Multivariate prediction of cognitive performance from the sleep electroencephalogram.
Cognition
Health
Intelligence
Sleep EEG
Sleep spindle
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
04
2023
revised:
06
08
2023
accepted:
10
08
2023
medline:
5
9
2023
pubmed:
14
8
2023
entrez:
13
8
2023
Statut:
ppublish
Résumé
Human cognitive performance is a key function whose biological foundations have been partially revealed by genetic and brain imaging studies. The sleep electroencephalogram (EEG) is tightly linked to structural and functional features of the central nervous system and serves as another promising biomarker. We used data from MrOS, a large cohort of older men and cross-validated regularized regression to link sleep EEG features to cognitive performance in cross-sectional analyses. In independent validation samples 2.5-10% of variance in cognitive performance can be accounted for by sleep EEG features, depending on the covariates used. Demographic characteristics account for more covariance between sleep EEG and cognition than health variables, and consequently reduce this association by a greater degree, but even with the strictest covariate sets a statistically significant association is present. Sigma power in NREM and beta power in REM sleep were associated with better cognitive performance, while theta power in REM sleep was associated with worse performance, with no substantial effect of coherence and other sleep EEG metrics. Our findings show that cognitive performance is associated with the sleep EEG (r = 0.283), with the strongest effect ascribed to spindle-frequency activity. This association becomes weaker after adjusting for demographic (r = 0.186) and health variables (r = 0.155), but its resilience to covariate inclusion suggest that it also partially reflects trait-like differences in cognitive ability.
Identifiants
pubmed: 37574121
pii: S1053-8119(23)00470-6
doi: 10.1016/j.neuroimage.2023.120319
pmc: PMC10661862
mid: NIHMS1942284
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
120319Subventions
Organisme : NHLBI NIH HHS
ID : R01 HL070848
Pays : United States
Organisme : NHLBI NIH HHS
ID : R01 HL071194
Pays : United States
Organisme : NHLBI NIH HHS
ID : R01 HL070847
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1 TR002369
Pays : United States
Organisme : NIA NIH HHS
ID : R01 AG070867
Pays : United States
Organisme : NIA NIH HHS
ID : U01 AG042145
Pays : United States
Organisme : NIA NIH HHS
ID : U01 AG042168
Pays : United States
Organisme : NHLBI NIH HHS
ID : R01 HL070841
Pays : United States
Organisme : NHLBI NIH HHS
ID : R24 HL114473
Pays : United States
Organisme : NHLBI NIH HHS
ID : R01 HL070839
Pays : United States
Organisme : NIA NIH HHS
ID : U01 AG027810
Pays : United States
Organisme : NIA NIH HHS
ID : U01 AG042139
Pays : United States
Organisme : NIAMS NIH HHS
ID : U01 AR066160
Pays : United States
Organisme : NHLBI NIH HHS
ID : R01 HL070842
Pays : United States
Organisme : NIA NIH HHS
ID : R01 AG066671
Pays : United States
Organisme : NIA NIH HHS
ID : U01 AG042124
Pays : United States
Organisme : NIA NIH HHS
ID : U01 AG042140
Pays : United States
Organisme : NHLBI NIH HHS
ID : R01 HL070838
Pays : United States
Organisme : NHLBI NIH HHS
ID : R01 HL070837
Pays : United States
Organisme : NIA NIH HHS
ID : U01 AG042143
Pays : United States
Informations de copyright
Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of Competing Interest None.
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