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Multifractal and entropy analysis of resting-state electroencephalography reveals spatial organization in local dynamic functional connectivity
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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6748940/ https://www.ncbi.nlm.nih.gov/pubmed/31530857 http://dx.doi.org/10.1038/s41598-019-49726-5 |
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author | Racz, Frigyes Samuel Stylianou, Orestis Mukli, Peter Eke, Andras |
author_facet | Racz, Frigyes Samuel Stylianou, Orestis Mukli, Peter Eke, Andras |
author_sort | Racz, Frigyes Samuel |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6748940 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-67489402019-09-27 Multifractal and entropy analysis of resting-state electroencephalography reveals spatial organization in local dynamic functional connectivity Racz, Frigyes Samuel Stylianou, Orestis Mukli, Peter Eke, Andras Sci Rep Article 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. Nature Publishing Group UK 2019-09-17 /pmc/articles/PMC6748940/ /pubmed/31530857 http://dx.doi.org/10.1038/s41598-019-49726-5 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Racz, Frigyes Samuel Stylianou, Orestis Mukli, Peter Eke, Andras Multifractal and entropy analysis of resting-state electroencephalography reveals spatial organization in local dynamic functional connectivity |
title | Multifractal and entropy analysis of resting-state electroencephalography reveals spatial organization in local dynamic functional connectivity |
title_full | Multifractal and entropy analysis of resting-state electroencephalography reveals spatial organization in local dynamic functional connectivity |
title_fullStr | Multifractal and entropy analysis of resting-state electroencephalography reveals spatial organization in local dynamic functional connectivity |
title_full_unstemmed | Multifractal and entropy analysis of resting-state electroencephalography reveals spatial organization in local dynamic functional connectivity |
title_short | Multifractal and entropy analysis of resting-state electroencephalography reveals spatial organization in local dynamic functional connectivity |
title_sort | multifractal and entropy analysis of resting-state electroencephalography reveals spatial organization in local dynamic functional connectivity |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6748940/ https://www.ncbi.nlm.nih.gov/pubmed/31530857 http://dx.doi.org/10.1038/s41598-019-49726-5 |
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