Wessberg J, Stambaugh C R, Kralik J D, Beck P D, Laubach M, Chapin J K, Kim J, Biggs S J, Srinivasan M A, Nicolelis M A
Department of Neurobiology, Duke University, Durham, North Carolina 27710, USA.
Nature. 2000 Nov 16;408(6810):361-5. doi: 10.1038/35042582.
Signals derived from the rat motor cortex can be used for controlling one-dimensional movements of a robot arm. 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.
源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。然而，目前尚不清楚是否可以利用皮层信号的实时处理，在机器人设备中重现灵长类动物用于够取空间中物体的复杂手臂运动。在这里，当非人类灵长类动物执行两项不同的运动任务时，我们记录了分布在前运动皮层、初级运动皮层和顶叶后皮层区域的大量神经元的同步活动。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群活动，获得了对一维和三维手臂运动轨迹的准确实时预测。此外，源自皮层的信号成功地用于机器人设备的实时控制，包括本地控制和通过互联网的控制。这些结果表明，通过对源自灵长类动物多个皮层区域的神经元群体信号进行简单的实时转换，可以实现对复杂假肢机器人手臂运动的长期控制。
