Jiang Tianxiao, Jiang Tao, Wang Taylor, Mei Shanshan, Liu Qingzhu, Li Yunlin, Wang Xiaofei, Prabhu Sujit, Sha Zhiyi, Ince Nuri F
IEEE Trans Neural Syst Rehabil Eng. 2017 Apr;25(4):370-379. doi: 10.1109/TNSRE.2016.2647255. Epub 2017 Jan 4.
During awake brain surgeries, electrocorticogram (ECoG) was recorded using a high density electrode grid from the motor cortex of two subjects while they were asked to execute spontaneous hand extension and flexion. Firstly, we characterized the spatio-spectral patterns of high-density ECoG during the hand movements. In both subjects, we observed event related desynchronization (ERD) in low frequency band (LFB: 8-32 Hz) and event related synchronization (ERS) in high frequency band (HFB: 60-200 Hz) where HFB-ERS was more spatially localized and movement specific compared to LFB-ERD. In particular, improved spatial resolution of high density ECoG revealed HFB-ERS patterns with distinct timing in different anatomical regions. A few channels located anterior to the central sulcus were associated with HFB-ERS which started several hundred milliseconds prior to the movement onset. Several channels were associated with HFB-ERS which started close to the movement onset. Most importantly, only a small number of channels in the motor cortex regions exhibited long duration ERS which lasted while the subjects maintained their hand posture. A common spatial pattern (CSP) algorithm fused with linear discriminant analysis (LDA) was used to distinguish between hand extension and flexion at different time points based on subband features. ECoG data recorded from the channels located either anterior or posterior to the central sulcus were tested separately in classification. For both subjects, using channels located in motor area, HFB yielded almost 100% classification accuracy within 150-250 ms after the movement onset. The classification accuracies obtained from sensory areas were poor compared to motor areas and lagged the movement onset. These results suggest that spatial patterns of motor cortex captured with high-density ECoG in HFB can effectively drive a neural prosthetic to perform hand flexion and extension.
在清醒脑部手术期间，使用高密度电极网格记录了两名受试者运动皮层的脑电图（ECoG），同时要求他们进行自发的手部伸展和屈曲动作。首先，我们对手部运动期间高密度ECoG的时空谱模式进行了表征。在两名受试者中，我们均观察到低频带（LFB：8 - 32 Hz）中的事件相关去同步化（ERD）以及高频带（HFB：60 - 200 Hz）中的事件相关同步化（ERS），其中与LFB - ERD相比，HFB - ERS在空间上更具局限性且与运动更具特异性。特别是，高密度ECoG的空间分辨率提高揭示了不同解剖区域中具有不同时间的HFB - ERS模式。位于中央沟前方的少数通道与运动开始前几百毫秒开始的HFB - ERS相关。几个通道与接近运动开始时开始的HFB - ERS相关。最重要的是，运动皮层区域中只有少数通道表现出长时间的ERS，在受试者保持手部姿势时持续存在。一种与线性判别分析（LDA）融合的公共空间模式（CSP）算法用于根据子带特征在不同时间点区分手部伸展和屈曲。从中央沟前后位置的通道记录的ECoG数据在分类中分别进行测试。对于两名受试者，使用位于运动区域的通道，HFB在运动开始后150 - 250毫秒内产生了几乎100%的分类准确率。与运动区域相比，从感觉区域获得的分类准确率较低，且滞后于运动开始时间。这些结果表明，在HFB中用高密度ECoG捕获的运动皮层空间模式可以有效地驱动神经假体执行手部屈曲和伸展动作。
