Motion state-dependent motor learning based on explicit visual feedback is quickly recalled, but is less stable than adaptation to physical perturbations
Author:
Affiliation:
1. Department of Neurobiology, Physiology and Behavior, University of California, Davis, California
2. Department of Neurology, University of California, Davis, California
Abstract
Funder
NSF | ENG | Division of Chemical, Bioengineering, Environmental, and Transport Systems
Publisher
American Physiological Society
Subject
Physiology,General Neuroscience
Link
https://journals.physiology.org/doi/pdf/10.1152/jn.00520.2021
Reference92 articles.
1. The 24-h savings of adaptation to novel movement dynamics initially reflects the recall of previous performance
2. The decay of motor adaptation to novel movement dynamics reveals an asymmetry in the stability of motion state-dependent learning
3. Linear Hypergeneralization of Learned Dynamics Across Movement Speeds Reveals Anisotropic, Gain-Encoding Primitives for Motor Adaptation
4. The training schedule affects the stability, not the magnitude, of the interlimb transfer of learned dynamics
5. Adaptive representation of dynamics during learning of a motor task
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