Macroscopic Quantities of Collective Brain Activity during Wakefulness and Anesthesia.
Collective activity
Imaximum entropy models
brain states
consciousness
fMR
phase transitions
Journal
Cerebral cortex (New York, N.Y. : 1991)
ISSN: 1460-2199
Titre abrégé: Cereb Cortex
Pays: United States
ID NLM: 9110718
Informations de publication
Date de publication:
10 01 2022
10 01 2022
Historique:
received:
24
03
2021
revised:
02
06
2021
accepted:
07
06
2021
pubmed:
8
7
2021
medline:
1
4
2022
entrez:
7
7
2021
Statut:
ppublish
Résumé
The study of states of arousal is key to understand the principles of consciousness. Yet, how different brain states emerge from the collective activity of brain regions remains unknown. Here, we studied the fMRI brain activity of monkeys during wakefulness and anesthesia-induced loss of consciousness. We showed that the coupling between each brain region and the rest of the cortex provides an efficient statistic to classify the two brain states. Based on this and other statistics, we estimated maximum entropy models to derive collective, macroscopic properties that quantify the system's capabilities to produce work, to contain information, and to transmit it, which were all maximized in the awake state. The differences in these properties were consistent with a phase transition from critical dynamics in the awake state to supercritical dynamics in the anesthetized state. Moreover, information-theoretic measures identified those parameters that impacted the most the network dynamics. We found that changes in the state of consciousness primarily depended on changes in network couplings of insular, cingulate, and parietal cortices. Our findings suggest that the brain state transition underlying the loss of consciousness is predominantly driven by the uncoupling of specific brain regions from the rest of the network.
Identifiants
pubmed: 34231843
pii: 6316621
doi: 10.1093/cercor/bhab209
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
298-311Informations de copyright
© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.