4.6 Article

EEG Microstates and Its Relationship With Clinical Symptoms in Patients With Schizophrenia

期刊

FRONTIERS IN PSYCHIATRY
卷 12, 期 -, 页码 -

出版社

FRONTIERS MEDIA SA
DOI: 10.3389/fpsyt.2021.761203

关键词

schizophrenia; clinical symptoms; resting-state; electroencephalogram (EEG); microstates

资金

  1. National Natural Science Foundation of China

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This study identified abnormal EEG microstate patterns in patients with schizophrenia and found that different levels of clinical symptoms severity had varying effects on microstates. Patients with schizophrenia showed increased duration and contribution of microstate class C, decreased contribution and occurrence of microstate class B compared to healthy controls.
Schizophrenia is a complex and devastating disorder with unclear pathogenesis. Electroencephalogram (EEG) microstates have been suggested as a potential endophenotype for this disorder. However, no clear dynamic pattern of microstates has been found. This study aims to identify the dynamics of EEG microstates in schizophrenia and to test whether schizophrenia patients with altered clinical symptoms severity showed different microstates abnormalities compared with healthy controls. Resting-state EEG data in 46 individuals who met the ICD-10 diagnostic criteria for schizophrenia and 39 healthy controls was recorded. The patients with schizophrenia were divided into subgroups based on the level of their negative or positive symptoms assessed using the Positive and Negative Syndrome Scale. Microstate parameters (contribution, occurrence, and duration) of four prototypical microstate classes (A-D) were investigated. Compared with healthy controls, individuals with schizophrenia showed increased duration and contribution of microstate class C, decreased contribution and occurrence of microstate class B. Different microstate patterns were found between subgroups and healthy controls. Results in this study support the consistent observation of abnormal EEG microstates patterns in patients with schizophrenia and highlight the necessity to divide subjects into subgroups according to their clinical symptoms.

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