Yue Xipeng, Li Ziqiang, Li Ying, Gao Jiahuan, Han Hui, Zhang Ge, Li Xiaochen, Shen Yu, Wei Wei, Bai Yan, Xie Jiapei, Luo Zhi, Zhang Xianchang, Wang Meiyun
Department of Medical Imaging, Zhengzhou University People's Hospital & Henan Provincial People's Hospital, Zhengzhou, China; Academy of Medical Sciences, Zhengzhou University, Zhengzhou, China.
Xinxiang Medical University & Henan Provincial People's Hospital, Zhengzhou & Xinxiang, Henan, China.
Neurosci Lett. 2023 Mar 16;799:137097. doi: 10.1016/j.neulet.2023.137097. Epub 2023 Jan 27.
Post-stroke cognitive impairment (PSCI) is a common symptom following brain stroke, yet the mechanisms remain unknown. This study aimed to investigate alterations of static and dynamic functional network connectivity (sFNC and dFNC) in PSCI patients. We prospectively recruited 17 PSCI patients and 24 Healthy controls (HC). Restingstate fMRI (rs-fMRI) and Mini-Mental State Examination (MMSE) were performed. Independent component analysis combined with sliding-window and K-means clustering approach were applied to examine the FNC among 11 resting-state networks: auditory network (AUDN), left executive control network (lECN), language network (LN), precuneus network (PCUN), right executive control network (rECN), salience network (SN), visuospatial network (VN), dorsal default mode network (dDMN), higher visual network (hVIS), primary visual network (pVIS), and ventral mode network (vDMN). The FNC and dynamic indices (fraction time, mean dwell time, transition number) were calculated. Static and dynamic measures were compared between two groups and the correlation between clinical and imaging indicators was analyzed. For sFNC, PSCI group showed decreased interactions in dDMN-vDMN, vDMN-SN, dDMN-hVIS, AUDN-rECN, and AUDN-VN. For dFNC, we derived 3 states of FNC that occurred repeatedly. Significant group differences were found, including decreased interactions in the AUDN-VN, AUDN-pVIS in state 2 and dDMN-VN in state 3. The mean dwell time in PSCI group was longer in state 1, and negatively correlated with MMSE score. These results demonstrated that PSCI patients are characterized with altered sFNC and dFNC, which could help us explore the neural mechanisms of the PSCI from a new perspective.
中风后认知障碍（PSCI）是脑中风后的常见症状，但其机制尚不清楚。本研究旨在调查PSCI患者静态和动态功能网络连接性（sFNC和dFNC）的变化。我们前瞻性招募了17例PSCI患者和24例健康对照者（HC）。进行了静息态功能磁共振成像（rs-fMRI）和简易精神状态检查表（MMSE）。应用独立成分分析结合滑动窗口和K均值聚类方法来检查11个静息态网络之间的功能网络连接性：听觉网络（AUDN）、左侧执行控制网络（lECN）、语言网络（LN）、楔前叶网络（PCUN）、右侧执行控制网络（rECN）、突显网络（SN）、视觉空间网络（VN）、背侧默认模式网络（dDMN）、高级视觉网络（hVIS）、初级视觉网络（pVIS）和腹侧模式网络（vDMN）。计算了功能网络连接性和动态指标（分数时间、平均停留时间、转换次数）。比较了两组之间的静态和动态测量结果，并分析了临床指标与影像学指标之间的相关性。对于sFNC，PSCI组在dDMN-vDMN、vDMN-SN、dDMN-hVIS、AUDN-rECN和AUDN-VN中的交互作用降低。对于dFNC，我们得出了反复出现的3种功能网络连接状态。发现了显著的组间差异，包括状态2下AUDN-VN、AUDN-pVIS以及状态3下dDMN-VN的交互作用降低。PSCI组在状态1下的平均停留时间更长，且与MMSE评分呈负相关。这些结果表明，PSCI患者具有sFNC和dFNC改变的特征，这有助于我们从新的角度探索PSCI的神经机制。
