Complex spatiotemporal oscillations emerge from transverse instabilities in large-scale brain networks

Spatiotemporal oscillations underlie all cognitive brain functions. Large-scale brain models, constrained by neuroimaging data, aim to trace the principles underlying such macroscopic neural activity from the intricate and multi-scale structure of the brain. Despite substantial progress in the field...

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Detalles Bibliográficos
Autores: Clusella, Pau, Deco, Gustavo, Kringelbach, Morten L., Ruffini, Giulio, García Ojalvo, Jordi
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2023
País:España
Institución:Universitat Pompeu Fabra
Repositorio:Repositorio Digital de la UPF
OAI Identifier:oai:repositori.upf.edu:10230/57164
Acceso en línea:http://hdl.handle.net/10230/57164
http://dx.doi.org/10.1371/journal.pcbi.1010781
Access Level:acceso abierto
Palabra clave:Neurons
Neural networks
Eigenvalues
Traveling waves
Eigenvectors
Membrane potential
Manifolds
Simulation and modeling
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spelling Complex spatiotemporal oscillations emerge from transverse instabilities in large-scale brain networksClusella, PauDeco, GustavoKringelbach, Morten L.Ruffini, GiulioGarcía Ojalvo, JordiNeuronsNeural networksEigenvaluesTraveling wavesEigenvectorsMembrane potentialManifoldsSimulation and modelingSpatiotemporal oscillations underlie all cognitive brain functions. Large-scale brain models, constrained by neuroimaging data, aim to trace the principles underlying such macroscopic neural activity from the intricate and multi-scale structure of the brain. Despite substantial progress in the field, many aspects about the mechanisms behind the onset of spatiotemporal neural dynamics are still unknown. In this work we establish a simple framework for the emergence of complex brain dynamics, including high-dimensional chaos and travelling waves. The model consists of a complex network of 90 brain regions, whose structural connectivity is obtained from tractography data. The activity of each brain area is governed by a Jansen neural mass model and we normalize the total input received by each node so it amounts the same across all brain areas. This assumption allows for the existence of an homogeneous invariant manifold, i.e., a set of different stationary and oscillatory states in which all nodes behave identically. Stability analysis of these homogeneous solutions unveils a transverse instability of the synchronized state, which gives rise to different types of spatiotemporal dynamics, such as chaotic alpha activity. Additionally, we illustrate the ubiquity of this route towards complex spatiotemporal activity in a network of next generation neural mass models. Altogehter, our results unveil the bifurcation landscape that underlies the emergence of function from structure in the brain.PC, GD, GR, and JGO have received funding from the Future and Emerging Technologies Programme (FET) of the European Union’s Horizon 2020 research and innovation programme (project NEUROTWIN, grant agreement No 101017716). JGO also acknowledges financial support from the Spanish Ministry of Science and Innovation and FEDER (grant PID2021-127311NB-I00), by the “Maria de Maeztu” Programme for Units of Excellence in R&D (grant CEX2018-000792-M), and by the Generalitat de Catalunya (ICREA Academia programme). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Public Library of Science (PLoS)202320232023info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttp://hdl.handle.net/10230/57164http://dx.doi.org/10.1371/journal.pcbi.1010781reponame:Repositorio Digital de la UPFinstname:Universitat Pompeu FabraInglésPLoS Comput Biol. 2023 Apr 12;19(4):e1010781info:eu-repo/grantAgreement/ES/3PE/PID2021-127311NB-I00© 2023 Clusella et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.http://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:repositori.upf.edu:10230/571642026-06-12T07:21:37Z
dc.title.none.fl_str_mv Complex spatiotemporal oscillations emerge from transverse instabilities in large-scale brain networks
title Complex spatiotemporal oscillations emerge from transverse instabilities in large-scale brain networks
spellingShingle Complex spatiotemporal oscillations emerge from transverse instabilities in large-scale brain networks
Clusella, Pau
Neurons
Neural networks
Eigenvalues
Traveling waves
Eigenvectors
Membrane potential
Manifolds
Simulation and modeling
title_short Complex spatiotemporal oscillations emerge from transverse instabilities in large-scale brain networks
title_full Complex spatiotemporal oscillations emerge from transverse instabilities in large-scale brain networks
title_fullStr Complex spatiotemporal oscillations emerge from transverse instabilities in large-scale brain networks
title_full_unstemmed Complex spatiotemporal oscillations emerge from transverse instabilities in large-scale brain networks
title_sort Complex spatiotemporal oscillations emerge from transverse instabilities in large-scale brain networks
dc.creator.none.fl_str_mv Clusella, Pau
Deco, Gustavo
Kringelbach, Morten L.
Ruffini, Giulio
García Ojalvo, Jordi
author Clusella, Pau
author_facet Clusella, Pau
Deco, Gustavo
Kringelbach, Morten L.
Ruffini, Giulio
García Ojalvo, Jordi
author_role author
author2 Deco, Gustavo
Kringelbach, Morten L.
Ruffini, Giulio
García Ojalvo, Jordi
author2_role author
author
author
author
dc.subject.none.fl_str_mv Neurons
Neural networks
Eigenvalues
Traveling waves
Eigenvectors
Membrane potential
Manifolds
Simulation and modeling
topic Neurons
Neural networks
Eigenvalues
Traveling waves
Eigenvectors
Membrane potential
Manifolds
Simulation and modeling
description Spatiotemporal oscillations underlie all cognitive brain functions. Large-scale brain models, constrained by neuroimaging data, aim to trace the principles underlying such macroscopic neural activity from the intricate and multi-scale structure of the brain. Despite substantial progress in the field, many aspects about the mechanisms behind the onset of spatiotemporal neural dynamics are still unknown. In this work we establish a simple framework for the emergence of complex brain dynamics, including high-dimensional chaos and travelling waves. The model consists of a complex network of 90 brain regions, whose structural connectivity is obtained from tractography data. The activity of each brain area is governed by a Jansen neural mass model and we normalize the total input received by each node so it amounts the same across all brain areas. This assumption allows for the existence of an homogeneous invariant manifold, i.e., a set of different stationary and oscillatory states in which all nodes behave identically. Stability analysis of these homogeneous solutions unveils a transverse instability of the synchronized state, which gives rise to different types of spatiotemporal dynamics, such as chaotic alpha activity. Additionally, we illustrate the ubiquity of this route towards complex spatiotemporal activity in a network of next generation neural mass models. Altogehter, our results unveil the bifurcation landscape that underlies the emergence of function from structure in the brain.
publishDate 2023
dc.date.none.fl_str_mv 2023
2023
2023
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10230/57164
http://dx.doi.org/10.1371/journal.pcbi.1010781
url http://hdl.handle.net/10230/57164
http://dx.doi.org/10.1371/journal.pcbi.1010781
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv PLoS Comput Biol. 2023 Apr 12;19(4):e1010781
info:eu-repo/grantAgreement/ES/3PE/PID2021-127311NB-I00
dc.rights.none.fl_str_mv http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
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:Repositorio Digital de la UPF
instname:Universitat Pompeu Fabra
instname_str Universitat Pompeu Fabra
reponame_str Repositorio Digital de la UPF
collection Repositorio Digital de la UPF
repository.name.fl_str_mv
repository.mail.fl_str_mv
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