Time Restricted Feeding Mitigates High-Fat-Diet Induced Sleep Disruption and Amplifies NREM Substates

The effects of diet quality and timing on sleep quality remain poorly understood, particularly at the level of sleep microarchitecture. Traditional visual scoring captures only coarse sleep stages, overlooking the marked heterogeneity of electroencephalographic (EEG) patterns in non-rapid eye movement (NREM) sleep of mice. Here, we apply a pipeline that combines EEG feature extraction with unsupervised machine-learning-based clustering to resolve discrete NREM substates and ask how a high-fat diet (HFD) and time-restricted feeding (TRF) affect sleep microarchitectures. HFD increases sleep latency and sleep fragmentation; both abnormalities were ameliorated by active phase TRF. Clustering of 10s epochs identified two high-amplitude NREM substates sensitive to TRF: Cluster 1, enriched in low-delta power and peaking early in the light phase (ZT 0-6), consistent with canonical slow-wave sleep, and Cluster 6, characterized by elevated alpha, sigma, and beta power and peaking in the latter half of the light phase (ZT6-12). TRF increases the frequency of both NREM substates, particularly within longer uninterrupted sleep episodes during the light phases. These findings introduce an objective framework for quantifying murine sleep microarchitecture and show that aligning caloric intake with the circadian active window mitigates HFD-induced macro-level sleep disruption while selectively enhancing two physiologically distinct NREM substates.