Decoding information about cognitive health from the brainwaves of sleep.
Sci Rep
; 13(1): 11448, 2023 07 15.
Article
in En
| MEDLINE
| ID: mdl-37454163
ABSTRACT
Sleep electroencephalogram (EEG) signals likely encode brain health information that may identify individuals at high risk for age-related brain diseases. Here, we evaluate the correlation of a previously proposed brain age biomarker, the "brain age index" (BAI), with cognitive test scores and use machine learning to develop and validate a series of new sleep EEG-based indices, termed "sleep cognitive indices" (SCIs), that are directly optimized to correlate with specific cognitive scores. Three overarching cognitive processes were examined total, fluid (a measure of cognitive processes involved in reasoning-based problem solving and susceptible to aging and neuropathology), and crystallized cognition (a measure of cognitive processes involved in applying acquired knowledge toward problem-solving). We show that SCI decoded information about total cognition (Pearson's r = 0.37) and fluid cognition (Pearson's r = 0.56), while BAI correlated only with crystallized cognition (Pearson's r = - 0.25). Overall, these sleep EEG-derived biomarkers may provide accessible and clinically meaningful indicators of neurocognitive health.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Sleep
/
Brain Waves
Type of study:
Prognostic_studies
Limits:
Humans
Language:
En
Journal:
Sci Rep
Year:
2023
Document type:
Article
Affiliation country: