Zhang Jing, Tang Hui, Zuo Lijun, Liu Hao, Liu Chang, Li Zixiao, Jing Jing, Wang Yongjun, Liu Tao
Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, Beijing, 100191 China.
Department of Neurology, Beijing TianTan Hospital, Capital Medical University, Beijing, 100070 China.
Cogn Neurodyn. 2024 Dec;18(6):3741-3756. doi: 10.1007/s11571-024-10139-4. Epub 2024 Aug 12.
Altered connectivity within complex functional networks has been observed in individuals with post-stroke cognitive impairment (PSCI) and during cognitive tasks. This study aimed to identify a cognitive function network that is responsive to cognitive changes during cognitive tasks and also sensitive to PSCI. To explore the network, we analyzed resting-state fMRI data from 20 PSCI patients and task-state fMRI data from 100 unrelated healthy young adults using functional connectivity analysis. We further employed spectral dynamic causal modeling to examine the effective connectivity among the pivotal regions within the network. Our findings revealed a common cognitive network that encompassed the hub regions 231 in the Subcortical network (SC), 70, 199, 242 in the Frontoparietal network (FP), 214 in the Visual II network, and 253 in the Cerebellum network (CBL). These hubs' effective connectivity, which showed reliable but slight changes during different cognitive tasks, exhibited notable alterations when comparing post-stroke cognitive impairment and improvement statuses. Decreased coupling strengths were observed in effective connections to CBL253 and from SC231 and FP70 in the improvement status. Increased connections to SC231 and FP70, from CBL253 and FP242, as well as from FP199 and FP242 to FP242 were observed in this status. These alterations exhibited a high sensitivity to signs of recovery, ranging from 80 to 100%. The effective connectivity pattern in both post-stroke cognitive statuses also reflected the influence of the MoCA score. This research succeeded in identifying a cognitive network with sensitive effective connectivity to cognitive changes after stroke, presenting a potential neuroimaging biomarker for forthcoming interventional studies.
The online version contains supplementary material available at 10.1007/s11571-024-10139-4.
在患有中风后认知障碍（PSCI）的个体以及认知任务期间，已观察到复杂功能网络内的连接性改变。本研究旨在识别一个对认知任务期间的认知变化有反应且对PSCI敏感的认知功能网络。为了探索该网络，我们使用功能连接分析，分析了20例PSCI患者的静息态功能磁共振成像（fMRI）数据和100名无关健康年轻成年人的任务态fMRI数据。我们进一步采用频谱动态因果模型来检查网络内关键区域之间的有效连接性。我们的研究结果揭示了一个共同的认知网络，该网络包括皮质下网络（SC）中的枢纽区域231、额顶网络（FP）中的70、199、242、视觉II网络中的214以及小脑网络（CBL）中的253。这些枢纽的有效连接性在不同认知任务期间显示出可靠但轻微的变化，在比较中风后认知障碍和改善状态时表现出显著改变。在改善状态下，观察到与CBL253的有效连接以及从SC231和FP70的有效连接的耦合强度降低。在该状态下，观察到从CBL253和FP242以及从FP199和FP242到FP242的连接增加。这些改变对恢复迹象表现出高敏感性，范围为80%至100%。两种中风后认知状态下的有效连接模式也反映了蒙特利尔认知评估量表（MoCA）评分的影响。本研究成功识别出一个对中风后认知变化具有敏感有效连接性的认知网络，为即将开展的干预研究提供了一种潜在的神经影像学生物标志物。
在线版本包含可在10.1007/s11571-024-10139-4获取的补充材料。
