Loss of consciousness reduces the stability of brain hubs and the heterogeneity of brain dynamics.
Journal
Communications biology
ISSN: 2399-3642
Titre abrégé: Commun Biol
Pays: England
ID NLM: 101719179
Informations de publication
Date de publication:
06 09 2021
06 09 2021
Historique:
received:
24
11
2020
accepted:
11
08
2021
entrez:
7
9
2021
pubmed:
8
9
2021
medline:
15
12
2021
Statut:
epublish
Résumé
Low-level states of consciousness are characterized by disruptions of brain activity that sustain arousal and awareness. Yet, how structural, dynamical, local and network brain properties interplay in the different levels of consciousness is unknown. Here, we study fMRI brain dynamics from patients that suffered brain injuries leading to a disorder of consciousness and from healthy subjects undergoing propofol-induced sedation. We show that pathological and pharmacological low-level states of consciousness display less recurrent, less connected and more segregated synchronization patterns than conscious state. We use whole-brain models built upon healthy and injured structural connectivity to interpret these dynamical effects. We found that low-level states of consciousness were associated with reduced network interactions, together with more homogeneous and more structurally constrained local dynamics. Notably, these changes lead the structural hub regions to lose their stability during low-level states of consciousness, thus attenuating the differences between hubs and non-hubs brain dynamics.
Identifiants
pubmed: 34489535
doi: 10.1038/s42003-021-02537-9
pii: 10.1038/s42003-021-02537-9
pmc: PMC8421429
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1037Subventions
Organisme : EC | Horizon 2020 Framework Programme (EU Framework Programme for Research and Innovation H2020)
ID : 945539
Organisme : Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (Swiss National Science Foundation)
ID : 170873
Organisme : Danmarks Grundforskningsfond (Danish National Research Foundation)
ID : DNRF117
Informations de copyright
© 2021. The Author(s).
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