Sleep spindles as neurophysiological biomarkers of schizophrenia.

EEG GABA glutamate sleep thalamocortical networks

Journal

The European journal of neuroscience
ISSN: 1460-9568
Titre abrégé: Eur J Neurosci
Pays: France
ID NLM: 8918110

Informations de publication

Date de publication:
26 Oct 2023
Historique:
revised: 17 09 2023
received: 11 06 2023
accepted: 11 10 2023
medline: 27 10 2023
pubmed: 27 10 2023
entrez: 27 10 2023
Statut: aheadofprint

Résumé

Schizophrenia (SCZ) is a complex psychiatric disorder characterized by a wide range of clinical symptoms, including disrupted sleep. In recent years, there has been growing interest in assessing alterations in sleep parameters in patients with SCZ. Sleep spindles are brief (0.5-2 s) bursts of 12- to 16-Hz rhythmic electroencephalogram (EEG) oscillatory activity occurring during non-rapid eye movement (NREM) sleep. Spindles have been implicated in several critical brain functions, including learning, memory and plasticity, and are thought to reflect the integrity of underlying thalamocortical circuits. This review aims to provide an overview of the current research investigating sleep spindles in SCZ. After briefly describing the neurophysiological features of sleep spindles, I will discuss alterations in spindle characteristics observed in SCZ, their associations with the clinical symptomatology of these patients and their putative underlying neuronal and molecular mechanisms. I will then discuss the utility of sleep spindle measures as predictors of treatment response and disease progression. Finally, I will highlight future directions for research in this emerging field, including the prospect of utilizing sleep spindles as neurophysiological biomarkers of SCZ.

Identifiants

pubmed: 37885306
doi: 10.1111/ejn.16178
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : NIMH NIH HHS
ID : R01MH125816
Pays : United States
Organisme : NIMH NIH HHS
ID : R01MH130376
Pays : United States

Informations de copyright

© 2023 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

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Auteurs

Fabio Ferrarelli (F)

Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.

Classifications MeSH