학술논문
Decoding information about cognitive health from the brainwaves of sleep
Document Type
article
Author
Noor Adra; Lisa W. Dümmer; Luis Paixao; Ryan A. Tesh; Haoqi Sun; Wolfgang Ganglberger; Mike Westmeijer; Madalena Da Silva Cardoso; Anagha Kumar; Elissa Ye; Jonathan Henry; Sydney S. Cash; Erin Kitchener; Catherine L. Leveroni; Rhoda Au; Jonathan Rosand; Joel Salinas; Alice D. Lam; Robert J. Thomas; M. Brandon Westover
Source
Scientific Reports, Vol 13, Iss 1, Pp 1-14 (2023)
Subject
Language
English
ISSN
2045-2322
Abstract
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.