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Critical dynamics in spontaneous EEG predict anesthetic-induced loss of consciousness and perturbational complexity.

Authors :
Maschke, Charlotte
O'Byrne, Jordan
Colombo, Michele Angelo
Boly, Melanie
Gosseries, Olivia
Laureys, Steven
Rosanova, Mario
Jerbi, Karim
Blain-Moraes, Stefanie
Source :
Communications Biology; 8/5/2024, Vol. 7 Issue 1, p1-14, 14p
Publication Year :
2024

Abstract

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 investigate dynamical properties of the resting-state electroencephalogram (EEG) of healthy subjects undergoing general anesthesia with propofol, xenon or ketamine. Importantly, 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. For each condition, we measure (i) avalanche criticality, (ii) chaoticity, and (iii) criticality-related metrics, revealing that states of unconsciousness are characterized by a distancing from both avalanche criticality and the edge of chaos. We then ask whether these same dynamical properties are predictive of the perturbational complexity index (PCI), a TMS-based measure that has shown remarkably high sensitivity in detecting consciousness independently of behavior. We successfully predict individual subjects' PCI values with considerably high accuracy from resting-state EEG dynamical properties alone. Our results establish a firm link between perturbational complexity and criticality, and provide further evidence that criticality is a necessary condition for the emergence of consciousness. An EEG study demonstrates that dynamical properties of resting-state EEG mark (un)consciousness under propofol, xenon and ketamine anesthesia and are able to predict the TMS-derived perturbational complexity index (PCI) in healthy adults. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
23993642
Volume :
7
Issue :
1
Database :
Complementary Index
Journal :
Communications Biology
Publication Type :
Academic Journal
Accession number :
178836604
Full Text :
https://doi.org/10.1038/s42003-024-06613-8