Effects of poor sleep quality on brain functional connectivity revealed by wavelet-based coherence analysis using NIRS methods in elderly subjects

Abstract

ObjectivePoor sleep quality, which is typically related to impairments in cognitive control, is pervasive among the elderly. However, the brain function mechanisms underlying the association between sleep and elderly behavior remain elusive. This study aims to assess the effects of poor sleep quality on low-frequency neural oscillations based on the wavelet phase coherence (WPCO) and wavelet amplitude (WA) of oxyhemoglobin concentration changes (Delta [HbO2]) measured through near-infrared spectroscopy (NIRS) method. MethodsSubjective sleep quality was measured through the Pittsburgh Sleep Quality Index (PSQI). Continuously recorded NIRS signals from the prefrontal cortex, sensorimotor cortical, and occipital lobes of 15 poor-sleep-quality elderly subjects (PSQ group) as well as 14 healthy elderly subjects (control group) in the resting and task states. The WPCO and WA values were calculated in low frequency (0.01–0.08 Hz). Pearson correlation analysis was used to assess the respective degrees of correlation between the WPCO of bilateral prefrontal lobes, WA of left prefrontal cortex (LPFC), WA of right prefrontal cortex (RPFC), F1 scores, and PSQI scores, respectively. ResultsThe WPCO values were significantly lower in the PSQ group than in the control group (p < 0.05). Compared with the control group, the WA was significantly higher in the PSQ group and was also significantly higher in the resting state than in the task state. The F1 scores were significantly lower in the PSQ group when performing 1-back task. In the PSQ group, the correlation analysis showed the negative correlation between the PSQI scores and WPCO values. The WA values of LPFC and RFFC exhibited positive correlations with the PSQI scores. ConclusionsCollectively, these results suggest that poor sleep reduces phase synchronization, which may contribute to the diminished cognitive functions among the sample population.