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Large-Scale Information Flow in Conscious and Unconscious States: an ECoG Study in Monkeys

Consciousness is an emergent property of the complex brain network. In order to understand how consciousness is constructed, neural interactions within this network must be elucidated. Previous studies have shown that specific neural interactions between the thalamus and frontoparietal cortices; fro...

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Autores principales: Yanagawa, Toru, Chao, Zenas C., Hasegawa, Naomi, Fujii, Naotaka
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3829858/
https://www.ncbi.nlm.nih.gov/pubmed/24260491
http://dx.doi.org/10.1371/journal.pone.0080845
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author Yanagawa, Toru
Chao, Zenas C.
Hasegawa, Naomi
Fujii, Naotaka
author_facet Yanagawa, Toru
Chao, Zenas C.
Hasegawa, Naomi
Fujii, Naotaka
author_sort Yanagawa, Toru
collection PubMed
description Consciousness is an emergent property of the complex brain network. In order to understand how consciousness is constructed, neural interactions within this network must be elucidated. Previous studies have shown that specific neural interactions between the thalamus and frontoparietal cortices; frontal and parietal cortices; and parietal and temporal cortices are correlated with levels of consciousness. However, due to technical limitations, the network underlying consciousness has not been investigated in terms of large-scale interactions with high temporal and spectral resolution. In this study, we recorded neural activity with dense electrocorticogram (ECoG) arrays and used the spectral Granger causality to generate a more comprehensive network that relates to consciousness in monkeys. We found that neural interactions were significantly different between conscious and unconscious states in all combinations of cortical region pairs. Furthermore, the difference in neural interactions between conscious and unconscious states could be represented in 4 frequency-specific large-scale networks with unique interaction patterns: 2 networks were related to consciousness and showed peaks in alpha and beta bands, while the other 2 networks were related to unconsciousness and showed peaks in theta and gamma bands. Moreover, networks in the unconscious state were shared amongst 3 different unconscious conditions, which were induced either by ketamine and medetomidine, propofol, or sleep. Our results provide a novel picture that the difference between conscious and unconscious states is characterized by a switch in frequency-specific modes of large-scale communications across the entire cortex, rather than the cessation of interactions between specific cortical regions.
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spelling pubmed-38298582013-11-20 Large-Scale Information Flow in Conscious and Unconscious States: an ECoG Study in Monkeys Yanagawa, Toru Chao, Zenas C. Hasegawa, Naomi Fujii, Naotaka PLoS One Research Article Consciousness is an emergent property of the complex brain network. In order to understand how consciousness is constructed, neural interactions within this network must be elucidated. Previous studies have shown that specific neural interactions between the thalamus and frontoparietal cortices; frontal and parietal cortices; and parietal and temporal cortices are correlated with levels of consciousness. However, due to technical limitations, the network underlying consciousness has not been investigated in terms of large-scale interactions with high temporal and spectral resolution. In this study, we recorded neural activity with dense electrocorticogram (ECoG) arrays and used the spectral Granger causality to generate a more comprehensive network that relates to consciousness in monkeys. We found that neural interactions were significantly different between conscious and unconscious states in all combinations of cortical region pairs. Furthermore, the difference in neural interactions between conscious and unconscious states could be represented in 4 frequency-specific large-scale networks with unique interaction patterns: 2 networks were related to consciousness and showed peaks in alpha and beta bands, while the other 2 networks were related to unconsciousness and showed peaks in theta and gamma bands. Moreover, networks in the unconscious state were shared amongst 3 different unconscious conditions, which were induced either by ketamine and medetomidine, propofol, or sleep. Our results provide a novel picture that the difference between conscious and unconscious states is characterized by a switch in frequency-specific modes of large-scale communications across the entire cortex, rather than the cessation of interactions between specific cortical regions. Public Library of Science 2013-11-15 /pmc/articles/PMC3829858/ /pubmed/24260491 http://dx.doi.org/10.1371/journal.pone.0080845 Text en © 2013 Yanagawa et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Yanagawa, Toru
Chao, Zenas C.
Hasegawa, Naomi
Fujii, Naotaka
Large-Scale Information Flow in Conscious and Unconscious States: an ECoG Study in Monkeys
title Large-Scale Information Flow in Conscious and Unconscious States: an ECoG Study in Monkeys
title_full Large-Scale Information Flow in Conscious and Unconscious States: an ECoG Study in Monkeys
title_fullStr Large-Scale Information Flow in Conscious and Unconscious States: an ECoG Study in Monkeys
title_full_unstemmed Large-Scale Information Flow in Conscious and Unconscious States: an ECoG Study in Monkeys
title_short Large-Scale Information Flow in Conscious and Unconscious States: an ECoG Study in Monkeys
title_sort large-scale information flow in conscious and unconscious states: an ecog study in monkeys
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3829858/
https://www.ncbi.nlm.nih.gov/pubmed/24260491
http://dx.doi.org/10.1371/journal.pone.0080845
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