Dynamic primitives of brain network interaction
Mostra el registre complet Registre parcial de l'ítem
- dc.contributor.author Schirner, Michael
- dc.contributor.author Kong, Xiaolu
- dc.contributor.author Yeo, B.T. Thomas
- dc.contributor.author Deco, Gustavo
- dc.contributor.author Ritter, Petra
- dc.date.accessioned 2023-03-03T07:43:00Z
- dc.date.available 2023-03-03T07:43:00Z
- dc.date.issued 2022
- dc.description.abstract What dynamic processes underly functional brain networks? Functional connectivity (FC) and functional connectivity dynamics (FCD) are used to represent the patterns and dynamics of functional brain networks. FC(D) is related to the synchrony of brain activity: when brain areas oscillate in a coordinated manner this yields a high correlation between their signal time series. To explain the processes underlying FC(D) we review how synchronized oscillations emerge from coupled neural populations in brain network models (BNMs). From detailed spiking networks to more abstract population models, there is strong support for the idea that the brain operates near critical instabilities that give rise to multistable or metastable dynamics that in turn lead to the intermittently synchronized slow oscillations underlying FC(D). We explore further consequences from these fundamental mechanisms and how they fit with reality. We conclude by highlighting the need for integrative brain models that connect separate mechanisms across levels of description and spatiotemporal scales and link them with cognitive function.
- dc.description.sponsorship We acknowledge support by H2020 Research and Innovation Action grants Human Brain Project SGA2 785907, SGA3 945539, VirtualBrainCloud 826421 and ERC 683049; Berlin Institute of Health & Foundation Charité, Johanna Quandt Excellence Initiative. Several computations have also been performed on the HPC for Research cluster of the Berlin Institute of Health. We acknowledge the use of Fenix Infrastructure resources, which are partially funded from the European Union's Horizon 2020 research and innovation programme through the ICEI project under the grant agreement No. 800858. German Research Foundation SFB 1436 (project ID 425899996); SFB 1315 (project ID 327654276); SFB 936 (project ID 178316478); SFB-TRR 295 (project ID 424778381); SPP Computational Connectomics RI 2073/6-1, RI 2073/10-2, RI 2073/9-1. BTTY is supported by the Singapore National Research Foundation (NRF) Fellowship (Class of 2017), the NUS Yong Loo Lin School of Medicine (NUHSRO/2020/124/TMR/LOA), the Singapore National Medical Research Council (NMRC) LCG (OFLCG19May-0035) and the United States National Institutes of Health (R01MH120080).
- dc.format.mimetype application/pdf
- dc.identifier.citation Schirner M, Kong X, Yeo BTT, Deco G, Ritter P. Dynamic primitives of brain network interaction. Neuroimage. 2022;250:118928. DOI: 10.1016/j.neuroimage.2022.118928
- dc.identifier.doi http://dx.doi.org/10.1016/j.neuroimage.2022.118928
- dc.identifier.issn 1053-8119
- dc.identifier.uri http://hdl.handle.net/10230/56020
- dc.language.iso eng
- dc.publisher Elsevier
- dc.relation.ispartof NeuroImage. 2022;250:118928.
- dc.relation.isreferencedby https://github.com/BrainModes/Review_DynamicPrimitives
- dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/785907
- dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/945539
- dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/826421
- dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/683049
- dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/800858
- dc.rights © 2022 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)
- dc.rights.accessRights info:eu-repo/semantics/openAccess
- dc.rights.uri http://creativecommons.org/licenses/by/4.0/
- dc.subject.other Xarxes neuronals (Neurobiologia)
- dc.title Dynamic primitives of brain network interaction
- dc.type info:eu-repo/semantics/article
- dc.type.version info:eu-repo/semantics/publishedVersion