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Criticality of resting-state EEG predicts perturbational complexity and level of consciousness during anesthesia
Consciousness has been proposed to be supported by electrophysiological patterns poised at criticality, a dynamical regime which exhibits adaptive computational properties, maximally complex patterns and divergent sensitivity to perturbation. Here, we investigated dynamical properties of the resting...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10664178/ https://www.ncbi.nlm.nih.gov/pubmed/37994368 http://dx.doi.org/10.1101/2023.10.26.564247 |
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author | Maschke, Charlotte O’Byrne, Jordan Colombo, Michele Angelo Boly, Melanie Gosseries, Olivia Laureys, Steven Rosanova, Mario Jerbi, Karim Blain-Moraes, Stefanie |
author_facet | Maschke, Charlotte O’Byrne, Jordan Colombo, Michele Angelo Boly, Melanie Gosseries, Olivia Laureys, Steven Rosanova, Mario Jerbi, Karim Blain-Moraes, Stefanie |
author_sort | Maschke, Charlotte |
collection | PubMed |
description | Consciousness has been proposed to be supported by electrophysiological patterns poised at criticality, a dynamical regime which exhibits adaptive computational properties, maximally complex patterns and divergent sensitivity to perturbation. Here, we investigated dynamical properties of the resting-state electroencephalogram of healthy subjects undergoing general anesthesia with propofol, xenon or ketamine. We then studied the relation of these dynamic properties with the perturbational complexity index (PCI), which has shown remarkably high sensitivity in detecting consciousness independent of behavior. All participants were unresponsive under anesthesia, while consciousness was retained only during ketamine anesthesia (in the form of vivid dreams)., enabling an experimental dissociation between unresponsiveness and unconsciousness. We estimated (i) avalanche criticality, (ii) chaoticity, and (iii) criticality-related measures, and found that states of unconsciousness were characterized by a distancing from both the edge of activity propagation and the edge of chaos. We were then able to predict individual subjects’ PCI (i.e., PCI(max)) with a mean absolute error below 7%. Our results establish a firm link between the PCI and criticality and provide further evidence for the role of criticality in the emergence of consciousness. |
format | Online Article Text |
id | pubmed-10664178 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Cold Spring Harbor Laboratory |
record_format | MEDLINE/PubMed |
spelling | pubmed-106641782023-11-22 Criticality of resting-state EEG predicts perturbational complexity and level of consciousness during anesthesia Maschke, Charlotte O’Byrne, Jordan Colombo, Michele Angelo Boly, Melanie Gosseries, Olivia Laureys, Steven Rosanova, Mario Jerbi, Karim Blain-Moraes, Stefanie bioRxiv Article Consciousness has been proposed to be supported by electrophysiological patterns poised at criticality, a dynamical regime which exhibits adaptive computational properties, maximally complex patterns and divergent sensitivity to perturbation. Here, we investigated dynamical properties of the resting-state electroencephalogram of healthy subjects undergoing general anesthesia with propofol, xenon or ketamine. We then studied the relation of these dynamic properties with the perturbational complexity index (PCI), which has shown remarkably high sensitivity in detecting consciousness independent of behavior. All participants were unresponsive under anesthesia, while consciousness was retained only during ketamine anesthesia (in the form of vivid dreams)., enabling an experimental dissociation between unresponsiveness and unconsciousness. We estimated (i) avalanche criticality, (ii) chaoticity, and (iii) criticality-related measures, and found that states of unconsciousness were characterized by a distancing from both the edge of activity propagation and the edge of chaos. We were then able to predict individual subjects’ PCI (i.e., PCI(max)) with a mean absolute error below 7%. Our results establish a firm link between the PCI and criticality and provide further evidence for the role of criticality in the emergence of consciousness. Cold Spring Harbor Laboratory 2023-10-31 /pmc/articles/PMC10664178/ /pubmed/37994368 http://dx.doi.org/10.1101/2023.10.26.564247 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator. |
spellingShingle | Article Maschke, Charlotte O’Byrne, Jordan Colombo, Michele Angelo Boly, Melanie Gosseries, Olivia Laureys, Steven Rosanova, Mario Jerbi, Karim Blain-Moraes, Stefanie Criticality of resting-state EEG predicts perturbational complexity and level of consciousness during anesthesia |
title | Criticality of resting-state EEG predicts perturbational complexity and level of consciousness during anesthesia |
title_full | Criticality of resting-state EEG predicts perturbational complexity and level of consciousness during anesthesia |
title_fullStr | Criticality of resting-state EEG predicts perturbational complexity and level of consciousness during anesthesia |
title_full_unstemmed | Criticality of resting-state EEG predicts perturbational complexity and level of consciousness during anesthesia |
title_short | Criticality of resting-state EEG predicts perturbational complexity and level of consciousness during anesthesia |
title_sort | criticality of resting-state eeg predicts perturbational complexity and level of consciousness during anesthesia |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10664178/ https://www.ncbi.nlm.nih.gov/pubmed/37994368 http://dx.doi.org/10.1101/2023.10.26.564247 |
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