Real-time control of a robot arm using simultaneously recorded neurons in the motor cortex

To determine whether simultaneously recorded motor cortex neurons can be us ed for real-time device control, rats were trained to position a robot arm to obtain water by pressing a lever. Mathematical transformations, includin g neural networks, converted multineuron signals into 'neuronal population functions' that accurately predicted lever trajectory. Next, these function s were electronically converted into real-time signals for robot arm contro l. After switching to this 'neurorobotic' mode, 4 of 6 animals (those with >25 task-related neurons) routinely used these brain-derived signals to pos ition the robot arm and obtain water. With continued training in neurorobot ic mode, the animals' lever movement diminished or stopped. These results s uggest a possible means for movement restoration in paralysis patients.