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Exploring large-scale brain networks in functional MRI

Guillaume Marrelec, Pierre Bellec, Habib Benali
2006 Journal of Physiology - Paris  
Increasing emphasis has been recently put on large-scale network processing of brain functions.  ...  To explore these networks, many approaches have been proposed in functional magnetic resonance imaging (fMRI).  ...  Acknowledgements The authors wish to thank an anonymous referee for improving the quality of this manuscript and Barry Horwitz for providing us with an historical perspective on functional connectivity  ... 
doi:10.1016/j.jphysparis.2007.01.003 pmid:17344038 fatcat:r5o6cg57zrfu7mspi7w77msgpe

Large-scale brain networks in cognition: emerging methods and principles

Steven L. Bressler, Vinod Menon
2010 Trends in Cognitive Sciences  
view that cognition results from the dynamic interactions of distributed brain areas operating in large-scale networks.  ...  We thus emphasize the structural and functional architectures of large-scale brain networks (Box 1).  ...  Acknowledgments This article expands on the theme of a conference on the large-scale brain networks of cognition that was held at UC Berkeley in 2007 with funding from the National Science Foundation.  ... 
doi:10.1016/j.tics.2010.04.004 pmid:20493761 fatcat:6tlmicz5k5a6zniudedxsmxfd4

Mapping cognitive and emotional networks in neurosurgical patients using resting-state functional magnetic resonance imaging

Michael P. Catalino, Shun Yao, Deborah L. Green, Edward R. Laws, Alexandra J. Golby, Yanmei Tie
2020 Neurosurgical Focus  
In this review, the authors give an overview of the rs-fMRI technique and associated cognitive and emotional resting-state networks, discuss the potential applications of rs-fMRI, and propose future directions  ...  Over the last 2 decades, we have seen dramatic improvements in the way we can image the human brain and noninvasively estimate the location of critical functional networks.  ...  . 30 The FPN has shown high variability in its functional topography among individuals, calling for large-scale studies of its clinical usefulness. 37 Salience Network The salience network (SN) is  ... 
doi:10.3171/2019.11.focus19773 pmid:32006946 pmcid:PMC7712886 fatcat:s3ci3bx36bcefeccbkd4c4fr4e

A deconvolution-based approach to identifying large-scale effective connectivity

Keith Bush, Suijian Zhou, Josh Cisler, Jiang Bian, Onder Hazaroglu, Keenan Gillispie, Kenji Yoshigoe, Clint Kilts
2015 Magnetic Resonance Imaging  
We then validated the ability for the proposed method to reliably detect effective connectivity in whole-brain fMRI signal parcellated into networks of viable size.  ...  We then test, both in simulation as well as whole-brain fMRI BOLD signal, the viability of this approach.  ...  Acknowledgements This work was supported in part by National Institutes of Health grants R21MH097784-01 and R01DA036360-01 as well as by as the National Science Foundation grants CRI CNS-0855248 and MRI  ... 
doi:10.1016/j.mri.2015.07.015 pmid:26248273 pmcid:PMC4658309 fatcat:aa3adnv7mzaxfpmgxgmgpnpxge

Connectome-scale functional intrinsic connectivity networks in macaques

Wei Zhang, Xi Jiang, Shu Zhang, Brittany R Howell, Yu Zhao, Tuo Zhang, Lei Guo, Mar M. Sanchez, Xiaoping Hu, Tianming Liu
2017 Neuroscience  
There have been extensive studies of intrinsic connectivity networks (ICNs) in the human brains using resting state fMRI in the literature.  ...  In this work, we propose a computational framework to identify connectome-scale group-wise consistent ICNs in macaques via sparse representation of whole-brain resting state fMRI data.  ...  The YNPRC is fully accredited by the Association for the Assessment and Accreditation of Laboratory Animal Care AAALAC), International.  ... 
doi:10.1016/j.neuroscience.2017.08.022 pmid:28842187 pmcid:PMC5653451 fatcat:dlg6v2gc7ndwfdf36ivk56cngy

Pushing the Limits of EEG: Estimation of Large-Scale Functional Brain Networks and Their Dynamics Validated by Simultaneous fMRI

Rodolfo Abreu, Marco Simões, Miguel Castelo-Branco
2020 Frontiers in Neuroscience  
Functional magnetic resonance imaging (fMRI) is the technique of choice for detecting large-scale functional brain networks and to investigate their dynamics.  ...  Then, we measured the dFC using EEG for the first time in this context, estimated dFC brain states using dictionary learning, and compared such states with those obtained from the fMRI.  ...  INTRODUCTION A large-scale functional brain network is defined as a subset of interconnected, possibly distant, brain regions that interact with each other in order to perform a plethora of tasks of different  ... 
doi:10.3389/fnins.2020.00323 pmid:32372908 pmcid:PMC7177188 fatcat:f5maeb43ffcchbobgzjbfgvtl4

Sparse temporally dynamic resting-state functional connectivity networks for early MCI identification

Chong-Yaw Wee, Sen Yang, Pew-Thian Yap, Dinggang Shen
2015 Brain Imaging and Behavior  
To preserve temporal smoothness of R-fMRI sub-series, we suggest to jointly estimate the temporal networks by maximizing a penalized log likelihood using a fused sparse learning algorithm.  ...  We design a disease identification framework based on the estimated temporal networks, and group level network property differences and classification results demonstrate the importance of including temporally  ...  Acknowledgments This work was supported in part by NIH grants AG041721, AG042599, EB008374, EB009634, and MH100217.  ... 
doi:10.1007/s11682-015-9408-2 pmid:26123390 pmcid:PMC4692725 fatcat:jics2l5mbrfsrm3zq2m2q3s5ku

Artificial Intelligence – State of Art Convolution Neural Network Architectures in a Nutshell

2019 VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE  
the human brain function by understanding how each part of the brain works.  ...  The Convolution neural network (CNN) is one of best deep architecture suitable to handle variety of inputs.  ...  DNN -LARGE SCALE AUDIO INPUT The Audio Set is a large audio dataset [8] III. CDNN-MUSIC INPUT The convolutional Deep neural network is used in automaticmusic content analysis.  ... 
doi:10.35940/ijitee.k1257.09811s19 fatcat:jedj52arj5etfeepmnhd4aurqi

The intrinsic spatiotemporal organization of the human brain - A multi-dimensional functional network atlas [article]

Jian Li, Yijun Liu, Jessica L. Wisnowski, Richard M. Leahy
2021 bioRxiv   pre-print
A canonical set of large-scale networks has been historically identified from resting-state fMRI (rs-fMRI), including the default mode, visual, somatomotor, salience, attention, and executive control.  ...  However, the methods used in identification of these networks have relied on assumptions that may inadvertently constrain their properties and consequently our understanding of the human connectome.  ...  Acknowledgment This work was supported by National Institutes of Health grants R01-EB009048, R01-EB026299, R01-NS089212, and K23-HD099309.  ... 
doi:10.1101/2021.12.09.472035 fatcat:2hoxcvd7ajdm7bs5dl5q5xbvyq

Estimation of high-dimensional brain connectivity from FMRI data using factor modeling

Chee-Ming Ting, Abd-Krim Seghouane, Sh-Hussain Salleh, A. B. Mohd Noor
2014 2014 IEEE Workshop on Statistical Signal Processing (SSP)  
We consider identifying effective connectivity of brain networks from fMRI time series.  ...  The standard vector autoregressive (VAR) models fail to give reliable network estimates, typically involving very large number of nodes.  ...  We apply it for effective connectivity analysis of large-scaled brain networks.  ... 
doi:10.1109/ssp.2014.6884578 dblp:conf/ssp/TingSSN14 fatcat:exui7i3xxve7ngnlqjyw7zprg4

Association of Brain Functions in Children With Anhedonia Mapped Onto Brain Imaging Measures

Narun Pornpattananangkul, Ellen Leibenluft, Daniel S. Pine, Argyris Stringaris
2019 JAMA psychiatry  
Using the Adolescent Brain Cognitive Development study data set, phenotype-specific alterations were found in intrinsic large-scale connectivity and task-evoked activation in children with anhedonia.  ...  To map anhedonia in children onto changes in intrinsic large-scale connectivity and task-evoked activation and to probe the specificity of these changes in anhedonia against other clinical phenotypes (  ...  between pairs of regions within each large-scale network (12) , between large-scale networks (66) , and between large-scale networks and subcortical regions (228).  ... 
doi:10.1001/jamapsychiatry.2019.0020 pmid:30865236 pmcid:PMC6552295 fatcat:6dephrpueje3jggqkatx2stxgu

When makes you unique: Temporality of the human brain fingerprint

Dimitri Van De Ville, Younes Farouj, Maria Giulia Preti, Raphaël Liégeois, Enrico Amico
2021 Science Advances  
E.A. acknowledges financial support from the SNSF Ambizione project "Fingerprinting the brain: Network science to extract features of cognition, behavior and dysfunction" (grant number PZ00P2_185716).  ...  R.L. was supported by the National Centre of Competence in Research-Evolving Language (grant number 51NF40_180888). Author contributions: E.A., M.G.P., and R.L. processed the data. D.V.D.V.  ...  This would allow us to extend the range of accessible time scales across modalities for dynamic identification.  ... 
doi:10.1126/sciadv.abj0751 pmid:34652937 pmcid:PMC8519575 fatcat:f4aqv4bfk5h4xinilguidgluau

Data Aggregation, Synthesis and Replication: Why Resting State fMRI Is and Is Not Ideal [article]

Michael P. Milham
2017 Figshare  
Talk given during the "Harmonise This! Analyzing Diverse Neuroimaging Datasets" workshop at the 2015 Organization for Human Brain Mapping (OHBM) conference in Hawaii, 14-18 June.  ...  the identification of hubs in the human brain, using resting-state functional connectivity datasets.  ...  Thus, we aimed to determine the location of the functional connectivity hubs in the human brain by using data from the "1000 Functional Connectomes Project" (17), which is a large public database of resting-state  ... 
doi:10.6084/m9.figshare.5477833.v1 fatcat:rbab7nn5ozf5jed6kw63fwb7hq

Resting‐state functional magnetic resonance imaging versus task‐based activity for language mapping and correlation with perioperative cortical mapping

Jean‐Michel Lemée, David Hassanein Berro, Florian Bernard, Eva Chinier, Louis‐Marie Leiber, Philippe Menei, Aram Ter Minassian
2019 Brain and Behavior  
identification of functional networks without performing any explicit task through the analysis of the synchronicity of spontaneous BOLD signal oscillation between brain areas.  ...  Preoperative language mapping using functional magnetic resonance imaging (fMRI) aims to identify eloquent areas in the vicinity of surgically resectable brain lesions. fMRI methodology relies on the blood-oxygen-level-dependent  ...  For rsfMRI data analysis, a spatial independent component analysis (sICA) approach was used, employing a customized version of the Infomax algorithm running under MATLAB, for the identification of large-scale  ... 
doi:10.1002/brb3.1362 pmid:31568681 pmcid:PMC6790308 fatcat:qxfrdytlmjfgpjhugndqwwktaa

Modeling of Circuits within Networks by fMRI

G. de Marco, A. le Pellec
2010 Wireless Sensor Network  
The description of specific circuits in networks should allow a more realistic definition of dynamic functioning of the central nervous system which underlies various brain functions.  ...  After defining the concept of functional and effective connectivity, the authors describe various methods of identification and modeling of circuits within networks.  ...  A key tool to assess the validity of large-scale distributed networks in fMRI is knowledge of the underlying anatomical connections.  ... 
doi:10.4236/wsn.2010.23028 fatcat:uqudzrg23nhmjosonbw6tptx5q
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