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Association between Slow-Wave Activity from Multi-Night At-Home Wireless EEG Records and Cognitive Performance in Older Adults

  • 0Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Tahir Foundation Building (MD1), 12 Science Drive 2, #13-03, Singapore  117549.
Sleep +

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October 22, 2025

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October 22, 2025

View abstract on PubMed

Summary

This summary is machine-generated.

Nightly variations in sleep slow wave activity (SWA) in older adults impact cognitive function. Reliable at-home EEG recordings show SWA, not N3 duration, is linked to cognition.

Area Of Science

  • Neuroscience
  • Gerontology
  • Sleep Science

Background

  • Cognitive function decline is a concern in aging populations.
  • The relationship between sleep, particularly slow wave sleep (SWA), and cognition in older adults remains unclear.
  • Inconsistent findings highlight the need for reliable, long-term sleep monitoring methods.

Purpose Of The Study

  • To investigate the association between sleep slow wave measures and cognitive function in older adults.
  • To assess the impact of night-to-night variability in sleep electroencephalography (EEG) data on this association.
  • To determine if SWA or N3 duration is more consistently linked to cognitive performance.

Main Methods

  • Utilized 8 nights of at-home EEG recordings from 49 community-dwelling older adults (median age 75.3 years).
  • Measured night-to-night variability using the coefficient of variation (CV) for sleep stages and spectral power (SWA, Theta, Alpha, Sigma).
  • Assessed correlations between stable sleep metrics and multi-domain cognitive performance.

Main Results

  • At-home EEG collection using a wearable headband was feasible and well-accepted by older adults.
  • High night-to-night variability was observed for N3 percentage (CV=47%), while relative SWA showed low variability (CV=3-17%).
  • Relative SWA was significantly associated with global cognitive function, both in averaged (r=0.55) and single-night (r=0.2-0.5) assessments.

Conclusions

  • Wearable EEG devices can reliably capture multi-night sleep data in older adults.
  • Relative SWA demonstrated high intra-individual stability and was robustly associated with cognitive function.
  • N3 duration variability did not show a significant association with cognitive performance, unlike SWA.

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