Li Fali, Jiang Lin, Zhang Yangsong, Huang Dongfeng, Wei Xijun, Jiang Yuanling, Yao Dezhong, Xu Peng, Li Hai
The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, 611731 China.
School of Life Science and Technology, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu, 611731 China.
Cogn Neurodyn. 2022 Aug;16(4):757-766. doi: 10.1007/s11571-021-09738-2. Epub 2021 Nov 2.
Hemiplegia is a common dysfunction caused by the brain stroke and leads to movement disability. Although the lateralization of movement-related potential, the event-related desynchronization, and more complicated inter-regional information coupling have been investigated, seldom studies have focused on investigating the dynamic information exchanging among multiple brain regions during motor execution for post-stroke hemiplegic patients. With high temporal-resolution electroencephalogram (EEG), the time-varying network is able to reflect the dynamical complex network modalities corresponding to the movements at a millisecond level. In our present study, the wrist extension experiment was designed, along with related EEG datasets being collected. Thereafter, the corresponding time-varying networks underlying the wrist extension were accordingly constructed by adopting the adaptive directed transfer function and then statistically explored, to further uncover the dynamic network deficits (i.e., motor dysfunction) in post-stroke hemiplegic patients. Results of this study found the effective connectivity between the stroked motor area and other areas decreased in patients when compared to healthy controls; on the contrary, the enhanced connectivity between non-stroked motor areas and other areas, especially the frontal and parietal-occipital lobes, were further identified for patients during their accomplishing the designed wrist extension, which might dynamically compensate for the deficited patients' motor behaviors. These findings not only helped deepen our knowledge of the mechanism underlying the patients' motor behaviors, but also facilitated the real-time strategies for clinical therapy of brain stroke, as well as providing a reliable biomarker to predict the future rehabilitation.
The online version contains supplementary material available at 10.1007/s11571-021-09738-2.
偏瘫是由脑卒引起的常见功能障碍,会导致运动残疾。尽管已经对与运动相关电位的偏侧化、事件相关去同步化以及更复杂的区域间信息耦合进行了研究,但很少有研究关注中风后偏瘫患者运动执行过程中多个脑区之间的动态信息交换。利用高时间分辨率脑电图(EEG),时变网络能够在毫秒级别反映与运动相对应的动态复杂网络模式。在我们目前的研究中,设计了手腕伸展实验,并收集了相关的EEG数据集。此后,通过采用自适应定向传递函数构建了手腕伸展相应的时变网络,并进行了统计探索,以进一步揭示中风后偏瘫患者的动态网络缺陷(即运动功能障碍)。本研究结果发现,与健康对照组相比,患者中风侧运动区与其他区域之间的有效连接减少;相反,在患者完成设计的手腕伸展过程中,进一步发现非中风侧运动区与其他区域,特别是额叶和顶枕叶之间的连接增强,这可能会动态补偿患者受损的运动行为。这些发现不仅有助于加深我们对患者运动行为潜在机制的认识,还促进了脑卒临床治疗的实时策略,以及提供了一个可靠的生物标志物来预测未来的康复情况。
在线版本包含可在10.1007/s11571-021-09738-2获取的补充材料。