Revealing the relevant spatiotemporal scale underlying whole-brain dynamics

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• dc.contributor.author Kobeleva, Xenia
• dc.contributor.author López-González, Ane, 1993-
• dc.contributor.author Kringelbach, Morten L.
• dc.contributor.author Deco, Gustavo
• dc.date.accessioned 2022-06-27T06:31:22Z
• dc.date.available 2022-06-27T06:31:22Z
• dc.date.issued 2021
• dc.description.abstract The brain rapidly processes and adapts to new information by dynamically transitioning between whole-brain functional networks. In this whole-brain modeling study we investigate the relevance of spatiotemporal scale in whole-brain functional networks. This is achieved through estimating brain parcellations at different spatial scales (100– 900 regions) and time series at different temporal scales (from milliseconds to seconds) generated by a whole-brain model fitted to fMRI data. We quantify the richness of the dynamic repertoire at each spatiotemporal scale by computing the entropy of transitions between whole-brain functional networks. The results show that the optimal relevant spatial scale is around 300 regions and a temporal scale of around 150 ms. Overall, this study provides much needed evidence for the relevant spatiotemporal scales and recommendations for analyses of brain dynamics.
• dc.description.sponsorship This work was supported by a short-term fellowship of the European Molecular Biology Organization (Grant No. 7366) and by an InEurope fellowship of the International Brain Research Organization of XK. AL-G was supported by Swiss National Science Foundation Sinergia (Grant No. 170873). GD was supported by AWAKENING Using whole-brain models perturbational approaches for predicting external stimulation to force transitions between different brain states (Ref. PID2019- 105772GB-I00 and AEI FEDER EU), funded by the Spanish Ministry of Science, Innovation and Universities (MCIU), State Research Agency (AEI) and European Regional Development Funds (FEDER), by HBP SGA3 Human Brain Project Specific Grant Agreement 3 (Grant Agreement No. 945539), funded by the EU H2020 FET Flagship program and by SGR Research Support Group support (Ref. 2017 SGR 1545), funded by the Catalan Agency for Management of University and Research Grants (AGAUR). MK was supported by the ERC Consolidator Grant: CAREGIVING (Grant No. 615539), Center for Music in the Brain, funded by the Danish National Research Foundation (DNRF117), and Centre for Eudaimonia and Human Flourishing funded by the Pettit and Carlsberg Foundations.
• dc.format.mimetype application/pdf
• dc.identifier.citation Kobeleva X, López-González A, Kringelbach ML, Deco G. Revealing the relevant spatiotemporal scale underlying whole-brain dynamics. Front Neurosci. 2021;15:715861. DOI: 10.3389/fnins.2021.715861
• dc.identifier.doi http://doi.org/10.3389/fnins.2021.715861
• dc.identifier.issn 1662-4548
• dc.identifier.uri http://hdl.handle.net/10230/53592
• dc.language.iso eng
• dc.publisher Frontiers
• dc.relation.ispartof Frontiers in neuroscience. 2021;15:715861.
• dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/945539
• dc.relation.projectID info:eu-repo/grantAgreement/ES/2PE/PID2019-105772GB-I00 P
• dc.rights © 2021 Kobeleva, López-González, Kringelbach and Deco. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri https://creativecommons.org/licenses/by/4.0/
• dc.subject.keyword modeling
• dc.subject.keyword spatiotemporal
• dc.subject.keyword brain dynamics
• dc.subject.keyword functional connectivity
• dc.subject.keyword brain networks
• dc.title Revealing the relevant spatiotemporal scale underlying whole-brain dynamics
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/publishedVersion