Abstract: Objective To explore the underlying neuroelectrophysiological mechanisms in patients with acute post-stroke accompanying cognitive impairment (APSACI) and to identify the associated specific electroencephalography microstates.
Methods Patients with acute ischemic stroke who were admitted to Tongzhou Campus of Dongzhimen Hospital, Beijing University of Chinese Medicine from October 1, 2024 to June 30, 2025 were consecutively enrolled. According to the MoCA score, patients were divided into two groups: those with a score≥26 were assigned to the acute post-stroke non-cognitive impairment (APSNCI) group, and those with a score<26 were assigned to the APSACI group. Resting-state electroencephalography data were collected to analyze temporal parameters of four typical microstates: duration, occurrence, coverage, and transition probability. Pearson correlation analysis was employed to investigate the associations between these temporal parameters and MoCA scores, and ROC curve analysis was adopted to verify the results with significant correlations.
Results A total of 31 patients with acute ischemic stroke were enrolled in this study, including 14 cases in the APSNCI group (11 males and 3 females) and 17 cases in the APSACI group (13 males and 4 females). There were significant differences between the two groups in the duration of microstate C and D, as well as the occurrence and coverage of microstate D (all P<0.05). After Bonferroni correction, the between-group difference in the duration of microstate D  emained statistically significant (P=0.002). Significant differences were observed in the transition probabilities of microstate A→D, B→C, B→D, and D→B between the two groups (all P<0.05). The duration, occurrence, and coverage of microstate D, as well as the transition probability of microstate D→B showed significant positive correlations with MoCA scores (all P<0.05). The AUC values of duration-D and coverage-D were relatively high, while the AUC value of microstate D→B was relatively low.
Conclusions Patients with APSACI exhibit specific large-scale brain network dysfunctions, particularly involving microstate C/D-related networks, as well as abnormalities in dynamic coordination. Parameters associated with microstate D show significant correlations with the severity of cognitive impairment. Electroencephalography microstate features could serve as potential biomarkers reflecting the neuroelectrophysiological mechanisms of APSACI and assessing its severity of cognitive impairment. These findings are helpful for understanding the pathological basis of APSACI and developing auxiliary diagnostic tools in the future.

Key words: Post-stroke cognitive impairment; Electroencephalography; Microstate

摘要： 目的 探索卒中后急性期伴认知障碍（acute post-stroke accompanying cognitive impairment，APSACI）患者潜在的神经电生理机制，并识别与之相关的特异性脑电图微状态。
方法 连续纳入2024年10月1日—2025年6月30日于北京中医药大学东直门医院通州院区就诊的急性缺血性卒中患者。根据MoCA评分对其进行分组，≥26分纳入卒中后急性期不伴认知障碍（acute post-stroke non-cognitive impairment，APSNCI）组，＜26分纳入APSACI组。采集静息态脑电图数据，分析四类经典微状态的时间参数：持续时间、发生频率、覆盖率及转换概率。利用皮尔逊相关分析探讨时间参数与MoCA评分的相关性，并采用ROC曲线对有显著相关性的结果进行验证。
结果 本研究共纳入31例急性缺血性卒中患者，其中APSNCI组14例（男性11例，女性3例），APSACI组17例（男性13例，女性4例）。两组在微状态C和D的持续时间、微状态D的发生频率及覆盖率方面的差异均具有统计学意义（均P<0.05），经Bonferroni校正后，微状态D的持续时间的组间差异仍具有统计学意义（P=0.002）。两组在微状态A→D、B→C、B→D、D→B的转换概率方面的差异均具有统计学意义（均P<0.05）。微状态D的持续时间、发生频率、覆盖率及微状态D→B的转换概率与MoCA评分均呈正相关（均P<0.05）。微状态D的持续时间和覆盖率的AUC值较高，微状态D→B的AUC值相对较低。
结论 APSACI患者存在特定的大规模脑网络功能障碍（尤其涉及微状态C/D相关网络）及动态协调异常。微状态D相关参数与认知障碍严重程度显著相关。脑电图微状态特征可作为反映APSACI的神经电生理机制，以及评估其认知障碍严重程度的潜在生物标志物，有助于深入理解APSACI的病理基础及未来开发辅助诊断工具。

关键词: 卒中后认知障碍; 脑电图; 微状态