Microstate Analysis Reflects Maturation of the Preterm Brain.

Biomedical signal processing Brain maturation Microstate analysis Neonatal EEG Quantitative EEG

Journal

Brain topography
ISSN: 1573-6792
Titre abrégé: Brain Topogr
Pays: United States
ID NLM: 8903034

Informations de publication

Date de publication:
May 2024
Historique:
received: 13 05 2023
accepted: 11 09 2023
medline: 19 4 2024
pubmed: 12 10 2023
entrez: 12 10 2023
Statut: ppublish

Résumé

Preterm neonates are at risk of long-term neurodevelopmental impairments due to disruption of natural brain development. Electroencephalography (EEG) analysis can provide insights into brain development of preterm neonates. This study aims to explore the use of microstate (MS) analysis to evaluate global brain dynamics changes during maturation in preterm neonates with normal neurodevelopmental outcome.The dataset included 135 EEGs obtained from 48 neonates at varying postmenstrual ages (26.4 to 47.7 weeks), divided into four age groups. For each recording we extracted a 5-minute epoch during quiet sleep (QS) and during non-quiet sleep (NQS), resulting in eight groups (4 age group x 2 sleep states). We compared MS maps and corresponding (map-specific) MS metrics across groups using group-level maps. Additionally, we investigated individual map metrics.Four group-level MS maps accounted for approximately 70% of the global variance and showed non-random syntax. MS topographies and transitions changed significantly when neonates reached 37 weeks. For both sleep states and all MS maps, MS duration decreased and occurrence increased with age. The same relationships were found using individual maps, showing strong correlations (Pearson coefficients up to 0.74) between individual map metrics and post-menstrual age. Moreover, the Hurst exponent of the individual MS sequence decreased with age.The observed changes in MS metrics with age might reflect the development of the preterm brain, which is characterized by formation of neural networks. Therefore, MS analysis is a promising tool for monitoring preterm neonatal brain maturation, while our study can serve as a valuable reference for investigating EEGs of neonates with abnormal neurodevelopmental outcomes.

Identifiants

pubmed: 37823945
doi: 10.1007/s10548-023-01008-0
pii: 10.1007/s10548-023-01008-0
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

461-474

Informations de copyright

© 2023. The Author(s).

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Auteurs

Tim Hermans (T)

Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, KU Leuven, Leuven, Belgium.

Mohammad Khazaei (M)

Department of Neuroscience Imaging and Clinical Sciences, G. d'Annunzio University of Chieti-Pescara, Chieti, Italy.

Khadijeh Raeisi (K)

Department of Neuroscience Imaging and Clinical Sciences, G. d'Annunzio University of Chieti-Pescara, Chieti, Italy.

Pierpaolo Croce (P)

Department of Neuroscience Imaging and Clinical Sciences, G. d'Annunzio University of Chieti-Pescara, Chieti, Italy.
Behavioral Imaging and Neural Dynamics Center, G. d'Annunzio University of Chieti-Pescara, Chieti, Italy.

Gabriella Tamburro (G)

Department of Neuroscience Imaging and Clinical Sciences, G. d'Annunzio University of Chieti-Pescara, Chieti, Italy.
Behavioral Imaging and Neural Dynamics Center, G. d'Annunzio University of Chieti-Pescara, Chieti, Italy.

Anneleen Dereymaeker (A)

Department of Development and Regeneration, KU Leuven, Leuven, Belgium.
Neonatal Intensive Care Unit, UZ Leuven, Leuven, Belgium.

Maarten De Vos (M)

Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, KU Leuven, Leuven, Belgium.
Department of Development and Regeneration, KU Leuven, Leuven, Belgium.

Filippo Zappasodi (F)

Department of Neuroscience Imaging and Clinical Sciences, G. d'Annunzio University of Chieti-Pescara, Chieti, Italy.
Behavioral Imaging and Neural Dynamics Center, G. d'Annunzio University of Chieti-Pescara, Chieti, Italy.
Institute for Advanced Biomedical Technologies, G. d'Annunzio University of Chieti-Pescara, Chieti, Italy.

Silvia Comani (S)

Department of Neuroscience Imaging and Clinical Sciences, G. d'Annunzio University of Chieti-Pescara, Chieti, Italy. comani@unich.it.
Behavioral Imaging and Neural Dynamics Center, G. d'Annunzio University of Chieti-Pescara, Chieti, Italy. comani@unich.it.

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