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  Time-resolved resting-state functional magnetic resonance imaging analysis: Current status, challenges, and new directions

Keilholz, S., Caballero-Gaudes, C., Bandettini, P., Deco, G., & Calhoun, V. (2017). Time-resolved resting-state functional magnetic resonance imaging analysis: Current status, challenges, and new directions. Brain Connectivity, 7(8), 465-481. doi:10.1089/brain.2017.0543.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-002E-2511-A Version Permalink: http://hdl.handle.net/21.11116/0000-0005-52F4-B
Genre: Journal Article

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 Creators:
Keilholz, Shella1, Author
Caballero-Gaudes, Cesar2, Author
Bandettini, Peter3, 4, Author
Deco, Gustavo5, 6, 7, 8, Author              
Calhoun, Vince9, 10, Author
Affiliations:
1Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA, USA, ou_persistent22              
2Basque Center on Cognition, Brain and Language, Donostia-San Sebastián, Spain, ou_persistent22              
3Section on Functional Imaging Methods, National Institute of Mental Health, Bethesda, MD, USA, ou_persistent22              
4Functional MRI Core Facility, National Institute of Mental Health, Bethesda, MD, USA, ou_persistent22              
5Department of Information and Communication Technologies, Center for Brain and Cognition, University Pompeu Fabra, Barcelona, Spain, ou_persistent22              
6Catalan Institution for Research and Advanced Studies (ICREA), University Pompeu Fabra, Barcelona, Spain, ou_persistent22              
7Department Neuropsychology, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634551              
8School of Psychological Sciences, Monash University, Melbourne, Australia, ou_persistent22              
9The Mind Research Network (MRN), Albuquerque, NM, USA, ou_persistent22              
10Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM, USA, ou_persistent22              

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Free keywords: Dynamic analysis; Dynamic connectivity; Network dynamics; Time-resolved resting-state fMRI
 Abstract: Time-resolved analysis of resting-state functional magnetic resonance imaging (rs-fMRI) data allows researchers to extract more information about brain function than traditional functional connectivity analysis, yet a number of challenges in data analysis and interpretation remain. This article briefly summarizes common methods for time-resolved analysis and presents some of the pressing issues and opportunities in the field. From there, the discussion moves to interpretation of the network dynamics observed with rs-fMRI and the role that rs-fMRI can play in elucidating the large-scale organization of brain activity.

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Language(s): eng - English
 Dates: 2017-09-062017-10-01
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: Peer
 Identifiers: DOI: 10.1089/brain.2017.0543
PMID: 28874061
PMC: PMC5653134
 Degree: -

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Title: Brain Connectivity
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: Mary Ann Liebert
Pages: - Volume / Issue: 7 (8) Sequence Number: - Start / End Page: 465 - 481 Identifier: Other: 2158-0022
CoNE: https://pure.mpg.de/cone/journals/resource/2158-0022