Human Motor Control and the Internal Model Principle

Abstract: In the motor behavior literature, the observation that humans can learn and adapt to altered limb dynamics is often explained with reference to internal models. Forward internal models enable robust performance even when feedback is intermittent or delayed while inverse models simplify the loop dynamics to manageable form. Internal models of coupled limb/object dynamics, however, do not address the skill with which humans track references or reject disturbances that can be recognized and anticipated. We propose that internal models of reference or disturbance signals create a useful framework for addressing open questions in human motor behavior. We appeal to the Internal Model Principle in control theory, which suggests that a model of the predictable signal (a signal generator) belongs in the controller. When the control loop is already stable, such an internal model will produce perfect tracking or disturbance rejection in steady state. In this paper we apply the Internal Model Principle to hypothesize controllers that elicit cyclic behaviors from systems that feature elastic and inertial energy storage. We also outfit this model with features that describe human neuromuscular dynamics and thereby enable the description of two roles for force feedback: carrying power that couples the human/machine dynamics and carrying information for neural control processing.