Depression is an increasingly prevalent mental health condition. Patients with depression have disrupted rapid eye movement (REM) sleep as characterized by shortened REM latency, increased REM sleep duration, and increased… Click to show full abstract
Depression is an increasingly prevalent mental health condition. Patients with depression have disrupted rapid eye movement (REM) sleep as characterized by shortened REM latency, increased REM sleep duration, and increased REM density. However, it is unknown whether the dynamic patterns of EEG within REM episodes are altered in these patients. Here we investigated the complexity of EEG during REM sleep using the analysis of irregularity on multiple temporal time scales and compared the difference in such a nonlinear property of EEG between patients with depression and controls. We analyzed the overnight EEG recordings (256 Hz) collected from the left central channel in 19 older men with depression and 19 age-matched otherwise healthy control men in the Osteoporotic Fractures in Men Study (MrOS) obtained from the National Sleep Research Resource (NSRR). To quantify the irregularity/complexity in EEG fluctuations during REM, a Multiscale Entropy (MSE) analysis was performed on each 30-second epoch to calculate the entropy at different time scales between ~0.004 and ~0.078 seconds (i.e., 1/256, 2/256, …, 20/256 seconds). As compared to control men, men with depression had significantly lower entropy values at multiple time scales between 0.023-0.031 seconds (time scale =6/256 second: 0.363□0.008 [SE] for depression, 0.408□0.009 for controls; time scale =7/256 second: 0.295□0.009 for depression, 0.342□0.008 for controls; time scale =8/256 second: 0.225□0.009 for depression, 0.269□0.008 for controls; all FDR-adjusted P-values< 0.001), indicating reduced temporal irregularity/complexity in EEG fluctuations. The differences were not statistically significant at smaller or larger time scales. EEG complexity/irregularity within REM sleep were altered in patients with depression. Our results indicate the capability of MSE analysis in capturing important complexity features of EEG fluctuations, which might be missed using those entropy algorithms focused on EEG fluctuations at a single time scale. RF1AG059867, RF1AG064312. The National Heart, Lung, and Blood Institute provided funding for the ancillary MrOS Sleep Study, "Outcomes of Sleep Disorders in Older Men," under the following grant numbers: R01 HL071194, R01 HL070848, R01 HL070847, R01 HL070842, R01 HL070841, R01 HL070837, R01 HL070838, and R01 HL070839. The NSRR was supported by the National Heart, Lung, and Blood Institute (R24 HL114473, 75N92019R002).
               
Click one of the above tabs to view related content.