The Effect of noise on the synchronization dynamics of the Kuramoto model on a large human connectome graph
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- dc.contributor.author Ódor, Géza
- dc.contributor.author Kelling, Jeffrey
- dc.contributor.author Deco, Gustavo
- dc.date.accessioned 2022-06-21T05:56:46Z
- dc.date.available 2022-06-21T05:56:46Z
- dc.date.issued 2021
- dc.description.abstract We have extended the study of the Kuramoto model with additive Gaussian noise running on the KKI-18 large human connectome graph. We determined the dynamical behavior of this model by solving it numerically in an assumed homeostatic state, below the synchronization crossover point we determined previously. The de-synchronization duration distributions exhibit power-law tails, characterized by the exponent in the range 1:1 < st < 2, overlapping the in vivo human brain activity experiments by Palva et al. We show that these scaling results remain valid, by a transformation of the ultra-slow eigenfrequencies to Gaussian with unit variance. We also compare the connectome results with those, obtained on a regular cube with N ¼ 106 nodes, related to the embedding space, and show that the quenched internal frequencies themselves can cause frustrated synchronization scaling in an extended coupling space.
- dc.description.sponsorship The work has been performed under the Project HPC-EUROPA3 (INFRAIA-2016-1-730897), with the support of the EC Research Innovation Action under the H2020 Programme; in particular, G. Ó. gratefully acknowledges the support of Center for Brain and Cognition Theoretical and Computational Group Universitat Pompeu Fabra/ ICREA Barcelona and the computer resources and technical support provided by BSC Barcelona. Support from the Hungarian National Research, Development and Innovation Office NKFIH (K128989), the Initiative and Networking Fund of the Helmholtz Association via the W2/W3 Programme (W2/W3-026) and the Helmholtz Excellence Network DCM-MatDNA (ExNet-0028) is acknowledged.
- dc.format.mimetype application/pdf
- dc.identifier.citation Ódor G, Kelling J, Deco G. The Effect of noise on the synchronization dynamics of the Kuramoto model on a large human connectome graph. Neurocomputing. 2021;461:696-704. DOI: 10.1016/j.neucom.2020.04.161
- dc.identifier.doi http://doi.org/10.1016/j.neucom.2020.04.161
- dc.identifier.issn 0925-2312
- dc.identifier.uri http://hdl.handle.net/10230/53533
- dc.language.iso eng
- dc.publisher Elsevier
- dc.relation.ispartof Neurocomputing. 2021;461:696-704.
- dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/1-7308
- dc.rights © 2021 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
- dc.rights.accessRights info:eu-repo/semantics/openAccess
- dc.rights.uri http://creativecommons.org/licenses/by/4.0/
- dc.subject.keyword Frustrated synchronization
- dc.subject.keyword Human connectome
- dc.subject.keyword Chimera states
- dc.subject.keyword Noisy Kuramoto
- dc.subject.keyword Criticality in resting state
- dc.title The Effect of noise on the synchronization dynamics of the Kuramoto model on a large human connectome graph
- dc.type info:eu-repo/semantics/article
- dc.type.version info:eu-repo/semantics/publishedVersion