WM/GM and the complementary information embedded in DTI/fMRI data, it is natural and well-justified to combine these two neuroimaging modalities together to investigate brain structure and function and their relationships simultaneously. In the past decade, there have been remarkable achievements of DTI/fMRI fusion methods and applications in neuroimaging and human brain mapping community. This survey paper aims to review recent advancements on methodologies and applications in incorporating multimodal DTI and fMRI data, and offer our perspectives on future research directions. We envision that effective fusion of DTI/fMRI techniques will play increasingly important roles in neuroimaging and brain sciences in the years to come. PMID:24103849

Advantages in functional imaging of the brain.

PubMed

Mier, Walter; Mier, Daniela

2015-01-01

As neuronal pathologies cause only minor morphological alterations, molecular imaging techniques are a prerequisite for the study of diseases of the brain. The development of molecular probes that specifically bind biochemical markers and the advances of instrumentation have revolutionized the possibilities to gain insight into the human brain organization and beyond this-visualize structure-function and brain-behavior relationships. The review describes the development and current applications of functional brain imaging techniques with a focus on applications in psychiatry. A historical overview of the development of functional imaging is followed by the portrayal of the principles and applications of positron emission tomography (PET) and functional magnetic resonance imaging (fMRI), two key molecular imaging techniques that have revolutionized the ability to image molecular processes in the brain. We conclude that the juxtaposition of PET and fMRI in hybrid PET/MRI scanners enhances the significance of both modalities for research in neurology and psychiatry and might pave the way for a new area of personalized medicine.

Correlation of neurocognitive function and brain lesion load on magnetic resonance imaging in systemic lupus erythematosus.

PubMed

Roldan, Paola C; Jung, Rex E; Sibbitt, Wilmer L; Qualls, Clifford R; Flores, Ranee A; Roldan, Carlos A

2018-06-13

Neurocognitive dysfunction and brain injury on magnetic resonance imaging (MRI) are common in patients with systemic lupus erythematosus (SLE) and are associated with increased morbidity and mortality. However, brain MRI is expensive, is restricted by payers, and requires high expertise. Neurocognitive assessment is an easily available, safe, and inexpensive clinical tool that may select patients needing brain MRI. In this cross-sectional and controlled study, 76 SLE patients (69 women, age 37 ± 12 years) and 26 age and gender-matched healthy subjects (22 women, age 34 ± 11 years) underwent assessment of attention, memory, processing speed, executive function, motor function, and global neurocognitive function. All subjects underwent brain MRI with T1-weighted, fluid-attenuated inversion recovery (FLAIR), and diffusion-weighted imaging. Hemispheric and whole brain lesion load in cm 3 were determined using semi-automated methods. Neurocognitive z-scores in all clinical domains were significantly lower and whole brain and right and left hemispheres brain lesion load were significantly greater in patients than in controls (all p ≤ 0.02). There was significant correlation between neurocognitive z-scores in all domains and whole brain lesion load: processing speed (r = - 0.46; p < 0.0001), attention (r = - 0.42; p < 0.001), memory (r = - 0.40; p = 0.0004), executive function (r = - 0.25; p = 0.03), motor function (r = - 0.25; p = 0.05), and global neurocognitive function (r = - 0.38; p = 0.006). Similar correlations were found for brain hemisphere lesion loads (all p ≤ 0.05). These correlations were strengthened when adjusted for glucocorticoid therapy and SLE disease activity index. Finally, global neurocognitive z-score and erythrosedimentation rate were the only independent predictors of whole brain lesion load (both p ≤ 0.007). Neurocognitive measures and brain lesion load are worse in SLE patients than in controls. In SLE patients, neurocognitive z-scores correlate negatively with and independently predict brain lesion load. Therefore, neurocognitive testing may be an effective clinical tool to select patients needing brain MRI.

Structural and functional network connectivity breakdown in Alzheimer’s disease studied with magnetic resonance imaging techniques.

PubMed

Filippi, Massimo; Agosta, Federica

2011-01-01

Patients with Alzheimer’s disease (AD) experience a brain network breakdown, reflecting disconnection at both the structural and functional system level. Resting-state (RS) functional MRI (fMRI) studies demonstrated that the regional coherence of the fMRI signal is significantly altered in patients with AD and amnestic mild cognitive impairment. Diffusion tensor (DT) MRI has made it possible to track fiber bundle projections across the brain, revealing a substantially abnormal interplay of “critical” white matter tracts in these conditions. The observed agreement between the results of RS fMRI and DT MRI tractography studies in healthy individuals is encouraging and offers interesting hypotheses to be tested in patients with AD, a MCI, and other dementias in order to improve our understanding of their pathobiology in vivo. In this review,we describe the major findings obtained in AD using RS fMRI and DT MRI tractography, and discuss how the relationship between structure and function of the brain networks in AD may be better understood through the application of MR-based technology. This research endeavor holds a great promise in clarifying the mechanisms of cognitive decline in complex chronic neurodegenerative disorders.

Structural and Functional Bases for Individual Differences in Motor Learning

PubMed Central

Tomassini, Valentina; Jbabdi, Saad; Kincses, Zsigmond T.; Bosnell, Rose; Douaud, Gwenaelle; Pozzilli, Carlo; Matthews, Paul M.; Johansen-Berg, Heidi

2013-01-01

People vary in their ability to learn new motor skills. We hypothesize that between-subject variability in brain structure and function can explain differences in learning. We use brain functional and structural MRI methods to characterize such neural correlates of individual variations in motor learning. Healthy subjects applied isometric grip force of varying magnitudes with their right hands cued visually to generate smoothly-varying pressures following a regular pattern. We tested whether individual variations in motor learning were associated with anatomically colocalized variations in magnitude of functional MRI (fMRI) signal or in MRI differences related to white and grey matter microstructure. We found that individual motor learning was correlated with greater functional activation in the prefrontal, premotor, and parietal cortices, as well as in the basal ganglia and cerebellum. Structural MRI correlates were found in the premotor cortex [for fractional anisotropy (FA)] and in the cerebellum [for both grey matter density and FA]. The cerebellar microstructural differences were anatomically colocalized with fMRI correlates of learning. This study thus suggests that variations across the population in the function and structure of specific brain regions for motor control explain some of the individual differences in skill learning. This strengthens the notion that brain structure determines some limits to cognitive function even in a healthy population. Along with evidence from pathology suggesting a role for these regions in spontaneous motor recovery, our results also highlight potential targets for therapeutic interventions designed to maximize plasticity for recovery of similar visuomotor skills after brain injury. PMID:20533562

What is feasible with imaging human brain function and connectivity using functional magnetic resonance imaging

PubMed Central

2016-01-01

When we consider all of the methods we employ to detect brain function, from electrophysiology to optical techniques to functional magnetic resonance imaging (fMRI), we do not really have a ‘golden technique’ that meets all of the needs for studying the brain. We have methods, each of which has significant limitations but provide often complimentary information. Clearly, there are many questions that need to be answered about fMRI, which unlike other methods, allows us to study the human brain. However, there are also extraordinary accomplishments or demonstration of the feasibility of reaching new and previously unexpected scales of function in the human brain. This article reviews some of the work we have pursued, often with extensive collaborations with other co-workers, towards understanding the underlying mechanisms of the methodology, defining its limitations, and developing solutions to advance it. No doubt, our knowledge of human brain function has vastly expanded since the introduction of fMRI. However, methods and instrumentation in this dynamic field have evolved to a state that discoveries about the human brain based on fMRI principles, together with information garnered at a much finer spatial and temporal scale through other methods, are poised to significantly accelerate in the next decade. This article is part of the themed issue ‘Interpreting BOLD: a dialogue between cognitive and cellular neuroscience’. PMID:27574313

What is feasible with imaging human brain function and connectivity using functional magnetic resonance imaging.

PubMed

Ugurbil, Kamil

2016-10-05

When we consider all of the methods we employ to detect brain function, from electrophysiology to optical techniques to functional magnetic resonance imaging (fMRI), we do not really have a 'golden technique' that meets all of the needs for studying the brain. We have methods, each of which has significant limitations but provide often complimentary information. Clearly, there are many questions that need to be answered about fMRI, which unlike other methods, allows us to study the human brain. However, there are also extraordinary accomplishments or demonstration of the feasibility of reaching new and previously unexpected scales of function in the human brain. This article reviews some of the work we have pursued, often with extensive collaborations with other co-workers, towards understanding the underlying mechanisms of the methodology, defining its limitations, and developing solutions to advance it. No doubt, our knowledge of human brain function has vastly expanded since the introduction of fMRI. However, methods and instrumentation in this dynamic field have evolved to a state that discoveries about the human brain based on fMRI principles, together with information garnered at a much finer spatial and temporal scale through other methods, are poised to significantly accelerate in the next decade.This article is part of the themed issue 'Interpreting BOLD: a dialogue between cognitive and cellular neuroscience'. © 2016 The Author(s).

Magnetic Resonance, Functional (fMRI) -- Brain

MedlinePlus

... thought, speech, movement and sensation, which is called brain mapping. help assess the effects of stroke, trauma, or degenerative disease (such as Alzheimer's) on brain function. monitor the growth and function of brain ...

Role of mitochondrial calcium uptake homeostasis in resting state fMRI brain networks.

PubMed

Kannurpatti, Sridhar S; Sanganahalli, Basavaraju G; Herman, Peter; Hyder, Fahmeed

2015-11-01

Mitochondrial Ca(2+) uptake influences both brain energy metabolism and neural signaling. Given that brain mitochondrial organelles are distributed in relation to vascular density, which varies considerably across brain regions, we hypothesized different physiological impacts of mitochondrial Ca(2+) uptake across brain regions. We tested the hypothesis by monitoring brain "intrinsic activity" derived from the resting state functional MRI (fMRI) blood oxygen level dependent (BOLD) fluctuations in different functional networks spanning the somatosensory cortex, caudate putamen, hippocampus and thalamus, in normal and perturbed mitochondrial Ca(2+) uptake states. In anesthetized rats at 11.7 T, mitochondrial Ca(2+) uptake was inhibited or enhanced respectively by treatments with Ru360 or kaempferol. Surprisingly, mitochondrial Ca(2+) uptake inhibition by Ru360 and enhancement by kaempferol led to similar dose-dependent decreases in brain-wide intrinsic activities in both the frequency domain (spectral amplitude) and temporal domain (resting state functional connectivity; RSFC). The fact that there were similar dose-dependent decreases in the frequency and temporal domains of the resting state fMRI-BOLD fluctuations during mitochondrial Ca(2+) uptake inhibition or enhancement indicated that mitochondrial Ca(2+) uptake and its homeostasis may strongly influence the brain's functional organization at rest. Interestingly, the resting state fMRI-derived intrinsic activities in the caudate putamen and thalamic regions saturated much faster with increasing dosage of either drug treatment than the drug-induced trends observed in cortical and hippocampal regions. Regional differences in how the spectral amplitude and RSFC changed with treatment indicate distinct mitochondrion-mediated spontaneous neuronal activity coupling within the various RSFC networks determined by resting state fMRI. Copyright © 2015 John Wiley & Sons, Ltd.

Tracking brain arousal fluctuations with fMRI

PubMed Central

Chang, Catie; Leopold, David A.; Schölvinck, Marieke Louise; Mandelkow, Hendrik; Picchioni, Dante; Liu, Xiao; Ye, Frank Q.; Turchi, Janita N.; Duyn, Jeff H.

2016-01-01

Changes in brain activity accompanying shifts in vigilance and arousal can interfere with the study of other intrinsic and task-evoked characteristics of brain function. However, the difficulty of tracking and modeling the arousal state during functional MRI (fMRI) typically precludes the assessment of arousal-dependent influences on fMRI signals. Here we combine fMRI, electrophysiology, and the monitoring of eyelid behavior to demonstrate an approach for tracking continuous variations in arousal level from fMRI data. We first characterize the spatial distribution of fMRI signal fluctuations that track a measure of behavioral arousal; taking this pattern as a template, and using the local field potential as a simultaneous and independent measure of cortical activity, we observe that the time-varying expression level of this template in fMRI data provides a close approximation of electrophysiological arousal. We discuss the potential benefit of these findings for increasing the sensitivity of fMRI as a cognitive and clinical biomarker. PMID:27051064

Brain functional connectivity network studies of acupuncture: a systematic review on resting-state fMRI.

PubMed

Cai, Rong-Lin; Shen, Guo-Ming; Wang, Hao; Guan, Yuan-Yuan

2018-01-01

Functional magnetic resonance imaging (fMRI) is a novel method for studying the changes of brain networks due to acupuncture treatment. In recent years, more and more studies have focused on the brain functional connectivity network of acupuncture stimulation. To offer an overview of the different influences of acupuncture on the brain functional connectivity network from studies using resting-state fMRI. The authors performed a systematic search according to PRISMA guidelines. The database PubMed was searched from January 1, 2006 to December 31, 2016 with restriction to human studies in English language. Electronic searches were conducted in PubMed using the keywords "acupuncture" and "neuroimaging" or "resting-state fMRI" or "functional connectivity". Selection of included articles, data extraction and methodological quality assessments were respectively conducted by two review authors. Forty-four resting-state fMRI studies were included in this systematic review according to inclusion criteria. Thirteen studies applied manual acupuncture vs. sham, four studies applied electro-acupuncture vs. sham, two studies also compared transcutaneous electrical acupoint stimulation vs. sham, and nine applied sham acupoint as control. Nineteen studies with a total number of 574 healthy subjects selected to perform fMRI only considered healthy adult volunteers. The brain functional connectivity of the patients had varying degrees of change. Compared with sham acupuncture, verum acupuncture could increase default mode network and sensorimotor network connectivity with pain-, affective- and memory-related brain areas. It has significantly greater connectivity of genuine acupuncture between the periaqueductal gray, anterior cingulate cortex, left posterior cingulate cortex, right anterior insula, limbic/paralimbic and precuneus compared with sham acupuncture. Some research had also shown that acupuncture could adjust the limbic-paralimbic-neocortical network, brainstem, cerebellum, subcortical and hippocampus brain areas. It can be presumed that the functional connectivity network is closely related to the mechanism of acupuncture, and central integration plays a critical role in the acupuncture mechanism. Copyright © 2017 Shanghai Changhai Hospital. Published by Elsevier B.V. All rights reserved.

Functional brain MRI in patients complaining of electrohypersensitivity after long term exposure to electromagnetic fields.

PubMed

Heuser, Gunnar; Heuser, Sylvia A

2017-09-26

Ten adult patients with electromagnetic hypersensitivity underwent functional magnetic resonance imaging (fMRI) brain scans. All scans were abnormal with abnormalities which were consistent and similar. It is proposed that fMRI brain scans be used as a diagnostic aid for determining whether or not a patient has electromagnetic hypersensitivity. Over the years we have seen an increasing number of patients who had developed multi system complaints after long term repeated exposure to electromagnetic fields (EMFs). These complaints included headaches, intermittent cognitive and memory problems, intermittent disorientation, and also sensitivity to EMF exposure. Regular laboratory tests were within normal limits in these patients. The patients refused to be exposed to radioactivity. This of course ruled out positron emission tomography (PET) and single-photon emission computed tomography (SPECT) brain scanning. This is why we ordered fMRI brain scans on these patients. We hoped that we could document objective abnormalities in these patients who had often been labeled as psychiatric cases. Ten patients first underwent a regular magnetic resonance imaging (MRI) brain scan, using a 3 Tesla Siemens Verio MRI open system. A functional MRI study was then performed in the resting state using the following sequences: A three-dimensional, T1-weighted, gradient-echo (MPRAGE) Resting state network. The echo-planar imaging (EPI) sequences for this resting state blood oxygenation level dependent (BOLD) scan were then post processed on a 3D workstation and the independent component analysis was performed separating out the various networks. Arterial spin labeling. Tractography and fractional anisotropy. All ten patients had abnormal functional MRI brain scans. The abnormality was often described as hyper connectivity of the anterior component of the default mode in the medial orbitofrontal area. Other abnormalities were usually found. Regular MRI studies of the brain were mostly unremarkable in these patients. We propose that functional MRI studies should become a diagnostic aid when evaluating a patient who claims electrohypersensitivity (EHS) and has otherwise normal studies. Interestingly, the differential diagnosis for the abnormalities seen on the fMRI includes head injury. It turns out that many of our patients indeed had a history of head injury which was then followed sometime later by the development of EHS. Many of our patients also had a history of exposure to potentially neurotoxic chemicals, especially mold. Head injury and neurotoxic chemical exposure may make a patient more vulnerable to develop EHS.

Default mode network, motor network, dorsal and ventral basal ganglia networks in the rat brain: comparison to human networks using resting state-fMRI.

PubMed

Sierakowiak, Adam; Monnot, Cyril; Aski, Sahar Nikkhou; Uppman, Martin; Li, Tie-Qiang; Damberg, Peter; Brené, Stefan

2015-01-01

Rodent models are developed to enhance understanding of the underlying biology of different brain disorders. However, before interpreting findings from animal models in a translational aspect to understand human disease, a fundamental step is to first have knowledge of similarities and differences of the biological systems studied. In this study, we analyzed and verified four known networks termed: default mode network, motor network, dorsal basal ganglia network, and ventral basal ganglia network using resting state functional MRI (rsfMRI) in humans and rats. Our work supports the notion that humans and rats have common robust resting state brain networks and that rsfMRI can be used as a translational tool when validating animal models of brain disorders. In the future, rsfMRI may be used, in addition to short-term interventions, to characterize longitudinal effects on functional brain networks after long-term intervention in humans and rats.

Default Mode Network, Motor Network, Dorsal and Ventral Basal Ganglia Networks in the Rat Brain: Comparison to Human Networks Using Resting State-fMRI

PubMed Central

Sierakowiak, Adam; Monnot, Cyril; Aski, Sahar Nikkhou; Uppman, Martin; Li, Tie-Qiang; Damberg, Peter; Brené, Stefan

2015-01-01

Rodent models are developed to enhance understanding of the underlying biology of different brain disorders. However, before interpreting findings from animal models in a translational aspect to understand human disease, a fundamental step is to first have knowledge of similarities and differences of the biological systems studied. In this study, we analyzed and verified four known networks termed: default mode network, motor network, dorsal basal ganglia network, and ventral basal ganglia network using resting state functional MRI (rsfMRI) in humans and rats. Our work supports the notion that humans and rats have common robust resting state brain networks and that rsfMRI can be used as a translational tool when validating animal models of brain disorders. In the future, rsfMRI may be used, in addition to short-term interventions, to characterize longitudinal effects on functional brain networks after long-term intervention in humans and rats. PMID:25789862

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

PubMed

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.

What can spontaneous fluctuations of the blood oxygenation-level-dependent signal tell us about psychiatric disorders?

PubMed

Fornito, Alex; Bullmore, Edward T

2010-05-01

Resting-state functional MRI (rs-fMRI) is an increasingly popular technique for studying brain dysfunction in psychiatric patients, and is widely assumed to measure intrinsic properties of functional brain organization. Here, we review rs-fMRI studies of psychiatric populations and consider how recent evidence concerning the neuronal basis, behavioural relevance, and the stability of rs-fMRI measures can inform and constrain interpretation of findings obtained using case-control designs. A range of rs-fMRI measures have been applied to different patient groups, although the findings have not always been consistent. The large-scale organization of rs-fMRI networks is robust and reproducible, and rs-fMRI measures show correlations with behavioural phenotypes relevant to psychiatry. However, evidence that such measures are also influenced by preceding psychological states and contexts, as well as individual variations in physiological arousal, may help to explain inconsistent findings in case-control comparisons. rs-fMRI measures show both stable and dynamic properties, the nature of which are only beginning to be uncovered. As such, interpreting significant differences between patients and controls on rs-fMRI measures as evidence for alterations in intrinsic functional brain organization should be done cautiously. Better understanding of the relationship between stable and transient aspects of spontaneous brain dynamics will be necessary to constrain interpretation of case-control studies and inform pathophysiological models.

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

PubMed Central

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.

PubMed

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.

Supervised dictionary learning for inferring concurrent brain networks.

PubMed

Zhao, Shijie; Han, Junwei; Lv, Jinglei; Jiang, Xi; Hu, Xintao; Zhao, Yu; Ge, Bao; Guo, Lei; Liu, Tianming

2015-10-01

Task-based fMRI (tfMRI) has been widely used to explore functional brain networks via predefined stimulus paradigm in the fMRI scan. Traditionally, the general linear model (GLM) has been a dominant approach to detect task-evoked networks. However, GLM focuses on task-evoked or event-evoked brain responses and possibly ignores the intrinsic brain functions. In comparison, dictionary learning and sparse coding methods have attracted much attention recently, and these methods have shown the promise of automatically and systematically decomposing fMRI signals into meaningful task-evoked and intrinsic concurrent networks. Nevertheless, two notable limitations of current data-driven dictionary learning method are that the prior knowledge of task paradigm is not sufficiently utilized and that the establishment of correspondences among dictionary atoms in different brains have been challenging. In this paper, we propose a novel supervised dictionary learning and sparse coding method for inferring functional networks from tfMRI data, which takes both of the advantages of model-driven method and data-driven method. The basic idea is to fix the task stimulus curves as predefined model-driven dictionary atoms and only optimize the other portion of data-driven dictionary atoms. Application of this novel methodology on the publicly available human connectome project (HCP) tfMRI datasets has achieved promising results.

“Awake” intraoperative functional MRI (ai-fMRI) for mapping the eloquent cortex: Is it possible in awake craniotomy?☆

PubMed Central

Lu, Jun-Feng; Zhang, Han; Wu, Jin-Song; Yao, Cheng-Jun; Zhuang, Dong-Xiao; Qiu, Tian-Ming; Jia, Wen-Bin; Mao, Ying; Zhou, Liang-Fu

2012-01-01

As a promising noninvasive imaging technique, functional MRI (fMRI) has been extensively adopted as a functional localization procedure for surgical planning. However, the information provided by preoperative fMRI (pre-fMRI) is hampered by the brain deformation that is secondary to surgical procedures. Therefore, intraoperative fMRI (i-fMRI) becomes a potential alternative that can compensate for brain shifts by updating the functional localization information during craniotomy. However, previous i-fMRI studies required that patients be under general anesthesia, preventing the wider application of such a technique as the patients cannot perform tasks unless they are awake. In this study, we propose a new technique that combines awake surgery and i-fMRI, named “awake” i-fMRI (ai-fMRI). We introduced ai-fMRI to the real-time localization of sensorimotor areas during awake craniotomy in seven patients. The results showed that ai-fMRI could successfully detect activations in the bilateral primary sensorimotor areas and supplementary motor areas for all patients, indicating the feasibility of this technique in eloquent area localization. The reliability of ai-fMRI was further validated using intraoperative stimulation mapping (ISM) in two of the seven patients. Comparisons between the pre-fMRI-derived localization result and the ai-fMRI derived result showed that the former was subject to a heavy brain shift and led to incorrect localization, while the latter solved that problem. Additionally, the approaches for the acquisition and processing of the ai-fMRI data were fully illustrated and described. Some practical issues on employing ai-fMRI in awake craniotomy were systemically discussed, and guidelines were provided. PMID:24179766

Adaptation of brain functional and structural networks in aging.

PubMed

Lee, Annie; Ratnarajah, Nagulan; Tuan, Ta Anh; Chen, Shen-Hsing Annabel; Qiu, Anqi

2015-01-01

The human brain, especially the prefrontal cortex (PFC), is functionally and anatomically reorganized in order to adapt to neuronal challenges in aging. This study employed structural MRI, resting-state fMRI (rs-fMRI), and high angular resolution diffusion imaging (HARDI), and examined the functional and structural reorganization of the PFC in aging using a Chinese sample of 173 subjects aged from 21 years and above. We found age-related increases in the structural connectivity between the PFC and posterior brain regions. Such findings were partially mediated by age-related increases in the structural connectivity of the occipital lobe within the posterior brain. Based on our findings, it is thought that the PFC reorganization in aging could be partly due to the adaptation to age-related changes in the structural reorganization of the posterior brain. This thus supports the idea derived from task-based fMRI that the PFC reorganization in aging may be adapted to the need of compensation for resolving less distinctive stimulus information from the posterior brain regions. In addition, we found that the structural connectivity of the PFC with the temporal lobe was fully mediated by the temporal cortical thickness, suggesting that the brain morphology plays an important role in the functional and structural reorganization with aging.

Constructing fMRI connectivity networks: a whole brain functional parcellation method for node definition.

PubMed

Maggioni, Eleonora; Tana, Maria Gabriella; Arrigoni, Filippo; Zucca, Claudio; Bianchi, Anna Maria

2014-05-15

Functional Magnetic Resonance Imaging (fMRI) is used for exploring brain functionality, and recently it was applied for mapping the brain connection patterns. To give a meaningful neurobiological interpretation to the connectivity network, it is fundamental to properly define the network framework. In particular, the choice of the network nodes may affect the final connectivity results and the consequent interpretation. We introduce a novel method for the intra subject topological characterization of the nodes of fMRI brain networks, based on a whole brain parcellation scheme. The proposed whole brain parcellation algorithm divides the brain into clusters that are homogeneous from the anatomical and functional point of view, each of which constitutes a node. The functional parcellation described is based on the Tononi's cluster index, which measures instantaneous correlation in terms of intrinsic and extrinsic statistical dependencies. The method performance and reliability were first tested on simulated data, then on a real fMRI dataset acquired on healthy subjects during visual stimulation. Finally, the proposed algorithm was applied to epileptic patients' fMRI data recorded during seizures, to verify its usefulness as preparatory step for effective connectivity analysis. For each patient, the nodes of the network involved in ictal activity were defined according to the proposed parcellation scheme and Granger Causality Analysis (GCA) was applied to infer effective connectivity. We showed that the algorithm 1) performed well on simulated data, 2) was able to produce reliable inter subjects results and 3) led to a detailed definition of the effective connectivity pattern. Copyright © 2014 Elsevier B.V. All rights reserved.

Probing the brain with molecular fMRI.

PubMed

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

2018-06-01

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.

Multivariate Heteroscedasticity Models for Functional Brain Connectivity.

PubMed

Seiler, Christof; Holmes, Susan

2017-01-01

Functional brain connectivity is the co-occurrence of brain activity in different areas during resting and while doing tasks. The data of interest are multivariate timeseries measured simultaneously across brain parcels using resting-state fMRI (rfMRI). We analyze functional connectivity using two heteroscedasticity models. Our first model is low-dimensional and scales linearly in the number of brain parcels. Our second model scales quadratically. We apply both models to data from the Human Connectome Project (HCP) comparing connectivity between short and conventional sleepers. We find stronger functional connectivity in short than conventional sleepers in brain areas consistent with previous findings. This might be due to subjects falling asleep in the scanner. Consequently, we recommend the inclusion of average sleep duration as a covariate to remove unwanted variation in rfMRI studies. A power analysis using the HCP data shows that a sample size of 40 detects 50% of the connectivity at a false discovery rate of 20%. We provide implementations using R and the probabilistic programming language Stan.

Resting-state functional magnetic resonance imaging in hepatic encephalopathy: current status and perspectives.

PubMed

Zhang, Long Jiang; Wu, Shengyong; Ren, Jiaqian; Lu, Guang Ming

2014-09-01

Hepatic encephalopathy (HE) is a neuropsychiatric syndrome which develops in patients with severe liver diseases and/or portal-systemic shunting. Minimal HE, the earliest manifestation of HE, has drawn increasing attention in the last decade. Minimal HE is associated with a series of brain functional changes, such as attention, working memory, and so on. Blood oxygen level dependent (BOLD) functional MRI (fMRI), especially resting-state fMRI has been used to explore the brain functional changes of HE, yielding important insights for understanding pathophysiological mechanisms and functional reorganization of HE. This paper briefly reviews the principles of BOLD fMRI, potential applications of resting-state fMRI with advanced post-processing algorithms such as regional homogeneity, amplitude of low frequency fluctuation, functional connectivity and future research perspective in this field.

Study of tonotopic brain changes with functional MRI and FDG-PET in a patient with unilateral objective cochlear tinnitus.

PubMed

Guinchard, A-C; Ghazaleh, Naghmeh; Saenz, M; Fornari, E; Prior, J O; Maeder, P; Adib, S; Maire, R

2016-11-01

We studied possible brain changes with functional MRI (fMRI) and fluorodeoxyglucose positron emission tomography (FDG-PET) in a patient with a rare, high-intensity "objective tinnitus" (high-level SOAEs) in the left ear of 10 years duration, with no associated hearing loss. This is the first case of objective cochlear tinnitus to be investigated with functional neuroimaging. The objective cochlear tinnitus was measured by Spontaneous Otoacoustic Emissions (SOAE) equipment (frequency 9689 Hz, intensity 57 dB SPL) and is clearly audible to anyone standing near the patient. Functional modifications in primary auditory areas and other brain regions were evaluated using 3T and 7T fMRI and FDG-PET. In the fMRI evaluations, a saturation of the auditory cortex at the tinnitus frequency was observed, but the global cortical tonotopic organization remained intact when compared to the results of fMRI of healthy subjects. The FDG-PET showed no evidence of an increase or decrease of activity in the auditory cortices or in the limbic system as compared to normal subjects. In this patient with high-intensity objective cochlear tinnitus, fMRI and FDG-PET showed no significant brain reorganization in auditory areas and/or in the limbic system, as reported in the literature in patients with chronic subjective tinnitus. Copyright © 2016 Elsevier B.V. All rights reserved.

Brain-wide pathway for waste clearance captured by contrast-enhanced MRI.

PubMed

Iliff, Jeffrey J; Lee, Hedok; Yu, Mei; Feng, Tian; Logan, Jean; Nedergaard, Maiken; Benveniste, Helene

2013-03-01

The glymphatic system is a recently defined brain-wide paravascular pathway for cerebrospinal fluid (CSF) and interstitial fluid (ISF) exchange that facilitates efficient clearance of solutes and waste from the brain. CSF enters the brain along para-arterial channels to exchange with ISF, which is in turn cleared from the brain along para-venous pathways. Because soluble amyloid β clearance depends on glymphatic pathway function, we proposed that failure of this clearance system contributes to amyloid plaque deposition and Alzheimer's disease progression. Here we provide proof of concept that glymphatic pathway function can be measured using a clinically relevant imaging technique. Dynamic contrast-enhanced MRI was used to visualize CSF-ISF exchange across the rat brain following intrathecal paramagnetic contrast agent administration. Key features of glymphatic pathway function were confirmed, including visualization of para-arterial CSF influx and molecular size-dependent CSF-ISF exchange. Whole-brain imaging allowed the identification of two key influx nodes at the pituitary and pineal gland recesses, while dynamic MRI permitted the definition of simple kinetic parameters to characterize glymphatic CSF-ISF exchange and solute clearance from the brain. We propose that this MRI approach may provide the basis for a wholly new strategy to evaluate Alzheimer's disease susceptibility and progression in the live human brain.

Brain-wide pathway for waste clearance captured by contrast-enhanced MRI

PubMed Central

Iliff, Jeffrey J.; Lee, Hedok; Yu, Mei; Feng, Tian; Logan, Jean; Nedergaard, Maiken; Benveniste, Helene

2013-01-01

The glymphatic system is a recently defined brain-wide paravascular pathway for cerebrospinal fluid (CSF) and interstitial fluid (ISF) exchange that facilitates efficient clearance of solutes and waste from the brain. CSF enters the brain along para-arterial channels to exchange with ISF, which is in turn cleared from the brain along para-venous pathways. Because soluble amyloid β clearance depends on glymphatic pathway function, we proposed that failure of this clearance system contributes to amyloid plaque deposition and Alzheimer’s disease progression. Here we provide proof of concept that glymphatic pathway function can be measured using a clinically relevant imaging technique. Dynamic contrast-enhanced MRI was used to visualize CSF-ISF exchange across the rat brain following intrathecal paramagnetic contrast agent administration. Key features of glymphatic pathway function were confirmed, including visualization of para-arterial CSF influx and molecular size-dependent CSF-ISF exchange. Whole-brain imaging allowed the identification of two key influx nodes at the pituitary and pineal gland recesses, while dynamic MRI permitted the definition of simple kinetic parameters to characterize glymphatic CSF-ISF exchange and solute clearance from the brain. We propose that this MRI approach may provide the basis for a wholly new strategy to evaluate Alzheimer’s disease susceptibility and progression in the live human brain. PMID:23434588

Impact of brain injury on functional measures of amplitude-integrated EEG at term equivalent age in premature infants.

PubMed

El Ters, N M; Vesoulis, Z A; Liao, S M; Smyser, C D; Mathur, A M

2017-08-01

To evaluate the association between qualitative and quantitative amplitude-integrated EEG (aEEG) measures at term equivalent age (TEA) and brain injury on magnetic resonance imaging (MRI) in preterm infants. A cohort of premature infants born at <30 weeks of gestation and with moderate-to-severe MRI injury on a TEA MRI scan was identified. A contemporaneous group of gestational age-matched control infants also born at <30 weeks of gestation with none/mild injury on MRI was also recruited. Quantitative aEEG measures, including maximum and minimum amplitudes, bandwidth span and spectral edge frequency (SEF 90 ), were calculated using an offline software package. The aEEG recordings were qualitatively scored using the Burdjalov system. MRI scans, performed on the same day as aEEG, occurred at a mean postmenstrual age of 38.0 (range 37 to 42) weeks and were scored for abnormality in a blinded manner using an established MRI scoring system. Twenty-eight (46.7%) infants had a normal MRI or mild brain abnormality, while 32 (53.3%) infants had moderate-to-severe brain abnormality. Univariate regression analysis demonstrated an association between severity of brain abnormality and quantitative measures of left and right SEF 90 and bandwidth span (β=-0.38, -0.40 and 0.30, respectively) and qualitative measures of cyclicity, continuity and total Burdjalov score (β=-0.10, -0.14 and -0.12, respectively). After correcting for confounding variables, the relationship between MRI abnormality score and aEEG measures of SEF 90 , bandwidth span and Burdjalov score remained significant. Brain abnormalities on MRI at TEA in premature infants are associated with abnormalities on term aEEG measures, suggesting that anatomical brain injury may contribute to delay in functional brain maturation as assessed using aEEG.

Scanning fast and slow: current limitations of 3 Tesla functional MRI and future potential

NASA Astrophysics Data System (ADS)

Boubela, Roland N.; Kalcher, Klaudius; Nasel, Christian; Moser, Ewald

2014-02-01

Functional MRI at 3T has become a workhorse for the neurosciences, e.g., neurology, psychology, and psychiatry, enabling non-invasive investigation of brain function and connectivity. However, BOLD-based fMRI is a rather indirect measure of brain function, confounded by fluctuation related signals, e.g. head or brain motion, brain pulsation, blood flow, intermixed with susceptibility differences close or distant to the region of neuronal activity. Even though a plethora of preprocessing strategies have been published to address these confounds, their efficiency is still under discussion. In particular, physiological signal fluctuations closely related to brain supply may mask BOLD signal changes related to "true" neuronal activation. Here we explore recent technical and methodological advancements aimed at disentangling the various components, employing fast multiband vs. standard EPI, in combination with fast temporal ICA.Our preliminary results indicate that fast (TR< 0.5s) scanning may help to identify and eliminate physiologic components, increasing tSNR and functional contrast. In addition, biological variability can be studied and task performance better correlated to other measures. This should increase specificity and reliability in fMRI studies. Furthermore, physiological signal changes during scanning may then be recognized as a source of information rather than a nuisance. As we are currently still undersampling the complexity of the brain, even at a rather coarse macroscopic level, we should be very cautious in the interpretation of neuroscientific findings, in particular when comparing different groups (e.g., age, sex, medication, pathology, etc.). From a technical point of view our goal should be to sample brain activity at layer specific resolution with low TR, covering as much of the brain as possible without violating SAR limits. We hope to stimulate discussion towards a better understanding and a more quantitative use of fMRI.

Functional brain networks reconstruction using group sparsity-regularized learning.

PubMed

Zhao, Qinghua; Li, Will X Y; Jiang, Xi; Lv, Jinglei; Lu, Jianfeng; Liu, Tianming

2018-06-01

Investigating functional brain networks and patterns using sparse representation of fMRI data has received significant interests in the neuroimaging community. It has been reported that sparse representation is effective in reconstructing concurrent and interactive functional brain networks. To date, most of data-driven network reconstruction approaches rarely take consideration of anatomical structures, which are the substrate of brain function. Furthermore, it has been rarely explored whether structured sparse representation with anatomical guidance could facilitate functional networks reconstruction. To address this problem, in this paper, we propose to reconstruct brain networks utilizing the structure guided group sparse regression (S2GSR) in which 116 anatomical regions from the AAL template, as prior knowledge, are employed to guide the network reconstruction when performing sparse representation of whole-brain fMRI data. Specifically, we extract fMRI signals from standard space aligned with the AAL template. Then by learning a global over-complete dictionary, with the learned dictionary as a set of features (regressors), the group structured regression employs anatomical structures as group information to regress whole brain signals. Finally, the decomposition coefficients matrix is mapped back to the brain volume to represent functional brain networks and patterns. We use the publicly available Human Connectome Project (HCP) Q1 dataset as the test bed, and the experimental results indicate that the proposed anatomically guided structure sparse representation is effective in reconstructing concurrent functional brain networks.

Gender similarities and differences in brain activation strategies: Voxel-based meta-analysis on fMRI studies.

PubMed

AlRyalat, Saif Aldeen

2017-01-01

Gender similarities and differences have long been a matter of debate in almost all human research, especially upon reaching the discussion about brain functions. This large scale meta-analysis was performed on functional MRI studies. It included more than 700 active brain foci from more than 70 different experiments to study gender related similarities and differences in brain activation strategies for three of the main brain functions: Visual-spatial cognition, memory, and emotion. Areas that are significantly activated by both genders (i.e. core areas) for the tested brain function are mentioned, whereas those areas significantly activated exclusively in one gender are the gender specific areas. During visual-spatial cognition task, and in addition to the core areas, males significantly activated their left superior frontal gyrus, compared with left superior parietal lobule in females. For memory tasks, several different brain areas activated by each gender, but females significantly activated two areas from the limbic system during memory retrieval tasks. For emotional task, males tend to recruit their bilateral prefrontal regions, whereas females tend to recruit their bilateral amygdalae. This meta-analysis provides an overview based on functional MRI studies on how males and females use their brain.

Spontaneous low frequency BOLD signal variations from resting-state fMRI are decreased in Alzheimer disease

PubMed Central

Manning, Kathryn Y.; Rajakumar, Nagalingam; Gómez, Francisco A.; Soddu, Andrea; Borrie, Michael J.

2017-01-01

Previous studies have demonstrated altered brain activity in Alzheimer's disease using task based functional MRI (fMRI), network based resting-state fMRI, and glucose metabolism from 18F fluorodeoxyglucose-PET (FDG-PET). Our goal was to define a novel indicator of neuronal activity based on a first-order textural feature of the resting state functional MRI (RS-fMRI) signal. Furthermore, we examined the association between this neuronal activity metric and glucose metabolism from 18F FDG-PET. We studied 15 normal elderly controls (NEC) and 15 probable Alzheimer disease (AD) subjects from the AD Neuroimaging Initiative. An independent component analysis was applied to the RS-fMRI, followed by template matching to identify neuronal components (NC). A regional brain activity measurement was constructed based on the variation of the RS-fMRI signal of these NC. The standardized glucose uptake values of several brain regions relative to the cerebellum (SUVR) were measured from partial volume corrected FDG-PET images. Comparing the AD and NEC groups, the mean brain activity metric was significantly lower in the accumbens, while the glucose SUVR was significantly lower in the amygdala and hippocampus. The RS-fMRI brain activity metric was positively correlated with cognitive measures and amyloid β1–42 cerebral spinal fluid levels; however, these did not remain significant following Bonferroni correction. There was a significant linear correlation between the brain activity metric and the glucose SUVR measurements. This proof of concept study demonstrates that this novel and easy to implement RS-fMRI brain activity metric can differentiate a group of healthy elderly controls from a group of people with AD. PMID:28582450

Spontaneous low frequency BOLD signal variations from resting-state fMRI are decreased in Alzheimer disease.

PubMed

Kazemifar, Samaneh; Manning, Kathryn Y; Rajakumar, Nagalingam; Gómez, Francisco A; Soddu, Andrea; Borrie, Michael J; Menon, Ravi S; Bartha, Robert

2017-01-01

Previous studies have demonstrated altered brain activity in Alzheimer's disease using task based functional MRI (fMRI), network based resting-state fMRI, and glucose metabolism from 18F fluorodeoxyglucose-PET (FDG-PET). Our goal was to define a novel indicator of neuronal activity based on a first-order textural feature of the resting state functional MRI (RS-fMRI) signal. Furthermore, we examined the association between this neuronal activity metric and glucose metabolism from 18F FDG-PET. We studied 15 normal elderly controls (NEC) and 15 probable Alzheimer disease (AD) subjects from the AD Neuroimaging Initiative. An independent component analysis was applied to the RS-fMRI, followed by template matching to identify neuronal components (NC). A regional brain activity measurement was constructed based on the variation of the RS-fMRI signal of these NC. The standardized glucose uptake values of several brain regions relative to the cerebellum (SUVR) were measured from partial volume corrected FDG-PET images. Comparing the AD and NEC groups, the mean brain activity metric was significantly lower in the accumbens, while the glucose SUVR was significantly lower in the amygdala and hippocampus. The RS-fMRI brain activity metric was positively correlated with cognitive measures and amyloid β1-42 cerebral spinal fluid levels; however, these did not remain significant following Bonferroni correction. There was a significant linear correlation between the brain activity metric and the glucose SUVR measurements. This proof of concept study demonstrates that this novel and easy to implement RS-fMRI brain activity metric can differentiate a group of healthy elderly controls from a group of people with AD.

Characterization of the resting-state brain network topology in the 6-hydroxydopamine rat model of Parkinson’s disease

PubMed Central

Simmons, Camilla; Mesquita, Michel B.; Wood, Tobias C.; Williams, Steve C. R.; Vernon, Anthony C.; Cash, Diana

2017-01-01

Resting-state functional MRI (rsfMRI) is an imaging technology that has recently gained attention for its ability to detect disruptions in functional brain networks in humans, including in patients with Parkinson’s disease (PD), revealing early and widespread brain network abnormalities. This methodology is now readily applicable to experimental animals offering new possibilities for cross-species translational imaging. In this context, we herein describe the application of rsfMRI to the unilaterally-lesioned 6-hydroxydopamine (6-OHDA) rat, a robust experimental model of the dopamine depletion implicated in PD. Using graph theory to analyse the rsfMRI data, we were able to provide meaningful and translatable measures of integrity, influence and segregation of the underlying functional brain architecture. Specifically, we confirm that rats share a similar functional brain network topology as observed in humans, characterised by small-worldness and modularity. Interestingly, we observed significantly reduced functional connectivity in the 6-OHDA rats, primarily in the ipsilateral (lesioned) hemisphere as evidenced by significantly lower node degree, local efficiency and clustering coefficient in the motor, orbital and sensorimotor cortices. In contrast, we found significantly, and bilaterally, increased thalamic functional connectivity in the lesioned rats. The unilateral deficits in the cortex are consistent with the unilateral nature of this model and further support the validity of the rsfMRI technique in rodents. We thereby provide a methodological framework for the investigation of brain networks in other rodent experimental models of PD, as well as of animal models in general, for cross-comparison with human data. PMID:28249008

Functional integrity in children with anoxic brain injury from drowning.

PubMed

Ishaque, Mariam; Manning, Janessa H; Woolsey, Mary D; Franklin, Crystal G; Tullis, Elizabeth W; Beckmann, Christian F; Fox, Peter T

2017-10-01

Drowning is a leading cause of accidental injury and death in young children. Anoxic brain injury (ABI) is a common consequence of drowning and can cause severe neurological morbidity in survivors. Assessment of functional status and prognostication in drowning victims can be extremely challenging, both acutely and chronically. Structural neuroimaging modalities (CT and MRI) have been of limited clinical value. Here, we tested the utility of resting-state functional MRI (rs-fMRI) for assessing brain functional integrity in this population. Eleven children with chronic, spastic quadriplegia due to drowning-induced ABI were investigated. All were comatose immediately after the injury and gradually regained consciousness, but with varying ability to communicate their cognitive state. Eleven neurotypical children matched for age and gender formed the control group. Resting-state fMRI and co-registered T1-weighted anatomical MRI were acquired at night during drug-aided sleep. Network integrity was quantified by independent components analysis (ICA), at both group- and per-subject levels. Functional-status assessments based on in-home observations were provided by families and caregivers. Motor ICNs were grossly compromised in ABI patients both group-wise and individually, concordant with their prominent motor deficits. Striking preservations of perceptual and cognitive ICNs were observed, and the degree of network preservation correlated (ρ = 0.74) with the per-subject functional status assessments. Collectively, our findings indicate that rs-fMRI has promise for assessing brain functional integrity in ABI and, potentially, in other disorders. Furthermore, our observations suggest that the severe motor deficits observed in this population can mask relatively intact perceptual and cognitive capabilities. Hum Brain Mapp 38:4813-4831, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

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

PubMed

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

2008-09-01

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

Diffusion and perfusion weighted magnetic resonance imaging for tumor volume definition in radiotherapy of brain tumors.

PubMed

Guo, Lu; Wang, Gang; Feng, Yuanming; Yu, Tonggang; Guo, Yu; Bai, Xu; Ye, Zhaoxiang

2016-09-21

Accurate target volume delineation is crucial for the radiotherapy of tumors. Diffusion and perfusion magnetic resonance imaging (MRI) can provide functional information about brain tumors, and they are able to detect tumor volume and physiological changes beyond the lesions shown on conventional MRI. This review examines recent studies that utilized diffusion and perfusion MRI for tumor volume definition in radiotherapy of brain tumors, and it presents the opportunities and challenges in the integration of multimodal functional MRI into clinical practice. The results indicate that specialized and robust post-processing algorithms and tools are needed for the precise alignment of targets on the images, and comprehensive validations with more clinical data are important for the improvement of the correlation between histopathologic results and MRI parameter images.

MRI evaluation and functional assessment of brain injury after hypoxic ischemia in neonatal mice.

PubMed

Adén, Ulrika; Dahlberg, Viktoria; Fredholm, Bertil B; Lai, Li-Ju; Chen, Zhengguan; Bjelke, Börje

2002-05-01

Severe perinatal asphyxia is an important cause of brain injury in the newborn infant. We examined early events after hypoxic ischemia (HI) in the 7-day-old mouse brain by MRI and related them to long-term functional effects and histopathology in the same animals at 4 to 5 weeks of age. HI was induced in 7-day-old CD1 mice by exposure to 8% oxygen for 30 minutes after occlusion of the left common carotid artery. The resulting unilateral focal lesion was evaluated in vivo by MRI (T2 maps and apparent diffusion coefficient maps) at 3, 6, and 24 hours and 5 days after hypoxia. Locomotion and sensorimotor function were analyzed after 3 weeks. Four weeks after HI, the mice were killed, and cresyl violet-stained brain sections were examined morphologically. A decrease in apparent diffusion coefficient values in cortex on the affected side was found at 3 hours after HI. T2 values were significantly increased after 6 hours and remained so for 5 days. Maximal size of the lesion was attained at 3 to 6 hours after HI and declined thereafter. Animals with MRI-detected lesions had decreased forward locomotion, performed worse than controls in the beam-walking test, and showed a unilateral hypotrophy in the cresyl violet-stained brain sections 4 weeks later. The temporal progression of the damage after HI in 7-day-old mice differs from that of the adult brain as judged by MRI. The early lesions detected by MRI were related to functional impairments for these mice in near-adult life.

Functional magnetic resonance imaging in clinical practice: State of the art and science.

PubMed

Barras, Christen D; Asadi, Hamed; Baldeweg, Torsten; Mancini, Laura; Yousry, Tarek A; Bisdas, Sotirios

2016-11-01

Functional magnetic resonance imaging (fMRI) has become a mainstream neuroimaging modality in the assessment of patients being evaluated for brain tumour and epilepsy surgeries. Thus, it is important for doctors in primary care settings to be well acquainted with the present and potential future applications, as well as limitations, of this modality. The objective of this article is to introduce the theoretical principles and state-of-the-art clinical applications of fMRI in brain tumour and epilepsy surgery, with a focus on the implications for clinical primary care. fMRI enables non-invasive functional mapping of specific cortical tasks (eg motor, language, memory-based, visual), revealing information about functional localisation, anatomical variation in cortical function, and disease effects and adaptations, including the fascinating phenomenon of brain plasticity. fMRI is currently ordered by specialist neurologists and neurosurgeons for the purposes of pre-surgical assessment, and within the context of an experienced multidisciplinary team to prepare, conduct and interpret the scan. With an increasing number of patients undergoing fMRI, general practitioners can expect questions about the current and emerging role of fMRI in clinical care from these patients and their families.

Functional magnetic resonance imaging reflects changes in brain functioning with sedation.

PubMed

Starbuck, Victoria N; Kay, Gary G; Platenberg, R. Craig; Lin, Chin-Shoou; Zielinski, Brandon A

2000-12-01

Functional magnetic resonance imaging (fMRI) studies have demonstrated localized brain activation during cognitive tasks. Brain activation increases with task complexity and decreases with familiarity. This study investigates how sleepiness alters the relationship between brain activation and task familiarity. We hypothesize that sleepiness prevents the reduction in activation associated with practice. Twenty-nine individuals rated their sleepiness using the Stanford Sleepiness Scale before fMRI. During imaging, subjects performed the Paced Auditory Serial Addition Test, a continuous mental arithmetic task. A positive correlation was observed between self-rated sleepiness and frontal brain activation. Fourteen subjects participated in phase 2. Sleepiness was induced by evening dosing with chlorpheniramine (CP) (8 mg or 12 mg) and terfenadine (60 mg) in the morning for 3 days before the second fMRI scan. The Multiple Sleep Latency Test (MSLT) was also performed. Results revealed a significant increase in fMRI activation in proportion to the dose of CP. In contrast, for all subjects receiving placebo there was a reduction in brain activation. MSLT revealed significant daytime sleepiness for subjects receiving CP. These findings suggest that sleepiness interferes with efficiency of brain functioning. The sleepy or sedated brain shows increased oxygen utilization during performance of a familiar cognitive task. Thus, the beneficial effect of prior task exposure is lost under conditions of sedation. Copyright 2000 John Wiley & Sons, Ltd.

Improving Functional MRI Registration Using Whole-Brain Functional Correlation Tensors.

PubMed

Zhou, Yujia; Yap, Pew-Thian; Zhang, Han; Zhang, Lichi; Feng, Qianjin; Shen, Dinggang

2017-09-01

Population studies of brain function with resting-state functional magnetic resonance imaging (rs-fMRI) largely rely on the accurate inter-subject registration of functional areas. This is typically achieved through registration of the corresponding T1-weighted MR images with more structural details. However, accumulating evidence has suggested that such strategy cannot well-align functional regions which are not necessarily confined by the anatomical boundaries defined by the T1-weighted MR images. To mitigate this problem, various registration algorithms based directly on rs-fMRI data have been developed, most of which have utilized functional connectivity (FC) as features for registration. However, most of the FC-based registration methods usually extract the functional features only from the thin and highly curved cortical grey matter (GM), posing a great challenge in accurately estimating the whole-brain deformation field. In this paper, we demonstrate that the additional useful functional features can be extracted from brain regions beyond the GM, particularly, white-matter (WM) based on rs-fMRI, for improving the overall functional registration. Specifically, we quantify the local anisotropic correlation patterns of the blood oxygenation level-dependent (BOLD) signals, modeled by functional correlation tensors (FCTs), in both GM and WM. Functional registration is then performed based on multiple components of the whole-brain FCTs using a multichannel Large Deformation Diffeomorphic Metric Mapping (mLDDMM) algorithm. Experimental results show that our proposed method achieves superior functional registration performance, compared with other conventional registration methods.

Functional magnetic resonance imaging.

PubMed

Buchbinder, Bradley R

2016-01-01

Functional magnetic resonance imaging (fMRI) maps the spatiotemporal distribution of neural activity in the brain under varying cognitive conditions. Since its inception in 1991, blood oxygen level-dependent (BOLD) fMRI has rapidly become a vital methodology in basic and applied neuroscience research. In the clinical realm, it has become an established tool for presurgical functional brain mapping. This chapter has three principal aims. First, we review key physiologic, biophysical, and methodologic principles that underlie BOLD fMRI, regardless of its particular area of application. These principles inform a nuanced interpretation of the BOLD fMRI signal, along with its neurophysiologic significance and pitfalls. Second, we illustrate the clinical application of task-based fMRI to presurgical motor, language, and memory mapping in patients with lesions near eloquent brain areas. Integration of BOLD fMRI and diffusion tensor white-matter tractography provides a road map for presurgical planning and intraoperative navigation that helps to maximize the extent of lesion resection while minimizing the risk of postoperative neurologic deficits. Finally, we highlight several basic principles of resting-state fMRI and its emerging translational clinical applications. Resting-state fMRI represents an important paradigm shift, focusing attention on functional connectivity within intrinsic cognitive networks. © 2016 Elsevier B.V. All rights reserved.

Repeated exposure of the developing rat brain to magnetic resonance imaging did not affect neurogenesis, cell death or memory function

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhu, Changlian; Department of Pediatrics, The Third Affiliated Hospital, Zhengzhou University; Gao, Jianfeng

2011-01-07

Research highlights: {yields} The effect of MRI on the developing brain is a matter of debate. {yields} Repeated exposure to MRI did not affect neurogenesis. {yields} Memory function was not affected by repeated MRI during development. {yields} Neither late gestation nor young postnatal brains were affected by MRI. {yields} Repeated MRI did not cause cell death in the neurogenic region of the hippocampus. -- Abstract: The effect of magnetic fields on the brain is a matter of debate. The objective of this study was to investigate whether repeated exposure to strong magnetic fields, such as during magnetic resonance imaging (MRI),more » could elicit changes in the developing rat brain. Embryonic day 15 (E15) and postnatal day 14 (P14) rats were exposed to MRI using a 7.05 T MR system. The animals were anesthetized and exposed for 35 min per day for 4 successive days. Control animals were anesthetized but no MRI was performed. Body temperature was maintained at 37 {sup o}C. BrdU was injected after each session (50 mg/kg). One month later, cell proliferation, neurogenesis and astrogenesis in the dentate gyrus were evaluated, revealing no effects of MRI, neither in the E15, nor in the P14 group. DNA damage in the dentate gyrus in the P14 group was evaluated on P18, 1 day after the last session, using TUNEL staining. There was no difference in the number of TUNEL-positive cells after MRI compared with controls, neither in mature neurons, nor in newborn progenitors (BrdU/TUNEL double-labeled cells). Novel object recognition was performed to assess memory function 1 month after MRI. There was no difference in the recognition index observed after MRI compared with the control rats, neither for the E15, nor for the P14 group. In conclusion, repeated exposure to MRI did not appear to affect neurogenesis, cell death or memory function in rats, neither in late gestation (E15-E18) nor in young postnatal (P14-P17) rats.« less

Neural and Behavioral Sequelae of Blast-Related Traumatic Brain Injury

DTIC Science & Technology

2012-11-01

testing and advanced MRI techniques [task-activated functional MRI (fMRI) and diffusion tensor imaging ( DTI )] to gain a comprehensive understanding of... DTI fiber tracking) and neurobehavioral testing (computerized assessment and standard neuropsychological testing) on 60 chronic trauma patients: 15...data analysis. 15. SUBJECT TERMS Blast-related traumatic brain injury (TBI), fMRI, DTI , cognition 16. SECURITY CLASSIFICATION OF: 17. LIMITATION

A test-retest dataset for assessing long-term reliability of brain morphology and resting-state brain activity.

PubMed

Huang, Lijie; Huang, Taicheng; Zhen, Zonglei; Liu, Jia

2016-03-15

We present a test-retest dataset for evaluation of long-term reliability of measures from structural and resting-state functional magnetic resonance imaging (sMRI and rfMRI) scans. The repeated scan dataset was collected from 61 healthy adults in two sessions using highly similar imaging parameters at an interval of 103-189 days. However, as the imaging parameters were not completely identical, the reliability estimated from this dataset shall reflect the lower bounds of the true reliability of sMRI/rfMRI measures. Furthermore, in conjunction with other test-retest datasets, our dataset may help explore the impact of different imaging parameters on reliability of sMRI/rfMRI measures, which is especially critical for assessing datasets collected from multiple centers. In addition, intelligence quotient (IQ) was measured for each participant using Raven's Advanced Progressive Matrices. The data can thus be used for purposes other than assessing reliability of sMRI/rfMRI alone. For example, data from each single session could be used to associate structural and functional measures of the brain with the IQ metrics to explore brain-IQ association.

Resting-state functional MRI as a tool for evaluating brain hemodynamic responsiveness to external stimuli in rats.

PubMed

Paasonen, Jaakko; Salo, Raimo A; Huttunen, Joanna K; Gröhn, Olli

2017-09-01

Anesthesia is a major confounding factor in functional MRI (fMRI) experiments attributed to its effects on brain function. Recent evidence suggests that parameters obtained with resting-state fMRI (rs-fMRI) are coupled with anesthetic depth. Therefore, we investigated whether parameters obtained with rs-fMRI, such as functional connectivity (FC), are also directly related to blood-oxygen-level-dependent (BOLD) responses. A simple rs-fMRI protocol was implemented in a pharmacological fMRI study to evaluate the coupling between hemodynamic responses and FC under five anesthetics (α-chloralose, isoflurane, medetomidine, thiobutabarbital, and urethane). Temporal change in the FC was evaluated at 1-hour interval. Supplementary forepaw stimulation experiments were also conducted. Under thiobutabarbital anesthesia, FC was clearly coupled with nicotine-induced BOLD responses. Good correlation values were also obtained under isoflurane and medetomidine anesthesia. The observations in the thiobutabarbital group were supported by forepaw stimulation experiments. Additionally, the rs-fMRI protocol revealed significant temporal changes in the FC in the α-chloralose, thiobutabarbital, and urethane groups. Our results suggest that FC can be used to estimate brain hemodynamic responsiveness to stimuli and evaluate the level and temporal changes of anesthesia. Therefore, analysis of the fMRI baseline signal may be highly valuable tool for controlling the outcome of preclinical fMRI experiments. Magn Reson Med 78:1136-1146, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Measuring speaker–listener neural coupling with functional near infrared spectroscopy

PubMed Central

Liu, Yichuan; Piazza, Elise A.; Simony, Erez; Shewokis, Patricia A.; Onaral, Banu; Hasson, Uri; Ayaz, Hasan

2017-01-01

The present study investigates brain-to-brain coupling, defined as inter-subject correlations in the hemodynamic response, during natural verbal communication. We used functional near-infrared spectroscopy (fNIRS) to record brain activity of 3 speakers telling stories and 15 listeners comprehending audio recordings of these stories. Listeners’ brain activity was significantly correlated with speakers’ with a delay. This between-brain correlation disappeared when verbal communication failed. We further compared the fNIRS and functional Magnetic Resonance Imaging (fMRI) recordings of listeners comprehending the same story and found a significant relationship between the fNIRS oxygenated-hemoglobin concentration changes and the fMRI BOLD in brain areas associated with speech comprehension. This correlation between fNIRS and fMRI was only present when data from the same story were compared between the two modalities and vanished when data from different stories were compared; this cross-modality consistency further highlights the reliability of the spatiotemporal brain activation pattern as a measure of story comprehension. Our findings suggest that fNIRS can be used for investigating brain-to-brain coupling during verbal communication in natural settings. PMID:28240295

Altered resting-state whole-brain functional networks of neonates with intrauterine growth restriction.

PubMed

Batalle, Dafnis; Muñoz-Moreno, Emma; Tornador, Cristian; Bargallo, Nuria; Deco, Gustavo; Eixarch, Elisenda; Gratacos, Eduard

2016-04-01

The feasibility to use functional MRI (fMRI) during natural sleep to assess low-frequency basal brain activity fluctuations in human neonates has been demonstrated, although its potential to characterise pathologies of prenatal origin has not yet been exploited. In the present study, we used intrauterine growth restriction (IUGR) as a model of altered neurodevelopment due to prenatal condition to show the suitability of brain networks to characterise functional brain organisation at neonatal age. Particularly, we analysed resting-state fMRI signal of 20 neonates with IUGR and 13 controls, obtaining whole-brain functional networks based on correlations of blood oxygen level-dependent (BOLD) signal in 90 grey matter regions of an anatomical atlas (AAL). Characterisation of the networks obtained with graph theoretical features showed increased network infrastructure and raw efficiencies but reduced efficiency after normalisation, demonstrating hyper-connected but sub-optimally organised IUGR functional brain networks. Significant association of network features with neurobehavioral scores was also found. Further assessment of spatiotemporal dynamics displayed alterations into features associated to frontal, cingulate and lingual cortices. These findings show the capacity of functional brain networks to characterise brain reorganisation from an early age, and their potential to develop biomarkers of altered neurodevelopment. Copyright © 2016 Elsevier Ltd. All rights reserved.

Decreased Complexity in Alzheimer's Disease: Resting-State fMRI Evidence of Brain Entropy Mapping.

PubMed

Wang, Bin; Niu, Yan; Miao, Liwen; Cao, Rui; Yan, Pengfei; Guo, Hao; Li, Dandan; Guo, Yuxiang; Yan, Tianyi; Wu, Jinglong; Xiang, Jie; Zhang, Hui

2017-01-01

Alzheimer's disease (AD) is a frequently observed, irreversible brain function disorder among elderly individuals. Resting-state functional magnetic resonance imaging (rs-fMRI) has been introduced as an alternative approach to assessing brain functional abnormalities in AD patients. However, alterations in the brain rs-fMRI signal complexities in mild cognitive impairment (MCI) and AD patients remain unclear. Here, we described the novel application of permutation entropy (PE) to investigate the abnormal complexity of rs-fMRI signals in MCI and AD patients. The rs-fMRI signals of 30 normal controls (NCs), 33 early MCI (EMCI), 32 late MCI (LMCI), and 29 AD patients were obtained from the Alzheimer's disease Neuroimaging Initiative (ADNI) database. After preprocessing, whole-brain entropy maps of the four groups were extracted and subjected to Gaussian smoothing. We performed a one-way analysis of variance (ANOVA) on the brain entropy maps of the four groups. The results after adjusting for age and sex differences together revealed that the patients with AD exhibited lower complexity than did the MCI and NC controls. We found five clusters that exhibited significant differences and were distributed primarily in the occipital, frontal, and temporal lobes. The average PE of the five clusters exhibited a decreasing trend from MCI to AD. The AD group exhibited the least complexity. Additionally, the average PE of the five clusters was significantly positively correlated with the Mini-Mental State Examination (MMSE) scores and significantly negatively correlated with Functional Assessment Questionnaire (FAQ) scores and global Clinical Dementia Rating (CDR) scores in the patient groups. Significant correlations were also found between the PE and regional homogeneity (ReHo) in the patient groups. These results indicated that declines in PE might be related to changes in regional functional homogeneity in AD. These findings suggested that complexity analyses using PE in rs-fMRI signals can provide important information about the fMRI characteristics of cognitive impairments in MCI and AD.

Decreased Complexity in Alzheimer's Disease: Resting-State fMRI Evidence of Brain Entropy Mapping

PubMed Central

Wang, Bin; Niu, Yan; Miao, Liwen; Cao, Rui; Yan, Pengfei; Guo, Hao; Li, Dandan; Guo, Yuxiang; Yan, Tianyi; Wu, Jinglong; Xiang, Jie; Zhang, Hui

2017-01-01

Alzheimer's disease (AD) is a frequently observed, irreversible brain function disorder among elderly individuals. Resting-state functional magnetic resonance imaging (rs-fMRI) has been introduced as an alternative approach to assessing brain functional abnormalities in AD patients. However, alterations in the brain rs-fMRI signal complexities in mild cognitive impairment (MCI) and AD patients remain unclear. Here, we described the novel application of permutation entropy (PE) to investigate the abnormal complexity of rs-fMRI signals in MCI and AD patients. The rs-fMRI signals of 30 normal controls (NCs), 33 early MCI (EMCI), 32 late MCI (LMCI), and 29 AD patients were obtained from the Alzheimer's disease Neuroimaging Initiative (ADNI) database. After preprocessing, whole-brain entropy maps of the four groups were extracted and subjected to Gaussian smoothing. We performed a one-way analysis of variance (ANOVA) on the brain entropy maps of the four groups. The results after adjusting for age and sex differences together revealed that the patients with AD exhibited lower complexity than did the MCI and NC controls. We found five clusters that exhibited significant differences and were distributed primarily in the occipital, frontal, and temporal lobes. The average PE of the five clusters exhibited a decreasing trend from MCI to AD. The AD group exhibited the least complexity. Additionally, the average PE of the five clusters was significantly positively correlated with the Mini-Mental State Examination (MMSE) scores and significantly negatively correlated with Functional Assessment Questionnaire (FAQ) scores and global Clinical Dementia Rating (CDR) scores in the patient groups. Significant correlations were also found between the PE and regional homogeneity (ReHo) in the patient groups. These results indicated that declines in PE might be related to changes in regional functional homogeneity in AD. These findings suggested that complexity analyses using PE in rs-fMRI signals can provide important information about the fMRI characteristics of cognitive impairments in MCI and AD. PMID:29209199

Optimization of flow-sensitive alternating inversion recovery (FAIR) for perfusion functional MRI of rodent brain.

PubMed

Nasrallah, Fatima A; Lee, Eugene L Q; Chuang, Kai-Hsiang

2012-11-01

Arterial spin labeling (ASL) MRI provides a noninvasive method to image perfusion, and has been applied to map neural activation in the brain. Although pulsed labeling methods have been widely used in humans, continuous ASL with a dedicated neck labeling coil is still the preferred method in rodent brain functional MRI (fMRI) to maximize the sensitivity and allow multislice acquisition. However, the additional hardware is not readily available and hence its application is limited. In this study, flow-sensitive alternating inversion recovery (FAIR) pulsed ASL was optimized for fMRI of rat brain. A practical challenge of FAIR is the suboptimal global inversion by the transmit coil of limited dimensions, which results in low effective labeling. By using a large volume transmit coil and proper positioning to optimize the body coverage, the perfusion signal was increased by 38.3% compared with positioning the brain at the isocenter. An additional 53.3% gain in signal was achieved using optimized repetition and inversion times compared with a long TR. Under electrical stimulation to the forepaws, a perfusion activation signal change of 63.7 ± 6.3% can be reliably detected in the primary somatosensory cortices using single slice or multislice echo planar imaging at 9.4 T. This demonstrates the potential of using pulsed ASL for multislice perfusion fMRI in functional and pharmacological applications in rat brain. Copyright © 2012 John Wiley & Sons, Ltd.

Comparison of brain MRI findings with language and motor function in the dystroglycanopathies.

PubMed

Brun, Brianna N; Mockler, Shelley R H; Laubscher, Katie M; Stephan, Carrie M; Wallace, Anne M; Collison, Julia A; Zimmerman, M Bridget; Dobyns, William B; Mathews, Katherine D

2017-02-14

To describe the spectrum of brain MRI findings in a cohort of individuals with dystroglycanopathies (DGs) and relate MRI results to function. All available brain MRIs done for clinical indications on individuals enrolled in a DG natural history study (NCT00313677) were reviewed. Reports were reviewed when MRI was not available. MRIs were categorized as follows: (1) cortical, brainstem, and cerebellar malformations; (2) cortical and cerebellar malformations; or (3) normal. Language development was assigned to 1 of 3 categories by a speech pathologist. Maximal motor function and presence of epilepsy were determined by history or examination. Twenty-five MRIs and 9 reports were reviewed. The most common MRI abnormalities were cobblestone cortex or dysgyria with an anterior-posterior gradient and cerebellar hypoplasia. Seven individuals had MRIs in group 1, 8 in group 2, and 19 in group 3. Language was impaired in 100% of those in MRI groups 1 and 2, and degree of language impairment correlated with severity of imaging. Eighty-five percent of the whole group achieved independent walking, but only 33% did in group 1. Epilepsy was present in 8% of the cohort and rose to 37% of those with an abnormal MRI. Developmental abnormalities of the brain such as cobblestone lissencephaly, cerebellar cysts, pontine hypoplasia, and brainstem bowing are hallmarks of DG and should prompt consideration of these diagnoses. Brain imaging in individuals with DG helps to predict outcomes, especially language development, aiding clinicians in prognostic counseling. © 2017 American Academy of Neurology.

MRI Guided Brain Stimulation without the Use of a Neuronavigation System

PubMed Central

Vaghefi, Ehsan; Byblow, Winston D.; Stinear, Cathy M.; Thompson, Benjamin

2015-01-01

A key issue in the field of noninvasive brain stimulation (NIBS) is the accurate localization of scalp positions that correspond to targeted cortical areas. The current gold standard is to combine structural and functional brain imaging with a commercially available “neuronavigation” system. However, neuronavigation systems are not commonplace outside of specialized research environments. Here we describe a technique that allows for the use of participant-specific functional and structural MRI data to guide NIBS without a neuronavigation system. Surface mesh representations of the head were generated using Brain Voyager and vectors linking key anatomical landmarks were drawn on the mesh. Our technique was then used to calculate the precise distances on the scalp corresponding to these vectors. These calculations were verified using actual measurements of the head and the technique was used to identify a scalp position corresponding to a brain area localized using functional MRI. PMID:26413537

Functional Magnetic Resonance Imaging Methods

PubMed Central

Chen, Jingyuan E.; Glover, Gary H.

2015-01-01

Since its inception in 1992, Functional Magnetic Resonance Imaging (fMRI) has become an indispensible tool for studying cognition in both the healthy and dysfunctional brain. FMRI monitors changes in the oxygenation of brain tissue resulting from altered metabolism consequent to a task-based evoked neural response or from spontaneous fluctuations in neural activity in the absence of conscious mentation (the “resting state”). Task-based studies have revealed neural correlates of a large number of important cognitive processes, while fMRI studies performed in the resting state have demonstrated brain-wide networks that result from brain regions with synchronized, apparently spontaneous activity. In this article, we review the methods used to acquire and analyze fMRI signals. PMID:26248581

Technetium-99m-HMPAO SPECT, CT and MRI in the evaluation of patients with chronic traumatic brain injury: a correlation with neuropsychological performance.

PubMed

Ichise, M; Chung, D G; Wang, P; Wortzman, G; Gray, B G; Franks, W

1994-02-01

The purposes of this study were: (1) to compare 99mTc-hexamethylpropyleneamineoxime (HMPAO) SPECT with CT and MRI in chronic traumatic brain injury (TBI) patients and (2) to correlate both functional and structural neuroimaging measurements of brain damage with neuropsychological (NP) performance. Twenty-nine patients (minor TBI, n = 15 and major TBI, n = 14) and 17 normal controls (NC) underwent HMPAO SPECT, CT, MRI and NP testing. Imaging data were analyzed both visually and quantitatively. Nineteen (66%) patients showed 42 abnormalities on SPECT images, whereas 13 (45%) and 10 (34%) patients showed 29 abnormalities on MRI and 24 abnormalities on CT. SPECT detected relatively more abnormalities than CT or MRI in the minor TBI subgroup. The TBI group showed impairment on 11 tests for memory, attention and executive function. Of these, the anterior-posterior ratio (APR) correlated with six tests, whereas the ventricle-to-brain ratio (VBR), a known structural index of a poor NP outcome, correlated with only two tests. In evaluating chronic TBI patients, HMPAO SPECT, as a complement to CT or MRI, may play a useful role by demonstrating brain dysfunction in morphologically intact brain regions and providing objective evidence for some of the impaired NP performance.

Comprehensive Review on Magnetic Resonance Imaging in Alzheimer's Disease.

PubMed

Dona, Olga; Thompson, Jeff; Druchok, Cheryl

2016-01-01

Alzheimer's disease (AD) is the most common cause of dementia in the elderly. However, definitive diagnosis of AD is only achievable postmortem and currently relies on clinical neurological evaluation. Magnetic resonance imaging (MRI) can evaluate brain changes typical of AD, including brain atrophy, presence of amyloid β (Aβ) plaques, and functional and biochemical abnormalities. Structural MRI (sMRI) has historically been used to assess the inherent brain atrophy present in AD. However, new techniques have recently emerged that have refined sMRI into a more precise tool to quantify the thickness and volume of AD-sensitive cerebral structures. Aβ plaques, a defining pathology of AD, are widely believed to contribute to the progressive cognitive decline in AD, but accurate assessment is only possible on autopsy. In vivo MRI of plaques, although currently limited to mouse models of AD, is a very promising technique. Measuring changes in activation and connectivity in AD-specific regions of the brain can be performed with functional MRI (fMRI). To help distinguish AD from diseases with similar symptoms, magnetic resonance spectroscopy (MRS) can be used to look for differing metabolite concentrations in vivo. Together, these MR techniques, evaluating various brain changes typical of AD, may help to provide a more definitive diagnosis and ease the assessment of the disease over time, noninvasively.

Increased power spectral density in resting-state pain-related brain networks in fibromyalgia.

PubMed

Kim, Ji-Young; Kim, Seong-Ho; Seo, Jeehye; Kim, Sang-Hyon; Han, Seung Woo; Nam, Eon Jeong; Kim, Seong-Kyu; Lee, Hui Joong; Lee, Seung-Jae; Kim, Yang-Tae; Chang, Yongmin

2013-09-01

Fibromyalgia (FM), characterized by chronic widespread pain, is known to be associated with heightened responses to painful stimuli and atypical resting-state functional connectivity among pain-related regions of the brain. Previous studies of FM using resting-state functional magnetic resonance imaging (rs-fMRI) have focused on intrinsic functional connectivity, which maps the spatial distribution of temporal correlations among spontaneous low-frequency fluctuation in functional MRI (fMRI) resting-state data. In the current study, using rs-fMRI data in the frequency domain, we investigated the possible alteration of power spectral density (PSD) of low-frequency fluctuation in brain regions associated with central pain processing in patients with FM. rsfMRI data were obtained from 19 patients with FM and 20 age-matched healthy female control subjects. For each subject, the PSDs for each brain region identified from functional connectivity maps were computed for the frequency band of 0.01 to 0.25 Hz. For each group, the average PSD was determined for each brain region and a 2-sample t test was performed to determine the difference in power between the 2 groups. According to the results, patients with FM exhibited significantly increased frequency power in the primary somatosensory cortex (S1), supplementary motor area (SMA), dorsolateral prefrontal cortex, and amygdala. In patients with FM, the increase in PSD did not show an association with depression or anxiety. Therefore, our findings of atypical increased frequency power during the resting state in pain-related brain regions may implicate the enhanced resting-state baseline neural activity in several brain regions associated with pain processing in FM. Copyright © 2013 International Association for the Study of Pain. Published by Elsevier B.V. All rights reserved.

Brain Abnormalities in Congenital Fibrosis of the Extraocular Muscles Type 1: A Multimodal MRI Imaging Study.

PubMed

Miao, Wen; Man, Fengyuan; Wu, Shaoqin; Lv, Bin; Wang, Zhenchang; Xian, Junfang; Sabel, Bernhard A; He, Huiguang; Jiao, Yonghong

2015-01-01

To explore the possible brain structural and functional alterations in congenital fibrosis of extraocular muscles type 1 (CFEOM1) patients using multimodal MRI imaging. T1-weighted, diffusion tensor images and functional MRI data were obtained from 9 KIF21A positive patients and 19 age- and gender-matched healthy controls. Voxel based morphometry and tract based spatial statistics were applied to the T1-weighted and diffusion tensor images, respectively. Amplitude of low frequency fluctuations and regional homogeneity were used to process the functional MRI data. We then compared these multimodal characteristics between CFEOM1 patients and healthy controls. Compared with healthy controls, CFEOM1 patients demonstrated increased grey matter volume in bilateral frontal orbital cortex and in the right temporal pole. No diffusion indices changes were detected, indicating unaffected white matter microstructure. In addition, from resting state functional MRI data, trend of amplitude of low-frequency fluctuations increases were noted in the right inferior parietal lobe and in the right frontal cortex, and a trend of ReHo increase (p<0.001 uncorrected) in the left precentral gyrus, left orbital frontal cortex, temporal pole and cingulate gyrus. CFEOM1 patients had structural and functional changes in grey matter, but the white matter was unaffected. These alterations in the brain may be due to the abnormality of extraocular muscles and their innervating nerves. Future studies should consider the possible correlations between brain morphological/functional findings and clinical data, especially pertaining to eye movements, to obtain more precise answers about the role of brain area changes and their functional consequence in CFEOM1.

Spatially Regularized Machine Learning for Task and Resting-state fMRI

PubMed Central

Song, Xiaomu; Panych, Lawrence P.; Chen, Nan-kuei

2015-01-01

Background Reliable mapping of brain function across sessions and/or subjects in task- and resting-state has been a critical challenge for quantitative fMRI studies although it has been intensively addressed in the past decades. New Method A spatially regularized support vector machine (SVM) technique was developed for the reliable brain mapping in task- and resting-state. Unlike most existing SVM-based brain mapping techniques, which implement supervised classifications of specific brain functional states or disorders, the proposed method performs a semi-supervised classification for the general brain function mapping where spatial correlation of fMRI is integrated into the SVM learning. The method can adapt to intra- and inter-subject variations induced by fMRI nonstationarity, and identify a true boundary between active and inactive voxels, or between functionally connected and unconnected voxels in a feature space. Results The method was evaluated using synthetic and experimental data at the individual and group level. Multiple features were evaluated in terms of their contributions to the spatially regularized SVM learning. Reliable mapping results in both task- and resting-state were obtained from individual subjects and at the group level. Comparison with Existing Methods A comparison study was performed with independent component analysis, general linear model, and correlation analysis methods. Experimental results indicate that the proposed method can provide a better or comparable mapping performance at the individual and group level. Conclusions The proposed method can provide accurate and reliable mapping of brain function in task- and resting-state, and is applicable to a variety of quantitative fMRI studies. PMID:26470627

Electrophysiological correlates of the BOLD signal for EEG-informed fMRI

PubMed Central

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 brain activity during voluntary anal sphincter contraction: Comparative study in women with and without fecal incontinence.

PubMed

Parés, D; Martínez-Vilalta, M; Ortiz, H; Soriano-Mas, C; Maestre-Gonzalez, Y; Pujol, J; Grande, L

2018-04-14

Voluntary anal sphincter function is driven by an extended network of brain structures, most of which are still unknown. Disturbances in this function may cause fecal incontinence. The aim of this study was to characterize the cerebral areas involved in voluntary contraction of the anorectal sphincter in healthy women and in a group of patients with fecal incontinence by using a standardized functional magnetic resonance imaging (fMRI) protocol. This comparative study included 12 healthy women (mean age 53.17 ± 4.93 years) and 12 women with fecal incontinence (56.25 ± 6.94 years). An MRI-compatible anal manometer was used to register voluntary external anal sphincter contraction. During brain fMRI imaging, participants were cued to perform 10-s series of self-paced anal sphincter contractions at an approximate rate of 1 Hz. Brain structures linked to anal sphincter contractions were mapped and the findings were compared between the 2 study groups. There were no differences in the evoked brain activity between the 2 groups. In healthy women, group fMRI analysis revealed significant activations in medial primary motor cortices, supplementary motor area, bilateral putamen, and cerebellum, as well as in the supramarginal gyrus and visual areas. In patients with fecal incontinence, the activation pattern involved similar regions without significant differences with healthy women. This brain fMRI-anorectal protocol was able to map the brain regions linked to voluntary anal sphincter function in healthy and women with fecal incontinence. © 2018 John Wiley & Sons Ltd.

Event-related functional MRI: Past, present, and future

PubMed Central

Rosen, Bruce R.; Buckner, Randy L.; Dale, Anders M.

1998-01-01

The past two decades have seen an enormous growth in the field of human brain mapping. Investigators have extensively exploited techniques such as positron emission tomography and MRI to map patterns of brain activity based on changes in cerebral hemodynamics. However, until recently, most studies have investigated equilibrium changes in blood flow measured over time periods upward of 1 min. The advent of high-speed MRI methods, capable of imaging the entire brain with a temporal resolution of a few seconds, allows for brain mapping based on more transient aspects of the hemodynamic response. Today it is now possible to map changes in cerebrovascular parameters essentially in real time, conferring the ability to observe changes in brain state that occur over time periods of seconds. Furthermore, because robust hemodynamic alterations are detectable after neuronal stimuli lasting only a few tens of milliseconds, a new class of task paradigms designed to measure regional responses to single sensory or cognitive events can now be studied. Such “event related” functional MRI should provide for fundamentally new ways to interrogate brain function, and allow for the direct comparison and ultimately integration of data acquired by using more traditional behavioral and electrophysiological methods. PMID:9448240

Temporal Dynamics Assessment of Spatial Overlap Pattern of Functional Brain Networks Reveals Novel Functional Architecture of Cerebral Cortex.

PubMed

Jiang, Xi; Li, Xiang; Lv, Jinglei; Zhao, Shijie; Zhang, Shu; Zhang, Wei; Zhang, Tuo; Han, Junwei; Guo, Lei; Liu, Tianming

2018-06-01

Various studies in the brain mapping field have demonstrated that there exist multiple concurrent functional networks that are spatially overlapped and interacting with each other during specific task performance to jointly realize the total brain function. Assessing such spatial overlap patterns of functional networks (SOPFNs) based on functional magnetic resonance imaging (fMRI) has thus received increasing interest for brain function studies. However, there are still two crucial issues to be addressed. First, the SOPFNs are assessed over the entire fMRI scan assuming the temporal stationarity, while possibly time-dependent dynamics of the SOPFNs is not sufficiently explored. Second, the SOPFNs are assessed within individual subjects, while group-wise consistency of the SOPFNs is largely unknown. To address the two issues, we propose a novel computational framework of group-wise sparse representation of whole-brain fMRI temporal segments to assess the temporal dynamic spatial patterns of SOPFNs that are consistent across different subjects. Experimental results based on the recently publicly released Human Connectome Project grayordinate task fMRI data demonstrate that meaningful SOPFNs exhibiting dynamic spatial patterns across different time periods are effectively and robustly identified based on the reconstructed concurrent functional networks via the proposed framework. Specifically, those SOPFNs locate significantly more on gyral regions than on sulcal regions across different time periods. These results reveal novel functional architecture of cortical gyri and sulci. Moreover, these results help better understand functional dynamics mechanisms of cerebral cortex in the future.

Altered intrinsic brain activity after chemotherapy in patients with gastric cancer: A preliminary study.

PubMed

Kim, Hyun Gi; Shin, Na-Young; Bak, Yunjin; Kim, Kyung Ran; Jung, Young-Chul; Han, Kyunghwa; Lee, Seung-Koo; Lim, Soo Mee

2017-07-01

To characterize the pattern of altered intrinsic brain activity in gastric cancer patients after chemotherapy (CTx). Patients before and after CTx (n = 14) and control subjects (n = 11) underwent resting-state functional MRI (rsfMRI) at baseline and 3 months after CTx. Regional homogeneity (ReHo), amplitude of low-frequency fluctuation (ALFF), and fractional ALFF (fALFF) were calculated and compared between the groups using the two-sample t test. Correlation analysis was also performed between rsfMRI values (i.e., ReHo, ALFF, and fALFF) and neuropsychological test results. Patients showed poor performance in verbal memory and executive function and decreased rsfMRI values in the frontal areas even before CTx and showed decreased attention/working memory and executive function after CTx compared to the control subjects. In direct comparison of values before and after CTx, there were no significant differences in neuropsychological test scores, but decreased rsfMRI values were observed at the frontal lobes and right cerebellar region. Among rsfMRI values, lower ALFF in the left inferior frontal gyrus was significantly associated with poor performance of the executive function test. We observed decreased attention/working memory and executive function that corresponded to the decline of frontal region activation in gastric cancer patients who underwent CTx. • Intrinsic brain activity of gastric cancer patients after chemotherapy was described. • Brain activity and neuropsychological test results were correlated. • Working memory and executive function decreased after chemotherapy. • Decreased cognitive function corresponded to decreased activation of the frontal region.

Resting-state fMRI study of patients with fragile X syndrome

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

The effect of alcohol consumption on the adolescent brain: A systematic review of MRI and fMRI studies of alcohol-using youth

PubMed Central

Feldstein Ewing, Sarah W.; Sakhardande, Ashok; Blakemore, Sarah-Jayne

2014-01-01

Background A large proportion of adolescents drink alcohol, with many engaging in high-risk patterns of consumption, including binge drinking. Here, we systematically review and synthesize the existing empirical literature on how consuming alcohol affects the developing human brain in alcohol-using (AU) youth. Methods For this systematic review, we began by conducting a literature search using the PubMED database to identify all available peer-reviewed magnetic resonance imaging (MRI) and functional magnetic resonance imaging (fMRI) studies of AU adolescents (aged 19 and under). All studies were screened against a strict set of criteria designed to constrain the impact of confounding factors, such as co-occurring psychiatric conditions. Results Twenty-one studies (10 MRI and 11 fMRI) met the criteria for inclusion. A synthesis of the MRI studies suggested that overall, AU youth showed regional differences in brain structure as compared with non-AU youth, with smaller grey matter volumes and lower white matter integrity in relevant brain areas. In terms of fMRI outcomes, despite equivalent task performance between AU and non-AU youth, AU youth showed a broad pattern of lower task-relevant activation, and greater task-irrelevant activation. In addition, a pattern of gender differences was observed for brain structure and function, with particularly striking effects among AU females. Conclusions Alcohol consumption during adolescence was associated with significant differences in structure and function in the developing human brain. However, this is a nascent field, with several limiting factors (including small sample sizes, cross-sectional designs, presence of confounding factors) within many of the reviewed studies, meaning that results should be interpreted in light of the preliminary state of the field. Future longitudinal and large-scale studies are critical to replicate the existing findings, and to provide a more comprehensive and conclusive picture of the effect of alcohol consumption on the developing brain. PMID:26958467

The effect of alcohol consumption on the adolescent brain: A systematic review of MRI and fMRI studies of alcohol-using youth.

PubMed

Ewing, Sarah W Feldstein; Sakhardande, Ashok; Blakemore, Sarah-Jayne

2014-01-01

A large proportion of adolescents drink alcohol, with many engaging in high-risk patterns of consumption, including binge drinking. Here, we systematically review and synthesize the existing empirical literature on how consuming alcohol affects the developing human brain in alcohol-using (AU) youth. For this systematic review, we began by conducting a literature search using the PubMED database to identify all available peer-reviewed magnetic resonance imaging (MRI) and functional magnetic resonance imaging (fMRI) studies of AU adolescents (aged 19 and under). All studies were screened against a strict set of criteria designed to constrain the impact of confounding factors, such as co-occurring psychiatric conditions. Twenty-one studies (10 MRI and 11 fMRI) met the criteria for inclusion. A synthesis of the MRI studies suggested that overall, AU youth showed regional differences in brain structure as compared with non-AU youth, with smaller grey matter volumes and lower white matter integrity in relevant brain areas. In terms of fMRI outcomes, despite equivalent task performance between AU and non-AU youth, AU youth showed a broad pattern of lower task-relevant activation, and greater task-irrelevant activation. In addition, a pattern of gender differences was observed for brain structure and function, with particularly striking effects among AU females. Alcohol consumption during adolescence was associated with significant differences in structure and function in the developing human brain. However, this is a nascent field, with several limiting factors (including small sample sizes, cross-sectional designs, presence of confounding factors) within many of the reviewed studies, meaning that results should be interpreted in light of the preliminary state of the field. Future longitudinal and large-scale studies are critical to replicate the existing findings, and to provide a more comprehensive and conclusive picture of the effect of alcohol consumption on the developing brain.

The Whole-Brain “Global” Signal from Resting State fMRI as a Potential Biomarker of Quantitative State Changes in Glucose Metabolism

PubMed Central

Thompson, Garth J.; Grimmer, Timo; Drzezga, Alexander; Herman, Peter

2016-01-01

Abstract The evolution of functional magnetic resonance imaging to resting state (R-fMRI) allows measurement of changes in brain networks attributed to state changes, such as in neuropsychiatric diseases versus healthy controls. Since these networks are observed by comparing normalized R-fMRI signals, it is difficult to determine the metabolic basis of such group differences. To investigate the metabolic basis of R-fMRI network differences within a normal range, eyes open versus eyes closed in healthy human subjects was used. R-fMRI was recorded simultaneously with fluoro-deoxyglucose positron emission tomography (FDG-PET). Higher baseline FDG was observed in the eyes open state. Variance-based metrics calculated from R-fMRI did not match the baseline shift in FDG. Functional connectivity density (FCD)-based metrics showed a shift similar to the baseline shift of FDG, however, this was lost if R-fMRI “nuisance signals” were regressed before FCD calculation. Average correlation with the mean R-fMRI signal across the whole brain, generally regarded as a “nuisance signal,” also showed a shift similar to the baseline of FDG. Thus, despite lacking a baseline itself, changes in whole-brain correlation may reflect changes in baseline brain metabolism. Conversely, variance-based metrics may remain similar between states due to inherent region-to-region differences overwhelming the differences between normal physiological states. As most previous studies have excluded the spatial means of R-fMRI metrics from their analysis, this work presents the first evidence of a potential R-fMRI biomarker for baseline shifts in quantifiable metabolism between brain states. PMID:27029438

The Whole-Brain "Global" Signal from Resting State fMRI as a Potential Biomarker of Quantitative State Changes in Glucose Metabolism.

PubMed

Thompson, Garth J; Riedl, Valentin; Grimmer, Timo; Drzezga, Alexander; Herman, Peter; Hyder, Fahmeed

2016-07-01

The evolution of functional magnetic resonance imaging to resting state (R-fMRI) allows measurement of changes in brain networks attributed to state changes, such as in neuropsychiatric diseases versus healthy controls. Since these networks are observed by comparing normalized R-fMRI signals, it is difficult to determine the metabolic basis of such group differences. To investigate the metabolic basis of R-fMRI network differences within a normal range, eyes open versus eyes closed in healthy human subjects was used. R-fMRI was recorded simultaneously with fluoro-deoxyglucose positron emission tomography (FDG-PET). Higher baseline FDG was observed in the eyes open state. Variance-based metrics calculated from R-fMRI did not match the baseline shift in FDG. Functional connectivity density (FCD)-based metrics showed a shift similar to the baseline shift of FDG, however, this was lost if R-fMRI "nuisance signals" were regressed before FCD calculation. Average correlation with the mean R-fMRI signal across the whole brain, generally regarded as a "nuisance signal," also showed a shift similar to the baseline of FDG. Thus, despite lacking a baseline itself, changes in whole-brain correlation may reflect changes in baseline brain metabolism. Conversely, variance-based metrics may remain similar between states due to inherent region-to-region differences overwhelming the differences between normal physiological states. As most previous studies have excluded the spatial means of R-fMRI metrics from their analysis, this work presents the first evidence of a potential R-fMRI biomarker for baseline shifts in quantifiable metabolism between brain states.

On the feasibility of concurrent human TMS-EEG-fMRI measurements

PubMed Central

Reithler, Joel; Schuhmann, Teresa; de Graaf, Tom; Uludağ, Kâmil; Goebel, Rainer; Sack, Alexander T.

2013-01-01

Simultaneously combining the complementary assets of EEG, functional MRI (fMRI), and transcranial magnetic stimulation (TMS) within one experimental session provides synergetic results, offering insights into brain function that go beyond the scope of each method when used in isolation. The steady increase of concurrent EEG-fMRI, TMS-EEG, and TMS-fMRI studies further underlines the added value of such multimodal imaging approaches. Whereas concurrent EEG-fMRI enables monitoring of brain-wide network dynamics with high temporal and spatial resolution, the combination with TMS provides insights in causal interactions within these networks. Thus the simultaneous use of all three methods would allow studying fast, spatially accurate, and distributed causal interactions in the perturbed system and its functional relevance for intact behavior. Concurrent EEG-fMRI, TMS-EEG, and TMS-fMRI experiments are already technically challenging, and the three-way combination of TMS-EEG-fMRI might yield additional difficulties in terms of hardware strain or signal quality. The present study explored the feasibility of concurrent TMS-EEG-fMRI studies by performing safety and quality assurance tests based on phantom and human data combining existing commercially available hardware. Results revealed that combined TMS-EEG-fMRI measurements were technically feasible, safe in terms of induced temperature changes, allowed functional MRI acquisition with comparable image quality as during concurrent EEG-fMRI or TMS-fMRI, and provided artifact-free EEG before and from 300 ms after TMS pulse application. Based on these empirical findings, we discuss the conceptual benefits of this novel complementary approach to investigate the working human brain and list a number of precautions and caveats to be heeded when setting up such multimodal imaging facilities with current hardware. PMID:23221407

A feature-based approach to combine functional MRI, structural MRI and EEG brain imaging data.

PubMed

Calhoun, V; Adali, T; Liu, J

2006-01-01

The acquisition of multiple brain imaging types for a given study is a very common practice. However these data are typically examined in separate analyses, rather than in a combined model. We propose a novel methodology to perform joint independent component analysis across image modalities, including structural MRI data, functional MRI activation data and EEG data, and to visualize the results via a joint histogram visualization technique. Evaluation of which combination of fused data is most useful is determined by using the Kullback-Leibler divergence. We demonstrate our method on a data set composed of functional MRI data from two tasks, structural MRI data, and EEG data collected on patients with schizophrenia and healthy controls. We show that combining data types can improve our ability to distinguish differences between groups.

EKG-based detection of deep brain stimulation in fMRI studies.

PubMed

Fiveland, Eric; Madhavan, Radhika; Prusik, Julia; Linton, Renee; Dimarzio, Marisa; Ashe, Jeffrey; Pilitsis, Julie; Hancu, Ileana

2018-04-01

To assess the impact of synchronization errors between the assumed functional MRI paradigm timing and the deep brain stimulation (DBS) on/off cycling using a custom electrocardiogram-based triggering system METHODS: A detector for measuring and predicting the on/off state of cycling deep brain stimulation was developed and tested in six patients in office visits. Three-electrode electrocardiogram measurements, amplified by a commercial bio-amplifier, were used as input for a custom electronics box (e-box). The e-box transformed the deep brain stimulation waveforms into transistor-transistor logic pulses, recorded their timing, and propagated it in time. The e-box was used to trigger task-based deep brain stimulation functional MRI scans in 5 additional subjects; the impact of timing accuracy on t-test values was investigated in a simulation study using the functional MRI data. Following locking to each patient's individual waveform, the e-box was shown to predict stimulation onset with an average absolute error of 112 ± 148 ms, 30 min after disconnecting from the patients. The subsecond accuracy of the e-box in predicting timing onset is more than adequate for our slow varying, 30-/30-s on/off stimulation paradigm. Conversely, the experimental deep brain stimulation onset prediction accuracy in the absence of the e-box, which could be off by as much as 4 to 6 s, could significantly decrease activation strength. Using this detector, stimulation can be accurately synchronized to functional MRI acquisitions, without adding any additional hardware in the MRI environment. Magn Reson Med 79:2432-2439, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Large-Scale functional network overlap is a general property of brain functional organization: Reconciling inconsistent fMRI findings from general-linear-model-based analyses

PubMed Central

Xu, Jiansong; Potenza, Marc N.; Calhoun, Vince D.; Zhang, Rubin; Yip, Sarah W.; Wall, John T.; Pearlson, Godfrey D.; Worhunsky, Patrick D.; Garrison, Kathleen A.; Moran, Joseph M.

2016-01-01

Functional magnetic resonance imaging (fMRI) studies regularly use univariate general-linear-model-based analyses (GLM). Their findings are often inconsistent across different studies, perhaps because of several fundamental brain properties including functional heterogeneity, balanced excitation and inhibition (E/I), and sparseness of neuronal activities. These properties stipulate heterogeneous neuronal activities in the same voxels and likely limit the sensitivity and specificity of GLM. This paper selectively reviews findings of histological and electrophysiological studies and fMRI spatial independent component analysis (sICA) and reports new findings by applying sICA to two existing datasets. The extant and new findings consistently demonstrate several novel features of brain functional organization not revealed by GLM. They include overlap of large-scale functional networks (FNs) and their concurrent opposite modulations, and no significant modulations in activity of most FNs across the whole brain during any task conditions. These novel features of brain functional organization are highly consistent with the brain’s properties of functional heterogeneity, balanced E/I, and sparseness of neuronal activity, and may help reconcile inconsistent GLM findings. PMID:27592153

Inferring deep-brain activity from cortical activity using functional near-infrared spectroscopy

PubMed Central

Liu, Ning; Cui, Xu; Bryant, Daniel M.; Glover, Gary H.; Reiss, Allan L.

2015-01-01

Functional near-infrared spectroscopy (fNIRS) is an increasingly popular technology for studying brain function because it is non-invasive, non-irradiating and relatively inexpensive. Further, fNIRS potentially allows measurement of hemodynamic activity with high temporal resolution (milliseconds) and in naturalistic settings. However, in comparison with other imaging modalities, namely fMRI, fNIRS has a significant drawback: limited sensitivity to hemodynamic changes in deep-brain regions. To overcome this limitation, we developed a computational method to infer deep-brain activity using fNIRS measurements of cortical activity. Using simultaneous fNIRS and fMRI, we measured brain activity in 17 participants as they completed three cognitive tasks. A support vector regression (SVR) learning algorithm was used to predict activity in twelve deep-brain regions using information from surface fNIRS measurements. We compared these predictions against actual fMRI-measured activity using Pearson’s correlation to quantify prediction performance. To provide a benchmark for comparison, we also used fMRI measurements of cortical activity to infer deep-brain activity. When using fMRI-measured activity from the entire cortex, we were able to predict deep-brain activity in the fusiform cortex with an average correlation coefficient of 0.80 and in all deep-brain regions with an average correlation coefficient of 0.67. The top 15% of predictions using fNIRS signal achieved an accuracy of 0.7. To our knowledge, this study is the first to investigate the feasibility of using cortical activity to infer deep-brain activity. This new method has the potential to extend fNIRS applications in cognitive and clinical neuroscience research. PMID:25798327

Estimation of the EEG power spectrum using MRI T(2) relaxation time in traumatic brain injury.

PubMed

Thatcher, R W; Biver, C; Gomez, J F; North, D; Curtin, R; Walker, R A; Salazar, A

2001-09-01

To study the relationship between magnetic resonance imaging (MRI) T(2) relaxation time and the power spectrum of the electroencephalogram (EEG) in long-term follow up of traumatic brain injury. Nineteen channel quantitative electroencephalograms or qEEG, tests of cognitive function and quantitative MRI T(2) relaxation times (qMRI) were measured in 18 mild to severe closed head injured outpatients 2 months to 4.6 years after injury and 11 normal controls. MRI T(2) and the Laplacian of T(2) were then correlated with the power spectrum of the scalp electrical potentials and current source densities of the qEEG. qEEG and qMRI T(2) were related by a frequency tuning with maxima in the alpha (8-12Hz) and the lower EEG frequencies (0.5-5Hz), which varied as a function of spatial location. The Laplacian of T(2) acted like a spatial-temporal "lens" by increasing the spatial-temporal resolution of correlation between 3-dimensional T(2) and the ear referenced alert but resting spontaneous qEEG. The severity of traumatic brain injury can be modeled by a linear transfer function that relates the molecular qMRI to qEEG resonant frequencies.

Community structure in networks of functional connectivity: resolving functional organization in the rat brain with pharmacological MRI.

PubMed

Schwarz, Adam J; Gozzi, Alessandro; Bifone, Angelo

2009-08-01

In the study of functional connectivity, fMRI data can be represented mathematically as a network of nodes and links, where image voxels represent the nodes and the connections between them reflect a degree of correlation or similarity in their response. Here we show that, within this framework, functional imaging data can be partitioned into 'communities' of tightly interconnected voxels corresponding to maximum modularity within the overall network. We evaluated this approach systematically in application to networks constructed from pharmacological MRI (phMRI) of the rat brain in response to acute challenge with three different compounds with distinct mechanisms of action (d-amphetamine, fluoxetine, and nicotine) as well as vehicle (physiological saline). This approach resulted in bilaterally symmetric sub-networks corresponding to meaningful anatomical and functional connectivity pathways consistent with the purported mechanism of action of each drug. Interestingly, common features across all three networks revealed two groups of tightly coupled brain structures that responded as functional units independent of the specific neurotransmitter systems stimulated by the drug challenge, including a network involving the prefrontal cortex and sub-cortical regions extending from the striatum to the amygdala. This finding suggests that each of these networks includes general underlying features of the functional organization of the rat brain.

Characterizing and Differentiating Brain State Dynamics via Hidden Markov Models

PubMed Central

Ou, Jinli; Xie, Li; Jin, Changfeng; Li, Xiang; Zhu, Dajiang; Jiang, Rongxin; Chen, Yaowu

2014-01-01

Functional connectivity measured from resting state fMRI (R-fMRI) data has been widely used to examine the brain’s functional activities and has been recently used to characterize and differentiate brain conditions. However, the dynamical transition patterns of the brain’s functional states have been less explored. In this work, we propose a novel computational framework to quantitatively characterize the brain state dynamics via hidden Markov models (HMMs) learned from the observations of temporally dynamic functional connectomics, denoted as functional connectome states. The framework has been applied to the R-fMRI dataset including 44 post-traumatic stress disorder (PTSD) patients and 51 normal control (NC) subjects. Experimental results show that both PTSD and NC brains were undergoing remarkable changes in resting state and mainly transiting amongst a few brain states. Interestingly, further prediction with the best-matched HMM demonstrates that PTSD would enter into, but could not disengage from, a negative mood state. Importantly, 84 % of PTSD patients and 86 % of NC subjects are successfully classified via multiple HMMs using majority voting. PMID:25331991

Changes in Gray Matter Density, Regional Homogeneity, and Functional Connectivity in Methamphetamine-Associated Psychosis: A Resting-State Functional Magnetic Resonance Imaging (fMRI) Study.

PubMed

Zhang, Shengyu; Hu, Qiang; Tang, Tao; Liu, Chao; Li, Chengchong; Zang, Yin-Yin; Cai, Wei-Xiong

2018-06-13

BACKGROUND Using regional homogeneity (ReHo) blood oxygen level-dependent functional MR (BOLD-fMRI), we investigated the structural and functional alterations of brain regions among patients with methamphetamine-associated psychosis (MAP). MATERIAL AND METHODS This retrospective study included 17 MAP patients, 16 schizophrenia (SCZ) patients, and 18 healthy controls. Informed consent was obtained from all patients before the clinical assessment, the severity of clinical symptoms was evaluated prior to the fMRI scanning, and then images were acquired and preprocessed after each participant received 6-min fRMI scanning. The participants all underwent BOLD-fMRI scanning. Voxel-based morphometry was used to measure gray matter density (GMD). Resting-state fMRI (rs-fMRI) was conducted to analyze functional MR, ReHo, and functional connectivity (FC). RESULTS GMD analysis results suggest that MAP patients, SCZ patients, and healthy volunteers show different GMDs within different brain regions. Similarly, the ReHo analysis results suggest that MAP patients, SCZ patients, and healthy volunteers have different GMDs within different brain regions. Negative correlations were found between ReHo- and the PANSS-positive scores within the left orbital interior frontal gyrus (L-orb-IFG) of MAP patients. ReHo- and PANSS-negative scores of R-SFG were negatively correlated among SCZ patients. The abnormal FC of R-MFG showed a negative correlation with the PANSS score among MAP patients. CONCLUSIONS The abnormalities in brain structure and FC were associated with the development of MAP.

The development of Human Functional Brain Networks

PubMed Central

Power, Jonathan D; Fair, Damien A; Schlaggar, Bradley L

2010-01-01

Recent advances in MRI technology have enabled precise measurements of correlated activity throughout the brain, leading to the first comprehensive descriptions of functional brain networks in humans. This article reviews the growing literature on the development of functional networks, from infancy through adolescence, as measured by resting state functional connectivity MRI. We note several limitations of traditional approaches to describing brain networks, and describe a powerful framework for analyzing networks, called graph theory. We argue that characterization of the development of brain systems (e.g. the default mode network) should be comprehensive, considering not only relationships within a given system, but also how these relationships are situated within wider network contexts. We note that, despite substantial reorganization of functional connectivity, several large-scale network properties appear to be preserved across development, suggesting that functional brain networks, even in children, are organized in manners similar to other complex systems. PMID:20826306

High density event-related potential data acquisition in cognitive neuroscience.

PubMed

Slotnick, Scott D

2010-04-16

Functional magnetic resonance imaging (fMRI) is currently the standard method of evaluating brain function in the field of Cognitive Neuroscience, in part because fMRI data acquisition and analysis techniques are readily available. Because fMRI has excellent spatial resolution but poor temporal resolution, this method can only be used to identify the spatial location of brain activity associated with a given cognitive process (and reveals virtually nothing about the time course of brain activity). By contrast, event-related potential (ERP) recording, a method that is used much less frequently than fMRI, has excellent temporal resolution and thus can track rapid temporal modulations in neural activity. Unfortunately, ERPs are under utilized in Cognitive Neuroscience because data acquisition techniques are not readily available and low density ERP recording has poor spatial resolution. In an effort to foster the increased use of ERPs in Cognitive Neuroscience, the present article details key techniques involved in high density ERP data acquisition. Critically, high density ERPs offer the promise of excellent temporal resolution and good spatial resolution (or excellent spatial resolution if coupled with fMRI), which is necessary to capture the spatial-temporal dynamics of human brain function.

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.

PubMed

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.

Glucose Administration Enhances fMRI Brain Activation and Connectivity Related to Episodic Memory Encoding for Neutral and Emotional Stimuli

ERIC Educational Resources Information Center

Parent, Marise B.; Krebs-Kraft, Desiree L.; Ryan, John P.; Wilson, Jennifer S.; Harenski, Carla; Hamann, Stephan

2011-01-01

Glucose enhances memory in a variety of species. In humans, glucose administration enhances episodic memory encoding, although little is known regarding the neural mechanisms underlying these effects. Here we examined whether elevating blood glucose would enhance functional MRI (fMRI) activation and connectivity in brain regions associated with…

Education and the cognitive decline associated with MRI-defined brain infarct.

PubMed

Elkins, J S; Longstreth, W T; Manolio, T A; Newman, A B; Bhadelia, R A; Johnston, S C

2006-08-08

To assess whether educational attainment, a correlate of cognitive reserve, predicts the amount of cognitive decline associated with a new brain infarct. The Cardiovascular Health Study is a population-based, longitudinal study of people aged 65 years and older. Cognitive function was measured annually using the Modified Mini-Mental State Examination (3MS) and the Digit-Symbol Substitution Test (DSST). The authors tested whether education level modified 1) the cross-sectional association between cognitive performance and MRI-defined infarct and 2) the change in cognitive function associated with an incident infarct at a follow-up MRI. In cross-sectional analysis (n = 3,660), MRI-defined infarct was associated with a greater impact on 3MS performance in the lowest education quartile when compared with others (p for heterogeneity = 0.012). Among those with a follow-up MRI who had no infarct on initial MRI (n = 1,433), education level was not associated with the incidence, size, or location of new brain infarct. However, a new MRI-defined infarct predicted substantially greater decline in 3MS scores in the lowest education group compared with the others (6.3, 95% CI 4.4- to 8.2-point decline vs 1.7, 95% CI 0.7- to 2.7-point decline; p for heterogeneity < 0.001). Higher education was not associated with smaller declines in DSST performance in the setting of MRI-defined infarct. Education seems to modify an individual's decline on a test of general cognitive function when there is incident brain infarct. These findings are consistent with the hypothesis that cognitive reserve influences the impact of vascular injury in the brain.

A Multimodal Imaging- and Stimulation-based Method of Evaluating Connectivity-related Brain Excitability in Patients with Epilepsy

PubMed Central

Shafi, Mouhsin M.; Whitfield-Gabrieli, Susan; Chu, Catherine J.; Pascual-Leone, Alvaro; Chang, Bernard S.

2017-01-01

Resting-state functional connectivity MRI (rs-fcMRI) is a technique that identifies connectivity between different brain regions based on correlations over time in the blood-oxygenation level dependent signal. rs-fcMRI has been applied extensively to identify abnormalities in brain connectivity in different neurologic and psychiatric diseases. However, the relationship among rs-fcMRI connectivity abnormalities, brain electrophysiology and disease state is unknown, in part because the causal significance of alterations in functional connectivity in disease pathophysiology has not been established. Transcranial Magnetic Stimulation (TMS) is a technique that uses electromagnetic induction to noninvasively produce focal changes in cortical activity. When combined with electroencephalography (EEG), TMS can be used to assess the brain's response to external perturbations. Here we provide a protocol for combining rs-fcMRI, TMS and EEG to assess the physiologic significance of alterations in functional connectivity in patients with neuropsychiatric disease. We provide representative results from a previously published study in which rs-fcMRI was used to identify regions with abnormal connectivity in patients with epilepsy due to a malformation of cortical development, periventricular nodular heterotopia (PNH). Stimulation in patients with epilepsy resulted in abnormal TMS-evoked EEG activity relative to stimulation of the same sites in matched healthy control patients, with an abnormal increase in the late component of the TMS-evoked potential, consistent with cortical hyperexcitability. This abnormality was specific to regions with abnormal resting-state functional connectivity. Electrical source analysis in a subject with previously recorded seizures demonstrated that the origin of the abnormal TMS-evoked activity co-localized with the seizure-onset zone, suggesting the presence of an epileptogenic circuit. These results demonstrate how rs-fcMRI, TMS and EEG can be utilized together to identify and understand the physiological significance of abnormal brain connectivity in human diseases. PMID:27911366

Evolving knowledge of sex differences in brain structure, function, and chemistry.

PubMed

Cosgrove, Kelly P; Mazure, Carolyn M; Staley, Julie K

2007-10-15

Clinical and epidemiologic evidence demonstrates sex differences in the prevalence and course of various psychiatric disorders. Understanding sex-specific brain differences in healthy individuals is a critical first step toward understanding sex-specific expression of psychiatric disorders. Here, we evaluate evidence on sex differences in brain structure, chemistry, and function using imaging methodologies, including functional magnetic resonance imaging (fMRI), positron emission tomography (PET), single photon emission computed tomography (SPECT), and structural magnetic resonance imaging (MRI) in mentally healthy individuals. MEDLINE searches of English-language literature (1980-November 2006) using the terms sex, gender, PET, SPECT, MRI, fMRI, morphometry, neurochemistry, and neurotransmission were performed to extract relevant sources. The literature suggests that while there are many similarities in brain structure, function, and neurotransmission in healthy men and women, there are important differences that distinguish the male from the female brain. Overall, brain volume is greater in men than women; yet, when controlling for total volume, women have a higher percentage of gray matter and men a higher percentage of white matter. Regional volume differences are less consistent. Global cerebral blood flow is higher in women than in men. Sex-specific differences in dopaminergic, serotonergic, and gamma-aminobutyric acid (GABA)ergic markers indicate that male and female brains are neurochemically distinct. Insight into the etiology of sex differences in the normal living human brain provides an important foundation to delineate the pathophysiological mechanisms underlying sex differences in neuropsychiatric disorders and to guide the development of sex-specific treatments for these devastating brain disorders.

Value of Frequency Domain Resting-State Functional Magnetic Resonance Imaging Metrics Amplitude of Low-Frequency Fluctuation and Fractional Amplitude of Low-Frequency Fluctuation in the Assessment of Brain Tumor-Induced Neurovascular Uncoupling.

PubMed

Agarwal, Shruti; Lu, Hanzhang; Pillai, Jay J

2017-08-01

The aim of this study was to explore whether the phenomenon of brain tumor-related neurovascular uncoupling (NVU) in resting-state blood oxygen level-dependent functional magnetic resonance imaging (BOLD fMRI) (rsfMRI) may also affect the resting-state fMRI (rsfMRI) frequency domain metrics the amplitude of low-frequency fluctuation (ALFF) and fractional ALFF (fALFF). Twelve de novo brain tumor patients, who underwent clinical fMRI examinations, including task-based fMRI (tbfMRI) and rsfMRI, were included in this Institutional Review Board-approved study. Each patient displayed decreased/absent tbfMRI activation in the primary ipsilesional (IL) sensorimotor cortex in the absence of a corresponding motor deficit or suboptimal task performance, consistent with NVU. Z-score maps for the motor tasks were obtained from general linear model analysis (reflecting motor activation vs. rest). Seed-based correlation analysis (SCA) maps of sensorimotor network, ALFF, and fALFF were calculated from rsfMRI data. Precentral and postcentral gyri in contralesional (CL) and IL hemispheres were parcellated using an automated anatomical labeling template for each patient. Region of interest (ROI) analysis was performed on four maps: tbfMRI, SCA, ALFF, and fALFF. Voxel values in the CL and IL ROIs of each map were divided by the corresponding global mean of ALFF and fALFF in the cortical brain tissue. Group analysis revealed significantly decreased IL ALFF (p = 0.02) and fALFF (p = 0.03) metrics compared with CL ROIs, consistent with similar findings of significantly decreased IL BOLD signal for tbfMRI (p = 0.0005) and SCA maps (p = 0.0004). The frequency domain metrics ALFF and fALFF may be markers of lesion-induced NVU in rsfMRI similar to previously reported alterations in tbfMRI activation and SCA-derived resting-state functional connectivity maps.

INVESTIGATING DIFFERENCES IN BRAIN FUNCTIONAL NETWORKS USING HIERARCHICAL COVARIATE-ADJUSTED INDEPENDENT COMPONENT ANALYSIS.

PubMed

Shi, Ran; Guo, Ying

2016-12-01

Human brains perform tasks via complex functional networks consisting of separated brain regions. A popular approach to characterize brain functional networks in fMRI studies is independent component analysis (ICA), which is a powerful method to reconstruct latent source signals from their linear mixtures. In many fMRI studies, an important goal is to investigate how brain functional networks change according to specific clinical and demographic variabilities. Existing ICA methods, however, cannot directly incorporate covariate effects in ICA decomposition. Heuristic post-ICA analysis to address this need can be inaccurate and inefficient. In this paper, we propose a hierarchical covariate-adjusted ICA (hc-ICA) model that provides a formal statistical framework for estimating covariate effects and testing differences between brain functional networks. Our method provides a more reliable and powerful statistical tool for evaluating group differences in brain functional networks while appropriately controlling for potential confounding factors. We present an analytically tractable EM algorithm to obtain maximum likelihood estimates of our model. We also develop a subspace-based approximate EM that runs significantly faster while retaining high accuracy. To test the differences in functional networks, we introduce a voxel-wise approximate inference procedure which eliminates the need of computationally expensive covariance matrix estimation and inversion. We demonstrate the advantages of our methods over the existing method via simulation studies. We apply our method to an fMRI study to investigate differences in brain functional networks associated with post-traumatic stress disorder (PTSD).

Hierarchical functional modularity in the resting-state human brain.

PubMed

Ferrarini, Luca; Veer, Ilya M; Baerends, Evelinda; van Tol, Marie-José; Renken, Remco J; van der Wee, Nic J A; Veltman, Dirk J; Aleman, André; Zitman, Frans G; Penninx, Brenda W J H; van Buchem, Mark A; Reiber, Johan H C; Rombouts, Serge A R B; Milles, Julien

2009-07-01

Functional magnetic resonance imaging (fMRI) studies have shown that anatomically distinct brain regions are functionally connected during the resting state. Basic topological properties in the brain functional connectivity (BFC) map have highlighted the BFC's small-world topology. Modularity, a more advanced topological property, has been hypothesized to be evolutionary advantageous, contributing to adaptive aspects of anatomical and functional brain connectivity. However, current definitions of modularity for complex networks focus on nonoverlapping clusters, and are seriously limited by disregarding inclusive relationships. Therefore, BFC's modularity has been mainly qualitatively investigated. Here, we introduce a new definition of modularity, based on a recently improved clustering measurement, which overcomes limitations of previous definitions, and apply it to the study of BFC in resting state fMRI of 53 healthy subjects. Results show hierarchical functional modularity in the brain. Copyright 2009 Wiley-Liss, Inc

Brain Abnormalities in Congenital Fibrosis of the Extraocular Muscles Type 1: A Multimodal MRI Imaging Study

PubMed Central

Wu, Shaoqin; Lv, Bin; Wang, Zhenchang; Xian, Junfang; Sabel, Bernhard A.; He, Huiguang; Jiao, Yonghong

2015-01-01

Purpose To explore the possible brain structural and functional alterations in congenital fibrosis of extraocular muscles type 1 (CFEOM1) patients using multimodal MRI imaging. Methods T1-weighted, diffusion tensor images and functional MRI data were obtained from 9 KIF21A positive patients and 19 age- and gender- matched healthy controls. Voxel based morphometry and tract based spatial statistics were applied to the T1-weighted and diffusion tensor images, respectively. Amplitude of low frequency fluctuations and regional homogeneity were used to process the functional MRI data. We then compared these multimodal characteristics between CFEOM1 patients and healthy controls. Results Compared with healthy controls, CFEOM1 patients demonstrated increased grey matter volume in bilateral frontal orbital cortex and in the right temporal pole. No diffusion indices changes were detected, indicating unaffected white matter microstructure. In addition, from resting state functional MRI data, trend of amplitude of low-frequency fluctuations increases were noted in the right inferior parietal lobe and in the right frontal cortex, and a trend of ReHo increase (p<0.001 uncorrected) in the left precentral gyrus, left orbital frontal cortex, temporal pole and cingulate gyrus. Conclusions CFEOM1 patients had structural and functional changes in grey matter, but the white matter was unaffected. These alterations in the brain may be due to the abnormality of extraocular muscles and their innervating nerves. Future studies should consider the possible correlations between brain morphological/functional findings and clinical data, especially pertaining to eye movements, to obtain more precise answers about the role of brain area changes and their functional consequence in CFEOM1. PMID:26186732

Scanning fast and slow: current limitations of 3 Tesla functional MRI and future potential

PubMed Central

Boubela, Roland N.; Kalcher, Klaudius; Nasel, Christian; Moser, Ewald

2017-01-01

Functional MRI at 3T has become a workhorse for the neurosciences, e.g., neurology, psychology, and psychiatry, enabling non-invasive investigation of brain function and connectivity. However, BOLD-based fMRI is a rather indirect measure of brain function, confounded by physiology related signals, e.g., head or brain motion, brain pulsation, blood flow, intermixed with susceptibility differences close or distant to the region of neuronal activity. Even though a plethora of preprocessing strategies have been published to address these confounds, their efficiency is still under discussion. In particular, physiological signal fluctuations closely related to brain supply may mask BOLD signal changes related to “true” neuronal activation. Here we explore recent technical and methodological advancements aimed at disentangling the various components, employing fast multiband vs. standard EPI, in combination with fast temporal ICA. Our preliminary results indicate that fast (TR <0.5 s) scanning may help to identify and eliminate physiologic components, increasing tSNR and functional contrast. In addition, biological variability can be studied and task performance better correlated to other measures. This should increase specificity and reliability in fMRI studies. Furthermore, physiological signal changes during scanning may then be recognized as a source of information rather than a nuisance. As we are currently still undersampling the complexity of the brain, even at a rather coarse macroscopic level, we should be very cautious in the interpretation of neuroscientific findings, in particular when comparing different groups (e.g., age, sex, medication, pathology, etc.). From a technical point of view our goal should be to sample brain activity at layer specific resolution with low TR, covering as much of the brain as possible without violating SAR limits. We hope to stimulate discussion toward a better understanding and a more quantitative use of fMRI. PMID:28164083

MRI-based methods for quantification of the cerebral metabolic rate of oxygen

PubMed Central

Rodgers, Zachary B; Detre, John A

2016-01-01

The brain depends almost entirely on oxidative metabolism to meet its significant energy requirements. As such, the cerebral metabolic rate of oxygen (CMRO2) represents a key measure of brain function. Quantification of CMRO2 has helped elucidate brain functional physiology and holds potential as a clinical tool for evaluating neurological disorders including stroke, brain tumors, Alzheimer’s disease, and obstructive sleep apnea. In recent years, a variety of magnetic resonance imaging (MRI)-based CMRO2 quantification methods have emerged. Unlike positron emission tomography – the current “gold standard” for measurement and mapping of CMRO2 – MRI is non-invasive, relatively inexpensive, and ubiquitously available in modern medical centers. All MRI-based CMRO2 methods are based on modeling the effect of paramagnetic deoxyhemoglobin on the magnetic resonance signal. The various methods can be classified in terms of the MRI contrast mechanism used to quantify CMRO2: T2*, T2′, T2, or magnetic susceptibility. This review article provides an overview of MRI-based CMRO2 quantification techniques. After a brief historical discussion motivating the need for improved CMRO2 methodology, current state-of-the-art MRI-based methods are critically appraised in terms of their respective tradeoffs between spatial resolution, temporal resolution, and robustness, all of critical importance given the spatially heterogeneous and temporally dynamic nature of brain energy requirements. PMID:27089912

Structural Brain Atlases: Design, Rationale, and Applications in Normal and Pathological Cohorts

PubMed Central

Mandal, Pravat K.; Mahajan, Rashima; Dinov, Ivo D.

2015-01-01

Structural magnetic resonance imaging (MRI) provides anatomical information about the brain in healthy as well as in diseased conditions. On the other hand, functional MRI (fMRI) provides information on the brain activity during performance of a specific task. Analysis of fMRI data requires the registration of the data to a reference brain template in order to identify the activated brain regions. Brain templates also find application in other neuroimaging modalities, such as diffusion tensor imaging and multi-voxel spectroscopy. Further, there are certain differences (e.g., brain shape and size) in the brains of populations of different origin and during diseased conditions like in Alzheimer’s disease (AD), population and disease-specific brain templates may be considered crucial for accurate registration and subsequent analysis of fMRI as well as other neuroimaging data. This manuscript provides a comprehensive review of the history, construction and application of brain atlases. A chronological outline of the development of brain template design, starting from the Talairach and Tournoux atlas to the Chinese brain template (to date), along with their respective detailed construction protocols provides the backdrop to this manuscript. The manuscript also provides the automated workflow-based protocol for designing a population-specific brain atlas from structural MRI data using LONI Pipeline graphical workflow environment. We conclude by discussing the scope of brain templates as a research tool and their application in various neuroimaging modalities. PMID:22647262

Learning Computational Models of Video Memorability from fMRI Brain Imaging.

PubMed

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.

A brain stress test: Cerebral perfusion during memory encoding in mild cognitive impairment.

PubMed

Xie, Long; Dolui, Sudipto; Das, Sandhitsu R; Stockbower, Grace E; Daffner, Molly; Rao, Hengyi; Yushkevich, Paul A; Detre, John A; Wolk, David A

2016-01-01

Arterial spin labeled perfusion magnetic resonance imaging (ASL MRI) provides non-invasive quantification of cerebral blood flow, which can be used as a biomarker of brain function due to the tight coupling between cerebral blood flow (CBF) and brain metabolism. A growing body of literature suggests that regional CBF is altered in neurodegenerative diseases. Here we examined ASL MRI CBF in subjects with amnestic mild cognitive impairment (n = 65) and cognitively normal healthy controls (n = 62), both at rest and during performance of a memory-encoding task. As compared to rest, task-enhanced ASL MRI improved group discrimination, which supports the notion that physiologic measures during a cognitive challenge, or "stress test", may increase the ability to detect subtle functional changes in early disease stages. Further, logistic regression analysis demonstrated that ASL MRI and concomitantly acquired structural MRI provide complementary information of disease status. The current findings support the potential utility of task-enhanced ASL MRI as a biomarker in early Alzheimer's disease.

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

PubMed

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.

Structural connectome topology relates to regional BOLD signal dynamics in the mouse brain

NASA Astrophysics Data System (ADS)

Sethi, Sarab S.; Zerbi, Valerio; Wenderoth, Nicole; Fornito, Alex; Fulcher, Ben D.

2017-04-01

Brain dynamics are thought to unfold on a network determined by the pattern of axonal connections linking pairs of neuronal elements; the so-called connectome. Prior work has indicated that structural brain connectivity constrains pairwise correlations of brain dynamics ("functional connectivity"), but it is not known whether inter-regional axonal connectivity is related to the intrinsic dynamics of individual brain areas. Here we investigate this relationship using a weighted, directed mesoscale mouse connectome from the Allen Mouse Brain Connectivity Atlas and resting state functional MRI (rs-fMRI) time-series data measured in 184 brain regions in eighteen anesthetized mice. For each brain region, we measured degree, betweenness, and clustering coefficient from weighted and unweighted, and directed and undirected versions of the connectome. We then characterized the univariate rs-fMRI dynamics in each brain region by computing 6930 time-series properties using the time-series analysis toolbox, hctsa. After correcting for regional volume variations, strong and robust correlations between structural connectivity properties and rs-fMRI dynamics were found only when edge weights were accounted for, and were associated with variations in the autocorrelation properties of the rs-fMRI signal. The strongest relationships were found for weighted in-degree, which was positively correlated to the autocorrelation of fMRI time series at time lag τ = 34 s (partial Spearman correlation ρ = 0.58 ), as well as a range of related measures such as relative high frequency power (f > 0.4 Hz: ρ = - 0.43 ). Our results indicate that the topology of inter-regional axonal connections of the mouse brain is closely related to intrinsic, spontaneous dynamics such that regions with a greater aggregate strength of incoming projections display longer timescales of activity fluctuations.

Distinctive time-lagged resting-state networks revealed by simultaneous EEG-fMRI.

PubMed

Feige, Bernd; Spiegelhalder, Kai; Kiemen, Andrea; Bosch, Oliver G; Tebartz van Elst, Ludger; Hennig, Jürgen; Seifritz, Erich; Riemann, Dieter

2017-01-15

Functional activation as evidenced by blood oxygen level-dependent (BOLD) functional MRI changes or event-related EEG is known to closely follow patterns of stimulation or self-paced action. Any lags are compatible with axonal conduction velocities and neural integration times. The important analysis of resting state networks is generally based on the assumption that these principles also hold for spontaneous fluctuations in brain activity. Previous observations using simultaneous EEG and fMRI indicate that slower processes, with delays in the seconds range, determine at least part of the relationship between spontaneous EEG and fMRI. To assess this relationship systematically, we used deconvolution analysis of EEG-fMRI during the resting state, assessing the relationship between EEG frequency bands and fMRI BOLD across the whole brain while allowing for time lags of up to 10.5s. Cluster analysis, identifying similar BOLD time courses in relation to EEG band power peaks, showed a clear segregation of functional subsystems of the brain. Our analysis shows that fMRI BOLD increases commonly precede EEG power increases by seconds. Most zero-lag correlations, on the other hand, were negative. This indicates two main distinct neuromodulatory mechanisms: an "idling" mechanism of simultaneous electric and metabolic network anticorrelation and a "regulatory" mechanism in which metabolic network activity precedes increased EEG power by some seconds. This has to be taken into consideration in further studies which address the causal and functional relationship of metabolic and electric brain activity patterns. Copyright © 2016 Elsevier Inc. All rights reserved.

Tracking the development of brain connectivity in adolescence through a fast Bayesian integrative method

NASA Astrophysics Data System (ADS)

Zhang, Aiying; Jia, Bochao; Wang, Yu-Ping

2018-03-01

Adolescence is a transitional period between childhood and adulthood with physical changes, as well as increasing emotional activity. Studies have shown that the emotional sensitivity is related to a second dramatical brain growth. However, there is little focus on the trend of brain development during this period. In this paper, we aim to track the functional brain connectivity development in adolescence using resting state fMRI (rs-fMRI), which amounts to a time-series analysis problem. Most existing methods either require the time point to be fairly long or are only applicable to small graphs. To this end, we adapted a fast Bayesian integrative analysis (FBIA) to address the short time-series difficulty, and combined with adaptive sum of powered score (aSPU) test for group difference. The data we used are the resting state fMRI (rs-fMRI) obtained from the publicly available Philadelphia Neurodevelopmental Cohort (PNC). They include 861 individuals aged 8-22 years who were divided into five different adolescent stages. We summarized the networks with global measurements: segregation and integration, and provided full brain functional connectivity pattern in various stages of adolescence. Moreover, our research revealed several brain functional modules development trends. Our results are shown to be both statistically and biologically significant.

Determination of Vascular Dementia Brain in Distinct Frequency Bands with Whole Brain Functional Connectivity Patterns

PubMed Central

Zhang, Delong; Liu, Bo; Chen, Jun; Peng, Xiaoling; Liu, Xian; Fan, Yuanyuan; Liu, Ming; Huang, Ruiwang

2013-01-01

Recent studies have shown that multivariate pattern analysis (MVPA) can be useful for distinguishing brain disorders into categories. Such analyses can substantially enrich and facilitate clinical diagnoses. Using MPVA methods, whole brain functional networks, especially those derived using different frequency windows, can be applied to detect brain states. We constructed whole brain functional networks for groups of vascular dementia (VaD) patients and controls using resting state BOLD-fMRI (rsfMRI) data from three frequency bands - slow-5 (0.01∼0.027 Hz), slow-4 (0.027∼0.073 Hz), and whole-band (0.01∼0.073 Hz). Then we used the support vector machine (SVM), a type of MVPA classifier, to determine the patterns of functional connectivity. Our results showed that the brain functional networks derived from rsfMRI data (19 VaD patients and 20 controls) in these three frequency bands appear to reflect neurobiological changes in VaD patients. Such differences could be used to differentiate the brain states of VaD patients from those of healthy individuals. We also found that the functional connectivity patterns of the human brain in the three frequency bands differed, as did their ability to differentiate brain states. Specifically, the ability of the functional connectivity pattern to differentiate VaD brains from healthy ones was more efficient in the slow-5 (0.01∼0.027 Hz) band than in the other two frequency bands. Our findings suggest that the MVPA approach could be used to detect abnormalities in the functional connectivity of VaD patients in distinct frequency bands. Identifying such abnormalities may contribute to our understanding of the pathogenesis of VaD. PMID:23359801

Neurofeedback with fMRI: A critical systematic review.

PubMed

Thibault, Robert T; MacPherson, Amanda; Lifshitz, Michael; Roth, Raquel R; Raz, Amir

2018-05-15

Neurofeedback relying on functional magnetic resonance imaging (fMRI-nf) heralds new prospects for self-regulating brain and behavior. Here we provide the first comprehensive review of the fMRI-nf literature and the first systematic database of fMRI-nf findings. We synthesize information from 99 fMRI-nf experiments-the bulk of currently available data. The vast majority of fMRI-nf findings suggest that self-regulation of specific brain signatures seems viable; however, replication of concomitant behavioral outcomes remains sparse. To disentangle placebo influences and establish the specific effects of neurofeedback, we highlight the need for double-blind placebo-controlled studies alongside rigorous and standardized statistical analyses. Before fMRI-nf can join the clinical armamentarium, research must first confirm the sustainability, transferability, and feasibility of fMRI-nf in patients as well as in healthy individuals. Whereas modulating specific brain activity promises to mold cognition, emotion, thought, and action, reducing complex mental health issues to circumscribed brain regions may represent a tenuous goal. We can certainly change brain activity with fMRI-nf. However, it remains unclear whether such changes translate into meaningful behavioral improvements in the clinical domain. Copyright © 2017 Elsevier Inc. All rights reserved.

Altered functional connectivity in early Alzheimer's disease: a resting-state fMRI study.

PubMed

Wang, Kun; Liang, Meng; Wang, Liang; Tian, Lixia; Zhang, Xinqing; Li, Kuncheng; Jiang, Tianzi

2007-10-01

Previous studies have led to the proposal that patients with Alzheimer's disease (AD) may have disturbed functional connectivity between different brain regions. Furthermore, recent resting-state functional magnetic resonance imaging (fMRI) studies have also shown that low-frequency (<0.08 Hz) fluctuations (LFF) of the blood oxygenation level-dependent signals were abnormal in several brain areas of AD patients. However, few studies have investigated disturbed LFF connectivity in AD patients. By using resting-state fMRI, this study sought to investigate the abnormal functional connectivities throughout the entire brain of early AD patients, and analyze the global distribution of these abnormalities. For this purpose, the authors divided the whole brain into 116 regions and identified abnormal connectivities by comparing the correlation coefficients of each pair. Compared with healthy controls, AD patients had decreased positive correlations between the prefrontal and parietal lobes, but increased positive correlations within the prefrontal lobe, parietal lobe, and occipital lobe. The AD patients also had decreased negative correlations (closer to zero) between two intrinsically anti-correlated networks that had previously been found in the resting brain. By using resting-state fMRI, our results supported previous studies that have reported an anterior-posterior disconnection phenomenon and increased within-lobe functional connectivity in AD patients. In addition, the results also suggest that AD may disturb the correlation/anti-correlation effect in the two intrinsically anti-correlated networks. Wiley-Liss, Inc.

Neurophysiological Basis of Multi-Scale Entropy of Brain Complexity and Its Relationship With Functional Connectivity.

PubMed

Wang, Danny J J; Jann, Kay; Fan, Chang; Qiao, Yang; Zang, Yu-Feng; Lu, Hanbing; Yang, Yihong

2018-01-01

Recently, non-linear statistical measures such as multi-scale entropy (MSE) have been introduced as indices of the complexity of electrophysiology and fMRI time-series across multiple time scales. In this work, we investigated the neurophysiological underpinnings of complexity (MSE) of electrophysiology and fMRI signals and their relations to functional connectivity (FC). MSE and FC analyses were performed on simulated data using neural mass model based brain network model with the Brain Dynamics Toolbox, on animal models with concurrent recording of fMRI and electrophysiology in conjunction with pharmacological manipulations, and on resting-state fMRI data from the Human Connectome Project. Our results show that the complexity of regional electrophysiology and fMRI signals is positively correlated with network FC. The associations between MSE and FC are dependent on the temporal scales or frequencies, with higher associations between MSE and FC at lower temporal frequencies. Our results from theoretical modeling, animal experiment and human fMRI indicate that (1) Regional neural complexity and network FC may be two related aspects of brain's information processing: the more complex regional neural activity, the higher FC this region has with other brain regions; (2) MSE at high and low frequencies may represent local and distributed information processing across brain regions. Based on literature and our data, we propose that the complexity of regional neural signals may serve as an index of the brain's capacity of information processing-increased complexity may indicate greater transition or exploration between different states of brain networks, thereby a greater propensity for information processing.

Cardiac index is associated with brain aging: the Framingham Heart Study.

PubMed

Jefferson, Angela L; Himali, Jayandra J; Beiser, Alexa S; Au, Rhoda; Massaro, Joseph M; Seshadri, Sudha; Gona, Philimon; Salton, Carol J; DeCarli, Charles; O'Donnell, Christopher J; Benjamin, Emelia J; Wolf, Philip A; Manning, Warren J

2010-08-17

Cardiac dysfunction is associated with neuroanatomic and neuropsychological changes in aging adults with prevalent cardiovascular disease, theoretically because systemic hypoperfusion disrupts cerebral perfusion, contributing to subclinical brain injury. We hypothesized that cardiac function, as measured by cardiac index, would be associated with preclinical brain magnetic resonance imaging (MRI) and neuropsychological markers of ischemia and Alzheimer disease in the community. Brain MRI, cardiac MRI, neuropsychological, and laboratory data were collected on 1504 Framingham Offspring Cohort participants free of clinical stroke, transient ischemic attack, or dementia (age, 61+/-9 years; 54% women). Neuropsychological and brain MRI variables were related to cardiac MRI-assessed cardiac index (cardiac output/body surface area). In multivariable-adjusted models, cardiac index was positively related to total brain volume (P=0.03) and information processing speed (P=0.02) and inversely related to lateral ventricular volume (P=0.048). When participants with clinically prevalent cardiovascular disease were excluded, the relation between cardiac index and total brain volume remained (P=0.02). Post hoc comparisons revealed that participants in the bottom cardiac index tertile (values <2.54) and middle cardiac index tertile (values between 2.54 and 2.92) had significantly lower brain volumes (P=0.04) than participants in the top cardiac index tertile (values >2.92). Although observational data cannot establish causality, our findings are consistent with the hypothesis that decreasing cardiac function, even at normal cardiac index levels, is associated with accelerated brain aging.

Cardiac index is associated with brain aging: The Framingham Heart Study

PubMed Central

Jefferson, Angela L.; Himali, Jayandra J.; Beiser, Alexa S.; Au, Rhoda; Massaro, Joseph M.; Seshadri, Sudha; Gona, Philimon; Salton, Carol J.; DeCarli, Charles; O’Donnell, Christopher J.; Benjamin, Emelia J.; Wolf, Philip A.; Manning, Warren J.

2010-01-01

Background Cardiac dysfunction is associated with neuroanatomic and neuropsychological changes in aging adults with prevalent cardiovascular disease (CVD), theoretically because systemic hypoperfusion disrupts cerebral perfusion, contributing to subclinical brain injury. We hypothesized that cardiac function, as measured by cardiac index, would be associated with pre-clinical brain magnetic resonance imaging (MRI) and neuropsychological markers of ischemia and Alzheimer’s disease in the community. Methods and Results Brain MRI, cardiac MRI, neuropsychological, and laboratory data were collected on 1504 Framingham Offspring Cohort participants free from clinical stroke, transient ischemic attack, or dementia (61±9 years; 54% women). Neuropsychological and brain MRI variables were related to cardiac MRI-assessed cardiac index (cardiac output/body surface area). In multivariable-adjusted models, cardiac index was positively related to total brain volume (P=0.03) and information processing speed (P=0.02) and inversely related to lateral ventricular volume (P=0.048). When participants with clinically prevalent CVD were excluded, the relation between cardiac index and total brain volume remained (P=0.02). Post-hoc comparisons revealed that participants in the bottom cardiac index tertile (values<2.54) and middle cardiac index tertile (values between 2.54 and 2.92) had significantly lower brain volumes (P=0.04) than participants in the top cardiac index tertile (values>2.92). Conclusions Although observational data cannot establish causality, our findings are consistent with the hypothesis that decreasing cardiac function, even at normal cardiac index levels, is associated with accelerated brain aging. PMID:20679552

Lack of sex effect on brain activity during a visuomotor response task: functional MR imaging study.

PubMed

Mikhelashvili-Browner, Nina; Yousem, David M; Wu, Colin; Kraut, Michael A; Vaughan, Christina L; Oguz, Kader Karli; Calhoun, Vince D

2003-03-01

As more individuals are enrolled in clinical functional MR imaging (fMRI) studies, an understanding of how sex may influence fMRI-measured brain activation is critical. We used fixed- and random-effects models to study the influence of sex on fMRI patterns of brain activation during a simple visuomotor reaction time task in the group of 26 age-matched men and women. We evaluated the right visual, left visual, left primary motor, left supplementary motor, and left anterior cingulate areas. Volumes of activations did not significantly differ between the groups in any defined regions. Analysis of variance failed to show any significant correlations between sex and volumes of brain activation in any location studied. Mean percentage signal-intensity changes for all locations were similar between men and women. A two-way t test of brain activation in men and women, performed as a part of random-effects modeling, showed no significant difference at any site. Our results suggest that sex seems to have little influence on fMRI brain activation when we compared performance on the simple reaction-time task. The need to control for sex effects is not critical in the analysis of this task with fMRI.

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

PubMed

Makary, Meena M; Seulgi, Eun; Kyungmo Park

2017-07-01

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

Uses, misuses, new uses and fundamental limitations of magnetic resonance imaging in cognitive science

PubMed Central

2016-01-01

When blood oxygenation level-dependent (BOLD) contrast functional magnetic resonance imaging (fMRI) was discovered in the early 1990s, it provoked an explosion of interest in exploring human cognition, using brain mapping techniques based on MRI. Standards for data acquisition and analysis were rapidly put in place, in order to assist comparison of results across laboratories. Recently, MRI data acquisition capabilities have improved dramatically, inviting a rethink of strategies for relating functional brain activity at the systems level with its neuronal substrates and functional connections. This paper reviews the established capabilities of BOLD contrast fMRI, the perceived weaknesses of major methods of analysis, and current results that may provide insights into improved brain modelling. These results have inspired the use of in vivo myeloarchitecture for localizing brain activity, individual subject analysis without spatial smoothing and mapping of changes in cerebral blood volume instead of BOLD activation changes. The apparent fundamental limitations of all methods based on nuclear magnetic resonance are also discussed. This article is part of the themed issue ‘Interpreting BOLD: a dialogue between cognitive and cellular neuroscience’. PMID:27574303

Brain-heart interactions: challenges and opportunities with functional magnetic resonance imaging at ultra-high field.

PubMed

Chang, Catie; Raven, Erika P; Duyn, Jeff H

2016-05-13

Magnetic resonance imaging (MRI) at ultra-high field (UHF) strengths (7 T and above) offers unique opportunities for studying the human brain with increased spatial resolution, contrast and sensitivity. However, its reliability can be compromised by factors such as head motion, image distortion and non-neural fluctuations of the functional MRI signal. The objective of this review is to provide a critical discussion of the advantages and trade-offs associated with UHF imaging, focusing on the application to studying brain-heart interactions. We describe how UHF MRI may provide contrast and resolution benefits for measuring neural activity of regions involved in the control and mediation of autonomic processes, and in delineating such regions based on anatomical MRI contrast. Limitations arising from confounding signals are discussed, including challenges with distinguishing non-neural physiological effects from the neural signals of interest that reflect cardiorespiratory function. We also consider how recently developed data analysis techniques may be applied to high-field imaging data to uncover novel information about brain-heart interactions. © 2016 The Author(s).

Uses, misuses, new uses and fundamental limitations of magnetic resonance imaging in cognitive science.

PubMed

Turner, Robert

2016-10-05

When blood oxygenation level-dependent (BOLD) contrast functional magnetic resonance imaging (fMRI) was discovered in the early 1990s, it provoked an explosion of interest in exploring human cognition, using brain mapping techniques based on MRI. Standards for data acquisition and analysis were rapidly put in place, in order to assist comparison of results across laboratories. Recently, MRI data acquisition capabilities have improved dramatically, inviting a rethink of strategies for relating functional brain activity at the systems level with its neuronal substrates and functional connections. This paper reviews the established capabilities of BOLD contrast fMRI, the perceived weaknesses of major methods of analysis, and current results that may provide insights into improved brain modelling. These results have inspired the use of in vivo myeloarchitecture for localizing brain activity, individual subject analysis without spatial smoothing and mapping of changes in cerebral blood volume instead of BOLD activation changes. The apparent fundamental limitations of all methods based on nuclear magnetic resonance are also discussed.This article is part of the themed issue 'Interpreting BOLD: a dialogue between cognitive and cellular neuroscience'. © 2016 The Authors.

Increased resting-state brain entropy in Alzheimer's disease.

PubMed

Xue, Shao-Wei; Guo, Yonghu

2018-03-07

Entropy analysis of resting-state functional MRI (R-fMRI) is a novel approach to characterize brain temporal dynamics and facilitates the identification of abnormal brain activity caused by several disease conditions. However, Alzheimer's disease (AD)-related brain entropy mapping based on R-fMRI has not been assessed. Here, we measured the sample entropy and voxel-wise connectivity of the network degree centrality (DC) of the intrinsic brain activity acquired by R-fMRI in 26 patients with AD and 26 healthy controls. Compared with the controls, AD patients showed increased entropy in the middle temporal gyrus and the precentral gyrus and also showed decreased DC in the precuneus. Moreover, the magnitude of the negative correlation between local brain activity (entropy) and network connectivity (DC) was increased in AD patients in comparison with healthy controls. These findings provide new evidence on AD-related brain entropy alterations.

The effects of physical activity on functional MRI activation associated with cognitive control in children: a randomized controlled intervention

PubMed Central

Chaddock-Heyman, Laura; Erickson, Kirk I.; Voss, Michelle W.; Knecht, Anya M.; Pontifex, Matthew B.; Castelli, Darla M.; Hillman, Charles H.; Kramer, Arthur F.

2013-01-01

This study used functional magnetic resonance imaging (fMRI) to examine the influence of a 9-month physical activity program on task-evoked brain activation during childhood. The results demonstrated that 8- to 9-year-old children who participated in 60+ min of physical activity, 5 days per week, for 9 months, showed decreases in fMRI brain activation in the right anterior prefrontal cortex coupled with within-group improvements in performance on a task of attentional and interference control. Children assigned to a wait-list control group did not show changes in brain function. Furthermore, at post-test, children in the physical activity group showed similar anterior frontal brain patterns and incongruent accuracy rates to a group of college-aged young adults. Children in the wait-list control group still differed from the young adults in terms of anterior prefrontal activation and performance at post-test. There were no significant changes in fMRI activation in the anterior cingulate cortex (ACC) for either group. These results suggest that physical activity during childhood may enhance specific elements of prefrontal cortex function involved in cognitive control. PMID:23487583

Studies in nonlinear optics and functional magnetic resonance imaging

NASA Astrophysics Data System (ADS)

Dai, Tehui

There are two parts in this thesis. The first part will involve a study in the anomalous dispersion phase matched second-harmonic generation, and the second part will be a study in functional magnetic resonance imaging (fMRI) and a biophysical model of the human muscle. In part I, we report on a series of tricyanovinylaniline chromophores for use as dopants in poled poly(methyl methacrylate) waveguides for anomalous-dispersion phase- matched second-harmonic generation. Second-harmonic generation measurements as a function of mode index confirmed anomalous dispersion phase-matching efficiencies as large as 245%/Wcm2 over a propagation length of ~35 μm. The waveguide coupling technique limited the interaction length. The photostability of the chromophores was measured directly and found to agree qualitatively with second-harmonic measurements over time and was found to be improved over previously reported materials. In part II, we designed a system that could record joint force and surface electromyography (EMG) simultaneously with fMRI data. I-Egh quality force and EMG data were obtained at the same time that excellent fMRI brain images were achieved. Using this system we determined the relationship between the fMRI-measured brain activation and the handgrip force, and between the fMRI-measured brain activation and the EMG of finger flexor muscles. We found that in the whole brain and in the majority of motor function-related cortical fields, the degree of muscle activation is directly proportional to the amplitude of the brain signal determined by the fMRI measurement. The similarity in the relationship between muscle output and fMRI signal in a number of brain areas suggests that multiple cortical fields are involved in controlling muscle force. The factors that may contribute to the fMRI signals are discussed. A biophysical twitch force model was developed to predict force response under electrical stimulation. Comparison between experimental and modeled force profiles, peak forces, and force duration shows excellent agreement between the model and the experimental data. It is concluded that the present model allows us to reproduce the main features of muscle activation under stimulation.

Co-activation patterns in resting-state fMRI signals.

PubMed

Liu, Xiao; Zhang, Nanyin; Chang, Catie; Duyn, Jeff H

2018-02-08

The brain is a complex system that integrates and processes information across multiple time scales by dynamically coordinating activities over brain regions and circuits. Correlations in resting-state functional magnetic resonance imaging (rsfMRI) signals have been widely used to infer functional connectivity of the brain, providing a metric of functional associations that reflects a temporal average over an entire scan (typically several minutes or longer). Not until recently was the study of dynamic brain interactions at much shorter time scales (seconds to minutes) considered for inference of functional connectivity. One method proposed for this objective seeks to identify and extract recurring co-activation patterns (CAPs) that represent instantaneous brain configurations at single time points. Here, we review the development and recent advancement of CAP methodology and other closely related approaches, as well as their applications and associated findings. We also discuss the potential neural origins and behavioral relevance of CAPs, along with methodological issues and future research directions in the analysis of fMRI co-activation patterns. Copyright © 2018 Elsevier Inc. All rights reserved.

Prediction of brain maturity in infants using machine-learning algorithms.

PubMed

Smyser, Christopher D; Dosenbach, Nico U F; Smyser, Tara A; Snyder, Abraham Z; Rogers, Cynthia E; Inder, Terrie E; Schlaggar, Bradley L; Neil, Jeffrey J

2016-08-01

Recent resting-state functional MRI investigations have demonstrated that much of the large-scale functional network architecture supporting motor, sensory and cognitive functions in older pediatric and adult populations is present in term- and prematurely-born infants. Application of new analytical approaches can help translate the improved understanding of early functional connectivity provided through these studies into predictive models of neurodevelopmental outcome. One approach to achieving this goal is multivariate pattern analysis, a machine-learning, pattern classification approach well-suited for high-dimensional neuroimaging data. It has previously been adapted to predict brain maturity in children and adolescents using structural and resting state-functional MRI data. In this study, we evaluated resting state-functional MRI data from 50 preterm-born infants (born at 23-29weeks of gestation and without moderate-severe brain injury) scanned at term equivalent postmenstrual age compared with data from 50 term-born control infants studied within the first week of life. Using 214 regions of interest, binary support vector machines distinguished term from preterm infants with 84% accuracy (p<0.0001). Inter- and intra-hemispheric connections throughout the brain were important for group categorization, indicating that widespread changes in the brain's functional network architecture associated with preterm birth are detectable by term equivalent age. Support vector regression enabled quantitative estimation of birth gestational age in single subjects using only term equivalent resting state-functional MRI data, indicating that the present approach is sensitive to the degree of disruption of brain development associated with preterm birth (using gestational age as a surrogate for the extent of disruption). This suggests that support vector regression may provide a means for predicting neurodevelopmental outcome in individual infants. Copyright © 2016 Elsevier Inc. All rights reserved.

Prediction of brain maturity in infants using machine-learning algorithms

PubMed Central

Smyser, Christopher D.; Dosenbach, Nico U.F.; Smyser, Tara A.; Snyder, Abraham Z.; Rogers, Cynthia E.; Inder, Terrie E.; Schlaggar, Bradley L.; Neil, Jeffrey J.

2016-01-01

Recent resting-state functional MRI investigations have demonstrated that much of the large-scale functional network architecture supporting motor, sensory and cognitive functions in older pediatric and adult populations is present in term- and prematurely-born infants. Application of new analytical approaches can help translate the improved understanding of early functional connectivity provided through these studies into predictive models of neurodevelopmental outcome. One approach to achieving this goal is multivariate pattern analysis, a machine-learning, pattern classification approach well-suited for high-dimensional neuroimaging data. It has previously been adapted to predict brain maturity in children and adolescents using structural and resting state-functional MRI data. In this study, we evaluated resting state-functional MRI data from 50 preterm-born infants (born at 23–29 weeks of gestation and without moderate–severe brain injury) scanned at term equivalent postmenstrual age compared with data from 50 term-born control infants studied within the first week of life. Using 214 regions of interest, binary support vector machines distinguished term from preterm infants with 84% accuracy (p < 0.0001). Inter- and intra-hemispheric connections throughout the brain were important for group categorization, indicating that widespread changes in the brain's functional network architecture associated with preterm birth are detectable by term equivalent age. Support vector regression enabled quantitative estimation of birth gestational age in single subjects using only term equivalent resting state-functional MRI data, indicating that the present approach is sensitive to the degree of disruption of brain development associated with preterm birth (using gestational age as a surrogate for the extent of disruption). This suggests that support vector regression may provide a means for predicting neurodevelopmental outcome in individual infants. PMID:27179605

Brain Genomics Superstruct Project initial data release with structural, functional, and behavioral measures

PubMed Central

Holmes, Avram J.; Hollinshead, Marisa O.; O’Keefe, Timothy M.; Petrov, Victor I.; Fariello, Gabriele R.; Wald, Lawrence L.; Fischl, Bruce; Rosen, Bruce R.; Mair, Ross W.; Roffman, Joshua L.; Smoller, Jordan W.; Buckner, Randy L.

2015-01-01

The goal of the Brain Genomics Superstruct Project (GSP) is to enable large-scale exploration of the links between brain function, behavior, and ultimately genetic variation. To provide the broader scientific community data to probe these associations, a repository of structural and functional magnetic resonance imaging (MRI) scans linked to genetic information was constructed from a sample of healthy individuals. The initial release, detailed in the present manuscript, encompasses quality screened cross-sectional data from 1,570 participants ages 18 to 35 years who were scanned with MRI and completed demographic and health questionnaires. Personality and cognitive measures were obtained on a subset of participants. Each dataset contains a T1-weighted structural MRI scan and either one (n=1,570) or two (n=1,139) resting state functional MRI scans. Test-retest reliability datasets are included from 69 participants scanned within six months of their initial visit. For the majority of participants self-report behavioral and cognitive measures are included (n=926 and n=892 respectively). Analyses of data quality, structure, function, personality, and cognition are presented to demonstrate the dataset’s utility. PMID:26175908

Brain Genomics Superstruct Project initial data release with structural, functional, and behavioral measures.

PubMed

Holmes, Avram J; Hollinshead, Marisa O; O'Keefe, Timothy M; Petrov, Victor I; Fariello, Gabriele R; Wald, Lawrence L; Fischl, Bruce; Rosen, Bruce R; Mair, Ross W; Roffman, Joshua L; Smoller, Jordan W; Buckner, Randy L

2015-01-01

The goal of the Brain Genomics Superstruct Project (GSP) is to enable large-scale exploration of the links between brain function, behavior, and ultimately genetic variation. To provide the broader scientific community data to probe these associations, a repository of structural and functional magnetic resonance imaging (MRI) scans linked to genetic information was constructed from a sample of healthy individuals. The initial release, detailed in the present manuscript, encompasses quality screened cross-sectional data from 1,570 participants ages 18 to 35 years who were scanned with MRI and completed demographic and health questionnaires. Personality and cognitive measures were obtained on a subset of participants. Each dataset contains a T1-weighted structural MRI scan and either one (n=1,570) or two (n=1,139) resting state functional MRI scans. Test-retest reliability datasets are included from 69 participants scanned within six months of their initial visit. For the majority of participants self-report behavioral and cognitive measures are included (n=926 and n=892 respectively). Analyses of data quality, structure, function, personality, and cognition are presented to demonstrate the dataset's utility.

fMRI Brain-Computer Interface: A Tool for Neuroscientific Research and Treatment

PubMed Central

Sitaram, Ranganatha; Caria, Andrea; Veit, Ralf; Gaber, Tilman; Rota, Giuseppina; Kuebler, Andrea; Birbaumer, Niels

2007-01-01

Brain-computer interfaces based on functional magnetic resonance imaging (fMRI-BCI) allow volitional control of anatomically specific regions of the brain. Technological advancement in higher field MRI scanners, fast data acquisition sequences, preprocessing algorithms, and robust statistical analysis are anticipated to make fMRI-BCI more widely available and applicable. This noninvasive technique could potentially complement the traditional neuroscientific experimental methods by varying the activity of the neural substrates of a region of interest as an independent variable to study its effects on behavior. If the neurobiological basis of a disorder (e.g., chronic pain, motor diseases, psychopathy, social phobia, depression) is known in terms of abnormal activity in certain regions of the brain, fMRI-BCI can be targeted to modify activity in those regions with high specificity for treatment. In this paper, we review recent results of the application of fMRI-BCI to neuroscientific research and psychophysiological treatment. PMID:18274615

Spinal Cord Injury Disrupts Resting-State Networks in the Human Brain.

PubMed

Hawasli, Ammar H; Rutlin, Jerrel; Roland, Jarod L; Murphy, Rory K J; Song, Sheng-Kwei; Leuthardt, Eric C; Shimony, Joshua S; Ray, Wilson Z

2018-03-15

Despite 253,000 spinal cord injury (SCI) patients in the United States, little is known about how SCI affects brain networks. Spinal MRI provides only structural information with no insight into functional connectivity. Resting-state functional MRI (RS-fMRI) quantifies network connectivity through the identification of resting-state networks (RSNs) and allows detection of functionally relevant changes during disease. Given the robust network of spinal cord afferents to the brain, we hypothesized that SCI produces meaningful changes in brain RSNs. RS-fMRIs and functional assessments were performed on 10 SCI subjects. Blood oxygen-dependent RS-fMRI sequences were acquired. Seed-based correlation mapping was performed using five RSNs: default-mode (DMN), dorsal-attention (DAN), salience (SAL), control (CON), and somatomotor (SMN). RSNs were compared with normal control subjects using false-discovery rate-corrected two way t tests. SCI reduced brain network connectivity within the SAL, SMN, and DMN and disrupted anti-correlated connectivity between CON and SMN. When divided into separate cohorts, complete but not incomplete SCI disrupted connectivity within SAL, DAN, SMN and DMN and between CON and SMN. Finally, connectivity changed over time after SCI: the primary motor cortex decreased connectivity with the primary somatosensory cortex, the visual cortex decreased connectivity with the primary motor cortex, and the visual cortex decreased connectivity with the sensory parietal cortex. These unique findings demonstrate the functional network plasticity that occurs in the brain as a result of injury to the spinal cord. Connectivity changes after SCI may serve as biomarkers to predict functional recovery following an SCI and guide future therapy.

Error-related processing following severe traumatic brain injury: An event-related functional magnetic resonance imaging (fMRI) study

PubMed Central

Sozda, Christopher N.; Larson, Michael J.; Kaufman, David A.S.; Schmalfuss, Ilona M.; Perlstein, William M.

2011-01-01

Continuous monitoring of one’s performance is invaluable for guiding behavior towards successful goal attainment by identifying deficits and strategically adjusting responses when performance is inadequate. In the present study, we exploited the advantages of event-related functional magnetic resonance imaging (fMRI) to examine brain activity associated with error-related processing after severe traumatic brain injury (sTBI). fMRI and behavioral data were acquired while 10 sTBI participants and 12 neurologically-healthy controls performed a task-switching cued-Stroop task. fMRI data were analyzed using a random-effects whole-brain voxel-wise general linear model and planned linear contrasts. Behaviorally, sTBI patients showed greater error-rate interference than neurologically-normal controls. fMRI data revealed that, compared to controls, sTBI patients showed greater magnitude error-related activation in the anterior cingulate cortex (ACC) and an increase in the overall spatial extent of error-related activation across cortical and subcortical regions. Implications for future research and potential limitations in conducting fMRI research in neurologically-impaired populations are discussed, as well as some potential benefits of employing multimodal imaging (e.g., fMRI and event-related potentials) of cognitive control processes in TBI. PMID:21756946

Error-related processing following severe traumatic brain injury: an event-related functional magnetic resonance imaging (fMRI) study.

PubMed

Sozda, Christopher N; Larson, Michael J; Kaufman, David A S; Schmalfuss, Ilona M; Perlstein, William M

2011-10-01

Continuous monitoring of one's performance is invaluable for guiding behavior towards successful goal attainment by identifying deficits and strategically adjusting responses when performance is inadequate. In the present study, we exploited the advantages of event-related functional magnetic resonance imaging (fMRI) to examine brain activity associated with error-related processing after severe traumatic brain injury (sTBI). fMRI and behavioral data were acquired while 10 sTBI participants and 12 neurologically-healthy controls performed a task-switching cued-Stroop task. fMRI data were analyzed using a random-effects whole-brain voxel-wise general linear model and planned linear contrasts. Behaviorally, sTBI patients showed greater error-rate interference than neurologically-normal controls. fMRI data revealed that, compared to controls, sTBI patients showed greater magnitude error-related activation in the anterior cingulate cortex (ACC) and an increase in the overall spatial extent of error-related activation across cortical and subcortical regions. Implications for future research and potential limitations in conducting fMRI research in neurologically-impaired populations are discussed, as well as some potential benefits of employing multimodal imaging (e.g., fMRI and event-related potentials) of cognitive control processes in TBI. Copyright © 2011 Elsevier B.V. All rights reserved.

Tracing Activity Across the Whole Brain Neural Network with Optogenetic Functional Magnetic Resonance Imaging

PubMed Central

Lee, Jin Hyung

2011-01-01

Despite the overwhelming need, there has been a relatively large gap in our ability to trace network level activity across the brain. The complex dense wiring of the brain makes it extremely challenging to understand cell-type specific activity and their communication beyond a few synapses. Recent development of the optogenetic functional magnetic resonance imaging (ofMRI) provides a new impetus for the study of brain circuits by enabling causal tracing of activities arising from defined cell types and firing patterns across the whole brain. Brain circuit elements can be selectively triggered based on their genetic identity, cell body location, and/or their axonal projection target with temporal precision while the resulting network response is monitored non-invasively with unprecedented spatial and temporal accuracy. With further studies including technological innovations to bring ofMRI to its full potential, ofMRI is expected to play an important role in our system-level understanding of the brain circuit mechanism. PMID:22046160

The physics of functional magnetic resonance imaging (fMRI)

NASA Astrophysics Data System (ADS)

Buxton, Richard B.

2013-09-01

Functional magnetic resonance imaging (fMRI) is a methodology for detecting dynamic patterns of activity in the working human brain. Although the initial discoveries that led to fMRI are only about 20 years old, this new field has revolutionized the study of brain function. The ability to detect changes in brain activity has a biophysical basis in the magnetic properties of deoxyhemoglobin, and a physiological basis in the way blood flow increases more than oxygen metabolism when local neural activity increases. These effects translate to a subtle increase in the local magnetic resonance signal, the blood oxygenation level dependent (BOLD) effect, when neural activity increases. With current techniques, this pattern of activation can be measured with resolution approaching 1 mm3 spatially and 1 s temporally. This review focuses on the physical basis of the BOLD effect, the imaging methods used to measure it, the possible origins of the physiological effects that produce a mismatch of blood flow and oxygen metabolism during neural activation, and the mathematical models that have been developed to understand the measured signals. An overarching theme is the growing field of quantitative fMRI, in which other MRI methods are combined with BOLD methods and analyzed within a theoretical modeling framework to derive quantitative estimates of oxygen metabolism and other physiological variables. That goal is the current challenge for fMRI: to move fMRI from a mapping tool to a quantitative probe of brain physiology.

The physics of functional magnetic resonance imaging (fMRI)

PubMed Central

Buxton, Richard B

2015-01-01

Functional magnetic resonance imaging (fMRI) is a methodology for detecting dynamic patterns of activity in the working human brain. Although the initial discoveries that led to fMRI are only about 20 years old, this new field has revolutionized the study of brain function. The ability to detect changes in brain activity has a biophysical basis in the magnetic properties of deoxyhemoglobin, and a physiological basis in the way blood flow increases more than oxygen metabolism when local neural activity increases. These effects translate to a subtle increase in the local magnetic resonance signal, the blood oxygenation level dependent (BOLD) effect, when neural activity increases. With current techniques, this pattern of activation can be measured with resolution approaching 1 mm3 spatially and 1 s temporally. This review focuses on the physical basis of the BOLD effect, the imaging methods used to measure it, the possible origins of the physiological effects that produce a mismatch of blood flow and oxygen metabolism during neural activation, and the mathematical models that have been developed to understand the measured signals. An overarching theme is the growing field of quantitative fMRI, in which other MRI methods are combined with BOLD methods and analyzed within a theoretical modeling framework to derive quantitative estimates of oxygen metabolism and other physiological variables. That goal is the current challenge for fMRI: to move fMRI from a mapping tool to a quantitative probe of brain physiology. PMID:24006360

The physics of functional magnetic resonance imaging (fMRI).

PubMed

Buxton, Richard B

2013-09-01

Functional magnetic resonance imaging (fMRI) is a methodology for detecting dynamic patterns of activity in the working human brain. Although the initial discoveries that led to fMRI are only about 20 years old, this new field has revolutionized the study of brain function. The ability to detect changes in brain activity has a biophysical basis in the magnetic properties of deoxyhemoglobin, and a physiological basis in the way blood flow increases more than oxygen metabolism when local neural activity increases. These effects translate to a subtle increase in the local magnetic resonance signal, the blood oxygenation level dependent (BOLD) effect, when neural activity increases. With current techniques, this pattern of activation can be measured with resolution approaching 1 mm(3) spatially and 1 s temporally. This review focuses on the physical basis of the BOLD effect, the imaging methods used to measure it, the possible origins of the physiological effects that produce a mismatch of blood flow and oxygen metabolism during neural activation, and the mathematical models that have been developed to understand the measured signals. An overarching theme is the growing field of quantitative fMRI, in which other MRI methods are combined with BOLD methods and analyzed within a theoretical modeling framework to derive quantitative estimates of oxygen metabolism and other physiological variables. That goal is the current challenge for fMRI: to move fMRI from a mapping tool to a quantitative probe of brain physiology.

Cortical and subcortical mapping of language areas: correlation of functional MRI and tractography in a 3T scanner with intraoperative cortical and subcortical stimulation in patients with brain tumors located in eloquent areas.

PubMed

Jiménez de la Peña, M; Gil Robles, S; Recio Rodríguez, M; Ruiz Ocaña, C; Martínez de Vega, V

2013-01-01

To describe the detection of cortical areas and subcortical pathways involved in language observed in MRI activation studies and tractography in a 3T MRI scanner and to correlate the findings of these functional studies with direct intraoperative cortical and subcortical stimulation. We present a series of 14 patients with focal brain tumors adjacent to eloquent brain areas. All patients underwent neuropsychological evaluation before and after surgery. All patients underwent MRI examination including structural sequences, perfusion imaging, spectroscopy, functional imaging to determine activation of motor and language areas, and 3D tractography. All patients underwent cortical mapping through cortical and subcortical stimulation during the operation to resect the tumor. Postoperative follow-up studies were done 24 hours after surgery. The correlation of motor function and of the corticospinal tract determined by functional MRI and tractography with intraoperative mapping of cortical and subcortical motor areas was complete. The eloquent brain areas of language expression and reception were strongly correlated with intraoperative cortical mapping in all but two cases (a high grade infiltrating glioma and a low grade glioma located in the frontal lobe). 3D tractography identified the arcuate fasciculus, the lateral part of the superior longitudinal fasciculus, the subcallosal fasciculus, the inferior fronto-occipital fasciculus, and the optic radiations, which made it possible to mark the limits of the resection. The correlation with the subcortical mapping of the anatomic arrangement of the fasciculi with respect to the lesions was complete. The best treatment for brain tumors is maximum resection without associated deficits, so high quality functional studies are necessary for preoperative planning. Copyright © 2011 SERAM. Published by Elsevier Espana. All rights reserved.

Advances in fMRI Real-Time Neurofeedback.

PubMed

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.

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

PubMed

Kühn, Simone; Strelow, Enrique; Gallinat, Jürgen

2016-08-01

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

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

PubMed Central

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

2012-01-01

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

Preliminary pilot fMRI study of neuropostural optimization with a noninvasive asymmetric radioelectric brain stimulation protocol in functional dysmetria

PubMed Central

Mura, Marco; Castagna, Alessandro; Fontani, Vania; Rinaldi, Salvatore

2012-01-01

Purpose This study assessed changes in functional dysmetria (FD) and in brain activation observable by functional magnetic resonance imaging (fMRI) during a leg flexion-extension motor task following brain stimulation with a single radioelectric asymmetric conveyer (REAC) pulse, according to the precisely defined neuropostural optimization (NPO) protocol. Population and methods Ten healthy volunteers were assessed using fMRI conducted during a simple motor task before and immediately after delivery of a single REAC-NPO pulse. The motor task consisted of a flexion-extension movement of the legs with the knees bent. FD signs and brain activation patterns were compared before and after REAC-NPO. Results A single 250-millisecond REAC-NPO treatment alleviated FD, as evidenced by patellar asymmetry during a sit-up motion, and modulated activity patterns in the brain, particularly in the cerebellum, during the performance of the motor task. Conclusion Activity in brain areas involved in motor control and coordination, including the cerebellum, is altered by administration of a REAC-NPO treatment and this effect is accompanied by an alleviation of FD. PMID:22536071

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

PubMed

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.

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

PubMed Central

Tang, Li

2014-01-01

Summary An important goal in fMRI studies is to decompose the observed series of brain images to identify and characterize underlying brain functional networks. Independent component analysis (ICA) has been shown to be a powerful computational tool for this purpose. Classic ICA has been successfully applied to single-subject fMRI data. The extension of ICA to group inferences in neuroimaging studies, however, is challenging due to the unavailability of a pre-specified group design matrix. Existing group ICA methods generally concatenate observed fMRI data across subjects on the temporal domain and then decompose multi-subject data in a similar manner to single-subject ICA. The major limitation of existing methods is that they ignore between-subject variability in spatial distributions of brain functional networks in group ICA. In this paper, we propose a new hierarchical probabilistic group ICA method to formally model subject-specific effects in both temporal and spatial domains when decomposing multi-subject fMRI data. The proposed method provides model-based estimation of brain functional networks at both the population and subject level. An important advantage of the hierarchical model is that it provides a formal statistical framework to investigate similarities and differences in brain functional networks across subjects, e.g., subjects with mental disorders or neurodegenerative diseases such as Parkinson’s as compared to normal subjects. We develop an EM algorithm for model estimation where both the E-step and M-step have explicit forms. We compare the performance of the proposed hierarchical model with that of two popular group ICA methods via simulation studies. We illustrate our method with application to an fMRI study of Zen meditation. PMID:24033125

Functional magnetic resonance imaging can be used to explore tactile and nociceptive processing in the infant brain

PubMed Central

Williams, Gemma; Fabrizi, Lorenzo; Meek, Judith; Jackson, Deborah; Tracey, Irene; Robertson, Nicola; Slater, Rebeccah; Fitzgerald, Maria

2015-01-01

Aim Despite the importance of neonatal skin stimulation, little is known about activation of the newborn human infant brain by sensory stimulation of the skin. We carried out functional magnetic resonance imaging (fMRI) to assess the feasibility of measuring brain activation to a range of mechanical stimuli applied to the skin of neonatal infants. Methods We studied 19 term infants with a mean age of 13 days. Brain activation was measured in response to brushing, von Frey hair (vFh) punctate stimulation and, in one case, nontissue damaging pinprick stimulation of the plantar surface of the foot. Initial whole brain analysis was followed by region of interest analysis of specific brain areas. Results Distinct patterns of functional brain activation were evoked by brush and vFh punctate stimulation, which were reduced, but still present, under chloral hydrate sedation. Brain activation increased with increasing stimulus intensity. The feasibility of using pinprick stimulation in fMRI studies was established in one unsedated healthy full-term infant. Conclusion Distinct brain activity patterns can be measured in response to different modalities and intensities of skin sensory stimulation in term infants. This indicates the potential for fMRI studies in exploring tactile and nociceptive processing in the infant brain. PMID:25358870

Real-time functional magnetic resonance imaging neurofeedback in motor neurorehabilitation.

PubMed

Linden, David E J; Turner, Duncan L

2016-08-01

Recent developments in functional magnetic resonance imaging (fMRI) have catalyzed a new field of translational neuroscience. Using fMRI to monitor the aspects of task-related changes in neural activation or brain connectivity, investigators can offer feedback of simple or complex neural signals/patterns back to the participant on a quasireal-time basis [real-time-fMRI-based neurofeedback (rt-fMRI-NF)]. Here, we introduce some background methodology of the new developments in this field and give a perspective on how they may be used in neurorehabilitation in the future. The development of rt-fMRI-NF has been used to promote self-regulation of activity in several brain regions and networks. In addition, and unlike other noninvasive techniques, rt-fMRI-NF can access specific subcortical regions and in principle any region that can be monitored using fMRI including the cerebellum, brainstem and spinal cord. In Parkinson's disease and stroke, rt-fMRI-NF has been demonstrated to alter neural activity after the self-regulation training was completed and to modify specific behaviours. Future exploitation of rt-fMRI-NF could be used to induce neuroplasticity in brain networks that are involved in certain neurological conditions. However, currently, the use of rt-fMRI-NF in randomized, controlled clinical trials is in its infancy.

Functional MRI and Multivariate Autoregressive Models

PubMed Central

Rogers, Baxter P.; Katwal, Santosh B.; Morgan, Victoria L.; Asplund, Christopher L.; Gore, John C.

2010-01-01

Connectivity refers to the relationships that exist between different regions of the brain. In the context of functional magnetic resonance imaging (fMRI), it implies a quantifiable relationship between hemodynamic signals from different regions. One aspect of this relationship is the existence of small timing differences in the signals in different regions. Delays of 100 ms or less may be measured with fMRI, and these may reflect important aspects of the manner in which brain circuits respond as well as the overall functional organization of the brain. The multivariate autoregressive time series model has features to recommend it for measuring these delays, and is straightforward to apply to hemodynamic data. In this review, we describe the current usage of the multivariate autoregressive model for fMRI, discuss the issues that arise when it is applied to hemodynamic time series, and consider several extensions. Connectivity measures like Granger causality that are based on the autoregressive model do not always reflect true neuronal connectivity; however, we conclude that careful experimental design could make this methodology quite useful in extending the information obtainable using fMRI. PMID:20444566

[Initial diagnosis of Parkinson's disease - neuroradiological diagnosis].

PubMed

Orimo, Satoshi

2013-01-01

Brain MRI is essential for differentiating Parkinson's disease (PD) from other parkinsonian syndromes. The purpose of performing brain MRI is not to make a diagnosis of PD but is to exclude other parkinsonian syndromes. Recently, several new MRI techniques such as voxel based morphometry, relaxometry, magnetization transfer, spectroscopy, tractography, and functional MRI have been introduced in the diagnosis of PD. Neuromelanin imaging is one of the new techniques and can be useful to make an initial diagnosis of PD. MIBG myocardial scintigraphy is a sensitive imaging tool to differentiate PD from other parkinsonian syndromes and is one of the good tools to make an initial diagnosis of PD. Brain perfusion imaging is sometimes useful to make an initial diagnosis of PD, because reduced brain perfusion area can be detected before brain MRI detects morphological changes of the brain. Dopamine transporter imaging, not available in Japan, is a sensitive tool to detect very early parkinsonism and is useful to make an initial diagnosis of PD. However, it is difficult to differentiate PD from other parkinsonian syndromes.

Role of eNOS in water exchange index maintenance-MRI studies

NASA Astrophysics Data System (ADS)

Atochin, D.; Litvak, M.; Huang, S.; Kim, Y. R.; Huang, P.

2017-08-01

Stroke studies employ experimental models of cerebral ischemic and reperfusion injury in rodents. MRI provides valuable supravital data of cerebral blood flow and brain tissue damage. This paper presents MRI applications for cerebral blood flow research in mice lines with impaired nitric oxide production by endothelial nitric oxide synthase. Our data demonstrates that specific modifications of MRI methodology in transgenic mouse models help to evaluate the role of eNOS in the brain-blood barrier function.

The contributions of resting state and task-based functional connectivity studies to our understanding of adolescent brain network maturation.

PubMed

Stevens, Michael C

2016-11-01

This review summarizes functional magnetic resonance imaging (fMRI) research done over the past decade that examined changes in the function and organization of brain networks across human adolescence. Its over-arching goal is to highlight how both resting state functional connectivity (rs-fcMRI) and task-based functional connectivity (t-fcMRI) have jointly contributed - albeit in different ways - to our understanding of the scope and types of network organization changes that occur from puberty until young adulthood. These two approaches generally have tested different types of hypotheses using different analysis techniques. This has hampered the convergence of findings. Although much has been learned about system-wide changes to adolescents' neural network organization, if both rs-fcMRI and t-fcMRI approaches draw upon each other's methodology and ask broader questions, it will produce a more detailed connectome-informed theory of adolescent neurodevelopment to guide physiological, clinical, and other lines of research. Copyright © 2016 Elsevier Ltd. All rights reserved.

Methods of the pharmacological imaging of the cannabinoid system (PhICS) study: towards understanding the role of the brain endocannabinoid system in human cognition.

PubMed

van Hell, Hendrika H; Bossong, Matthijs G; Jager, Gerry; Kahn, René S; Ramsey, Nick F

2011-03-01

Various lines of (pre)clinical research indicate that cannabinoid agents carry the potential for therapeutic application to reduce symptoms in several psychiatric disorders. However, direct testing of the involvement of cannabinoid brain systems in psychiatric syndromes is essential for further development. In the Pharmacological Imaging of the Cannabinoid System (PhICS) study, the involvement of the endocannabinoid system in cognitive brain function is assessed by comparing acute effects of the cannabinoid agonist Δ9-tetrahydrocannabinol (THC) on brain function between healthy controls and groups of psychiatric patients showing cognitive dysfunction. This article describes the objectives and methods of the PhICS study and presents preliminary results of the administration procedure on subjective and neurophysiological parameters. Core elements in the methodology of PhICS are the administration method (THC is administered by inhalation using a vaporizing device) and a comprehensive use of pharmacological magnetic resonance imaging (phMRI) combining several types of MRI scans including functional MRI (fMRI), Arterial Spin Labeling (ASL) to measure brain perfusion, and resting-state fMRI. Additional methods like neuropsychological testing further specify the exact role of the endocannabinoid system in regulating cognition. Preliminary results presented in this paper indicate robust behavioral and subjective effects of THC. In addition, fMRI paradigms demonstrate activation of expected networks of brain regions in the cognitive domains of interest. The presented administration and assessment protocol provides a basis for further research on the involvement of the endocannabionoid systems in behavior and in psychopathology, which in turn may lead to development of therapeutic opportunities of cannabinoid ligands. Copyright © 2011 John Wiley & Sons, Ltd.

Warping of a computerized 3-D atlas to match brain image volumes for quantitative neuroanatomical and functional analysis

NASA Astrophysics Data System (ADS)

Evans, Alan C.; Dai, Weiqian; Collins, D. Louis; Neelin, Peter; Marrett, Sean

1991-06-01

We describe the implementation, experience and preliminary results obtained with a 3-D computerized brain atlas for topographical and functional analysis of brain sub-regions. A volume-of-interest (VOI) atlas was produced by manual contouring on 64 adjacent 2 mm-thick MRI slices to yield 60 brain structures in each hemisphere which could be adjusted, originally by global affine transformation or local interactive adjustments, to match individual MRI datasets. We have now added a non-linear deformation (warp) capability (Bookstein, 1989) into the procedure for fitting the atlas to the brain data. Specific target points are identified in both atlas and MRI spaces which define a continuous 3-D warp transformation that maps the atlas on to the individual brain image. The procedure was used to fit MRI brain image volumes from 16 young normal volunteers. Regional volume and positional variability were determined, the latter in such a way as to assess the extent to which previous linear models of brain anatomical variability fail to account for the true variation among normal individuals. Using a linear model for atlas deformation yielded 3-D fits of the MRI data which, when pooled across subjects and brain regions, left a residual mis-match of 6 - 7 mm as compared to the non-linear model. The results indicate a substantial component of morphometric variability is not accounted for by linear scaling. This has profound implications for applications which employ stereotactic coordinate systems which map individual brains into a common reference frame: quantitative neuroradiology, stereotactic neurosurgery and cognitive mapping of normal brain function with PET. In the latter case, the combination of a non-linear deformation algorithm would allow for accurate measurement of individual anatomic variations and the inclusion of such variations in inter-subject averaging methodologies used for cognitive mapping with PET.

Multimodal MRI in cerebral small vessel disease: its relationship with cognition and sensitivity to change over time.

PubMed

Nitkunan, Arani; Barrick, Tom R; Charlton, Rebecca A; Clark, Chris A; Markus, Hugh S

2008-07-01

Cerebral small vessel disease is the most common cause of vascular dementia. Interest in using MRI parameters as surrogate markers of disease to assess therapies is increasing. In patients with symptomatic sporadic small vessel disease, we determined which MRI parameters best correlated with cognitive function on cross-sectional analysis and which changed over a period of 1 year. Thirty-five patients with lacunar stroke and leukoaraiosis were recruited. They underwent multimodal MRI (brain volume, fluid-attenuated inversion recovery lesion load, lacunar infarct number, fractional anisotropy, and mean diffusivity from diffusion tensor imaging) and neuropsychological testing. Twenty-seven agreed to reattend for repeat MRI and neuropsychology at 1 year. An executive function score correlated most strongly with diffusion tensor imaging (fractional anisotropy histogram, r=-0.640, P=0.004) and brain volume (r=0.501, P=0.034). Associations with diffusion tensor imaging were stronger than with all other MRI parameters. On multiple regression of all imaging parameters, a model that contained brain volume and fractional anisotropy, together with age, gender, and premorbid IQ, explained 74% of the variance of the executive function score (P=0.0001). Changes in mean diffusivity and fractional anisotropy were detectable over the 1-year follow-up; in contrast, no change in other MRI parameters was detectable over this time period. A multimodal MRI model explains a large proportion of the variation in executive function in cerebral small vessel disease. In particular, diffusion tensor imaging correlates best with executive function and is the most sensitive to change. This supports the use of MRI, in particular diffusion tensor imaging, as a surrogate marker in treatment trials.

MRI Evaluation and Safety in the Developing Brain

PubMed Central

Tocchio, Shannon; Kline-Fath, Beth; Kanal, Emanuel; Schmithorst, Vincent J.; Panigrahy, Ashok

2015-01-01

Magnetic resonance imaging (MRI) evaluation of the developing brain has dramatically increased over the last decade. Faster acquisitions and the development of advanced MRI sequences such as magnetic resonance spectroscopy (MRS), diffusion tensor imaging (DTI), perfusion imaging, functional MR imaging (fMRI), and susceptibility weighted imaging (SWI), as well as the use of higher magnetic field strengths has made MRI an invaluable tool for detailed evaluation of the developing brain. This article will provide an overview of the use and challenges associated with 1.5T and 3T static magnetic fields for evaluation of the developing brain. This review will also summarize the advantages, clinical challenges and safety concerns specifically related to MRI in the fetus and newborn, including the implications of increased magnetic field strength, logistics related to transporting and monitoring of neonates during scanning, sedation considerations and a discussion of current technologies such as MRI-conditional neonatal incubators and dedicated small-foot print neonatal intensive care unit (NICU) scanners. PMID:25743582

MRI evaluation and safety in the developing brain.

PubMed

Tocchio, Shannon; Kline-Fath, Beth; Kanal, Emanuel; Schmithorst, Vincent J; Panigrahy, Ashok

2015-03-01

Magnetic resonance imaging (MRI) evaluation of the developing brain has dramatically increased over the last decade. Faster acquisitions and the development of advanced MRI sequences, such as magnetic resonance spectroscopy (MRS), diffusion tensor imaging (DTI), perfusion imaging, functional MR imaging (fMRI), and susceptibility-weighted imaging (SWI), as well as the use of higher magnetic field strengths has made MRI an invaluable tool for detailed evaluation of the developing brain. This article will provide an overview of the use and challenges associated with 1.5-T and 3-T static magnetic fields for evaluation of the developing brain. This review will also summarize the advantages, clinical challenges, and safety concerns specifically related to MRI in the fetus and newborn, including the implications of increased magnetic field strength, logistics related to transporting and monitoring of neonates during scanning, and sedation considerations, and a discussion of current technologies such as MRI conditional neonatal incubators and dedicated small-foot print neonatal intensive care unit (NICU) scanners. Copyright © 2015 Elsevier Inc. All rights reserved.

Intraoperative visualisation of functional structures facilitates safe frameless stereotactic biopsy in the motor eloquent regions of the brain.

PubMed

Zhang, Jia-Shu; Qu, Ling; Wang, Qun; Jin, Wei; Hou, Yuan-Zheng; Sun, Guo-Chen; Li, Fang-Ye; Yu, Xin-Guang; Xu, Ban-Nan; Chen, Xiao-Lei

2017-12-20

For stereotactic brain biopsy involving motor eloquent regions, the surgical objective is to enhance diagnostic yield and preserve neurological function. To achieve this aim, we implemented functional neuro-navigation and intraoperative magnetic resonance imaging (iMRI) into the biopsy procedure. The impact of this integrated technique on the surgical outcome and postoperative neurological function was investigated and evaluated. Thirty nine patients with lesions involving motor eloquent structures underwent frameless stereotactic biopsy assisted by functional neuro-navigation and iMRI. Intraoperative visualisation was realised by integrating anatomical and functional information into a navigation framework to improve biopsy trajectories and preserve eloquent structures. iMRI was conducted to guarantee the biopsy accuracy and detect intraoperative complications. The perioperative change of motor function and biopsy error before and after iMRI were recorded, and the role of functional information in trajectory selection and the relationship between the distance from sampling site to nearby eloquent structures and the neurological deterioration were further analyzed. Functional neuro-navigation helped modify the original trajectories and sampling sites in 35.90% (16/39) of cases to avoid the damage of eloquent structures. Even though all the lesions were high-risk of causing neurological deficits, no significant difference was found between preoperative and postoperative muscle strength. After data analysis, 3mm was supposed to be the safe distance for avoiding transient neurological deterioration. During surgery, the use of iMRI significantly reduced the biopsy errors (p = 0.042) and potentially increased the diagnostic yield from 84.62% (33/39) to 94.87% (37/39). Moreover, iMRI detected intraoperative haemorrhage in 5.13% (2/39) of patients, all of them benefited from the intraoperative strategies based on iMRI findings. Intraoperative visualisation of functional structures could be a feasible, safe and effective technique. Combined with intraoperative high-field MRI, it contributed to enhance the biopsy accuracy and lower neurological complications in stereotactic brain biopsy involving motor eloquent areas.

Dynamics of the brain: Mathematical models and non-invasive experimental studies

NASA Astrophysics Data System (ADS)

Toronov, V.; Myllylä, T.; Kiviniemi, V.; Tuchin, V. V.

2013-10-01

Dynamics is an essential aspect of the brain function. In this article we review theoretical models of neural and haemodynamic processes in the human brain and experimental non-invasive techniques developed to study brain functions and to measure dynamic characteristics, such as neurodynamics, neurovascular coupling, haemodynamic changes due to brain activity and autoregulation, and cerebral metabolic rate of oxygen. We focus on emerging theoretical biophysical models and experimental functional neuroimaging results, obtained mostly by functional magnetic resonance imaging (fMRI) and near-infrared spectroscopy (NIRS). We also included our current results on the effects of blood pressure variations on cerebral haemodynamics and simultaneous measurements of fast processes in the brain by near-infrared spectroscopy and a very novel functional MRI technique called magnetic resonance encephalography. Based on a rapid progress in theoretical and experimental techniques and due to the growing computational capacities and combined use of rapidly improving and emerging neuroimaging techniques we anticipate during next decade great achievements in the overall knowledge of the human brain.

Similarity-Based Fusion of MEG and fMRI Reveals Spatio-Temporal Dynamics in Human Cortex During Visual Object Recognition

PubMed Central

Cichy, Radoslaw Martin; Pantazis, Dimitrios; Oliva, Aude

2016-01-01

Every human cognitive function, such as visual object recognition, is realized in a complex spatio-temporal activity pattern in the brain. Current brain imaging techniques in isolation cannot resolve the brain's spatio-temporal dynamics, because they provide either high spatial or temporal resolution but not both. To overcome this limitation, we developed an integration approach that uses representational similarities to combine measurements of magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) to yield a spatially and temporally integrated characterization of neuronal activation. Applying this approach to 2 independent MEG–fMRI data sets, we observed that neural activity first emerged in the occipital pole at 50–80 ms, before spreading rapidly and progressively in the anterior direction along the ventral and dorsal visual streams. Further region-of-interest analyses established that dorsal and ventral regions showed MEG–fMRI correspondence in representations later than early visual cortex. Together, these results provide a novel and comprehensive, spatio-temporally resolved view of the rapid neural dynamics during the first few hundred milliseconds of object vision. They further demonstrate the feasibility of spatially unbiased representational similarity-based fusion of MEG and fMRI, promising new insights into how the brain computes complex cognitive functions. PMID:27235099

Whole-brain analytic measures of network communication reveal increased structure-function correlation in right temporal lobe epilepsy.

PubMed

Wirsich, Jonathan; Perry, Alistair; Ridley, Ben; Proix, Timothée; Golos, Mathieu; Bénar, Christian; Ranjeva, Jean-Philippe; Bartolomei, Fabrice; Breakspear, Michael; Jirsa, Viktor; Guye, Maxime

2016-01-01

The in vivo structure-function relationship is key to understanding brain network reorganization due to pathologies. This relationship is likely to be particularly complex in brain network diseases such as temporal lobe epilepsy, in which disturbed large-scale systems are involved in both transient electrical events and long-lasting functional and structural impairments. Herein, we estimated this relationship by analyzing the correlation between structural connectivity and functional connectivity in terms of analytical network communication parameters. As such, we targeted the gradual topological structure-function reorganization caused by the pathology not only at the whole brain scale but also both in core and peripheral regions of the brain. We acquired diffusion (dMRI) and resting-state fMRI (rsfMRI) data in seven right-lateralized TLE (rTLE) patients and fourteen healthy controls and analyzed the structure-function relationship by using analytical network communication metrics derived from the structural connectome. In rTLE patients, we found a widespread hypercorrelated functional network. Network communication analysis revealed greater unspecific branching of the shortest path (search information) in the structural connectome and a higher global correlation between the structural and functional connectivity for the patient group. We also found evidence for a preserved structural rich-club in the patient group. In sum, global augmentation of structure-function correlation might be linked to a smaller functional repertoire in rTLE patients, while sparing the central core of the brain which may represent a pathway that facilitates the spread of seizures.

Oxytocin, brain physiology, and functional connectivity: a review of intranasal oxytocin fMRI studies.

PubMed

Bethlehem, Richard A I; van Honk, Jack; Auyeung, Bonnie; Baron-Cohen, Simon

2013-07-01

In recent years the neuropeptide oxytocin (OT) has become one of the most studied peptides of the human neuroendocrine system. Research has shown widespread behavioural effects and numerous potential therapeutic benefits. However, little is known about how OT triggers these effects in the brain. Here, we discuss some of the physiological properties of OT in the human brain including the long half-life of neuropeptides, the diffuse projections of OT throughout the brain and interactions with other systems such as the dopaminergic system. These properties indicate that OT acts without clear spatial and temporal specificity. Therefore, it is likely to have widespread effects on the brain's intrinsic functioning. Additionally, we review studies that have used functional magnetic resonance imaging (fMRI) concurrently with OT administration. These studies reveal a specific set of 'social' brain regions that are likely to be the strongest targets for OT's potential to influence human behaviour. On the basis of the fMRI literature and the physiological properties of the neuropeptide, we argue that OT has the potential to not only modulate activity in a set of specific brain regions, but also the functional connectivity between these regions. In light of the increasing knowledge of the behavioural effects of OT in humans, studies of the effects of OT administration on brain function can contribute to our understanding of the neural networks in the social brain. Copyright © 2012 Elsevier Ltd. All rights reserved.

Robust prediction of individual creative ability from brain functional connectivity.

PubMed

Beaty, Roger E; Kenett, Yoed N; Christensen, Alexander P; Rosenberg, Monica D; Benedek, Mathias; Chen, Qunlin; Fink, Andreas; Qiu, Jiang; Kwapil, Thomas R; Kane, Michael J; Silvia, Paul J

2018-01-30

People's ability to think creatively is a primary means of technological and cultural progress, yet the neural architecture of the highly creative brain remains largely undefined. Here, we employed a recently developed method in functional brain imaging analysis-connectome-based predictive modeling-to identify a brain network associated with high-creative ability, using functional magnetic resonance imaging (fMRI) data acquired from 163 participants engaged in a classic divergent thinking task. At the behavioral level, we found a strong correlation between creative thinking ability and self-reported creative behavior and accomplishment in the arts and sciences ( r = 0.54). At the neural level, we found a pattern of functional brain connectivity related to high-creative thinking ability consisting of frontal and parietal regions within default, salience, and executive brain systems. In a leave-one-out cross-validation analysis, we show that this neural model can reliably predict the creative quality of ideas generated by novel participants within the sample. Furthermore, in a series of external validation analyses using data from two independent task fMRI samples and a large task-free resting-state fMRI sample, we demonstrate robust prediction of individual creative thinking ability from the same pattern of brain connectivity. The findings thus reveal a whole-brain network associated with high-creative ability comprised of cortical hubs within default, salience, and executive systems-intrinsic functional networks that tend to work in opposition-suggesting that highly creative people are characterized by the ability to simultaneously engage these large-scale brain networks.

Influences of Hunger, Satiety and Oral Glucose on Functional Brain Connectivity: A Multimethod Resting-State fMRI Study.

PubMed

Al-Zubaidi, Arkan; Heldmann, Marcus; Mertins, Alfred; Jauch-Chara, Kamila; Münte, Thomas F

2018-07-01

A major regulatory task of the organism is to keep brain functions relatively constant in spite of metabolic changes (e.g., hunger vs. satiety) or availability of energy (e.g., glucose administration). Resting-state functional magnetic resonance imaging (rs-fMRI) can reveal resulting changes in brain function but previous studies have focused mostly on the hypothalamus. Therefore, we took a whole-brain approach and examined 24 healthy normal-weight men once after 36 h of fasting and once in a satiated state (six meals over the course of 36 h). At the end of each treatment, rs-fMRI was recorded before and after the oral administration of 75 g of glucose. We calculated local connectivity (regional homogeneity [ReHo]), global connectivity (degree of centrality [DC]), and amplitude (fractional amplitude of low-frequency fluctuation [fALFF]) maps from the rs-fMRI data. We found that glucose administration reduced all measures selectively in the left supplementary motor area and increased ReHo and fALFF in the right middle and superior frontal gyri. For fALFF, we observed a significant interaction between metabolic states and glucose in the left thalamus. This interaction was driven by a fALFF increase after glucose treatment in the hunger relative to the satiety condition. Our results indicate that fALFF analysis is the most sensitive measure to detect effects of metabolic states on resting-state brain activity. Moreover, we show that multimethod rs-fMRI provides an unbiased approach to identify spontaneous brain activity associated with changes in homeostasis and caloric intake. Copyright © 2018 IBRO. Published by Elsevier Ltd. All rights reserved.

The Exercising Brain: Changes in Functional Connectivity Induced by an Integrated Multimodal Cognitive and Whole-Body Coordination Training

PubMed Central

Demirakca, Traute; Cardinale, Vita; Dehn, Sven; Ruf, Matthias; Ende, Gabriele

2016-01-01

This study investigated the impact of “life kinetik” training on brain plasticity in terms of an increased functional connectivity during resting-state functional magnetic resonance imaging (rs-fMRI). The training is an integrated multimodal training that combines motor and cognitive aspects and challenges the brain by introducing new and unfamiliar coordinative tasks. Twenty-one subjects completed at least 11 one-hour-per-week “life kinetik” training sessions in 13 weeks as well as before and after rs-fMRI scans. Additionally, 11 control subjects with 2 rs-fMRI scans were included. The CONN toolbox was used to conduct several seed-to-voxel analyses. We searched for functional connectivity increases between brain regions expected to be involved in the exercises. Connections to brain regions representing parts of the default mode network, such as medial frontal cortex and posterior cingulate cortex, did not change. Significant connectivity alterations occurred between the visual cortex and parts of the superior parietal area (BA7). Premotor area and cingulate gyrus were also affected. We can conclude that the constant challenge of unfamiliar combinations of coordination tasks, combined with visual perception and working memory demands, seems to induce brain plasticity expressed in enhanced connectivity strength of brain regions due to coactivation. PMID:26819776

Functional Brain Imaging

PubMed Central

2006-01-01

Executive Summary Objective The objective of this analysis is to review a spectrum of functional brain imaging technologies to identify whether there are any imaging modalities that are more effective than others for various brain pathology conditions. This evidence-based analysis reviews magnetoencephalography (MEG), magnetic resonance spectroscopy (MRS), positron emission tomography (PET), and functional magnetic resonance imaging (fMRI) for the diagnosis or surgical management of the following conditions: Alzheimer’s disease (AD), brain tumours, epilepsy, multiple sclerosis (MS), and Parkinson’s disease (PD). Clinical Need: Target Population and Condition Alzheimer’s disease is a progressive, degenerative, neurologic condition characterized by cognitive impairment and memory loss. The Canadian Study on Health and Aging estimated that there will be 97,000 incident cases (about 60,000 women) of dementia (including AD) in Canada in 2006. In Ontario, there will be an estimated 950 new cases and 580 deaths due to brain cancer in 2006. Treatments for brain tumours include surgery and radiation therapy. However, one of the limitations of radiation therapy is that it damages tissue though necrosis and scarring. Computed tomography (CT) and magnetic resonance imaging (MRI) may not distinguish between radiation effects and resistant tissue, creating a potential role for functional brain imaging. Epilepsy is a chronic disorder that provokes repetitive seizures. In Ontario, the rate of epilepsy is estimated to be 5 cases per 1,000 people. Most people with epilepsy are effectively managed with drug therapy; but about 50% do not respond to drug therapy. Surgical resection of the seizure foci may be considered in these patients, and functional brain imaging may play a role in localizing the seizure foci. Multiple sclerosis is a progressive, inflammatory, demyelinating disease of the central nervous system (CNS). The cause of MS is unknown; however, it is thought to be due to a combination of etiologies, including genetic and environmental components. The prevalence of MS in Canada is 240 cases per 100,000 people. Parkinson’s disease is the most prevalent movement disorder; it affects an estimated 100,000 Canadians. Currently, the standard for measuring disease progression is through the use of scales, which are subjective measures of disease progression. Functional brain imaging may provide an objective measure of disease progression, differentiation between parkinsonian syndromes, and response to therapy. The Technology Being Reviewed Functional Brain Imaging Functional brain imaging technologies measure blood flow and metabolism. The results of these tests are often used in conjunction with structural imaging (e.g., MRI or CT). Positron emission tomography and MRS identify abnormalities in brain tissues. The former measures abnormalities through uptake of radiotracers in the brain, while the latter measures chemical shifts in metabolite ratios to identify abnormalities. The potential role of functional MRI (fMRI) is to identify the areas of the brain responsible for language, sensory and motor function (sensorimotor cortex), rather than identifying abnormalities in tissues. Magnetoencephalography measures magnetic fields of the electric currents in the brain, identifying aberrant activity. Magnetoencephalography may have the potential to localize seizure foci and to identify the sensorimotor cortex, visual cortex and auditory cortex. In terms of regulatory status, MEG and PET are licensed by Health Canada. Both MRS and fMRI use a MRI platform; thus, they do not have a separate licence from Health Canada. The radiotracers used in PET scanning are not licensed by Health Canada for general use but can be used through a Clinical Trials Application. Review Strategy The literature published up to September 2006 was searched in the following databases: MEDLINE, MEDLINE In-Process & Other Non-Indexed Citations, EMBASE, Cochrane Database of Systematic Reviews, CENTRAL, and International Network of Agencies for Health Technology Assessment (INAHTA). The database search was supplemented with a search of relevant Web sites and a review of the bibliographies of selected papers. General inclusion criteria were applied to all conditions. Those criteria included the following: Full reports of systematic reviews, randomized controlled trials (RCTs), cohort-control studies, prospective cohort studies (PCS’), and retrospective studies. Sample sizes of at least 20 patients (≥ 10 with condition being reviewed). English-language studies. Human studies. Any age. Studying at least one of the following: fMRI, PET, MRS, or MEG. Functional brain imaging modality must be compared with a clearly defined reference standard. Must report at least one of the following outcomes: sensitivity, specificity, accuracy, positive predictive value (PPV), receiver operating characteristic curve, outcome measuring impact on diagnostic testing, treatment, patient health, or cost. Summary of Findings There is evidence to indicate that PET can accurately diagnose AD; however, at this time, there is no evidence to suggest that a diagnosis of AD with PET alters the clinical outcomes of patients. The addition of MRS or O-(2-18F-Fluoroethyl)-L-Tyrosine (FET)-PET to gadolinium (Gd)-enhanced MRI for distinguishing malignant from benign tumours during primary diagnosis may provide a higher specificity than Gd-enhanced MRI alone. The clinical utility of additional imaging in patients to distinguish malignant from benign tumours is unclear, because patients with a suspected brain tumour will likely undergo a biopsy despite additional imaging results. The addition of MRS, FET-PET, or MRI T2 to Gd-enhanced MRI for the differentiation of recurrence from radiation necrosis may provide a higher specificity than Gd-enhanced MRI alone. The clinical utility of additional imaging in patients with a suspected recurrence is in the monitoring of patients. Based on the evidence available, it is unclear if one of the imaging modalities (MRS, FET-PET, or MRI T2) offers significantly improved specificity over another. There may be a role for fMRI in the identification of surgical candidates for tumour resection; however, this requires further research. Based on the studies available, it is unclear if MEG has similar accuracy in localizing seizure foci to intracranial electroencephalogram (ICEEG). More high-quality research is needed to establish whether there is a difference in accuracy between MEG and ICEEG. The results of the studies comparing PET to noninvasive electroencephalogram (EEG) did not demonstrate that PET was more accurate at localizing seizure foci; however, there may be some specific conditions, such as tuberous sclerosis, where PET may be more accurate than noninvasive EEG. There may be some clinical utility for MEG or fMRI in presurgical functional mapping; however, this needs further investigation involving comparisons with other modalities. The clinical utility of MRS has yet to be established for patients with epilepsy. Positron emission tomography has high sensitivity and specificity in the diagnosis of PD and the differential diagnosis of parkinsonian syndromes; however, it is unclear at this time if the addition of PET in the diagnosis of these conditions contributes to the treatment and clinical outcomes of patients. There is limited clinical utility of functional brain imaging in the management of patients with MS at this time. Diagnosis of MS is established through clinical history, evoked potentials, and MRI. Magnetic resonance imaging can identify the multifocal white lesions and other structural characteristics of MS. PMID:23074493

Functional brain imaging: an evidence-based analysis.

PubMed

2006-01-01

The objective of this analysis is to review a spectrum of functional brain imaging technologies to identify whether there are any imaging modalities that are more effective than others for various brain pathology conditions. This evidence-based analysis reviews magnetoencephalography (MEG), magnetic resonance spectroscopy (MRS), positron emission tomography (PET), and functional magnetic resonance imaging (fMRI) for the diagnosis or surgical management of the following conditions: Alzheimer's disease (AD), brain tumours, epilepsy, multiple sclerosis (MS), and Parkinson's disease (PD). TARGET POPULATION AND CONDITION Alzheimer's disease is a progressive, degenerative, neurologic condition characterized by cognitive impairment and memory loss. The Canadian Study on Health and Aging estimated that there will be 97,000 incident cases (about 60,000 women) of dementia (including AD) in Canada in 2006. In Ontario, there will be an estimated 950 new cases and 580 deaths due to brain cancer in 2006. Treatments for brain tumours include surgery and radiation therapy. However, one of the limitations of radiation therapy is that it damages tissue though necrosis and scarring. Computed tomography (CT) and magnetic resonance imaging (MRI) may not distinguish between radiation effects and resistant tissue, creating a potential role for functional brain imaging. Epilepsy is a chronic disorder that provokes repetitive seizures. In Ontario, the rate of epilepsy is estimated to be 5 cases per 1,000 people. Most people with epilepsy are effectively managed with drug therapy; but about 50% do not respond to drug therapy. Surgical resection of the seizure foci may be considered in these patients, and functional brain imaging may play a role in localizing the seizure foci. Multiple sclerosis is a progressive, inflammatory, demyelinating disease of the central nervous system (CNS). The cause of MS is unknown; however, it is thought to be due to a combination of etiologies, including genetic and environmental components. The prevalence of MS in Canada is 240 cases per 100,000 people. Parkinson's disease is the most prevalent movement disorder; it affects an estimated 100,000 Canadians. Currently, the standard for measuring disease progression is through the use of scales, which are subjective measures of disease progression. Functional brain imaging may provide an objective measure of disease progression, differentiation between parkinsonian syndromes, and response to therapy. FUNCTIONAL BRAIN IMAGING: Functional brain imaging technologies measure blood flow and metabolism. The results of these tests are often used in conjunction with structural imaging (e.g., MRI or CT). Positron emission tomography and MRS identify abnormalities in brain tissues. The former measures abnormalities through uptake of radiotracers in the brain, while the latter measures chemical shifts in metabolite ratios to identify abnormalities. The potential role of functional MRI (fMRI) is to identify the areas of the brain responsible for language, sensory and motor function (sensorimotor cortex), rather than identifying abnormalities in tissues. Magnetoencephalography measures magnetic fields of the electric currents in the brain, identifying aberrant activity. Magnetoencephalography may have the potential to localize seizure foci and to identify the sensorimotor cortex, visual cortex and auditory cortex. In terms of regulatory status, MEG and PET are licensed by Health Canada. Both MRS and fMRI use a MRI platform; thus, they do not have a separate licence from Health Canada. The radiotracers used in PET scanning are not licensed by Health Canada for general use but can be used through a Clinical Trials Application. The literature published up to September 2006 was searched in the following databases: MEDLINE, MEDLINE In-Process & Other Non-Indexed Citations, EMBASE, Cochrane Database of Systematic Reviews, CENTRAL, and International Network of Agencies for Health Technology Assessment (INAHTA). The database search was supplemented with a search of relevant Web sites and a review of the bibliographies of selected papers. General inclusion criteria were applied to all conditions. Those criteria included the following: Full reports of systematic reviews, randomized controlled trials (RCTs), cohort-control studies, prospective cohort studies (PCS'), and retrospective studies.Sample sizes of at least 20 patients (≥ 10 with condition being reviewed).English-language studies.Human studies.Any age.STUDYING AT LEAST ONE OF THE FOLLOWING: fMRI, PET, MRS, or MEG.Functional brain imaging modality must be compared with a clearly defined reference standard.MUST REPORT AT LEAST ONE OF THE FOLLOWING OUTCOMES: sensitivity, specificity, accuracy, positive predictive value (PPV), receiver operating characteristic curve, outcome measuring impact on diagnostic testing, treatment, patient health, or cost. There is evidence to indicate that PET can accurately diagnose AD; however, at this time, there is no evidence to suggest that a diagnosis of AD with PET alters the clinical outcomes of patients. The addition of MRS or O-(2-(18)F-Fluoroethyl)-L-Tyrosine (FET)-PET to gadolinium (Gd)-enhanced MRI for distinguishing malignant from benign tumours during primary diagnosis may provide a higher specificity than Gd-enhanced MRI alone. The clinical utility of additional imaging in patients to distinguish malignant from benign tumours is unclear, because patients with a suspected brain tumour will likely undergo a biopsy despite additional imaging results. The addition of MRS, FET-PET, or MRI T2 to Gd-enhanced MRI for the differentiation of recurrence from radiation necrosis may provide a higher specificity than Gd-enhanced MRI alone. The clinical utility of additional imaging in patients with a suspected recurrence is in the monitoring of patients. Based on the evidence available, it is unclear if one of the imaging modalities (MRS, FET-PET, or MRI T2) offers significantly improved specificity over another. There may be a role for fMRI in the identification of surgical candidates for tumour resection; however, this requires further research. Based on the studies available, it is unclear if MEG has similar accuracy in localizing seizure foci to intracranial electroencephalogram (ICEEG). More high-quality research is needed to establish whether there is a difference in accuracy between MEG and ICEEG. The results of the studies comparing PET to noninvasive electroencephalogram (EEG) did not demonstrate that PET was more accurate at localizing seizure foci; however, there may be some specific conditions, such as tuberous sclerosis, where PET may be more accurate than noninvasive EEG. There may be some clinical utility for MEG or fMRI in presurgical functional mapping; however, this needs further investigation involving comparisons with other modalities. The clinical utility of MRS has yet to be established for patients with epilepsy. Positron emission tomography has high sensitivity and specificity in the diagnosis of PD and the differential diagnosis of parkinsonian syndromes; however, it is unclear at this time if the addition of PET in the diagnosis of these conditions contributes to the treatment and clinical outcomes of patients. There is limited clinical utility of functional brain imaging in the management of patients with MS at this time. Diagnosis of MS is established through clinical history, evoked potentials, and MRI. Magnetic resonance imaging can identify the multifocal white lesions and other structural characteristics of MS.

Effects of chondroitin sulfate on brain response to painful stimulation in knee osteoarthritis patients. A randomized, double-blind, placebo-controlled functional magnetic resonance imaging study.

PubMed

Monfort, Jordi; Pujol, Jesús; Contreras-Rodríguez, Oren; Llorente-Onaindia, Jone; López-Solà, Marina; Blanco-Hinojo, Laura; Vergés, Josep; Herrero, Marta; Sánchez, Laura; Ortiz, Hector; Montañés, Francisco; Deus, Joan; Benito, Pere

2017-06-21

Knee osteoarthritis is causing pain and functional disability. One of the inherent problems with efficacy assessment of pain medication was the lack of objective pain measurements, but functional magnetic resonance imaging (fMRI) has emerged as a useful means to objectify brain response to painful stimulation. We have investigated the effect of chondroitin sulfate (CS) on brain response to knee painful stimulation in patients with knee osteoarthritis using fMRI. Twenty-two patients received CS (800mg/day) and 27 patients placebo, and were assessed at baseline and after 4 months of treatment. Two fMRI tests were conducted in each session by applying painful pressure on the knee interline and on the patella surface. The outcome measurement was attenuation of the response evoked by knee painful stimulation in the brain. fMRI of patella pain showed significantly greater activation reduction under CS compared with placebo in the region of the mesencephalic periaquecductal gray. The CS group, additionally showed pre/post-treatment activation reduction in the cortical representation of the leg. No effects of CS were detected using the interline pressure test. fMRI was sensitive to objectify CS effects on brain response to painful pressure on patellofemoral cartilage, which is consistent with the known CS action on chondrocyte regeneration. The current work yields further support to the utility of fMRI to objectify treatment effects on osteoarthritis pain. Copyright © 2017 Elsevier España, S.L.U. All rights reserved.

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

PubMed

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 < 0.001 and spatial extent threshold of P < 0.05). These results demonstrate the feasibility of using fMRI to study brain activity in mothers listening to infant cries and that the anterior cingulate may be involved in mothers listening to crying babies. We are currently replicating this study in a larger group of mothers. Future work in this area may help (1) unravel the functional neuroanatomy of the 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.

Integrating EEG and fMRI in epilepsy.

PubMed

Formaggio, Emanuela; Storti, Silvia Francesca; Bertoldo, Alessandra; Manganotti, Paolo; Fiaschi, Antonio; Toffolo, Gianna Maria

2011-02-14

Integrating electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) studies enables to non-invasively investigate human brain function and to find the direct correlation of these two important measures of brain activity. Presurgical evaluation of patients with epilepsy is one of the areas where EEG and fMRI integration has considerable clinical relevance for localizing the brain regions generating interictal epileptiform activity. The conventional analysis of EEG-fMRI data is based on the visual identification of the interictal epileptiform discharges (IEDs) on scalp EEG. The convolution of these EEG events, represented as stick functions, with a model of the fMRI response, i.e. the hemodynamic response function, provides the regressor for general linear model (GLM) analysis of fMRI data. However, the conventional analysis is not automatic and suffers of some subjectivity in IEDs classification. Here, we present an easy-to-use and automatic approach for combined EEG-fMRI analysis able to improve IEDs identification based on Independent Component Analysis and wavelet analysis. EEG signal due to IED is reconstructed and its wavelet power is used as a regressor in GLM. The method was validated on simulated data and then applied on real data set consisting of 2 normal subjects and 5 patients with partial epilepsy. In all continuous EEG-fMRI recording sessions a good quality EEG was obtained allowing the detection of spontaneous IEDs and the analysis of the related BOLD activation. The main clinical finding in EEG-fMRI studies of patients with partial epilepsy is that focal interictal slow-wave activity was invariably associated with increased focal BOLD responses in a spatially related brain area. Our study extends current knowledge on epileptic foci localization and confirms previous reports suggesting that BOLD activation associated with slow activity might have a role in localizing the epileptogenic region even in the absence of clear interictal spikes. Copyright © 2010 Elsevier Inc. All rights reserved.

Functional magnetic resonance imaging (FMRI) with auditory stimulation in songbirds.

PubMed

Van Ruijssevelt, Lisbeth; De Groof, Geert; Van der Kant, Anne; Poirier, Colline; Van Audekerke, Johan; Verhoye, Marleen; Van der Linden, Annemie

2013-06-03

The neurobiology of birdsong, as a model for human speech, is a pronounced area of research in behavioral neuroscience. Whereas electrophysiology and molecular approaches allow the investigation of either different stimuli on few neurons, or one stimulus in large parts of the brain, blood oxygenation level dependent (BOLD) functional Magnetic Resonance Imaging (fMRI) allows combining both advantages, i.e. compare the neural activation induced by different stimuli in the entire brain at once. fMRI in songbirds is challenging because of the small size of their brains and because their bones and especially their skull comprise numerous air cavities, inducing important susceptibility artifacts. Gradient-echo (GE) BOLD fMRI has been successfully applied to songbirds (1-5) (for a review, see (6)). These studies focused on the primary and secondary auditory brain areas, which are regions free of susceptibility artifacts. However, because processes of interest may occur beyond these regions, whole brain BOLD fMRI is required using an MRI sequence less susceptible to these artifacts. This can be achieved by using spin-echo (SE) BOLD fMRI (7,8) . In this article, we describe how to use this technique in zebra finches (Taeniopygia guttata), which are small songbirds with a bodyweight of 15-25 g extensively studied in behavioral neurosciences of birdsong. The main topic of fMRI studies on songbirds is song perception and song learning. The auditory nature of the stimuli combined with the weak BOLD sensitivity of SE (compared to GE) based fMRI sequences makes the implementation of this technique very challenging.

Inferring multi-scale neural mechanisms with brain network modelling

PubMed Central

Schirner, Michael; McIntosh, Anthony Randal; Jirsa, Viktor; Deco, Gustavo

2018-01-01

The neurophysiological processes underlying non-invasive brain activity measurements are incompletely understood. Here, we developed a connectome-based brain network model that integrates individual structural and functional data with neural population dynamics to support multi-scale neurophysiological inference. Simulated populations were linked by structural connectivity and, as a novelty, driven by electroencephalography (EEG) source activity. Simulations not only predicted subjects' individual resting-state functional magnetic resonance imaging (fMRI) time series and spatial network topologies over 20 minutes of activity, but more importantly, they also revealed precise neurophysiological mechanisms that underlie and link six empirical observations from different scales and modalities: (1) resting-state fMRI oscillations, (2) functional connectivity networks, (3) excitation-inhibition balance, (4, 5) inverse relationships between α-rhythms, spike-firing and fMRI on short and long time scales, and (6) fMRI power-law scaling. These findings underscore the potential of this new modelling framework for general inference and integration of neurophysiological knowledge to complement empirical studies. PMID:29308767

Detection of Brain Reorganization in Pediatric Multiple Sclerosis Using Functional MRI

DTIC Science & Technology

2015-10-01

accomplish this, we apply comparative assessments of fMRI mappings of language, memory , and motor function, and performance on clinical neurocognitive...community at a target rate of 13 volunteers per quarter period; acquire fMRI data for language, memory , and visual-motor functions (months 3-12). c...consensus fMRI activation maps for language, memory , and visual-motor tasks (months 8-12). f) Subtask 1f. Prepare publication to disseminate our

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

PubMed Central

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

Functional brain segmentation using inter-subject correlation in fMRI.

PubMed

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.

Assessing Variations in Areal Organization for the Intrinsic Brain: From Fingerprints to Reliability

PubMed Central

Xu, Ting; Opitz, Alexander; Craddock, R. Cameron; Wright, Margaret J.; Zuo, Xi-Nian; Milham, Michael P.

2016-01-01

Resting state fMRI (R-fMRI) is a powerful in-vivo tool for examining the functional architecture of the human brain. Recent studies have demonstrated the ability to characterize transitions between functionally distinct cortical areas through the mapping of gradients in intrinsic functional connectivity (iFC) profiles. To date, this novel approach has primarily been applied to iFC profiles averaged across groups of individuals, or in one case, a single individual scanned multiple times. Here, we used a publically available R-fMRI dataset, in which 30 healthy participants were scanned 10 times (10 min per session), to investigate differences in full-brain transition profiles (i.e., gradient maps, edge maps) across individuals, and their reliability. 10-min R-fMRI scans were sufficient to achieve high accuracies in efforts to “fingerprint” individuals based upon full-brain transition profiles. Regarding test–retest reliability, the image-wise intraclass correlation coefficient (ICC) was moderate, and vertex-level ICC varied depending on region; larger durations of data yielded higher reliability scores universally. Initial application of gradient-based methodologies to a recently published dataset obtained from twins suggested inter-individual variation in areal profiles might have genetic and familial origins. Overall, these results illustrate the utility of gradient-based iFC approaches for studying inter-individual variation in brain function. PMID:27600846

Evaluation of the factors influencing brain language laterality in presurgical planning.

PubMed

Batouli, Seyed Amir Hossein; Hasani, Nafiseh; Gheisari, Sara; Behzad, Ebrahim; Oghabian, Mohammad Ali

2016-10-01

Brain lesions cause functional deficits, and one treatment for this condition is lesion resection. In most cases, presurgical planning (PSP) and the information from laterality indices are necessary for maximum preservation of the critical functions after surgery. Language laterality index (LI) is reliably estimated using functional magnetic resonance imaging (fMRI); however, this measure is under the influence of some external factors. In this study, we investigated the influence of a number of factors on language LI, using data from 120 patients (mean age=35.65 (±13.4) years) who underwent fMRI for PSP. Using two proposed language tasks from our previous works, brain left hemisphere was showed to be dominant for the language function, although a higher LI was obtained using the "Word Generation" task, compared to the "Reverse Word Reading". In addition, decline of LIs with age, and lower LI when the lesion invaded brain language area were observed. Meanwhile, gender, lesion side (affected hemisphere), LI calculation strategy, and fMRI analysis Z-values did not statistically show any influences on the LIs. Although fMRI is widely used to estimate language LI, it is shown here that in order to present a reliable language LI and to correctly select the dominant hemisphere of the brain, the influence of external factors should be carefully considered. Copyright © 2016 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

[Changes of brain pain center and default mode network an electro acupuncture in Weizhong and Dachangshu acupoints: a task-fMRI study].

PubMed

Zhou, S; Cao, H X; Yu, L C; Jin, Y J; Jia, R H; Wen, Y R; Chen, X F

2016-02-23

To investigate the functional brain pain center and default mode network response to electro acupuncture stimulate in weizhong acupoints(BL40) and dachangshu acupoints(BL25). During January to February 2015, volunteers were enrolled in this study from the staff and student interns of Gansu Province Traditional Chinese Medicine Hospital. A total of 20 healthy, right-handed subjects, male 9, female 11, age (23±3) years, participated in this study. Block design task functional magnetic resonance imaging(fMRI) 3.0 T was performed in all subjects by electro acupuncture stimulating at BL40 and BL25 from the same experienced acupuncturist.The needle connected electric acupuncture apparatus through tow long coaxial-cable. A block design with five 120 s blocks of rest time (OFF block, electric acupuncture turn off ) interspersed between five 60 s blocks of stimulation (ON block, electric acupuncture turn on) fMRI scan. Magnetic resonance data of brain function was collected and FSL(fMRI Software Library) software was used to analyze the data. All subjects' data were analyzed except 2 cases whose head movement were more than 2 mm. Activated brain function regions by electro acupuncture stimulate included temporal lobe lateral sulcus, lobus insularis, thalamus, supramarginal gyrus, prefrontal medial frontal gyrus. Negative activated brain regions included middle frontal gyrus, parahippocampal gyrus, cingulate cortex abdominal segment, parietal cortex.The functional pain central and default mode network were changed when electro acupuncture stimulate in(BL40) and(BL25). There are several brain activation regions and negative activated brain regions when administering electro acupuncture stimulation at BL40 and BL25.

A guide to using functional magnetic resonance imaging to study Alzheimer's disease in animal models.

PubMed

Asaad, Mazen; Lee, Jin Hyung

2018-05-18

Alzheimer's disease is a leading healthcare challenge facing our society today. Functional magnetic resonance imaging (fMRI) of the brain has played an important role in our efforts to understand how Alzheimer's disease alters brain function. Using fMRI in animal models of Alzheimer's disease has the potential to provide us with a more comprehensive understanding of the observations made in human clinical fMRI studies. However, using fMRI in animal models of Alzheimer's disease presents some unique challenges. Here, we highlight some of these challenges and discuss potential solutions for researchers interested in performing fMRI in animal models. First, we briefly summarize our current understanding of Alzheimer's disease from a mechanistic standpoint. We then overview the wide array of animal models available for studying this disease and how to choose the most appropriate model to study, depending on which aspects of the condition researchers seek to investigate. Finally, we discuss the contributions of fMRI to our understanding of Alzheimer's disease and the issues to consider when designing fMRI studies for animal models, such as differences in brain activity based on anesthetic choice and ways to interrogate more specific questions in rodents beyond those that can be addressed in humans. The goal of this article is to provide information on the utility of fMRI, and approaches to consider when using fMRI, for studies of Alzheimer's disease in animal models. © 2018. Published by The Company of Biologists Ltd.

A guide to using functional magnetic resonance imaging to study Alzheimer's disease in animal models

PubMed Central

Asaad, Mazen

2018-01-01

ABSTRACT Alzheimer's disease is a leading healthcare challenge facing our society today. Functional magnetic resonance imaging (fMRI) of the brain has played an important role in our efforts to understand how Alzheimer's disease alters brain function. Using fMRI in animal models of Alzheimer's disease has the potential to provide us with a more comprehensive understanding of the observations made in human clinical fMRI studies. However, using fMRI in animal models of Alzheimer's disease presents some unique challenges. Here, we highlight some of these challenges and discuss potential solutions for researchers interested in performing fMRI in animal models. First, we briefly summarize our current understanding of Alzheimer's disease from a mechanistic standpoint. We then overview the wide array of animal models available for studying this disease and how to choose the most appropriate model to study, depending on which aspects of the condition researchers seek to investigate. Finally, we discuss the contributions of fMRI to our understanding of Alzheimer's disease and the issues to consider when designing fMRI studies for animal models, such as differences in brain activity based on anesthetic choice and ways to interrogate more specific questions in rodents beyond those that can be addressed in humans. The goal of this article is to provide information on the utility of fMRI, and approaches to consider when using fMRI, for studies of Alzheimer's disease in animal models. PMID:29784664

Structural brain changes versus self-report: machine-learning classification of chronic fatigue syndrome patients.

PubMed

Sevel, Landrew S; Boissoneault, Jeff; Letzen, Janelle E; Robinson, Michael E; Staud, Roland

2018-05-30

Chronic fatigue syndrome (CFS) is a disorder associated with fatigue, pain, and structural/functional abnormalities seen during magnetic resonance brain imaging (MRI). Therefore, we evaluated the performance of structural MRI (sMRI) abnormalities in the classification of CFS patients versus healthy controls and compared it to machine learning (ML) classification based upon self-report (SR). Participants included 18 CFS patients and 15 healthy controls (HC). All subjects underwent T1-weighted sMRI and provided visual analogue-scale ratings of fatigue, pain intensity, anxiety, depression, anger, and sleep quality. sMRI data were segmented using FreeSurfer and 61 regions based on functional and structural abnormalities previously reported in patients with CFS. Classification was performed in RapidMiner using a linear support vector machine and bootstrap optimism correction. We compared ML classifiers based on (1) 61 a priori sMRI regional estimates and (2) SR ratings. The sMRI model achieved 79.58% classification accuracy. The SR (accuracy = 95.95%) outperformed both sMRI models. Estimates from multiple brain areas related to cognition, emotion, and memory contributed strongly to group classification. This is the first ML-based group classification of CFS. Our findings suggest that sMRI abnormalities are useful for discriminating CFS patients from HC, but SR ratings remain most effective in classification tasks.

Tau and Beta-Amyloid Deposition, Microhemorrhage and Brain Function after Traumatic Brain Injury in War Veterans

DTIC Science & Technology

2015-10-01

imaging and 7T- MRI to the Australian Imaging Biomarkers and Lifestyle - Veterans study (AIBL-VETS) of post-traumatic stress disorder and...focal and widespread changes in white matter integrity. 4: 7T- MRI will reveal more extensive microhemorrhage than seen on 3T- MRI and this will relate to...PET imaging, and MRI as well as clinical and neuropsychological tools to identify war veterans at risk of Alzheimer’s disease (AD) and chronic

Intensity-Curvature Measurement Approaches for the Diagnosis of Magnetic Resonance Imaging Brain Tumors.

PubMed

Ciulla, Carlo; Veljanovski, Dimitar; Rechkoska Shikoska, Ustijana; Risteski, Filip A

2015-11-01

This research presents signal-image post-processing techniques called Intensity-Curvature Measurement Approaches with application to the diagnosis of human brain tumors detected through Magnetic Resonance Imaging (MRI). Post-processing of the MRI of the human brain encompasses the following model functions: (i) bivariate cubic polynomial, (ii) bivariate cubic Lagrange polynomial, (iii) monovariate sinc, and (iv) bivariate linear. The following Intensity-Curvature Measurement Approaches were used: (i) classic-curvature, (ii) signal resilient to interpolation, (iii) intensity-curvature measure and (iv) intensity-curvature functional. The results revealed that the classic-curvature, the signal resilient to interpolation and the intensity-curvature functional are able to add additional information useful to the diagnosis carried out with MRI. The contribution to the MRI diagnosis of our study are: (i) the enhanced gray level scale of the tumor mass and the well-behaved representation of the tumor provided through the signal resilient to interpolation, and (ii) the visually perceptible third dimension perpendicular to the image plane provided through the classic-curvature and the intensity-curvature functional.

Intensity-Curvature Measurement Approaches for the Diagnosis of Magnetic Resonance Imaging Brain Tumors

PubMed Central

Ciulla, Carlo; Veljanovski, Dimitar; Rechkoska Shikoska, Ustijana; Risteski, Filip A.

2015-01-01

This research presents signal-image post-processing techniques called Intensity-Curvature Measurement Approaches with application to the diagnosis of human brain tumors detected through Magnetic Resonance Imaging (MRI). Post-processing of the MRI of the human brain encompasses the following model functions: (i) bivariate cubic polynomial, (ii) bivariate cubic Lagrange polynomial, (iii) monovariate sinc, and (iv) bivariate linear. The following Intensity-Curvature Measurement Approaches were used: (i) classic-curvature, (ii) signal resilient to interpolation, (iii) intensity-curvature measure and (iv) intensity-curvature functional. The results revealed that the classic-curvature, the signal resilient to interpolation and the intensity-curvature functional are able to add additional information useful to the diagnosis carried out with MRI. The contribution to the MRI diagnosis of our study are: (i) the enhanced gray level scale of the tumor mass and the well-behaved representation of the tumor provided through the signal resilient to interpolation, and (ii) the visually perceptible third dimension perpendicular to the image plane provided through the classic-curvature and the intensity-curvature functional. PMID:26644943

Resting-state functional magnetic resonance imaging: the impact of regression analysis.

PubMed

Yeh, Chia-Jung; Tseng, Yu-Sheng; Lin, Yi-Ru; Tsai, Shang-Yueh; Huang, Teng-Yi

2015-01-01

To investigate the impact of regression methods on resting-state functional magnetic resonance imaging (rsfMRI). During rsfMRI preprocessing, regression analysis is considered effective for reducing the interference of physiological noise on the signal time course. However, it is unclear whether the regression method benefits rsfMRI analysis. Twenty volunteers (10 men and 10 women; aged 23.4 ± 1.5 years) participated in the experiments. We used node analysis and functional connectivity mapping to assess the brain default mode network by using five combinations of regression methods. The results show that regressing the global mean plays a major role in the preprocessing steps. When a global regression method is applied, the values of functional connectivity are significantly lower (P ≤ .01) than those calculated without a global regression. This step increases inter-subject variation and produces anticorrelated brain areas. rsfMRI data processed using regression should be interpreted carefully. The significance of the anticorrelated brain areas produced by global signal removal is unclear. Copyright © 2014 by the American Society of Neuroimaging.

On consciousness, resting state fMRI, and neurodynamics

PubMed Central

2010-01-01

Background During the last years, functional magnetic resonance imaging (fMRI) of the brain has been introduced as a new tool to measure consciousness, both in a clinical setting and in a basic neurocognitive research. Moreover, advanced mathematical methods and theories have arrived the field of fMRI (e.g. computational neuroimaging), and functional and structural brain connectivity can now be assessed non-invasively. Results The present work deals with a pluralistic approach to "consciousness'', where we connect theory and tools from three quite different disciplines: (1) philosophy of mind (emergentism and global workspace theory), (2) functional neuroimaging acquisitions, and (3) theory of deterministic and statistical neurodynamics – in particular the Wilson-Cowan model and stochastic resonance. Conclusions Based on recent experimental and theoretical work, we believe that the study of large-scale neuronal processes (activity fluctuations, state transitions) that goes on in the living human brain while examined with functional MRI during "resting state", can deepen our understanding of graded consciousness in a clinical setting, and clarify the concept of "consiousness" in neurocognitive and neurophilosophy research. PMID:20522270

Hyperpolarized xenon magnetic resonance of the lung and the brain

NASA Astrophysics Data System (ADS)

Venkatesh, Arvind Krishnamachari

2001-04-01

Hyperpolarized noble gas Magnetic Resonance Imaging (MRI) is a new diagnostic modality that has been used successfully for lung imaging. Xenon is soluble in blood and inhaled xenon is transported to the brain via circulating blood. Xenon also accumulates in the lipid rich white matter of the brain. Hyperpolarized xenon can hence be used as a tissue- sensitive probe of brain function. The goals of this study were to identify the NMR resonances of xenon in the rat brain and evaluate the role of hyperpolarized xenon for brain MRI. We have developed systems to produce sufficient volumes of hyperpolarized xenon for in vivo brain experiments. The specialized instrumentation developed include an apparatus for optical pump-cell manufacture and high purity gas manifolds for filling cells. A hyperpolarized gas delivery system was designed to ventilate small animals with hyperpolarized xenon for transport to the brain. The T1 of xenon dissolved in blood indicates that the lifetime of xenon in the blood is sufficient for significant magnetization to be transferred to distal tissues. A variety of carrier agents for intravenous delivery of hyperpolarized xenon were tested for transport to distal tissues. Using our new gas delivery system, high SNR 129Xe images of rat lungs were obtained. Spectroscopy with hyperpolarized xenon indicated that xenon was transported from the lungs to the blood and tissues with intact magnetization. After preliminary studies that indicated the feasibility for in vivo rat brain studies, experiments were performed with adult rats and young rats with different stages of white matter development. Both in vivo and in vitro experiments showed the prominence of one peak from xenon in the rat brain, which was assigned to brain lipids. Cerebral brain perfusion was calculated from the wash-out of the hyperpolarized xenon signal in the brain. An increase in brain perfusion during maturation was observed. These experiments showed that hyperpolarized xenon MRI can be used to develop unique approaches to studying white matter and gray matter in the brain. Some of the possible applications of hyperpolarized xenon MRI in the brain are clinical diagnosis of white matter diseases, functional MRI (fMRI) and measurement of cerebral blood perfusion.

Functional Geometry Alignment and Localization of Brain Areas.

PubMed

Langs, Georg; Golland, Polina; Tie, Yanmei; Rigolo, Laura; Golby, Alexandra J

2010-01-01

Matching functional brain regions across individuals is a challenging task, largely due to the variability in their location and extent. It is particularly difficult, but highly relevant, for patients with pathologies such as brain tumors, which can cause substantial reorganization of functional systems. In such cases spatial registration based on anatomical data is only of limited value if the goal is to establish correspondences of functional areas among different individuals, or to localize potentially displaced active regions. Rather than rely on spatial alignment, we propose to perform registration in an alternative space whose geometry is governed by the functional interaction patterns in the brain. We first embed each brain into a functional map that reflects connectivity patterns during a fMRI experiment. The resulting functional maps are then registered, and the obtained correspondences are propagated back to the two brains. In application to a language fMRI experiment, our preliminary results suggest that the proposed method yields improved functional correspondences across subjects. This advantage is pronounced for subjects with tumors that affect the language areas and thus cause spatial reorganization of the functional regions.

Mapping Informative Clusters in a Hierarchial Framework of fMRI Multivariate Analysis

PubMed Central

Xu, Rui; Zhen, Zonglei; Liu, Jia

2010-01-01

Pattern recognition methods have become increasingly popular in fMRI data analysis, which are powerful in discriminating between multi-voxel patterns of brain activities associated with different mental states. However, when they are used in functional brain mapping, the location of discriminative voxels varies significantly, raising difficulties in interpreting the locus of the effect. Here we proposed a hierarchical framework of multivariate approach that maps informative clusters rather than voxels to achieve reliable functional brain mapping without compromising the discriminative power. In particular, we first searched for local homogeneous clusters that consisted of voxels with similar response profiles. Then, a multi-voxel classifier was built for each cluster to extract discriminative information from the multi-voxel patterns. Finally, through multivariate ranking, outputs from the classifiers were served as a multi-cluster pattern to identify informative clusters by examining interactions among clusters. Results from both simulated and real fMRI data demonstrated that this hierarchical approach showed better performance in the robustness of functional brain mapping than traditional voxel-based multivariate methods. In addition, the mapped clusters were highly overlapped for two perceptually equivalent object categories, further confirming the validity of our approach. In short, the hierarchical framework of multivariate approach is suitable for both pattern classification and brain mapping in fMRI studies. PMID:21152081

Altered Brain Microstate Dynamics in Adolescents with Narcolepsy

PubMed Central

Drissi, Natasha M.; Szakács, Attila; Witt, Suzanne T.; Wretman, Anna; Ulander, Martin; Ståhlbrandt, Henriettae; Darin, Niklas; Hallböök, Tove; Landtblom, Anne-Marie; Engström, Maria

2016-01-01

Narcolepsy is a chronic sleep disorder caused by a loss of hypocretin-1 producing neurons in the hypothalamus. Previous neuroimaging studies have investigated brain function in narcolepsy during rest using positron emission tomography (PET) and single photon emission computed tomography (SPECT). In addition to hypothalamic and thalamic dysfunction they showed aberrant prefrontal perfusion and glucose metabolism in narcolepsy. Given these findings in brain structure and metabolism in narcolepsy, we anticipated that changes in functional magnetic resonance imaging (fMRI) resting state network (RSN) dynamics might also be apparent in patients with narcolepsy. The objective of this study was to investigate and describe brain microstate activity in adolescents with narcolepsy and correlate these to RSNs using simultaneous fMRI and electroencephalography (EEG). Sixteen adolescents (ages 13–20) with a confirmed diagnosis of narcolepsy were recruited and compared to age-matched healthy controls. Simultaneous EEG and fMRI data were collected during 10 min of wakeful rest. EEG data were analyzed for microstates, which are discrete epochs of stable global brain states obtained from topographical EEG analysis. Functional MRI data were analyzed for RSNs. Data showed that narcolepsy patients were less likely than controls to spend time in a microstate which we found to be related to the default mode network and may suggest a disruption of this network that is disease specific. We concluded that adolescents with narcolepsy have altered resting state brain dynamics. PMID:27536225

Causes, effects and connectivity changes in MS-related cognitive decline.

PubMed

Rimkus, Carolina de Medeiros; Steenwijk, Martijn D; Barkhof, Frederik

2016-01-01

Cognitive decline is a frequent but undervalued aspect of multiple sclerosis (MS). Currently, it remains unclear what the strongest determinants of cognitive dysfunction are, with grey matter damage most directly related to cognitive impairment. Multi-parametric studies seem to indicate that individual factors of MS-pathology are highly interdependent causes of grey matter atrophy and permanent brain damage. They are associated with intermediate functional effects (e.g. in functional MRI) representing a balance between disconnection and (mal) adaptive connectivity changes. Therefore, a more comprehensive MRI approach is warranted, aiming to link structural changes with functional brain organization. To better understand the disconnection syndromes and cognitive decline in MS, this paper reviews the associations between MRI metrics and cognitive performance, by discussing the interactions between multiple facets of MS pathology as determinants of brain damage and how they affect network efficiency.

Relations of arterial stiffness and endothelial function to brain aging in the community.

PubMed

Tsao, Connie W; Seshadri, Sudha; Beiser, Alexa S; Westwood, Andrew J; Decarli, Charles; Au, Rhoda; Himali, Jayandra J; Hamburg, Naomi M; Vita, Joseph A; Levy, Daniel; Larson, Martin G; Benjamin, Emelia J; Wolf, Philip A; Vasan, Ramachandran S; Mitchell, Gary F

2013-09-10

To determine the association of arterial stiffness and pressure pulsatility, which can damage small vessels in the brain, with vascular and Alzheimer-type brain aging. Stroke- and dementia-free Framingham Offspring Study participants (n = 1,587, 61 ± 9 years, 45% male) underwent study of tonometric arterial stiffness and endothelial function (1998-2001) and brain MRI and cognition (1999-2002). We related carotid-femoral pulse wave velocity (CFPWV), mean arterial and central pulse pressure, and endothelial function to vascular brain aging by MRI (total cerebral brain volume [TCBV], white matter hyperintensity volume, silent cerebral infarcts) and vascular and Alzheimer-type cognitive aging (Trails B minus Trails A and logical memory-delayed recall, respectively). Higher CFPWV was associated with lower TCBV, greater white matter hyperintensity volume, and greater prevalence of silent cerebral infarcts (all p < 0.05). Each SD greater CFPWV was associated with lower TCBV equivalent to 1.2 years of brain aging. Mean arterial and central pulse pressure were associated with greater white matter hyperintensity volume (p = 0.005) and lower TCBV (p = 0.02), respectively, and worse verbal memory (both p < 0.05). Associations of tonometry variables with TCBV and white matter hyperintensity volume were stronger among those aged 65 years and older vs those younger than 65 years (p < 0.10 for interaction). Brachial artery endothelial function was unrelated to MRI measures (all p > 0.05). Greater arterial stiffness and pressure pulsatility are associated with brain aging, MRI vascular insults, and memory deficits typically seen in Alzheimer dementia. Future investigations are warranted to evaluate the potential impact of prevention and treatment of unfavorable arterial hemodynamics on neurocognitive outcomes.

The effect of inflammation and its reduction on brain plasticity in multiple sclerosis: MRI evidence

PubMed Central

d'Ambrosio, Alessandro; Petsas, Nikolaos; Wise, Richard G.; Sbardella, Emilia; Allen, Marek; Tona, Francesca; Fanelli, Fulvia; Foster, Catherine; Carnì, Marco; Gallo, Antonio; Pantano, Patrizia; Pozzilli, Carlo

2016-01-01

Abstract Brain plasticity is the basis for systems‐level functional reorganization that promotes recovery in multiple sclerosis (MS). As inflammation interferes with plasticity, its pharmacological modulation may restore plasticity by promoting desired patterns of functional reorganization. Here, we tested the hypothesis that brain plasticity probed by a visuomotor adaptation task is impaired with MS inflammation and that pharmacological reduction of inflammation facilitates its restoration. MS patients were assessed twice before (sessions 1 and 2) and once after (session 3) the beginning of Interferon beta (IFN beta), using behavioural and structural MRI measures. During each session, 2 functional MRI runs of a visuomotor task, separated by 25‐minutes of task practice, were performed. Within‐session between‐run change in task‐related functional signal was our imaging marker of plasticity. During session 1, patients were compared with healthy controls. Comparison of patients' sessions 2 and 3 tested the effect of reduced inflammation on our imaging marker of plasticity. The proportion of patients with gadolinium‐enhancing lesions reduced significantly during IFN beta. In session 1, patients demonstrated a greater between‐run difference in functional MRI activity of secondary visual areas and cerebellum than controls. This abnormally large practice‐induced signal change in visual areas, and in functionally connected posterior parietal and motor cortices, was reduced in patients in session 3 compared with 2. Our results suggest that MS inflammation alters short‐term plasticity underlying motor practice. Reduction of inflammation with IFN beta is associated with a restoration of this plasticity, suggesting that modulation of inflammation may enhance recovery‐oriented strategies that rely on patients' brain plasticity. Hum Brain Mapp 37:2431–2445, 2016. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc. PMID:26991559

The clinical outcomes of deep gray matter injury in children with cerebral palsy in relation with brain magnetic resonance imaging.

PubMed

Choi, Ja Young; Choi, Yoon Seong; Rha, Dong-Wook; Park, Eun Sook

2016-08-01

In the present study we investigated the nature and extent of clinical outcomes using various classifications and analyzed the relationship between brain magnetic resonance imaging (MRI) findings and the extent of clinical outcomes in children with cerebral palsy (CP) with deep gray matter injury. The deep gray matter injuries of 69 children were classified into hypoxic ischemic encephalopathy (HIE) and kernicterus patterns. HIE patterns were divided into four groups (I-IV) based on severity. Functional classification was investigated using the gross motor function classification system-expanded and revised, manual ability classification system, communication function classification system, and tests of cognitive function, and other associated problems. The severity of HIE pattern on brain MRI was strongly correlated with the severity of clinical outcomes in these various domains. Children with a kernicterus pattern showed a wide range of clinical outcomes in these areas. Children with severe HIE are at high risk of intellectual disability (ID) or epilepsy and children with a kernicterus pattern are at risk of hearing impairment and/or ID. Grading severity of HIE pattern on brain MRI is useful for predicting overall outcomes. The clinical outcomes of children with a kernicterus pattern range widely from mild to severe. Delineation of the clinical outcomes of children with deep gray matter injury, which are a common abnormal brain MRI finding in children with CP, is necessary. The present study provides clinical outcomes for various domains in children with deep gray matter injury on brain MRI. The deep gray matter injuries were divided into two major groups; HIE and kernicterus patterns. Our study showed that severity of HIE pattern on brain MRI was strongly associated with the severity of impairments in gross motor function, manual ability, communication function, and cognition. These findings suggest that severity of HIE pattern can be useful for predicting the severity of impairments. Conversely, children with a kernicterus pattern showed a wide range of clinical outcomes in various domains. Children with severe HIE pattern are at high risk of ID or epilepsy and children with kernicterus pattern are at risk of hearing impairment or ID. The strength of our study was the assessment of clinical outcomes after 3 years of age using standardized classification systems in various domains in children with deep gray matter injury. Copyright © 2016 Elsevier Ltd. All rights reserved.

Visual assessment of brain magnetic resonance imaging detects injury to cognitive regulatory sites in patients with heart failure.

PubMed

Pan, Alan; Kumar, Rajesh; Macey, Paul M; Fonarow, Gregg C; Harper, Ronald M; Woo, Mary A

2013-02-01

Heart failure (HF) patients exhibit depression and executive function impairments that contribute to HF mortality. Using specialized magnetic resonance imaging (MRI) analysis procedures, brain changes appear in areas regulating these functions (mammillary bodies, hippocampi, and frontal cortex). However, specialized MRI procedures are not part of standard clinical assessment for HF (which is usually a visual evaluation), and it is unclear whether visual MRI examination can detect changes in these structures. Using brain MRI, we visually examined the mammillary bodies and frontal cortex for global and hippocampi for global and regional tissue changes in 17 HF and 50 control subjects. Significantly global changes emerged in the right mammillary body (HF 1.18 ± 1.13 vs control 0.52 ± 0.74; P = .024), right hippocampus (HF 1.53 ± 0.94 vs control 0.80 ± 0.86; P = .005), and left frontal cortex (HF 1.76 ± 1.03 vs control 1.24 ± 0.77; P = .034). Comparison of the visual method with specialized MRI techniques corroborates right hippocampal and left frontal cortical, but not mammillary body, tissue changes. Visual examination of brain MRI can detect damage in HF in areas regulating depression and executive function, including the right hippocampus and left frontal cortex. Visual MRI assessment in HF may facilitate evaluation of injury to these structures and the assessment of the impact of potential treatments for this damage. Copyright © 2013 Elsevier Inc. All rights reserved.

R6/2 Huntington's disease mice develop early and progressive abnormal brain metabolism and seizures.

PubMed

Cepeda-Prado, Efrain; Popp, Susanna; Khan, Usman; Stefanov, Dimitre; Rodríguez, Jorge; Menalled, Liliana B; Dow-Edwards, Diana; Small, Scott A; Moreno, Herman

2012-05-09

A hallmark feature of Huntington's disease pathology is the atrophy of brain regions including, but not limited to, the striatum. Though MRI studies have identified structural CNS changes in several Huntington's disease (HD) mouse models, the functional consequences of HD pathology during the progression of the disease have yet to be investigated using in vivo functional MRI (fMRI). To address this issue, we first established the structural and functional MRI phenotype of juvenile HD mouse model R6/2 at early and advanced stages of disease. Significantly higher fMRI signals [relative cerebral blood volumes (rCBVs)] and atrophy were observed in both age groups in specific brain regions. Next, fMRI results were correlated with electrophysiological analysis, which showed abnormal increases in neuronal activity in affected brain regions, thus identifying a mechanism accounting for the abnormal fMRI findings. [(14)C] 2-deoxyglucose maps to investigate patterns of glucose utilization were also generated. An interesting mismatch between increases in rCBV and decreases in glucose uptake was observed. Finally, we evaluated the sensitivity of this mouse line to audiogenic seizures early in the disease course. We found that R6/2 mice had an increased susceptibility to develop seizures. Together, these findings identified seizure activity in R6/2 mice and show that neuroimaging measures sensitive to oxygen metabolism can be used as in vivo biomarkers, preceding the onset of an overt behavioral phenotype. Since fMRI-rCBV can also be obtained in patients, we propose that it may serve as a translational tool to evaluate therapeutic responses in humans and HD mouse models.

Test-retest reliability of functional connectivity networks during naturalistic fMRI paradigms.

PubMed

Wang, Jiahui; Ren, Yudan; Hu, Xintao; Nguyen, Vinh Thai; Guo, Lei; Han, Junwei; Guo, Christine Cong

2017-04-01

Functional connectivity analysis has become a powerful tool for probing the human brain function and its breakdown in neuropsychiatry disorders. So far, most studies adopted resting-state paradigm to examine functional connectivity networks in the brain, thanks to its low demand and high tolerance that are essential for clinical studies. However, the test-retest reliability of resting-state connectivity measures is moderate, potentially due to its low behavioral constraint. On the other hand, naturalistic neuroimaging paradigms, an emerging approach for cognitive neuroscience with high ecological validity, could potentially improve the reliability of functional connectivity measures. To test this hypothesis, we characterized the test-retest reliability of functional connectivity measures during a natural viewing condition, and benchmarked it against resting-state connectivity measures acquired within the same functional magnetic resonance imaging (fMRI) session. We found that the reliability of connectivity and graph theoretical measures of brain networks is significantly improved during natural viewing conditions over resting-state conditions, with an average increase of almost 50% across various connectivity measures. Not only sensory networks for audio-visual processing become more reliable, higher order brain networks, such as default mode and attention networks, but also appear to show higher reliability during natural viewing. Our results support the use of natural viewing paradigms in estimating functional connectivity of brain networks, and have important implications for clinical application of fMRI. Hum Brain Mapp 38:2226-2241, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Structural network efficiency is associated with cognitive impairment in small-vessel disease.

PubMed

Lawrence, Andrew J; Chung, Ai Wern; Morris, Robin G; Markus, Hugh S; Barrick, Thomas R

2014-07-22

To characterize brain network connectivity impairment in cerebral small-vessel disease (SVD) and its relationship with MRI disease markers and cognitive impairment. A cross-sectional design applied graph-based efficiency analysis to deterministic diffusion tensor tractography data from 115 patients with lacunar infarction and leukoaraiosis and 50 healthy individuals. Structural connectivity was estimated between 90 cortical and subcortical brain regions and efficiency measures of resulting graphs were analyzed. Networks were compared between SVD and control groups, and associations between efficiency measures, conventional MRI disease markers, and cognitive function were tested. Brain diffusion tensor tractography network connectivity was significantly reduced in SVD: networks were less dense, connection weights were lower, and measures of network efficiency were significantly disrupted. The degree of brain network disruption was associated with MRI measures of disease severity and cognitive function. In multiple regression models controlling for confounding variables, associations with cognition were stronger for network measures than other MRI measures including conventional diffusion tensor imaging measures. A total mediation effect was observed for the association between fractional anisotropy and mean diffusivity measures and executive function and processing speed. Brain network connectivity in SVD is disturbed, this disturbance is related to disease severity, and within a mediation framework fully or partly explains previously observed associations between MRI measures and SVD-related cognitive dysfunction. These cross-sectional results highlight the importance of network disruption in SVD and provide support for network measures as a disease marker in treatment studies. © 2014 American Academy of Neurology.

Structural network efficiency is associated with cognitive impairment in small-vessel disease

PubMed Central

Chung, Ai Wern; Morris, Robin G.; Markus, Hugh S.; Barrick, Thomas R.

2014-01-01

Objective: To characterize brain network connectivity impairment in cerebral small-vessel disease (SVD) and its relationship with MRI disease markers and cognitive impairment. Methods: A cross-sectional design applied graph-based efficiency analysis to deterministic diffusion tensor tractography data from 115 patients with lacunar infarction and leukoaraiosis and 50 healthy individuals. Structural connectivity was estimated between 90 cortical and subcortical brain regions and efficiency measures of resulting graphs were analyzed. Networks were compared between SVD and control groups, and associations between efficiency measures, conventional MRI disease markers, and cognitive function were tested. Results: Brain diffusion tensor tractography network connectivity was significantly reduced in SVD: networks were less dense, connection weights were lower, and measures of network efficiency were significantly disrupted. The degree of brain network disruption was associated with MRI measures of disease severity and cognitive function. In multiple regression models controlling for confounding variables, associations with cognition were stronger for network measures than other MRI measures including conventional diffusion tensor imaging measures. A total mediation effect was observed for the association between fractional anisotropy and mean diffusivity measures and executive function and processing speed. Conclusions: Brain network connectivity in SVD is disturbed, this disturbance is related to disease severity, and within a mediation framework fully or partly explains previously observed associations between MRI measures and SVD-related cognitive dysfunction. These cross-sectional results highlight the importance of network disruption in SVD and provide support for network measures as a disease marker in treatment studies. PMID:24951477

Correlation of the CT Compatible Stereotaxic Craniotomy with MRI Scans of the Patients for Removing Cranial Lesions Located Eloquent Areas and Deep Sites of Brain.

PubMed

Gulsen, Salih

2015-03-15

The first goal in neurosurgery is to protect neural function as long as it is possible. Moreover, while protecting the neural function, a neurosurgeon should extract the maximum amount of tumoral tissue from the tumour region of the brain. So neurosurgery and technological advancement go hand in hand to realize this goal. Using of CT compatible stereotaxy for removing a cranial tumour is to be commended as a cornerstone of these technological advancements. Following CT compatible stereotaxic system applications in neurosurgery, different techniques have taken place in neurosurgical practice. These techniques are magnetic resonance imaging (MRI), MRI compatible stereotaxis, frameless stereotaxy, volumetric stereotaxy, functional MRI, diffusion tensor (DT) imaging techniques (tractography of the white matter), intraoperative MRI and neuronavigation systems. However, to use all of this equipment having these technologies would be impossible because of economic reasons. However, when we correlated this technique with MRI scans of the patients with CT compatible stereotaxy scans, it is possible to provide gross total resection and protect and improve patients' neural functions.

A new vibrator to stimulate muscle proprioceptors in fMRI.

PubMed

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

2009-03-01

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

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

NASA Astrophysics Data System (ADS)

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

2007-03-01

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

The Use of Functional MRI to Study Appetite Control in the CNS

PubMed Central

De Silva, Akila; Salem, Victoria; Matthews, Paul M.; Dhillo, Waljit S.

2012-01-01

Functional magnetic resonance imaging (fMRI) has provided the opportunity to safely investigate the workings of the human brain. This paper focuses on its use in the field of human appetitive behaviour and its impact in obesity research. In the present absence of any safe or effective centrally acting appetite suppressants, a better understanding of how appetite is controlled is vital for the development of new antiobesity pharmacotherapies. Early functional imaging techniques revealed an attenuation of brain reward area activity in response to visual food stimuli when humans are fed—in other words, the physiological state of hunger somehow increases the appeal value of food. Later studies have investigated the action of appetite modulating hormones on the fMRI signal, showing how the attenuation of brain reward region activity that follows feeding can be recreated in the fasted state by the administration of anorectic gut hormones. Furthermore, differences in brain activity between obese and lean individuals have provided clues about the possible aetiology of overeating. The hypothalamus acts as a central gateway modulating homeostatic and nonhomeostatic drives to eat. As fMRI techniques constantly improve, functional data regarding the role of this small but hugely important structure in appetite control is emerging. PMID:22719753

Defining functional SMA and pre-SMA subregions in human MFC using resting state fMRI: functional connectivity-based parcellation method.

PubMed

Kim, Jae-Hun; Lee, Jong-Min; Jo, Hang Joon; Kim, Sook Hui; Lee, Jung Hee; Kim, Sung Tae; Seo, Sang Won; Cox, Robert W; Na, Duk L; Kim, Sun I; Saad, Ziad S

2010-02-01

Noninvasive parcellation of the human cerebral cortex is an important goal for understanding and examining brain functions. Recently, the patterns of anatomical connections using diffusion tensor imaging (DTI) have been used to parcellate brain regions. Here, we present a noninvasive parcellation approach that uses "functional fingerprints" obtained by correlation measures on resting state functional magnetic resonance imaging (fMRI) data to parcellate brain regions. In other terms, brain regions are parcellated based on the similarity of their connection--as reflected by correlation during resting state--to the whole brain. The proposed method was used to parcellate the medial frontal cortex (MFC) into supplementary motor areas (SMA) and pre-SMA subregions. In agreement with anatomical landmark-based parcellation, we find that functional fingerprint clustering of the MFC results in anterior and posterior clusters. The probabilistic maps from 12 subjects showed that the anterior cluster is mainly located rostral to the vertical commissure anterior (VCA) line, whereas the posterior cluster is mainly located caudal to VCA line, suggesting the homologues of pre-SMA and SMA. The functional connections from the putative pre-SMA cluster were connected to brain regions which are responsible for complex/cognitive motor control, whereas those from the putative SMA cluster were connected to brain regions which are related to the simple motor control. These findings demonstrate the feasibility of the functional connectivity-based parcellation of the human cerebral cortex using resting state fMRI. Copyright (c) 2009 Elsevier Inc. All rights reserved.

Rapid and minimum invasive functional brain mapping by real-time visualization of high gamma activity during awake craniotomy.

PubMed

Ogawa, Hiroshi; Kamada, Kyousuke; Kapeller, Christoph; Hiroshima, Satoru; Prueckl, Robert; Guger, Christoph

2014-11-01

Electrocortical stimulation (ECS) is the gold standard for functional brain mapping during an awake craniotomy. The critical issue is to set aside enough time to identify eloquent cortices by ECS. High gamma activity (HGA) ranging between 80 and 120 Hz on electrocorticogram is assumed to reflect localized cortical processing. In this report, we used real-time HGA mapping and functional neuronavigation integrated with functional magnetic resonance imaging (fMRI) for rapid and reliable identification of motor and language functions. Four patients with intra-axial tumors in their dominant hemisphere underwent preoperative fMRI and lesion resection with an awake craniotomy. All patients showed significant fMRI activation evoked by motor and language tasks. During the craniotomy, we recorded electrocorticogram activity by placing subdural grids directly on the exposed brain surface. Each patient performed motor and language tasks and demonstrated real-time HGA dynamics in hand motor areas and parts of the inferior frontal gyrus. Sensitivity and specificity of HGA mapping were 100% compared with ECS mapping in the frontal lobe, which suggested HGA mapping precisely indicated eloquent cortices. We found different HGA dynamics of language tasks in frontal and temporal regions. Specificities of the motor and language-fMRI did not reach 85%. The results of HGA mapping was mostly consistent with those of ECS mapping, although fMRI tended to overestimate functional areas. This novel technique enables rapid and accurate identification of motor and frontal language areas. Furthermore, real-time HGA mapping sheds light on underlying physiological mechanisms related to human brain functions. Copyright © 2014 Elsevier Inc. All rights reserved.

Visual analytics of brain networks.

PubMed

Li, Kaiming; Guo, Lei; Faraco, Carlos; Zhu, Dajiang; Chen, Hanbo; Yuan, Yixuan; Lv, Jinglei; Deng, Fan; Jiang, Xi; Zhang, Tuo; Hu, Xintao; Zhang, Degang; Miller, L Stephen; Liu, Tianming

2012-05-15

Identification of regions of interest (ROIs) is a fundamental issue in brain network construction and analysis. Recent studies demonstrate that multimodal neuroimaging approaches and joint analysis strategies are crucial for accurate, reliable and individualized identification of brain ROIs. In this paper, we present a novel approach of visual analytics and its open-source software for ROI definition and brain network construction. By combining neuroscience knowledge and computational intelligence capabilities, visual analytics can generate accurate, reliable and individualized ROIs for brain networks via joint modeling of multimodal neuroimaging data and an intuitive and real-time visual analytics interface. Furthermore, it can be used as a functional ROI optimization and prediction solution when fMRI data is unavailable or inadequate. We have applied this approach to an operation span working memory fMRI/DTI dataset, a schizophrenia DTI/resting state fMRI (R-fMRI) dataset, and a mild cognitive impairment DTI/R-fMRI dataset, in order to demonstrate the effectiveness of visual analytics. Our experimental results are encouraging. Copyright © 2012 Elsevier Inc. All rights reserved.

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

PubMed Central

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

The effects of alcohol on the nonhuman primate brain: a network science approach to neuroimaging.

PubMed

Telesford, Qawi K; Laurienti, Paul J; Friedman, David P; Kraft, Robert A; Daunais, James B

2013-11-01

Animal studies have long been an important tool for basic research as they offer a degree of control often lacking in clinical studies. Of particular value is the use of nonhuman primates (NHPs) for neuroimaging studies. Currently, studies have been published using functional magnetic resonance imaging (fMRI) to understand the default-mode network in the NHP brain. Network science provides an alternative approach to neuroimaging allowing for evaluation of whole-brain connectivity. In this study, we used network science to build NHP brain networks from fMRI data to understand the basic functional organization of the NHP brain. We also explored how the brain network is affected following an acute ethanol (EtOH) pharmacological challenge. Baseline resting-state fMRI was acquired in an adult male rhesus macaque (n = 1) and a cohort of vervet monkeys (n = 10). A follow-up scan was conducted in the rhesus macaque to assess network variability and to assess the effects of an acute EtOH challenge on the brain network. The most connected regions in the resting-state networks were similar across species and matched regions identified as the default-mode network in previous NHP fMRI studies. Under an acute EtOH challenge, the functional organization of the brain was significantly impacted. Network science offers a great opportunity to understand the brain as a complex system and how pharmacological conditions can affect the system globally. These models are sensitive to changes in the brain and may prove to be a valuable tool in long-term studies on alcohol exposure. Copyright © 2013 by the Research Society on Alcoholism.

Variability comparison of simultaneous brain near-infrared spectroscopy (NIRS) and functional MRI (fMRI) during visual stimulation

PubMed Central

Minati, Ludovico; Visani, Elisa; Dowell, Nick G; Medford, Nick; Critchley, Hugo D

2011-01-01

Brain near-infrared spectroscopy (NIRS) is emerging as a potential alternative to functional MRI (fMRI). To date, no study has explicitly compared the two techniques in terms of measurement variability, a key parameter dictating attainable statistical power. Here, NIRS and fMRI were simultaneously recorded during event-related visual stimulation. Inter-subject coefficients of variation (CVs) for peak response amplitude were considerably larger for NIRS than fMRI, but inter-subject CVs for response latency and intra-subject CVs for response amplitude were overall comparable. Our results may represent an optimistic estimate of the CVs of NIRS measurements, as optode positioning was guided by structural MRI, which is normally unavailable. We conclude that fMRI may be preferable to NIRS for group comparisons, but NIRS is equally powerful when comparing conditions within participants. The discrepancy between inter- and intra-subject CVs is likely related to variability in head anatomy and tissue properties which may be better accounted for by emerging NIRS technology. PMID:21780948

Breaking down the barriers: fMRI applications in pain, analgesia and analgesics

PubMed Central

Borsook, David; Becerra, Lino R

2006-01-01

This review summarizes functional magnetic resonance imaging (fMRI) findings that have informed our current understanding of pain, analgesia and related phenomena, and discusses the potential role of fMRI in improved therapeutic approaches to pain. It is divided into 3 main sections: (1) fMRI studies of acute and chronic pain. Physiological studies of pain have found numerous regions of the brain to be involved in the interpretation of the 'pain experience'; studies in chronic pain conditions have identified a significant CNS component; and fMRI studies of surrogate models of chronic pain are also being used to further this understanding. (2) fMRI studies of endogenous pain processing including placebo, empathy, attention or cognitive modulation of pain. (3) The use of fMRI to evaluate the effects of analgesics on brain function in acute and chronic pain. fMRI has already provided novel insights into the neurobiology of pain. These insights should significantly advance therapeutic approaches to chronic pain. PMID:16982005

Test-Retest Reliability of fMRI Brain Activity during Memory Encoding

PubMed Central

Brandt, David J.; Sommer, Jens; Krach, Sören; Bedenbender, Johannes; Kircher, Tilo; Paulus, Frieder M.; Jansen, Andreas

2013-01-01

The mechanisms underlying hemispheric specialization of memory are not completely understood. Functional magnetic resonance imaging (fMRI) can be used to develop and test models of hemispheric specialization. In particular for memory tasks however, the interpretation of fMRI results is often hampered by the low reliability of the data. In the present study we therefore analyzed the test-retest reliability of fMRI brain activation related to an implicit memory encoding task, with a particular focus on brain activity of the medial temporal lobe (MTL). Fifteen healthy subjects were scanned with fMRI on two sessions (average retest interval 35 days) using a commonly applied novelty encoding paradigm contrasting known and unknown stimuli. To assess brain lateralization, we used three different stimuli classes that differed in their verbalizability (words, scenes, fractals). Test-retest reliability of fMRI brain activation was assessed by an intraclass-correlation coefficient (ICC), describing the stability of inter-individual differences in the brain activation magnitude over time. We found as expected a left-lateralized brain activation network for the words paradigm, a bilateral network for the scenes paradigm, and predominantly right-hemispheric brain activation for the fractals paradigm. Although these networks were consistently activated in both sessions on the group level, across-subject reliabilities were only poor to fair (ICCs ≤ 0.45). Overall, the highest ICC values were obtained for the scenes paradigm, but only in strongly activated brain regions. In particular the reliability of brain activity of the MTL was poor for all paradigms. In conclusion, for novelty encoding paradigms the interpretation of fMRI results on a single subject level is hampered by its low reliability. More studies are needed to optimize the retest reliability of fMRI activation for memory tasks. PMID:24367338

Diffusion MRI at 25: Exploring brain tissue structure and function

PubMed Central

Bihan, Denis Le; Johansen-Berg, Heidi

2013-01-01

Diffusion MRI (or dMRI) came into existence in the mid-1980s. During the last 25 years, diffusion MRI has been extraordinarily successful (with more than 300,000 entries on Google Scholar for diffusion MRI). Its main clinical domain of application has been neurological disorders, especially for the management of patients with acute stroke. It is also rapidly becoming a standard for white matter disorders, as diffusion tensor imaging (DTI) can reveal abnormalities in white matter fiber structure and provide outstanding maps of brain connectivity. The ability to visualize anatomical connections between different parts of the brain, non-invasively and on an individual basis, has emerged as a major breakthrough for neurosciences. The driving force of dMRI is to monitor microscopic, natural displacements of water molecules that occur in brain tissues as part of the physical diffusion process. Water molecules are thus used as a probe that can reveal microscopic details about tissue architecture, either normal or in a diseased state. PMID:22120012

Changes of Visual Pathway and Brain Connectivity in Glaucoma: A Systematic Review

PubMed Central

Nuzzi, Raffaele; Dallorto, Laura; Rolle, Teresa

2018-01-01

Background: Glaucoma is a leading cause of irreversible blindness worldwide. The increasing interest in the involvement of the cortical visual pathway in glaucomatous patients is due to the implications in recent therapies, such as neuroprotection and neuroregeneration. Objective: In this review, we outline the current understanding of brain structural, functional, and metabolic changes detected with the modern techniques of neuroimaging in glaucomatous subjects. Methods: We screened MEDLINE, EMBASE, CINAHL, CENTRAL, LILACS, Trip Database, and NICE for original contributions published until 31 October 2017. Studies with at least six patients affected by any type of glaucoma were considered. We included studies using the following neuroimaging techniques: functional Magnetic Resonance Imaging (fMRI), resting-state fMRI (rs-fMRI), magnetic resonance spectroscopy (MRS), voxel- based Morphometry (VBM), surface-based Morphometry (SBM), diffusion tensor MRI (DTI). Results: Over a total of 1,901 studies, 56 case series with a total of 2,381 patients were included. Evidence of neurodegenerative process in glaucomatous patients was found both within and beyond the visual system. Structural alterations in visual cortex (mainly reduced cortex thickness and volume) have been demonstrated with SBM and VBM; these changes were not limited to primary visual cortex but also involved association visual areas. Other brain regions, associated with visual function, demonstrated a certain grade of increased or decreased gray matter volume. Functional and metabolic abnormalities resulted within primary visual cortex in all studies with fMRI and MRS. Studies with rs-fMRI found disrupted connectivity between the primary and higher visual cortex and between visual cortex and associative visual areas in the task-free state of glaucomatous patients. Conclusions: This review contributes to the better understanding of brain abnormalities in glaucoma. It may stimulate further speculation about brain plasticity at a later age and therapeutic strategies, such as the prevention of cortical degeneration in patients with glaucoma. Structural, functional, and metabolic neuroimaging methods provided evidence of changes throughout the visual pathway in glaucomatous patients. Other brain areas, not directly involved in the processing of visual information, also showed alterations. PMID:29896087

MRI-based comparative study of different mild cognitive impairment subtypes: protocol for an observational case-control study.

PubMed

Yu, Yang; Zhao, Weina; Li, Siou; Yin, Changhao

2017-03-08

Amnestic mild cognitive impairment (aMCI) and vascular mild cognitive impairment (VaMCI) comprise the 2 main types of mild cognitive impairment (MCI). The first condition generally progresses to Alzheimer's disease, whereas the second is likely to develop into vascular dementia (VD). The brain structure and function of patients with MCI differ from those of normal elderly individuals. However, whether brain structures or functions differ between these 2 MCI subtypes has not been studied. This study is designed to analyse neuroimages of brain in patients with VaMCI and aMCI using multimodality MRI (structural MRI (sMRI), functional MRI and diffusion tensor imaging (DTI)). In this study, 80 participants diagnosed with aMCI, 80 participants diagnosed with VaMCI, and 80 age-matched, gender-matched and education-matched normal controls (NCs) will be recruited to the Hongqi Hospital of Mudanjiang Medical University, Heilongjiang, China. All participants will undergo neuroimaging and neuropsychological evaluations. The primary outcome measures will be (1) microstructural alterations revealed by multimodal MRIs, including sMRI, resting-state functional MRI and DTI; and (2) a neuropsychological evaluation, including the Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), Auditory Verbal Learning Test (AVLT), Memory and Executive Screening (MES), trail making test, Stroop colour naming condition and Clinical Dementia Rating (CDR) scale, to evaluate global cognition, memory function, attention, visuospatial skills, processing speed, executive function and emotion, respectively. NCT02706210; Pre-results. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Susceptibility-based functional brain mapping by 3D deconvolution of an MR-phase activation map.

PubMed

Chen, Zikuan; Liu, Jingyu; Calhoun, Vince D

2013-05-30

The underlying source of T2*-weighted magnetic resonance imaging (T2*MRI) for brain imaging is magnetic susceptibility (denoted by χ). T2*MRI outputs a complex-valued MR image consisting of magnitude and phase information. Recent research has shown that both the magnitude and the phase images are morphologically different from the source χ, primarily due to 3D convolution, and that the source χ can be reconstructed from complex MR images by computed inverse MRI (CIMRI). Thus, we can obtain a 4D χ dataset from a complex 4D MR dataset acquired from a brain functional MRI study by repeating CIMRI to reconstruct 3D χ volumes at each timepoint. Because the reconstructed χ is a more direct representation of neuronal activity than the MR image, we propose a method for χ-based functional brain mapping, which is numerically characterised by a temporal correlation map of χ responses to a stimulant task. Under the linear imaging conditions used for T2*MRI, we show that the χ activation map can be calculated from the MR phase map by CIMRI. We validate our approach using numerical simulations and Gd-phantom experiments. We also analyse real data from a finger-tapping visuomotor experiment and show that the χ-based functional mapping provides additional activation details (in the form of positive and negative correlation patterns) beyond those generated by conventional MR-magnitude-based mapping. Copyright © 2013 Elsevier B.V. All rights reserved.

A reliability study on brain activation during active and passive arm movements supported by an MRI-compatible robot.

PubMed

Estévez, Natalia; Yu, Ningbo; Brügger, Mike; Villiger, Michael; Hepp-Reymond, Marie-Claude; Riener, Robert; Kollias, Spyros

2014-11-01

In neurorehabilitation, longitudinal assessment of arm movement related brain function in patients with motor disability is challenging due to variability in task performance. MRI-compatible robots monitor and control task performance, yielding more reliable evaluation of brain function over time. The main goals of the present study were first to define the brain network activated while performing active and passive elbow movements with an MRI-compatible arm robot (MaRIA) in healthy subjects, and second to test the reproducibility of this activation over time. For the fMRI analysis two models were compared. In model 1 movement onset and duration were included, whereas in model 2 force and range of motion were added to the analysis. Reliability of brain activation was tested with several statistical approaches applied on individual and group activation maps and on summary statistics. The activated network included mainly the primary motor cortex, primary and secondary somatosensory cortex, superior and inferior parietal cortex, medial and lateral premotor regions, and subcortical structures. Reliability analyses revealed robust activation for active movements with both fMRI models and all the statistical methods used. Imposed passive movements also elicited mainly robust brain activation for individual and group activation maps, and reliability was improved by including additional force and range of motion using model 2. These findings demonstrate that the use of robotic devices, such as MaRIA, can be useful to reliably assess arm movement related brain activation in longitudinal studies and may contribute in studies evaluating therapies and brain plasticity following injury in the nervous system.

Cortical thickness and surface area correlates with cognitive dysfunction among first-episode psychosis patients.

PubMed

Haring, L; Müürsepp, A; Mõttus, R; Ilves, P; Koch, K; Uppin, K; Tarnovskaja, J; Maron, E; Zharkovsky, A; Vasar, E; Vasar, V

2016-07-01

In studies using magnetic resonance imaging (MRI), some have reported specific brain structure-function relationships among first-episode psychosis (FEP) patients, but findings are inconsistent. We aimed to localize the brain regions where cortical thickness (CTh) and surface area (cortical area; CA) relate to neurocognition, by performing an MRI on participants and measuring their neurocognitive performance using the Cambridge Neuropsychological Test Automated Battery (CANTAB), in order to investigate any significant differences between FEP patients and control subjects (CS). Exploration of potential correlations between specific cognitive functions and brain structure was performed using CANTAB computer-based neurocognitive testing and a vertex-by-vertex whole-brain MRI analysis of 63 FEP patients and 30 CS. Significant correlations were found between cortical parameters in the frontal, temporal, cingular and occipital brain regions and performance in set-shifting, working memory manipulation, strategy usage and sustained attention tests. These correlations were significantly dissimilar between FEP patients and CS. Significant correlations between CTh and CA with neurocognitive performance were localized in brain areas known to be involved in cognition. The results also suggested a disrupted structure-function relationship in FEP patients compared with CS.

Reproducibility assessment of brain responses to visual food stimuli in adults with overweight and obesity.

PubMed

Drew Sayer, R; Tamer, Gregory G; Chen, Ningning; Tregellas, Jason R; Cornier, Marc-Andre; Kareken, David A; Talavage, Thomas M; McCrory, Megan A; Campbell, Wayne W

2016-10-01

The brain's reward system influences ingestive behavior and subsequently obesity risk. Functional magnetic resonance imaging (fMRI) is a common method for investigating brain reward function. This study sought to assess the reproducibility of fasting-state brain responses to visual food stimuli using BOLD fMRI. A priori brain regions of interest included bilateral insula, amygdala, orbitofrontal cortex, caudate, and putamen. Fasting-state fMRI and appetite assessments were completed by 28 women (n = 16) and men (n = 12) with overweight or obesity on 2 days. Reproducibility was assessed by comparing mean fasting-state brain responses and measuring test-retest reliability of these responses on the two testing days. Mean fasting-state brain responses on day 2 were reduced compared with day 1 in the left insula and right amygdala, but mean day 1 and day 2 responses were not different in the other regions of interest. With the exception of the left orbitofrontal cortex response (fair reliability), test-retest reliabilities of brain responses were poor or unreliable. fMRI-measured responses to visual food cues in adults with overweight or obesity show relatively good mean-level reproducibility but considerable within-subject variability. Poor test-retest reliability reduces the likelihood of observing true correlations and increases the necessary sample sizes for studies. © 2016 The Obesity Society.

Three-dimensional functional magnetic resonance imaging of human brain on a clinical 1.5-T scanner.

PubMed Central

van Gelderen, P; Ramsey, N F; Liu, G; Duyn, J H; Frank, J A; Weinberger, D R; Moonen, C T

1995-01-01

Functional magnetic resonance imaging (fMRI) is a tool for mapping brain function that utilizes neuronal activity-induced changes in blood oxygenation. An efficient three-dimensional fMRI method is presented for imaging brain activity on conventional, widely available, 1.5-T scanners, without additional hardware. This approach uses large magnetic susceptibility weighting based on the echo-shifting principle combined with multiple gradient echoes per excitation. Motor stimulation, induced by self-paced finger tapping, reliably produced significant signal increase in the hand region of the contralateral primary motor cortex in every subject tested. Images Fig. 2 Fig. 3 PMID:7624341

Large-scale topology and the default mode network in the mouse connectome

PubMed Central

Stafford, James M.; Jarrett, Benjamin R.; Miranda-Dominguez, Oscar; Mills, Brian D.; Cain, Nicholas; Mihalas, Stefan; Lahvis, Garet P.; Lattal, K. Matthew; Mitchell, Suzanne H.; David, Stephen V.; Fryer, John D.; Nigg, Joel T.; Fair, Damien A.

2014-01-01

Noninvasive functional imaging holds great promise for serving as a translational bridge between human and animal models of various neurological and psychiatric disorders. However, despite a depth of knowledge of the cellular and molecular underpinnings of atypical processes in mouse models, little is known about the large-scale functional architecture measured by functional brain imaging, limiting translation to human conditions. Here, we provide a robust processing pipeline to generate high-resolution, whole-brain resting-state functional connectivity MRI (rs-fcMRI) images in the mouse. Using a mesoscale structural connectome (i.e., an anterograde tracer mapping of axonal projections across the mouse CNS), we show that rs-fcMRI in the mouse has strong structural underpinnings, validating our procedures. We next directly show that large-scale network properties previously identified in primates are present in rodents, although they differ in several ways. Last, we examine the existence of the so-called default mode network (DMN)—a distributed functional brain system identified in primates as being highly important for social cognition and overall brain function and atypically functionally connected across a multitude of disorders. We show the presence of a potential DMN in the mouse brain both structurally and functionally. Together, these studies confirm the presence of basic network properties and functional networks of high translational importance in structural and functional systems in the mouse brain. This work clears the way for an important bridge measurement between human and rodent models, enabling us to make stronger conclusions about how regionally specific cellular and molecular manipulations in mice relate back to humans. PMID:25512496

Category representations in the brain are both discretely localized and widely distributed.

PubMed

Shehzad, Zarrar; McCarthy, Gregory

2018-06-01

Whether category information is discretely localized or represented widely in the brain remains a contentious issue. Initial functional MRI studies supported the localizationist perspective that category information is represented in discrete brain regions. More recent fMRI studies using machine learning pattern classification techniques provide evidence for widespread distributed representations. However, these latter studies have not typically accounted for shared information. Here, we find strong support for distributed representations when brain regions are considered separately. However, localized representations are revealed by using analytical methods that separate unique from shared information among brain regions. The distributed nature of shared information and the localized nature of unique information suggest that brain connectivity may encourage spreading of information but category-specific computations are carried out in distinct domain-specific regions. NEW & NOTEWORTHY Whether visual category information is localized in unique domain-specific brain regions or distributed in many domain-general brain regions is hotly contested. We resolve this debate by using multivariate analyses to parse functional MRI signals from different brain regions into unique and shared variance. Our findings support elements of both models and show information is initially localized and then shared among other regions leading to distributed representations being observed.

Advanced Connectivity Analysis (ACA): a Large Scale Functional Connectivity Data Mining Environment.

PubMed

Chen, Rong; Nixon, Erika; Herskovits, Edward

2016-04-01

Using resting-state functional magnetic resonance imaging (rs-fMRI) to study functional connectivity is of great importance to understand normal development and function as well as a host of neurological and psychiatric disorders. Seed-based analysis is one of the most widely used rs-fMRI analysis methods. Here we describe a freely available large scale functional connectivity data mining software package called Advanced Connectivity Analysis (ACA). ACA enables large-scale seed-based analysis and brain-behavior analysis. It can seamlessly examine a large number of seed regions with minimal user input. ACA has a brain-behavior analysis component to delineate associations among imaging biomarkers and one or more behavioral variables. We demonstrate applications of ACA to rs-fMRI data sets from a study of autism.

Real-Time fMRI in Neuroscience Research and Its Use in Studying the Aging Brain

PubMed Central

Rana, Mohit; Varan, Andrew Q.; Davoudi, Anis; Cohen, Ronald A.; Sitaram, Ranganatha; Ebner, Natalie C.

2016-01-01

Cognitive decline is a major concern in the aging population. It is normative to experience some deterioration in cognitive abilities with advanced age such as related to memory performance, attention distraction to interference, task switching, and processing speed. However, intact cognitive functioning in old age is important for leading an independent day-to-day life. Thus, studying ways to counteract or delay the onset of cognitive decline in aging is crucial. The literature offers various explanations for the decline in cognitive performance in aging; among those are age-related gray and white matter atrophy, synaptic degeneration, blood flow reduction, neurochemical alterations, and change in connectivity patterns with advanced age. An emerging literature on neurofeedback and Brain Computer Interface (BCI) reports exciting results supporting the benefits of volitional modulation of brain activity on cognition and behavior. Neurofeedback studies based on real-time functional magnetic resonance imaging (rtfMRI) have shown behavioral changes in schizophrenia and behavioral benefits in nicotine addiction. This article integrates research on cognitive and brain aging with evidence of brain and behavioral modification due to rtfMRI neurofeedback. We offer a state-of-the-art description of the rtfMRI technique with an eye towards its application in aging. We present preliminary results of a feasibility study exploring the possibility of using rtfMRI to train older adults to volitionally control brain activity. Based on these first findings, we discuss possible implementations of rtfMRI neurofeedback as a novel technique to study and alleviate cognitive decline in healthy and pathological aging. PMID:27803662

Validation of brain-derived signals in near-infrared spectroscopy through multivoxel analysis of concurrent functional magnetic resonance imaging.

PubMed

Moriguchi, Yoshiya; Noda, Takamasa; Nakayashiki, Kosei; Takata, Yohei; Setoyama, Shiori; Kawasaki, Shingo; Kunisato, Yoshihiko; Mishima, Kazuo; Nakagome, Kazuyuki; Hanakawa, Takashi

2017-10-01

Near-infrared spectroscopy (NIRS) is a convenient and safe brain-mapping tool. However, its inevitable confounding with hemodynamic responses outside the brain, especially in the frontotemporal head, has questioned its validity. Some researchers attempted to validate NIRS signals through concurrent measurements with functional magnetic resonance imaging (fMRI), but, counterintuitively, NIRS signals rarely correlate with local fMRI signals in NIRS channels, although both mapping techniques should measure the same hemoglobin concentration. Here, we tested a novel hypothesis that different voxels within the scalp and the brain tissues might have substantially different hemoglobin absorption rates of near-infrared light, which might differentially contribute to NIRS signals across channels. Therefore, we newly applied a multivariate approach, a partial least squares regression, to explain NIRS signals with multivoxel information from fMRI within the brain and soft tissues in the head. We concurrently obtained fMRI and NIRS signals in 9 healthy human subjects engaging in an n-back task. The multivariate fMRI model was quite successfully able to predict the NIRS signals by cross-validation (interclass correlation coefficient = ∼0.85). This result confirmed that fMRI and NIRS surely measure the same hemoglobin concentration. Additional application of Monte-Carlo permutation tests confirmed that the model surely reflects temporal and spatial hemodynamic information, not random noise. After this thorough validation, we calculated the ratios of the contributions of the brain and soft-tissue hemodynamics to the NIRS signals, and found that the contribution ratios were quite different across different NIRS channels in reality, presumably because of the structural complexity of the frontotemporal regions. Hum Brain Mapp 38:5274-5291, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Brain regions implicated in inhibitory control and appetite regulation are activated in response to food portion size and energy density in children.

PubMed

English, L K; Fearnbach, S N; Lasschuijt, M; Schlegel, A; Anderson, K; Harris, S; Wilson, S J; Fisher, J O; Savage, J S; Rolls, B J; Keller, K L

2016-10-01

Large portions of energy-dense foods drive energy intake but the brain mechanisms underlying this effect are not clear. Our main objective was to investigate brain function in response to food images varied by portion size (PS) and energy density (ED) in children using functional magnetic resonance imaging (fMRI). Blood-oxygen-level-dependent (BOLD) fMRI was completed in 36 children (ages 7-10 years) after a 2-h fast while viewing food images at two levels of PS (Large PS, Small PS) and two levels of ED (High ED, Low ED). Children rated perceived fullness pre- and post-fMRI, as well as liking of images on visual analog scales post-fMRI. Anthropometrics were completed 4 weeks before the fMRI. Large PS vs Small PS and High ED vs Low ED were compared with region-of-interest analyses using Brain Voyager v 2.8. Region-of-interest analyses revealed that activation in the right inferior frontal gyrus (P=0.03) was greater for Large PS vs Small PS. Activation was reduced for High ED vs Low ED in the left hypothalamus (P=0.03). Main effects were no longer significant after adjustment for pre-fMRI fullness and liking ratings (PS, P=0.92; ED, P=0.58). This is the first fMRI study to report increased activation to large portions in a brain region that is involved in inhibitory control. These findings may contribute to understanding why some children overeat when presented with large portions of palatable food.

Functional Magnetic Resonance Imaging Networks Induced by Intracranial Stimulation May Help Defining the Epileptogenic Zone

PubMed Central

Zhang, Myron; Avitsian, Rafi; Bhattacharyya, Pallab; Bulacio, Juan; Cendes, Fernando; Enatsu, Rei; Lowe, Mark; Najm, Imad; Nair, Dileep; Phillips, Michael; Gonzalez-Martinez, Jorge

2014-01-01

Abstract Patients with medically intractable epilepsy often undergo invasive evaluation and surgery, with a 50% success rate. The low success rate is likely due to poor identification of the epileptogenic zone (EZ), the brain area causing seizures. This work introduces a new method using functional magnetic resonance imaging (fMRI) with simultaneous direct electrical stimulation of the brain that could help localize the EZ, performed in five patients with medically intractable epilepsy undergoing invasive evaluation with intracranial depth electrodes. Stimulation occurred in a location near the hypothesized EZ and a location away. Electrical recordings in response to stimulation were recorded and compared to fMRI. Multiple stimulation parameters were varied, like current and frequency. The brain areas showing fMRI response were compared with the areas resected and the success of surgery. Robust fMRI maps of activation networks were easily produced, which also showed a significant but weak positive correlation between quantitative measures of blood-oxygen-level-dependent (BOLD) activity and measures of electrical activity in response to direct electrical stimulation (mean correlation coefficient of 0.38 for all acquisitions that produced a strong BOLD response). For four patients with outcome data at 6 months, successful surgical outcome is consistent with the resection of brain areas containing high local fMRI activity. In conclusion, this method demonstrates the feasibility of simultaneous direct electrical stimulation and fMRI in humans, which allows the study of brain connectivity with high resolution and full spatial coverage. This innovative technique could be used to better define the localization and extension of the EZ in intractable epilepsies, as well as for other functional neurosurgical procedures. PMID:24735069

Novel frontiers in ultra-structural and molecular MRI of the brain.

PubMed

Duyn, Jeff H; Koretsky, Alan P

2011-08-01

Recent developments in the MRI of the brain continue to expand its use in basic and clinical neuroscience. This review highlights some areas of recent progress. Higher magnetic field strengths and improved signal detectors have allowed improved visualization of the various properties of the brain, facilitating the anatomical definition of function-specific areas and their connections. For example, by sensitizing the MRI signal to the magnetic susceptibility of tissue, it is starting to become possible to reveal the laminar structure of the cortex and identify millimeter-scale fiber bundles. Using exogenous contrast agents, and innovative ways to manipulate contrast, it is becoming possible to highlight specific fiber tracts and cell populations. These techniques are bringing us closer to understanding the evolutionary blueprint of the brain, improving the detection and characterization of disease, and help to guide treatment. Recent MRI techniques are leading to more detailed and more specific contrast in the study of the brain.

Connectomic markers of symptom severity in sport-related concussion: Whole-brain analysis of resting-state fMRI.

PubMed

Churchill, Nathan W; Hutchison, Michael G; Graham, Simon J; Schweizer, Tom A

2018-01-01

Concussion is associated with significant adverse effects within the first week post-injury, including physical complaints and altered cognition, sleep and mood. It is currently unknown whether these subjective disturbances have reliable functional brain correlates. Resting-state functional magnetic resonance imaging (rs-fMRI) has been used to measure functional connectivity of individuals after traumatic brain injury, but less is known about the relationship between functional connectivity and symptom assessments after a sport concussion. In this study, rs-fMRI was used to evaluate whole-brain functional connectivity for seventy (70) university-level athletes, including 35 with acute concussion and 35 healthy matched controls. Univariate analyses showed that greater symptom severity was mainly associated with lower pairwise connectivity in frontal, temporal and insular regions, along with higher connectivity in a sparser set of cerebellar regions. A novel multivariate approach also extracted two components that showed reliable covariation with symptom severity: (1) a network of frontal, temporal and insular regions where connectivity was negatively correlated with symptom severity (replicating the univariate findings); and (2) a network with anti-correlated elements of the default-mode network and sensorimotor system, where connectivity was positively correlated with symptom severity. These findings support the presence of connectomic signatures of symptom complaints following a sport-related concussion, including both increased and decreased functional connectivity within distinct functional brain networks.

Local Brain Activity Differences Between Herpes Zoster and Postherpetic Neuralgia Patients: A Resting-State Functional MRI Study.

PubMed

Cao, Song; Li, Ying; Deng, Wenwen; Qin, Bangyong; Zhang, Yi; Xie, Peng; Yuan, Jie; Yu, Buwei; Yu, Tian

2017-07-01

Herpes zoster (HZ) can develop into postherpetic neuralgia (PHN), both of which are painful diseases. PHN patients suffer chronic pain and emotional disorders. Previous studies showed that the PHN brain displayed abnormal activity and structural change, but the difference in brain activity between HZ and PHN is still not known. To identify regional brain activity changes in HZ and PHN brains with resting-state functional magnetic resonance imaging (rs-fMRI) technique, and to observe the differences between HZ and PHN patients. Observational study. University hospital. Regional homogeneity (ReHo) and fractional aptitude of low-frequency fluctuation (fALFF) methods were employed to analysis resting-state brain activity. Seventy-three age and gender matched patients (50 HZ, 23 PHN) and 55 healthy controls were enrolled. ReHo and fALFF changes were analyzed to detect the functional abnormality in HZ and PHN brains. Compared with healthy controls, HZ and PHN patients exhibited abnormal ReHo and fALFF values in classic pain-related brain regions (such as the frontal lobe, thalamus, insular, and cerebellum) as well as the brainstem, limbic lobe, and temporal lobe. When HZ developed to PHN, the activity in the vast area of the cerebellum significantly increased while that of some regions in the occipital lobe, temporal lobe, parietal lobe, and limbic lobe showed an apparent decrease. (a) Relatively short pain duration (mean 12.2 months) and small sample size (n = 23) for PHN group. (b) Comparisons at different time points (with paired t-tests) for each patient may minimize individual differences. HZ and PHN induced local brain activity changed in the pain matrix, brainstem, and limbic system. HZ chronification induced functional change in the cerebellum, occipital lobe, temporal lobe, parietal lobe, and limbic lobe. These brain activity changes may be correlated with HZ-PHN transition. Herpes zoster, postherpetic neuralgia, resting-state fMRI (rs-fMRI), regional homogeneity (ReHo), fractional aptitude of low-frequency fluctuation (fALFF).

Infant fMRI: A Model System for Cognitive Neuroscience.

PubMed

Ellis, Cameron T; Turk-Browne, Nicholas B

2018-05-01

Our understanding of the typical human brain has benefitted greatly from studying different kinds of brains and their associated behavioral repertoires, including animal models and neuropsychological patients. This same comparative perspective can be applied to early development - the environment, behavior, and brains of infants provide a model system for understanding how the mature brain works. This approach requires noninvasive methods for measuring brain function in awake, behaving infants. fMRI is becoming increasingly viable for this purpose, with the unique ability to precisely measure the entire brain, including both cortical and subcortical structures. Here we discuss potential lessons from infant fMRI for several domains of adult cognition and consider the challenges of conducting such research and how they might be mitigated. Copyright © 2018 Elsevier Ltd. All rights reserved.

Fuzzy cluster analysis of high-field functional MRI data.

PubMed

Windischberger, Christian; Barth, Markus; Lamm, Claus; Schroeder, Lee; Bauer, Herbert; Gur, Ruben C; Moser, Ewald

2003-11-01

Functional magnetic resonance imaging (fMRI) based on blood-oxygen level dependent (BOLD) contrast today is an established brain research method and quickly gains acceptance for complementary clinical diagnosis. However, neither the basic mechanisms like coupling between neuronal activation and haemodynamic response are known exactly, nor can the various artifacts be predicted or controlled. Thus, modeling functional signal changes is non-trivial and exploratory data analysis (EDA) may be rather useful. In particular, identification and separation of artifacts as well as quantification of expected, i.e. stimulus correlated, and novel information on brain activity is important for both, new insights in neuroscience and future developments in functional MRI of the human brain. After an introduction on fuzzy clustering and very high-field fMRI we present several examples where fuzzy cluster analysis (FCA) of fMRI time series helps to identify and locally separate various artifacts. We also present and discuss applications and limitations of fuzzy cluster analysis in very high-field functional MRI: differentiate temporal patterns in MRI using (a) a test object with static and dynamic parts, (b) artifacts due to gross head motion artifacts. Using a synthetic fMRI data set we quantitatively examine the influences of relevant FCA parameters on clustering results in terms of receiver-operator characteristics (ROC) and compare them with a commonly used model-based correlation analysis (CA) approach. The application of FCA in analyzing in vivo fMRI data is shown for (a) a motor paradigm, (b) data from multi-echo imaging, and (c) a fMRI study using mental rotation of three-dimensional cubes. We found that differentiation of true "neural" from false "vascular" activation is possible based on echo time dependence and specific activation levels, as well as based on their signal time-course. Exploratory data analysis methods in general and fuzzy cluster analysis in particular may help to identify artifacts and add novel and unexpected information valuable for interpretation, classification and characterization of functional MRI data which can be used to design new data acquisition schemes, stimulus presentations, neuro(physio)logical paradigms, as well as to improve quantitative biophysical models.

The heritability of the functional connectome is robust to common nonlinear registration methods

NASA Astrophysics Data System (ADS)

Hafzalla, George W.; Prasad, Gautam; Baboyan, Vatche G.; Faskowitz, Joshua; Jahanshad, Neda; McMahon, Katie L.; de Zubicaray, Greig I.; Wright, Margaret J.; Braskie, Meredith N.; Thompson, Paul M.

2016-03-01

Nonlinear registration algorithms are routinely used in brain imaging, to align data for inter-subject and group comparisons, and for voxelwise statistical analyses. To understand how the choice of registration method affects maps of functional brain connectivity in a sample of 611 twins, we evaluated three popular nonlinear registration methods: Advanced Normalization Tools (ANTs), Automatic Registration Toolbox (ART), and FMRIB's Nonlinear Image Registration Tool (FNIRT). Using both structural and functional MRI, we used each of the three methods to align the MNI152 brain template, and 80 regions of interest (ROIs), to each subject's T1-weighted (T1w) anatomical image. We then transformed each subject's ROIs onto the associated resting state functional MRI (rs-fMRI) scans and computed a connectivity network or functional connectome for each subject. Given the different degrees of genetic similarity between pairs of monozygotic (MZ) and same-sex dizygotic (DZ) twins, we used structural equation modeling to estimate the additive genetic influences on the elements of the function networks, or their heritability. The functional connectome and derived statistics were relatively robust to nonlinear registration effects.

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

PubMed

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

2016-01-01

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

Brain Functional Connectivity in MS: An EEG-NIRS Study

DTIC Science & Technology

2015-10-01

electrical (EEG) and blood volume and blood oxygen-based (NIRS and fMRI ) signals, and to use the results to help optimize blood oxygen level...dependent (BOLD) fMRI analyses of brain activity. Participants will be patients with MS (n=25) and healthy demographically matched controls (n=25) who will...undergo standardized evaluations and imaging using combined EEG-NIRS- fMRI . EEG-NIRS data will be used to construct maps of neurovascular coupling

Fast-GPU-PCC: A GPU-Based Technique to Compute Pairwise Pearson's Correlation Coefficients for Time Series Data-fMRI Study.

PubMed

Eslami, Taban; Saeed, Fahad

2018-04-20

Functional magnetic resonance imaging (fMRI) is a non-invasive brain imaging technique, which has been regularly used for studying brain’s functional activities in the past few years. A very well-used measure for capturing functional associations in brain is Pearson’s correlation coefficient. Pearson’s correlation is widely used for constructing functional network and studying dynamic functional connectivity of the brain. These are useful measures for understanding the effects of brain disorders on connectivities among brain regions. The fMRI scanners produce huge number of voxels and using traditional central processing unit (CPU)-based techniques for computing pairwise correlations is very time consuming especially when large number of subjects are being studied. In this paper, we propose a graphics processing unit (GPU)-based algorithm called Fast-GPU-PCC for computing pairwise Pearson’s correlation coefficient. Based on the symmetric property of Pearson’s correlation, this approach returns N ( N − 1 ) / 2 correlation coefficients located at strictly upper triangle part of the correlation matrix. Storing correlations in a one-dimensional array with the order as proposed in this paper is useful for further usage. Our experiments on real and synthetic fMRI data for different number of voxels and varying length of time series show that the proposed approach outperformed state of the art GPU-based techniques as well as the sequential CPU-based versions. We show that Fast-GPU-PCC runs 62 times faster than CPU-based version and about 2 to 3 times faster than two other state of the art GPU-based methods.

Relationship between brain lesion characteristics and communication in preschool children with cerebral palsy.

PubMed

Coleman, Andrea; Fiori, Simona; Weir, Kelly A; Ware, Robert S; Boyd, Roslyn N

2016-11-01

MRI shows promise as a prognostic tool for clinical findings such as gross motor function in children with cerebral palsy(CP), however the relationship with communication skills requires exploration. To examine the relationship between the type and severity of brain lesion on MRI and communication skills in children with CP. 131 children with CP (73 males(56%)), mean corrected age(SD) 28(5) months, Gross Motor Functional Classification System distribution: I=57(44%), II=14(11%), III=19(14%), IV=17(13%), V=24(18%). Children were assessed on the Communication and Symbolic Behavioral Scales Developmental Profile (CSBS-DP) Infant-Toddler Checklist. Structural MRI was analysed with reference to type and semi-quantitative assessment of the severity of brain lesion. Children were classified for motor type, distribution and GMFCS. The relationships between type/severity of brain lesion and communication ability were analysed using multivariable tobit regression. Children with periventricular white matter lesions had better speech than children with cortical/deep grey matter lesions (β=-2.6, 95%CI=-5.0, -0.2, p=0.04). Brain lesion severity on the semi-quantitative scale was related to overall communication skills (β=-0.9, 95%CI=-1.4, -0.5, p<0.001). Motor impairment better accounted for impairment in overall communication skills than brain lesion severity. Structural MRI has potential prognostic value for communication impairment in children with CP. WHAT THIS PAPER ADDS?: This is the first paper to explore important aspects of communication in relation to the type and severity of brain lesion on MRI in a representative cohort of preschool-aged children with CP. We found a relationship between the type of brain lesion and communication skills, children who had cortical and deep grey matter lesions had overall communication skills>1 SD below children with periventricular white matter lesions. Children with more severe brain lesions on MRI had poorer overall communication skills. Children with CP born at term had poorer communication than those born prematurely and were more likely to have cortical and deep grey matter lesions. Gross motor function better accounted for overall communication skills than the type of brain lesion or brain lesion severity. Copyright © 2016. Published by Elsevier Ltd.

Genetic and Diagnostic Biomarker Development in ASD Toddlers Using Resting State Functional MRI

DTIC Science & Technology

2016-09-01

networks during resting states. Autism spectrum disorder (ASD) begins prenatal, and early maldevelopment is present in many sites and systems that mediate...molecular and genomic evidence indicates autism spectrum disorder (ASD) begins prenatally, most likely by or before the late second trimester 10-15 as...ages 3 to 4 years. 2. KEYWORDS Autism spectrum disorder, ASD, early brain development, intrinsic functional brain networks, fMRI, infants, toddlers

Investigation of the Correlation Between Neurocognitive Function with Advanced Magnetic Resonance Imaging (MRI), Electroencephalography (EEG) in Patients with Traumatic Brain Injury Exposure: Neurocognitive function and advanced MRI and EEG

DTIC Science & Technology

2011-01-01

rotation soudaine , à la tête engendré par des forces externes. Des symptômes persistants tels que maux de tête, troubles du sommeil, problèmes...neuropsychological findings in veterans with traumatic brain injury and/or post traumatic stress disorder. Military Medicine. Brenner, L.A. et al . (2010

Novel MRI methodology to detect human whole-brain connectivity changes after ingestion of fructose or glucose

NASA Astrophysics Data System (ADS)

Tsao, Sinchai; Wilkins, Bryce; Page, Kathleen A.; Singh, Manbir

2012-03-01

A novel MRI protocol has been developed to investigate the differential effects of glucose or fructose consumption on whole-brain functional brain connectivity. A previous study has reported a decrease in the fMRI blood oxygen level dependent (BOLD) signal of the hypothalamus following glucose ingestion, but due to technical limitations, was restricted to a single slice covering the hypothalamus, and thus unable to detect whole-brain connectivity. In another previous study, a protocol was devised to acquire whole-brain fMRI data following food intake, but only after restricting image acquisition to an MR sampling or repetition time (TR) of 20s, making the protocol unsuitable to detect functional connectivity above 0.025Hz. We have successfully implemented a continuous 36-min, 40 contiguous slices, whole-brain BOLD acquisition protocol on a 3T scanner with TR=4.5s to ensure detection of up to 0.1Hz frequencies for whole-brain functional connectivity analysis. Human data were acquired first with ingestion of water only, followed by a glucose or fructose drink within the scanner, without interrupting the scanning. Whole-brain connectivity was analyzed using standard correlation methodology in the 0.01-0.1 Hz range. The correlation coefficient differences between fructose and glucose ingestion among targeted regions were converted to t-scores using the water-only correlation coefficients as a null condition. Results show a dramatic increase in the hypothalamic connectivity to the hippocampus, amygdala, insula, caudate and the nucleus accumben for fructose over glucose. As these regions are known to be key components of the feeding and reward brain circuits, these results suggest a preference for fructose ingestion.

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

PubMed

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.

Tau and Beta-Amyloid Deposition, Micro-Hemorrhage and Brain Function after Traumatic Brain Injury in War Veterans

DTIC Science & Technology

2016-10-01

tau PET imaging and 7T- MRI to the Australian Imaging Biomarkers and Lifestyle - Veterans study (AIBL-VETS) of post-traumatic stress disorder and...focal and widespread changes in white matter integrity. 4. 7T- MRI will reveal more extensive microhemorrhage than seen on 3T- MRI and this will relate...injury in war veterans. 6 | P a g e 1. Introduction The project will utilize tau, amyloid and FDG PET imaging, and MRI as well as clinical and

The implications of brain connectivity in the neuropsychology of autism

PubMed Central

Maximo, Jose O.; Cadena, Elyse J.; Kana, Rajesh K.

2014-01-01

Autism is a neurodevelopmental disorder that has been associated with atypical brain functioning. Functional connectivity MRI (fcMRI) studies examining neural networks in autism have seen an exponential rise over the last decade. Such investigations have led to characterization of autism as a distributed neural systems disorder. Studies have found widespread cortical underconnectivity, local overconnectivity, and mixed results suggesting disrupted brain connectivity as a potential neural signature of autism. In this review, we summarize the findings of previous fcMRI studies in autism with a detailed examination of their methodology, in order to better understand its potential and to delineate the pitfalls. We also address how a multimodal neuroimaging approach (incorporating different measures of brain connectivity) may help characterize the complex neurobiology of autism at a global level. Finally, we also address the potential of neuroimaging-based markers in assisting neuropsychological assessment of autism. The quest for a biomarker for autism is still ongoing, yet new findings suggest that aberrant brain connectivity may be a promising candidate. PMID:24496901

A human brain atlas derived via n-cut parcellation of resting-state and task-based fMRI data.

PubMed

James, George Andrew; Hazaroglu, Onder; Bush, Keith A

2016-02-01

The growth of functional MRI has led to development of human brain atlases derived by parcellating resting-state connectivity patterns into functionally independent regions of interest (ROIs). All functional atlases to date have been derived from resting-state fMRI data. But given that functional connectivity between regions varies with task, we hypothesized that an atlas incorporating both resting-state and task-based fMRI data would produce an atlas with finer characterization of task-relevant regions than an atlas derived from resting-state alone. To test this hypothesis, we derived parcellation atlases from twenty-nine healthy adult participants enrolled in the Cognitive Connectome project, an initiative to improve functional MRI's translation into clinical decision-making by mapping normative variance in brain-behavior relationships. Participants underwent resting-state and task-based fMRI spanning nine cognitive domains: motor, visuospatial, attention, language, memory, affective processing, decision-making, working memory, and executive function. Spatially constrained n-cut parcellation derived brain atlases using (1) all participants' functional data (Task) or (2) a single resting-state scan (Rest). An atlas was also derived from random parcellation for comparison purposes (Random). Two methods were compared: (1) a parcellation applied to the group's mean edge weights (mean), and (2) a two-stage approach with parcellation of individual edge weights followed by parcellation of mean binarized edges (two-stage). The resulting Task and Rest atlases had significantly greater similarity with each other (mean Jaccard indices JI=0.72-0.85) than with the Random atlases (JI=0.59-0.63; all p<0.001 after Bonferroni correction). Task and Rest atlas similarity was greatest for the two-stage method (JI=0.85), which has been shown as more robust than the mean method; these atlases also better reproduced voxelwise seed maps of the left dorsolateral prefrontal cortex during rest and performing the n-back working memory task (r=0.75-0.80) than the Random atlases (r=0.64-0.72), further validating their utility. We expected regions governing higher-order cognition (such as frontal and anterior temporal lobes) to show greatest difference between Task and Rest atlases; contrary to expectations, these areas had greatest similarity between atlases. Our findings indicate that atlases derived from parcellation of task-based and resting-state fMRI data are highly comparable, and existing resting-state atlases are suitable for task-based analyses. We introduce an anatomically labeled fMRI-derived whole-brain human atlas for future Cognitive Connectome analyses. Copyright © 2015 Elsevier Inc. All rights reserved.

Correlated gene expression and anatomical communication support synchronized brain activity in the mouse functional connectome.

PubMed

Mills, Brian D; Grayson, David S; Shunmugavel, Anandakumar; Miranda-Dominguez, Oscar; Feczko, Eric; Earl, Eric; Neve, Kim; Fair, Damien A

2018-05-22

Cognition and behavior depend on synchronized intrinsic brain activity that is organized into functional networks across the brain. Research has investigated how anatomical connectivity both shapes and is shaped by these networks, but not how anatomical connectivity interacts with intra-areal molecular properties to drive functional connectivity. Here, we present a novel linear model to explain functional connectivity by integrating systematically obtained measurements of axonal connectivity, gene expression, and resting state functional connectivity MRI in the mouse brain. The model suggests that functional connectivity arises from both anatomical links and inter-areal similarities in gene expression. By estimating these effects, we identify anatomical modules in which correlated gene expression and anatomical connectivity support functional connectivity. Along with providing evidence that not all genes equally contribute to functional connectivity, this research establishes new insights regarding the biological underpinnings of coordinated brain activity measured by BOLD fMRI. SIGNIFICANCE STATEMENT Efforts at characterizing the functional connectome with fMRI have risen exponentially over the last decade. Yet despite this rise, the biological underpinnings of these functional measurements are still largely unknown. The current report begins to fill this void by investigating the molecular underpinnings of the functional connectome through an integration of systematically obtained structural information and gene expression data throughout the rodent brain. We find that both white matter connectivity and similarity in regional gene expression relate to resting state functional connectivity. The current report furthers our understanding of the biological underpinnings of the functional connectome and provides a linear model that can be utilized to streamline preclinical animal studies of disease. Copyright © 2018 the authors.

The inclusion of functional connectivity information into fMRI-based neurofeedback improves its efficacy in the reduction of cigarette cravings.

PubMed

Kim, Dong-Youl; Yoo, Seung-Schik; Tegethoff, Marion; Meinlschmidt, Gunther; Lee, Jong-Hwan

2015-08-01

Real-time fMRI (rtfMRI) neurofeedback (NF) facilitates volitional control over brain activity and the modulation of associated mental functions. The NF signals of traditional rtfMRI-NF studies predominantly reflect neuronal activity within ROIs. In this study, we describe a novel rtfMRI-NF approach that includes a functional connectivity (FC) component in the NF signal (FC-added rtfMRI-NF). We estimated the efficacy of the FC-added rtfMRI-NF method by applying it to nicotine-dependent heavy smokers in an effort to reduce cigarette craving. ACC and medial pFC as well as the posterior cingulate cortex and precuneus are associated with cigarette craving and were chosen as ROIs. Fourteen heavy smokers were randomly assigned to receive one of two types of NF: traditional activity-based rtfMRI-NF or FC-added rtfMRI-NF. Participants received rtfMRI-NF training during two separate visits after overnight smoking cessation, and cigarette craving score was assessed. The FC-added rtfMRI-NF resulted in greater neuronal activity and increased FC between the targeted ROIs than the traditional activity-based rtfMRI-NF and resulted in lower craving score. In the FC-added rtfMRI-NF condition, the average of neuronal activity and FC was tightly associated with craving score (Bonferroni-corrected p = .028). However, in the activity-based rtfMRI-NF condition, no association was detected (uncorrected p > .081). Non-rtfMRI data analysis also showed enhanced neuronal activity and FC with FC-added NF than with activity-based NF. These results demonstrate that FC-added rtfMRI-NF facilitates greater volitional control over brain activity and connectivity and greater modulation of mental function than activity-based rtfMRI-NF.

Dynamic functional connectivity reveals altered variability in functional connectivity among patients with major depressive disorder.

PubMed

Demirtaş, Murat; Tornador, Cristian; Falcón, Carles; López-Solà, Marina; Hernández-Ribas, Rosa; Pujol, Jesús; Menchón, José M; Ritter, Petra; Cardoner, Narcis; Soriano-Mas, Carles; Deco, Gustavo

2016-08-01

Resting-state fMRI (RS-fMRI) has become a useful tool to investigate the connectivity structure of mental health disorders. In the case of major depressive disorder (MDD), recent studies regarding the RS-fMRI have found abnormal connectivity in several regions of the brain, particularly in the default mode network (DMN). Thus, the relevance of the DMN to self-referential thoughts and ruminations has made the use of the resting-state approach particularly important for MDD. The majority of such research has relied on the grand averaged functional connectivity measures based on the temporal correlations between the BOLD time series of various brain regions. We, in our study, investigated the variations in the functional connectivity over time at global and local level using RS-fMRI BOLD time series of 27 MDD patients and 27 healthy control subjects. We found that global synchronization and temporal stability were significantly increased in the MDD patients. Furthermore, the participants with MDD showed significantly increased overall average (static) functional connectivity (sFC) but decreased variability of functional connectivity (vFC) within specific networks. Static FC increased to predominance among the regions pertaining to the default mode network (DMN), while the decreased variability of FC was observed in the connections between the DMN and the frontoparietal network. Hum Brain Mapp 37:2918-2930, 2016. © 2016 Wiley Periodicals, Inc. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Living With Anxiety Disorders, Worried Sick | NIH MedlinePlus the Magazine

MedlinePlus

... behaviors. Using an imaging technique called functional MRI (fMRI), scientists are scanning the brain in action as ... Bishop of the University of California, Berkeley, uses fMRI to study people at high risk for anxiety ...

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

PubMed

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.

Combining self-organizing mapping and supervised affinity propagation clustering approach to investigate functional brain networks involved in motor imagery and execution with fMRI measurements.

PubMed

Zhang, Jiang; Liu, Qi; Chen, Huafu; Yuan, Zhen; Huang, Jin; Deng, Lihua; Lu, Fengmei; Zhang, Junpeng; Wang, Yuqing; Wang, Mingwen; Chen, Liangyin

2015-01-01

Clustering analysis methods have been widely applied to identifying the functional brain networks of a multitask paradigm. However, the previously used clustering analysis techniques are computationally expensive and thus impractical for clinical applications. In this study a novel method, called SOM-SAPC that combines self-organizing mapping (SOM) and supervised affinity propagation clustering (SAPC), is proposed and implemented to identify the motor execution (ME) and motor imagery (MI) networks. In SOM-SAPC, SOM was first performed to process fMRI data and SAPC is further utilized for clustering the patterns of functional networks. As a result, SOM-SAPC is able to significantly reduce the computational cost for brain network analysis. Simulation and clinical tests involving ME and MI were conducted based on SOM-SAPC, and the analysis results indicated that functional brain networks were clearly identified with different response patterns and reduced computational cost. In particular, three activation clusters were clearly revealed, which include parts of the visual, ME and MI functional networks. These findings validated that SOM-SAPC is an effective and robust method to analyze the fMRI data with multitasks.

Detecting activity-evoked pH changes in human brain

PubMed Central

Magnotta, Vincent A.; Heo, Hye-Young; Dlouhy, Brian J.; Dahdaleh, Nader S.; Follmer, Robin L.; Thedens, Daniel R.; Welsh, Michael J.; Wemmie, John A.

2012-01-01

Localized pH changes have been suggested to occur in the brain during normal function. However, the existence of such pH changes has also been questioned. Lack of methods for noninvasively measuring pH with high spatial and temporal resolution has limited insight into this issue. Here we report that a magnetic resonance imaging (MRI) strategy, T1 relaxation in the rotating frame (T1ρ), is sufficiently sensitive to detect widespread pH changes in the mouse and human brain evoked by systemically manipulating carbon dioxide or bicarbonate. Moreover, T1ρ detected a localized acidosis in the human visual cortex induced by a flashing checkerboard. Lactate measurements and pH-sensitive 31P spectroscopy at the same site also identified a localized acidosis. Consistent with the established role for pH in blood flow recruitment, T1ρ correlated with blood oxygenation level-dependent contrast commonly used in functional MRI. However, T1ρ was not directly sensitive to blood oxygen content. These observations indicate that localized pH fluctuations occur in the human brain during normal function. Furthermore, they suggest a unique functional imaging strategy based on pH that is independent of traditional functional MRI contrast mechanisms. PMID:22566645

Using fMRI to Study Conceptual Change: Why and How?

ERIC Educational Resources Information Center

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

2012-01-01

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

Functional Brain Activity Changes after 4 Weeks Supplementation with a Multi-Vitamin/Mineral Combination: A Randomized, Double-Blind, Placebo-Controlled Trial Exploring Functional Magnetic Resonance Imaging and Steady-State Visual Evoked Potentials during Working Memory.

PubMed

White, David J; Cox, Katherine H M; Hughes, Matthew E; Pipingas, Andrew; Peters, Riccarda; Scholey, Andrew B

2016-01-01

This study explored the neurocognitive effects of 4 weeks daily supplementation with a multi-vitamin and -mineral combination (MVM) in healthy adults (aged 18-40 years). Using a randomized, double-blind, placebo-controlled design, participants underwent assessments of brain activity using functional Magnetic Resonance Imaging (fMRI; n = 32, 16 females) and Steady-State Visual Evoked Potential recordings (SSVEP; n = 39, 20 females) during working memory and continuous performance tasks at baseline and following 4 weeks of active MVM treatment or placebo. There were several treatment-related effects suggestive of changes in functional brain activity associated with MVM administration. SSVEP data showed latency reductions across centro-parietal regions during the encoding period of a spatial working memory task following 4 weeks of active MVM treatment. Complementary results were observed with the fMRI data, in which a subset of those completing fMRI assessment after SSVEP assessment ( n = 16) demonstrated increased BOLD response during completion of the Rapid Visual Information Processing task (RVIP) within regions of interest including bilateral parietal lobes. No treatment-related changes in fMRI data were observed in those who had not first undergone SSVEP assessment, suggesting these results may be most evident under conditions of fatigue. Performance on the working memory and continuous performance tasks did not significantly differ between treatment groups at follow-up. In addition, within the fatigued fMRI sample, increased RVIP BOLD response was correlated with the change in number of target detections as part of the RVIP task. This study provides preliminary evidence of changes in functional brain activity during working memory associated with 4 weeks of daily treatment with a multi-vitamin and -mineral combination in healthy adults, using two distinct but complementary measures of functional brain activity.

Functional Brain Activity Changes after 4 Weeks Supplementation with a Multi-Vitamin/Mineral Combination: A Randomized, Double-Blind, Placebo-Controlled Trial Exploring Functional Magnetic Resonance Imaging and Steady-State Visual Evoked Potentials during Working Memory

PubMed Central

White, David J.; Cox, Katherine H. M.; Hughes, Matthew E.; Pipingas, Andrew; Peters, Riccarda; Scholey, Andrew B.

2016-01-01

This study explored the neurocognitive effects of 4 weeks daily supplementation with a multi-vitamin and -mineral combination (MVM) in healthy adults (aged 18–40 years). Using a randomized, double-blind, placebo-controlled design, participants underwent assessments of brain activity using functional Magnetic Resonance Imaging (fMRI; n = 32, 16 females) and Steady-State Visual Evoked Potential recordings (SSVEP; n = 39, 20 females) during working memory and continuous performance tasks at baseline and following 4 weeks of active MVM treatment or placebo. There were several treatment-related effects suggestive of changes in functional brain activity associated with MVM administration. SSVEP data showed latency reductions across centro-parietal regions during the encoding period of a spatial working memory task following 4 weeks of active MVM treatment. Complementary results were observed with the fMRI data, in which a subset of those completing fMRI assessment after SSVEP assessment (n = 16) demonstrated increased BOLD response during completion of the Rapid Visual Information Processing task (RVIP) within regions of interest including bilateral parietal lobes. No treatment-related changes in fMRI data were observed in those who had not first undergone SSVEP assessment, suggesting these results may be most evident under conditions of fatigue. Performance on the working memory and continuous performance tasks did not significantly differ between treatment groups at follow-up. In addition, within the fatigued fMRI sample, increased RVIP BOLD response was correlated with the change in number of target detections as part of the RVIP task. This study provides preliminary evidence of changes in functional brain activity during working memory associated with 4 weeks of daily treatment with a multi-vitamin and -mineral combination in healthy adults, using two distinct but complementary measures of functional brain activity. PMID:27994548

Brain activation patterns elicited by the 'Faces Symbol Test' -- a pilot fMRI study.

PubMed

Grabner, Rh; Popotnig, F; Ropele, S; Neuper, C; Gorani, F; Petrovic, K; Ebner, F; Strasser-Fuchs, S; Fazekas, F; Enzinger, C

2008-04-01

The Faces Symbol Test (FST) has recently been proposed as a brief and patient-friendly screening instrument for the assessment of cognitive dysfunction in patients with multiple sclerosis (MS). However, in contrast to well-established MS screening tests such as the Paced Auditory Serial Addition Test, the neural correlates of the FST have not been investigated so far. In the present study, we developed a functional MRI (fMRI) version of the FST to provide first data on brain regions and networks involved in this test. A sample of 19 healthy participants completed a version of the FST adapted for fMRI, requiring matching of faces and symbols in a multiple choice test and two further experimental conditions drawing on cognitive subcomponents (face matching and symbol matching). Imaging data showed a differential involvement of a fronto-parieto-occipital network in the three conditions. The most demanding FST condition elicited brain activation patterns related with sustained attention and executive control. These results suggest that the FST recruits brain networks critical for higher-order cognitive functions often impaired in MS patients.

Resting-State Functional Connectivity in the Infant Brain: Methods, Pitfalls, and Potentiality.

PubMed

Mongerson, Chandler R L; Jennings, Russell W; Borsook, David; Becerra, Lino; Bajic, Dusica

2017-01-01

Early brain development is characterized by rapid growth and perpetual reconfiguration, driven by a dynamic milieu of heterogeneous processes. Postnatal brain plasticity is associated with increased vulnerability to environmental stimuli. However, little is known regarding the ontogeny and temporal manifestations of inter- and intra-regional functional connectivity that comprise functional brain networks. Resting-state functional magnetic resonance imaging (rs-fMRI) has emerged as a promising non-invasive neuroinvestigative tool, measuring spontaneous fluctuations in blood oxygen level dependent (BOLD) signal at rest that reflect baseline neuronal activity. Over the past decade, its application has expanded to infant populations providing unprecedented insight into functional organization of the developing brain, as well as early biomarkers of abnormal states. However, many methodological issues of rs-fMRI analysis need to be resolved prior to standardization of the technique to infant populations. As a primary goal, this methodological manuscript will (1) present a robust methodological protocol to extract and assess resting-state networks in early infancy using independent component analysis (ICA), such that investigators without previous knowledge in the field can implement the analysis and reliably obtain viable results consistent with previous literature; (2) review the current methodological challenges and ethical considerations associated with emerging field of infant rs-fMRI analysis; and (3) discuss the significance of rs-fMRI application in infants for future investigations of neurodevelopment in the context of early life stressors and pathological processes. The overarching goal is to catalyze efforts toward development of robust, infant-specific acquisition, and preprocessing pipelines, as well as promote greater transparency by researchers regarding methods used.

Resting-State Functional Connectivity in the Infant Brain: Methods, Pitfalls, and Potentiality

PubMed Central

Mongerson, Chandler R. L.; Jennings, Russell W.; Borsook, David; Becerra, Lino; Bajic, Dusica

2017-01-01

Early brain development is characterized by rapid growth and perpetual reconfiguration, driven by a dynamic milieu of heterogeneous processes. Postnatal brain plasticity is associated with increased vulnerability to environmental stimuli. However, little is known regarding the ontogeny and temporal manifestations of inter- and intra-regional functional connectivity that comprise functional brain networks. Resting-state functional magnetic resonance imaging (rs-fMRI) has emerged as a promising non-invasive neuroinvestigative tool, measuring spontaneous fluctuations in blood oxygen level dependent (BOLD) signal at rest that reflect baseline neuronal activity. Over the past decade, its application has expanded to infant populations providing unprecedented insight into functional organization of the developing brain, as well as early biomarkers of abnormal states. However, many methodological issues of rs-fMRI analysis need to be resolved prior to standardization of the technique to infant populations. As a primary goal, this methodological manuscript will (1) present a robust methodological protocol to extract and assess resting-state networks in early infancy using independent component analysis (ICA), such that investigators without previous knowledge in the field can implement the analysis and reliably obtain viable results consistent with previous literature; (2) review the current methodological challenges and ethical considerations associated with emerging field of infant rs-fMRI analysis; and (3) discuss the significance of rs-fMRI application in infants for future investigations of neurodevelopment in the context of early life stressors and pathological processes. The overarching goal is to catalyze efforts toward development of robust, infant-specific acquisition, and preprocessing pipelines, as well as promote greater transparency by researchers regarding methods used. PMID:28856131

Brain changes detected by functional magnetic resonance imaging and spectroscopy in patients with Crohn's disease.

PubMed

Lv, Kun; Fan, Yi-Hong; Xu, Li; Xu, Mao-Sheng

2017-05-28

Crohn's disease (CD) is a chronic, non-specific granulomatous inflammatory disorder that commonly affects the small intestine and is a phenotype of inflammatory bowel disease (IBD). CD is prone to relapse, and its incidence displays a persistent increase in developing countries. However, the pathogenesis of CD is poorly understood, with some studies emphasizing the link between CD and the intestinal microbiota. Specifically, studies point to the brain-gut-enteric microbiota axis as a key player in the occurrence and development of CD. Furthermore, investigations have shown white-matter lesions and neurologic deficits in patients with IBD. Based on these findings, brain activity changes in CD patients have been detected by blood oxygenation level dependent functional magnetic resonance imaging (BOLD-fMRI). BOLD-fMRI functions by detecting a local increase in relative blood oxygenation that results from neurotransmitter activity and thus reflects local neuronal firing rates. Therefore, biochemical concentrations of neurotransmitters or metabolites may change in corresponding brain regions of CD patients. To further study this phenomenon, brain changes of CD patients can be detected non-invasively, effectively and accurately by BOLD-fMRI combined with magnetic resonance spectroscopy (MRS). This approach can further shed light on the mechanisms of the occurrence and development of neurological CD. Overall, this paper reviews the current status and prospects on fMRI and MRS for evaluation of patients with CD based on the brain-gut-enteric microbiota axis.

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

PubMed

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

2015-09-30

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

Alterations of functional connectivities from early to middle adulthood: Clues from multivariate pattern analysis of resting-state fMRI data.

PubMed

Tian, Lixia; Ma, Lin; Wang, Linlin

2016-04-01

In contrast to extended research interests in the maturation and aging of human brain, alterations of brain structure and function from early to middle adulthood have been much less studied. The aim of the present study was to investigate the extent and pattern of the alterations of functional interactions between brain regions from early to middle adulthood. We carried out the study by multivariate pattern analysis of resting-state fMRI (RS-fMRI) data of 63 adults aged 18 to 45 years. Specifically, using elastic net, we performed brain age estimation and age-group classification (young adults aged 18-28 years vs. middle-aged adults aged 35-45 years) based on the resting-state functional connectivities (RSFCs) between 160 regions of interest (ROIs) evaluated on the RS-fMRI data of each subject. The results indicate that the estimated brain ages were significantly correlated with the chronological age (R=0.78, MAE=4.81), and a classification rate of 94.44% and area under the receiver operating characteristic curve (AUC) of 0.99 were obtained when classifying the young and middle-aged adults. These results provide strong evidence that functional interactions between brain regions undergo notable alterations from early to middle adulthood. By analyzing the RSFCs that contribute to brain age estimation/age-group classification, we found that a majority of the RSFCs were inter-network, and we speculate that inter-network RSFCs might mature late but age early as compared to intra-network ones. In addition, the strengthening/weakening of the RSFCs associated with the left/right hemispheric ROIs, the weakening of cortico-cerebellar RSFCs and the strengthening of the RSFCs between the default mode network and other networks contributed much to both brain age estimation and age-group classification. All these alterations might reflect that aging of brain function is already in progress in middle adulthood. Overall, the present study indicated that the RSFCs undergo notable alterations from early to middle adulthood and highlighted the necessity of careful considerations of possible influences of these alterations in related studies. Copyright © 2016 Elsevier Inc. All rights reserved.

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

PubMed

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

2017-12-01

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

Functional Evaluation of Hidden Figures Object Analysis in Children with Autistic Disorder

ERIC Educational Resources Information Center

Malisza, Krisztina L.; Clancy, Christine; Shiloff, Deborah; Foreman, Derek; Holden, Jeanette; Jones, Cheryl; Paulson, K.; Summers, Randy; Yu, C. T.; Chudley, Albert E.

2011-01-01

Functional magnetic resonance imaging (fMRI) during performance of a hidden figures task (HFT) was used to compare differences in brain function in children diagnosed with autism disorder (AD) compared to children with attention-deficit/hyperactivity disorder (ADHD) and typical controls (TC). Overall greater functional MRI activity was observed in…

Functional connectome fingerprinting: identifying individuals using patterns of brain connectivity.

PubMed

Finn, Emily S; Shen, Xilin; Scheinost, Dustin; Rosenberg, Monica D; Huang, Jessica; Chun, Marvin M; Papademetris, Xenophon; Constable, R Todd

2015-11-01

Functional magnetic resonance imaging (fMRI) studies typically collapse data from many subjects, but brain functional organization varies between individuals. Here we establish that this individual variability is both robust and reliable, using data from the Human Connectome Project to demonstrate that functional connectivity profiles act as a 'fingerprint' that can accurately identify subjects from a large group. Identification was successful across scan sessions and even between task and rest conditions, indicating that an individual's connectivity profile is intrinsic, and can be used to distinguish that individual regardless of how the brain is engaged during imaging. Characteristic connectivity patterns were distributed throughout the brain, but the frontoparietal network emerged as most distinctive. Furthermore, we show that connectivity profiles predict levels of fluid intelligence: the same networks that were most discriminating of individuals were also most predictive of cognitive behavior. Results indicate the potential to draw inferences about single subjects on the basis of functional connectivity fMRI.

Translating Neurocognitive Models of Auditory-Verbal Hallucinations into Therapy: Using Real-time fMRI-Neurofeedback to Treat Voices

PubMed Central

Fovet, Thomas; Orlov, Natasza; Dyck, Miriam; Allen, Paul; Mathiak, Klaus; Jardri, Renaud

2016-01-01

Auditory-verbal hallucinations (AVHs) are frequent and disabling symptoms, which can be refractory to conventional psychopharmacological treatment in more than 25% of the cases. Recent advances in brain imaging allow for a better understanding of the neural underpinnings of AVHs. These findings strengthened transdiagnostic neurocognitive models that characterize these frequent and disabling experiences. At the same time, technical improvements in real-time functional magnetic resonance imaging (fMRI) enabled the development of innovative and non-invasive methods with the potential to relieve psychiatric symptoms, such as fMRI-based neurofeedback (fMRI-NF). During fMRI-NF, brain activity is measured and fed back in real time to the participant in order to help subjects to progressively achieve voluntary control over their own neural activity. Precisely defining the target brain area/network(s) appears critical in fMRI-NF protocols. After reviewing the available neurocognitive models for AVHs, we elaborate on how recent findings in the field may help to develop strong a priori strategies for fMRI-NF target localization. The first approach relies on imaging-based “trait markers” (i.e., persistent traits or vulnerability markers that can also be detected in the presymptomatic and remitted phases of AVHs). The goal of such strategies is to target areas that show aberrant activations during AVHs or are known to be involved in compensatory activation (or resilience processes). Brain regions, from which the NF signal is derived, can be based on structural MRI and neurocognitive knowledge, or functional MRI information collected during specific cognitive tasks. Because hallucinations are acute and intrusive symptoms, a second strategy focuses more on “state markers.” In this case, the signal of interest relies on fMRI capture of the neural networks exhibiting increased activity during AVHs occurrences, by means of multivariate pattern recognition methods. The fine-grained activity patterns concomitant to hallucinations can then be fed back to the patients for therapeutic purpose. Considering the potential cost necessary to implement fMRI-NF, proof-of-concept studies are urgently required to define the optimal strategy for application in patients with AVHs. This technique has the potential to establish a new brain imaging-guided psychotherapy for patients that do not respond to conventional treatments and take functional neuroimaging to therapeutic applications. PMID:27445865

Consistency of magnetoencephalographic functional connectivity and network reconstruction using a template versus native MRI for co‐registration

PubMed Central

Douw, Linda; Stam, Cornelis J.; Tewarie, Prejaas; Hillebrand, Arjan

2017-01-01

Abstract Introduction Studies using functional connectivity and network analyses based on magnetoencephalography (MEG) with source localization are rapidly emerging in neuroscientific literature. However, these analyses currently depend on the availability of costly and sometimes burdensome individual MR scans for co‐registration. We evaluated the consistency of these measures when using a template MRI, instead of native MRI, for the analysis of functional connectivity and network topology. Methods Seventeen healthy participants underwent resting‐state eyes‐closed MEG and anatomical MRI. These data were projected into source space using an atlas‐based peak voxel and a centroid beamforming approach either using (1) participants’ native MRIs or (2) the Montreal Neurological Institute's template. For both methods, time series were reconstructed from 78 cortical atlas regions. Relative power was determined in six classical frequency bands per region and globally averaged. Functional connectivity (phase lag index) between each pair of regions was calculated. The adjacency matrices were then used to reconstruct functional networks, of which regional and global metrics were determined. Intraclass correlation coefficients were calculated and Bland–Altman plots were made to quantify the consistency and potential bias of the use of template versus native MRI. Results Co‐registration with the template yielded largely consistent relative power, connectivity, and network estimates compared to native MRI. Discussion These findings indicate that there is no (systematic) bias or inconsistency between template and native MRI co‐registration of MEG. They open up possibilities for retrospective and prospective analyses to MEG datasets in the general population that have no native MRIs available. Hum Brain Mapp, 2017. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc. Hum Brain Mapp 39:104–119, 2018. © 2017 Wiley Periodicals, Inc. PMID:28990264

Same-session functional assessment of rat retina and brain with manganese-enhanced MRI

PubMed Central

Bissig, David; Berkowitz, Bruce A.

2013-01-01

Manganese-enhanced MRI (MEMRI) is a powerful non-invasive approach for objectively measuring either retina or binocular visual brain activity in vivo. In this study, we investigated the sensitivity of MEMRI to monocular stimulation using a new protocol for providing within-subject functional comparisons in the retina and brain in the same scanning session. Adult Sprague Dawley or Long–Evans rats had one eye covered with an opaque patch. After intraperitoneal Mn2+ administration on the following day, rats underwent visual stimulation for 8 h. Animals were then anesthetized, and the brain and each eye examined by MEMRI. Function was assessed through pairwise comparisons of the patched (dark-adapted) versus unpatched (light-exposed) eyes, and of differentially-stimulated brain structures – the dorsal lateral geniculate nucleus, superior colliculus, and visual cortical regions – contralateral to the patched versus unpatched eye. As expected, Mn2+ uptake was greater in the outer retina of dark-adapted, relative to light-exposed, eyes (P<0.05). Contralateral to the unpatched eye, significantly more Mn2+ uptake was found throughout the visual brain regions than in the corresponding structures contralateral to the patched eye (P<0.05). Notably, this regional pattern of activity corresponded well to previous work with monocular stimulation. No stimulation-dependent differences in Mn2+ uptake were observed in negative control brain regions (P>0.05). Post-hoc assessment of functional data by animal age and strain revealed no significant effects. These results demonstrate, for the first time, the acquisition of functional MRI data from the eye and visual brain regions in a single scanning session. PMID:21749922

Pharmacologic Modulation of Hand Pain in Osteoarthritis: A Double-Blind Placebo-Controlled Functional Magnetic Resonance Imaging Study Using Naproxen

PubMed Central

Sanders, Duncan; Krause, Kristina; O'Muircheartaigh, Jonathan; Thacker, Michael A; Huggins, John P; Vennart, William; Massat, Nathalie J; Choy, Ernest; Williams, Steven C R; Howard, Matthew A

2015-01-01

Objective In an attempt to shed light on management of chronic pain conditions, there has long been a desire to complement behavioral measures of pain perception with measures of underlying brain mechanisms. Using functional magnetic resonance imaging (fMRI), we undertook this study to investigate changes in brain activity following the administration of naproxen or placebo in patients with pain related to osteoarthritis (OA) of the carpometacarpal (CMC) joint. Methods A placebo-controlled, double-blind, 2-period crossover study was performed in 19 individuals with painful OA of the CMC joint of the right hand. Following placebo or naproxen treatment periods, a functionally relevant task was performed, and behavioral measures of the pain experience were collected in identical fMRI examinations. Voxelwise and a priori region of interest analyses were performed to detect between-period differences in brain activity. Results Significant reductions in brain activity following treatment with naproxen, compared to placebo, were observed in brain regions commonly associated with pain perception, including the bilateral primary somatosensory cortex, thalamus, and amygdala. Significant relationships between changes in perceived pain intensity and changes in brain activity were also observed in brain regions previously associated with pain intensity. Conclusion This study demonstrates the sensitivity of fMRI to detect the mechanisms underlying treatments of known efficacy. The data illustrate the enticing potential of fMRI as an adjunct to self-report for detecting early signals of efficacy of novel therapies, both pharmacologic and nonpharmacologic, in small numbers of individuals with persistent pain. PMID:25533872

The Cambridge Centre for Ageing and Neuroscience (Cam-CAN) data repository: Structural and functional MRI, MEG, and cognitive data from a cross-sectional adult lifespan sample.

PubMed

Taylor, Jason R; Williams, Nitin; Cusack, Rhodri; Auer, Tibor; Shafto, Meredith A; Dixon, Marie; Tyler, Lorraine K; Cam-Can; Henson, Richard N

2017-01-01

This paper describes the data repository for the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) initial study cohort. The Cam-CAN Stage 2 repository contains multi-modal (MRI, MEG, and cognitive-behavioural) data from a large (approximately N=700), cross-sectional adult lifespan (18-87years old) population-based sample. The study is designed to characterise age-related changes in cognition and brain structure and function, and to uncover the neurocognitive mechanisms that support healthy cognitive ageing. The database contains raw and preprocessed structural MRI, functional MRI (active tasks and resting state), and MEG data (active tasks and resting state), as well as derived scores from cognitive behavioural experiments spanning five broad domains (attention, emotion, action, language, and memory), and demographic and neuropsychological data. The dataset thus provides a depth of neurocognitive phenotyping that is currently unparalleled, enabling integrative analyses of age-related changes in brain structure, brain function, and cognition, and providing a testbed for novel analyses of multi-modal neuroimaging data. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Reproducibility assessment of brain responses to visual food stimuli in adults with overweight and obesity

PubMed Central

Sayer, R Drew; Tamer, Gregory G; Chen, Ningning; Tregellas, Jason R; Cornier, Marc-Andre; Kareken, David A; Talavage, Thomas M; McCrory, Megan A; Campbell, Wayne W

2016-01-01

Objective The brain’s reward system influences ingestive behavior and subsequently, obesity risk. Functional magnetic resonance imaging (fMRI) is a common method for investigating brain reward function. We sought to assess the reproducibility of fasting-state brain responses to visual food stimuli using BOLD fMRI. Methods A priori brain regions of interest included bilateral insula, amygdala, orbitofrontal cortex, caudate, and putamen. Fasting-state fMRI and appetite assessments were completed by 28 women (n=16) and men (n=12) with overweight or obesity on 2 days. Reproducibility was assessed by comparing mean fasting-state brain responses and measuring test-retest reliability of these responses on the 2 testing days. Results Mean fasting-state brain responses on Day 2 were reduced compared to Day 1 in the left insula and right amygdala, but mean Day 1 and Day 2 responses were not different in the other regions of interest. With the exception of the left orbitofrontal cortex response (fair reliability), test-retest reliabilities of brain responses were poor or unreliable. Conclusion fMRI-measured responses to visual food cues in adults with overweight or obesity show relatively good mean-level reproducibility, but considerable within-subject variability. Poor test-retest reliability reduces the likelihood of observing true correlations and increases the necessary sample sizes for studies. PMID:27542906

Benevolent sexism alters executive brain responses.

PubMed

Dardenne, Benoit; Dumont, Muriel; Sarlet, Marie; Phillips, Christophe; Balteau, Evelyne; Degueldre, Christian; Luxen, André; Salmon, Eric; Maquet, Pierre; Collette, Fabienne

2013-07-10

Benevolence is widespread in our societies. It is defined as considering a subordinate group nicely but condescendingly, that is, with charity. Deleterious consequences for the target have been reported in the literature. In this experiment, we used functional MRI (fMRI) to identify whether being the target of (sexist) benevolence induces changes in brain activity associated with a working memory task. Participants were confronted by benevolent, hostile, or neutral comments before and while performing a reading span test in an fMRI environment. fMRI data showed that brain regions associated previously with intrusive thought suppression (bilateral, dorsolateral, prefrontal, and anterior cingulate cortex) reacted specifically to benevolent sexism compared with hostile sexism and neutral conditions during the performance of the task. These findings indicate that, despite being subjectively positive, benevolence modifies task-related brain networks by recruiting supplementary areas likely to impede optimal cognitive performance.

Implementations of clinical functional magnetic resonance imaging using character-based paradigms for the prediction of Chinese language dominance.

PubMed

Liu, Ho-Ling; Wu, Chien-Te; Chen, Jian-Chuan; Hsu, Yuan-Yu; Wai, Yau-Yau; Wan, Yung-Liang

2003-01-01

Recently, functional MRI (fMRI) using word generation (WG) tasks has been shown to be effective for mapping the Chinese language-related brain areas. In clinical applications, however, patients' performance cannot be easily monitored during WG tasks. In this study, we evaluated the feasibility of a word choice (WC) paradigm in the clinical setting and compared the results with those from WG tasks. Intrasubject comparisons of fMRI with both WG and WC paradigms were performed on six normal human subjects and two tumor patients. Subject responses in the WC paradigm, based on semantic judgments, were recorded. Activation strength, extent, and laterality were evaluated and compared. Our results showed that fMRI with the WC paradigm evoked weaker neuronal activation than that with the WG paradigm in Chinese language-related brain areas. It was sufficient to reveal language laterality for clinical use, however. In addition, it resulted in less nonlanguage-specific brain activation. Results from the patient data demonstrated strong evidence for the necessity of incorporating response monitoring during fMRI studies, which suggested that fMRI with the WC paradigm is more appropriate to be implemented for the prediction of Chinese language dominance in clinical environments.

Quantitative prediction of perceptual decisions during near-threshold fear detection

NASA Astrophysics Data System (ADS)

Pessoa, Luiz; Padmala, Srikanth

2005-04-01

A fundamental goal of cognitive neuroscience is to explain how mental decisions originate from basic neural mechanisms. The goal of the present study was to investigate the neural correlates of perceptual decisions in the context of emotional perception. To probe this question, we investigated how fluctuations in functional MRI (fMRI) signals were correlated with behavioral choice during a near-threshold fear detection task. fMRI signals predicted behavioral choice independently of stimulus properties and task accuracy in a network of brain regions linked to emotional processing: posterior cingulate cortex, medial prefrontal cortex, right inferior frontal gyrus, and left insula. We quantified the link between fMRI signals and behavioral choice in a whole-brain analysis by determining choice probabilities by means of signal-detection theory methods. Our results demonstrate that voxel-wise fMRI signals can reliably predict behavioral choice in a quantitative fashion (choice probabilities ranged from 0.63 to 0.78) at levels comparable to neuronal data. We suggest that the conscious decision that a fearful face has been seen is represented across a network of interconnected brain regions that prepare the organism to appropriately handle emotionally challenging stimuli and that regulate the associated emotional response. decision making | emotion | functional MRI

Hallucination- and speech-specific hypercoupling in frontotemporal auditory and language networks in schizophrenia using combined task-based fMRI data: An fBIRN study.

PubMed

Lavigne, Katie M; Woodward, Todd S

2018-04-01

Hypercoupling of activity in speech-perception-specific brain networks has been proposed to play a role in the generation of auditory-verbal hallucinations (AVHs) in schizophrenia; however, it is unclear whether this hypercoupling extends to nonverbal auditory perception. We investigated this by comparing schizophrenia patients with and without AVHs, and healthy controls, on task-based functional magnetic resonance imaging (fMRI) data combining verbal speech perception (SP), inner verbal thought generation (VTG), and nonverbal auditory oddball detection (AO). Data from two previously published fMRI studies were simultaneously analyzed using group constrained principal component analysis for fMRI (group fMRI-CPCA), which allowed for comparison of task-related functional brain networks across groups and tasks while holding the brain networks under study constant, leading to determination of the degree to which networks are common to verbal and nonverbal perception conditions, and which show coordinated hyperactivity in hallucinations. Three functional brain networks emerged: (a) auditory-motor, (b) language processing, and (c) default-mode (DMN) networks. Combining the AO and sentence tasks allowed the auditory-motor and language networks to separately emerge, whereas they were aggregated when individual tasks were analyzed. AVH patients showed greater coordinated activity (deactivity for DMN regions) than non-AVH patients during SP in all networks, but this did not extend to VTG or AO. This suggests that the hypercoupling in AVH patients in speech-perception-related brain networks is specific to perceived speech, and does not extend to perceived nonspeech or inner verbal thought generation. © 2017 Wiley Periodicals, Inc.

BRAPH: A graph theory software for the analysis of brain connectivity

PubMed Central

Mijalkov, Mite; Kakaei, Ehsan; Pereira, Joana B.; Westman, Eric; Volpe, Giovanni

2017-01-01

The brain is a large-scale complex network whose workings rely on the interaction between its various regions. In the past few years, the organization of the human brain network has been studied extensively using concepts from graph theory, where the brain is represented as a set of nodes connected by edges. This representation of the brain as a connectome can be used to assess important measures that reflect its topological architecture. We have developed a freeware MatLab-based software (BRAPH–BRain Analysis using graPH theory) for connectivity analysis of brain networks derived from structural magnetic resonance imaging (MRI), functional MRI (fMRI), positron emission tomography (PET) and electroencephalogram (EEG) data. BRAPH allows building connectivity matrices, calculating global and local network measures, performing non-parametric permutations for group comparisons, assessing the modules in the network, and comparing the results to random networks. By contrast to other toolboxes, it allows performing longitudinal comparisons of the same patients across different points in time. Furthermore, even though a user-friendly interface is provided, the architecture of the program is modular (object-oriented) so that it can be easily expanded and customized. To demonstrate the abilities of BRAPH, we performed structural and functional graph theory analyses in two separate studies. In the first study, using MRI data, we assessed the differences in global and nodal network topology in healthy controls, patients with amnestic mild cognitive impairment, and patients with Alzheimer’s disease. In the second study, using resting-state fMRI data, we compared healthy controls and Parkinson’s patients with mild cognitive impairment. PMID:28763447

Analysis of Resting-State fMRI Topological Graph Theory Properties in Methamphetamine Drug Users Applying Box-Counting Fractal Dimension.

PubMed

Siyah Mansoory, Meysam; Oghabian, Mohammad Ali; Jafari, Amir Homayoun; Shahbabaie, Alireza

2017-01-01

Graph theoretical analysis of functional Magnetic Resonance Imaging (fMRI) data has provided new measures of mapping human brain in vivo. Of all methods to measure the functional connectivity between regions, Linear Correlation (LC) calculation of activity time series of the brain regions as a linear measure is considered the most ubiquitous one. The strength of the dependence obligatory for graph construction and analysis is consistently underestimated by LC, because not all the bivariate distributions, but only the marginals are Gaussian. In a number of studies, Mutual Information (MI) has been employed, as a similarity measure between each two time series of the brain regions, a pure nonlinear measure. Owing to the complex fractal organization of the brain indicating self-similarity, more information on the brain can be revealed by fMRI Fractal Dimension (FD) analysis. In the present paper, Box-Counting Fractal Dimension (BCFD) is introduced for graph theoretical analysis of fMRI data in 17 methamphetamine drug users and 18 normal controls. Then, BCFD performance was evaluated compared to those of LC and MI methods. Moreover, the global topological graph properties of the brain networks inclusive of global efficiency, clustering coefficient and characteristic path length in addict subjects were investigated too. Compared to normal subjects by using statistical tests (P<0.05), topological graph properties were postulated to be disrupted significantly during the resting-state fMRI. Based on the results, analyzing the graph topological properties (representing the brain networks) based on BCFD is a more reliable method than LC and MI.

BRAPH: A graph theory software for the analysis of brain connectivity.

PubMed

Mijalkov, Mite; Kakaei, Ehsan; Pereira, Joana B; Westman, Eric; Volpe, Giovanni

2017-01-01

The brain is a large-scale complex network whose workings rely on the interaction between its various regions. In the past few years, the organization of the human brain network has been studied extensively using concepts from graph theory, where the brain is represented as a set of nodes connected by edges. This representation of the brain as a connectome can be used to assess important measures that reflect its topological architecture. We have developed a freeware MatLab-based software (BRAPH-BRain Analysis using graPH theory) for connectivity analysis of brain networks derived from structural magnetic resonance imaging (MRI), functional MRI (fMRI), positron emission tomography (PET) and electroencephalogram (EEG) data. BRAPH allows building connectivity matrices, calculating global and local network measures, performing non-parametric permutations for group comparisons, assessing the modules in the network, and comparing the results to random networks. By contrast to other toolboxes, it allows performing longitudinal comparisons of the same patients across different points in time. Furthermore, even though a user-friendly interface is provided, the architecture of the program is modular (object-oriented) so that it can be easily expanded and customized. To demonstrate the abilities of BRAPH, we performed structural and functional graph theory analyses in two separate studies. In the first study, using MRI data, we assessed the differences in global and nodal network topology in healthy controls, patients with amnestic mild cognitive impairment, and patients with Alzheimer's disease. In the second study, using resting-state fMRI data, we compared healthy controls and Parkinson's patients with mild cognitive impairment.

A regularized clustering approach to brain parcellation from functional MRI data

NASA Astrophysics Data System (ADS)

Dillon, Keith; Wang, Yu-Ping

2017-08-01

We consider a data-driven approach for the subdivision of an individual subject's functional Magnetic Resonance Imaging (fMRI) scan into regions of interest, i.e., brain parcellation. The approach is based on a computational technique for calculating resolution from inverse problem theory, which we apply to neighborhood selection for brain connectivity networks. This can be efficiently calculated even for very large images, and explicitly incorporates regularization in the form of spatial smoothing and a noise cutoff. We demonstrate the reproducibility of the method on multiple scans of the same subjects, as well as the variations between subjects.

Functional and structural correlates of magnetic resonance patterns in a new in vitro model of cerebral ischemia by transient occlusion of the medial cerebral artery.

PubMed

Breschi, Gian Luca; Librizzi, Laura; Pastori, Chiara; Zucca, Ileana; Mastropietro, Alfonso; Cattalini, Alessandro; de Curtis, Marco

2010-08-01

Magnetic resonance imaging (MRI) during the acute phase of a stroke contributes to recognize ischemic regions and is potentially useful to predict clinical outcome. Yet, the functional significance of early MRI alterations during brain ischemia is not clearly understood. We achieved an experimental study to interpret MRI signals in a novel model of focal ischemia in the in vitro isolated guinea pig brain. By combining neurophysiological and morphological analysis with MR-imaging, we evaluated the suitability of MR to identify ischemic and peri-ischemic regions. Extracellular recordings demonstrated depolarizations in the ischemic core, but not in adjacent areas, where evoked activity was preserved and brief peri-infarct depolarizations occurred. Diffusion-weighted MRI and immunostaining performed after neurophysiological characterization showed changes restricted to the core region. Diffusion-weighted MR alterations did not include the penumbra region characterized by peri-infarct depolarizations. Therefore, by comparing neurophysiological, imaging and anatomical data, we can conclude that DW-MRI underestimates the extension of the tissue damage involved in brain ischemia.

The effect of inflammation and its reduction on brain plasticity in multiple sclerosis: MRI evidence.

PubMed

Tomassini, Valentina; d'Ambrosio, Alessandro; Petsas, Nikolaos; Wise, Richard G; Sbardella, Emilia; Allen, Marek; Tona, Francesca; Fanelli, Fulvia; Foster, Catherine; Carnì, Marco; Gallo, Antonio; Pantano, Patrizia; Pozzilli, Carlo

2016-07-01

Brain plasticity is the basis for systems-level functional reorganization that promotes recovery in multiple sclerosis (MS). As inflammation interferes with plasticity, its pharmacological modulation may restore plasticity by promoting desired patterns of functional reorganization. Here, we tested the hypothesis that brain plasticity probed by a visuomotor adaptation task is impaired with MS inflammation and that pharmacological reduction of inflammation facilitates its restoration. MS patients were assessed twice before (sessions 1 and 2) and once after (session 3) the beginning of Interferon beta (IFN beta), using behavioural and structural MRI measures. During each session, 2 functional MRI runs of a visuomotor task, separated by 25-minutes of task practice, were performed. Within-session between-run change in task-related functional signal was our imaging marker of plasticity. During session 1, patients were compared with healthy controls. Comparison of patients' sessions 2 and 3 tested the effect of reduced inflammation on our imaging marker of plasticity. The proportion of patients with gadolinium-enhancing lesions reduced significantly during IFN beta. In session 1, patients demonstrated a greater between-run difference in functional MRI activity of secondary visual areas and cerebellum than controls. This abnormally large practice-induced signal change in visual areas, and in functionally connected posterior parietal and motor cortices, was reduced in patients in session 3 compared with 2. Our results suggest that MS inflammation alters short-term plasticity underlying motor practice. Reduction of inflammation with IFN beta is associated with a restoration of this plasticity, suggesting that modulation of inflammation may enhance recovery-oriented strategies that rely on patients' brain plasticity. Hum Brain Mapp 37:2431-2445, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Neuroimaging effects of prenatal alcohol exposure on the developing human brain: a magnetic resonance imaging review.

PubMed

Donald, Kirsten Ann; Eastman, Emma; Howells, Fleur Margaret; Adnams, Colleen; Riley, Edward Patrick; Woods, Roger Paul; Narr, Katherine Louise; Stein, Dan Joseph

2015-10-01

This paper reviews the magnetic resonance imaging (MRI) literature on the effects of prenatal alcohol exposure on the developing human brain. A literature search was conducted through the following databases: PubMed, PsycINFO and Google Scholar. Combinations of the following search terms and keywords were used to identify relevant studies: 'alcohol', 'fetal alcohol spectrum disorders', 'fetal alcohol syndrome', 'FAS', 'FASD', 'MRI', 'DTI', 'MRS', 'neuroimaging', 'children' and 'infants'. A total of 64 relevant articles were identified across all modalities. Overall, studies reported smaller total brain volume as well as smaller volume of both the white and grey matter in specific cortical regions. The most consistently reported structural MRI findings were alterations in the shape and volume of the corpus callosum, as well as smaller volume in the basal ganglia and hippocampi. The most consistent finding from diffusion tensor imaging studies was lower fractional anisotropy in the corpus callosum. Proton magnetic resonance spectroscopy studies are few to date, but showed altered neurometabolic profiles in the frontal and parietal cortex, thalamus and dentate nuclei. Resting-state functional MRI studies reported reduced functional connectivity between cortical and deep grey matter structures. Discussion There is a critical gap in the literature of MRI studies in alcohol-exposed children under 5 years of age across all MRI modalities. The dynamic nature of brain maturation and appreciation of the effects of alcohol exposure on the developing trajectory of the structural and functional network argue for the prioritisation of studies that include a longitudinal approach to understanding this spectrum of effects and potential therapeutic time points.

Visual Learning Induces Changes in Resting-State fMRI Multivariate Pattern of Information.

PubMed

Guidotti, Roberto; Del Gratta, Cosimo; Baldassarre, Antonello; Romani, Gian Luca; Corbetta, Maurizio

2015-07-08

When measured with functional magnetic resonance imaging (fMRI) in the resting state (R-fMRI), spontaneous activity is correlated between brain regions that are anatomically and functionally related. Learning and/or task performance can induce modulation of the resting synchronization between brain regions. Moreover, at the neuronal level spontaneous brain activity can replay patterns evoked by a previously presented stimulus. Here we test whether visual learning/task performance can induce a change in the patterns of coded information in R-fMRI signals consistent with a role of spontaneous activity in representing task-relevant information. Human subjects underwent R-fMRI before and after perceptual learning on a novel visual shape orientation discrimination task. Task-evoked fMRI patterns to trained versus novel stimuli were recorded after learning was completed, and before the second R-fMRI session. Using multivariate pattern analysis on task-evoked signals, we found patterns in several cortical regions, as follows: visual cortex, V3/V3A/V7; within the default mode network, precuneus, and inferior parietal lobule; and, within the dorsal attention network, intraparietal sulcus, which discriminated between trained and novel visual stimuli. The accuracy of classification was strongly correlated with behavioral performance. Next, we measured multivariate patterns in R-fMRI signals before and after learning. The frequency and similarity of resting states representing the task/visual stimuli states increased post-learning in the same cortical regions recruited by the task. These findings support a representational role of spontaneous brain activity. Copyright © 2015 the authors 0270-6474/15/359786-13$15.00/0.

Genetic and Diagnostic Biomarker Development in ASD Toddlers Using Resting State Functional MRI

DTIC Science & Technology

2015-09-01

for public release; distribution unlimited Autism spectrum disorder (ASD); biomarker; early brain development; intrinsic functional brain networks...three large neuroimaging/neurobehavioral datasets to identify brain-imaging based biomarkers for Autism Spectrum Disorders (ASD). At Yale, we focus...neurobehavioral!datasets!in!order!to!identify! brainFimaging!based!biomarkers!for! Autism ! Spectrum ! Disorders !(ASD),!including!1)!BrainMap,! developed!and

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

PubMed

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

2016-10-01

The use of functional magnetic resonance imaging (fMRI) in mice is increasingly prevalent, providing a means to non-invasively characterise functional abnormalities associated with genetic models of human diseases. The predominant stimulus used in task-based fMRI in the mouse is electrical stimulation of the paw. Task-based fMRI in mice using visual stimuli remains underexplored, despite visual stimuli being common in human fMRI studies. In this study, we map the mouse brain visual system with BOLD measurements at 9.4T using flashing light stimuli with medetomidine anaesthesia. BOLD responses were observed in the lateral geniculate nucleus, the superior colliculus and the primary visual area of the cortex, and were modulated by the flashing frequency, diffuse vs focussed light and stimulus context. Negative BOLD responses were measured in the visual cortex at 10Hz flashing frequency; but turned positive below 5Hz. In addition, the use of interleaved snapshot GE-EPI improved fMRI image quality without diminishing the temporal contrast-noise-ratio. Taken together, this work demonstrates a novel methodological protocol in which the mouse brain visual system can be non-invasively investigated using BOLD fMRI. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

White Matter Connectivity of the Thalamus Delineates the Functional Architecture of Competing Thalamocortical Systems

PubMed Central

O'Muircheartaigh, Jonathan; Keller, Simon S.; Barker, Gareth J.; Richardson, Mark P.

2015-01-01

There is an increasing awareness of the involvement of thalamic connectivity on higher level cortical functioning in the human brain. This is reflected by the influence of thalamic stimulation on cortical activity and behavior as well as apparently cortical lesion syndromes occurring as a function of small thalamic insults. Here, we attempt to noninvasively test the correspondence of structural and functional connectivity of the human thalamus using diffusion-weighted and resting-state functional MRI. Using a large sample of 102 adults, we apply tensor independent component analysis to diffusion MRI tractography data to blindly parcellate bilateral thalamus according to diffusion tractography-defined structural connectivity. Using resting-state functional MRI collected in the same subjects, we show that the resulting structurally defined thalamic regions map to spatially distinct, and anatomically predictable, whole-brain functional networks in the same subjects. Although there was significant variability in the functional connectivity patterns, the resulting 51 structural and functional patterns could broadly be reduced to a subset of 7 similar core network types. These networks were distinct from typical cortical resting-state networks. Importantly, these networks were distributed across the brain and, in a subset, map extremely well to known thalamocortico-basal-ganglial loops. PMID:25899706

Blood oxygen-level dependent functional assessment of cerebrovascular reactivity: Feasibility for intraoperative 3 Tesla MRI.

PubMed

Fierstra, Jorn; Burkhardt, Jan-Karl; van Niftrik, Christiaan Hendrik Bas; Piccirelli, Marco; Pangalu, Athina; Kocian, Roman; Neidert, Marian Christoph; Valavanis, Antonios; Regli, Luca; Bozinov, Oliver

2017-02-01

To assess the feasibility of functional blood oxygen-level dependent (BOLD) MRI to evaluate intraoperative cerebrovascular reactivity (CVR) at 3 Tesla field strength. Ten consecutive neurosurgical subjects scheduled for a clinical intraoperative MRI examination were enrolled in this study. In addition to the clinical protocol a BOLD sequence was implemented with three cycles of 44 s apnea to calculate CVR values on a voxel-by-voxel basis throughout the brain. The CVR range was then color-coded and superimposed on an anatomical volume to create high spatial resolution CVR maps. Ten subjects (mean age 34.8 ± 13.4; 2 females) uneventfully underwent the intraoperative BOLD protocol, with no complications occurring. Whole-brain CVR for all subjects was (mean ± SD) 0.69 ± 0.42, whereas CVR was markedly higher for tumor subjects as compared to vascular subjects, 0.81 ± 0.44 versus 0.33 ± 0.10, respectively. Furthermore, color-coded functional maps could be robustly interpreted for a whole-brain assessment of CVR. We demonstrate that intraoperative BOLD MRI is feasible in creating functional maps to assess cerebrovascular reactivity throughout the brain in subjects undergoing a neurosurgical procedure. Magn Reson Med 77:806-813, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Probabilistic atlases of default mode, executive control and salience network white matter tracts: an fMRI-guided diffusion tensor imaging and tractography study

PubMed Central

Figley, Teresa D.; Bhullar, Navdeep; Courtney, Susan M.; Figley, Chase R.

2015-01-01

Diffusion tensor imaging (DTI) is a powerful MRI technique that can be used to estimate both the microstructural integrity and the trajectories of white matter pathways throughout the central nervous system. This fiber tracking (aka, “tractography”) approach is often carried out using anatomically-defined seed points to identify white matter tracts that pass through one or more structures, but can also be performed using functionally-defined regions of interest (ROIs) that have been determined using functional MRI (fMRI) or other methods. In this study, we performed fMRI-guided DTI tractography between all of the previously defined nodes within each of six common resting-state brain networks, including the: dorsal Default Mode Network (dDMN), ventral Default Mode Network (vDMN), left Executive Control Network (lECN), right Executive Control Network (rECN), anterior Salience Network (aSN), and posterior Salience Network (pSN). By normalizing the data from 32 healthy control subjects to a standard template—using high-dimensional, non-linear warping methods—we were able to create probabilistic white matter atlases for each tract in stereotaxic coordinates. By investigating all 198 ROI-to-ROI combinations within the aforementioned resting-state networks (for a total of 6336 independent DTI tractography analyses), the resulting probabilistic atlases represent a comprehensive cohort of functionally-defined white matter regions that can be used in future brain imaging studies to: (1) ascribe DTI or other white matter changes to particular functional brain networks, and (2) compliment resting state fMRI or other functional connectivity analyses. PMID:26578930

[Introduction of neuroethics: out of clinic, beyond academia in human brain research].

PubMed

Fukushi, Tamami; Sakura, Osamu

2008-11-01

Higher cognitive function in human brain is one of well-developed fields of neuroscience research in the 21st century. Especially functional magnetic resonance imaging (fMRI) and near infrared recording system have brought so many non-clinical researchers whose background is such as cognitive psychology, economics, politics, pedagogy, and so on, to the human brain mapping study. Authors have introduced the ethical issues related to incidental findings during the fMRI recording for non-clinical purpose, which is a typical problem derived from such expanded human brain research under non clinical condition, that is, neuroethics. In the present article we would introduce neuroethical issues in contexts of "out of clinic" and "beyond academia".

Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion

PubMed Central

Power, Jonathan D; Barnes, Kelly A; Snyder, Abraham Z; Schlaggar, Bradley L; Petersen, Steven E

2011-01-01

Here, we demonstrate that subject motion produces substantial changes in the timecourses of resting state functional connectivity MRI (rs-fcMRI) data despite compensatory spatial registration and regression of motion estimates from the data. These changes cause systematic but spurious correlation structures throughout the brain. Specifically, many long-distance correlations are decreased by subject motion, whereas many short-distance correlations are increased. These changes in rs-fcMRI correlations do not arise from, nor are they adequately countered by, some common functional connectivity processing steps. Two indices of data quality are proposed, and a simple method to reduce motion-related effects in rs-fcMRI analyses is demonstrated that should be flexibly implementable across a variety of software platforms. We demonstrate how application of this technique impacts our own data, modifying previous conclusions about brain development. These results suggest the need for greater care in dealing with subject motion, and the need to critically revisit previous rs-fcMRI work that may not have adequately controlled for effects of transient subject movements. PMID:22019881

HAFNI-enabled largescale platform for neuroimaging informatics (HELPNI).

PubMed

Makkie, Milad; Zhao, Shijie; Jiang, Xi; Lv, Jinglei; Zhao, Yu; Ge, Bao; Li, Xiang; Han, Junwei; Liu, Tianming

Tremendous efforts have thus been devoted on the establishment of functional MRI informatics systems that recruit a comprehensive collection of statistical/computational approaches for fMRI data analysis. However, the state-of-the-art fMRI informatics systems are especially designed for specific fMRI sessions or studies of which the data size is not really big, and thus has difficulty in handling fMRI 'big data.' Given the size of fMRI data are growing explosively recently due to the advancement of neuroimaging technologies, an effective and efficient fMRI informatics system which can process and analyze fMRI big data is much needed. To address this challenge, in this work, we introduce our newly developed informatics platform, namely, 'HAFNI-enabled largescale platform for neuroimaging informatics (HELPNI).' HELPNI implements our recently developed computational framework of sparse representation of whole-brain fMRI signals which is called holistic atlases of functional networks and interactions (HAFNI) for fMRI data analysis. HELPNI provides integrated solutions to archive and process large-scale fMRI data automatically and structurally, to extract and visualize meaningful results information from raw fMRI data, and to share open-access processed and raw data with other collaborators through web. We tested the proposed HELPNI platform using publicly available 1000 Functional Connectomes dataset including over 1200 subjects. We identified consistent and meaningful functional brain networks across individuals and populations based on resting state fMRI (rsfMRI) big data. Using efficient sampling module, the experimental results demonstrate that our HELPNI system has superior performance than other systems for large-scale fMRI data in terms of processing and storing the data and associated results much faster.

HAFNI-enabled largescale platform for neuroimaging informatics (HELPNI).

PubMed

Makkie, Milad; Zhao, Shijie; Jiang, Xi; Lv, Jinglei; Zhao, Yu; Ge, Bao; Li, Xiang; Han, Junwei; Liu, Tianming

2015-12-01

Tremendous efforts have thus been devoted on the establishment of functional MRI informatics systems that recruit a comprehensive collection of statistical/computational approaches for fMRI data analysis. However, the state-of-the-art fMRI informatics systems are especially designed for specific fMRI sessions or studies of which the data size is not really big, and thus has difficulty in handling fMRI 'big data.' Given the size of fMRI data are growing explosively recently due to the advancement of neuroimaging technologies, an effective and efficient fMRI informatics system which can process and analyze fMRI big data is much needed. To address this challenge, in this work, we introduce our newly developed informatics platform, namely, 'HAFNI-enabled largescale platform for neuroimaging informatics (HELPNI).' HELPNI implements our recently developed computational framework of sparse representation of whole-brain fMRI signals which is called holistic atlases of functional networks and interactions (HAFNI) for fMRI data analysis. HELPNI provides integrated solutions to archive and process large-scale fMRI data automatically and structurally, to extract and visualize meaningful results information from raw fMRI data, and to share open-access processed and raw data with other collaborators through web. We tested the proposed HELPNI platform using publicly available 1000 Functional Connectomes dataset including over 1200 subjects. We identified consistent and meaningful functional brain networks across individuals and populations based on resting state fMRI (rsfMRI) big data. Using efficient sampling module, the experimental results demonstrate that our HELPNI system has superior performance than other systems for large-scale fMRI data in terms of processing and storing the data and associated results much faster.

Detecting nonlinear dynamics of functional connectivity

NASA Astrophysics Data System (ADS)

LaConte, Stephen M.; Peltier, Scott J.; Kadah, Yasser; Ngan, Shing-Chung; Deshpande, Gopikrishna; Hu, Xiaoping

2004-04-01

Functional magnetic resonance imaging (fMRI) is a technique that is sensitive to correlates of neuronal activity. The application of fMRI to measure functional connectivity of related brain regions across hemispheres (e.g. left and right motor cortices) has great potential for revealing fundamental physiological brain processes. Primarily, functional connectivity has been characterized by linear correlations in resting-state data, which may not provide a complete description of its temporal properties. In this work, we broaden the measure of functional connectivity to study not only linear correlations, but also those arising from deterministic, non-linear dynamics. Here the delta-epsilon approach is extended and applied to fMRI time series. The method of delays is used to reconstruct the joint system defined by a reference pixel and a candidate pixel. The crux of this technique relies on determining whether the candidate pixel provides additional information concerning the time evolution of the reference. As in many correlation-based connectivity studies, we fix the reference pixel. Every brain location is then used as a candidate pixel to estimate the spatial pattern of deterministic coupling with the reference. Our results indicate that measured connectivity is often emphasized in the motor cortex contra-lateral to the reference pixel, demonstrating the suitability of this approach for functional connectivity studies. In addition, discrepancies with traditional correlation analysis provide initial evidence for non-linear dynamical properties of resting-state fMRI data. Consequently, the non-linear characterization provided from our approach may provide a more complete description of the underlying physiology and brain function measured by this type of data.

Antidepressant Effects of Electroconvulsive Therapy Correlate With Subgenual Anterior Cingulate Activity and Connectivity in Depression

PubMed Central

Liu, Yi; Du, Lian; Li, Yongmei; Liu, Haixia; Zhao, Wenjing; Liu, Dan; Zeng, Jinkun; Li, Xingbao; Fu, Yixiao; Qiu, Haitang; Li, Xirong; Qiu, Tian; Hu, Hua; Meng, Huaqing; Luo, Qinghua

2015-01-01

Abstract The mechanisms underlying the effects of electroconvulsive therapy (ECT) in major depressive disorder (MDD) are not fully understood. Resting-state functional magnetic resonance imaging (rs-fMRI) is a new tool to study the effects of brain stimulation interventions, particularly ECT. The authors aim to investigate the mechanisms of ECT in MDD by rs-fMRI. They used rs-fMRI to measure functional changes in the brain of first-episode, treatment-naive MDD patients (n = 23) immediately before and then following 8 ECT sessions (brief-pulse square-wave apparatus, bitemporal). They also computed voxel-wise amplitude of low-frequency fluctuation (ALFF) as a measure of regional brain activity and selected the left subgenual anterior cingulate cortex (sgACC) to evaluate functional connectivity between the sgACC and other brain regions. Increased regional brain activity measured by ALFF mainly in the left sgACC following ECT. Functional connectivity of the left sgACC increased in the ipsilateral parahippocampal gyrus, pregenual ACC, contralateral middle temporal pole, and orbitofrontal cortex. Importantly, reduction in depressive symptoms were negatively correlated with increased ALFF in the left sgACC and left hippocampus, and with distant functional connectivity between the left sgACC and contralateral middle temporal pole. That is, across subjects, as depression improved, regional brain activity in sgACC and its functional connectivity increased in the brain. Eight ECT sessions in MDD patients modulated activity in the sgACC and its networks. The antidepressant effects of ECT were negatively correlated with sgACC brain activity and connectivity. These findings suggest that sgACC-associated prefrontal-limbic structures are associated with the therapeutic effects of ECT in MDD. PMID:26559309

Growth and development of the brain and impact on cognitive outcomes.

PubMed

Hüppi, Petra S

2010-01-01

Understanding human brain development from the fetal life to adulthood is of great clinical importance as many neurological and neurobehavioral disorders have their origin in early structural and functional cerebral maturation. The developing brain is particularly prone to being affected by endogenous and exogenous events through the fetal and early postnatal life. The concept of 'developmental plasticity or disruption of the developmental program' summarizes these events. Increases in white matter, which speed up communication between brain cells, growing complexity of neuronal networks suggested by gray and white matter changes, and environmentally sensitive plasticity are all essential aspects in a child's ability to mentalize and maintain the adaptive flexibility necessary for achieving high sociocognitive functioning. Advancement in neuroimaging has opened up new ways for examining the developing human brain in vivo, the study of the effects of early antenatal, perinatal and neonatal events on later structural and functional brain development resulting in developmental disabilities or developmental resilience. In this review, methods of quantitative assessment of human brain development, such as 3D-MRI with image segmentation, diffusion tensor imaging to assess connectivity and functional MRI to visualize brain function will be presented. Copyright (c) 2010 S. Karger AG, Basel.

Longitudinal assessment of chemotherapy-induced changes in brain and cognitive functioning: A systematic review.

PubMed

Li, Mingmei; Caeyenberghs, Karen

2018-05-20

In addition to the burden of a life-threatening diagnosis, cancer patients are struggling with adverse side-effects from cancer treatment. Chemotherapy has been linked to an array of cognitive impairments and alterations in brain structure and function ("chemobrain"). In this review, we summarized the existing evidence that evaluate the changes in cognitive functioning and brain with chemotherapy, as assessed using structural and functional MRI-based techniques in a longitudinal design. This review followed the latest PRISMA guidelines using Embase, Medline, PsychINFO, Scopus, and Web of Science databases with date restrictions from 2012-2017. Fourteen research articles met the key inclusion criteria: (i) the studies involved adult cancer patients (mean age≥18); (ii) the use of chemotherapy in the treatment of cancer; (iii) pre-post assessment of behavioral and brain-based outcomes; and (iv) abstracts written in English. Effect sizes of subjective and objective cognitive impairments from the reviewed studies were estimated using Cohen's d or z-scores. We calculated percentage of mean change or effect sizes for main neuroimaging findings when data were available. Strength of the correlations between brain alterations and cognitive changes was obtained using squared correlation coefficients. We showed small to medium effect sizes on individual tests of attention, processing speed, verbal memory, and executive control; and medium effect sizes on self-report questionnaires. Neuroimaging data showed reduced grey matter density in cancer patients in frontal, parietal, and temporal regions. Changes in brain function (brain activation and cerebral blood flow) were observed with cancer across functional networks involving (pre)frontal, parietal, occipital, temporal, and cerebellar regions. Data from diffusion-weighted MRI suggested reduced white matter integrity involving the superior longitudinal fasciculus, corpus callosum, forceps major, and corona radiate, and altered structural connectivity across the whole brain network. Finally, we observed moderate-to-strong correlations between worsening cognitive function and morphological changes in frontal brain regions. While MRI is a powerful tool for detection of longitudinal brain changes in the 'chemobrain', the underlying biological mechanisms are still unclear. Continued work in this field will hopefully detect MRI metrics to be used as biomarkers to help guide cognitive treatment at the individual cancer patient level. Copyright © 2018. Published by Elsevier Ltd.

Visual imagery and functional connectivity in blindness: a single-case study

PubMed Central

Boucard, Christine C.; Rauschecker, Josef P.; Neufang, Susanne; Berthele, Achim; Doll, Anselm; Manoliu, Andrej; Riedl, Valentin; Sorg, Christian; Wohlschläger, Afra; Mühlau, Mark

2016-01-01

We present a case report on visual brain plasticity after total blindness acquired in adulthood. SH lost her sight when she was 27. Despite having been totally blind for 43 years, she reported to strongly rely on her vivid visual imagery. Three-Tesla magnetic resonance imaging (MRI) of SH and age-matched controls was performed. The MRI sequence included anatomical MRI, resting-state functional MRI, and task-related functional MRI where SH was instructed to imagine colours, faces, and motion. Compared to controls, voxel-based analysis revealed white matter loss along SH's visual pathway as well as grey matter atrophy in the calcarine sulci. Yet we demonstrated activation in visual areas, including V1, using functional MRI. Of the four identified visual resting-state networks, none showed alterations in spatial extent; hence, SH's preserved visual imagery seems to be mediated by intrinsic brain networks of normal extent. Time courses of two of these networks showed increased correlation with that of the inferior posterior default mode network, which may reflect adaptive changes supporting SH's strong internal visual representations. Overall, our findings demonstrate that conscious visual experience is possible even after years of absence of extrinsic input. PMID:25690326

Visual imagery and functional connectivity in blindness: a single-case study.

PubMed

Boucard, Christine C; Rauschecker, Josef P; Neufang, Susanne; Berthele, Achim; Doll, Anselm; Manoliu, Andrej; Riedl, Valentin; Sorg, Christian; Wohlschläger, Afra; Mühlau, Mark

2016-05-01

We present a case report on visual brain plasticity after total blindness acquired in adulthood. SH lost her sight when she was 27. Despite having been totally blind for 43 years, she reported to strongly rely on her vivid visual imagery. Three-Tesla magnetic resonance imaging (MRI) of SH and age-matched controls was performed. The MRI sequence included anatomical MRI, resting-state functional MRI, and task-related functional MRI where SH was instructed to imagine colours, faces, and motion. Compared to controls, voxel-based analysis revealed white matter loss along SH's visual pathway as well as grey matter atrophy in the calcarine sulci. Yet we demonstrated activation in visual areas, including V1, using functional MRI. Of the four identified visual resting-state networks, none showed alterations in spatial extent; hence, SH's preserved visual imagery seems to be mediated by intrinsic brain networks of normal extent. Time courses of two of these networks showed increased correlation with that of the inferior posterior default mode network, which may reflect adaptive changes supporting SH's strong internal visual representations. Overall, our findings demonstrate that conscious visual experience is possible even after years of absence of extrinsic input.

Fast periodic stimulation (FPS): a highly effective approach in fMRI brain mapping.

PubMed

Gao, Xiaoqing; Gentile, Francesco; Rossion, Bruno

2018-06-01

Defining the neural basis of perceptual categorization in a rapidly changing natural environment with low-temporal resolution methods such as functional magnetic resonance imaging (fMRI) is challenging. Here, we present a novel fast periodic stimulation (FPS)-fMRI approach to define face-selective brain regions with natural images. Human observers are presented with a dynamic stream of widely variable natural object images alternating at a fast rate (6 images/s). Every 9 s, a short burst of variable face images contrasting with object images in pairs induces an objective face-selective neural response at 0.111 Hz. A model-free Fourier analysis achieves a twofold increase in signal-to-noise ratio compared to a conventional block-design approach with identical stimuli and scanning duration, allowing to derive a comprehensive map of face-selective areas in the ventral occipito-temporal cortex, including the anterior temporal lobe (ATL), in all individual brains. Critically, periodicity of the desired category contrast and random variability among widely diverse images effectively eliminates the contribution of low-level visual cues, and lead to the highest values (80-90%) of test-retest reliability in the spatial activation map yet reported in imaging higher level visual functions. FPS-fMRI opens a new avenue for understanding brain function with low-temporal resolution methods.

A multimodal MRI dataset of professional chess players.

PubMed

Li, Kaiming; Jiang, Jing; Qiu, Lihua; Yang, Xun; Huang, Xiaoqi; Lui, Su; Gong, Qiyong

2015-01-01

Chess is a good model to study high-level human brain functions such as spatial cognition, memory, planning, learning and problem solving. Recent studies have demonstrated that non-invasive MRI techniques are valuable for researchers to investigate the underlying neural mechanism of playing chess. For professional chess players (e.g., chess grand masters and masters or GM/Ms), what are the structural and functional alterations due to long-term professional practice, and how these alterations relate to behavior, are largely veiled. Here, we report a multimodal MRI dataset from 29 professional Chinese chess players (most of whom are GM/Ms), and 29 age matched novices. We hope that this dataset will provide researchers with new materials to further explore high-level human brain functions.

Effects of hypoglycemia on human brain activation measured with fMRI.

PubMed

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 < .05). These changes were reversed when euglycemia was restored. These data provide a basis of comparison for studies that quantify hypoglycemia-related changes in fMRI activity during cognitive tasks based on visual stimuli and demonstrate that variations in blood glucose levels may modulate BOLD signals in the healthy brain.

Maintenance and Representation of Mind Wandering during Resting-State fMRI.

PubMed

Chou, Ying-Hui; Sundman, Mark; Whitson, Heather E; Gaur, Pooja; Chu, Mei-Lan; Weingarten, Carol P; Madden, David J; Wang, Lihong; Kirste, Imke; Joliot, Marc; Diaz, Michele T; Li, Yi-Ju; Song, Allen W; Chen, Nan-Kuei

2017-01-12

Major advances in resting-state functional magnetic resonance imaging (fMRI) techniques in the last two decades have provided a tool to better understand the functional organization of the brain both in health and illness. Despite such developments, characterizing regulation and cerebral representation of mind wandering, which occurs unavoidably during resting-state fMRI scans and may induce variability of the acquired data, remains a work in progress. Here, we demonstrate that a decrease or decoupling in functional connectivity involving the caudate nucleus, insula, medial prefrontal cortex and other domain-specific regions was associated with more sustained mind wandering in particular thought domains during resting-state fMRI. Importantly, our findings suggest that temporal and between-subject variations in functional connectivity of above-mentioned regions might be linked with the continuity of mind wandering. Our study not only provides a preliminary framework for characterizing the maintenance and cerebral representation of different types of mind wandering, but also highlights the importance of taking mind wandering into consideration when studying brain organization with resting-state fMRI in the future.

Functional magnetic resonance imaging: basic principles and application in the neurosciences.

PubMed

Labbé Atenas, T; Ciampi Díaz, E; Cruz Quiroga, J P; Uribe Arancibia, S; Cárcamo Rodríguez, C

2018-03-12

Functional magnetic resonance imaging (fMRI) is an advanced tool for the study of brain functions in healthy subjects and in neuropsychiatric patients. This tool makes it possible to identify and locate specific phenomena related to neuronal metabolism and activity. Starting with the detection of changes in the blood supply to a region that participates in a function, more complex approaches have been developed to study the dynamics of neuronal networks. Studies examining the brain at rest or involved in different tasks have provided evidence related to the onset, development, and/or response to treatment in various diseases. The diversity of the possible artifacts associated with image registration as well as the complexity of the analytical experimental designs has generated abundant debate about the technique behind fMRI. This article aims to introduce readers to the fundamentals underlying fMRI, to explain how fMRI studies are interpreted, and to discuss fMRI's contributions to the study of the mechanisms underlying diverse diseases of the nervous system. Copyright © 2018 SERAM. Publicado por Elsevier España, S.L.U. All rights reserved.

Altered spontaneous brain activity in MRI-negative refractory temporal lobe epilepsy patients with major depressive disorder: A resting-state fMRI study.

PubMed

Zhu, Xi; He, Zhongqiong; Luo, Cheng; Qiu, Xiangmiao; He, Shixu; Peng, Anjiao; Zhang, Lin; Chen, Lei

2018-03-15

To investigate alterations in spontaneous brain activity in MRI-negative refractory temporal lobe epilepsy patients with major depressive disorder using resting-state functional magnetic resonance imaging (RS-fMRI). Eighteen MRI-negative refractory temporal lobe epilepsy patients with major depressive disorder (PDD), 17 MRI-negative refractory temporal lobe epilepsy patients without major depressive disorder (nPDD), and 21 matched healthy controls (HC) were recruited from West China Hospital of SiChuan University from April 2016 to June 2017. The Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) and 17-item Hamilton Depression Rating Scale were employed to confirm the diagnosis of major depressive disorder and assess the severity of depression. All participants underwent RS-fMRI scans using a 3.0T MRI system. MRI data were compared and analyzed using the amplitude of low-frequency fluctuations (ALFF) and regional homogeneity (ReHo) to measure spontaneous brain activity. These two methods were both used to evaluate spontaneous cerebral activity. The PDD group showed significantly altered spontaneous brain activity in the bilateral mesial prefrontal cortex, precuneus, angular gyrus, right parahippocampal gyrus, and right temporal pole. Meanwhile, compared with HC, the nPDD group demonstrated altered spontaneous brain activity in the temporal neocortex but no changes in mesial temporal structures. The PDD group showed regional brain activity alterations in the prefrontal-limbic system and dysfunction of the default mode network. The underlying pathophysiology of PDD may be provided for further studies. Copyright © 2018 Elsevier B.V. All rights reserved.

Motor programme activating therapy influences adaptive brain functions in multiple sclerosis: clinical and MRI study.

PubMed

Rasova, Kamila; Prochazkova, Marie; Tintera, Jaroslav; Ibrahim, Ibrahim; Zimova, Denisa; Stetkarova, Ivana

2015-03-01

There is still little scientific evidence for the efficacy of neurofacilitation approaches and their possible influence on brain plasticity and adaptability. In this study, the outcome of a new kind of neurofacilitation approach, motor programme activating therapy (MPAT), was evaluated on the basis of a set of clinical functions and with MRI. Eighteen patients were examined four times with standardized clinical tests and diffusion tensor imaging to monitor changes without therapy, immediately after therapy and 1 month after therapy. Moreover, the strength of effective connectivity was analysed before and after therapy. Patients underwent a 1-h session of MPAT twice a week for 2 months. The data were analysed by nonparametric tests of association and were subsequently statistically evaluated. The therapy led to significant improvement in clinical functions, significant increment of fractional anisotropy and significant decrement of mean diffusivity, and decrement of effective connectivity at supplementary motor areas was observed immediately after the therapy. Changes in clinical functions and diffusion tensor images persisted 1 month after completing the programme. No statistically significant changes in clinical functions and no differences in MRI-diffusion tensor images were observed without physiotherapy. Positive immediate and long-term effects of MPAT on clinical and brain functions, as well as brain microstructure, were confirmed.

Enhancing Motor Network Activity Using Real-Time Functional MRI Neurofeedback of Left Premotor Cortex

PubMed Central

Marins, Theo F.; Rodrigues, Erika C.; Engel, Annerose; Hoefle, Sebastian; Basílio, Rodrigo; Lent, Roberto; Moll, Jorge; Tovar-Moll, Fernanda

2015-01-01

Neurofeedback by functional magnetic resonance imaging (fMRI) is a technique of potential therapeutic relevance that allows individuals to be aware of their own neurophysiological responses and to voluntarily modulate the activity of specific brain regions, such as the premotor cortex (PMC), important for motor recovery after brain injury. We investigated (i) whether healthy human volunteers are able to up-regulate the activity of the left PMC during a right hand finger tapping motor imagery (MI) task while receiving continuous fMRI-neurofeedback, and (ii) whether successful modulation of brain activity influenced non-targeted motor control regions. During the MI task, participants of the neurofeedback group (NFB) received ongoing visual feedback representing the level of fMRI responses within their left PMC. Control (CTL) group participants were shown similar visual stimuli, but these were non-contingent on brain activity. Both groups showed equivalent levels of behavioral ratings on arousal and MI, before and during the fMRI protocol. In the NFB, but not in CLT group, brain activation during the last run compared to the first run revealed increased activation in the left PMC. In addition, the NFB group showed increased activation in motor control regions extending beyond the left PMC target area, including the supplementary motor area, basal ganglia and cerebellum. Moreover, in the last run, the NFB group showed stronger activation in the left PMC/inferior frontal gyrus when compared to the CTL group. Our results indicate that modulation of PMC and associated motor control areas can be achieved during a single neurofeedback-fMRI session. These results contribute to a better understanding of the underlying mechanisms of MI-based neurofeedback training, with direct implications for rehabilitation strategies in severe brain disorders, such as stroke. PMID:26733832

MRI measurements of Blood-Brain Barrier function in dementia: A review of recent studies.

PubMed

Raja, Rajikha; Rosenberg, Gary A; Caprihan, Arvind

2018-05-15

Blood-brain barrier (BBB) separates the systemic circulation and the brain, regulating transport of most molecules to protect the brain microenvironment. Multiple structural and functional components preserve the integrity of the BBB. Several imaging modalities are available to study disruption of the BBB. However, the subtle changes in BBB leakage that occurs in vascular cognitive impairment and Alzheimer's disease have been less well studied. Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) is the most widely adopted non-invasive imaging technique for evaluating BBB breakdown. It is used as a significant marker for a wide variety of diseases with large permeability leaks, such as brain tumors and multiple sclerosis, to more subtle disruption in chronic vascular disease and dementia. DCE-MRI analysis of BBB includes both model-free parameters and quantitative parameters using pharmacokinetic modelling. We review MRI studies of BBB breakdown in dementia. The challenges in measuring subtle BBB changes and the state of the art techniques are initially examined. Subsequently, a systematic review comparing methodologies from recent in-vivo MRI studies is presented. Various factors related to subtle BBB permeability measurement such as DCE-MRI acquisition parameters, arterial input assessment, T 1 mapping and data analysis methods are reviewed with the focus on finding the optimal technique. Finally, the reported BBB permeability values in dementia are compared across different studies and across various brain regions. We conclude that reliable measurement of low-level BBB permeability across sites remains a difficult problem and a standardization of the methodology for both data acquisition and quantitative analysis is required. This article is part of the Special Issue entitled 'Cerebral Ischemia'. Copyright © 2017 Elsevier Ltd. All rights reserved.

Comparison of fMRI paradigms assessing visuospatial processing: Robustness and reproducibility

PubMed Central

Herholz, Peer; Zimmermann, Kristin M.; Westermann, Stefan; Frässle, Stefan; Jansen, Andreas

2017-01-01

The development of brain imaging techniques, in particular functional magnetic resonance imaging (fMRI), made it possible to non-invasively study the hemispheric lateralization of cognitive brain functions in large cohorts. Comprehensive models of hemispheric lateralization are, however, still missing and should not only account for the hemispheric specialization of individual brain functions, but also for the interactions among different lateralized cognitive processes (e.g., language and visuospatial processing). This calls for robust and reliable paradigms to study hemispheric lateralization for various cognitive functions. While numerous reliable imaging paradigms have been developed for language, which represents the most prominent left-lateralized brain function, the reliability of imaging paradigms investigating typically right-lateralized brain functions, such as visuospatial processing, has received comparatively less attention. In the present study, we aimed to establish an fMRI paradigm that robustly and reliably identifies right-hemispheric activation evoked by visuospatial processing in individual subjects. In a first study, we therefore compared three frequently used paradigms for assessing visuospatial processing and evaluated their utility to robustly detect right-lateralized brain activity on a single-subject level. In a second study, we then assessed the test-retest reliability of the so-called Landmark task–the paradigm that yielded the most robust results in study 1. At the single-voxel level, we found poor reliability of the brain activation underlying visuospatial attention. This suggests that poor signal-to-noise ratios can become a limiting factor for test-retest reliability. This represents a common detriment of fMRI paradigms investigating visuospatial attention in general and therefore highlights the need for careful considerations of both the possibilities and limitations of the respective fMRI paradigm–in particular, when being interested in effects at the single-voxel level. Notably, however, when focusing on the reliability of measures of hemispheric lateralization (which was the main goal of study 2), we show that hemispheric dominance (quantified by the lateralization index, LI, with |LI| >0.4) of the evoked activation could be robustly determined in more than 62% and, if considering only two categories (i.e., left, right), in more than 93% of our subjects. Furthermore, the reliability of the lateralization strength (LI) was “fair” to “good”. In conclusion, our results suggest that the degree of right-hemispheric dominance during visuospatial processing can be reliably determined using the Landmark task, both at the group and single-subject level, while at the same time stressing the need for future refinements of experimental paradigms and more sophisticated fMRI data acquisition techniques. PMID:29059201

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

PubMed

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 cognitive processes in MS.

ALE Meta-Analysis of Schizophrenics Performing the N-Back Task

NASA Astrophysics Data System (ADS)

Harrell, Zachary

2010-10-01

MRI/fMRI has already proven itself as a valuable tool in the diagnosis and treatment of many illnesses of the brain, including cognitive problems. By exploiting the differences in magnetic susceptibility between oxygenated and deoxygenated hemoglobin, fMRI can measure blood flow in various regions of interest within the brain. This can determine the level of brain activity in relation to motor or cognitive functions and provide a metric for tissue damage or illness symptoms. Structural imaging techniques have shown lesions or deficiencies in tissue volumes in schizophrenics corresponding to areas primarily in the frontal and temporal lobes. These areas are currently known to be involved in working memory and attention, which many schizophrenics have trouble with. The ALE (Activation Likelihood Estimation) Meta-Analysis is able to statistically determine the significance of brain area activations based on the post-hoc combination of multiple studies. This process is useful for giving a general model of brain function in relation to a particular task designed to engage the affected areas (such as working memory for the n-back task). The advantages of the ALE Meta-Analysis include elimination of single subject anomalies, elimination of false/extremely weak activations, and verification of function/location hypotheses.

Reorganization of functional brain networks mediates the improvement of cognitive performance following real-time neurofeedback training of working memory.

PubMed

Zhang, Gaoyan; Yao, Li; Shen, Jiahui; Yang, Yihong; Zhao, Xiaojie

2015-05-01

Working memory (WM) is essential for individuals' cognitive functions. Neuroimaging studies indicated that WM fundamentally relied on a frontoparietal working memory network (WMN) and a cinguloparietal default mode network (DMN). Behavioral training studies demonstrated that the two networks can be modulated by WM training. Different from the behavioral training, our recent study used a real-time functional MRI (rtfMRI)-based neurofeedback method to conduct WM training, demonstrating that WM performance can be significantly improved after successfully upregulating the activity of the target region of interest (ROI) in the left dorsolateral prefrontal cortex (Zhang et al., [2013]: PloS One 8:e73735); however, the neural substrate of rtfMRI-based WM training remains unclear. In this work, we assessed the intranetwork and internetwork connectivity changes of WMN and DMN during the training, and their correlations with the change of brain activity in the target ROI as well as with the improvement of post-training behavior. Our analysis revealed an "ROI-network-behavior" correlation relationship underlying the rtfMRI training. Further mediation analysis indicated that the reorganization of functional brain networks mediated the effect of self-regulation of the target brain activity on the improvement of cognitive performance following the neurofeedback training. The results of this study enhance our understanding of the neural basis of real-time neurofeedback and suggest a new direction to improve WM performance by regulating the functional connectivity in the WM related networks. © 2014 Wiley Periodicals, Inc.

Rapid geodesic mapping of brain functional connectivity: implementation of a dedicated co-processor in a field-programmable gate array (FPGA) and application to resting state functional MRI.

PubMed

Minati, Ludovico; Cercignani, Mara; Chan, Dennis

2013-10-01

Graph theory-based analyses of brain network topology can be used to model the spatiotemporal correlations in neural activity detected through fMRI, and such approaches have wide-ranging potential, from detection of alterations in preclinical Alzheimer's disease through to command identification in brain-machine interfaces. However, due to prohibitive computational costs, graph-based analyses to date have principally focused on measuring connection density rather than mapping the topological architecture in full by exhaustive shortest-path determination. This paper outlines a solution to this problem through parallel implementation of Dijkstra's algorithm in programmable logic. The processor design is optimized for large, sparse graphs and provided in full as synthesizable VHDL code. An acceleration factor between 15 and 18 is obtained on a representative resting-state fMRI dataset, and maps of Euclidean path length reveal the anticipated heterogeneous cortical involvement in long-range integrative processing. These results enable high-resolution geodesic connectivity mapping for resting-state fMRI in patient populations and real-time geodesic mapping to support identification of imagined actions for fMRI-based brain-machine interfaces. Copyright © 2013 IPEM. Published by Elsevier Ltd. All rights reserved.

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

PubMed

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).

Simultaneous MRI and PET imaging of a rat brain

NASA Astrophysics Data System (ADS)

Raylman, Raymond R.; Majewski, Stan; Lemieux, Susan K.; Sendhil Velan, S.; Kross, Brian; Popov, Vladimir; Smith, Mark F.; Weisenberger, Andrew G.; Zorn, Carl; Marano, Gary D.

2006-12-01

Multi-modality imaging is rapidly becoming a valuable tool in the diagnosis of disease and in the development of new drugs. Functional images produced with PET fused with anatomical structure images created by MRI will allow the correlation of form with function. Our group is developing a system to acquire MRI and PET images contemporaneously. The prototype device consists of two opposed detector heads, operating in coincidence mode. Each MRI-PET detector module consists of an array of LSO detector elements coupled through a long fibre optic light guide to a single Hamamatsu flat panel position-sensitive photomultiplier tube (PSPMT). The use of light guides allows the PSPMTs to be positioned outside the bore of a 3T MRI scanner where the magnetic field is relatively small. To test the device, simultaneous MRI and PET images of the brain of a male Sprague Dawley rat injected with FDG were successfully obtained. The images revealed no noticeable artefacts in either image set. Future work includes the construction of a full ring PET scanner, improved light guides and construction of a specialized MRI coil to permit higher quality MRI imaging.

Biocytin-Derived MRI Contrast Agent for Longitudinal Brain Connectivity Studies

PubMed Central

2011-01-01

To investigate the connectivity of brain networks noninvasively and dynamically, we have developed a new strategy to functionalize neuronal tracers and designed a biocompatible probe that can be visualized in vivo using magnetic resonance imaging (MRI). Furthermore, the multimodal design used allows combined ex vivo studies with microscopic spatial resolution by conventional histochemical techniques. We present data on the functionalization of biocytin, a well-known neuronal tract tracer, and demonstrate the validity of the approach by showing brain networks of cortical connectivity in live rats under MRI, together with the corresponding microscopic details, such as fibers and neuronal morphology under light microscopy. We further demonstrate that the developed molecule is the first MRI-visible probe to preferentially trace retrograde connections. Our study offers a new platform for the development of multimodal molecular imaging tools of broad interest in neuroscience, that capture in vivo the dynamics of large scale neural networks together with their microscopic characteristics, thereby spanning several organizational levels. PMID:22860157

Clinical utility of resting-state functional connectivity magnetic resonance imaging for mood and cognitive disorders.

PubMed

Takamura, T; Hanakawa, T

2017-07-01

Although functional magnetic resonance imaging (fMRI) has long been used to assess task-related brain activity in neuropsychiatric disorders, it has not yet become a widely available clinical tool. Resting-state fMRI (rs-fMRI) has been the subject of recent attention in the fields of basic and clinical neuroimaging research. This method enables investigation of the functional organization of the brain and alterations of resting-state networks (RSNs) in patients with neuropsychiatric disorders. Rs-fMRI does not require participants to perform a demanding task, in contrast to task fMRI, which often requires participants to follow complex instructions. Rs-fMRI has a number of advantages over task fMRI for application with neuropsychiatric patients, for example, although applications of task fMR to participants for healthy are easy. However, it is difficult to apply these applications to patients with psychiatric and neurological disorders, because they may have difficulty in performing demanding cognitive task. Here, we review the basic methodology and analysis techniques relevant to clinical studies, and the clinical applications of the technique for examining neuropsychiatric disorders, focusing on mood disorders (major depressive disorder and bipolar disorder) and dementia (Alzheimer's disease and mild cognitive impairment).

Functional Magnetic Resonance Imaging

ERIC Educational Resources Information Center

Voos, Avery; Pelphrey, Kevin

2013-01-01

Functional magnetic resonance imaging (fMRI), with its excellent spatial resolution and ability to visualize networks of neuroanatomical structures involved in complex information processing, has become the dominant technique for the study of brain function and its development. The accessibility of in-vivo pediatric brain-imaging techniques…

Evaluating effects of methylphenidate on brain activity in cocaine addiction: a machine-learning approach

NASA Astrophysics Data System (ADS)

Rish, Irina; Bashivan, Pouya; Cecchi, Guillermo A.; Goldstein, Rita Z.

2016-03-01

The objective of this study is to investigate effects of methylphenidate on brain activity in individuals with cocaine use disorder (CUD) using functional MRI (fMRI). Methylphenidate hydrochloride (MPH) is an indirect dopamine agonist commonly used for treating attention deficit/hyperactivity disorders; it was also shown to have some positive effects on CUD subjects, such as improved stop signal reaction times associated with better control/inhibition,1 as well as normalized task-related brain activity2 and resting-state functional connectivity in specific areas.3 While prior fMRI studies of MPH in CUDs have focused on mass-univariate statistical hypothesis testing, this paper evaluates multivariate, whole-brain effects of MPH as captured by the generalization (prediction) accuracy of different classification techniques applied to features extracted from resting-state functional networks (e.g., node degrees). Our multivariate predictive results based on resting-state data from3 suggest that MPH tends to normalize network properties such as voxel degrees in CUD subjects, thus providing additional evidence for potential benefits of MPH in treating cocaine addiction.

A Novel Data-Driven Approach to Preoperative Mapping of Functional Cortex Using Resting-State Functional Magnetic Resonance Imaging

PubMed Central

Mitchell, Timothy J.; Hacker, Carl D.; Breshears, Jonathan D.; Szrama, Nick P.; Sharma, Mohit; Bundy, David T.; Pahwa, Mrinal; Corbetta, Maurizio; Snyder, Abraham Z.; Shimony, Joshua S.

2013-01-01

BACKGROUND: Recent findings associated with resting-state cortical networks have provided insight into the brain's organizational structure. In addition to their neuroscientific implications, the networks identified by resting-state functional magnetic resonance imaging (rs-fMRI) may prove useful for clinical brain mapping. OBJECTIVE: To demonstrate that a data-driven approach to analyze resting-state networks (RSNs) is useful in identifying regions classically understood to be eloquent cortex as well as other functional networks. METHODS: This study included 6 patients undergoing surgical treatment for intractable epilepsy and 7 patients undergoing tumor resection. rs-fMRI data were obtained before surgery and 7 canonical RSNs were identified by an artificial neural network algorithm. Of these 7, the motor and language networks were then compared with electrocortical stimulation (ECS) as the gold standard in the epilepsy patients. The sensitivity and specificity for identifying these eloquent sites were calculated at varying thresholds, which yielded receiver-operating characteristic (ROC) curves and their associated area under the curve (AUC). RSNs were plotted in the tumor patients to observe RSN distortions in altered anatomy. RESULTS: The algorithm robustly identified all networks in all patients, including those with distorted anatomy. When all ECS-positive sites were considered for motor and language, rs-fMRI had AUCs of 0.80 and 0.64, respectively. When the ECS-positive sites were analyzed pairwise, rs-fMRI had AUCs of 0.89 and 0.76 for motor and language, respectively. CONCLUSION: A data-driven approach to rs-fMRI may be a new and efficient method for preoperative localization of numerous functional brain regions. ABBREVIATIONS: AUC, area under the curve BA, Brodmann area BOLD, blood oxygen level dependent ECS, electrocortical stimulation fMRI, functional magnetic resonance imaging ICA, independent component analysis MLP, multilayer perceptron MP-RAGE, magnetization-prepared rapid gradient echo ROC, receiver-operating characteristic rs-fMRI, resting-state functional magnetic resonance imaging RSN, resting-state network PMID:24264234

Sparse network-based models for patient classification using fMRI

PubMed Central

Rosa, Maria J.; Portugal, Liana; Hahn, Tim; Fallgatter, Andreas J.; Garrido, Marta I.; Shawe-Taylor, John; Mourao-Miranda, Janaina

2015-01-01

Pattern recognition applied to whole-brain neuroimaging data, such as functional Magnetic Resonance Imaging (fMRI), has proved successful at discriminating psychiatric patients from healthy participants. However, predictive patterns obtained from whole-brain voxel-based features are difficult to interpret in terms of the underlying neurobiology. Many psychiatric disorders, such as depression and schizophrenia, are thought to be brain connectivity disorders. Therefore, pattern recognition based on network models might provide deeper insights and potentially more powerful predictions than whole-brain voxel-based approaches. Here, we build a novel sparse network-based discriminative modeling framework, based on Gaussian graphical models and L1-norm regularized linear Support Vector Machines (SVM). In addition, the proposed framework is optimized in terms of both predictive power and reproducibility/stability of the patterns. Our approach aims to provide better pattern interpretation than voxel-based whole-brain approaches by yielding stable brain connectivity patterns that underlie discriminative changes in brain function between the groups. We illustrate our technique by classifying patients with major depressive disorder (MDD) and healthy participants, in two (event- and block-related) fMRI datasets acquired while participants performed a gender discrimination and emotional task, respectively, during the visualization of emotional valent faces. PMID:25463459

FMRI connectivity analysis of acupuncture effects on an amygdala-associated brain network

PubMed Central

Qin, Wei; Tian, Jie; Bai, Lijun; Pan, Xiaohong; Yang, Lin; Chen, Peng; Dai, Jianping; Ai, Lin; Zhao, Baixiao; Gong, Qiyong; Wang, Wei; von Deneen, Karen M; Liu, Yijun

2008-01-01

Background Recently, increasing evidence has indicated that the primary acupuncture effects are mediated by the central nervous system. However, specific brain networks underpinning these effects remain unclear. Results In the present study using fMRI, we employed a within-condition interregional covariance analysis method to investigate functional connectivity of brain networks involved in acupuncture. The fMRI experiment was performed before, during and after acupuncture manipulations on healthy volunteers at an acupuncture point, which was previously implicated in a neural pathway for pain modulation. We first identified significant fMRI signal changes during acupuncture stimulation in the left amygdala, which was subsequently selected as a functional reference for connectivity analyses. Our results have demonstrated that there is a brain network associated with the amygdala during a resting condition. This network encompasses the brain structures that are implicated in both pain sensation and pain modulation. We also found that such a pain-related network could be modulated by both verum acupuncture and sham acupuncture. Furthermore, compared with a sham acupuncture, the verum acupuncture induced a higher level of correlations among the amygdala-associated network. Conclusion Our findings indicate that acupuncture may change this amygdala-specific brain network into a functional state that underlies pain perception and pain modulation. PMID:19014532

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

PubMed

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

2012-01-01

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

Functional Connectivity Mapping in the Animal Model: Principles and Applications of Resting-State fMRI

PubMed Central

Gorges, Martin; Roselli, Francesco; Müller, Hans-Peter; Ludolph, Albert C.; Rasche, Volker; Kassubek, Jan

2017-01-01

“Resting-state” fMRI has substantially contributed to the understanding of human and non-human functional brain organization by the analysis of correlated patterns in spontaneous activity within dedicated brain systems. Spontaneous neural activity is indirectly measured from the blood oxygenation level-dependent signal as acquired by echo planar imaging, when subjects quietly “resting” in the scanner. Animal models including disease or knockout models allow a broad spectrum of experimental manipulations not applicable in humans. The non-invasive fMRI approach provides a promising tool for cross-species comparative investigations. This review focuses on the principles of “resting-state” functional connectivity analysis and its applications to living animals. The translational aspect from in vivo animal models toward clinical applications in humans is emphasized. We introduce the fMRI-based investigation of the non-human brain’s hemodynamics, the methodological issues in the data postprocessing, and the functional data interpretation from different abstraction levels. The longer term goal of integrating fMRI connectivity data with structural connectomes obtained with tracing and optical imaging approaches is presented and will allow the interrogation of fMRI data in terms of directional flow of information and may identify the structural underpinnings of observed functional connectivity patterns. PMID:28539914

Residual effects of cannabis use in adolescent and adult brains - A meta-analysis of fMRI studies.

PubMed

Blest-Hopley, Grace; Giampietro, Vincent; Bhattacharyya, Sagnik

2018-05-01

While numerous studies have investigated the residual effects of cannabis use on human brain function, results of these studies have been inconsistent. Using meta-analytic approaches we summarize the effects of prolonged cannabis exposure on human brain function as measured using task-based functional MRI (fMRI) across studies employing a range of cognitive activation tasks comparing regular cannabis users with non-users. Separate meta-analyses were carried out for studies investigating adult and adolescent cannabis users. Systematic literature search identified 20 manuscripts (13 adult and 7 adolescent studies) meeting study inclusion criteria. Adult analyses compared 530 cannabis users to 580 healthy controls while adolescent analyses compared 219 cannabis users to 224 healthy controls. In adult cannabis users brain activation was increased in the superior and posterior transverse temporal and inferior frontal gyri and decreased in the striate area, insula and middle temporal gyrus. In adolescent cannabis users, activation was increased in the inferior parietal gyrus and putamen compared to healthy controls. Functional alteration in these areas may reflect compensatory neuroadaptive changes in cannabis users. Copyright © 2018 Elsevier Ltd. All rights reserved.

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

PubMed Central

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

2016-01-01

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

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

PubMed

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.

Abnormal resting-state connectivity of motor and cognitive networks in early manifest Huntington's disease.

PubMed

Wolf, R C; Sambataro, F; Vasic, N; Depping, M S; Thomann, P A; Landwehrmeyer, G B; Süssmuth, S D; Orth, M

2014-11-01

Functional magnetic resonance imaging (fMRI) of multiple neural networks during the brain's 'resting state' could facilitate biomarker development in patients with Huntington's disease (HD) and may provide new insights into the relationship between neural dysfunction and clinical symptoms. To date, however, very few studies have examined the functional integrity of multiple resting state networks (RSNs) in manifest HD, and even less is known about whether concomitant brain atrophy affects neural activity in patients. Using MRI, we investigated brain structure and RSN function in patients with early HD (n = 20) and healthy controls (n = 20). For resting-state fMRI data a group-independent component analysis identified spatiotemporally distinct patterns of motor and prefrontal RSNs of interest. We used voxel-based morphometry to assess regional brain atrophy, and 'biological parametric mapping' analyses to investigate the impact of atrophy on neural activity. Compared with controls, patients showed connectivity changes within distinct neural systems including lateral prefrontal, supplementary motor, thalamic, cingulate, temporal and parietal regions. In patients, supplementary motor area and cingulate cortex connectivity indices were associated with measures of motor function, whereas lateral prefrontal connectivity was associated with cognition. This study provides evidence for aberrant connectivity of RSNs associated with motor function and cognition in early manifest HD when controlling for brain atrophy. This suggests clinically relevant changes of RSN activity in the presence of HD-associated cortical and subcortical structural abnormalities.

A review of technical aspects of T1-weighted dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in human brain tumors.

PubMed

Bergamino, M; Bonzano, L; Levrero, F; Mancardi, G L; Roccatagliata, L

2014-09-01

In the last few years, several imaging methods, such as magnetic resonance imaging (MRI) and computed tomography, have been used to investigate the degree of blood-brain barrier (BBB) permeability in patients with neurological diseases including multiple sclerosis, ischemic stroke, and brain tumors. One promising MRI method for assessing the BBB permeability of patients with neurological diseases in vivo is T1-weighted dynamic contrast-enhanced (DCE)-MRI. Here we review the technical issues involved in DCE-MRI in the study of human brain tumors. In the first part of this paper, theoretical models for the DCE-MRI analysis will be described, including the Toft-Kety models, the adiabatic approximation to the tissue homogeneity model and the two-compartment exchange model. These models can be used to estimate important kinetic parameters related to BBB permeability. In the second part of this paper, details of the data acquisition, issues related to the arterial input function, and procedures for DCE-MRI image analysis are illustrated. Copyright © 2014 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Functional Magnetic Resonance Imaging (fMRI), Pre-intraoperative Tractography in Neurosurgery: The Experience of Sant' Andrea Rome University Hospital.

PubMed

D'Andrea, Giancarlo; Trillo', Giuseppe; Picotti, Veronica; Raco, Antonino

2017-01-01

The goal of neurosurgery for cerebral intraparenchymal neoplasms of the eloquent areas is maximal resection with the preservation of normal functions, and minimizing operative risk and postoperative morbidity. Currently, modern technological advances in neuroradiological tools, neuronavigation, and intraoperative magnetic resonance imaging (MRI) have produced great improvements in postoperative morbidity after the surgery of cerebral eloquent areas. The integration of preoperative functional MRI (fMRI), intraoperative MRI (volumetric and diffusion tensor imaging [DTI]), and neuronavigation, defined as "functional neuronavigation" has improved the intraoperative detection of the eloquent areas. We reviewed 142 patients operated between 2004 and 2010 for intraparenchymal neoplasms involving or close to one or more major white matter tracts (corticospinal tract [CST], arcuate fasciculus [AF], optic radiation). All the patients underwent neurosurgery in a BrainSUITE equipped with a 1.5 T MR scanner and were preoperatively studied with fMRI and DTI for tractography for surgical planning. The patients underwent MRI and DTI during surgery after dural opening, after the gross total resection close to the white matter tracts, and at the end of the procedure. We evaluated the impact of fMRI on surgical planning and on the selection of the entry point on the cortical surface. We also evaluated the impact of preoperative and intraoperative DTI, in order to modify the surgical approach, to define the borders of resection, and to correlate this modality with subcortical neurophysiological monitoring. We evaluated the impact of the preoperative fMRI by intraoperative neurophysiological monitoring, performing "neuronavigational" brain mapping, following its data to localize the previously elicited areas after brain shift correction by intraoperative MRI. The mean age of the 142 patients (89 M/53 F) was 59.1 years and the lesion involved the CST in 66 patients (57 %), the language pathways in 24 (21 %), and the optic radiations in 25 (22 %). The integration of tractographic data into the volumetric dataset for neuronavigation was technically possible in all cases. In all patients intraoperative DTI demonstrated a shift of the bundle position caused by the surgical procedure; its dislocation was both outward and inward in the range of +6 mm and -2 mm. We found a high concordance between fMRI/DTI and intraoperative brain mapping; their combination improves the sensitivity of each technique, reducing pitfalls and so defining "functional neuronavigation", increasing the definition of eloquent areas and also reducing the time of surgery.

Department of Veterans Affairs, Gulf War Veterans’ Illnesses Task Force to the Secretary of Veterans Affairs

DTIC Science & Technology

2010-09-29

estimate for FY10 includes 40% of MRI imaging equipment upgrade at San Francisco for Gulf War research and use of unobligated FY2009 UTSW Contract funds...atrophy. (2) Explore the sensitivity of these tests to the localization of focal brain damage as confirmed on magnetic resonance imaging ( MRI ) in...2004 Gulf War RFA Effects of Gulf War Illness on Brain Structure, Function and Metabolism: MRI /MRS at 4 Tesla Gulf War Veterans Determine if

Department of Veterans Affairs Gulf War Veterans’ Illnesses Task Force to the Secretary of Veterans Affairs

DTIC Science & Technology

2010-09-29

estimate for FY10 includes 40% of MRI imaging equipment upgrade at San Francisco for Gulf War research and use of unobligated FY2009 UTSW Contract...atrophy. (2) Explore the sensitivity of these tests to the localization of focal brain damage as confirmed on magnetic resonance imaging ( MRI ) in...16 2004 Gulf War RFA Effects of Gulf War Illness on Brain Structure, Function and Metabolism: MRI /MRS at 4 Tesla Gulf War Veterans Determine

Relationship between brain function (aEEG) and brain structure (MRI) and their predictive value for neurodevelopmental outcome of preterm infants.

PubMed

Hüning, Britta; Storbeck, Tobias; Bruns, Nora; Dransfeld, Frauke; Hobrecht, Julia; Karpienski, Julia; Sirin, Selma; Schweiger, Bernd; Weiss, Christel; Felderhoff-Müser, Ursula; Müller, Hanna

2018-05-22

To improve the prediction of neurodevelopmental outcome in very preterm infants, this study used the combination of amplitude-integrated electroencephalography (aEEG) within the first 72 h of life and cranial magnetic resonance imaging (MRI) at term equivalent age. A single-center cohort of 38 infants born before 32 weeks of gestation was subjected to both investigations. Structural measurements were performed on MRI. Multiple regression analysis was used to identify independent factors including functional and structural brain measurements associated with outcome at a corrected age of 24 months. aEEG parameters significantly correlated with MRI measurements. Reduced deep gray matter volume was associated with low Burdjalov Score on day 3 (p < 0.0001) and day 1-3 (p = 0.0012). The biparietal width and the transcerebellar diameter were related to Burdjalov Score on day 1 (p = 0.0111; p = 0.0002). The final multiple regression analysis revealed independent predictors of neurodevelopmental outcome: intraventricular hemorrhage (p = 0.0060) and interhemispheric distance (p = 0.0052) for mental developmental index; Burdjalov Score day 1 (p = 0.0201) and interhemispheric distance (p = 0.0142) for psychomotor developmental index. Functional aEEG parameters were associated with altered brain maturation on MRI. The combination of aEEG and MRI contributes to the prediction of outcome at 24 months. What is Known: • Prematurity remains a risk factor for impaired neurodevelopment. • aEEG is used to measure brain activity in preterm infants and cranial MRI is performed to identify structural gray and white matter abnormalities with impact on neurodevelopmental outcome. What is New: • aEEG parameters observed within the first 72 h of life were associated with altered deep gray matter volumes, biparietal width, and transcerebellar diameter at term equivalent age. • The combination of aEEG and MRI contributes to the prediction of neurodevelopmental outcome at 2 years of corrected age in very preterm infants.

Structural Image Analysis of the Brain in Neuropsychology Using Magnetic Resonance Imaging (MRI) Techniques.

PubMed

Bigler, Erin D

2015-09-01

Magnetic resonance imaging (MRI) of the brain provides exceptional image quality for visualization and neuroanatomical classification of brain structure. A variety of image analysis techniques provide both qualitative as well as quantitative methods to relate brain structure with neuropsychological outcome and are reviewed herein. Of particular importance are more automated methods that permit analysis of a broad spectrum of anatomical measures including volume, thickness and shape. The challenge for neuropsychology is which metric to use, for which disorder and the timing of when image analysis methods are applied to assess brain structure and pathology. A basic overview is provided as to the anatomical and pathoanatomical relations of different MRI sequences in assessing normal and abnormal findings. Some interpretive guidelines are offered including factors related to similarity and symmetry of typical brain development along with size-normalcy features of brain anatomy related to function. The review concludes with a detailed example of various quantitative techniques applied to analyzing brain structure for neuropsychological outcome studies in traumatic brain injury.

A Novel Approach of Groupwise fMRI-Guided Tractography Allowing to Characterize the Clinical Evolution of Alzheimer's Disease

PubMed Central

Preti, Maria Giulia; Makris, Nikos; Papadimitriou, George; Laganà, Maria Marcella; Griffanti, Ludovica; Clerici, Mario; Nemni, Raffaello; Westin, Carl-Fredrik; Baselli, Giuseppe; Baglio, Francesca

2014-01-01

Guiding diffusion tract-based anatomy by functional magnetic resonance imaging (fMRI), we aim to investigate the relationship between structural connectivity and functional activity in the human brain. To this purpose, we introduced a novel groupwise fMRI-guided tractographic approach, that was applied on a population ranging between prodromic and moderate stages of Alzheimer's disease (AD). The study comprised of 15 subjects affected by amnestic mild cognitive impairment (aMCI), 14 diagnosed with AD and 14 elderly healthy adults who were used as controls. By creating representative (ensemble) functionally guided tracts within each group of participants, our methodology highlighted the white matter fiber connections involved in verbal fluency functions for a specific population, and hypothesized on brain compensation mechanisms that potentially counteract or reduce cognitive impairment symptoms in prodromic AD. Our hope is that this fMRI-guided tractographic approach could have potential impact in various clinical studies, while investigating white/gray matter connectivity, in both health and disease. PMID:24637718

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

NASA Astrophysics Data System (ADS)

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

2016-03-01

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

An Investigation of the Relationship Between fMRI and ERP Source Localized Measurements of Brain Activity during Face Processing

PubMed Central

Richards, Todd; Webb, Sara Jane; Murias, Michael; Merkle, Kristen; Kleinhans, Natalia M.; Johnson, L. Clark; Poliakov, Andrew; Aylward, Elizabeth; Dawson, Geraldine

2013-01-01

Brain activity patterns during face processing have been extensively explored with functional magnetic resonance imaging (fMRI) and event-related potentials (ERPs). ERP source localization adds a spatial dimension to the ERP time series recordings, which allows for a more direct comparison and integration with fMRI findings. The goals for this study were (1) to compare the spatial descriptions of neuronal activity during face processing obtained with fMRI and ERP source localization using low-resolution electro-magnetic tomography (LORETA), and (2) to use the combined information from source localization and fMRI to explore how the temporal sequence of brain activity during face processing is summarized in fMRI activation maps. fMRI and high-density ERP data were acquired in separate sessions for 17 healthy adult males for a face and object processing task. LORETA statistical maps for the comparison of viewing faces and viewing houses were coregistered and compared to fMRI statistical maps for the same conditions. The spatial locations of face processing-sensitive activity measured by fMRI and LORETA were found to overlap in a number of areas including the bilateral fusiform gyri, the right superior, middle and inferior temporal gyri, and the bilateral precuneus. Both the fMRI and LORETA solutions additionally demon-strated activity in regions that did not overlap. fMRI and LORETA statistical maps of face processing-sensitive brain activity were found to converge spatially primarily at LORETA solution latencies that were within 18 ms of the N170 latency. The combination of data from these techniques suggested that electrical brain activity at the latency of the N170 is highly represented in fMRI statistical maps. PMID:19322649

Intensity-based masking: A tool to improve functional connectivity results of resting-state fMRI.

PubMed

Peer, Michael; Abboud, Sami; Hertz, Uri; Amedi, Amir; Arzy, Shahar

2016-07-01

Seed-based functional connectivity (FC) of resting-state functional MRI data is a widely used methodology, enabling the identification of functional brain networks in health and disease. Based on signal correlations across the brain, FC measures are highly sensitive to noise. A somewhat neglected source of noise is the fMRI signal attenuation found in cortical regions in close vicinity to sinuses and air cavities, mainly in the orbitofrontal, anterior frontal and inferior temporal cortices. BOLD signal recorded at these regions suffers from dropout due to susceptibility artifacts, resulting in an attenuated signal with reduced signal-to-noise ratio in as many as 10% of cortical voxels. Nevertheless, signal attenuation is largely overlooked during FC analysis. Here we first demonstrate that signal attenuation can significantly influence FC measures by introducing false functional correlations and diminishing existing correlations between brain regions. We then propose a method for the detection and removal of the attenuated signal ("intensity-based masking") by fitting a Gaussian-based model to the signal intensity distribution and calculating an intensity threshold tailored per subject. Finally, we apply our method on real-world data, showing that it diminishes false correlations caused by signal dropout, and significantly improves the ability to detect functional networks in single subjects. Furthermore, we show that our method increases inter-subject similarity in FC, enabling reliable distinction of different functional networks. We propose to include the intensity-based masking method as a common practice in the pre-processing of seed-based functional connectivity analysis, and provide software tools for the computation of intensity-based masks on fMRI data. Hum Brain Mapp 37:2407-2418, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

[Functional magnetic resonance imaging of brain of college students with internet addiction].

PubMed

DU, Wanping; Liu, Jun; Gao, Xunping; Li, Lingjiang; Li, Weihui; Li, Xin; Zhang, Yan; Zhou, Shunke

2011-08-01

To explore the functional locations of brain regions related to internet addiction (IA)with task-functional magnetic resonance imaging (fMRI). Nineteen college students who had internet game addition and 19 controls accepted the stimuli of videos via computer. The 3.0 Tesla MRI was used to record the Results of echo plannar imaging. The block design method was used. Intragroup and intergroup analysis Results in the 2 groups were obtained. The differences between the 2 groups were analyzed. The internet game videos markedly activated the brain regions of the college students who had or had no internet game addiction. Compared with the control group, the IA group showed increased activation in the right superior parietal lobule, right insular lobe, right precuneus, right cingulated gyrus, and right superior temporal gyrus. Internet game tasks can activate the vision, space, attention and execution center which are composed of temporal occipital gyrus and frontal parietal gyrus. Abnormal brain function and lateral activation of the right brain may exist in IA.

A human brain atlas derived via n-cut parcellation of resting-state and task-based fMRI data

PubMed Central

James, G. Andrew; Hazaroglu, Onder; Bush, Keith A.

2015-01-01

The growth of functional MRI has led to development of human brain atlases derived by parcellating resting-state connectivity patterns into functionally independent regions of interest (ROIs). All functional atlases to date have been derived from resting-state fMRI data. But given that functional connectivity between regions varies with task, we hypothesized that an atlas incorporating both resting-state and task-based fMRI data would produce an atlas with finer characterization of task-relevant regions than an atlas derived from resting-state alone. To test this hypothesis, we derived parcellation atlases from twenty-nine healthy adult participants enrolled in the Cognitive Connectome project, an initiative to improve functional MRI’s translation into clinical decision-making by mapping normative variance in brain-behavior relationships. Participants underwent resting-state and task-based fMRI spanning nine cognitive domains: motor, visuospatial, attention, language, memory, affective processing, decision-making, working memory, and executive function. Spatially constrained n-cut parcellation derived brain atlases using (1) all participants’ functional data (Task) or (2) a single resting-state scan (Rest). An atlas was also derived from random parcellation for comparison purposes (Random). Two methods were compared: (1) a parcellation applied to the group’s mean edge weights (mean), and (2) a two-stage approach with parcellation of individual edge weights followed by parcellation of mean binarized edges (two-stage). The resulting Task and Rest atlases had significantly greater similarity with each other (mean Jaccard indices JI= 0.72–0.85) than with the Random atlases (JI=0.59–0.63; all p<0.001 after Bonferroni correction). Task and Rest atlas similarity was greatest for the two-stage method (JI=0.85), which has been shown as more robust than the mean method; these atlases also better reproduced voxelwise seed maps of the left dorsolateral prefrontal cortex during rest and performing the n-back working memory task (r=0.75–0.80) than the Random atlases (r=0.64–0.72), further validating their utility. We expected regions governing higher-order cognition (such as frontal and anterior temporal lobes) to show greatest difference between Task and Rest atlases; contrary to expectations, these areas had greatest similarity between atlases. Our findings indicate that atlases derived from parcellation of task-based and resting-state fMRI data are highly comparable, and existing resting-state atlases are suitable for task-based analyses. We introduce an anatomically labeled fMRI-derived whole-brain human atlas for future Cognitive Connectome analyses. PMID:26523655

Functional Magnetic Resonance Imaging (fMRI) Neurofeedback: Implementations and Applications

PubMed Central

DEWIPUTRI, Wan Ilma; AUER, Tibor

2013-01-01

Neurofeedback (NFB) allows subjects to learn how to volitionally influence the neuronal activation in the brain by employing real-time neural activity as feedback. NFB has already been performed with electroencephalography (EEG) since the 1970s. Functional MRI (fMRI), offering a higher spatial resolution, has further increased the spatial specificity. In this paper, we briefly outline the general principles behind NFB, the implementation of fMRI-NFB studies, the feasibility of fMRI-NFB, and the application of NFB as a supplementary therapy tool. PMID:24643368

Individual Functional ROI Optimization via Maximization of Group-wise Consistency of Structural and Functional Profiles

PubMed Central

Li, Kaiming; Guo, Lei; Zhu, Dajiang; Hu, Xintao; Han, Junwei; Liu, Tianming

2013-01-01

Studying connectivities among functional brain regions and the functional dynamics on brain networks has drawn increasing interest. A fundamental issue that affects functional connectivity and dynamics studies is how to determine the best possible functional brain regions or ROIs (regions of interest) for a group of individuals, since the connectivity measurements are heavily dependent on ROI locations. Essentially, identification of accurate, reliable and consistent corresponding ROIs is challenging due to the unclear boundaries between brain regions, variability across individuals, and nonlinearity of the ROIs. In response to these challenges, this paper presents a novel methodology to computationally optimize ROIs locations derived from task-based fMRI data for individuals so that the optimized ROIs are more consistent, reproducible and predictable across brains. Our computational strategy is to formulate the individual ROI location optimization as a group variance minimization problem, in which group-wise consistencies in functional/structural connectivity patterns and anatomic profiles are defined as optimization constraints. Our experimental results from multimodal fMRI and DTI data show that the optimized ROIs have significantly improved consistency in structural and functional profiles across individuals. These improved functional ROIs with better consistency could contribute to further study of functional interaction and dynamics in the human brain. PMID:22281931

Surface-Based fMRI-Driven Diffusion Tractography in the Presence of Significant Brain Pathology: A Study Linking Structure and Function in Cerebral Palsy

PubMed Central

Cunnington, Ross; Boyd, Roslyn N.; Rose, Stephen E.

2016-01-01

Diffusion MRI (dMRI) tractography analyses are difficult to perform in the presence of brain pathology. Automated methods that rely on cortical parcellation for structural connectivity studies often fail, while manually defining regions is extremely time consuming and can introduce human error. Both methods also make assumptions about structure-function relationships that may not hold after cortical reorganisation. Seeding tractography with functional-MRI (fMRI) activation is an emerging method that reduces these confounds, but inherent smoothing of fMRI signal may result in the inclusion of irrelevant pathways. This paper describes a novel fMRI-seeded dMRI-analysis pipeline based on surface-meshes that reduces these issues and utilises machine-learning to generate task specific white matter pathways, minimising the requirement for manually-drawn ROIs. We directly compared this new strategy to a standard voxelwise fMRI-dMRI approach, by investigating correlations between clinical scores and dMRI metrics of thalamocortical and corticomotor tracts in 31 children with unilateral cerebral palsy. The surface-based approach successfully processed more participants (87%) than the voxel-based approach (65%), and provided significantly more-coherent tractography. Significant correlations between dMRI metrics and five clinical scores of function were found for the more superior regions of these tracts. These significant correlations were stronger and more frequently found with the surface-based method (15/20 investigated were significant; R2 = 0.43–0.73) than the voxelwise analysis (2 sig. correlations; 0.38 & 0.49). More restricted fMRI signal, better-constrained tractography, and the novel track-classification method all appeared to contribute toward these differences. PMID:27487011

Brain and Behavioral Assessment of Executive Functions for Self-Regulating Levels of Language in Reading Brain.

PubMed

Berninger, Virginia W; Richards, Todd L; Abbott, Robert D

2017-11-01

This brief research report examines brain-behavioral relationships specific to levels of language in the complex reading brain. The first specific aim was to examine prior findings for significant fMRI connectivity from four seeds (left precuneus, left occipital temporal, left supramarginal, left inferior frontal) for each of four levels of language-subword, word (word-specific spelling or affixed words), syntax (with and without homonym foils or affix foils), and multi-sentence text to identify significant fMRI connectivity (a) unique to the lower level of language when compared to the immediately higher adjacent level of language across subword-word, word-syntax, and syntax-text comparisons; and (b) involving a brain region associated with executive functions. The second specific aim was to correlate the magnitude of that connectivity with standard scores on tests of Focused Attention (D-K EFS Color Word Form Inhibition) and Switching Attention (Wolf & Denckla Rapid Automatic Switching). Seven correlations were significant. Focused Attention was significantly correlated with the word level (word-specific spellings of real words) fMRI task in left cingulum from left inferior frontal seed. Switching Attention was significantly correlated with the (a) subword level (grapheme-phoneme correspondence) fMRI task in left and right Cerebellum V from left supramarginal seed; (b) the word level (word-specific spelling) fMRI task in right Cerebellum V from left precuneus seed; (c) the syntax level (with and without homonym foils) fMRI task in right Cerebellum V from left precuneus seed and from left supramarginal seed; and (d) syntax level (with and without affix foils) fMRI task in right Cerebellum V from left precuneus seed. Results are discussed in reference to neuropsychological assessment of supervisory attention (focused and switching) for specific levels of language related to reading acquisition in students with and without language-related specific learning disabilities and self-regulation of the complex reading brain.

Brain and Behavioral Assessment of Executive Functions for Self-Regulating Levels of Language in Reading Brain

PubMed Central

Berninger, Virginia W.; Richards, Todd L.; Abbott, Robert D.

2017-01-01

This brief research report examines brain-behavioral relationships specific to levels of language in the complex reading brain. The first specific aim was to examine prior findings for significant fMRI connectivity from four seeds (left precuneus, left occipital temporal, left supramarginal, left inferior frontal) for each of four levels of language—subword, word (word-specific spelling or affixed words), syntax (with and without homonym foils or affix foils), and multi-sentence text to identify significant fMRI connectivity (a) unique to the lower level of language when compared to the immediately higher adjacent level of language across subword-word, word-syntax, and syntax-text comparisons; and (b) involving a brain region associated with executive functions. The second specific aim was to correlate the magnitude of that connectivity with standard scores on tests of Focused Attention (D-K EFS Color Word Form Inhibition) and Switching Attention (Wolf & Denckla Rapid Automatic Switching). Seven correlations were significant. Focused Attention was significantly correlated with the word level (word-specific spellings of real words) fMRI task in left cingulum from left inferior frontal seed. Switching Attention was significantly correlated with the (a) subword level (grapheme-phoneme correspondence) fMRI task in left and right Cerebellum V from left supramarginal seed; (b) the word level (word-specific spelling) fMRI task in right Cerebellum V from left precuneus seed; (c) the syntax level (with and without homonym foils) fMRI task in right Cerebellum V from left precuneus seed and from left supramarginal seed; and (d) syntax level (with and without affix foils) fMRI task in right Cerebellum V from left precuneus seed. Results are discussed in reference to neuropsychological assessment of supervisory attention (focused and switching) for specific levels of language related to reading acquisition in students with and without language-related specific learning disabilities and self-regulation of the complex reading brain. PMID:29104930

Correlation between standardized assessment of concussion scores and small-world brain network in mild traumatic brain injury.

PubMed

Yan, Yan; Song, Jian; Xu, Guozheng; Yao, Shun; Cao, Chenglong; Li, Chang; Peng, Guibao; Du, Hao

2017-10-01

This study investigated the characteristics of the small-world brain network architecture of patients with mild traumatic brain injury (MTBI), and a correlation between brain functional connectivity network properties in the resting-state fMRI and Standardized Assessment of Concussion (SAC) parameters. The neurological conditions of 22 MTBI patients and 17 normal control individuals were evaluated according to the SAC. Resting-state fMRI was performed in all subjects 3 and 7days after injury respectively. After preprocessing the fMRI data, cortex functional regions were marked using AAL90 and Dosenbach160 templates. The small-world network parameters and areas under the integral curves were computed in the range of sparsity from 0.01 to 0.5. Independent-sample t-tests were used to compare these parameters between the MTBI and control group. Significantly different parameters were investigated for correlations with SAC scores; those that correlated were chosen for further curve fitting. The clustering coefficient, the communication efficiency across in local networks, and the strength of connectivity were all higher in MTBI patients relative to control individuals. Parameters in 160 brain regions of the MTBI group significantly correlated with total SAC score and score for attention; the network parameters may be a quadratic function of attention scores of SAC and a cubic function of SAC scores. MTBI patients were characterized by elevated communication efficiency across global brain regions, and in local networks, and strength of mean connectivity. These features may be associated with brain function compensation. The network parameters significantly correlated with SAC total and attention scores. Copyright © 2017 Elsevier Ltd. All rights reserved.

Neuroticism modulates brain visuo-vestibular and anxiety systems during a virtual rollercoaster task.

PubMed

Riccelli, Roberta; Indovina, Iole; Staab, Jeffrey P; Nigro, Salvatore; Augimeri, Antonio; Lacquaniti, Francesco; Passamonti, Luca

2017-02-01

Different lines of research suggest that anxiety-related personality traits may influence the visual and vestibular control of balance, although the brain mechanisms underlying this effect remain unclear. To our knowledge, this is the first functional magnetic resonance imaging (fMRI) study that investigates how individual differences in neuroticism and introversion, two key personality traits linked to anxiety, modulate brain regional responses and functional connectivity patterns during a fMRI task simulating self-motion. Twenty-four healthy individuals with variable levels of neuroticism and introversion underwent fMRI while performing a virtual reality rollercoaster task that included two main types of trials: (1) trials simulating downward or upward self-motion (vertical motion), and (2) trials simulating self-motion in horizontal planes (horizontal motion). Regional brain activity and functional connectivity patterns when comparing vertical versus horizontal motion trials were correlated with personality traits of the Five Factor Model (i.e., neuroticism, extraversion-introversion, openness, agreeableness, and conscientiousness). When comparing vertical to horizontal motion trials, we found a positive correlation between neuroticism scores and regional activity in the left parieto-insular vestibular cortex (PIVC). For the same contrast, increased functional connectivity between the left PIVC and right amygdala was also detected as a function of higher neuroticism scores. Together, these findings provide new evidence that individual differences in personality traits linked to anxiety are significantly associated with changes in the activity and functional connectivity patterns within visuo-vestibular and anxiety-related systems during simulated vertical self-motion. Hum Brain Mapp 38:715-726, 2017. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Functional Magnetic Resonance Imaging and Functional Near-Infrared Spectroscopy: Insights from Combined Recording Studies

PubMed Central

Scarapicchia, Vanessa; Brown, Cassandra; Mayo, Chantel; Gawryluk, Jodie R.

2017-01-01

Although blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) is a widely available, non-invasive technique that offers excellent spatial resolution, it remains limited by practical constraints imposed by the scanner environment. More recently, functional near infrared spectroscopy (fNIRS) has emerged as an alternative hemodynamic-based approach that possesses a number of strengths where fMRI is limited, most notably in portability and higher tolerance for motion. To date, fNIRS has shown promise in its ability to shed light on the functioning of the human brain in populations and contexts previously inaccessible to fMRI. Notable contributions include infant neuroimaging studies and studies examining full-body behaviors, such as exercise. However, much like fMRI, fNIRS has technical constraints that have limited its application to clinical settings, including a lower spatial resolution and limited depth of recording. Thus, by combining fMRI and fNIRS in such a way that the two methods complement each other, a multimodal imaging approach may allow for more complex research paradigms than is feasible with either technique alone. In light of these issues, the purpose of the current review is to: (1) provide an overview of fMRI and fNIRS and their associated strengths and limitations; (2) review existing combined fMRI-fNIRS recording studies; and (3) discuss how their combined use in future research practices may aid in advancing modern investigations of human brain function. PMID:28867998

Disrupted Brain Functional Network Architecture in Chronic Tinnitus Patients

PubMed Central

Chen, Yu-Chen; Feng, Yuan; Xu, Jin-Jing; Mao, Cun-Nan; Xia, Wenqing; Ren, Jun; Yin, Xindao

2016-01-01

Purpose: Resting-state functional magnetic resonance imaging (fMRI) studies have demonstrated the disruptions of multiple brain networks in tinnitus patients. Nonetheless, several studies found no differences in network processing between tinnitus patients and healthy controls (HCs). Its neural bases are poorly understood. To identify aberrant brain network architecture involved in chronic tinnitus, we compared the resting-state fMRI (rs-fMRI) patterns of tinnitus patients and HCs. Materials and Methods: Chronic tinnitus patients (n = 24) with normal hearing thresholds and age-, sex-, education- and hearing threshold-matched HCs (n = 22) participated in the current study and underwent the rs-fMRI scanning. We used degree centrality (DC) to investigate functional connectivity (FC) strength of the whole-brain network and Granger causality to analyze effective connectivity in order to explore directional aspects involved in tinnitus. Results: Compared to HCs, we found significantly increased network centrality in bilateral superior frontal gyrus (SFG). Unidirectionally, the left SFG revealed increased effective connectivity to the left middle orbitofrontal cortex (OFC), left posterior lobe of cerebellum (PLC), left postcentral gyrus, and right middle occipital gyrus (MOG) while the right SFG exhibited enhanced effective connectivity to the right supplementary motor area (SMA). In addition, the effective connectivity from the bilateral SFG to the OFC and SMA showed positive correlations with tinnitus distress. Conclusions: Rs-fMRI provides a new and novel method for identifying aberrant brain network architecture. Chronic tinnitus patients have disrupted FC strength and causal connectivity mostly in non-auditory regions, especially the prefrontal cortex (PFC). The current findings will provide a new perspective for understanding the neuropathophysiological mechanisms in chronic tinnitus. PMID:27458377

Correlation between brain circuit segregation and obesity.

PubMed

Chao, Seh-Huang; Liao, Yin-To; Chen, Vincent Chin-Hung; Li, Cheng-Jui; McIntyre, Roger S; Lee, Yena; Weng, Jun-Cheng

2018-01-30

Obesity is a major public health problem. Herein, we aim to identify the correlation between brain circuit segregation and obesity using multimodal functional magnetic resonance imaging (fMRI) techniques and analysis. Twenty obese patients (BMI=37.66±5.07) and 30 healthy controls (BMI=22.64±3.45) were compared using neuroimaging and assessed for symptoms of anxiety and depression using the Hospital Anxiety and Depression Scale (HADS). All participants underwent resting-state fMRI (rs-fMRI) and T1-weighted imaging using a 1.5T MRI. Multimodal MRI techniques and analyses were used to assess obese patients, including the functional connectivity (FC), amplitude of low-frequency fluctuations (ALFF), regional homogeneity (ReHo), graph theoretical analysis (GTA), and voxel-based morphometry (VBM). Correlations between brain circuit segregation and obesity were also calculated. In the VBM, obese patients showed altered gray matter volumes in the amygdala, thalamus and putamen. In the FC, the obesity group showed increased functional connectivity in the bilateral anterior cingulate cortex and decreased functional connectivity in the frontal gyrus of default mode network. The obesity group also exhibited altered ALFF and ReHo in the prefrontal cortex and precuneus. In the GTA, the obese patients showed a significant decrease in local segregation and a significant increase in global integration, suggesting a shift toward randomization in their functional networks. Our results may provide additional evidence for potential structural and functional imaging markers for clinical diagnosis and future research, and they may improve our understanding of the underlying pathophysiology of obesity. Copyright © 2017 Elsevier B.V. All rights reserved.

Alzheimer disease alters the relationship of cardiorespiratory fitness with brain activity during the stroop task.

PubMed

Vidoni, Eric D; Gayed, Matthew R; Honea, Robyn A; Savage, Cary R; Hobbs, Derek; Burns, Jeffrey M

2013-07-01

Despite mounting evidence that physical activity has positive benefits for brain and cognitive health, there has been little characterization of the relationship between cardiorespiratory (CR) fitness and cognition-associated brain activity as measured by functional magnetic resonance imaging (fMRI). The lack of evidence is particularly glaring for diseases such as Alzheimer disease (AD) that degrade cognitive and functional performance. The aim of this study was to describe the relationship between regional brain activity during cognitive tasks and CR fitness level in people with and without AD. A case-control, single-observation study design was used. Thirty-four individuals (18 without dementia and 16 in the earliest stages of AD) completed maximal exercise testing and performed a Stroop task during fMRI. Cardiorespiratory fitness was inversely associated with anterior cingulate activity in the participants without dementia (r=-.48, P=.05) and unassociated with activation in those with AD (P>.7). Weak associations of CR fitness and middle frontal cortex were noted. The wide age range and the use of a single task in fMRI rather than multiple tasks challenging different cognitive capacities were limitations of the study. The results offer further support of the relationship between CR fitness and regional brain activity. However, this relationship may be attenuated by disease. Future work in this area may provide clinicians and researchers with interpretable and dependable regional fMRI biomarker signatures responsive to exercise intervention. It also may shed light on mechanisms by which exercise can support cognitive function.

Japanese and English Sentence Reading Comprehension and Writing Systems: An fMRI Study of First and Second Language Effects on Brain Activation

ERIC Educational Resources Information Center

Buchweitz, Augusto; Mason, Robert A.; Hasegawa, Mihoko; Just, Marcel A.

2009-01-01

Functional magnetic resonance imaging (fMRI) was used to compare brain activation from native Japanese (L1) readers reading hiragana (syllabic) and kanji (logographic) sentences, and English as a second language (L2). Kanji showed more activation than hiragana in right-hemisphere occipito-temporal lobe areas associated with visuospatial…

Brain Regions Involved in the Retrieval of Spatial and Episodic Details Associated with a Familiar Environment: An fMRI Study

ERIC Educational Resources Information Center

Hirshhorn, Marnie; Grady, Cheryl; Rosenbaum, R. Shayna; Winocur, Gordon; Moscovitch, Morris

2012-01-01

Functional magnetic resonance imaging (fMRI) was used to compare brain activity during the retrieval of coarse- and fine-grained spatial details and episodic details associated with a familiar environment. Long-time Toronto residents compared pairs of landmarks based on their absolute geographic locations (requiring either coarse or fine…

Brief Report: Brain Activation to Social Words in a Sedated Child with Autism

ERIC Educational Resources Information Center

Carmody, Dennis P.; Moreno, Rosanne; Mars, Audrey E.; Seshadri, Kapila; Lambert, George H.; Lewis, Michael

2007-01-01

A functional magnetic resonance imaging (fMRI) study was performed on a 4-year-old girl with autism. While sedated, she listened to three utterances (numbers, hello, her own first name) played through headphones. Based on analyses of the fMRI data, the amount of total brain activation varied with the content of the utterance. The greatest volume…

Preoperative three-dimensional model creation of magnetic resonance brain images as a tool to assist neurosurgical planning.

PubMed

Spottiswoode, B S; van den Heever, D J; Chang, Y; Engelhardt, S; Du Plessis, S; Nicolls, F; Hartzenberg, H B; Gretschel, A

2013-01-01

Neurosurgeons regularly plan their surgery using magnetic resonance imaging (MRI) images, which may show a clear distinction between the area to be resected and the surrounding healthy brain tissue depending on the nature of the pathology. However, this distinction is often unclear with the naked eye during the surgical intervention, and it may be difficult to infer depth and an accurate volumetric interpretation from a series of MRI image slices. In this work, MRI data are used to create affordable patient-specific 3-dimensional (3D) scale models of the brain which clearly indicate the location and extent of a tumour relative to brain surface features and important adjacent structures. This is achieved using custom software and rapid prototyping. In addition, functionally eloquent areas identified using functional MRI are integrated into the 3D models. Preliminary in vivo results are presented for 2 patients. The accuracy of the technique was estimated both theoretically and by printing a geometrical phantom, with mean dimensional errors of less than 0.5 mm observed. This may provide a practical and cost-effective tool which can be used for training, and during neurosurgical planning and intervention. Copyright © 2013 S. Karger AG, Basel.

Delineation of early brain development from fetuses to infants with diffusion MRI and beyond.

PubMed

Ouyang, Minhui; Dubois, Jessica; Yu, Qinlin; Mukherjee, Pratik; Huang, Hao

2018-04-12

Dynamic macrostructural and microstructural changes take place from the mid-fetal stage to 2 years after birth. Delineating structural changes of the brain during early development provides new insights into the complicated processes of both typical development and the pathological mechanisms underlying various psychiatric and neurological disorders including autism, attention deficit hyperactivity disorder and schizophrenia. Decades of histological studies have identified strong spatial and functional maturation gradients in human brain gray and white matter. The recent improvements in magnetic resonance imaging (MRI) techniques, especially diffusion MRI (dMRI), relaxometry imaging, and magnetization transfer imaging (MTI) have provided unprecedented opportunities to non-invasively quantify and map the early developmental changes at whole brain and regional levels. Here, we review the recent advances in understanding early brain structural development during the second half of gestation and the first two postnatal years using modern MR techniques. Specifically, we review studies that delineate the emergence and microstructural maturation of white matter tracts, as well as dynamic mapping of inhomogeneous cortical microstructural organization unique to fetuses and infants. These imaging studies converge into maturational curves of MRI measurements that are distinctive across different white matter tracts and cortical regions. Furthermore, contemporary models offering biophysical interpretations of the dMRI-derived measurements are illustrated to infer the underlying microstructural changes. Collectively, this review summarizes findings that contribute to charting spatiotemporally heterogeneous gray and white matter structural development, offering MRI-based biomarkers of typical brain development and setting the stage for understanding aberrant brain development in neurodevelopmental disorders. Copyright © 2018 Elsevier Inc. All rights reserved.

A comparative study of brain perfusion single-photon emission computed tomography and magnetic resonance imaging in patients with post-traumatic anosmia.

PubMed

Atighechi, Saeid; Salari, Hadi; Baradarantar, Mohammad Hossein; Jafari, Rozita; Karimi, Ghasem; Mirjali, Mehdi

2009-01-01

Loss of smell is a problem that can occur in up to 30% of patients with head trauma. The olfactory function investigation methods so far in use have mostly relied on subjective responses given by patients. Recently, some studies have used magnetic resonance imaging (MRI) and single-photon emission computed tomography (SPECT) to evaluate patients with post-traumatic anosmia. The present study seeks to detect post-traumatic anosmia and the areas in the brain that are related to olfactory impairment by using SPECT and MRI as imaging techniques. The study was conducted on 21 patients suffering from head injury and consequently anosmia as defined by an olfactory identification test. Two control groups (traumatic normosmic and nontraumatic healthy individuals) were selected. Brain MRI, qualitative and semiquantitative SPECT with 99mtc-ethyl-cysteinate-dimer were taken from all the patients. Then the brain SPECT and MRI were compared with each other. Semi-quantitative assessment of the brain perfusion SPECT revealed frontal, left parietal, and left temporal hypoperfusion as compared with the two control groups. Eighty-five percent of the anosmic patients had abnormal brain MRI. Regarding the MRI, the main abnormality proved to be in the anterior inferior region of the frontal lobes and olfactory bulbs. The findings of this study suggest that damage to the frontal lobes and olfactory bulbs as shown in the brain MRI and hypoperfusion in the frontal, left parietal, and left temporal lobes in the semiquantitative SPECT corresponds to post-traumatic anosmia. Further neurophysiological and imaging studies are definitely needed to set the idea completely.

A brain MRI atlas of the common squirrel monkey, Saimiri sciureus

NASA Astrophysics Data System (ADS)

Gao, Yurui; Schilling, Kurt G.; Khare, Shweta P.; Panda, Swetasudha; Choe, Ann S.; Stepniewska, Iwona; Li, Xia; Ding, Zhoahua; Anderson, Adam; Landman, Bennett A.

2014-03-01

The common squirrel monkey, Saimiri sciureus, is a New World monkey with functional and microstructural organization of central nervous system similar to that of humans. It is one of the most commonly used South American primates in biomedical research. Unlike its Old World macaque cousins, no digital atlases have described the organization of the squirrel monkey brain. Here, we present a multi-modal magnetic resonance imaging (MRI) atlas constructed from the brain of an adult female squirrel monkey. In vivo MRI acquisitions include high resolution T2 structural imaging and low resolution diffusion tensor imaging. Ex vivo MRI acquisitions include high resolution T2 structural imaging and high resolution diffusion tensor imaging. Cortical regions were manually annotated on the co-registered volumes based on published histological sections.

Assessing the mean strength and variations of the time-to-time fluctuations of resting-state brain activity.

PubMed

Li, Zhengjun; Zang, Yu-Feng; Ding, Jianping; Wang, Ze

2017-04-01

The time-to-time fluctuations (TTFs) of resting-state brain activity as captured by resting-state fMRI (rsfMRI) have been repeatedly shown to be informative of functional brain structures and disease-related alterations. TTFs can be characterized by the mean and the range of successive difference. The former can be measured with the mean squared successive difference (MSSD), which is mathematically similar to standard deviation; the latter can be calculated by the variability of the successive difference (VSD). The purpose of this study was to evaluate both the resting state-MSSD and VSD of rsfMRI regarding their test-retest stability, sensitivity to brain state change, as well as their biological meanings. We hypothesized that MSSD and VSD are reliable in resting brain; both measures are sensitive to brain state changes such as eyes-open compared to eyes-closed condition; both are predictive of age. These hypotheses were tested with three rsfMRI datasets and proven true, suggesting both MSSD and VSD as reliable and useful tools for resting-state studies.

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

PubMed

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

2012-01-01

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

Resting-state activity in development and maintenance of normal brain function.

PubMed

Pizoli, Carolyn E; Shah, Manish N; Snyder, Abraham Z; Shimony, Joshua S; Limbrick, David D; Raichle, Marcus E; Schlaggar, Bradley L; Smyth, Matthew D

2011-07-12

One of the most intriguing recent discoveries concerning brain function is that intrinsic neuronal activity manifests as spontaneous fluctuations of the blood oxygen level-dependent (BOLD) functional MRI signal. These BOLD fluctuations exhibit temporal synchrony within widely distributed brain regions known as resting-state networks. Resting-state networks are present in the waking state, during sleep, and under general anesthesia, suggesting that spontaneous neuronal activity plays a fundamental role in brain function. Despite its ubiquitous presence, the physiological role of correlated, spontaneous neuronal activity remains poorly understood. One hypothesis is that this activity is critical for the development of synaptic connections and maintenance of synaptic homeostasis. We had a unique opportunity to test this hypothesis in a 5-y-old boy with severe epileptic encephalopathy. The child developed marked neurologic dysfunction in association with a seizure disorder, resulting in a 1-y period of behavioral regression and progressive loss of developmental milestones. His EEG showed a markedly abnormal pattern of high-amplitude, disorganized slow activity with frequent generalized and multifocal epileptiform discharges. Resting-state functional connectivity MRI showed reduced BOLD fluctuations and a pervasive lack of normal connectivity. The child underwent successful corpus callosotomy surgery for treatment of drop seizures. Postoperatively, the patient's behavior returned to baseline, and he resumed development of new skills. The waking EEG revealed a normal background, and functional connectivity MRI demonstrated restoration of functional connectivity architecture. These results provide evidence that intrinsic, coherent neuronal signaling may be essential to the development and maintenance of the brain's functional organization.

Volumetric brain magnetic resonance imaging predicts functioning in bipolar disorder: A machine learning approach.

PubMed

Sartori, Juliana M; Reckziegel, Ramiro; Passos, Ives Cavalcante; Czepielewski, Leticia S; Fijtman, Adam; Sodré, Leonardo A; Massuda, Raffael; Goi, Pedro D; Vianna-Sulzbach, Miréia; Cardoso, Taiane de Azevedo; Kapczinski, Flávio; Mwangi, Benson; Gama, Clarissa S

2018-08-01

Neuroimaging studies have been steadily explored in Bipolar Disorder (BD) in the last decades. Neuroanatomical changes tend to be more pronounced in patients with repeated episodes. Although the role of such changes in cognition and memory is well established, daily-life functioning impairments bulge among the consequences of the proposed progression. The objective of this study was to analyze MRI volumetric modifications in BD and healthy controls (HC) as possible predictors of daily-life functioning through a machine learning approach. Ninety-four participants (35 DSM-IV BD type I and 59 HC) underwent clinical and functioning assessments, and structural MRI. Functioning was assessed using the Functioning Assessment Short Test (FAST). The machine learning analysis was used to identify possible candidates of regional brain volumes that could predict functioning status, through a support vector regression algorithm. Patients with BD and HC did not differ in age, education and marital status. There were significant differences between groups in gender, BMI, FAST score, and employment status. There was significant correlation between observed and predicted FAST score for patients with BD, but not for controls. According to the model, the brain structures volumes that could predict FAST scores were: left superior frontal cortex, left rostral medial frontal cortex, right white matter total volume and right lateral ventricle volume. The machine learning approach demonstrated that brain volume changes in MRI were predictors of FAST score in patients with BD and could identify specific brain areas related to functioning impairment. Copyright © 2018 Elsevier Ltd. All rights reserved.

Family-Based Training Program Improves Brain Function, Cognition, and Behavior in Lower Socioeconomic Status Preschoolers

ERIC Educational Resources Information Center

Pakulak, Eric; Stevens, Courtney; Bell, Theodore A.; Fanning, Jessica; Klein, Scott; Isbell, Elif; Neville, Helen

2013-01-01

Over the course of several years of research, the authors have employed psychophysics, electrophysiological (ERP) and magnetic resonance imaging (MRI) techniques to study the development and neuroplasticity of the human brain. During this time, they observed that different brain systems and related functions display markedly different degrees or…

Functional MRI using robotic MRI compatible devices for monitoring rehabilitation from chronic stroke in the molecular medicine era (Review)

PubMed Central

ASTRAKAS, LOUKAS G.; NAQVI, SYED HASSAN ABBAS; KATEB, BABAK; TZIKA, A. ARIA

2012-01-01

The number of individuals suffering from stroke is increasing daily, and its consequences are a major contributor to invalidity in today’s society. Stroke rehabilitation is relatively new, having been hampered from the longstanding view that lost functions were not recoverable. Nowadays, robotic devices, which aid by stimulating brain plasticity, can assist in restoring movement compromised by stroke-induced pathological changes in the brain which can be monitored by MRI. Multiparametric magnetic resonance imaging (MRI) of stroke patients participating in a training program with a novel Magnetic Resonance Compatible Hand-Induced Robotic Device (MR_CHIROD) could yield a promising biomarker that, ultimately, will enhance our ability to advance hand motor recovery following chronic stroke. Using state-of-the art MRI in conjunction with MR_CHIROD-assisted therapy can provide novel biomarkers for stroke patient rehabilitation extracted by a meta-analysis of data. Successful completion of such studies may provide a ground breaking method for the future evaluation of stroke rehabilitation therapies. Their results will attest to the effectiveness of using MR-compatible hand devices with MRI to provide accurate monitoring during rehabilitative therapy. Furthermore, such results may identify biomarkers of brain plasticity that can be monitored during stroke patient rehabilitation. The potential benefit for chronic stroke patients is that rehabilitation may become possible for a longer period of time after stroke than previously thought, unveiling motor skill improvements possible even after six months due to retained brain plasticity. PMID:22426741

Brain atrophy can introduce age-related differences in BOLD response.

PubMed

Liu, Xueqing; Gerraty, Raphael T; Grinband, Jack; Parker, David; Razlighi, Qolamreza R

2017-04-11

Use of functional magnetic resonance imaging (fMRI) in studies of aging is often hampered by uncertainty about age-related differences in the amplitude and timing of the blood oxygenation level dependent (BOLD) response (i.e., hemodynamic impulse response function (HRF)). Such uncertainty introduces a significant challenge in the interpretation of the fMRI results. Even though this issue has been extensively investigated in the field of neuroimaging, there is currently no consensus about the existence and potential sources of age-related hemodynamic alterations. Using an event-related fMRI experiment with two robust and well-studied stimuli (visual and auditory), we detected a significant age-related difference in the amplitude of response to auditory stimulus. Accounting for brain atrophy by circumventing spatial normalization and processing the data in subjects' native space eliminated these observed differences. In addition, we simulated fMRI data using age differences in brain morphology while controlling HRF shape. Analyzing these simulated fMRI data using standard image processing resulted in differences in HRF amplitude, which were eliminated when the data were analyzed in subjects' native space. Our results indicate that age-related atrophy introduces inaccuracy in co-registration to standard space, which subsequently appears as attenuation in BOLD response amplitude. Our finding could explain some of the existing contradictory reports regarding age-related differences in the fMRI BOLD responses. Hum Brain Mapp, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Selective Audiovisual Semantic Integration Enabled by Feature-Selective Attention.

PubMed

Li, Yuanqing; Long, Jinyi; Huang, Biao; Yu, Tianyou; Wu, Wei; Li, Peijun; Fang, Fang; Sun, Pei

2016-01-13

An audiovisual object may contain multiple semantic features, such as the gender and emotional features of the speaker. Feature-selective attention and audiovisual semantic integration are two brain functions involved in the recognition of audiovisual objects. Humans often selectively attend to one or several features while ignoring the other features of an audiovisual object. Meanwhile, the human brain integrates semantic information from the visual and auditory modalities. However, how these two brain functions correlate with each other remains to be elucidated. In this functional magnetic resonance imaging (fMRI) study, we explored the neural mechanism by which feature-selective attention modulates audiovisual semantic integration. During the fMRI experiment, the subjects were presented with visual-only, auditory-only, or audiovisual dynamical facial stimuli and performed several feature-selective attention tasks. Our results revealed that a distribution of areas, including heteromodal areas and brain areas encoding attended features, may be involved in audiovisual semantic integration. Through feature-selective attention, the human brain may selectively integrate audiovisual semantic information from attended features by enhancing functional connectivity and thus regulating information flows from heteromodal areas to brain areas encoding the attended features.

Neural Signatures of Autism Spectrum Disorders: Insights into Brain Network Dynamics

PubMed Central

Hernandez, Leanna M; Rudie, Jeffrey D; Green, Shulamite A; Bookheimer, Susan; Dapretto, Mirella

2015-01-01

Neuroimaging investigations of autism spectrum disorders (ASDs) have advanced our understanding of atypical brain function and structure, and have recently converged on a model of altered network-level connectivity. Traditional task-based functional magnetic resonance imaging (MRI) and volume-based structural MRI studies have identified widespread atypicalities in brain regions involved in social behavior and other core ASD-related behavioral deficits. More recent advances in MR-neuroimaging methods allow for quantification of brain connectivity using diffusion tensor imaging, functional connectivity, and graph theoretic methods. These newer techniques have moved the field toward a systems-level understanding of ASD etiology, integrating functional and structural measures across distal brain regions. Neuroimaging findings in ASD as a whole have been mixed and at times contradictory, likely due to the vast genetic and phenotypic heterogeneity characteristic of the disorder. Future longitudinal studies of brain development will be crucial to yield insights into mechanisms of disease etiology in ASD sub-populations. Advances in neuroimaging methods and large-scale collaborations will also allow for an integrated approach linking neuroimaging, genetics, and phenotypic data. PMID:25011468

Visualizing the anatomical-functional correlation of the human brain

NASA Astrophysics Data System (ADS)

Chang, YuKuang; Rockwood, Alyn P.; Reiman, Eric M.

1995-04-01

Three-dimensional tomographic images obtained from different modalities or from the same modality at different times provide complementary information. For example, while PET shows brain function, images from MRI identify anatomical structures. In this paper, we investigate the problem of displaying available information about structures and function together. Several steps are described to achieve our goal. These include segmentation of the data, registration, resampling, and display. Segmentation is used to identify brain tissue from surrounding tissues, especially in the MRI data. Registration aligns the different modalities as closely as possible. Resampling arises from the registration since two data sets do not usually correspond and the rendering method is most easily achieved if the data correspond to the same grid used in display. We combine several techniques to display the data. MRI data is reconstructed from 2D slices into 3D structures from which isosurfaces are extracted and represented by approximating polygonalizations. These are then displayed using standard graphics pipelines including shaded and transparent images. PET data measures the qualitative rates of cerebral glucose utilization or oxygen consumption. PET image is best displayed as a volume of luminous particles. The combination of both display methods allows the viewer to compare the functional information contained in the PET data with the anatomically more precise MRI data.

Is Rest Really Rest? Resting State Functional Connectivity during Rest and Motor Task Paradigms.

PubMed

Jurkiewicz, Michael T; Crawley, Adrian P; Mikulis, David J

2018-04-18

Numerous studies have identified the default mode network (DMN) within the brain of healthy individuals, which has been attributed to the ongoing mental activity of the brain during the wakeful resting-state. While engaged during specific resting-state fMRI paradigms, it remains unclear as to whether traditional block-design simple movement fMRI experiments significantly influence the default mode network or other areas. Using blood-oxygen level dependent (BOLD) fMRI we characterized the pattern of functional connectivity in healthy subjects during a resting-state paradigm and compared this to the same resting-state analysis performed on motor task data residual time courses after regressing out the task paradigm. Using seed-voxel analysis to define the DMN, the executive control network (ECN), and sensorimotor, auditory and visual networks, the resting-state analysis of the residual time courses demonstrated reduced functional connectivity in the motor network and reduced connectivity between the insula and the ECN compared to the standard resting-state datasets. Overall, performance of simple self-directed motor tasks does little to change the resting-state functional connectivity across the brain, especially in non-motor areas. This would suggest that previously acquired fMRI studies incorporating simple block-design motor tasks could be mined retrospectively for assessment of the resting-state connectivity.

Resting-state functional connectivity and motor imagery brain activation

PubMed Central

Saiote, Catarina; Tacchino, Andrea; Brichetto, Giampaolo; Roccatagliata, Luca; Bommarito, Giulia; Cordano, Christian; Battaglia, Mario; Mancardi, Giovanni Luigi; Inglese, Matilde

2016-01-01

Motor imagery (MI) relies on the mental simulation of an action without any overt motor execution (ME), and can facilitate motor learning and enhance the effect of rehabilitation in patients with neurological conditions. While functional magnetic resonance imaging (fMRI) during MI and ME reveals shared cortical representations, the role and functional relevance of the resting-state functional connectivity (RSFC) of brain regions involved in MI is yet unknown. Here, we performed resting-state fMRI followed by fMRI during ME and MI with the dominant hand. We used a behavioral chronometry test to measure ME and MI movement duration and compute an index of performance (IP). Then, we analyzed the voxel-matched correlation between the individual MI parameter estimates and seed-based RSFC maps in the MI network to measure the correspondence between RSFC and MI fMRI activation. We found that inter-individual differences in intrinsic connectivity in the MI network predicted several clusters of activation. Taken together, present findings provide first evidence that RSFC within the MI network is predictive of the activation of MI brain regions, including those associated with behavioral performance, thus suggesting a role for RSFC in obtaining a deeper understanding of neural substrates of MI and of MI ability. PMID:27273577

Using fMRI to study reward processing in humans: past, present, and future

PubMed Central

Wang, Kainan S.; Smith, David V.

2016-01-01

Functional magnetic resonance imaging (fMRI) is a noninvasive tool used to probe cognitive and affective processes. Although fMRI provides indirect measures of neural activity, the advent of fMRI has allowed for 1) the corroboration of significant animal findings in the human brain, and 2) the expansion of models to include more common human attributes that inform behavior. In this review, we briefly consider the neural basis of the blood oxygenation level dependent signal to set up a discussion of how fMRI studies have applied it in examining cognitive models in humans and the promise of using fMRI to advance such models. Specifically, we illustrate the contribution that fMRI has made to the study of reward processing, focusing on the role of the striatum in encoding reward-related learning signals that drive anticipatory and consummatory behaviors. For instance, we discuss how fMRI can be used to link neural signals (e.g., striatal responses to rewards) to individual differences in behavior and traits. While this functional segregation approach has been constructive to our understanding of reward-related functions, many fMRI studies have also benefitted from a functional integration approach that takes into account how interconnected regions (e.g., corticostriatal circuits) contribute to reward processing. We contend that future work using fMRI will profit from using a multimodal approach, such as combining fMRI with noninvasive brain stimulation tools (e.g., transcranial electrical stimulation), that can identify causal mechanisms underlying reward processing. Consequently, advancements in implementing fMRI will promise new translational opportunities to inform our understanding of psychopathologies. PMID:26740530

Functional Neuroimaging of Spike-Wave Seizures

PubMed Central

Motelow, Joshua E.; Blumenfeld, Hal

2013-01-01

Generalized spike-wave seizures are typically brief events associated with dynamic changes in brain physiology, metabolism, and behavior. Functional magnetic resonance imaging (fMRI) provides a relatively high spatio-temporal resolution method for imaging cortical-subcortical network activity during spike-wave seizures. Patients with spike-wave seizures often have episodes of staring and unresponsiveness which interfere with normal behavior. Results from human fMRI studies suggest that spike-wave seizures disrupt specific networks in the thalamus and fronto-parietal association cortex which are critical for normal attentive consciousness. However, the neuronal activity underlying imaging changes seen during fMRI is not well understood, particularly in abnormal conditions such as seizures. Animal models have begun to provide important fundamental insights into the neuronal basis for fMRI changes during spike-wave activity. Work from these models including both fMRI and direct neuronal recordings suggest that, like in humans, specific cortical-subcortical networks are involved in spike-wave, while other regions are spared. Regions showing fMRI increases demonstrate correlated increases in neuronal activity in animal models. The mechanisms of fMRI decreases in spike-wave will require further investigation. A better understanding of the specific brain regions involved in generating spike-wave seizures may help guide efforts to develop targeted therapies aimed at preventing or reversing abnormal excitability in these brain regions, ultimately leading to a cure for this disorder. PMID:18839093

Spatially aggregated multiclass pattern classification in functional MRI using optimally selected functional brain areas.

PubMed

Zheng, Weili; Ackley, Elena S; Martínez-Ramón, Manel; Posse, Stefan

2013-02-01

In previous works, boosting aggregation of classifier outputs from discrete brain areas has been demonstrated to reduce dimensionality and improve the robustness and accuracy of functional magnetic resonance imaging (fMRI) classification. However, dimensionality reduction and classification of mixed activation patterns of multiple classes remain challenging. In the present study, the goals were (a) to reduce dimensionality by combining feature reduction at the voxel level and backward elimination of optimally aggregated classifiers at the region level, (b) to compare region selection for spatially aggregated classification using boosting and partial least squares regression methods and (c) to resolve mixed activation patterns using probabilistic prediction of individual tasks. Brain activation maps from interleaved visual, motor, auditory and cognitive tasks were segmented into 144 functional regions. Feature selection reduced the number of feature voxels by more than 50%, leaving 95 regions. The two aggregation approaches further reduced the number of regions to 30, resulting in more than 75% reduction of classification time and misclassification rates of less than 3%. Boosting and partial least squares (PLS) were compared to select the most discriminative and the most task correlated regions, respectively. Successful task prediction in mixed activation patterns was feasible within the first block of task activation in real-time fMRI experiments. This methodology is suitable for sparsifying activation patterns in real-time fMRI and for neurofeedback from distributed networks of brain activation. Copyright © 2013 Elsevier Inc. All rights reserved.

Liver transplantation nearly normalizes brain spontaneous activity and cognitive function at 1 month: a resting-state functional MRI study.

PubMed

Cheng, Yue; Huang, Lixiang; Zhang, Xiaodong; Zhong, Jianhui; Ji, Qian; Xie, Shuangshuang; Chen, Lihua; Zuo, Panli; Zhang, Long Jiang; Shen, Wen

2015-08-01

To investigate the short-term brain activity changes in cirrhotic patients with Liver transplantation (LT) using resting-state functional MRI (fMRI) with regional homogeneity (ReHo) method. Twenty-six cirrhotic patients as transplant candidates and 26 healthy controls were included in this study. The assessment was repeated for a sub-group of 12 patients 1 month after LT. ReHo values were calculated to evaluate spontaneous brain activity and whole brain voxel-wise analysis was carried to detect differences between groups. Correlation analyses were performed to explore the relationship between the change of ReHo with the change of clinical indexes pre- and post-LT. Compared to pre-LT, ReHo values increased in the bilateral inferior frontal gyrus (IFG), right inferior parietal lobule (IPL), right supplementary motor area (SMA), right STG and left middle frontal gyrus (MFG) in patients post-LT. Compared to controls, ReHo values of post-LT patients decreased in the right precuneus, right SMA and increased in bilateral temporal pole, left caudate, left MFG, and right STG. The changes of ReHo in the right SMA, STG and IFG were correlated with change of digit symbol test (DST) scores (P < 0.05 uncorrected). This study found that, at 1 month after LT, spontaneous brain activity of most brain regions with decreased ReHo in pre-LT was substantially improved and nearly normalized, while spontaneous brain activity of some brain regions with increased ReHo in pre-LT continuously increased. ReHo may provide information on the neural mechanisms of LT' effects on brain function.

Optimizing Within-Subject Experimental Designs for jICA of Multi-Channel ERP and fMRI

PubMed Central

Mangalathu-Arumana, Jain; Liebenthal, Einat; Beardsley, Scott A.

2018-01-01

Joint independent component analysis (jICA) can be applied within subject for fusion of multi-channel event-related potentials (ERP) and functional magnetic resonance imaging (fMRI), to measure brain function at high spatiotemporal resolution (Mangalathu-Arumana et al., 2012). However, the impact of experimental design choices on jICA performance has not been systematically studied. Here, the sensitivity of jICA for recovering neural sources in individual data was evaluated as a function of imaging SNR, number of independent representations of the ERP/fMRI data, relationship between instantiations of the joint ERP/fMRI activity (linear, non-linear, uncoupled), and type of sources (varying parametrically and non-parametrically across representations of the data), using computer simulations. Neural sources were simulated with spatiotemporal and noise attributes derived from experimental data. The best performance, maximizing both cross-modal data fusion and the separation of brain sources, occurred with a moderate number of representations of the ERP/fMRI data (10–30), as in a mixed block/event related experimental design. Importantly, the type of relationship between instantiations of the ERP/fMRI activity, whether linear, non-linear or uncoupled, did not in itself impact jICA performance, and was accurately recovered in the common profiles (i.e., mixing coefficients). Thus, jICA provides an unbiased way to characterize the relationship between ERP and fMRI activity across brain regions, in individual data, rendering it potentially useful for characterizing pathological conditions in which neurovascular coupling is adversely affected. PMID:29410611

Disrupted resting-state functional architecture of the brain after 45-day simulated microgravity

PubMed Central

Zhou, Yuan; Wang, Yun; Rao, Li-Lin; Liang, Zhu-Yuan; Chen, Xiao-Ping; Zheng, Dang; Tan, Cheng; Tian, Zhi-Qiang; Wang, Chun-Hui; Bai, Yan-Qiang; Chen, Shan-Guang; Li, Shu

2014-01-01

Long-term spaceflight induces both physiological and psychological changes in astronauts. To understand the neural mechanisms underlying these physiological and psychological changes, it is critical to investigate the effects of microgravity on the functional architecture of the brain. In this study, we used resting-state functional MRI (rs-fMRI) to study whether the functional architecture of the brain is altered after 45 days of −6° head-down tilt (HDT) bed rest, which is a reliable model for the simulation of microgravity. Sixteen healthy male volunteers underwent rs-fMRI scans before and after 45 days of −6° HDT bed rest. Specifically, we used a commonly employed graph-based measure of network organization, i.e., degree centrality (DC), to perform a full-brain exploration of the regions that were influenced by simulated microgravity. We subsequently examined the functional connectivities of these regions using a seed-based resting-state functional connectivity (RSFC) analysis. We found decreased DC in two regions, the left anterior insula (aINS) and the anterior part of the middle cingulate cortex (MCC; also called the dorsal anterior cingulate cortex in many studies), in the male volunteers after 45 days of −6° HDT bed rest. Furthermore, seed-based RSFC analyses revealed that a functional network anchored in the aINS and MCC was particularly influenced by simulated microgravity. These results provide evidence that simulated microgravity alters the resting-state functional architecture of the brains of males and suggest that the processing of salience information, which is primarily subserved by the aINS–MCC functional network, is particularly influenced by spaceflight. The current findings provide a new perspective for understanding the relationships between microgravity, cognitive function, autonomic neural function, and central neural activity. PMID:24926242

Alterations of parenchymal microstructure, neuronal connectivity and cerebrovascular resistance at adolescence following mild to moderate traumatic brain injury in early development.

PubMed

Parent, Maxime; Li, Ying; Santhakumar, Vijayalakshmi; Hyder, Fahmeed; Sanganahalli, Basavaraju G; Kannurpatti, Sridhar

2018-06-01

TBI is a leading cause of morbidity in children. To investigate outcome of early developmental TBI during adolescence, a rat model of fluid percussion injury was developed, where previous work reported deficits in sensorimotor behavior and cortical blood flow at adolescence. 1 Based on the non-localized outcome, we hypothesized that multiple neurophysiological components of brain function, namely neuronal connectivity, synapse/axonal microstructural integrity and neurovascular function are altered and magnetic resonance imaging (MRI) methods could be used to determine regional alterations. Adolescent outcomes of developmental TBI were studied 2-months after injury, using functional MRI (fMRI) and Diffusion Tensor Imaging (DTI). fMRI based resting state functional connectivity (RSFC), representing neural connectivity, was significantly altered between sham and TBI. RSFC strength decreased in the cortex, hippocampus and thalamus accompanied by decrease in the spatial extent of their corresponding RSFC networks and inter-hemispheric asymmetry. Cerebrovascular reactivity to arterial CO2 changes diminished after TBI across both hemispheres, with a more pronounced decrease in the ipsilateral hippocampus, thalamus and motor cortex. DTI measures of fractional anisotropy (FA) and apparent diffusion coefficient (ADC), reporting on axonal and microstructural integrity of the brain, indicated similar inter-hemispheric asymmetry, with highest change in the ipsilateral hippocampus and regions adjoining the ipsilateral thalamus, hypothalamus and amygdala. TBI-induced corpus callosal microstructural alterations indicated measurable changes in inter-hemispheric structural connectivity. Hippocampus, thalamus and select cortical regions were most consistently affected in multiple imaging markers. The multi-modal MRI results demonstrate cortical and subcortical alterations in neural connectivity, cerebrovascular resistance and parenchymal microstructure in the adolescent brain, indicating the highly diffuse and persistent nature of the lateral fluid percussion TBI early in development.

[Functional neuroimaging of the brain structures associated with language in healthy individuals and patients with post-stroke aphasia].

PubMed

Alferova, V V; Mayorova, L A; Ivanova, E G; Guekht, A B; Shklovskij, V M

2017-01-01

The introduction of non-invasive functional neuroimaging techniques such as functional magnetic resonance imaging (fMRI), in the practice of scientific and clinical research can increase our knowledge about the organization of cognitive processes, including language, in normal and reorganization of these cognitive functions in post-stroke aphasia. The article discusses the results of fMRI studies of functional organization of the cortex of a healthy adult's brain in the processing of various voice information as well as the main types of speech reorganization after post-stroke aphasia in different stroke periods. The concepts of 'effective' and 'ineffective' brain plasticity in post-stroke aphasia were considered. It was concluded that there was an urgent need for further comprehensive studies, including neuropsychological testing and several complementary methods of functional neuroimaging, to develop a phased treatment plan and neurorehabilitation of patients with post-stroke aphasia.

The effects of gender and COMT Val158Met polymorphism on fearful facial affect recognition: a fMRI study.

PubMed

Kempton, Matthew J; Haldane, Morgan; Jogia, Jigar; Christodoulou, Tessa; Powell, John; Collier, David; Williams, Steven C R; Frangou, Sophia

2009-04-01

The functional catechol-O-methyltransferase (COMT Val108/158Met) polymorphism has been shown to have an impact on tasks of executive function, memory and attention and recently, tasks with an affective component. As oestrogen reduces COMT activity, we focused on the interaction between gender and COMT genotype on brain activations during an affective processing task. We used functional MRI (fMRI) to record brain activations from 74 healthy subjects who engaged in a facial affect recognition task; subjects viewed and identified fearful compared to neutral faces. There was no main effect of the COMT polymorphism, gender or genotypexgender interaction on task performance. We found a significant effect of gender on brain activations in the left amygdala and right temporal pole, where females demonstrated increased activations over males. Within these regions, Val/Val carriers showed greater signal magnitude compared to Met/Met carriers, particularly in females. The COMT Val108/158Met polymorphism impacts on gender-related patterns of activation in limbic and paralimbic regions but the functional significance of any oestrogen-related COMT inhibition appears modest.

Relating Brain Damage to Brain Plasticity in Patients With Multiple Sclerosis

PubMed Central

Tomassini, Valentina; Johansen-Berg, Heidi; Jbabdi, Saad; Wise, Richard G.; Pozzilli, Carlo; Palace, Jacqueline; Matthews, Paul M.

2013-01-01

Background Failure of adaptive plasticity with increasing pathology is suggested to contribute to progression of disability in multiple sclerosis (MS). However, functional impairments can be reduced with practice, suggesting that brain plasticity is preserved even in patients with substantial damage. Objective Here, functional magnetic resonance imaging (fMRI) was used to probe systems-level mechanisms of brain plasticity associated with improvements in visuomotor performance in MS patients and related to measures of microstructural damage. Methods 23 MS patients and 12 healthy controls underwent brain fMRI during the first practice session of a visuomotor task (short-term practice) and after 2 weeks of daily practice with the same task (longer-term practice). Participants also underwent a structural brain MRI scan. Results Patients performed more poorly than controls at baseline. Nonetheless, with practice, patients showed performance improvements similar to controls and independent of the extent of MRI measures of brain pathology. Different relationships between performance improvements and activations were found between groups: greater short-term improvements were associated with lower activation in the sensorimotor, posterior cingulate, and parahippocampal cortices for patients, whereas greater long-term improvements correlated with smaller activation reductions in the visual cortex of controls. Conclusions Brain plasticity for visuomotor practice is preserved in MS patients despite a high burden of cerebral pathology. Cognitive systems different from those acting in controls contribute to this plasticity in patients. These findings challenge the notion that increasing pathology is accompanied by an outright failure of adaptive plasticity, supporting a neuroscientific rationale for recovery-oriented strategies even in chronically disabled patients. PMID:22328685

Nonlinear changes in brain activity during continuous word repetition: an event-related multiparametric functional MR imaging study.

PubMed

Hagenbeek, R E; Rombouts, S A R B; Veltman, D J; Van Strien, J W; Witter, M P; Scheltens, P; Barkhof, F

2007-10-01

Changes in brain activation as a function of continuous multiparametric word recognition have not been studied before by using functional MR imaging (fMRI), to our knowledge. Our aim was to identify linear changes in brain activation and, what is more interesting, nonlinear changes in brain activation as a function of extended word repetition. Fifteen healthy young right-handed individuals participated in this study. An event-related extended continuous word-recognition task with 30 target words was used to study the parametric effect of word recognition on brain activation. Word-recognition-related brain activation was studied as a function of 9 word repetitions. fMRI data were analyzed with a general linear model with regressors for linearly changing signal intensity and nonlinearly changing signal intensity, according to group average reaction time (RT) and individual RTs. A network generally associated with episodic memory recognition showed either constant or linearly decreasing brain activation as a function of word repetition. Furthermore, both anterior and posterior cingulate cortices and the left middle frontal gyrus followed the nonlinear curve of the group RT, whereas the anterior cingulate cortex was also associated with individual RT. Linear alteration in brain activation as a function of word repetition explained most changes in blood oxygen level-dependent signal intensity. Using a hierarchically orthogonalized model, we found evidence for nonlinear activation associated with both group and individual RTs.

Effect of deafferentation from spinal anesthesia on pain sensitivity and resting-state functional brain connectivity in healthy male volunteers.

PubMed

Niesters, Marieke; Sitsen, Elske; Oudejans, Linda; Vuyk, Jaap; Aarts, Leon P H J; Rombouts, Serge A R B; de Rover, Mischa; Khalili-Mahani, Najmeh; Dahan, Albert

2014-08-01

Patients may perceive paradoxical heat sensation during spinal anesthesia. This could be due to deafferentation-related functional changes at cortical, subcortical, or spinal levels. In the current study, the effect of spinal deafferentation on sensory (pain) sensitivity was studied and linked to whole-brain functional connectivity as assessed by resting-state functional magnetic resonance imaging (RS-fMRI) imaging. Deafferentation was induced by sham or spinal anesthesia (15 mg bupivacaine injected at L3-4) in 12 male volunteers. RS-fMRI brain connectivity was determined in relation to eight predefined and seven thalamic resting-state networks (RSNs) and measured before, and 1 and 2 h after spinal/sham injection. To measure the effect of deafferentation on pain sensitivity, responses to heat pain were measured at 15-min intervals on nondeafferented skin and correlated to RS-fMRI connectivity data. Spinal anesthesia altered functional brain connectivity within brain regions involved in the sensory discriminative (i.e., pain intensity related) and affective dimensions of pain perception in relation to somatosensory and thalamic RSNs. A significant enhancement of pain sensitivity on nondeafferented skin was observed after spinal anesthesia compared to sham (area-under-the-curve [mean (SEM)]: 190.4 [33.8] versus 13.7 [7.2]; p<0.001), which significantly correlated to functional connectivity changes observed within the thalamus in relation to the thalamo-prefrontal network, and in the anterior cingulate cortex and insula in relation to the thalamo-parietal network. Enhanced pain sensitivity from spinal deafferentation correlated with functional connectivity changes within brain regions involved in affective and sensory pain processing and areas involved in descending control of pain.

Methodology for functional MRI of simulated driving.

PubMed

Kan, Karen; Schweizer, Tom A; Tam, Fred; Graham, Simon J

2013-01-01

The developed world faces major socioeconomic and medical challenges associated with motor vehicle accidents caused by risky driving. Functional magnetic resonance imaging (fMRI) of individuals using virtual reality driving simulators may provide an important research tool to assess driving safety, based on brain activity and behavior. A fMRI-compatible driving simulator was developed and evaluated in the context of straight driving, turning, and stopping in 16 young healthy adults. Robust maps of brain activity were obtained, including activation of the primary motor cortex, cerebellum, visual cortex, and parietal lobe, with limited head motion (<1.5 mm deviation from mean head position in the superior∕inferior direction in all subjects) and only minor correlations between head motion, steering, or braking behavior. These results are consistent with previous literature and suggest that with care, fMRI of simulated driving is a feasible undertaking.

Brain functional network abnormality extends beyond the sensorimotor network in brachial plexus injury patients.

PubMed

Feng, Jun-Tao; Liu, Han-Qiu; Hua, Xu-Yun; Gu, Yu-Dong; Xu, Jian-Guang; Xu, Wen-Dong

2016-12-01

Brachial plexus injury (BPI) is a type of severe peripheral nerve trauma that leads to central remodeling in the brain, as revealed by functional MRI analysis. However, previously reported remodeling is mostly restricted to sensorimotor areas of the brain. Whether this disturbance in the sensorimotor network leads to larger-scale functional remodeling remains unknown. We sought to explore the higher-level brain functional abnormality pattern of BPI patients from a large-scale network function connectivity dimension in 15 right-handed BPI patients. Resting-state functional MRI data were collected and analyzed using independent component analysis methods. Five components of interest were recognized and compared between patients and healthy subjects. Patients showed significantly altered brain local functional activities in the bilateral fronto-parietal network (FPN), sensorimotor network (SMN), and executive-control network (ECN) compared with healthy subjects. Moreover, functional connectivity between SMN and ECN were significantly less in patients compared with healthy subjects, and connectivity strength between ECN and SMN was negatively correlated with patients' residual function of the affected limb. Functional connectivity between SMN and right FPN were also significantly less than in controls, although connectivity between ECN and default mode network (DMN) was greater than in controls. These data suggested that brain functional disturbance in BPI patients extends beyond the sensorimotor network and cascades serial remodeling in the brain, which significantly correlates with residual hand function of the paralyzed limb. Furthermore, functional remodeling in these higher-level functional networks may lead to cognitive alterations in complex tasks.

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

PubMed

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

2017-07-15

There is growing interest in understanding the dynamical properties of functional interactions between distributed brain regions. However, robust estimation of temporal dynamics from functional magnetic resonance imaging (fMRI) data remains challenging due to limitations in extant multivariate methods for modeling time-varying functional interactions between multiple brain areas. Here, we develop a Bayesian generative model for fMRI time-series within the framework of hidden Markov models (HMMs). The model is a dynamic variant of the static factor analysis model (Ghahramani and Beal, 2000). We refer to this model as Bayesian switching factor analysis (BSFA) as it integrates factor analysis into a generative HMM in a unified Bayesian framework. In BSFA, brain dynamic functional networks are represented by latent states which are learnt from the data. Crucially, BSFA is a generative model which estimates the temporal evolution of brain states and transition probabilities between states as a function of time. An attractive feature of BSFA is the automatic determination of the number of latent states via Bayesian model selection arising from penalization of excessively complex models. Key features of BSFA are validated using extensive simulations on carefully designed synthetic data. We further validate BSFA using fingerprint analysis of multisession resting-state fMRI data from the Human Connectome Project (HCP). Our results show that modeling temporal dependencies in the generative model of BSFA results in improved fingerprinting of individual participants. Finally, we apply BSFA to elucidate the dynamic functional organization of the salience, central-executive, and default mode networks-three core neurocognitive systems with central role in cognitive and affective information processing (Menon, 2011). Across two HCP sessions, we demonstrate a high level of dynamic interactions between these networks and determine that the salience network has the highest temporal flexibility among the three networks. Our proposed methods provide a novel and powerful generative model for investigating dynamic brain connectivity. Copyright © 2017 Elsevier Inc. All rights reserved.

Combined Functional and Causal Connectivity Analyses of Language Networks in Children: A Feasibility Study

ERIC Educational Resources Information Center

Wilke, Marko; Lidzba, Karen; Krageloh-Mann, Ingeborg

2009-01-01

Instead of assessing activation in distinct brain regions, approaches to investigating the networks underlying distinct brain functions have come into the focus of neuroscience research. Here, we provide a completely data-driven framework for assessing functional and causal connectivity in functional magnetic resonance imaging (fMRI) data,…

Revealing topological organization of human brain functional networks with resting-state functional near infrared spectroscopy.

PubMed

Niu, Haijing; Wang, Jinhui; Zhao, Tengda; Shu, Ni; He, Yong

2012-01-01

The human brain is a highly complex system that can be represented as a structurally interconnected and functionally synchronized network, which assures both the segregation and integration of information processing. Recent studies have demonstrated that a variety of neuroimaging and neurophysiological techniques such as functional magnetic resonance imaging (MRI), diffusion MRI and electroencephalography/magnetoencephalography can be employed to explore the topological organization of human brain networks. However, little is known about whether functional near infrared spectroscopy (fNIRS), a relatively new optical imaging technology, can be used to map functional connectome of the human brain and reveal meaningful and reproducible topological characteristics. We utilized resting-state fNIRS (R-fNIRS) to investigate the topological organization of human brain functional networks in 15 healthy adults. Brain networks were constructed by thresholding the temporal correlation matrices of 46 channels and analyzed using graph-theory approaches. We found that the functional brain network derived from R-fNIRS data had efficient small-world properties, significant hierarchical modular structure and highly connected hubs. These results were highly reproducible both across participants and over time and were consistent with previous findings based on other functional imaging techniques. Our results confirmed the feasibility and validity of using graph-theory approaches in conjunction with optical imaging techniques to explore the topological organization of human brain networks. These results may expand a methodological framework for utilizing fNIRS to study functional network changes that occur in association with development, aging and neurological and psychiatric disorders.

Addiction Related Alteration in Resting-state Brain Connectivity

PubMed Central

Ma, Ning; Liu, Ying; Li, Nan; Wang, Chang-Xin; Zhang, Hao; Jiang, Xiao-Feng; Xu, Hu-Sheng; Fu, Xian-Ming; Hu, Xiaoping; Zhang, Da-Ren

2009-01-01

It is widely accepted that addictive drug use is related to abnormal functional organization in the user’s brain. The present study aimed to identify this type of abnormality within the brain networks implicated in addiction by resting-state functional connectivity measured with functional magnetic resonance imaging (fMRI). With fMRI data acquired during resting state from 14 chronic heroin users (12 of whom were being treated with methadone) and 13 non-addicted controls, we investigated the addiction related alteration in functional connectivity between the regions in the circuits implicated in addiction with seed-based correlation analysis. Compared with controls, chronic heroin users showed increased functional connectivity between nucleus accumbens and ventral/rostral anterior cingulate cortex (ACC), and orbital frontal cortex (OFC), between amygdala and OFC; and reduced functional connectivity between prefrontal cortex and OFC, and ACC. These observations of altered resting-state functional connectivity suggested abnormal functional organization in the addicted brain and may provide additional evidence supporting the theory of addiction that emphasizes enhanced salience value of a drug and its related cues but weakened cognitive control in the addictive state. PMID:19703568

Altered resting brain function and structure in professional badminton players.

PubMed

Di, Xin; Zhu, Senhua; Jin, Hua; Wang, Pin; Ye, Zhuoer; Zhou, Ke; Zhuo, Yan; Rao, Hengyi

2012-01-01

Neuroimaging studies of professional athletic or musical training have demonstrated considerable practice-dependent plasticity in various brain structures, which may reflect distinct training demands. In the present study, structural and functional brain alterations were examined in professional badminton players and compared with healthy controls using magnetic resonance imaging (MRI) and resting-state functional MRI. Gray matter concentration (GMC) was assessed using voxel-based morphometry (VBM), and resting-brain functions were measured by amplitude of low-frequency fluctuation (ALFF) and seed-based functional connectivity. Results showed that the athlete group had greater GMC and ALFF in the right and medial cerebellar regions, respectively. The athlete group also demonstrated smaller ALFF in the left superior parietal lobule and altered functional connectivity between the left superior parietal and frontal regions. These findings indicate that badminton expertise is associated with not only plastic structural changes in terms of enlarged gray matter density in the cerebellum, but also functional alterations in fronto-parietal connectivity. Such structural and functional alterations may reflect specific experiences of badminton training and practice, including high-capacity visuo-spatial processing and hand-eye coordination in addition to refined motor skills.

A Magnetic Resonance Compatible Soft Wearable Robotic Glove for Hand Rehabilitation and Brain Imaging.

PubMed

Hong Kai Yap; Kamaldin, Nazir; Jeong Hoon Lim; Nasrallah, Fatima A; Goh, James Cho Hong; Chen-Hua Yeow

2017-06-01

In this paper, we present the design, fabrication and evaluation of a soft wearable robotic glove, which can be used with functional Magnetic Resonance imaging (fMRI) during the hand rehabilitation and task specific training. The soft wearable robotic glove, called MR-Glove, consists of two major components: a) a set of soft pneumatic actuators and b) a glove. The soft pneumatic actuators, which are made of silicone elastomers, generate bending motion and actuate finger joints upon pressurization. The device is MR-compatible as it contains no ferromagnetic materials and operates pneumatically. Our results show that the device did not cause artifacts to fMRI images during hand rehabilitation and task-specific exercises. This study demonstrated the possibility of using fMRI and MR-compatible soft wearable robotic device to study brain activities and motor performances during hand rehabilitation, and to unravel the functional effects of rehabilitation robotics on brain stimulation.

Prefrontal-hippocampal-fusiform activity during encoding predicts intraindividual differences in free recall ability: an event-related functional-anatomic MRI study.

PubMed

Dickerson, B C; Miller, S L; Greve, D N; Dale, A M; Albert, M S; Schacter, D L; Sperling, R A

2007-01-01

The ability to spontaneously recall recently learned information is a fundamental mnemonic activity of daily life, but has received little study using functional neuroimaging. We developed a functional MRI (fMRI) paradigm to study regional brain activity during encoding that predicts free recall. In this event-related fMRI study, ten lists of fourteen pictures of common objects were shown to healthy young individuals and regional brain activity during encoding was analyzed based on subsequent free recall performance. Free recall of items was predicted by activity during encoding in hippocampal, fusiform, and inferior prefrontal cortical regions. Within-subject variance in free recall performance for the ten lists was predicted by a linear combination of condition-specific inferior prefrontal, hippocampal, and fusiform activity. Recall performance was better for lists in which prefrontal activity was greater for all items of the list and hippocampal and fusiform activity were greater specifically for items that were recalled from the list. Thus, the activity of medial temporal, fusiform, and prefrontal brain regions during the learning of new information is important for the subsequent free recall of this information. These fronto-temporal brain regions act together as a large-scale memory-related network, the components of which make distinct yet interacting contributions during encoding that predict subsequent successful free recall performance.

Prefrontal-Hippocampal-Fusiform Activity During Encoding Predicts Intraindividual Differences in Free Recall Ability: An Event-Related Functional-Anatomic MRI Study

PubMed Central

Dickerson, B.C.; Miller, S.L.; Greve, D.N.; Dale, A.M.; Albert, M.S.; Schacter, D.L.; Sperling, R.A.

2009-01-01

The ability to spontaneously recall recently learned information is a fundamental mnemonic activity of daily life, but has received little study using functional neuroimaging. We developed a functional MRI (fMRI) paradigm to study regional brain activity during encoding that predicts free recall. In this event-related fMRI study, ten lists of fourteen pictures of common objects were shown to healthy young individuals and regional brain activity during encoding was analyzed based on subsequent free recall performance. Free recall of items was predicted by activity during encoding in hippocampal, fusiform, and inferior prefrontal cortical regions. Within-subject variance in free recall performance for the ten lists was predicted by a linear combination of condition-specific inferior prefrontal, hippocampal, and fusiform activity. Recall performance was better for lists in which pre-frontal activity was greater for all items of the list and hippocampal and fusi-form activity were greater specifically for items that were recalled from the list. Thus, the activity of medial temporal, fusiform, and prefrontal brain regions during the learning of new information is important for the subsequent free recall of this information. These fronto-temporal brain regions act together as a large-scale memory-related network, the components of which make distinct yet interacting contributions during encoding that predict subsequent successful free recall performance. PMID:17604356

Autobiographical Memory in Semantic Dementia: A Longitudinal fMRI Study

ERIC Educational Resources Information Center

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

2010-01-01

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

Lying about Facial Recognition: An fMRI Study

ERIC Educational Resources Information Center

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

2009-01-01

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

A computerized tablet with visual feedback of hand position for functional magnetic resonance imaging

PubMed Central

Karimpoor, Mahta; Tam, Fred; Strother, Stephen C.; Fischer, Corinne E.; Schweizer, Tom A.; Graham, Simon J.

2015-01-01

Neuropsychological tests behavioral tasks that very commonly involve handwriting and drawing are widely used in the clinic to detect abnormal brain function. Functional magnetic resonance imaging (fMRI) may be useful in increasing the specificity of such tests. However, performing complex pen-and-paper tests during fMRI involves engineering challenges. Previously, we developed an fMRI-compatible, computerized tablet system to address this issue. However, the tablet did not include visual feedback of hand position (VFHP), a human factors component that may be important for fMRI of certain patient populations. A real-time system was thus developed to provide VFHP and integrated with the tablet in an augmented reality display. The effectiveness of the system was initially tested in young healthy adults who performed various handwriting tasks in front of a computer display with and without VFHP. Pilot fMRI of writing tasks were performed by two representative individuals with and without VFHP. Quantitative analysis of the behavioral results indicated improved writing performance with VFHP. The pilot fMRI results suggest that writing with VFHP requires less neural resources compared to the without VFHP condition, to maintain similar behavior. Thus, the tablet system with VFHP is recommended for future fMRI studies involving patients with impaired brain function and where ecologically valid behavior is important. PMID:25859201

Cerebro-cerebellar functional connectivity profile of an epilepsy patient with periventricular nodular heterotopia.

PubMed

Emiliano, Santarnecchi; Giampaolo, Vatti; Daniela, Marino; Nicola, Polizzotto; Alfonso, Cerase; Raffaele, Rocchi; Alessandro, Rossi

2012-09-01

Periventricular nodular heterotopia (PNH) is a rare malformation of cortical development often associated with drug resistant focal onset epilepsy. The link between nodules and neocortex have been demonstrated with depth electrodes investigations showing that seizures may arise from both structures. In the last years fMRI resting-state (fMRI-RS) have received a surge in interest due to its capability to track non-invasively physiological and pathological relevant differences in brain network organization. We performed a cerebro-cerebellar voxel-wise and region-of-interest resting state fMRI (RS-fMRI) functional connectivity analysis in a seizure-free epilepsy patient with a PNH in the right temporal horn. Our finding confirms a spontaneous synchronization between PNH and its surrounding cortex, specifically in the inferior temporal, fusiform and occipital gyrus. We also found a significant connectivity with bilateral cerebellum, more intense and widespread on the PNH cerebellar contralateral lobule. RS-fMRI confirmed its potential as a promising tool for non-invasive mapping of cortical and subcortical brain functional organization. Copyright © 2012 Elsevier B.V. All rights reserved.

Design analysis of an MPI human functional brain scanner

PubMed Central

Mason, Erica E.; Cooley, Clarissa Z.; Cauley, Stephen F.; Griswold, Mark A.; Conolly, Steven M.; Wald, Lawrence L.

2017-01-01

MPI’s high sensitivity makes it a promising modality for imaging brain function. Functional contrast is proposed based on blood SPION concentration changes due to Cerebral Blood Volume (CBV) increases during activation, a mechanism utilized in fMRI studies. MPI offers the potential for a direct and more sensitive measure of SPION concentration, and thus CBV, than fMRI. As such, fMPI could surpass fMRI in sensitivity, enhancing the scientific and clinical value of functional imaging. As human-sized MPI systems have not been attempted, we assess the technical challenges of scaling MPI from rodent to human brain. We use a full-system MPI simulator to test arbitrary hardware designs and encoding practices, and we examine tradeoffs imposed by constraints that arise when scaling to human size as well as safety constraints (PNS and central nervous system stimulation) not considered in animal scanners, thereby estimating spatial resolutions and sensitivities achievable with current technology. Using a projection FFL MPI system, we examine coil hardware options and their implications for sensitivity and spatial resolution. We estimate that an fMPI brain scanner is feasible, although with reduced sensitivity (20×) and spatial resolution (5×) compared to existing rodent systems. Nonetheless, it retains sufficient sensitivity and spatial resolution to make it an attractive future instrument for studying the human brain; additional technical innovations can result in further improvements. PMID:28752130

Migraine classification using magnetic resonance imaging resting-state functional connectivity data.

PubMed

Chong, Catherine D; Gaw, Nathan; Fu, Yinlin; Li, Jing; Wu, Teresa; Schwedt, Todd J

2017-08-01

Background This study used machine-learning techniques to develop discriminative brain-connectivity biomarkers from resting-state functional magnetic resonance neuroimaging ( rs-fMRI) data that distinguish between individual migraine patients and healthy controls. Methods This study included 58 migraine patients (mean age = 36.3 years; SD = 11.5) and 50 healthy controls (mean age = 35.9 years; SD = 11.0). The functional connections of 33 seeded pain-related regions were used as input for a brain classification algorithm that tested the accuracy of determining whether an individual brain MRI belongs to someone with migraine or to a healthy control. Results The best classification accuracy using a 10-fold cross-validation method was 86.1%. Resting functional connectivity of the right middle temporal, posterior insula, middle cingulate, left ventromedial prefrontal and bilateral amygdala regions best discriminated the migraine brain from that of a healthy control. Migraineurs with longer disease durations were classified more accurately (>14 years; 96.7% accuracy) compared to migraineurs with shorter disease durations (≤14 years; 82.1% accuracy). Conclusions Classification of migraine using rs-fMRI provides insights into pain circuits that are altered in migraine and could potentially contribute to the development of a new, noninvasive migraine biomarker. Migraineurs with longer disease burden were classified more accurately than migraineurs with shorter disease burden, potentially indicating that disease duration leads to reorganization of brain circuitry.

A methodology for generating normal and pathological brain perfusion SPECT images for evaluation of MRI/SPECT fusion methods: application in epilepsy

NASA Astrophysics Data System (ADS)

Grova, C.; Jannin, P.; Biraben, A.; Buvat, I.; Benali, H.; Bernard, A. M.; Scarabin, J. M.; Gibaud, B.

2003-12-01

Quantitative evaluation of brain MRI/SPECT fusion methods for normal and in particular pathological datasets is difficult, due to the frequent lack of relevant ground truth. We propose a methodology to generate MRI and SPECT datasets dedicated to the evaluation of MRI/SPECT fusion methods and illustrate the method when dealing with ictal SPECT. The method consists in generating normal or pathological SPECT data perfectly aligned with a high-resolution 3D T1-weighted MRI using realistic Monte Carlo simulations that closely reproduce the response of a SPECT imaging system. Anatomical input data for the SPECT simulations are obtained from this 3D T1-weighted MRI, while functional input data result from an inter-individual analysis of anatomically standardized SPECT data. The method makes it possible to control the 'brain perfusion' function by proposing a theoretical model of brain perfusion from measurements performed on real SPECT images. Our method provides an absolute gold standard for assessing MRI/SPECT registration method accuracy since, by construction, the SPECT data are perfectly registered with the MRI data. The proposed methodology has been applied to create a theoretical model of normal brain perfusion and ictal brain perfusion characteristic of mesial temporal lobe epilepsy. To approach realistic and unbiased perfusion models, real SPECT data were corrected for uniform attenuation, scatter and partial volume effect. An anatomic standardization was used to account for anatomic variability between subjects. Realistic simulations of normal and ictal SPECT deduced from these perfusion models are presented. The comparison of real and simulated SPECT images showed relative differences in regional activity concentration of less than 20% in most anatomical structures, for both normal and ictal data, suggesting realistic models of perfusion distributions for evaluation purposes. Inter-hemispheric asymmetry coefficients measured on simulated data were found within the range of asymmetry coefficients measured on corresponding real data. The features of the proposed approach are compared with those of other methods previously described to obtain datasets appropriate for the assessment of fusion methods.

[From Brownian motion to mind imaging: diffusion MRI].

PubMed

Le Bihan, Denis

2006-11-01

The success of diffusion MRI, which was introduced in the mid 1980s is deeply rooted in the powerful concept that during their random, diffusion-driven movements water molecules probe tissue structure at a microscopic scale well beyond the usual image resolution. The observation of these movements thus provides valuable information on the structure and the geometric organization of tissues. The most successful application of diffusion MRI has been in brain ischemia, following the discovery that water diffusion drops at a very early stage of the ischemic event. Diffusion MRI provides some patients with the opportunity to receive suitable treatment at a very acute stage when brain tissue might still be salvageable. On the other hand, diffusion is modulated by the spatial orientation of large bundles of myelinated axons running in parallel through in brain white matter. This feature can be exploited to map out the orientation in space of the white matter tracks and to visualize the connections between different parts of the brain on an individual basis. Furthermore, recent data suggest that diffusion MRI may also be used to visualize rapid dynamic tissue changes, such as neuronal swelling, associated with cortical activation, offering a new and direct approach to brain functional imaging.

Resting state functional MRI reveals abnormal network connectivity in Neurofibromatosis 1

PubMed Central

Tomson, S.N.; Schreiner, M.; Narayan, M.; Rosser, Tena; Enrique, Nicole; Silva, Alcino J.; Allen, G.I.; Bookheimer, S.Y.; Bearden, C.E.

2015-01-01

Neurofibromatosis type I (NF1) is a genetic disorder caused by mutations in the neurofibromin 1 gene at locus 17q11.2. Individuals with NF1 have an increased incidence of learning disabilities, attention deficits and autism spectrum disorders. As a single gene disorder, NF1 represents a valuable model for understanding gene-brain-behavior relationships. While mouse models have elucidated molecular and cellular mechanisms underlying learning deficits associated with this mutation, little is known about functional brain architecture in human subjects with NF1. To address this question, we used resting state functional connectivity MRI (rs-fcMRI) to elucidate the intrinsic network structure of 30 NF1 participants compared with 30 healthy demographically matched controls during an eyes-open rs-fcMRI scan. Novel statistical methods were employed to quantify differences in local connectivity (edge strength) and modularity structure, in combination with traditional global graph theory applications. Our findings suggest that individuals with NF1 have reduced anterior-posterior connectivity, weaker bilateral edges, and altered modularity clustering relative to healthy controls. Further, edge strength and modular clustering indices were correlated with IQ and internalizing symptoms. These findings suggest that Ras signaling disruption may lead to abnormal functional brain connectivity; further investigation into the functional consequences of these alterations in both humans and in animal models is warranted. PMID:26304096

Real-time motion analytics during brain MRI improve data quality and reduce costs.

PubMed

Dosenbach, Nico U F; Koller, Jonathan M; Earl, Eric A; Miranda-Dominguez, Oscar; Klein, Rachel L; Van, Andrew N; Snyder, Abraham Z; Nagel, Bonnie J; Nigg, Joel T; Nguyen, Annie L; Wesevich, Victoria; Greene, Deanna J; Fair, Damien A

2017-11-01

Head motion systematically distorts clinical and research MRI data. Motion artifacts have biased findings from many structural and functional brain MRI studies. An effective way to remove motion artifacts is to exclude MRI data frames affected by head motion. However, such post-hoc frame censoring can lead to data loss rates of 50% or more in our pediatric patient cohorts. Hence, many scanner operators collect additional 'buffer data', an expensive practice that, by itself, does not guarantee sufficient high-quality MRI data for a given participant. Therefore, we developed an easy-to-setup, easy-to-use Framewise Integrated Real-time MRI Monitoring (FIRMM) software suite that provides scanner operators with head motion analytics in real-time, allowing them to scan each subject until the desired amount of low-movement data has been collected. Our analyses show that using FIRMM to identify the ideal scan time for each person can reduce total brain MRI scan times and associated costs by 50% or more. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Quasi-periodic patterns (QPP): large-scale dynamics in resting state fMRI that correlate with local infraslow electrical activity.

PubMed

Thompson, Garth John; Pan, Wen-Ju; Magnuson, Matthew Evan; Jaeger, Dieter; Keilholz, Shella Dawn

2014-01-01

Functional connectivity measurements from resting state blood-oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) are proving a powerful tool to probe both normal brain function and neuropsychiatric disorders. However, the neural mechanisms that coordinate these large networks are poorly understood, particularly in the context of the growing interest in network dynamics. Recent work in anesthetized rats has shown that the spontaneous BOLD fluctuations are tightly linked to infraslow local field potentials (LFPs) that are seldom recorded but comparable in frequency to the slow BOLD fluctuations. These findings support the hypothesis that long-range coordination involves low frequency neural oscillations and establishes infraslow LFPs as an excellent candidate for probing the neural underpinnings of the BOLD spatiotemporal patterns observed in both rats and humans. To further examine the link between large-scale network dynamics and infraslow LFPs, simultaneous fMRI and microelectrode recording were performed in anesthetized rats. Using an optimized filter to isolate shared components of the signals, we found that time-lagged correlation between infraslow LFPs and BOLD is comparable in spatial extent and timing to a quasi-periodic pattern (QPP) found from BOLD alone, suggesting that fMRI-measured QPPs and the infraslow LFPs share a common mechanism. As fMRI allows spatial resolution and whole brain coverage not available with electroencephalography, QPPs can be used to better understand the role of infraslow oscillations in normal brain function and neurological or psychiatric disorders. © 2013.

Quasi-periodic patterns (QPP): large-scale dynamics in resting state fMRI that correlate with local infraslow electrical activity

PubMed Central

Thompson, Garth John; Pan, Wen-Ju; Magnuson, Matthew Evan; Jaeger, Dieter; Keilholz, Shella Dawn

2013-01-01

Functional connectivity measurements from resting state blood-oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) are proving a powerful tool to probe both normal brain function and neuropsychiatric disorders. However, the neural mechanisms that coordinate these large networks are poorly understood, particularly in the context of the growing interest in network dynamics. Recent work in anesthetized rats has shown that the spontaneous BOLD fluctuations are tightly linked to infraslow local field potentials (LFPs) that are seldom recorded but comparable in frequency to the slow BOLD fluctuations. These findings support the hypothesis that long-range coordination involves low frequency neural oscillations and establishes infraslow LFPs as an excellent candidate for probing the neural underpinnings of the BOLD spatiotemporal patterns observed in both rats and humans. To further examine the link between large-scale network dynamics and infraslow LFPs, simultaneous fMRI and microelectrode recording were performed in anesthetized rats. Using an optimized filter to isolate shared components of the signals, we found that time-lagged correlation between infraslow LFPs and BOLD is comparable in spatial extent and timing to a quasi-periodic pattern (QPP) found from BOLD alone, suggesting that fMRI-measured QPPs and the infraslow LFPs share a common mechanism. As fMRI allows spatial resolution and whole brain coverage not available with electroencephalography, QPPs can be used to better understand the role of infraslow oscillations in normal brain function and neurological or psychiatric disorders. PMID:24071524

Large-scale Granger causality analysis on resting-state functional MRI

NASA Astrophysics Data System (ADS)

D'Souza, Adora M.; Abidin, Anas Zainul; Leistritz, Lutz; Wismüller, Axel

2016-03-01

We demonstrate an approach to measure the information flow between each pair of time series in resting-state functional MRI (fMRI) data of the human brain and subsequently recover its underlying network structure. By integrating dimensionality reduction into predictive time series modeling, large-scale Granger Causality (lsGC) analysis method can reveal directed information flow suggestive of causal influence at an individual voxel level, unlike other multivariate approaches. This method quantifies the influence each voxel time series has on every other voxel time series in a multivariate sense and hence contains information about the underlying dynamics of the whole system, which can be used to reveal functionally connected networks within the brain. To identify such networks, we perform non-metric network clustering, such as accomplished by the Louvain method. We demonstrate the effectiveness of our approach to recover the motor and visual cortex from resting state human brain fMRI data and compare it with the network recovered from a visuomotor stimulation experiment, where the similarity is measured by the Dice Coefficient (DC). The best DC obtained was 0.59 implying a strong agreement between the two networks. In addition, we thoroughly study the effect of dimensionality reduction in lsGC analysis on network recovery. We conclude that our approach is capable of detecting causal influence between time series in a multivariate sense, which can be used to segment functionally connected networks in the resting-state fMRI.

Evidence for Functional Networks within the Human Brain's White Matter.

PubMed

Peer, Michael; Nitzan, Mor; Bick, Atira S; Levin, Netta; Arzy, Shahar

2017-07-05

Investigation of the functional macro-scale organization of the human cortex is fundamental in modern neuroscience. Although numerous studies have identified networks of interacting functional modules in the gray-matter, limited research was directed to the functional organization of the white-matter. Recent studies have demonstrated that the white-matter exhibits blood oxygen level-dependent signal fluctuations similar to those of the gray-matter. Here we used these signal fluctuations to investigate whether the white-matter is organized as functional networks by applying a clustering analysis on resting-state functional MRI (RSfMRI) data from white-matter voxels, in 176 subjects (of both sexes). This analysis indicated the existence of 12 symmetrical white-matter functional networks, corresponding to combinations of white-matter tracts identified by diffusion tensor imaging. Six of the networks included interhemispheric commissural bridges traversing the corpus callosum. Signals in white-matter networks correlated with signals from functional gray-matter networks, providing missing knowledge on how these distributed networks communicate across large distances. These findings were replicated in an independent subject group and were corroborated by seed-based analysis in small groups and individual subjects. The identified white-matter functional atlases and analysis codes are available at http://mind.huji.ac.il/white-matter.aspx Our results demonstrate that the white-matter manifests an intrinsic functional organization as interacting networks of functional modules, similarly to the gray-matter, which can be investigated using RSfMRI. The discovery of functional networks within the white-matter may open new avenues of research in cognitive neuroscience and clinical neuropsychiatry. SIGNIFICANCE STATEMENT In recent years, functional MRI (fMRI) has revolutionized all fields of neuroscience, enabling identifications of functional modules and networks in the human brain. However, most fMRI studies ignored a major part of the brain, the white-matter, discarding signals from it as arising from noise. Here we use resting-state fMRI data from 176 subjects to show that signals from the human white-matter contain meaningful information. We identify 12 functional networks composed of interacting long-distance white-matter tracts. Moreover, we show that these networks are highly correlated to resting-state gray-matter networks, highlighting their functional role. Our findings enable reinterpretation of many existing fMRI datasets, and suggest a new way to explore the white-matter role in cognition and its disturbances in neuropsychiatric disorders. Copyright © 2017 the authors 0270-6474/17/376394-14$15.00/0.

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

PubMed

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

2015-11-01

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

Tentative Evidence for Striatal Hyperactivity in Adolescent Cannabis Using Boys: A Cross-Sectional Multicenter fMRI Study

PubMed Central

Jager, Gerry; Block, Robert I.; Luijten, Maartje; Ramsey, Nick F.

2013-01-01

Adolescents' risk-taking behavior has been linked to a maturational imbalance between reward (“go”) and inhibitory-control (“stop”) related brain circuitry. This may drive adolescent drug-taking, such as cannabis use. In this study we assessed the non-acute effects of adolescent cannabis use on reward-related brain function. We performed a two-site (United States and Netherlands; pooled data) functional magnetic resonance imaging (fMRI) study with a cross-sectional design. Twenty-one abstinent but frequent cannabis-using boys were compared with 24 non-using peers on reward-related brain function, using a monetary incentive delay task with fMRI. Focus was on anticipatory and response stages of reward and brain areas critically involved in reward processing like the striatum. Performance in users was normal. Region-of-interest analysis indicated striatal hyperactivity during anticipatory stages of reward in users. Intriguingly, this effect was most pronounced during non-rewarding events. Striatal hyperactivity in adolescent cannabis users may signify an overly sensitive motivational brain circuitry. Frequent cannabis use during adolescence may induce diminished ability to disengage the motivational circuit when no reward can be obtained. This could strengthen the search for reinforcements like drugs of abuse, even when facing the negative (non-rewarding) consequences. PMID:23909003

Tentative evidence for striatal hyperactivity in adolescent cannabis-using boys: a cross-sectional multicenter fMRI study.

PubMed

Jager, Gerry; Block, Robert I; Luijten, Maartje; Ramsey, Nick F

2013-01-01

Adolescents' risk-taking behavior has been linked to a maturational imbalance between reward ("go") and inhibitory-control ("stop")-related brain circuitry. This may drive adolescent drug-taking, such as cannabis use. In this study, we assessed the non-acute effects of adolescent cannabis use on reward-related brain function. We performed a two-site (United States and Netherlands; pooled data) functional magnetic resonance imaging (fMRI) study with a cross-sectional design. Twenty-one abstinent but frequent cannabis-using boys were compared with 24 non-using peers on reward-related brain function, using a monetary incentive delay task with fMRI. Focus was on anticipatory and response stages of reward and brain areas critically involved in reward processing like the striatum. Performance in users was normal. Region-of-interest analysis indicated striatal hyperactivity during anticipatory stages of reward in users. Intriguingly, this effect was most pronounced during non-rewarding events. Striatal hyperactivity in adolescent cannabis users may signify an overly sensitive motivational brain circuitry. Frequent cannabis use during adolescence may induce diminished ability to disengage the motivational circuit when no reward can be obtained. This could strengthen the search for reinforcements like drugs of abuse, even when facing the negative (non-rewarding) consequences.

Defining Functional Areas in Individual Human Brains using Resting Functional Connectivity MRI

PubMed Central

Cohen, Alexander L.; Fair, Damien A.; Dosenbach, Nico U.F.; Miezin, Francis M.; Dierker, Donna; Van Essen, David C.; Schlaggar, Bradley L.; Petersen, Steven E.

2009-01-01

The cerebral cortex is anatomically organized at many physical scales starting at the level of single neurons and extending up to functional systems. Current functional magnetic resonance imaging (fMRI) studies often focus at the level of areas, networks, and systems. Except in restricted domains, (e.g. topographically-organized sensory regions), it is difficult to determine area boundaries in the human brain using fMRI. The ability to delineate functional areas non-invasively would enhance the quality of many experimental analyses allowing more accurate across-subject comparisons of independently identified functional areas. Correlations in spontaneous BOLD activity, often referred to as resting state functional connectivity (rs-fcMRI), are especially promising as a way to accurately localize differences in patterns of correlated activity across large expanses of cortex. In the current report, we applied a novel set of image analysis tools to explore the utility of rs-fcMRI for defining wide-ranging functional area boundaries. We find that rs-fcMRI patterns show sharp transitions in correlation patterns and that these putative areal boundaries can be reliably detected in individual subjects as well as in group data. Additionally, combining surface-based analysis techniques with image processing algorithms allows automated mapping of putative areal boundaries across large expanses of cortex without the need for prior information about a region’s function or topography. Our approach reliably produces maps of bounded regions appropriate in size and number for putative functional areas. These findings will hopefully stimulate further methodological refinements and validations. PMID:18367410

Functional MRI registration with tissue-specific patch-based functional correlation tensors.

PubMed

Zhou, Yujia; Zhang, Han; Zhang, Lichi; Cao, Xiaohuan; Yang, Ru; Feng, Qianjin; Yap, Pew-Thian; Shen, Dinggang

2018-06-01

Population studies of brain function with resting-state functional magnetic resonance imaging (rs-fMRI) rely on accurate intersubject registration of functional areas. This is typically achieved through registration using high-resolution structural images with more spatial details and better tissue contrast. However, accumulating evidence has suggested that such strategy cannot align functional regions well because functional areas are not necessarily consistent with anatomical structures. To alleviate this problem, a number of registration algorithms based directly on rs-fMRI data have been developed, most of which utilize functional connectivity (FC) features for registration. However, most of these methods usually extract functional features only from the thin and highly curved cortical grey matter (GM), posing great challenges to accurate estimation of whole-brain deformation fields. In this article, we demonstrate that additional useful functional features can also be extracted from the whole brain, not restricted to the GM, particularly the white-matter (WM), for improving the overall functional registration. Specifically, we quantify local anisotropic correlation patterns of the blood oxygenation level-dependent (BOLD) signals using tissue-specific patch-based functional correlation tensors (ts-PFCTs) in both GM and WM. Functional registration is then performed by integrating the features from different tissues using the multi-channel large deformation diffeomorphic metric mapping (mLDDMM) algorithm. Experimental results show that our method achieves superior functional registration performance, compared with conventional registration methods. © 2018 Wiley Periodicals, Inc.

Effects of different correlation metrics and preprocessing factors on small-world brain functional networks: a resting-state functional MRI study.

PubMed

Liang, Xia; Wang, Jinhui; Yan, Chaogan; Shu, Ni; Xu, Ke; Gong, Gaolang; He, Yong

2012-01-01

Graph theoretical analysis of brain networks based on resting-state functional MRI (R-fMRI) has attracted a great deal of attention in recent years. These analyses often involve the selection of correlation metrics and specific preprocessing steps. However, the influence of these factors on the topological properties of functional brain networks has not been systematically examined. Here, we investigated the influences of correlation metric choice (Pearson's correlation versus partial correlation), global signal presence (regressed or not) and frequency band selection [slow-5 (0.01-0.027 Hz) versus slow-4 (0.027-0.073 Hz)] on the topological properties of both binary and weighted brain networks derived from them, and we employed test-retest (TRT) analyses for further guidance on how to choose the "best" network modeling strategy from the reliability perspective. Our results show significant differences in global network metrics associated with both correlation metrics and global signals. Analysis of nodal degree revealed differing hub distributions for brain networks derived from Pearson's correlation versus partial correlation. TRT analysis revealed that the reliability of both global and local topological properties are modulated by correlation metrics and the global signal, with the highest reliability observed for Pearson's-correlation-based brain networks without global signal removal (WOGR-PEAR). The nodal reliability exhibited a spatially heterogeneous distribution wherein regions in association and limbic/paralimbic cortices showed moderate TRT reliability in Pearson's-correlation-based brain networks. Moreover, we found that there were significant frequency-related differences in topological properties of WOGR-PEAR networks, and brain networks derived in the 0.027-0.073 Hz band exhibited greater reliability than those in the 0.01-0.027 Hz band. Taken together, our results provide direct evidence regarding the influences of correlation metrics and specific preprocessing choices on both the global and nodal topological properties of functional brain networks. This study also has important implications for how to choose reliable analytical schemes in brain network studies.

Constructing fine-granularity functional brain network atlases via deep convolutional autoencoder.

PubMed

Zhao, Yu; Dong, Qinglin; Chen, Hanbo; Iraji, Armin; Li, Yujie; Makkie, Milad; Kou, Zhifeng; Liu, Tianming

2017-12-01

State-of-the-art functional brain network reconstruction methods such as independent component analysis (ICA) or sparse coding of whole-brain fMRI data can effectively infer many thousands of volumetric brain network maps from a large number of human brains. However, due to the variability of individual brain networks and the large scale of such networks needed for statistically meaningful group-level analysis, it is still a challenging and open problem to derive group-wise common networks as network atlases. Inspired by the superior spatial pattern description ability of the deep convolutional neural networks (CNNs), a novel deep 3D convolutional autoencoder (CAE) network is designed here to extract spatial brain network features effectively, based on which an Apache Spark enabled computational framework is developed for fast clustering of larger number of network maps into fine-granularity atlases. To evaluate this framework, 10 resting state networks (RSNs) were manually labeled from the sparsely decomposed networks of Human Connectome Project (HCP) fMRI data and 5275 network training samples were obtained, in total. Then the deep CAE models are trained by these functional networks' spatial maps, and the learned features are used to refine the original 10 RSNs into 17 network atlases that possess fine-granularity functional network patterns. Interestingly, it turned out that some manually mislabeled outliers in training networks can be corrected by the deep CAE derived features. More importantly, fine granularities of networks can be identified and they reveal unique network patterns specific to different brain task states. By further applying this method to a dataset of mild traumatic brain injury study, it shows that the technique can effectively identify abnormal small networks in brain injury patients in comparison with controls. In general, our work presents a promising deep learning and big data analysis solution for modeling functional connectomes, with fine granularities, based on fMRI data. Copyright © 2017 Elsevier B.V. All rights reserved.

Reconstruction of human brain spontaneous activity based on frequency-pattern analysis of magnetoencephalography data

PubMed Central

Llinás, Rodolfo R.; Ustinin, Mikhail N.; Rykunov, Stanislav D.; Boyko, Anna I.; Sychev, Vyacheslav V.; Walton, Kerry D.; Rabello, Guilherme M.; Garcia, John

2015-01-01

A new method for the analysis and localization of brain activity has been developed, based on multichannel magnetic field recordings, over minutes, superimposed on the MRI of the individual. Here, a high resolution Fourier Transform is obtained over the entire recording period, leading to a detailed multi-frequency spectrum. Further analysis implements a total decomposition of the frequency components into functionally invariant entities, each having an invariant field pattern localizable in recording space. The method, addressed as functional tomography, makes it possible to find the distribution of magnetic field sources in space. Here, the method is applied to the analysis of simulated data, to oscillating signals activating a physical current dipoles phantom, and to recordings of spontaneous brain activity in 10 healthy adults. In the analysis of simulated data, 61 dipoles are localized with 0.7 mm precision. Concerning the physical phantom the method is able to localize three simultaneously activated current dipoles with 1 mm precision. Spatial resolution 3 mm was attained when localizing spontaneous alpha rhythm activity in 10 healthy adults, where the alpha peak was specified for each subject individually. Co-registration of the functional tomograms with each subject's head MRI localized alpha range activity to the occipital and/or posterior parietal brain region. This is the first application of this new functional tomography to human brain activity. The method successfully provides an overall view of brain electrical activity, a detailed spectral description and, combined with MRI, the localization of sources in anatomical brain space. PMID:26528119

An fMRI study of emotional face processing in adolescent major depression.

PubMed

Hall, Leah M J; Klimes-Dougan, Bonnie; Hunt, Ruskin H; Thomas, Kathleen M; Houri, Alaa; Noack, Emily; Mueller, Bryon A; Lim, Kelvin O; Cullen, Kathryn R

2014-10-01

Major depressive disorder (MDD) often begins during adolescence when the brain is still maturing. To better understand the neurobiological underpinnings of MDD early in development, this study examined brain function in response to emotional faces in adolescents with MDD and healthy (HC) adolescents using functional magnetic resonance imaging (fMRI). Thirty-two unmedicated adolescents with MDD and 23 healthy age- and gender-matched controls completed an fMRI task viewing happy and fearful faces. Fronto-limbic regions of interest (ROI; bilateral amygdala, insula, subgenual and rostral anterior cingulate cortices) and whole-brain analyses were conducted to examine between-group differences in brain function. ROI analyses revealed that patients had greater bilateral amygdala activity than HC in response to viewing fearful versus happy faces, which remained significant when controlling for comorbid anxiety. Whole-brain analyses revealed that adolescents with MDD had lower activation compared to HC in a right hemisphere cluster comprised of the insula, superior/middle temporal gyrus, and Heschl׳s gyrus when viewing fearful faces. Brain activity in the subgenual anterior cingulate cortex was inversely correlated with depression severity. Limitations include a cross-sectional design with a modest sample size and use of a limited range of emotional stimuli. Results replicate previous studies that suggest emotion processing in adolescent MDD is associated with abnormalities within fronto-limbic brain regions. Findings implicate elevated amygdalar arousal to negative stimuli in adolescents with depression and provide new evidence for a deficit in functioning of the saliency network, which may be a future target for early intervention and MDD treatment. Copyright © 2014 Elsevier B.V. All rights reserved.

[Resting-state functional magnetic resonance study of brain function changes after TIPS operation in patients with liver cirrhosis].

PubMed

Liu, C; Wang, H B; Yu, Y Q; Wang, M Q; Zhang, G B; Xu, L Y; Wu, J M

2016-12-20

Objective: To investigate the brain function changes in cirrhosis patients after transjugular intrahepatic portosystemic shunt (TIPS), resting-state functional MRI (rs-fMRI) performed and fractional amplitude of low frequency fluctuation (fALFF) was analyzed. Methods: From January 2014 to February 2016, a total of 96 cirrhotic patients from invasive technology department and infection department in the First Affiliated Hospital of Anhui Medical University were selected , the blood ammonia data of 96 cirrhotic patients with TIPS operation in four groups were collected after 1, 3, 6 and 12 month, and all subjects performed rs-fMRI scans. The rs-fMRI data processed with DPARSF and SPM12 softwares, whole-brain fALFF values were calculated, and One-Way analysis of variance , multiple comparison analysis and correlation analysis were performed. Results: There were brain regions with significant function changes in four groups patients with TIPS operation after 1, 3, 6 and 12 month, including bilateral superior temporal gyrus, right middle temportal gyrus , right hippocampus, right island of inferior frontal gyrus, left fusiform gyrus, left olfactory cortex, left orbital superior frontal gyrus (all P <0.005). Multiple comparison analysis showed that compared with patients in the 1-month follow-up, patients in the 3-month follow-up showed that brain function areas increased in left olfactory cortex, left inferior temporal gyrus, left fusiform gyrus, left orbital middle frontal gyrus, left putamen, left cerebelum, and decreased in left lingual gyrus; patients in the 6-month follow-up showed that brain function areas increased in left middle temportal gyrus, right supramarginal gyrus, right temporal pole, right central operculum, and decreased in left top edge of angular gyrus, left postcentral gyrus; patients in the 12-month follow-up showed that brain function areas increased in right hippocampus, right middle cingulate gyrus, and decreased in right middle temportal gyrus.Compared with patients in the 3-month follow-up, patients in the 6-month follow-up showed that brain function areas increased in left superior temporal gyrus, left middle temporal gyrus, right temporal pole, right island of inferior frontal gyrus, and decreased in left cerebelum, left orbital inferior frontal gyrus; patients in the 12-month follow-up showed that there were no obvious increase and decrease brain function areas.Compared with patients in the 6-month follow-up, patients in the 12-month follow-up showed that there were no obvious increase brain function areas , but brain function areas decreased in bilateral middle temportal gyrus( P <0.001). Brain regions were positively related to blood ammonia in right middle cingulate gyrus, right central operculum, left parahippocampal gyrus, while as brain regions were negatively related to blood ammonia in bilateral medial prefrontal lobe, anterior cingulate and paracingulate gyrus, right top edge of angular gyrus, right middle temportal gyrus, left anterior central gyrus, left posterior central gyrus (all P <0.005). Conclusion: The resting state brain function increased or decreased with course of disease in cirrhosis patients after TIPS operation. The brain activity of limbic system and sensorimotor system all had significant correlation with blood ammonia levels. The blood ammonia level and the function of relative brain regions after 6-month with TIPS operation can be gradually improved.

Cerebral microbleeds, cognitive impairment, and MRI in patients with diabetes mellitus.

PubMed

Zhou, Hong; Yang, Juan; Xie, Peihan; Dong, Yulan; You, Yong; Liu, Jincai

2017-07-01

Cerebral microbleeds (CMBs), a typical imaging manifestation marker of sporadic cerebral small vessel disease, play a critical role in vascular cognitive impairment, which is often accompanied by diabetes mellitus (DM). Hence, CMBs may, in part, be responsible for the occurrence and development of cognitive impairment in patients with diabetes. Novel magnetic resonance imaging (MRI) sequences, such as susceptibility-weighted imaging and T2*-weighted gradient-echo, have the capability of noninvasively revealing CMBs in the brain. Moreover, a correlation between CMBs and cognitive impairment in patients with diabetes has been suggested in applications of functional MRI (fMRI). Since pathological changes in the brain occur prior to observable decline in cognitive function, neuroimaging may help predict the progression of cognitive impairment in diabetic patients. In this article, we review the detection of CMBs using MRI in diabetic patients exhibiting cognitive impairment. Future studies should emphasize the development and establishment of a novel MRI protocol, including fMRI, for diabetic patients with cognitive impairment to detect CMBs. A reliable MRI protocol would also be helpful in understanding the pathological mechanisms of cognitive impairment in this important patient population. Copyright © 2017. Published by Elsevier B.V.

An Evolutionary Game Theory Model of Spontaneous Brain Functioning.

PubMed

Madeo, Dario; Talarico, Agostino; Pascual-Leone, Alvaro; Mocenni, Chiara; Santarnecchi, Emiliano

2017-11-22

Our brain is a complex system of interconnected regions spontaneously organized into distinct networks. The integration of information between and within these networks is a continuous process that can be observed even when the brain is at rest, i.e. not engaged in any particular task. Moreover, such spontaneous dynamics show predictive value over individual cognitive profile and constitute a potential marker in neurological and psychiatric conditions, making its understanding of fundamental importance in modern neuroscience. Here we present a theoretical and mathematical model based on an extension of evolutionary game theory on networks (EGN), able to capture brain's interregional dynamics by balancing emulative and non-emulative attitudes among brain regions. This results in the net behavior of nodes composing resting-state networks identified using functional magnetic resonance imaging (fMRI), determining their moment-to-moment level of activation and inhibition as expressed by positive and negative shifts in BOLD fMRI signal. By spontaneously generating low-frequency oscillatory behaviors, the EGN model is able to mimic functional connectivity dynamics, approximate fMRI time series on the basis of initial subset of available data, as well as simulate the impact of network lesions and provide evidence of compensation mechanisms across networks. Results suggest evolutionary game theory on networks as a new potential framework for the understanding of human brain network dynamics.

The Autism Brain Imaging Data Exchange: Towards Large-Scale Evaluation of the Intrinsic Brain Architecture in Autism

PubMed Central

Di Martino, Adriana; Yan, Chao-Gan; Li, Qingyang; Denio, Erin; Castellanos, Francisco X.; Alaerts, Kaat; Anderson, Jeffrey S.; Assaf, Michal; Bookheimer, Susan Y.; Dapretto, Mirella; Deen, Ben; Delmonte, Sonja; Dinstein, Ilan; Ertl-Wagner, Birgit; Fair, Damien A.; Gallagher, Louise; Kennedy, Daniel P.; Keown, Christopher L.; Keysers, Christian; Lainhart, Janet E.; Lord, Catherine; Luna, Beatriz; Menon, Vinod; Minshew, Nancy; Monk, Christopher S.; Mueller, Sophia; Müller, Ralph-Axel; Nebel, Mary Beth; Nigg, Joel T.; O’Hearn, Kirsten; Pelphrey, Kevin A.; Peltier, Scott J.; Rudie, Jeffrey D.; Sunaert, Stefan; Thioux, Marc; Tyszka, J. Michael; Uddin, Lucina Q.; Verhoeven, Judith S.; Wenderoth, Nicole; Wiggins, Jillian L.; Mostofsky, Stewart H.; Milham, Michael P.

2014-01-01

Autism spectrum disorders (ASD) represent a formidable challenge for psychiatry and neuroscience because of their high prevalence, life-long nature, complexity and substantial heterogeneity. Facing these obstacles requires large-scale multidisciplinary efforts. While the field of genetics has pioneered data sharing for these reasons, neuroimaging had not kept pace. In response, we introduce the Autism Brain Imaging Data Exchange (ABIDE) – a grassroots consortium aggregating and openly sharing 1112 existing resting-state functional magnetic resonance imaging (R-fMRI) datasets with corresponding structural MRI and phenotypic information from 539 individuals with ASD and 573 age-matched typical controls (TC; 7–64 years) (http://fcon_1000.projects.nitrc.org/indi/abide/). Here, we present this resource and demonstrate its suitability for advancing knowledge of ASD neurobiology based on analyses of 360 males with ASD and 403 male age-matched TC. We focused on whole-brain intrinsic functional connectivity and also survey a range of voxel-wise measures of intrinsic functional brain architecture. Whole-brain analyses reconciled seemingly disparate themes of both hypo and hyperconnectivity in the ASD literature; both were detected, though hypoconnectivity dominated, particularly for cortico-cortical and interhemispheric functional connectivity. Exploratory analyses using an array of regional metrics of intrinsic brain function converged on common loci of dysfunction in ASD (mid and posterior insula, posterior cingulate cortex), and highlighted less commonly explored regions such as thalamus. The survey of the ABIDE R-fMRI datasets provides unprecedented demonstrations of both replication and novel discovery. By pooling multiple international datasets, ABIDE is expected to accelerate the pace of discovery setting the stage for the next generation of ASD studies. PMID:23774715

Automatic recognition of holistic functional brain networks using iteratively optimized convolutional neural networks (IO-CNN) with weak label initialization.

PubMed

Zhao, Yu; Ge, Fangfei; Liu, Tianming

2018-07-01

fMRI data decomposition techniques have advanced significantly from shallow models such as Independent Component Analysis (ICA) and Sparse Coding and Dictionary Learning (SCDL) to deep learning models such Deep Belief Networks (DBN) and Convolutional Autoencoder (DCAE). However, interpretations of those decomposed networks are still open questions due to the lack of functional brain atlases, no correspondence across decomposed or reconstructed networks across different subjects, and significant individual variabilities. Recent studies showed that deep learning, especially deep convolutional neural networks (CNN), has extraordinary ability of accommodating spatial object patterns, e.g., our recent works using 3D CNN for fMRI-derived network classifications achieved high accuracy with a remarkable tolerance for mistakenly labelled training brain networks. However, the training data preparation is one of the biggest obstacles in these supervised deep learning models for functional brain network map recognitions, since manual labelling requires tedious and time-consuming labours which will sometimes even introduce label mistakes. Especially for mapping functional networks in large scale datasets such as hundreds of thousands of brain networks used in this paper, the manual labelling method will become almost infeasible. In response, in this work, we tackled both the network recognition and training data labelling tasks by proposing a new iteratively optimized deep learning CNN (IO-CNN) framework with an automatic weak label initialization, which enables the functional brain networks recognition task to a fully automatic large-scale classification procedure. Our extensive experiments based on ABIDE-II 1099 brains' fMRI data showed the great promise of our IO-CNN framework. Copyright © 2018 Elsevier B.V. All rights reserved.

The autism brain imaging data exchange: towards a large-scale evaluation of the intrinsic brain architecture in autism.

PubMed

Di Martino, A; Yan, C-G; Li, Q; Denio, E; Castellanos, F X; Alaerts, K; Anderson, J S; Assaf, M; Bookheimer, S Y; Dapretto, M; Deen, B; Delmonte, S; Dinstein, I; Ertl-Wagner, B; Fair, D A; Gallagher, L; Kennedy, D P; Keown, C L; Keysers, C; Lainhart, J E; Lord, C; Luna, B; Menon, V; Minshew, N J; Monk, C S; Mueller, S; Müller, R-A; Nebel, M B; Nigg, J T; O'Hearn, K; Pelphrey, K A; Peltier, S J; Rudie, J D; Sunaert, S; Thioux, M; Tyszka, J M; Uddin, L Q; Verhoeven, J S; Wenderoth, N; Wiggins, J L; Mostofsky, S H; Milham, M P

2014-06-01

Autism spectrum disorders (ASDs) represent a formidable challenge for psychiatry and neuroscience because of their high prevalence, lifelong nature, complexity and substantial heterogeneity. Facing these obstacles requires large-scale multidisciplinary efforts. Although the field of genetics has pioneered data sharing for these reasons, neuroimaging had not kept pace. In response, we introduce the Autism Brain Imaging Data Exchange (ABIDE)-a grassroots consortium aggregating and openly sharing 1112 existing resting-state functional magnetic resonance imaging (R-fMRI) data sets with corresponding structural MRI and phenotypic information from 539 individuals with ASDs and 573 age-matched typical controls (TCs; 7-64 years) (http://fcon_1000.projects.nitrc.org/indi/abide/). Here, we present this resource and demonstrate its suitability for advancing knowledge of ASD neurobiology based on analyses of 360 male subjects with ASDs and 403 male age-matched TCs. We focused on whole-brain intrinsic functional connectivity and also survey a range of voxel-wise measures of intrinsic functional brain architecture. Whole-brain analyses reconciled seemingly disparate themes of both hypo- and hyperconnectivity in the ASD literature; both were detected, although hypoconnectivity dominated, particularly for corticocortical and interhemispheric functional connectivity. Exploratory analyses using an array of regional metrics of intrinsic brain function converged on common loci of dysfunction in ASDs (mid- and posterior insula and posterior cingulate cortex), and highlighted less commonly explored regions such as the thalamus. The survey of the ABIDE R-fMRI data sets provides unprecedented demonstrations of both replication and novel discovery. By pooling multiple international data sets, ABIDE is expected to accelerate the pace of discovery setting the stage for the next generation of ASD studies.

Effect of Observation of Simple Hand Movement on Brain Activations in Patients with Unilateral Cerebral Palsy: An fMRI Study

ERIC Educational Resources Information Center

Dinomais, Mickael; Lignon, Gregoire; Chinier, Eva; Richard, Isabelle; Minassian, Aram Ter; The Tich, Sylvie N'Guyen

2013-01-01

The aim of this functional magnetic resonance imaging (fMRI) study was to examine and compare brain activation in patients with unilateral cerebral palsy (CP) during observation of simple hand movement performed by the paretic and nonparetic hand. Nineteen patients with clinical unilateral CP (14 male, mean age 14 years, 7-21 years) participated…

Continuous blood pressure recordings simultaneously with functional brain imaging: studies of the glymphatic system

NASA Astrophysics Data System (ADS)

Zienkiewicz, Aleksandra; Huotari, Niko; Raitamaa, Lauri; Raatikainen, Ville; Ferdinando, Hany; Vihriälä, Erkki; Korhonen, Vesa; Myllylä, Teemu; Kiviniemi, Vesa

2017-03-01

The lymph system is responsible for cleaning the tissues of metabolic waste products, soluble proteins and other harmful fluids etc. Lymph flow in the body is driven by body movements and muscle contractions. Moreover, it is indirectly dependent on the cardiovascular system, where the heart beat and blood pressure maintain force of pressure in lymphatic channels. Over the last few years, studies revealed that the brain contains the so-called glymphatic system, which is the counterpart of the systemic lymphatic system in the brain. Similarly, the flow in the glymphatic system is assumed to be mostly driven by physiological pulsations such as cardiovascular pulses. Thus, continuous measurement of blood pressure and heart function simultaneously with functional brain imaging is of great interest, particularly in studies of the glymphatic system. We present our MRI compatible optics based sensing system for continuous blood pressure measurement and show our current results on the effects of blood pressure variations on cerebral brain dynamics, with a focus on the glymphatic system. Blood pressure was measured simultaneously with near-infrared spectroscopy (NIRS) combined with an ultrafast functional brain imaging (fMRI) sequence magnetic resonance encephalography (MREG, 3D brain 10 Hz sampling rate).

Biology and therapy of fibromyalgia. Functional magnetic resonance imaging findings in fibromyalgia

PubMed Central

Williams, David A; Gracely, Richard H

2006-01-01

Techniques in neuroimaging such as functional magnetic resonance imaging (fMRI) have helped to provide insights into the role of supraspinal mechanisms in pain perception. This review focuses on studies that have applied fMRI in an attempt to gain a better understanding of the mechanisms involved in the processing of pain associated with fibromyalgia. This article provides an overview of the nociceptive system as it functions normally, reviews functional brain imaging methods, and integrates the existing literature utilizing fMRI to study central pain mechanisms in fibromyalgia. PMID:17254318

Functional Magnetic Resonance Imaging for Preoperative Planning in Brain Tumour Surgery.

PubMed

Lau, Jonathan C; Kosteniuk, Suzanne E; Bihari, Frank; Megyesi, Joseph F

2017-01-01

Functional magnetic resonance imaging (fMRI) is being increasingly used for the preoperative evaluation of patients with brain tumours. The study is a retrospective chart review investigating the use of clinical fMRI from 2002 through 2013 in the preoperative evaluation of brain tumour patients. Baseline demographic and clinical data were collected. The specific fMRI protocols used for each patient were recorded. Sixty patients were identified over the 12-year period. The tumour types most commonly investigated were high-grade glioma (World Health Organization grade III or IV), low-grade glioma (World Health Organization grade II), and meningioma. Most common presenting symptoms were seizures (69.6%), language deficits (23.2%), and headache (19.6%). There was a predominance of left hemispheric lesions investigated with fMRI (76.8% vs 23.2% for right). The most commonly involved lobes were frontal (64.3%), temporal (33.9%), parietal (21.4%), and insular (7.1%). The most common fMRI paradigms were language (83.9%), motor (75.0%), sensory (16.1%), and memory (10.7%). The majority of patients ultimately underwent a craniotomy (75.0%), whereas smaller groups underwent stereotactic biopsy (8.9%) and nonsurgical management (16.1%). Time from request for fMRI to actual fMRI acquisition was 3.1±2.3 weeks. Time from fMRI acquisition to intervention was 4.9±5.5 weeks. We have characterized patient demographics in a retrospective single-surgeon cohort undergoing preoperative clinical fMRI at a Canadian centre. Our experience suggests an acceptable wait time from scan request to scan completion/analysis and from scan to intervention.

Connectivity-based neurofeedback: Dynamic causal modeling for real-time fMRI☆

PubMed Central

Koush, Yury; Rosa, Maria Joao; Robineau, Fabien; Heinen, Klaartje; W. Rieger, Sebastian; Weiskopf, Nikolaus; Vuilleumier, Patrik; Van De Ville, Dimitri; Scharnowski, Frank

2013-01-01

Neurofeedback based on real-time fMRI is an emerging technique that can be used to train voluntary control of brain activity. Such brain training has been shown to lead to behavioral effects that are specific to the functional role of the targeted brain area. However, real-time fMRI-based neurofeedback so far was limited to mainly training localized brain activity within a region of interest. Here, we overcome this limitation by presenting near real-time dynamic causal modeling in order to provide feedback information based on connectivity between brain areas rather than activity within a single brain area. Using a visual–spatial attention paradigm, we show that participants can voluntarily control a feedback signal that is based on the Bayesian model comparison between two predefined model alternatives, i.e. the connectivity between left visual cortex and left parietal cortex vs. the connectivity between right visual cortex and right parietal cortex. Our new approach thus allows for training voluntary control over specific functional brain networks. Because most mental functions and most neurological disorders are associated with network activity rather than with activity in a single brain region, this novel approach is an important methodological innovation in order to more directly target functionally relevant brain networks. PMID:23668967

Network analysis of EEG related functional MRI changes due to medication withdrawal in focal epilepsy

PubMed Central

Hermans, Kees; Ossenblok, Pauly; van Houdt, Petra; Geerts, Liesbeth; Verdaasdonk, Rudolf; Boon, Paul; Colon, Albert; de Munck, Jan C.

2015-01-01

Anti-epileptic drugs (AEDs) have a global effect on the neurophysiology of the brain which is most likely reflected in functional brain activity recorded with EEG and fMRI. These effects may cause substantial inter-subject variability in studies where EEG correlated functional MRI (EEG–fMRI) is used to determine the epileptogenic zone in patients who are candidate for epilepsy surgery. In the present study the effects on resting state fMRI are quantified in conditions with AED administration and after withdrawal of AEDs. EEG–fMRI data were obtained from 10 patients in the condition that the patient was on the steady-state maintenance doses of AEDs as prescribed (condition A) and after withdrawal of AEDs (condition B), at the end of a clinically standard pre-surgical long term video-EEG monitoring session. Resting state networks (RSN) were extracted from fMRI. The epileptic component (ICE) was identified by selecting the RSN component with the largest overlap with the EEG–fMRI correlation pattern. Changes in RSN functional connectivity between conditions A and B were quantified. EEG–fMRI correlation analysis was successful in 30% and 100% of the cases in conditions A and B, respectively. Spatial patterns of ICEs are comparable in conditions A and B, except for one patient for whom it was not possible to identify the ICE in condition A. However, the resting state functional connectivity is significantly increased in the condition after withdrawal of AEDs (condition B), which makes resting state fMRI potentially a new tool to study AED effects. The difference in sensitivity of EEG–fMRI in conditions A and B, which is not related to the number of epileptic EEG events occurring during scanning, could be related to the increased functional connectivity in condition B. PMID:26137444

Moment-to-Moment BOLD Signal Variability Reflects Regional Changes in Neural Flexibility across the Lifespan.

PubMed

Nomi, Jason S; Bolt, Taylor S; Ezie, C E Chiemeka; Uddin, Lucina Q; Heller, Aaron S

2017-05-31

Variability of neuronal responses is thought to underlie flexible and optimal brain function. Because previous work investigating BOLD signal variability has been conducted within task-based fMRI contexts on adults and older individuals, very little is currently known regarding regional changes in spontaneous BOLD signal variability in the human brain across the lifespan. The current study used resting-state fMRI data from a large sample of male and female human participants covering a wide age range (6-85 years) across two different fMRI acquisition parameters (TR = 0.645 and 1.4 s). Variability in brain regions including a key node of the salience network (anterior insula) increased linearly across the lifespan across datasets. In contrast, variability in most other large-scale networks decreased linearly over the lifespan. These results demonstrate unique lifespan trajectories of BOLD variability related to specific regions of the brain and add to a growing literature demonstrating the importance of identifying normative trajectories of functional brain maturation. SIGNIFICANCE STATEMENT Although brain signal variability has traditionally been considered a source of unwanted noise, recent work demonstrates that variability in brain signals during task performance is related to brain maturation in old age as well as individual differences in behavioral performance. The current results demonstrate that intrinsic fluctuations in resting-state variability exhibit unique maturation trajectories in specific brain regions and systems, particularly those supporting salience detection. These results have implications for investigations of brain development and aging, as well as interpretations of brain function underlying behavioral changes across the lifespan. Copyright © 2017 the authors 0270-6474/17/375539-10$15.00/0.

Dynamic brain glucose metabolism identifies anti-correlated cortical-cerebellar networks at rest.

PubMed

Tomasi, Dardo G; Shokri-Kojori, Ehsan; Wiers, Corinde E; Kim, Sunny W; Demiral, Şukru B; Cabrera, Elizabeth A; Lindgren, Elsa; Miller, Gregg; Wang, Gene-Jack; Volkow, Nora D

2017-12-01

It remains unclear whether resting state functional magnetic resonance imaging (rfMRI) networks are associated with underlying synchrony in energy demand, as measured by dynamic 2-deoxy-2-[ 18 F]fluoroglucose (FDG) positron emission tomography (PET). We measured absolute glucose metabolism, temporal metabolic connectivity (t-MC) and rfMRI patterns in 53 healthy participants at rest. Twenty-two rfMRI networks emerged from group independent component analysis (gICA). In contrast, only two anti-correlated t-MC emerged from FDG-PET time series using gICA or seed-voxel correlations; one included frontal, parietal and temporal cortices, the other included the cerebellum and medial temporal regions. Whereas cerebellum, thalamus, globus pallidus and calcarine cortex arose as the strongest t-MC hubs, the precuneus and visual cortex arose as the strongest rfMRI hubs. The strength of the t-MC linearly increased with the metabolic rate of glucose suggesting that t-MC measures are strongly associated with the energy demand of the brain tissue, and could reflect regional differences in glucose metabolism, counterbalanced metabolic network demand, and/or differential time-varying delivery of FDG. The mismatch between metabolic and functional connectivity patterns computed as a function of time could reflect differences in the temporal characteristics of glucose metabolism as measured with PET-FDG and brain activation as measured with rfMRI.

Voxel-wise motion artifacts in population-level whole-brain connectivity analysis of resting-state FMRI.

PubMed

Spisák, Tamás; Jakab, András; Kis, Sándor A; Opposits, Gábor; Aranyi, Csaba; Berényi, Ervin; Emri, Miklós

2014-01-01

Functional Magnetic Resonance Imaging (fMRI) based brain connectivity analysis maps the functional networks of the brain by estimating the degree of synchronous neuronal activity between brain regions. Recent studies have demonstrated that "resting-state" fMRI-based brain connectivity conclusions may be erroneous when motion artifacts have a differential effect on fMRI BOLD signals for between group comparisons. A potential explanation could be that in-scanner displacement, due to rotational components, is not spatially constant in the whole brain. However, this localized nature of motion artifacts is poorly understood and is rarely considered in brain connectivity studies. In this study, we initially demonstrate the local correspondence between head displacement and the changes in the resting-state fMRI BOLD signal. Than, we investigate how connectivity strength is affected by the population-level variation in the spatial pattern of regional displacement. We introduce Regional Displacement Interaction (RDI), a new covariate parameter set for second-level connectivity analysis and demonstrate its effectiveness in reducing motion related confounds in comparisons of groups with different voxel-vise displacement pattern and preprocessed using various nuisance regression methods. The effect of using RDI as second-level covariate is than demonstrated in autism-related group comparisons. The relationship between the proposed method and some of the prevailing subject-level nuisance regression techniques is evaluated. Our results show that, depending on experimental design, treating in-scanner head motion as a global confound may not be appropriate. The degree of displacement is highly variable among various brain regions, both within and between subjects. These regional differences bias correlation-based measures of brain connectivity. The inclusion of the proposed second-level covariate into the analysis successfully reduces artifactual motion-related group differences and preserves real neuronal differences, as demonstrated by the autism-related comparisons.

Quantitative representations of an exaggerated anxiety response in the brain of female spider phobics-a parametric fMRI study.

PubMed

Zilverstand, Anna; Sorger, Bettina; Kaemingk, Anita; Goebel, Rainer

2017-06-01

We employed a novel parametric spider picture set in the context of a parametric fMRI anxiety provocation study, designed to tease apart brain regions involved in threat monitoring from regions representing an exaggerated anxiety response in spider phobics. For the stimulus set, we systematically manipulated perceived proximity of threat by varying a depicted spider's context, size, and posture. All stimuli were validated in a behavioral rating study (phobics n = 20; controls n = 20; all female). An independent group participated in a subsequent fMRI anxiety provocation study (phobics n = 7; controls n = 7; all female), in which we compared a whole-brain categorical to a whole-brain parametric analysis. Results demonstrated that the parametric analysis provided a richer characterization of the functional role of the involved brain networks. In three brain regions-the mid insula, the dorsal anterior cingulate, and the ventrolateral prefrontal cortex-activation was linearly modulated by perceived proximity specifically in the spider phobia group, indicating a quantitative representation of an exaggerated anxiety response. In other regions (e.g., the amygdala), activation was linearly modulated in both groups, suggesting a functional role in threat monitoring. Prefrontal regions, such as dorsolateral prefrontal cortex, were activated during anxiety provocation but did not show a stimulus-dependent linear modulation in either group. The results confirm that brain regions involved in anxiety processing hold a quantitative representation of a pathological anxiety response and more generally suggest that parametric fMRI designs may be a very powerful tool for clinical research in the future, particularly when developing novel brain-based interventions (e.g., neurofeedback training). Hum Brain Mapp 38:3025-3038, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Extraction of dynamic functional connectivity from brain grey matter and white matter for MCI classification.

PubMed

Chen, Xiaobo; Zhang, Han; Zhang, Lichi; Shen, Celina; Lee, Seong-Whan; Shen, Dinggang

2017-10-01

Brain functional connectivity (FC) extracted from resting-state fMRI (RS-fMRI) has become a popular approach for diagnosing various neurodegenerative diseases, including Alzheimer's disease (AD) and its prodromal stage, mild cognitive impairment (MCI). Current studies mainly construct the FC networks between grey matter (GM) regions of the brain based on temporal co-variations of the blood oxygenation level-dependent (BOLD) signals, which reflects the synchronized neural activities. However, it was rarely investigated whether the FC detected within the white matter (WM) could provide useful information for diagnosis. Motivated by the recently proposed functional correlation tensors (FCT) computed from RS-fMRI and used to characterize the structured pattern of local FC in the WM, we propose in this article a novel MCI classification method based on the information conveyed by both the FC between the GM regions and that within the WM regions. Specifically, in the WM, the tensor-based metrics (e.g., fractional anisotropy [FA], similar to the metric calculated based on diffusion tensor imaging [DTI]) are first calculated based on the FCT and then summarized along each of the major WM fiber tracts connecting each pair of the brain GM regions. This could capture the functional information in the WM, in a similar network structure as the FC network constructed for the GM, based only on the same RS-fMRI data. Moreover, a sliding window approach is further used to partition the voxel-wise BOLD signal into multiple short overlapping segments. Then, both the FC and FCT between each pair of the brain regions can be calculated based on the BOLD signal segments in the GM and WM, respectively. In such a way, our method can generate dynamic FC and dynamic FCT to better capture functional information in both GM and WM and further integrate them together by using our developed feature extraction, selection, and ensemble learning algorithms. The experimental results verify that the dynamic FCT can provide valuable functional information in the WM; by combining it with the dynamic FC in the GM, the diagnosis accuracy for MCI subjects can be significantly improved even using RS-fMRI data alone. Hum Brain Mapp 38:5019-5034, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Glucose administration enhances fMRI brain activation and connectivity related to episodic memory encoding for neutral and emotional stimuli.

PubMed

Parent, Marise B; Krebs-Kraft, Desiree L; Ryan, John P; Wilson, Jennifer S; Harenski, Carla; Hamann, Stephan

2011-04-01

Glucose enhances memory in a variety of species. In humans, glucose administration enhances episodic memory encoding, although little is known regarding the neural mechanisms underlying these effects. Here we examined whether elevating blood glucose would enhance functional MRI (fMRI) activation and connectivity in brain regions associated with episodic memory encoding and whether these effects would differ depending on the emotional valence of the material. We used a double-blind, within-participants, crossover design in which either glucose (50g) or a saccharin placebo were administered before scanning, on days approximately 1 week apart. We scanned healthy young male participants with fMRI as they viewed emotionally arousing negative pictures and emotionally neutral pictures, intermixed with baseline fixation. Free recall was tested at 5 min after scanning and again after 1 day. Glucose administration increased activation in brain regions associated with successful episodic memory encoding. Glucose also enhanced activation in regions whose activity was correlated with subsequent successful recall, including the hippocampus, prefrontal cortex, and other regions, and these effects differed for negative vs. neutral stimuli. Finally, glucose substantially increased functional connectivity between the hippocampus and amygdala and a network of regions previously implicated in successful episodic memory encoding. These findings fit with evidence from nonhuman animals indicating glucose modulates memory by selectively enhancing neural activity in brain regions engaged during memory tasks. Our results highlight the modulatory effects of glucose and the importance of examining both regional changes in activity and functional connectivity to fully characterize the effects of glucose on brain function and memory. Copyright © 2011 Elsevier Ltd. All rights reserved.

Increased brain connectivity and activation after cognitive rehabilitation in Parkinson's disease: a randomized controlled trial.

PubMed

Díez-Cirarda, María; Ojeda, Natalia; Peña, Javier; Cabrera-Zubizarreta, Alberto; Lucas-Jiménez, Olaia; Gómez-Esteban, Juan Carlos; Gómez-Beldarrain, Maria Ángeles; Ibarretxe-Bilbao, Naroa

2017-12-01

Cognitive rehabilitation programs have demonstrated efficacy in improving cognitive functions in Parkinson's disease (PD), but little is known about cerebral changes associated with an integrative cognitive rehabilitation in PD. To assess structural and functional cerebral changes in PD patients, after attending a three-month integrative cognitive rehabilitation program (REHACOP). Forty-four PD patients were randomly divided into REHACOP group (cognitive rehabilitation) and a control group (occupational therapy). T1-weighted, diffusion weighted and functional magnetic resonance images (fMRI) during resting-state and during a memory paradigm (with learning and recognition tasks) were acquired at pre-treatment and post-treatment. Cerebral changes were assessed with repeated measures ANOVA 2 × 2 for group x time interaction. During resting-state fMRI, the REHACOP group showed significantly increased brain connectivity between the left inferior temporal lobe and the bilateral dorsolateral prefrontal cortex compared to the control group. Moreover, during the recognition fMRI task, the REHACOP group showed significantly increased brain activation in the left middle temporal area compared to the control group. During the learning fMRI task, the REHACOP group showed increased brain activation in the left inferior frontal lobe at post-treatment compared to pre-treatment. No significant structural changes were found between pre- and post-treatment. Finally, the REHACOP group showed significant and positive correlations between the brain connectivity and activation and the cognitive performance at post-treatment. This randomized controlled trial suggests that an integrative cognitive rehabilitation program can produce significant functional cerebral changes in PD patients and adds evidence to the efficacy of cognitive rehabilitation programs in the therapeutic approach for PD.

Control networks and hubs.

PubMed

Gratton, Caterina; Sun, Haoxin; Petersen, Steven E

2018-03-01

Executive control functions are associated with frontal, parietal, cingulate, and insular brain regions that interact through distributed large-scale networks. Here, we discuss how fMRI functional connectivity can shed light on the organization of control networks and how they interact with other parts of the brain. In the first section of our review, we present convergent evidence from fMRI functional connectivity, activation, and lesion studies that there are multiple dissociable control networks in the brain with distinct functional properties. In the second section, we discuss how graph theoretical concepts can help illuminate the mechanisms by which control networks interact with other brain regions to carry out goal-directed functions, focusing on the role of specialized hub regions for mediating cross-network interactions. Again, we use a combination of functional connectivity, lesion, and task activation studies to bolster this claim. We conclude that a large-scale network perspective provides important neurobiological constraints on the neural underpinnings of executive control, which will guide future basic and translational research into executive function and its disruption in disease. © 2017 Society for Psychophysiological Research.

Dynamic functional connectivity: Promise, issues, and interpretations

PubMed Central

Hutchison, R. Matthew; Womelsdorf, Thilo; Allen, Elena A.; Bandettini, Peter A.; Calhoun, Vince D.; Corbetta, Maurizio; Penna, Stefania Della; Duyn, Jeff H.; Glover, Gary H.; Gonzalez-Castillo, Javier; Handwerker, Daniel A.; Keilholz, Shella; Kiviniemi, Vesa; Leopold, David A.; de Pasquale, Francesco; Sporns, Olaf; Walter, Martin; Chang, Catie

2013-01-01

The brain must dynamically integrate, coordinate, and respond to internal and external stimuli across multiple time scales. Non-invasive measurements of brain activity with fMRI have greatly advanced our understanding of the large-scale functional organization supporting these fundamental features of brain function. Conclusions from previous resting-state fMRI investigations were based upon static descriptions of functional connectivity (FC), and only recently studies have begun to capitalize on the wealth of information contained within the temporal features of spontaneous BOLD FC. Emerging evidence suggests that dynamic FC metrics may index changes in macroscopic neural activity patterns underlying critical aspects of cognition and behavior, though limitations with regard to analysis and interpretation remain. Here, we review recent findings, methodological considerations, neural and behavioral correlates, and future directions in the emerging field of dynamic FC investigations. PMID:23707587

A phenome-wide examination of neural and cognitive function.

PubMed

Poldrack, R A; Congdon, E; Triplett, W; Gorgolewski, K J; Karlsgodt, K H; Mumford, J A; Sabb, F W; Freimer, N B; London, E D; Cannon, T D; Bilder, R M

2016-12-06

This data descriptor outlines a shared neuroimaging dataset from the UCLA Consortium for Neuropsychiatric Phenomics, which focused on understanding the dimensional structure of memory and cognitive control (response inhibition) functions in both healthy individuals (130 subjects) and individuals with neuropsychiatric disorders including schizophrenia (50 subjects), bipolar disorder (49 subjects), and attention deficit/hyperactivity disorder (43 subjects). The dataset includes an extensive set of task-based fMRI assessments, resting fMRI, structural MRI, and high angular resolution diffusion MRI. The dataset is shared through the OpenfMRI project, and is formatted according to the Brain Imaging Data Structure (BIDS) standard.

Unmasking Language Lateralization in Human Brain Intrinsic Activity

PubMed Central

McAvoy, Mark; Mitra, Anish; Coalson, Rebecca S.; d'Avossa, Giovanni; Keidel, James L.; Petersen, Steven E.; Raichle, Marcus E.

2016-01-01

Lateralization of function is a fundamental feature of the human brain as exemplified by the left hemisphere dominance of language. Despite the prominence of lateralization in the lesion, split-brain and task-based fMRI literature, surprisingly little asymmetry has been revealed in the increasingly popular functional imaging studies of spontaneous fluctuations in the fMRI BOLD signal (so-called resting-state fMRI). Here, we show the global signal, an often discarded component of the BOLD signal in resting-state studies, reveals a leftward asymmetry that maps onto regions preferential for semantic processing in left frontal and temporal cortex and the right cerebellum and a rightward asymmetry that maps onto putative attention-related regions in right frontal, temporoparietal, and parietal cortex. Hemispheric asymmetries in the global signal resulted from amplitude modulation of the spontaneous fluctuations. To confirm these findings obtained from normal, healthy, right-handed subjects in the resting-state, we had them perform 2 semantic processing tasks: synonym and numerical magnitude judgment and sentence comprehension. In addition to establishing a new technique for studying lateralization through functional imaging of the resting-state, our findings shed new light on the physiology of the global brain signal. PMID:25636911

Search for Patterns of Functional Specificity in the Brain: A Nonparametric Hierarchical Bayesian Model for Group fMRI Data

PubMed Central

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

2012-01-01

Functional MRI studies have uncovered a number of brain areas that demonstrate highly specific functional patterns. In the case of visual object recognition, small, focal regions have been characterized with selectivity for visual categories such as human faces. In this paper, we develop an algorithm that automatically learns patterns of functional specificity from fMRI data in a group of subjects. The method does not require spatial alignment of functional images from different subjects. The algorithm is based on a generative model that comprises two main layers. At the lower level, we express the functional brain response to each stimulus as a binary activation variable. At the next level, we define a prior over sets of activation variables in all subjects. We use a Hierarchical Dirichlet Process as the prior in order to learn the patterns of functional specificity shared across the group, which we call functional systems, and estimate the number of these systems. Inference based on our model enables automatic discovery and characterization of dominant and consistent functional systems. We apply the method to data from a visual fMRI study comprised of 69 distinct stimulus images. The discovered system activation profiles correspond to selectivity for a number of image categories such as faces, bodies, and scenes. Among systems found by our method, we identify new areas that are deactivated by face stimuli. In empirical comparisons with perviously proposed exploratory methods, our results appear superior in capturing the structure in the space of visual categories of stimuli. PMID:21884803

Mapping the order and pattern of brain structural MRI changes using change-point analysis in premanifest Huntington's disease.

PubMed

Wu, Dan; Faria, Andreia V; Younes, Laurent; Mori, Susumu; Brown, Timothy; Johnson, Hans; Paulsen, Jane S; Ross, Christopher A; Miller, Michael I

2017-10-01

Huntington's disease (HD) is an autosomal dominant neurodegenerative disorder that progressively affects motor, cognitive, and emotional functions. Structural MRI studies have demonstrated brain atrophy beginning many years prior to clinical onset ("premanifest" period), but the order and pattern of brain structural changes have not been fully characterized. In this study, we investigated brain regional volumes and diffusion tensor imaging (DTI) measurements in premanifest HD, and we aim to determine (1) the extent of MRI changes in a large number of structures across the brain by atlas-based analysis, and (2) the initiation points of structural MRI changes in these brain regions. We adopted a novel multivariate linear regression model to detect the inflection points at which the MRI changes begin (namely, "change-points"), with respect to the CAG-age product (CAP, an indicator of extent of exposure to the effects of CAG repeat expansion). We used approximately 300 T1-weighted and DTI data from premanifest HD and control subjects in the PREDICT-HD study, with atlas-based whole brain segmentation and change-point analysis. The results indicated a distinct topology of structural MRI changes: the change-points of the volumetric measurements suggested a central-to-peripheral pattern of atrophy from the striatum to the deep white matter; and the change points of DTI measurements indicated the earliest changes in mean diffusivity in the deep white matter and posterior white matter. While interpretation needs to be cautious given the cross-sectional nature of the data, these findings suggest a spatial and temporal pattern of spread of structural changes within the HD brain. Hum Brain Mapp 38:5035-5050, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Continuous functional magnetic resonance imaging reveals dynamic nonlinearities of "dose-response" curves for finger opposition.

PubMed

Berns, G S; Song, A W; Mao, H

1999-07-15

Linear experimental designs have dominated the field of functional neuroimaging, but although successful at mapping regions of relative brain activation, the technique assumes that both cognition and brain activation are linear processes. To test these assumptions, we performed a continuous functional magnetic resonance imaging (MRI) experiment of finger opposition. Subjects performed a visually paced bimanual finger-tapping task. The frequency of finger tapping was continuously varied between 1 and 5 Hz, without any rest blocks. After continuous acquisition of fMRI images, the task-related brain regions were identified with independent components analysis (ICA). When the time courses of the task-related components were plotted against tapping frequency, nonlinear "dose- response" curves were obtained for most subjects. Nonlinearities appeared in both the static and dynamic sense, with hysteresis being prominent in several subjects. The ICA decomposition also demonstrated the spatial dynamics with different components active at different times. These results suggest that the brain response to tapping frequency does not scale linearly, and that it is history-dependent even after accounting for the hemodynamic response function. This implies that finger tapping, as measured with fMRI, is a nonstationary process. When analyzed with a conventional general linear model, a strong correlation to tapping frequency was identified, but the spatiotemporal dynamics were not apparent.

Insights from neuroenergetics into the interpretation of functional neuroimaging: an alternative empirical model for studying the brain's support of behavior

PubMed Central

Shulman, Robert G; Hyder, Fahmeed; Rothman, Douglas L

2014-01-01

Functional neuroimaging measures quantitative changes in neurophysiological parameters coupled to neuronal activity during observable behavior. These results have usually been interpreted by assuming that mental causation of behavior arises from the simultaneous actions of distinct psychological mechanisms or modules. However, reproducible localization of these modules in the brain using functional magnetic resonance imaging (MRI) and positron emission tomography (PET) imaging has been elusive other than for sensory systems. In this paper, we show that neuroenergetic studies using PET, calibrated functional magnetic resonance imaging (fMRI), 13C magnetic resonance spectroscopy, and electrical recordings do not support the standard approach, which identifies the location of mental modules from changes in brain activity. Of importance in reaching this conclusion is that changes in neuronal activities underlying the fMRI signal are many times smaller than the high ubiquitous, baseline neuronal activity, or energy in resting, awake humans. Furthermore, the incremental signal depends on the baseline activity contradicting theoretical assumptions about linearity and insertion of mental modules. To avoid these problems, while making use of these valuable results, we propose that neuroimaging should be used to identify observable brain activities that are necessary for a person's observable behavior rather than being used to seek hypothesized mental processes. PMID:25160670

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

PubMed Central

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

2012-01-01

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

Portable MRI

DOE Office of Scientific and Technical Information (OSTI.GOV)

Espy, Michelle A.

This project proposes to: (1) provide the power of MRI to situations where it presently isn't available; (2) perform the engineering required to move from lab to a functional prototype; and (3) leverage significant existing infrastructure and capability in ultra-low field MRI. The reasons for doing this: (1) MRI is the most powerful tool for imaging soft-tissue (e.g. brain); (2) Billions don't have access due to cost or safety issues; (3) metal will heat/move in high magnetic fields; (4) Millions of cases of traumatic brain injury in US alone; (5) even more of non-traumatic brain injury; (6) (e.g. stroke, infection,more » chemical exposure); (7) Need for early diagnostic; (8) 'Signature' wound of recent conflicts; (9) 22% of injuries; (10) Implications for post-traumatic stress disorder; and (11) chronic traumatic encephalopathy.« less

Hyperconnectivity is a fundamental response to neurological disruption.

PubMed

Hillary, Frank G; Roman, Cristina A; Venkatesan, Umesh; Rajtmajer, Sarah M; Bajo, Ricardo; Castellanos, Nazareth D

2015-01-01

In the cognitive and clinical neurosciences, the past decade has been marked by dramatic growth in a literature examining brain "connectivity" using noninvasive methods. We offer a critical review of the blood oxygen level dependent functional MRI (BOLD fMRI) literature examining neural connectivity changes in neurological disorders with focus on brain injury and dementia. The goal is to demonstrate that there are identifiable shifts in local and large-scale network connectivity that can be predicted by the degree of pathology. We anticipate that the most common network response to neurological insult is hyperconnectivity but that this response depends upon demand and resource availability. To examine this hypothesis, we initially reviewed the results from 1,426 studies examining functional brain connectivity in individuals diagnosed with multiple sclerosis, traumatic brain injury, mild cognitive impairment, and Alzheimer's disease. Based upon inclusionary criteria, 126 studies were included for detailed analysis. RESULTS from 126 studies examining local and whole brain connectivity demonstrated increased connectivity in traumatic brain injury and multiple sclerosis. This finding is juxtaposed with findings in mild cognitive impairment and Alzheimer's disease where there is a shift to diminished connectivity as degeneration progresses. This summary of the functional imaging literature using fMRI methods reveals that hyperconnectivity is a common response to neurological disruption and that it may be differentially observable across brain regions. We discuss the factors contributing to both hyper- and hypoconnectivity results after neurological disruption and the implications these findings have for network plasticity. PsycINFO Database Record (c) 2015 APA, all rights reserved.

Mapping the Alzheimer’s Brain with Connectomics

PubMed Central

Xie, Teng; He, Yong

2012-01-01

Alzheimer’s disease (AD) is the most common form of dementia. As an incurable, progressive, and neurodegenerative disease, it causes cognitive and memory deficits. However, the biological mechanisms underlying the disease are not thoroughly understood. In recent years, non-invasive neuroimaging and neurophysiological techniques [e.g., structural magnetic resonance imaging (MRI), diffusion MRI, functional MRI, and EEG/MEG] and graph theory based network analysis have provided a new perspective on structural and functional connectivity patterns of the human brain (i.e., the human connectome) in health and disease. Using these powerful approaches, several recent studies of patients with AD exhibited abnormal topological organization in both global and regional properties of neuronal networks, indicating that AD not only affects specific brain regions, but also alters the structural and functional associations between distinct brain regions. Specifically, disruptive organization in the whole-brain networks in AD is involved in the loss of small-world characters and the re-organization of hub distributions. These aberrant neuronal connectivity patterns were associated with cognitive deficits in patients with AD, even with genetic factors in healthy aging. These studies provide empirical evidence to support the existence of an aberrant connectome of AD. In this review we will summarize recent advances discovered in large-scale brain network studies of AD, mainly focusing on graph theoretical analysis of brain connectivity abnormalities. These studies provide novel insights into the pathophysiological mechanisms of AD and could be helpful in developing imaging biomarkers for disease diagnosis and monitoring. PMID:22291664

Information flow between interacting human brains: Identification, validation, and relationship to social expertise.

PubMed

Bilek, Edda; Ruf, Matthias; Schäfer, Axel; Akdeniz, Ceren; Calhoun, Vince D; Schmahl, Christian; Demanuele, Charmaine; Tost, Heike; Kirsch, Peter; Meyer-Lindenberg, Andreas

2015-04-21

Social interactions are fundamental for human behavior, but the quantification of their neural underpinnings remains challenging. Here, we used hyperscanning functional MRI (fMRI) to study information flow between brains of human dyads during real-time social interaction in a joint attention paradigm. In a hardware setup enabling immersive audiovisual interaction of subjects in linked fMRI scanners, we characterize cross-brain connectivity components that are unique to interacting individuals, identifying information flow between the sender's and receiver's temporoparietal junction. We replicate these findings in an independent sample and validate our methods by demonstrating that cross-brain connectivity relates to a key real-world measure of social behavior. Together, our findings support a central role of human-specific cortical areas in the brain dynamics of dyadic interactions and provide an approach for the noninvasive examination of the neural basis of healthy and disturbed human social behavior with minimal a priori assumptions.