Abstract

Suicide is a global health problem, and early and accurate identification of suicide attempt individuals has very important clinical significance. Thus the exploration of neurobiological mechanisms underlying suicidal behavior is crucial for systematically preventing suicide. However, the neurophysiological biomarkers for identifying affective disorders with suicidal attempt are remain unknown. Here, we recruited 28 patients with mental disorders from Tianjin Anding Hospital, and the subjects were divided into suicide attempt group (SA=14) and non suicide attempt group (NSA=14) according to whether they had attempted suicide. We also recruited 14 healthy subjects matched with age and sex ratio as healthy control group (HC=14). By recording the electroencephalogram(EEG) data of 60 electrodes in resting state for eight minutes (four minutes with open eyes and four minutes with close eyes), the absolute power of five frequency bands( delta(0.5-4Hz), theta(4-8Hz), alpha(8-13Hz), beta (13-30Hz), gamma(30-65Hz)) were analyzed to explore the changes of brain rhythm. And then the Modulation index (MI) was calculated to quantify the intensity of phase amplitude coupling (PAC) between different frequency bands in different brain regions, so as to observe the mechanism of neuronal synchronization in different frequency bands. We found that the absolute power of SA group was significantly higher than NSA group and HC group in delta (P<0.05), beta (P<0.05) and gamma (P<0.05) bands. The PAC strength between beta and gamma was calculated and it showed that the PAC strength of SA group was significantly weaker than NSA group in fronto-central regions, indicating that decreased synchronization between neurons could bring about brain function impairment. These findings suggest that the brain electrical activity in the fronto-central regions of the SA group may be damaged, which may lead to an increased suicidal risk in mental disoders. The EEG activity in delta, beta, gamma band and PAC in fronto-central regions may be used as a potential clinical biomarker for preventing suicide.

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