Resting-State EEG Reveals Abnormal Microstates Characteristics of Depression with Insomnia

Abstract

Abstract Background: Previous research has revealed various aspects of resting-state EEG for depression and insomnia. However, the EEG characteristics of depressed patients with co-morbid insomniac are rarely studied, especially EEG microstates that capture the dynamic activities of the large-scale brain network. Methods:To fill the research gaps, this study collected resting-state EEG data from 32 sub-clinical depressions with co-morbid insomnia (CI), 31 comorbid-free depressions (CFD), and 32 healthy controls (HC). Four topographic maps were generated from clean EEG data after clustering and rearrangement. Temporal characteristics were obtained for statistical analysis, including cross-group variance analysis (ANOVA) and intra-group correlation analysis. Results: The global clustering of all individuals in the EEG microstate analysis revealed the four previously discovered categories of microstates (A, B, C, and D). The occurrence of microstate B was found to be lower in CI than in CFD. The correlation analysis showed that the total PSQI score was negatively correlated with the occurrence of microstate C in CI (r=-0.354, p<.05). Conversely, there was a positive correlation between SDS scores and the duration of microstate C in CFD (r=0.359, p<.05). Conclusion: The spatiotemporal dynamics of the brain network can vary due to abnormalities in the visual network corresponding to microstate B in patients with depression and insomnia.. Further investigation is needed for microstate change can be related to high arousal and emotional problems in people suffering from depression and insomnia. Microstates may therefore become crucial neurobiological predictors to forecast the likelihood of future cases of depression and insomnia.