dc.contributor.author	Cakan, Caglar
dc.contributor.author	Dimulescu, Cristiana
dc.contributor.author	Khakimova, Liliia
dc.contributor.author	Obst, Daniela
dc.contributor.author	Flöel, Agnes
dc.contributor.author	Obermayer, Klaus
dc.date.accessioned	2022-02-01T14:02:57Z
dc.date.available	2022-02-01T14:02:57Z
dc.date.issued	2022-01-12
dc.date.updated	2022-01-26T10:23:20Z
dc.description.abstract	During 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.sponsorship	DFG, 327654276, SFB 1315: Mechanismen und Störungen der Gedächtniskonsolidierung: Von Synapsen zur Systemebene	en
dc.description.sponsorship	DFG, 414044773, Open Access Publizieren 2021 - 2022 / Technische Universität Berlin	en
dc.identifier.eissn	1662-5188
dc.identifier.uri	https://depositonce.tu-berlin.de/handle/11303/16234
dc.identifier.uri	http://dx.doi.org/10.14279/depositonce-15009
dc.language.iso	en	en
dc.rights.uri	https://creativecommons.org/licenses/by/4.0/	en
dc.subject.ddc	610 Medizin und Gesundheit	de
dc.subject.other	whole-brain model	en
dc.subject.other	slow-wave sleep	en
dc.subject.other	slow oscillations	en
dc.subject.other	mean-field model	en
dc.subject.other	evolutionary algorithm	en
dc.title	Spatiotemporal Patterns of Adaptation-Induced Slow Oscillations in a Whole-Brain Model of Slow-Wave Sleep	en
dc.type	Article	en
dc.type.version	publishedVersion	en
dcterms.bibliographicCitation.articlenumber	800101	en
dcterms.bibliographicCitation.doi	10.3389/fncom.2021.800101	en
dcterms.bibliographicCitation.journaltitle	Frontiers in Computational Neuroscience	en
dcterms.bibliographicCitation.originalpublishername	Frontiers	en
dcterms.bibliographicCitation.originalpublisherplace	Lausanne	en
dcterms.bibliographicCitation.volume	15	en
tub.accessrights.dnb	free	en
tub.affiliation	Fak. 4 Elektrotechnik und Informatik::Inst. Softwaretechnik und Theoretische Informatik::FG Neuronale Informationsverarbeitung	de
tub.affiliation.faculty	Fak. 4 Elektrotechnik und Informatik	de
tub.affiliation.group	FG Neuronale Informationsverarbeitung	de
tub.affiliation.institute	Inst. Softwaretechnik und Theoretische Informatik	de
tub.publisher.universityorinstitution	Technische Universität Berlin	en

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

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