Contextual connectivity: A framework for understanding the intrinsic dynamic architecture of large-scale functional brain networks

Abstract Investigations of the human brain’s connectomic architecture have produced two alternative models: one describes the brain’s spatial structure in terms of static localized networks, and the other describes the brain’s temporal structure in terms of dynamic whole-brain states. Here, we used...

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Autores principales:	Rastko Ciric, Jason S. Nomi, Lucina Q. Uddin, Ajay B. Satpute
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/515b522a58cb44e7b39fc6d550898545
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spelling	oai:doaj.org-article:515b522a58cb44e7b39fc6d5508985452021-12-02T15:05:48ZContextual connectivity: A framework for understanding the intrinsic dynamic architecture of large-scale functional brain networks10.1038/s41598-017-06866-w2045-2322https://doaj.org/article/515b522a58cb44e7b39fc6d5508985452017-07-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-06866-whttps://doaj.org/toc/2045-2322Abstract Investigations of the human brain’s connectomic architecture have produced two alternative models: one describes the brain’s spatial structure in terms of static localized networks, and the other describes the brain’s temporal structure in terms of dynamic whole-brain states. Here, we used tools from connectivity dynamics to develop a synthesis that bridges these models. Using resting fMRI data, we investigated the assumptions undergirding current models of the human connectome. Consistent with state-based models, our results suggest that static localized networks are superordinate approximations of underlying dynamic states. Furthermore, each of these localized, dynamic connectivity states is associated with global changes in the whole-brain functional connectome. By nesting localized dynamic connectivity states within their whole-brain contexts, we demonstrate the relative temporal independence of brain networks. Our assay for functional autonomy of coordinated neural systems is broadly applicable, and our findings provide evidence of structure in temporal state dynamics that complements the well-described static spatial organization of the brain.Rastko CiricJason S. NomiLucina Q. UddinAjay B. SatputeNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-16 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Rastko Ciric Jason S. Nomi Lucina Q. Uddin Ajay B. Satpute Contextual connectivity: A framework for understanding the intrinsic dynamic architecture of large-scale functional brain networks
description	Abstract Investigations of the human brain’s connectomic architecture have produced two alternative models: one describes the brain’s spatial structure in terms of static localized networks, and the other describes the brain’s temporal structure in terms of dynamic whole-brain states. Here, we used tools from connectivity dynamics to develop a synthesis that bridges these models. Using resting fMRI data, we investigated the assumptions undergirding current models of the human connectome. Consistent with state-based models, our results suggest that static localized networks are superordinate approximations of underlying dynamic states. Furthermore, each of these localized, dynamic connectivity states is associated with global changes in the whole-brain functional connectome. By nesting localized dynamic connectivity states within their whole-brain contexts, we demonstrate the relative temporal independence of brain networks. Our assay for functional autonomy of coordinated neural systems is broadly applicable, and our findings provide evidence of structure in temporal state dynamics that complements the well-described static spatial organization of the brain.
format	article
author	Rastko Ciric Jason S. Nomi Lucina Q. Uddin Ajay B. Satpute
author_facet	Rastko Ciric Jason S. Nomi Lucina Q. Uddin Ajay B. Satpute
author_sort	Rastko Ciric
title	Contextual connectivity: A framework for understanding the intrinsic dynamic architecture of large-scale functional brain networks
title_short	Contextual connectivity: A framework for understanding the intrinsic dynamic architecture of large-scale functional brain networks
title_full	Contextual connectivity: A framework for understanding the intrinsic dynamic architecture of large-scale functional brain networks
title_fullStr	Contextual connectivity: A framework for understanding the intrinsic dynamic architecture of large-scale functional brain networks
title_full_unstemmed	Contextual connectivity: A framework for understanding the intrinsic dynamic architecture of large-scale functional brain networks
title_sort	contextual connectivity: a framework for understanding the intrinsic dynamic architecture of large-scale functional brain networks
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/515b522a58cb44e7b39fc6d550898545
work_keys_str_mv	AT rastkociric contextualconnectivityaframeworkforunderstandingtheintrinsicdynamicarchitectureoflargescalefunctionalbrainnetworks AT jasonsnomi contextualconnectivityaframeworkforunderstandingtheintrinsicdynamicarchitectureoflargescalefunctionalbrainnetworks AT lucinaquddin contextualconnectivityaframeworkforunderstandingtheintrinsicdynamicarchitectureoflargescalefunctionalbrainnetworks AT ajaybsatpute contextualconnectivityaframeworkforunderstandingtheintrinsicdynamicarchitectureoflargescalefunctionalbrainnetworks
_version_	1718388704184107008

Contextual connectivity: A framework for understanding the intrinsic dynamic architecture of large-scale functional brain networks

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