Fifer Matthew S, Mollazadeh Mohsen, Acharya Soumyadipta, Thakor Nitish V, Crone Nathan E
Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21205, USA.
Annu Int Conf IEEE Eng Med Biol Soc. 2011;2011:4584-7. doi: 10.1109/IEMBS.2011.6091135.
Recent studies in primate neurophysiology have focused on decoding multi-joint kinematics from single unit and local field potential recordings. However, the extent to which these results can be generalized to human subjects is not known. We have recorded simultaneous electrocorticographic (ECoG) and hand kinematics in a human subject performing reach-grasp-hold of objects varying in shape and size. All Spectral features in various gamma bands (30-50 Hz, 70-100 Hz and 100-150 Hz frequency bands) were able to predict the time course of grasp aperture with high correlation (max r = 0.80) using as few as one ECoG feature from a single electrode (max r for single feature = 0.75) in single trials without prior knowledge of task timing. These results suggest that the population activity captured with ECoG contains information about coordinated finger movements that potentially can be exploited to control advanced upper limb neuroprosthetics.
最近在灵长类动物神经生理学方面的研究主要集中在从单个神经元和局部场电位记录中解码多关节运动学。然而，这些结果能在多大程度上推广到人类受试者尚不清楚。我们在一名人类受试者执行对形状和大小各异的物体进行伸手抓取握持动作时，同时记录了皮层脑电图（ECoG）和手部运动学。在单次试验中，无需事先了解任务时间，仅使用来自单个电极的最少一个ECoG特征（单个特征的最大相关系数r = 0.75），各个伽马波段（30 - 50赫兹、70 - 100赫兹和100 - 150赫兹频段）中的所有频谱特征都能够以高相关性（最大相关系数r = 0.80）预测抓握孔径的时间进程。这些结果表明，通过ECoG捕获的群体活动包含有关手指协调运动的信息，这些信息有可能被用于控制先进的上肢神经假肢。
