Learning and generalization in an isometric visuomotor task

Author:

Rotella Michele F.1,Nisky Ilana12,Koehler Margaret1,Rinderknecht Mike D.13,Bastian Amy J.45,Okamura Allison M.1

Affiliation:

1. Department of Mechanical Engineering, Stanford University, Stanford, California;

2. Department of Biomedical Engineering, Ben-Gurion University of the Negev, Beer Sheva, Israel;

3. Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland;

4. Kennedy Krieger Institute, The Johns Hopkins University, Baltimore, Maryland; and

5. Department of Neuroscience, The Johns Hopkins School of Medicine, Baltimore, Maryland

Abstract

Adaptation is a prominent feature of the human motor system and has been studied extensively in reaching movements. This study characterizes adaptation and generalization during isometric reaching in which the arm remains stationary and the participant controls a virtual cursor via force applied by the hand. We measured how learning of a visual cursor rotation generalizes across workspace 1) to determine the coordinate system that predominates visual rotation learning, and 2) to ascertain whether mapping type, namely position or velocity control, influences transfer. Participants performed virtual reaches to one of two orthogonal training targets with the applied rotation. In a new workspace, participants reached to a single target, similar to the training target in either hand or joint space. Furthermore, a control experiment measured within-workspace generalization to an orthogonal target. Across position and velocity mappings, learning transferred predominantly in intrinsic (joint) space, although the transfer was incomplete. The velocity mapping resulted in significantly larger aftereffects and broader within-workspace generalization than the position mapping, potentially due to slower peak speeds, longer trial times, greater target overshoot, or other factors. Although we cannot rule out a mixed reference frame in our task, the predominance of intrinsic coding of cursor kinematics in the isometric environment opposes the extrinsic coding of arm kinematics in real reaching but matches the intrinsic coding of dynamics found in prior work. These findings have implications for the design of isometric control systems in human-machine interaction or in rehabilitation when coordinated multi-degree-of-freedom movement is difficult to achieve.

Funder

Stanford University

National Science Foundation

Publisher

American Physiological Society

Subject

Physiology,General Neuroscience

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