Decoding brain states on the intrinsic manifold of human brain dynamics across wakefulness and sleep

Current state-of-the-art functional magnetic resonance imaging (fMRI) offers remarkable imaging quality and resolution, yet, the intrinsic dimensionality of brain dynamics in different states (wakefulness, light and deep sleep) remains unknown. Here we present a method to reveal the low dimensional...

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Autores: Rué-Queralt, Joan, Stevner, Angus, Tagliazucchi, Enzo, Laufs, Helmut, Kringelbach, Morten L., Deco, Gustavo, Atasoy, Selen
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2021
País:España
Institución:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:10230/53650
Acceso en línea:http://hdl.handle.net/10230/53650
http://doi.org/10.1038/s42003-021-02369-7
Access Level:acceso abierto
Palabra clave:Consciousness
Dynamical systems
Network models
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spelling Decoding brain states on the intrinsic manifold of human brain dynamics across wakefulness and sleepRué-Queralt, JoanStevner, AngusTagliazucchi, EnzoLaufs, HelmutKringelbach, Morten L.Deco, GustavoAtasoy, SelenConsciousnessDynamical systemsNetwork modelsCurrent state-of-the-art functional magnetic resonance imaging (fMRI) offers remarkable imaging quality and resolution, yet, the intrinsic dimensionality of brain dynamics in different states (wakefulness, light and deep sleep) remains unknown. Here we present a method to reveal the low dimensional intrinsic manifold underlying human brain dynamics, which is invariant of the high dimensional spatio-temporal representation of the neuroimaging technology. By applying this intrinsic manifold framework to fMRI data acquired in wakefulness and sleep, we reveal the nonlinear differences between wakefulness and three different sleep stages, and successfully decode these different brain states with a mean accuracy across participants of 96%. Remarkably, a further group analysis shows that the intrinsic manifolds of all participants share a common topology. Overall, our results reveal the intrinsic manifold underlying the spatiotemporal dynamics of brain activity and demonstrate how this manifold enables the decoding of different brain states such as wakefulness and various sleep stages.J.R.-Q. is funded by the Fundació Catalunya—La Pedrera Masters of Excellence Fellowship. M.L.K. and S.A. are supported by the ERC Consolidator Grant CAREGIVING (no. 615539) and Center for Music in the Brain, funded by the Danish National Research Foundation (DNRF117). G.D. is supported by a Spanish national research project (ref. PID2019- 105772GB-I00 /AEI/10.13039/501100011033 MCIU AEI) funded by the Spanish Ministry of Science, Innovation and Universities (MCIU), State Research Agency (AEI).Nature Research202220222021info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttp://hdl.handle.net/10230/53650http://doi.org/10.1038/s42003-021-02369-7reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)InglésCommunication biology. 2021;4:854.info:eu-repo/grantAgreement/ES/2PE/PID2019- 10© The Author(s) 2021 This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/.http://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:recercat.cat:10230/536502026-05-29T05:05:01Z
dc.title.none.fl_str_mv Decoding brain states on the intrinsic manifold of human brain dynamics across wakefulness and sleep
title Decoding brain states on the intrinsic manifold of human brain dynamics across wakefulness and sleep
spellingShingle Decoding brain states on the intrinsic manifold of human brain dynamics across wakefulness and sleep
Rué-Queralt, Joan
Consciousness
Dynamical systems
Network models
title_short Decoding brain states on the intrinsic manifold of human brain dynamics across wakefulness and sleep
title_full Decoding brain states on the intrinsic manifold of human brain dynamics across wakefulness and sleep
title_fullStr Decoding brain states on the intrinsic manifold of human brain dynamics across wakefulness and sleep
title_full_unstemmed Decoding brain states on the intrinsic manifold of human brain dynamics across wakefulness and sleep
title_sort Decoding brain states on the intrinsic manifold of human brain dynamics across wakefulness and sleep
dc.creator.none.fl_str_mv Rué-Queralt, Joan
Stevner, Angus
Tagliazucchi, Enzo
Laufs, Helmut
Kringelbach, Morten L.
Deco, Gustavo
Atasoy, Selen
author Rué-Queralt, Joan
author_facet Rué-Queralt, Joan
Stevner, Angus
Tagliazucchi, Enzo
Laufs, Helmut
Kringelbach, Morten L.
Deco, Gustavo
Atasoy, Selen
author_role author
author2 Stevner, Angus
Tagliazucchi, Enzo
Laufs, Helmut
Kringelbach, Morten L.
Deco, Gustavo
Atasoy, Selen
author2_role author
author
author
author
author
author
dc.subject.none.fl_str_mv Consciousness
Dynamical systems
Network models
topic Consciousness
Dynamical systems
Network models
description Current state-of-the-art functional magnetic resonance imaging (fMRI) offers remarkable imaging quality and resolution, yet, the intrinsic dimensionality of brain dynamics in different states (wakefulness, light and deep sleep) remains unknown. Here we present a method to reveal the low dimensional intrinsic manifold underlying human brain dynamics, which is invariant of the high dimensional spatio-temporal representation of the neuroimaging technology. By applying this intrinsic manifold framework to fMRI data acquired in wakefulness and sleep, we reveal the nonlinear differences between wakefulness and three different sleep stages, and successfully decode these different brain states with a mean accuracy across participants of 96%. Remarkably, a further group analysis shows that the intrinsic manifolds of all participants share a common topology. Overall, our results reveal the intrinsic manifold underlying the spatiotemporal dynamics of brain activity and demonstrate how this manifold enables the decoding of different brain states such as wakefulness and various sleep stages.
publishDate 2021
dc.date.none.fl_str_mv 2021
2022
2022
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/10230/53650
http://doi.org/10.1038/s42003-021-02369-7
url http://hdl.handle.net/10230/53650
http://doi.org/10.1038/s42003-021-02369-7
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Communication biology. 2021;4:854.
info:eu-repo/grantAgreement/ES/2PE/PID2019- 10
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 Nature Research
publisher.none.fl_str_mv Nature Research
dc.source.none.fl_str_mv reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
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