Motor Control Models: Learning and Performance

Abstract

The focus of the article is on the variety of attempts that have been investigated for capturing the complexity of purposive action and adaptive behavior, having defined a coordinated action as a class of movements plus a goal. Redundancy is a side effect of this connection, and thus redundancy is necessarily task oriented, something to be managed ‘online’ and rapidly updated as the action unfolds. The article then analyzes two main computational mechanisms that have been proposed as candidates of how the brain may deal with motor redundancy: (1) the force-field-based solution known as Equilibrium-Point Hypothesis (EPH) and (2) the cost-function-based solution to the degrees of freedom problem, namely Optimal Control Theory. However, both theories apply only to overt actions where force fields and cost functions are directly related to the interaction of the body with the physical world in the course of a real action. Considering that overt actions are just the tip of the iceberg, hiding the vast domain of covert actions that are the skeleton of motor cognition, an extension of EPH is described, Passive Motion Paradigm (PMP). The relationships between PMP, the simulation theory of covert actions, internal models, and the body schema concept are also analyzed. Finally, general learning mechanisms that may support the acquisition of internal computational modules are briefly summarized.