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A motor learning strategy reflects neural circuitry for limb control

Nature Neuroscience volume 6, pages 399–403 (2003)Cite this article

Abstract

During motor skill acquisition, the brain learns a mapping between intended limb motion and requisite muscular forces. We propose that regions where sensory and motor representations overlap are crucial for motor learning. In primary motor cortex, for example, cells that modulate their activity for motor actions at a joint tend to receive input from that same portion of the periphery. We predict that this correspondence reflects a default strategy—a Bayesian prior—in which subjects tend to associate loads at a joint with motion at that joint (local sensorimotor association) when there is ambiguity regarding the nature of the load. As predicted, we found that in the presence of uncertainty, humans inappropriately generalized elbow loads as though they were based on elbow velocity. Generalization improved when we reduced uncertainty by decreasing coupling between elbow velocity and load during training. These results illustrate a key link between motor learning and the underlying neural circuitry.

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Figure 1: The experimental apparatus, target locations and load types.
Figure 2: Reaching movements to the training target with the viscous (left, blue) and interaction (right, red) loads.
Figure 3: Results from the generalization phase of experiment 1.
Figure 4: Changes in elbow motion during training influences generalization of interaction loads.

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Acknowledgements

The authors would like to thank D.M. Wolpert and J.R. Flanagan for valuable comments on the manuscript. Financial support was provided by the Natural Sciences and Engineering Research Council and start-up funds from the Faculty of Health Sciences at Queen's University. Salary funding was provided by a Canadian Institutes of Health Research (CIHR) Doctoral Award to K.S. and a CIHR Scholar Award to S.H.S.

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  1. Department of Anatomy & Cell Biology, CIHR Group in Sensory-Motor Systems, Centre for Neuroscience Studies, Queen's University, Kingston, K7L 3N6, Ontario, Canada

    Kan Singh & Stephen H. Scott

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  1. Kan Singh
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Correspondence to Stephen H. Scott.

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S.H.S. holds a US patent for the robotic device used in these experiments.

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Singh, K., Scott, S. A motor learning strategy reflects neural circuitry for limb control. Nat Neurosci 6, 399–403 (2003). https://doi.org/10.1038/nn1026

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