Egyszerű nézet

dc.contributor.author Rácz, Frigyes Sámuel
dc.contributor.author Stylianou, O
dc.contributor.author Mukli, Péter
dc.contributor.author Eke, András
dc.date.accessioned 2020-04-09T07:55:42Z
dc.date.available 2020-04-09T07:55:42Z
dc.date.issued 2019
dc.identifier 85072272340
dc.identifier.citation journalVolume=9;journalIssueNumber=1;journalTitle=SCIENTIFIC REPORTS;pagination=13474, pages: 15;journalAbbreviatedTitle=SCI REP;
dc.identifier.uri http://repo.lib.semmelweis.hu//handle/123456789/7905
dc.identifier.uri doi:10.1038/s41598-019-49726-5
dc.description.abstract Functional connectivity of the brain fluctuates even in resting-state condition. It has been reported recently that fluctuations of global functional network topology and those of individual connections between brain regions expressed multifractal scaling. To expand on these findings, in this study we investigated if multifractality was indeed an inherent property of dynamic functional connectivity (DFC) on the regional level as well. Furthermore, we explored if local DFC showed region-specific differences in its multifractal and entropy-related features. DFC analyses were performed on 62-channel, resting-state electroencephalography recordings of twelve young, healthy subjects. Surrogate data testing verified the true multifractal nature of regional DFC that could be attributed to the presumed nonlinear nature of the underlying processes. Moreover, we found a characteristic spatial distribution of local connectivity dynamics, in that frontal and occipital regions showed stronger long-range correlation and higher degree of multifractality, whereas the highest values of entropy were found over the central and temporal regions. The revealed topology reflected well the underlying resting-state network organization of the brain. The presented results and the proposed analysis framework could improve our understanding on how resting-state brain activity is spatio-temporally organized and may provide potential biomarkers for future clinical research.
dc.relation.ispartof urn:issn:2045-2322)
dc.title Multifractal and entropy analysis of resting-state electroencephalography reveals spatial organization in local dynamic functional connectivity
dc.type Journal Article
dc.date.updated 2019-10-09T12:32:32Z
dc.language.rfc3066 en
dc.rights.holder NULL
dc.identifier.mtmt 30839630
dc.contributor.department SE/AOK/I/Élettani Intézet
dc.contributor.institution Semmelweis Egyetem


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