Sun Xiaolong, Dai Chunqiu, Wu Xiangbo, Han Tao, Li Qiaozhen, Lu Yixing, Liu Xinyu, Yuan Hua
Department of Rehabilitation Medicine, Xijing Hospital, Air Force Medical University (Fourth Military Medical University), Xi'an, Shaanxi, China.
Med Rev (2021). 2024 May 24;4(6):492-509. doi: 10.1515/mr-2024-0010. eCollection 2024 Dec.
Persistent motor deficits are highly prevalent among post-stroke survivors, contributing significantly to disability. Despite the prevalence of these deficits, the precise mechanisms underlying motor recovery after stroke remain largely elusive. The exploration of motor system reorganization using functional neuroimaging techniques represents a compelling yet challenging avenue of research. Quantitative electroencephalography (qEEG) parameters, including the power ratio index, brain symmetry index, and phase synchrony index, have emerged as potential prognostic markers for overall motor recovery post-stroke. Current evidence suggests a correlation between qEEG parameters and functional motor outcomes in stroke recovery. However, accurately identifying the source activity poses a challenge, prompting the integration of EEG with other neuroimaging modalities, such as functional near-infrared spectroscopy (fNIRS). fNIRS is nowadays widely employed to investigate brain function, revealing disruptions in the functional motor network induced by stroke. Combining these two methods, referred to as integrated fNIRS-EEG, neural activity and hemodynamics signals can be pooled out and offer new types of neurovascular coupling-related features, which may be more accurate than the individual modality alone. By harnessing integrated fNIRS-EEG source localization, brain connectivity analysis could be applied to characterize cortical reorganization associated with stroke, providing valuable insights into the assessment and treatment of post-stroke motor recovery.
持续性运动功能障碍在中风幸存者中极为普遍,是导致残疾的重要因素。尽管这些功能障碍很常见,但中风后运动恢复的确切机制在很大程度上仍不清楚。利用功能神经成像技术探索运动系统重组是一个引人关注但具有挑战性的研究途径。包括功率比指数、脑对称指数和相位同步指数在内的定量脑电图(qEEG)参数已成为中风后整体运动恢复的潜在预后标志物。目前的证据表明,qEEG参数与中风恢复中的功能性运动结果之间存在相关性。然而,准确识别源活动具有挑战性,这促使将脑电图与其他神经成像模态(如功能近红外光谱(fNIRS))相结合。如今,fNIRS被广泛用于研究脑功能,揭示中风引起的功能性运动网络的破坏。将这两种方法结合起来,即集成fNIRS-EEG,可以汇总神经活动和血流动力学信号,并提供新型的神经血管耦合相关特征,这可能比单独使用单一模态更准确。通过利用集成fNIRS-EEG源定位,可以应用脑连接性分析来表征与中风相关的皮质重组,为中风后运动恢复的评估和治疗提供有价值的见解。