OBJECTIVE: This study aims to investigate the difference between epilepsy comorbid with and without cognitive dysfunction.
METHODS: Participants were classified into patients with epilepsy comorbid cognitive dysfunction (PCCD) and patients with epilepsy without comorbid cognitive dysfunction (nPCCD). Microstate analysis was applied based on 20-channel electroencephalography (EEG) to detect the dynamic changes in the whole brain. The coverage, occurrence per second, duration, and transition probability were calculated.
RESULTS: The occurrence per second and the coverage of microstate B in the PCCD group were higher than that of the nPCCD group. Coverage in microstate D was lower in the PCCD group than in the nPCCD group. In addition, the PCCD group has a higher probability of A to B and B to A transitions and a lower probability of A to D and D to A transitions.
CONCLUSIONS: Our research scrutinizes the disparities observed within EEG microstates among epilepsy patients both with and without comorbid cognitive dysfunction.
CONCLUSIONS: EEG microstate analysis offers a novel metric for assessing neuropsychiatric disorders and supplies evidence for investigating the mechanisms and the dynamic change of epilepsy comorbid cognitive dysfunction.

Microstates have been proposed as topographical maps representing large-scale resting-state networks and have recently been suggested as markers for methamphetamine use disorder (MUD). However, it is unknown whether and how they change after repetitive transcranial magnetic stimulation (rTMS) intervention. This study included a comprehensive subject population to investigate the effect of rTMS on MUD microstates. 34 patients with MUD underwent a 4-week randomized, double-blind rTMS intervention (active=17, sham=17). Two resting-state EEG recordings and VAS evaluations were conducted before and after the intervention period. Additionally, 17 healthy individuals were included as baseline controls. The modified k-means clustering method was used to calculate four microstates (MS-A∼MS-D) of EEG, and the FC network was also analyzed. The differences in microstate indicators between groups and within groups were compared. The durations of MS-A and MS-B microstates in patients with MUD were significantly lower than that in HC but showed significant improvements after rTMS intervention. Changes in microstate indicators were found to be significantly correlated with changes in craving level. Furthermore, selective modulation of the resting-state network by rTMS was observed in the FC network. The findings indicate that changes in microstates in patients with MUD are associated with craving level improvement following rTMS, suggesting they may serve as valuable evaluation markers.

OBJECTIVE: Childhood traumatic experiences greatly influenced the brain network activities of patients with depression, and there is an urgent need to explore the temporal dynamics for these changes. This study aims to investigate the abnormalities of resting-state electroencephalogram (EEG) microstates in eye-open state of depressed adolescents and to explore the correlations between their EEG microstates and the childhood traumatic experience.
METHODS: Using resting-state EEG microstate analysis, we explored the temporal dynamics of brain activity in patients with adolescent depression. This study selected 66 adolescents with depression as a patient group, and 27 healthy adolescents as a healthy control group. A modified k-means clustering algorithm was used to classify the 64-channel resting-state EEG data into different microstates. Independent sample t-tests were used to compare the microstate parameters between the 2 groups and further assciations between these parameters and childhood traumatic experience in patients were explored via using Spearman correlation.
RESULTS: In this study, significant differences were observed in the occurrence and transition probabilities of EEG microstates between the healthy control and the patient group. Notably, there was a statistically significant difference (P<0.05) in the occurrence of microstate A across 2 groups, exhibiting a negative correlation with the emotional abuse component within the childhood trauma scores (Spearman\'s rho=-0.31, P=0.013). Furthermore, patient-specific, non-random transitions from microstate B to A (Spearman\'s rho=-0.30, P=0.015) and C to A (Spearman\'s rho=-0.31, P=0.013) were inversely associated with the scores of emotional abuse factors from childhood trauma in the patient group, showing statistically significant differences when comparing to the healthy controls (P<0.05). Upon stratification into quartiles based on the emotional abuse factor scores, the occurrence of microstate A, as well as the transition rates from microstates B to A and C to A, retained statistical significance following adjustment for multiple comparisons (all P<0.05).
CONCLUSIONS: The abnormal temporal dynamics in brain networks of adolescents with depression are linked to childhood emotional abuse. Those who have suffered severe emotional abuse may show greater impairments in the brain\'s visual and central executive networks. EEG microstate analysis could be a potential tool for detecting adolescent depression with severe childhood trauma.
目的: 童年期创伤经历对抑郁症患者的脑网络活动有显著影响，其时间动力学变化的探究亟待展开。本研究探讨睁眼状态下青少年抑郁症患者静息态脑电微状态的相关指标特征，并分析其与患者童年期创伤经历的相关性，旨在探索童年期创伤对青少年抑郁症患者脑网络动力学的影响。方法: 采用静息态脑电微状态分析探讨青少年抑郁症患者大脑活动的时间动力学特征。选取66例患抑郁症的青少年作为病例组，同期选取27例健康青少年作为健康对照组。选用改良k均值聚类算法，将64通道的静息态脑电数据分类成不同微状态，采用独立样本t检验比较2组间的微状态指标差异，Spearman相关并分析相关指标与患者童年期创伤间的相关性。结果: 健康对照组和病例组在微状态的每秒出现频次及转化率水平差异均有统计学意义(均P<0.05)。2组间在微状态A的每秒出现频次上差异有统计学意义(P<0.05)，且与童年期创伤中的情感虐待因子得分呈负相关(Spearman’s rho=-0.31，P=0.013)；病例组特异性非随机的微状态B→A转化(Spearman’s rho=-0.30，P=0.015)及C→A转化(Spearman’s rho=-0.31，P=0.013)均与童年期情感虐待因子得分呈负相关，并与健康对照组比较差异有统计学意义(均P<0.05)。以情感虐待因子分的高低四分位分组比较，微状态A的每秒出现频次、微状态B→A及C→A转化率3种指标经多重比较校正后差异均有统计学意义(均P<0.05)。结论: 青少年抑郁症的异常脑网络时间动力学特征与童年期情感虐待相关，且经历严重情感虐待的患者在大脑视觉网络、中央执行网络功能上可能存在异常。脑电微状态分析可能具有辅助识别伴严重童年期创伤的青少年抑郁症的作用。.