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Updated: May 16, 2025

Human Circadian Phenotyping and Diurnal Performance Testing in the Real World
Published on: April 7, 2020
[High individual stability of daytime sleep EEG characteristics in nighttime sleep restriction settings]
A N Puchkova1, O N Tkachenko1, E O Gandina1
1Institute of Higher Nervous Activity and Neurophysiology of the Russian Academy of Sciences, Moscow, Russia.
Objective:
To evaluate the stability of the electroencephalogram (EEG) spectral characteristics of daytime sleep with moderate nighttime sleep deprivation.
Material And Methods:
The study included 44 students without sleep disorders. The participants limited the nighttime sleep the day before the experiment to 5 hours; then, polysomnograms of a 90-minute daytime sleep were recorded in three repeated sessions. The obtained records were visually staged by experts. Spectral analysis of the wave amplitudes in the delta, theta, alpha, and sigma ranges and averaging for N1, N2, and N3 sleep phases in each record were performed. Stability was assessed through intra-group correlation coefficient (ICC).
Results:
N1 phase showed moderate individual stability (ICC 0.42-0.52) for all wave amplitudes except the sigma waves (ICC=0.68). In N2 phase, stability was increased: the sigma wave amplitude reached ICC=0.91 and 0.7-0.72 for theta and alpha wave amplitudes. In N3 phase, the delta and theta waves showed high stability (ICC=0.92-0.95). Sigma waves in the N3 phase were less stable. The results were consistent with those obtained for nighttime sleep: the sigma and delta waves were highly stable. Sigma waves (associated with sleep spindles) are most stable in N2; the delta and theta activity in N3. These observations show that despite external impacts, daytime sleep maintains intact individual neurophysiological patterns.
Conclusion:
Daytime sleep demonstrates significant stability in the EEG spectral characteristics, especially in the deeper phases. Single EEG recording can be used in assessing individual sleep patterns, which is important for developing personalized approaches to improve the effects of sleep deprivation.
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