Neural network control of simple limb movements
Hon C. Kwan, Tet Hin Yeap, Bai C. Jiang, Donald S. Borrett · Canadian Journal of Physiology and Pharmacology · 1990
It is possible to embed the control and computation of a simple single-joint movement at different speeds by a small non-linear network of neuron-like elements. The network "learns" by appropriate adjustment of the strengths of interconnection, or synaptic weights, between the neuron-like elements. The learning of a few movement trajectories is generalized to the learning of a family of unlearned trajectories. These observations are in support of our hypothesis that relaxation of a network from an initial state to a final equilibrium state is both causal and computational to movement generation and control.