Spatiotemporal Patterns of Adaptation-Induced Slow Oscillations in a Whole-Brain Model of Slow-Wave Sleep

dc.contributor.authorCakan, Caglar
dc.contributor.authorDimulescu, Cristiana
dc.contributor.authorKhakimova, Liliia
dc.contributor.authorObst, Daniela
dc.contributor.authorFlöel, Agnes
dc.contributor.authorObermayer, Klaus
dc.date.accessioned2022-02-01T14:02:57Z
dc.date.available2022-02-01T14:02:57Z
dc.date.issued2022-01-12
dc.date.updated2022-01-26T10:23:20Z
dc.description.abstractDuring slow-wave sleep, the brain is in a self-organized regime in which slow oscillations (SOs) between up- and down-states travel across the cortex. While an isolated piece of cortex can produce SOs, the brain-wide propagation of these oscillations are thought to be mediated by the long-range axonal connections. We address the mechanism of how SOs emerge and recruit large parts of the brain using a whole-brain model constructed from empirical connectivity data in which SOs are induced independently in each brain area by a local adaptation mechanism. Using an evolutionary optimization approach, good fits to human resting-state fMRI data and sleep EEG data are found at values of the adaptation strength close to a bifurcation where the model produces a balance between local and global SOs with realistic spatiotemporal statistics. Local oscillations are more frequent, last shorter, and have a lower amplitude. Global oscillations spread as waves of silence across the undirected brain graph, traveling from anterior to posterior regions. These traveling waves are caused by heterogeneities in the brain network in which the connection strengths between brain areas determine which areas transition to a down-state first, and thus initiate traveling waves across the cortex. Our results demonstrate the utility of whole-brain models for explaining the origin of large-scale cortical oscillations and how they are shaped by the connectome.en
dc.description.sponsorshipDFG, 327654276, SFB 1315: Mechanismen und Störungen der Gedächtniskonsolidierung: Von Synapsen zur Systemebeneen
dc.description.sponsorshipDFG, 414044773, Open Access Publizieren 2021 - 2022 / Technische Universität Berlinen
dc.identifier.eissn1662-5188
dc.identifier.urihttps://depositonce.tu-berlin.de/handle/11303/16234
dc.identifier.urihttp://dx.doi.org/10.14279/depositonce-15009
dc.language.isoenen
dc.relation.ispartof10.14279/depositonce-19806
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en
dc.subject.ddc610 Medizin und Gesundheitde
dc.subject.otherwhole-brain modelen
dc.subject.otherslow-wave sleepen
dc.subject.otherslow oscillationsen
dc.subject.othermean-field modelen
dc.subject.otherevolutionary algorithmen
dc.titleSpatiotemporal Patterns of Adaptation-Induced Slow Oscillations in a Whole-Brain Model of Slow-Wave Sleepen
dc.typeArticleen
dc.type.versionpublishedVersionen
dcterms.bibliographicCitation.articlenumber800101en
dcterms.bibliographicCitation.doi10.3389/fncom.2021.800101en
dcterms.bibliographicCitation.journaltitleFrontiers in Computational Neuroscienceen
dcterms.bibliographicCitation.originalpublishernameFrontiersen
dcterms.bibliographicCitation.originalpublisherplaceLausanneen
dcterms.bibliographicCitation.volume15en
tub.accessrights.dnbfreeen
tub.affiliationFak. 4 Elektrotechnik und Informatik::Inst. Softwaretechnik und Theoretische Informatik::FG Neuronale Informationsverarbeitungde
tub.affiliation.facultyFak. 4 Elektrotechnik und Informatikde
tub.affiliation.groupFG Neuronale Informationsverarbeitungde
tub.affiliation.instituteInst. Softwaretechnik und Theoretische Informatikde
tub.publisher.universityorinstitutionTechnische Universität Berlinen

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