Encoding of forelimb forces by corticospinal tract activity in the rat
Encoding of forelimb forces by corticospinal tract activity in the rat
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DOI：
10.3389/fnins.2014.00062
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发表时间：
2014-05-01
影响因子：
4.3
通讯作者：
Sahin, Mesut
中科院分区：
文献类型：
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作者：
Guo, Yi;Foulds, Richard A.;Sahin, Mesut
为了解决传统脑机接口（BCI）中长期存在的问题，脊髓的外侧降束提供了另一个位置来记录意志运动信号。由于皮质输出汇聚到脊髓降束的最终共同通路，与脊髓的神经界面可能在更小的解剖区域内获得更丰富的意志信息信号。本研究的主要目的是评估从大鼠脊髓皮质脊髓束（CST）提取运动控制信号的可行性。将柔性衬底、多电极阵列（MEA）植入杠杆按压训练大鼠的CST内。这种使用柔性基质MEAs的新方法允许使用当前的植入技术在行为动物中记录长达三周的CST活动。采用时频分析和主成分分析（PCA）对神经信号进行重构。然后使用计算的回归系数来预测其他试验中的等距力。6只动物在垂直方向上的平均测得力与预测值的相关性为0.67，R-2值为0.44。水平方向的力回归不太成功，可能是由于力的振幅较小。高伽马波段以上和附近的神经信号对力的预测贡献最大。本研究结果支持脊髓计算机接口（SCCI）在瘫痪个体中生成指令信号的可行性。
In search of a solution to the long standing problems encountered in traditional brain computer interfaces (BCI), the lateral descending tracts of the spinal cord present an alternative site for taping into the volitional motor signals. Due to the convergence of the cortical outputs into a final common pathway in the descending tracts of the spinal cord, neural interfaces with the spinal cord can potentially acquire signals richer with volitional information in a smaller anatomical region. The main objective of this study was to evaluate the feasibility of extracting motor control signals from the corticospinal tract (CST) of the rat spinal cord. Flexible substrate, multi-electrode arrays (MEA) were implanted in the CST of rats trained for a lever pressing task. This novel use of flexible substrate MEAs allowed recording of CST activity in behaving animals for up to three weeks with the current implantation technique. Time-frequency and principal component analyses (PCA) were applied to the neural signals to reconstruct isometric forelimb forces. Computed regression coefficients were then used to predict isometric forces in additional trials. The correlation between measured and predicted forces in the vertical direction averaged across six animals was 0.67 and R-2 value was 0.44. Force regression in the horizontal directions was less successful, possibly due to the small amplitude of forces. Neural signals above and near the high gamma band made the largest contributions to prediction of forces. The results of this study support the feasibility of a spinal cord computer interface (SCCI) for generation of command signals in paralyzed individuals.