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Time-Resolved Neural Oscillations Across Sleep Stages: Associations with Sleep Quality and Aging

Passaro, A. D.; Poltorak, A.

2024-12-17 neuroscience
10.1101/2024.12.16.628645 bioRxiv
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Sleep is a fundamental physiological process critical to cognitive function, memory consolidation, emotional regulation, and overall health. This study investigates the relationship between EEG spectral power dynamics and key sleep metrics, including percentage of N3, biological age, percentage of REM, and total sleep time (TST). Using high-resolution spectral analysis, we examine how power across multiple frequency bands (0.1-50 Hz) evolves temporally across sleep stages and influences sleep architecture. Our results reveal an inverse relationship between high-frequency power (sigma, beta, and gamma) during the N1 and N2 stages and the subsequent percentage of N3, suggesting that excessive low-frequency power in N2 may disrupt the smooth progression into deep sleep. Additionally, we identify a negative correlation between low delta power (0.1-0.5 Hz) during N2 and both percentages of N3 and TST, challenging traditional views on the role of delta activity in sleep regulation. These findings advance the understanding of how brain activity across frequencies modulates sleep depth and duration, with implications for addressing age-related sleep declines. Statement of SignificanceThis research highlights novel insights into the relationships between EEG spectral power dynamics and sleep architecture, offering a deeper understanding of how brain activity influences critical sleep metrics such as N3 percentage, REM percentage, and total sleep time. By revealing unexpected findings, such as the inverse relationship between low-frequency power during N2 and N3 duration, this study challenges conventional sleep science paradigms. These findings have significant implications for addressing age-related sleep declines and designing brain-computer interfaces (BCIs) to optimize sleep. By targeting specific frequency bands and leveraging real-time feedback, this work paves the way for personalized, non-invasive sleep modulation therapies, revolutionizing clinical and home-based sleep interventions.

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