Sleep deprivation changes frequency-specific functional organization of the resting human brain
BRAIN RESEARCH BULLETIN(2024)
Abstract
Previous resting -state functional magnetic resonance imaging (rs-fMRI) studies have widely explored the temporal connection changes in the human brain following long-term sleep deprivation (SD). However, the frequency -specific topological properties of sleep -deprived functional networks remain virtually unclear. In this study, thirty-seven healthy male subjects underwent resting -state fMRI during rested wakefulness (RW) and after 36 hours of SD, and we examined frequency -specific spectral connection changes (0.01 - 0.08 Hz, interval = 0.01 Hz) caused by SD. First, we conducted a multivariate pattern analysis combining linear SVM classifiers with a robust feature selection algorithm, and the results revealed that accuracies of 74.29%-84.29% could be achieved in the classification between RW and SD states in leave -one -out cross -validation at different frequency bands, moreover, the spectral connection at the lowest and highest frequency bands exhibited higher discriminative power. Connection involving the cingulo-opercular network increased most, while connection involving the default -mode network decreased most following SD. Then we performed a graph -theoretic analysis and observed reduced low -frequency modularity and high -frequency global efficiency in the SD state. Moreover, hub regions, which were primarily situated in the cerebellum and the cingulo-opercular network after SD, exhibited high discriminative power in the aforementioned classification consistently. The findings may indicate the frequency -dependent effects of SD on the functional network topology and its efficiency of information exchange, providing new insights into the impact of SD on the human brain.
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Key words
Sleep deprivation,Spectral connection,Robust feature selection,Cerebellum,Topology,Frequency specificity
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