Learning a visuomotor rotation: simultaneous visual and proprioceptive information is crucial for visuomotor remapping

Abstract

Visuomotor adaptation is mediated by errors between intended and sensory-detected arm positions. However, it is not clear whether visual-based errors that are shown during the course of motion lead to qualitatively different or more efficient adaptation than errors shown after movement. For instance, continuous visual feedback mediates online error corrections, which may facilitate or inhibit the adaptation process. We addressed this question by manipulating the timing of visual error information and task instructions during a visuomotor adaptation task. Subjects were exposed to a visuomotor rotation, during which they received continuous visual feedback (CF) of hand position with instructions to correct or not correct online errors, or knowledge-of-results (KR), provided as a static hand-path at the end of each trial. Our results showed that all groups improved performance with practice, and that online error corrections were inconsequential to the adaptation process. However, in contrast to the CF groups, the KR group showed relatively small reductions in mean error with practice, increased inter-trial variability during rotation exposure, and more limited generalization across target distances and workspace. Further, although the KR group showed improved performance with practice, after-effects were minimal when the rotation was removed. These findings suggest that simultaneous visual and proprioceptive information is critical in altering neural representations of visuomotor maps, although delayed error information may elicit compensatory strategies to offset perturbations.

Fig. 1

a Lateral and top view of the experimental apparatus. b Experimental task was a center-out reaching task with eight 15 cm targets oriented radially around a center start location (open circle) and separated by 45°. c For the generalization session, distance trials consisted of 22.5 cm targets oriented with respect to the baseline start location and workspace trials were oriented with respect to a new start location that was displaced 25 cm to the right of the baseline start circle

Fig. 2

Sample hand-paths for the CFc (top), CFnc (middle) and KR (bottom) groups from the pre-rotation (left), rotation (middle) and post-rotation (right) sessions. For the rotation session, hand-paths from the first (black) and last eight trials (gray) are shown. Gray circles indicate the visually presented targets and open circles represent the locations that would bring the cursor to the targets during the rotation task

Fig. 3

a Initial direction error (top) and variable initial direction error (bottom; means ± standard errors, across subjects) for the CFc (black line), CFnc (gray line) and KR (dotted line) groups, shown for each epoch in the pre-rotation, rotation and post-rotation sessions. While not shown, the generalization session occurred between the rotation and post-rotation sessions. Data highlighted with gray bars are expanded for ease of comparison (right). b Initial direction error (means ± standard errors, across subjects) for four trials (1, 6, 11, 16) from the first epoch of the rotation session for the CFc (black line), CFnc (gray line) and KR (dotted line) groups

Fig. 4

Sample hand-paths for the CFc (top), CFnc (middle) and KR (bottom) groups for the distance trials (left) and workspace trials (right) in the generalization session. Gray circles indicate the visually presented targets and open circles represent the locations that would bring the cursor to the targets during the rotation task

Fig. 5

Angle generalized (left) and variable initial direction error (right; means ± standard errors, across subjects) for the distance (D) and workspace (W) trials in the generalization session, shown for the CFc (black line), CFnc (gray line) and KR (dotted line) groups