Motor Planning and Sparse Motor Command Representation


The present article proposes a novel computational approach to the motor planning. In this approach, each motor command is represented as a linear combination of prefixed basis patterns, and the command for a given task is designed by minimizing a two-termed criterion consisting of a task optimization term and a parameter preference (i.e., sparseness) term. The result of a computer simulation with a single-joint reaching task confirmed that our "representation-based" criterion for motor planning appropriately worked, together with showing that the resultant trajectory qualitatively replicated Fitts' law.