Real-time prediction of hand trajectory by ensembles of cortical neurons in primates
Real-time prediction of hand trajectory by ensembles of cortical neurons in primates
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DOI：
10.1038/35042582
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发表时间：
2000-11-16
期刊：
影响因子：
64.8
通讯作者：
Nicolelis, MAL
中科院分区：
文献类型：
--
作者：
Wessberg, J;Stambaugh, CR;Nicolelis, MAL
来自大鼠运动皮层的信号可用于控制机器人手臂的一维运动（1）。然而，目前还不清楚是否可以利用皮层信号的实时处理来在机器人设备中再现灵长类动物在太空中到达物体时所使用的复杂手臂运动。在这里，我们记录了大量的神经元，分布在前运动，初级运动和后顶叶皮质区的同时活动，作为非人类灵长类动物进行两个不同的运动任务。通过将线性和非线性算法应用于从每只动物记录的皮层神经元集合活动，获得了一维和三维手臂运动轨迹的准确实时预测。此外，皮质衍生的信号被成功地用于本地和通过互联网对机器人设备进行实时控制。这些结果表明，复杂的假肢机器人手臂运动的长期控制，可以实现简单的实时转换的神经元群体信号来自多个皮层区域的灵长类动物。
Signals derived from the rat motor cortex can be used for controlling one-dimensional movements of a robot arm(1). It remains unknown, however, whether real-time processing of cortical signals can be employed to reproduce, in a robotic device, the kind of complex arm movements used by primates to reach objects in space. Here we recorded the simultaneous activity of large populations of neurons, distributed in the premotor, primary motor and posterior parietal cortical areas, as non-human primates performed two distinct motor tasks. Accurate real-time predictions of one- and three-dimensional arm movement trajectories were obtained by applying both linear and nonlinear algorithms to cortical neuronal ensemble activity recorded from each animal. In addition, cortically derived signals were successfully used for real-time control of robotic devices, both locally and through the Internet. These results suggest that long-term control of complex prosthetic robot arm movements can be achieved by simple real-time transformations of neuronal population signals derived from multiple cortical areas in primates.