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 used for real-time device
control, rats were trained to position a robot arm to obtain
water by pressing a lever. Mathematical transformations,
including neural networks, converted multineuron signals into
'neuronal population functions' that accurately predicted lever
trajectory. Next, these functions were electronically converted
into real-time signals for robot arm control. After switching to
this 'neurorobotic' mode, 4 of 6 animals (those with > 25 task-
related neurons) routinely used these brain-derived signals to
position the robot arm and obtain water. With continued training
in neurorobotic mode, the animals' lever movement diminished or
stopped. These results suggest a possible means for movement
restoration in paralysis patients.