Neonatal cortical activity organizes into transient network states that are affected by vigilance states and brain injury.
Brain dynamics
Functional networks
Hypoxic-ischemic encephalopathy
Neonatal EEG
Sleep
Journal
NeuroImage
ISSN: 1095-9572
Titre abrégé: Neuroimage
Pays: United States
ID NLM: 9215515
Informations de publication
Date de publication:
01 10 2023
01 10 2023
Historique:
received:
18
03
2023
revised:
11
08
2023
accepted:
21
08
2023
medline:
5
9
2023
pubmed:
25
8
2023
entrez:
24
8
2023
Statut:
ppublish
Résumé
Early neurodevelopment is critically dependent on the structure and dynamics of spontaneous neuronal activity; however, the natural organization of newborn cortical networks is poorly understood. Recent adult studies suggest that spontaneous cortical activity exhibits discrete network states with physiological correlates. Here, we studied newborn cortical activity during sleep using hidden Markov modeling to determine the presence of such discrete neonatal cortical states (NCS) in 107 newborn infants, with 47 of them presenting with a perinatal brain injury. Our results show that neonatal cortical activity organizes into four discrete NCSs that are present in both cardinal sleep states of a newborn infant, active and quiet sleep, respectively. These NCSs exhibit state-specific spectral and functional network characteristics. The sleep states exhibit different NCS dynamics, with quiet sleep presenting higher fronto-temporal activity and a stronger brain-wide neuronal coupling. Brain injury was associated with prolonged lifetimes of the transient NCSs, suggesting lowered dynamics, or flexibility, in the cortical networks. Taken together, the findings suggest that spontaneously occurring transient network states are already present at birth, with significant physiological and pathological correlates; this NCS analysis framework can be fully automatized, and it holds promise for offering an objective, global level measure of early brain function for benchmarking neurodevelopmental or clinical research.
Identifiants
pubmed: 37619792
pii: S1053-8119(23)00493-7
doi: 10.1016/j.neuroimage.2023.120342
pii:
doi:
Substances chimiques
Zinostatin
9014-02-2
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
120342Informations de copyright
Copyright © 2023. Published by Elsevier Inc.
Déclaration de conflit d'intérêts
Declaration of Competing Interest No conflict of interest exists. All authors approve the submission.