Journal
CLINICAL EEG AND NEUROSCIENCE
Volume 53, Issue 6, Pages 499-505Publisher
SAGE PUBLICATIONS INC
DOI: 10.1177/15500594211058260
Keywords
schizophrenia; quantitative electroencephalography; electroconvulsive therapy; mutual information; assortativity
Funding
- Shanghai Municipal Health Commission [2019ZB0201]
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This study found through QEEG analysis that in the beta band, the assortativity of the right temporal, right parietal, and right occipital cortex in the response group was significantly higher than that in the non-response group; in the theta band, the assortativity of the left frontal, parietal, right occipital cortex, and central area was higher in the response group compared to the non-response group.
Background: Electroconvulsive therapy (ECT) is a clinically effective treatment for schizophrenia (SZD). However, studies have shown that only about 50 to 80% of patients show response to ECT. To identify the most suitable patients for ECT, developing biomarkers predicting ECT response remains an important goal. This study aimed to explore the quantitative electroencephalography (QEEG) biomarkers to predict ECT efficacy. Methods: Thirty patients who met DSM-5 criteria for SZD and had been assigned to ECT were recruited. 32-lead Resting-EEG recordings were collected one hour before the initial ECT treatment. Positive and negative symptoms scale (PANSS) was assessed at baseline and after the eighth ECT session. EEG data were analyzed using mutual information. Results: In the brain network density threshold range of 0.05 to 0.2, the assortativity of the right temporal, right parietal, and right occipital cortex in the response group was significantly higher than that in the non-response group (p < .05) in the beta band. In the theta band, the left frontal, parietal, right occipital cortex, and central area assortativity were higher in the response group than in the non-response group (p < .05). Conclusions: QEEG might be a useful approach to identify the candidate biomarker for ECT in clinical practice.
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