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Updated: Aug 19, 2026

Quantifying Infra-slow Dynamics of Spectral Power and Heart Rate in Sleeping Mice
Published on: August 2, 2017
Exploring the differences in neural oscillation mechanisms before and after sleep deprivation
Zitong Cui1, Tiantian Xie2, Yueying Zhou3
12011 College, Nanjing Tech University, Nanjing, China.
Introduction:
Sleep deprivation is widespread in modern society and can impair cognitive function and behavioral performance. However, the neural changes associated with individual differences in vulnerability to sleep loss remain unclear, particularly whether temporal fluctuations in neural oscillations provide information beyond conventional mean spectral measures.
Methods:
We analyzed a publicly available resting-state electroencephalogram (EEG) dataset comprising 64 participants assessed under normal sleep and sleep deprivation conditions, including 28 participants with psychomotor vigilance task (PVT) data. Two oscillatory feature families, mean relative power and the across-epoch variability of relative power, were quantified in the theta, alpha, and beta bands, primarily at the regional level, with channel-level analyses used to further characterize their spatial distribution.
Results:
Theta-band features showed the most pronounced changes after sleep deprivation. In particular, theta power variability increased across widespread scalp regions, whereas changes in mean theta relative power were more spatially restricted. Greater increases in theta power variability in the frontal and centro-temporal regions were associated with greater slowing in PVT median reaction time, and the principal association pattern remained evident in sensitivity analyses. Exploratory sex-related analyses identified a significant sex-by-EEG interaction in the centro-temporal region, indicating different linear EEG-PVT slopes between males and females, although the corresponding difference in Spearman correlation strength was not significant.
Discussion:
Overall, theta power variability may provide complementary information beyond conventional mean spectral measures and may help characterize individual differences in vigilance decline after sleep deprivation.
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