对于瘫痪病人来说，如果能用意念控制假肢并获得触感，将极大改善生活质量，而这个设想正在逐渐接近现实。一项最新研究已经可以让猴子用意念控制虚拟手臂，而且还能获得反馈给大脑的触感。
英国《自然》杂志网站日前刊登报告说，美国杜克大学等机构研究人员设计出了这样一套系统。他们给猴子大脑中关于运动和触感的部位都接上电极，猴子可以单用意念来控制电脑屏幕上一个虚拟手臂的行动，当手臂碰到屏幕上虚拟的物体时，电极会传给大脑相应的触感信号。实验显示，猴子能够区分屏幕上看起来完全一样但“触感”不同的物体，通过控制虚拟手臂“触摸”指定物体。
过去的类似研究多停留在让猴子用意念控制机械臂等物体的阶段，缺少对大脑的触感反馈。而触感十分重要，比如要握住一个玻璃杯，除了要能够指挥机械臂有“握”的动作以外，还必须要有“握住”的感觉，才能避免杯子掉下或用力过大将其握碎。
因此，研究人员将此前研究中的“大脑－机器”接口模式改进为“大脑－机器－大脑”模式。通过使用这套系统，可以直接把大脑和外部设备联系到一起，用意念来指挥设备的行动并感知外界。
研究人员说，这项研究的最终目的就是能为瘫痪病人提供一套设备，让他们不仅能用大脑意念来控制这些假肢的行动，还能感受到“手”和“脚”上传回的感觉。研究人员还希望在2014年巴西世界杯上展示这套设备，让瘫痪病人在设备的帮助下走进绿茵场，自主地踢动足球。（生物谷 Bioon.com）
doi:10.1038/nature10489
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Active tactile exploration using a brain-machine-brain interface
Joseph E. O’Doherty; Mikhail A. Lebedev; Peter J. Ifft; Katie Z. Zhuang; Solaiman Shokur; Hannes Bleuler; Miguel A. L. Nicolelis
Brain–machine interfaces1, 2 use neuronal activity recorded from the brain to establish direct communication with external actuators, such as prosthetic arms. It is hoped that brain–machine interfaces can be used to restore the normal sensorimotor functions of the limbs, but so far they have lacked tactile sensation. Here we report the operation of a brain–machine–brain interface (BMBI) that both controls the exploratory reaching movements of an actuator and allows signalling of artificial tactile feedback through intracortical microstimulation (ICMS) of the primary somatosensory cortex. Monkeys performed an active exploration task in which an actuator (a computer cursor or a virtual-reality arm) was moved using a BMBI that derived motor commands from neuronal ensemble activity recorded in the primary motor cortex. ICMS feedback occurred whenever the actuator touched virtual objects. Temporal patterns of ICMS encoded the artificial tactile properties of each object. Neuronal recordings and ICMS epochs were temporally multiplexed to avoid interference. Two monkeys operated this BMBI to search for and distinguish one of three visually identical objects, using the virtual-reality arm to identify the unique artificial texture associated with each. These results suggest that clinical motor neuroprostheses might benefit from the addition of ICMS feedback to generate artificial somatic perceptions associated with mechanical, robotic or even virtual prostheses.
