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Markers of criticality in phase synchronization
The concept of the brain as a critical dynamical system is very attractive because systems close to criticality are thought to maximize their dynamic range of information processing and communication. To date, there have been two key experimental observations in support of this hypothesis: (i) neuro...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2014
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4173811/ https://www.ncbi.nlm.nih.gov/pubmed/25309353 http://dx.doi.org/10.3389/fnsys.2014.00176 |
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author | Botcharova, Maria Farmer, Simon F. Berthouze, Luc |
author_facet | Botcharova, Maria Farmer, Simon F. Berthouze, Luc |
author_sort | Botcharova, Maria |
collection | PubMed |
description | The concept of the brain as a critical dynamical system is very attractive because systems close to criticality are thought to maximize their dynamic range of information processing and communication. To date, there have been two key experimental observations in support of this hypothesis: (i) neuronal avalanches with power law distribution of size and (ii) long-range temporal correlations (LRTCs) in the amplitude of neural oscillations. The case for how these maximize dynamic range of information processing and communication is still being made and because a significant substrate for information coding and transmission is neural synchrony it is of interest to link synchronization measures with those of criticality. We propose a framework for characterizing criticality in synchronization based on an analysis of the moment-to-moment fluctuations of phase synchrony in terms of the presence of LRTCs. This framework relies on an estimation of the rate of change of phase difference and a set of methods we have developed to detect LRTCs. We test this framework against two classical models of criticality (Ising and Kuramoto) and recently described variants of these models aimed to more closely represent human brain dynamics. From these simulations we determine the parameters at which these systems show evidence of LRTCs in phase synchronization. We demonstrate proof of principle by analysing pairs of human simultaneous EEG and EMG time series, suggesting that LRTCs of corticomuscular phase synchronization can be detected in the resting state and experimentally manipulated. The existence of LRTCs in fluctuations of phase synchronization suggests that these fluctuations are governed by non-local behavior, with all scales contributing to system behavior. This has important implications regarding the conditions under which one should expect to see LRTCs in phase synchronization. Specifically, brain resting states may exhibit LRTCs reflecting a state of readiness facilitating rapid task-dependent shifts toward and away from synchronous states that abolish LRTCs. |
format | Online Article Text |
id | pubmed-4173811 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-41738112014-10-10 Markers of criticality in phase synchronization Botcharova, Maria Farmer, Simon F. Berthouze, Luc Front Syst Neurosci Neuroscience The concept of the brain as a critical dynamical system is very attractive because systems close to criticality are thought to maximize their dynamic range of information processing and communication. To date, there have been two key experimental observations in support of this hypothesis: (i) neuronal avalanches with power law distribution of size and (ii) long-range temporal correlations (LRTCs) in the amplitude of neural oscillations. The case for how these maximize dynamic range of information processing and communication is still being made and because a significant substrate for information coding and transmission is neural synchrony it is of interest to link synchronization measures with those of criticality. We propose a framework for characterizing criticality in synchronization based on an analysis of the moment-to-moment fluctuations of phase synchrony in terms of the presence of LRTCs. This framework relies on an estimation of the rate of change of phase difference and a set of methods we have developed to detect LRTCs. We test this framework against two classical models of criticality (Ising and Kuramoto) and recently described variants of these models aimed to more closely represent human brain dynamics. From these simulations we determine the parameters at which these systems show evidence of LRTCs in phase synchronization. We demonstrate proof of principle by analysing pairs of human simultaneous EEG and EMG time series, suggesting that LRTCs of corticomuscular phase synchronization can be detected in the resting state and experimentally manipulated. The existence of LRTCs in fluctuations of phase synchronization suggests that these fluctuations are governed by non-local behavior, with all scales contributing to system behavior. This has important implications regarding the conditions under which one should expect to see LRTCs in phase synchronization. Specifically, brain resting states may exhibit LRTCs reflecting a state of readiness facilitating rapid task-dependent shifts toward and away from synchronous states that abolish LRTCs. Frontiers Media S.A. 2014-09-24 /pmc/articles/PMC4173811/ /pubmed/25309353 http://dx.doi.org/10.3389/fnsys.2014.00176 Text en Copyright © 2014 Botcharova, Farmer and Berthouze. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neuroscience Botcharova, Maria Farmer, Simon F. Berthouze, Luc Markers of criticality in phase synchronization |
title | Markers of criticality in phase synchronization |
title_full | Markers of criticality in phase synchronization |
title_fullStr | Markers of criticality in phase synchronization |
title_full_unstemmed | Markers of criticality in phase synchronization |
title_short | Markers of criticality in phase synchronization |
title_sort | markers of criticality in phase synchronization |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4173811/ https://www.ncbi.nlm.nih.gov/pubmed/25309353 http://dx.doi.org/10.3389/fnsys.2014.00176 |
work_keys_str_mv | AT botcharovamaria markersofcriticalityinphasesynchronization AT farmersimonf markersofcriticalityinphasesynchronization AT berthouzeluc markersofcriticalityinphasesynchronization |