Low-dimensional organization of global brain states of reduced consciousness.
CP: Neuroscience
deep learning
fMRI
low-dimensional brain dynamics
reduced consciousness
variational autoencoders
whole-brain modeling
Journal
Cell reports
ISSN: 2211-1247
Titre abrégé: Cell Rep
Pays: United States
ID NLM: 101573691
Informations de publication
Date de publication:
30 05 2023
30 05 2023
Historique:
received:
23
11
2022
revised:
19
03
2023
accepted:
24
04
2023
medline:
5
6
2023
pubmed:
12
5
2023
entrez:
12
5
2023
Statut:
ppublish
Résumé
Brain states are frequently represented using a unidimensional scale measuring the richness of subjective experience (level of consciousness). This description assumes a mapping between the high-dimensional space of whole-brain configurations and the trajectories of brain states associated with changes in consciousness, yet this mapping and its properties remain unclear. We combine whole-brain modeling, data augmentation, and deep learning for dimensionality reduction to determine a mapping representing states of consciousness in a low-dimensional space, where distances parallel similarities between states. An orderly trajectory from wakefulness to patients with brain injury is revealed in a latent space whose coordinates represent metrics related to functional modularity and structure-function coupling, increasing alongside loss of consciousness. Finally, we investigate the effects of model perturbations, providing geometrical interpretation for the stability and reversibility of states. We conclude that conscious awareness depends on functional patterns encoded as a low-dimensional trajectory within the vast space of brain configurations.
Identifiants
pubmed: 37171963
pii: S2211-1247(23)00502-8
doi: 10.1016/j.celrep.2023.112491
pii:
doi:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
112491Subventions
Organisme : NIA NIH HHS
ID : R01 AG057234
Pays : United States
Informations de copyright
Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of interests The authors declare no competing interests.