Abstract
Movement planning is thought to be primarily determined by motor costs such as inaccuracy and effort. Solving for the optimal plan that minimizes these costs typically leads to specifying a time-varying feedback controller which both generates the movement and can optimally correct for errors that arise within a movement. However, the quality of the sensory feedback during a movement can depend substantially on the generated movement. We show that by incorporating such state-dependent sensory feedback, the optimal solution incorporates active sensing and is no longer a pure feedback process but includes a significant feedforward component. To examine whether people take into account such state-dependency in sensory feedback we asked people to make movements in which we controlled the reliability of sensory feedback. We made the visibility of the hand state-dependent, such that the visibility was proportional to the component of hand velocity in a particular direction. Subjects gradually adapted to such a sensory perturbation by making curved hand movements. In particular, they appeared to control the late visibility of the movement matching predictions of the optimal controller with state-dependent sensory noise. Our results show that trajectory planning is not only sensitive to motor costs but takes sensory costs into account and argues for optimal control of movement in which feedforward commands can play a significant role.
Highlights
Despite the abundance in the degrees of freedom of the human body, our movements occupy a very small subset of all possible movements, showing remarkably stereotypical patterns of motion for a given task
Our results show that the inclusion of such uncertainty requires both a feedback controller, as is typical, and the addition of a feedforward controller
The second experiment demonstrated that the planned movements were sensitive to subtle changes in the sensory feedback so that subjects produced movements with higher curvature in order to obtain similar levels of visual feedback
Summary
Despite the abundance in the degrees of freedom of the human body, our movements occupy a very small subset of all possible movements, showing remarkably stereotypical patterns of motion for a given task. An optimal controller that minimizes the overall cost generally has a purely feedback form, called an optimal feedback controller, where the sensory information obtained during the execution is exploited online to determine the motor output [3,4,5]. These time-varying feedback controllers both generate the movement and optimally correct for any variability that arises from sources such as noise. This concept of optimal feedback control has been successfully linked to the neural control of movement [for reviews see 2,6]
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