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Awakening: Predicting external stimulation to force transitions between different brain states

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dc.contributor.author Deco, Gustavo
dc.contributor.author Cruzat, Josephine
dc.contributor.author Cabral, Joana
dc.contributor.author Tagliazucchi, Enzo
dc.contributor.author Laufs, Helmut
dc.contributor.author Logothetis, Nikos K.
dc.contributor.author Kringelbach, Morten L.
dc.date.accessioned 2020-02-17T15:51:07Z
dc.date.available 2020-02-17T15:51:07Z
dc.date.issued 2019
dc.identifier.citation Deco G, Cruzat J, Cabral J, Tagliazucchi E, Laufs H, Logothetis NK, Kringelbach ML. Awakening: predicting external stimulation to force transitions between different brain states. Proc Natl Acad Sci U S A. 2019 Sep 3;116(36):18088-97. DOI: 10.1073/pnas.1905534116
dc.identifier.issn 0027-8424
dc.identifier.uri http://hdl.handle.net/10230/43620
dc.description.abstract A fundamental problem in systems neuroscience is how to force a transition from one brain state to another by external driven stimulation in, for example, wakefulness, sleep, coma, or neuropsychiatric diseases. This requires a quantitative and robust definition of a brain state, which has so far proven elusive. Here, we provide such a definition, which, together with whole-brain modeling, permits the systematic study in silico of how simulated brain stimulation can force transitions between different brain states in humans. Specifically, we use a unique neuroimaging dataset of human sleep to systematically investigate where to stimulate the brain to force an awakening of the human sleeping brain and vice versa. We show where this is possible using a definition of a brain state as an ensemble of “metastable substates,” each with a probabilistic stability and occurrence frequency fitted by a generative whole-brain model, fine-tuned on the basis of the effective connectivity. Given the biophysical limitations of direct electrical stimulation (DES) of microcircuits, this opens exciting possibilities for discovering stimulation targets and selecting connectivity patterns that can ensure propagation of DES-induced neural excitation, potentially making it possible to create awakenings from complex cases of brain injury.
dc.description.sponsorship G.D. is supported by the Spanish Research Project PSI2016-75688-P (Agencia Estatal de Investigación/Fondo Europeo de Desarrollo Regional, European Union); by the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreements 720270 (Human Brain Project [HBP] SGA1) and 785907 (HBP SGA2); and by the Catalan Agency for Management of University and Research Grants Programme 2017 SGR 1545. J. Cabral is supported by Portuguese Foundation for Science and Technology CEECIND/03325/2017, Portugal. M.L.K. is supported by the European Research Council Consolidator Grant: CAREGIVING (615539) and Center for Music in the Brain, funded by the Danish National Research Foundation (DNRF117).
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher National Academy of Sciences
dc.relation.ispartof Proceedings of the National Academy of Sciences of the United States of America. 2019 Sep 3;116(36):18088-97
dc.rights Copyright © 2019 the Author(s). Published by PNAS. This open access article is distributed under Creative Commons Attribution License 4.0 http://creativecommons.org/licenses/by/4.0/ (CC BY).
dc.rights.uri http://creativecommons.org/licenses/by/4.0/
dc.title Awakening: Predicting external stimulation to force transitions between different brain states
dc.type info:eu-repo/semantics/article
dc.identifier.doi http://dx.doi.org/10.1073/pnas.1905534116
dc.subject.keyword Brain states
dc.subject.keyword Metastates
dc.subject.keyword Electrical stimulation
dc.subject.keyword Computational neuroscience
dc.subject.keyword Modeling
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/720270
dc.relation.projectID info:eu-repo/grantAgreement/ES/1PE/PSI2016-75688-P
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/785907
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/publishedVersion

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