BackgroundPatients with depressive episode and schizophrenia have a high risk of suicide. The sleep electroencephalogram power spectral density characteristics of patients with depressive episode accompanied by suicidal behavior and those with schizophrenia may be different， but there is currently a lack of direct comparative studies on these two groups of patients. ObjectiveTo compare the sleep electroencephalogram power spectral density between depressive episode and schizophrenic patients with suicidal behavior， in order to provide references for exploring predictive indicators of suicidal behavior. MethodsFrom June 2018 to December 2020， 20 patients with depressive episode and 20 patients with schizophrenia who had committed suicide within the past month and were treated at the outpatient department of Shenzhen Kangning Hospital were selected. All of them met the diagnostic criteria for depressive episode or schizophrenia as defined in the International Classification of Diseases， tenth edition （ICD-10）. Using a random sampling method， 20 volunteers with matching gender and age to the patient groups were selected from the Cuiping community in Shenzhen as the control group. The subjective sleep of the patients was evaluated using the Insomnia Severity Index （ISI）， the Dysfunctional Belief and Attitude about Sleep （DBAS）， the Disturbing Dreams and Nightmare Severity Index （DDNSI）， and the Epworth Somnolence Scale （ESS）. The objective sleep of the patients was assessed using polysomnography. The sleep electroencephalogram was filtered and the power spectral density of the brain wave was analyzed and processed for all the subjects. The subjective and objective sleep conditions of the two patient groups were compared， and the sleep electroencephalogram power spectral density of the patient groups and the control group were also compared. ResultsA comparison of subjective and objective sleep conditions between patients with depressive episode accompanied by suicidal behavior and patients with schizophrenia accompanied by suicidal behavior showed no statistically significant differences （P>0.05）. Comparisons of sleep electroencephalogram power spectral density in the W stage （average power of α wave， total power of δ wave， average power of δ wave， average power of θ wave）， N1 stage （average power of β wave， total power of α wave， total power of δ wave）， N2 stage （total power of α wave， average power of α wave， total power of δ wave， average power of δ wave）， N3 stage （average power of α wave， average power of δ wave）， and R stage （total power of α wave， average power of α wave， total power of δ wave， average power of δ wave） between patients with depressive episode accompanied by suicidal behavior， patients with schizophrenia accompanied by suicidal behavior， and the control group showed statistically significant differences （P<0.05 or 0.01）. The total power of δ wave in the W stage and the average power of β wave and δ wave in the N1 stage were higher in two patient groups were higher than those of the control group. The total power of α wave and the average power of α wave in the N2 stage were lower than those of the control group， while the average power of δ wave was higher than that of the control group. The average power of α wave in the N3 stage of both patient groups were lower than that of the control group， while the average power of δ wave was higher than that of the control group. The total power and average power of α wave in the R stage were lower than those of the control group， while the total power and average power of δ wave were higher than those of the control group. All the differences were statistically significant. Patients with depressive episode accompanied by suicidal behavior had higher average powers of α wave， δ wave， and θ wave in the W stage compared with the control group， while the total power of α wave in the N1 stage was lower in the former group. All these differences were statistically significant （P<0.05）. ConclusionThe depressive episode patients accompanied by suicidal behavior have highly overlapping sleep electroencephalogram abnormal patterns with those of schizophrenia patients， mainly manifested as a general decrease in α wave power （N2， N3， R stage） and a general increase in δ wave power （W， N1， N2， N3， R stage） as well as β wave power in N1 stage. At the same time， patients with depressive episode accompanied by suicidal behavior also show specific changes， including an increase in the average power of α and θ waves during the wakefulness period （W stage）， and a decrease in the total power of α wave in N1 stage. ［Funded by Guangdong Province High-level Clinical Key Specialty （with supporting funds from Shenzhen City） （number， SZGSP013）； Shenzhen Key Medical Discipline （number， SZXK041）； Shenzhen Clinical Medicine Research Center Project （number， 20210617155253001）］

Aversive memories are the core pathology of many psychiatric disorders (such as posttraumatic stress disorder and depression), often impeding clinical treatment, which requires validated interventions. Animal researches and preclinical human studies have shown that memories are vulnerable after retrieval due to a memory process known as the memory reconsolidation mechanism, and that interventions during this process can potentially rewrite or update memories. The discovery of the reconsolidation mechanism has sparked a wave of research interest in its potential to rewrite aversive memories. This article presents a brief research history and advances in reconsolidation-based interventions, including pharmacological, non-invasive brain stimulation and behavioral interventions, as well as the biological mechanisms of reconsolidation. It is noted that pharmacological, behavioral and non-invasive brain stimulation interventions are all potential approaches for reconsolidation intervention, with propranolol, extinction/exposure therapy and transcranial magnetic stimulation being relatively effective. It is important to consider the differences between laboratory and clinical studies in future clinical translational research, and to overcome the " boundary conditions" of reconsolidation-based intervention in clinical applications, such as duration of memory retrieval, age of memory, individual differences, and so on, which may affect its efficacy.