BACKGROUND: Aberrant functional connectivity is a hallmark of schizophrenia. The precise nature and mechanism of dysconnectivity in schizophrenia remains unclear, but evidence suggests that dysconnectivity is different in wake versus sleep. Microstate analysis uses electroencephalography (EEG) to investigate large-scale patterns of coordinated brain activity by clustering EEG data into a small set of recurring spatial patterns, or microstates. We hypothesized that this technique would allow us to probe connectivity between brain networks at a fine temporal resolution and uncover previously unknown sleep-specific dysconnectivity. METHODS: We studied microstates during sleep in patients with schizophrenia by analyzing high-density EEG sleep data from 114 patients with schizophrenia and 79 control participants. We used a polarity-insensitive k-means analysis to extract a set of 6 microstate topographies. RESULTS: These 6 states included 4 widely reported canonical microstates. In patients and control participants, falling asleep was characterized by a shift from microstates A, B, and C to microstates D, E, and F. Microstate F was decreased in patients during wake, and microstate E was decreased in patients during sleep. The complexity of microstate transitions was greater in patients than control participants during wake, but this reversed during sleep. CONCLUSIONS: Our findings reveal behavioral state-dependent patterns of cortical dysconnectivity in schizophrenia. Furthermore, these findings are largely unrelated to previous sleep-related EEG markers of schizophrenia such as decreased sleep spindles. Therefore, these findings are driven by previously undescribed sleep-related pathology in schizophrenia.
Electroencephalographic Microstates During Sleep and Wake in Schizophrenia.
精神分裂症患者睡眠和清醒状态下的脑电图微状态
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作者:Murphy Michael, Jiang Chenguang, Wang Lei A, Kozhemiako Nataliia, Wang Yining, Wang Jun, Pan Jen Q, Purcell Shaun M
| 期刊: | Biological Psychiatry: Global Open Science | 影响因子: | 3.700 |
| 时间: | 2024 | 起止号: | 2024 Aug 9; 4(6):100371 |
| doi: | 10.1016/j.bpsgos.2024.100371 | ||
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