Dynamic brain-heart-gut coupling during sleep: a continuous physiological signal analysis.

BACKGROUND

Investigating brain-heart-gut coupling during sleep is crucial for understanding the coordinated regulatory mechanisms of multiple systems during sleep. Non-invasive continuous physiological signal acquisition techniques have been widely applied in brain-heart dynamic assessment. However, current research on gut function primarily focuses on gut microbiota, with a lack of systematic investigation into the macroscopic dynamic changes of gut function. This study, therefore, based on multiple non-invasive physiological signals, aims to explore the dynamic changes and underlying mechanisms of brain-heart-gut coupling during sleep.

METHODS

The study enrolled 24 healthy subjects, and collected electroencephalogram (EEG), electrocardiogram (ECG), and bowel sounds (BS) signals during sleep. Through signal processing and spectral analysis, power spectral values of each physiological signal in different frequency bands were extracted. The maximal information coefficient (MIC) method was employed to dynamically monitor and quantitatively analyze the coupling strength of brain-heart-gut during sleep.

RESULTS

The study revealed that the strength of brain-heart-gut coupling significantly varied with sleep stages, showing a gradual weakening trend as sleep deepened. In terms of heart-gut coupling (HGC), the coupling strength between the very low frequency (VLF) band of heart rate variability (HRV) and all BS-derived power sequences was significantly lower than other HRV frequency bands. Regarding brain-heart coupling (BHC), the EEG-beta band showed distinct sleep-stage-dependent coupling characteristics with HRV frequency bands, while the EEG-delta band exhibited higher coupling strength with HRV bands during non-rapid eye movement (NREM) sleep. Additionally, the coupling strength of HGC was significantly higher than that of BGC.

CONCLUSION

This study successfully achieved quantitative assessment of brain-heart-gut coupling during sleep based on continuous physiological signals, revealing specific patterns of coupling strength changes across different sleep stages. This research provides new methodological support for the diagnosis of sleep disorders and functional bowel diseases, holding significant theoretical value and clinical application prospects.