Controlling precise movement with stochastic signals
In a noisy system, such as the nervous system, can movements be precisely controlled as experimentally demonstrated? We point out that the existing theory of motor control fails to provide viable solutions. However, by adopting a generalized approach to the nonconvex optimization problem with the Young measure theory, we show that a precise movement control is possible even with stochastic control signals. Numerical results clearly demonstrate that a considerable significant improvement of movement precisions is achieved. Our generalized approach proposes a new way to solve optimization problems in biological systems when a precise control is needed.
young measure movement control neural control noncovnex optimization