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  Revealing the relevant spatiotemporal scale underlying whole-brain dynamics

Kobeleva, X., López-González, A., Kringelbach, M. L., & Deco, G. (2021). Revealing the relevant spatiotemporal scale underlying whole-brain dynamics. Frontiers in Neuroscience, 15: 715861. doi:10.3389/fnins.2021.715861.

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Item Permalink: https://hdl.handle.net/21.11116/0000-0009-9843-0 Version Permalink: https://hdl.handle.net/21.11116/0000-000D-7F5A-1
Genre: Journal Article

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 Creators:
Kobeleva, Xenia1, 2, 3, Author
López-González, Ane2, Author
Kringelbach, Morten L.4, 5, 6, Author
Deco, Gustavo2, 7, 8, 9, Author           
Affiliations:
1Department of Psychology, University Bonn, Germany, ou_persistent22              
2Computational Neuroscience Group, Department of Information and Communication Technologies, Center for Brain and Cognition, University Pompeu Fabra, Barcelona, Spain, ou_persistent22              
3German Center for Neurodegenerative Diseases, Bonn, Germany, ou_persistent22              
4Department of Psychiatry, University of Oxford, United Kingdom, ou_persistent22              
5Centre for Eudaimonia and Human Flourishing, University of Oxford, United Kingdom, ou_persistent22              
6Department of Clinical Medicine, Center for Music in the Brain, Aarhus University, Denmark, ou_persistent22              
7Catalan Institution for Research and Advanced Studies (ICREA), University Pompeu Fabra, Barcelona, Spain, ou_persistent22              
8Department Neuropsychology, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634551              
9School of Psychological Sciences, Monash University, Melbourne, Australia, ou_persistent22              

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Free keywords: Brain dynamics; Brain networks; Functional connectivity; Modeling; Spatiotemporal
 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.

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Language(s): eng - English
 Dates: 2021-05-272021-09-232021-10-22
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.3389/fnins.2021.715861
Other: eCollection 2021
PMID: 34744605
PMC: PMC8569182
 Degree: -

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Project name : -
Grant ID : 7366
Funding program : -
Funding organization : European Molecular Biology Organization (EMBO)
Project name : -
Grant ID : 170873; PID2019-105772GB-I00
Funding program : -
Funding organization : Swiss National Science Foundation (SNSF)
Project name : Human Brain Project
Grant ID : 945539
Funding program : -
Funding organization : European Union
Project name : -
Grant ID : 615539
Funding program : -
Funding organization : European Research Council (ERC)
Project name : -
Grant ID : DNRF117
Funding program : -
Funding organization : Danish National Research Foundation (DNRF)

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Title: Frontiers in Neuroscience
  Other : Front Neurosci
Source Genre: Journal
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Publ. Info: Lausanne, Switzerland : Frontiers Research Foundation
Pages: - Volume / Issue: 15 Sequence Number: 715861 Start / End Page: - Identifier: ISSN: 1662-4548
ISSN: 1662-453X
CoNE: https://pure.mpg.de/cone/journals/resource/1662-4548