Efficiency moderates the relationship between sleep-onset insomnia and resting-state electroencephalogram microstate

Ding, Xiaoqian; Cao, Fengzhi; Wang, Shenghan; Zhang, Yunshu; Wang, Xinshu; Tang, Rongxiang; Tang, Yi‐Yuan

doi:10.31083/j.jin2102052

Cited by 5 publications

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“…It could be associated with the improvement of body awareness and inner sensory sensitivity in insomniacs. Additionally, there was a signi cant correlation between sleep latency and sleep e ciency and the duration of microstate C (Ding et al, 2022).…”

Section: Introductionmentioning

confidence: 95%

“…Wei et al, 2018), and that duration was positively connected with both sleep latency and sleep e ciency(Ding et al, 2022) ; In the study of depression, it was found that the duration and contribution of microstate C were signi cantly lower in the depression group than in the control group(Zhao et al, 2022). And there was a slight correlation between the time parameter of microstate C and the results of the scales used to measure depression(Murphy et al, 2020;Yan et al, 2021).Studies have revealed a connection between microstate C and the salience network.…”

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confidence: 97%

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

Cao

Wang

et al. 2022

Preprint

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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.

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Section: Introductionmentioning

confidence: 95%