Resting-state temporal synchronization networks emerge from connectivity topology and heterogeneity

Spatial patterns of coherent activity across different brain areas have been identified during the resting-state fluctuations of the brain. However, recent studies indicate that resting-state activity is not stationary, but shows complex temporal dynamics. We were interested in the spatiotemporal dy...

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Autores: Ponce Álvarez, Adrián Fernando|||0000-0003-1446-7392, Deco, Gustavo, Hagmann, Patrick, Romani, Gian Luca, Mantini, Dante, Corbetta, Maurizio
Tipo de recurso: artículo
Fecha de publicación:2015
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/401890
Acceso en línea:https://hdl.handle.net/2117/401890
https://dx.doi.org/10.1371/journal.pcbi.1004100
Access Level:acceso abierto
Palabra clave:Neurology
Brain -- Research
Neurologia
Cervell -- Investigació
Classificació AMS::92 Biology and other natural sciences::92C Physiological, cellular and medical topics
Àrees temàtiques de la UPC::Ciències de la salut::Medicina::Neurologia
Àrees temàtiques de la UPC::Enginyeria biomèdica
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oai_identifier_str oai:upcommons.upc.edu:2117/401890
network_acronym_str ES
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spelling Resting-state temporal synchronization networks emerge from connectivity topology and heterogeneityPonce Álvarez, Adrián Fernando|||0000-0003-1446-7392Deco, GustavoHagmann, PatrickRomani, Gian LucaMantini, DanteCorbetta, MaurizioNeurologyBrain -- ResearchNeurologiaCervell -- InvestigacióClassificació AMS::92 Biology and other natural sciences::92C Physiological, cellular and medical topicsÀrees temàtiques de la UPC::Ciències de la salut::Medicina::NeurologiaÀrees temàtiques de la UPC::Enginyeria biomèdicaSpatial patterns of coherent activity across different brain areas have been identified during the resting-state fluctuations of the brain. However, recent studies indicate that resting-state activity is not stationary, but shows complex temporal dynamics. We were interested in the spatiotemporal dynamics of the phase interactions among resting-state fMRI BOLD signals from human subjects. We found that the global phase synchrony of the BOLD signals evolves on a characteristic ultra-slow (<0.01Hz) time scale, and that its temporal variations reflect the transient formation and dissolution of multiple communities of synchronized brain regions. Synchronized communities reoccurred intermittently in time and across scanning sessions. We found that the synchronization communities relate to previously defined functional networks known to be engaged in sensory-motor or cognitive function, called resting-state networks (RSNs), including the default mode network, the somato-motor network, the visual network, the auditory network, the cognitive control networks, the self-referential network, and combinations of these and other RSNs. We studied the mechanism originating the observed spatiotemporal synchronization dynamics by using a network model of phase oscillators connected through the brain’s anatomical connectivity estimated using diffusion imaging human data. The model consistently approximates the temporal and spatial synchronization patterns of the empirical data, and reveals that multiple clusters that transiently synchronize and desynchronize emerge from the complex topology of anatomical connections, provided that oscillators are heterogeneous.GD was supported by the ERC Advanced Grant: DYSTRUCTURE (n. 295129), by the Spanish Research Project SAF2010-16085, the FP7-ICT BrainScales and the Flagship Human Brain Project. PH was supported by Leenaards Foundation. DM was supported by the Swiss National Science Foundation (320030_146531), the European Commission (PCIG12-334039), the Wellcome Trust and the Royal Society (101253/Z/13/Z). MC was supported by NIH grants R01HD061117 and R01MH096482. APA was supported by the Brain Network Recovery Group through the James S. McDonnell Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Peer ReviewedPublic Library of Science (PLOS)20152015-02-1820242024-02-14journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/2117/401890https://dx.doi.org/10.1371/journal.pcbi.1004100reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2Attribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/4018902026-05-27T15:37:01Z
dc.title.none.fl_str_mv Resting-state temporal synchronization networks emerge from connectivity topology and heterogeneity
title Resting-state temporal synchronization networks emerge from connectivity topology and heterogeneity
spellingShingle Resting-state temporal synchronization networks emerge from connectivity topology and heterogeneity
Ponce Álvarez, Adrián Fernando|||0000-0003-1446-7392
Neurology
Brain -- Research
Neurologia
Cervell -- Investigació
Classificació AMS::92 Biology and other natural sciences::92C Physiological, cellular and medical topics
Àrees temàtiques de la UPC::Ciències de la salut::Medicina::Neurologia
Àrees temàtiques de la UPC::Enginyeria biomèdica
title_short Resting-state temporal synchronization networks emerge from connectivity topology and heterogeneity
title_full Resting-state temporal synchronization networks emerge from connectivity topology and heterogeneity
title_fullStr Resting-state temporal synchronization networks emerge from connectivity topology and heterogeneity
title_full_unstemmed Resting-state temporal synchronization networks emerge from connectivity topology and heterogeneity
title_sort Resting-state temporal synchronization networks emerge from connectivity topology and heterogeneity
dc.creator.none.fl_str_mv Ponce Álvarez, Adrián Fernando|||0000-0003-1446-7392
Deco, Gustavo
Hagmann, Patrick
Romani, Gian Luca
Mantini, Dante
Corbetta, Maurizio
author Ponce Álvarez, Adrián Fernando|||0000-0003-1446-7392
author_facet Ponce Álvarez, Adrián Fernando|||0000-0003-1446-7392
Deco, Gustavo
Hagmann, Patrick
Romani, Gian Luca
Mantini, Dante
Corbetta, Maurizio
author_role author
author2 Deco, Gustavo
Hagmann, Patrick
Romani, Gian Luca
Mantini, Dante
Corbetta, Maurizio
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv Neurology
Brain -- Research
Neurologia
Cervell -- Investigació
Classificació AMS::92 Biology and other natural sciences::92C Physiological, cellular and medical topics
Àrees temàtiques de la UPC::Ciències de la salut::Medicina::Neurologia
Àrees temàtiques de la UPC::Enginyeria biomèdica
topic Neurology
Brain -- Research
Neurologia
Cervell -- Investigació
Classificació AMS::92 Biology and other natural sciences::92C Physiological, cellular and medical topics
Àrees temàtiques de la UPC::Ciències de la salut::Medicina::Neurologia
Àrees temàtiques de la UPC::Enginyeria biomèdica
description Spatial patterns of coherent activity across different brain areas have been identified during the resting-state fluctuations of the brain. However, recent studies indicate that resting-state activity is not stationary, but shows complex temporal dynamics. We were interested in the spatiotemporal dynamics of the phase interactions among resting-state fMRI BOLD signals from human subjects. We found that the global phase synchrony of the BOLD signals evolves on a characteristic ultra-slow (<0.01Hz) time scale, and that its temporal variations reflect the transient formation and dissolution of multiple communities of synchronized brain regions. Synchronized communities reoccurred intermittently in time and across scanning sessions. We found that the synchronization communities relate to previously defined functional networks known to be engaged in sensory-motor or cognitive function, called resting-state networks (RSNs), including the default mode network, the somato-motor network, the visual network, the auditory network, the cognitive control networks, the self-referential network, and combinations of these and other RSNs. We studied the mechanism originating the observed spatiotemporal synchronization dynamics by using a network model of phase oscillators connected through the brain’s anatomical connectivity estimated using diffusion imaging human data. The model consistently approximates the temporal and spatial synchronization patterns of the empirical data, and reveals that multiple clusters that transiently synchronize and desynchronize emerge from the complex topology of anatomical connections, provided that oscillators are heterogeneous.
publishDate 2015
dc.date.none.fl_str_mv 2015
2015-02-18
2024
2024-02-14
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/2117/401890
https://dx.doi.org/10.1371/journal.pcbi.1004100
url https://hdl.handle.net/2117/401890
https://dx.doi.org/10.1371/journal.pcbi.1004100
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivatives 4.0 International
http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivatives 4.0 International
http://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Public Library of Science (PLOS)
publisher.none.fl_str_mv Public Library of Science (PLOS)
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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