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Brain criticality predicts individual levels of inter-areal synchronization in human electrophysiological data
Neuronal oscillations and their synchronization between brain areas are fundamental for healthy brain function. Yet, synchronization levels exhibit large inter-individual variability that is associated with behavioral variability. We test whether individual synchronization levels are predicted by in...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10406818/ https://www.ncbi.nlm.nih.gov/pubmed/37550300 http://dx.doi.org/10.1038/s41467-023-40056-9 |
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author | Fuscà, Marco Siebenhühner, Felix Wang, Sheng H. Myrov, Vladislav Arnulfo, Gabriele Nobili, Lino Palva, J. Matias Palva, Satu |
author_facet | Fuscà, Marco Siebenhühner, Felix Wang, Sheng H. Myrov, Vladislav Arnulfo, Gabriele Nobili, Lino Palva, J. Matias Palva, Satu |
author_sort | Fuscà, Marco |
collection | PubMed |
description | Neuronal oscillations and their synchronization between brain areas are fundamental for healthy brain function. Yet, synchronization levels exhibit large inter-individual variability that is associated with behavioral variability. We test whether individual synchronization levels are predicted by individual brain states along an extended regime of critical-like dynamics – the Griffiths phase (GP). We use computational modelling to assess how synchronization is dependent on brain criticality indexed by long-range temporal correlations (LRTCs). We analyze LRTCs and synchronization of oscillations from resting-state magnetoencephalography and stereo-electroencephalography data. Synchronization and LRTCs are both positively linearly and quadratically correlated among healthy subjects, while in epileptogenic areas they are negatively linearly correlated. These results show that variability in synchronization levels is explained by the individual position along the GP with healthy brain areas operating in its subcritical and epileptogenic areas in its supercritical side. We suggest that the GP is fundamental for brain function allowing individual variability while retaining functional advantages of criticality. |
format | Online Article Text |
id | pubmed-10406818 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-104068182023-08-09 Brain criticality predicts individual levels of inter-areal synchronization in human electrophysiological data Fuscà, Marco Siebenhühner, Felix Wang, Sheng H. Myrov, Vladislav Arnulfo, Gabriele Nobili, Lino Palva, J. Matias Palva, Satu Nat Commun Article Neuronal oscillations and their synchronization between brain areas are fundamental for healthy brain function. Yet, synchronization levels exhibit large inter-individual variability that is associated with behavioral variability. We test whether individual synchronization levels are predicted by individual brain states along an extended regime of critical-like dynamics – the Griffiths phase (GP). We use computational modelling to assess how synchronization is dependent on brain criticality indexed by long-range temporal correlations (LRTCs). We analyze LRTCs and synchronization of oscillations from resting-state magnetoencephalography and stereo-electroencephalography data. Synchronization and LRTCs are both positively linearly and quadratically correlated among healthy subjects, while in epileptogenic areas they are negatively linearly correlated. These results show that variability in synchronization levels is explained by the individual position along the GP with healthy brain areas operating in its subcritical and epileptogenic areas in its supercritical side. We suggest that the GP is fundamental for brain function allowing individual variability while retaining functional advantages of criticality. Nature Publishing Group UK 2023-08-07 /pmc/articles/PMC10406818/ /pubmed/37550300 http://dx.doi.org/10.1038/s41467-023-40056-9 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Fuscà, Marco Siebenhühner, Felix Wang, Sheng H. Myrov, Vladislav Arnulfo, Gabriele Nobili, Lino Palva, J. Matias Palva, Satu Brain criticality predicts individual levels of inter-areal synchronization in human electrophysiological data |
title | Brain criticality predicts individual levels of inter-areal synchronization in human electrophysiological data |
title_full | Brain criticality predicts individual levels of inter-areal synchronization in human electrophysiological data |
title_fullStr | Brain criticality predicts individual levels of inter-areal synchronization in human electrophysiological data |
title_full_unstemmed | Brain criticality predicts individual levels of inter-areal synchronization in human electrophysiological data |
title_short | Brain criticality predicts individual levels of inter-areal synchronization in human electrophysiological data |
title_sort | brain criticality predicts individual levels of inter-areal synchronization in human electrophysiological data |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10406818/ https://www.ncbi.nlm.nih.gov/pubmed/37550300 http://dx.doi.org/10.1038/s41467-023-40056-9 |
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