Optimal task-dependent changes of bimanual feedback control and adaptation

Abstract

The control and adaptation of bimanual movements is often considered to be a function of a fixed set of mechanisms [1, 2]. Here, I show that both feedback control and adaptation change optimally with task goals. Participants reached with two hands to two separate spatial targets (two-cursor condition) or used the same bimanual movements to move a cursor presented at the spatial average location of the two hands to a single target (one-cursor condition). A force field was randomly applied to one of the hands. In the two-cursor condition, online corrections occurred only on the perturbed hand, whereas the other movement was controlled independently. In the one-cursor condition, online correction could be detected on both hands as early as 190 ms after the start. These changes can be shown to be optimal in respect to a simple task-dependent cost function [3]. Adaptation, the influence of a perturbation onto the next movement, also depended on task goals. In the two-cursor condition, only the perturbed hand adapted to a force perturbation [2], whereas in the one-cursor condition, both hands adapted. These findings demonstrate that the central nervous system changes bimanual feedback control and adaptation optimally according to the current task requirements.

Figure 1

Experiment 1 Shows Bilateral Movement Corrections in the One-Cursor Condition (A) In the two-cursor condition, participants reached for two separate targets. In the one-cursor condition, they reached with both hands to move a common cursor to a single target. One of the hands was perturbed with a leftward (red) or rightward (blue) force field or was unperturbed (black). (B) Predicted movement trajectories based on the optimal control policy. (C) Movement trajectories observed in experiment 1, averaged across participants and hands. (D) The y velocity (dashed line) and x velocity (red, blue, and black solid lines) of the perturbed hand. (E and F) The x velocity of the unperturbed hand with (E) and without (F) visual feedback shows the onset of the correction in the one-cursor condition. The shaded area indicates the across-subject standard error (SE).

Figure 2

Task-Dependent Changes in Correction and Adaptation Rates (A) Correction rate, the proportion of initial direction error corrected by the same (black) and other (gray) hand within the same trial. The predicted optimal correction rates are plotted as dotted lines. (B) Adaptation rate, the influence of an initial direction error onto the initial direction of the same (black) and other (gray) hand. Error bars indicate the between-subject standard error of the mean (SEM). (C) For the one-cursor condition only, the between-hand correction rate correlates significantly with the between-hand adaptation rate. Each data point represents one hand of one participant under either the visual-feedback or no-visual-feedback condition.

Figure 3

Endpoint Correlation in Unperturbed Movements (A) Predicted endpoint correlation in the x direction in the two- (blue) and one- (red) cursor condition, with the same simulation parameters as in Figure 1. (B) Predicted time course of the correlation between movement directions. (C) Endpoint correlation of one representative participant in experiment 1. (D) Time course of correlation, averaged across all participants of experiment 1, with the shaded area indicating the SEM.

Figure 4

Experiment 2 Shows Bilateral Adaptation to a Constant Force Field in the One-Cursor Condition The initial direction error of the perturbed hand (A) and unperturbed hand (B) in normal (solid line) and catch (dashed line) trials. Results are averaged across participants, hands, and force fields. Error bars indicate the between-subject standard error of the mean (SEM).