ROBOT ARM CONTROL USING CORTICAL MULTINEURONAL RECORDING

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This proposal addresses the possibility of utilizing "motor" information extracted from simultaneous neuronal population recordings in the brain to remedy the loss of motor function associated with paralysis, limb amputation and other neurological conditions. This effort is also scientifically significant because it directly addresses the problem of neural population coding in the brain, and the possibility of controlling such coding through biofeedback. We have recently demonstrated in rats and monkeys the feasibility of using simultaneous neuronal population recordings in the motor cortex to control movement of a robot arm. The rats, in particular, were able to utilize their brain activity to accurately position (in one dimension) the robot arm under a water dropper, and then carry the water drop back to their mouths. Moreover, over continued training in this "neuro-robotic" mode, these animals were able progressively decorrelate this neural activity from the overt movements with which they were normally associated. This proposal has three specific aims: I. To utilize chronic neural ensemble recordings in monkeys to directly control multi-directional robot arm movement. The main issue is whether neuro-robotic feasibility be demonstrated for control of movements in multiple directions and under varying load conditions. II. To develop, implement and optimize new methods for transforming neuronal population activity into realtime neuro-robotic control signals. The main issue is whether simple linear neural population coding algorithms can be used to produce optimal neuro-robotic control functions, or whether nonlinear networks will be necessary. III. To investigate the feasibility of neuro-robotic control after sensorimotor denervation. The main question is whether neuro- robotic control is feasible after paralysis. This will be investigated here in rats subject to reversible denervation or amputation of the forelimb.