Ran Yuchen, Fan Yingwei, Wu Shuang, Chen Chao, Li Yangxi, Gao Tianxin, Zhang Houdi, Han Cong, Tang Xiaoying
School of Medical Technology, Beijing Institute of Technology, Beijing, 100081, China.
Department of Biomedical Engineering, School of Medicine, Tsinghua Univerisity, Beijing, 100084, China.
Transl Stroke Res. 2024 Dec 5. doi: 10.1007/s12975-024-01313-1.
Cognitive impairment in patients with moyamoya disease (MMD) manifests earlier than clinical symptoms. Early identification of brain connectivity changes is essential for uncovering the pathogenesis of cognitive impairment in MMD. We proposed a temporally driven canonical correlation analysis (TdCCA) method to achieve dual-modal synchronous information fusion from electroencephalogram (EEG) and functional near-infrared spectroscopy (fNIRS) for exploring the differences in brain connectivity between MMD and normal control groups. The dual-modal fusion features were extracted based on the imaginary part of coherence of the EEG signal (EEG iCOH) and the Pearson correlation coefficients of the fNIRS signal (fNIRS COR) in the resting and working memory state. The machine learning model showed that the accuracy of TdCCA method reached 97%, far higher than single-modal features and feature-level fusion CCA method. Brain connectivity analysis revealed a significant reduction in the strength of the connections between the right occipital lobe and frontal lobes (EEG iOCH: p = 0.022, fNIRS COR p = 0.011) in MMD. These differences reflected the impaired transient memory and executive function in MMD patients. This study contributes to the understanding of the neurophysiological nature of cognitive impairment in MMD and provides a potential adjuvant early identification method for individuals with chronic cerebral ischemia.
烟雾病（MMD）患者的认知障碍比临床症状出现得更早。早期识别大脑连接变化对于揭示MMD认知障碍的发病机制至关重要。我们提出了一种时间驱动的典型相关分析（TdCCA）方法，以实现来自脑电图（EEG）和功能近红外光谱（fNIRS）的双模态同步信息融合，用于探索MMD组和正常对照组之间大脑连接的差异。基于静息和工作记忆状态下EEG信号相干性的虚部（EEG iCOH）和fNIRS信号的Pearson相关系数（fNIRS COR）提取双模态融合特征。机器学习模型表明，TdCCA方法的准确率达到97%，远高于单模态特征和特征级融合CCA方法。大脑连接分析显示，MMD患者右侧枕叶与额叶之间的连接强度显著降低（EEG iOCH：p = 0.022，fNIRS COR p = 0.011）。这些差异反映了MMD患者的瞬时记忆和执行功能受损。本研究有助于理解MMD认知障碍的神经生理本质，并为慢性脑缺血个体提供一种潜在的辅助早期识别方法。
