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Learning from sensory and reward prediction errors during motor adaptation.

Jun Izawa1, Reza Shadmehr

  • 1Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America. jizawa@jhu.edu

Plos Computational Biology
|March 23, 2011
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Summary

Motor learning adapts commands using sensory prediction errors for high-quality feedback and reward prediction errors when feedback is poor. Sensory errors change predictions and generalize broadly, while reward errors generalize locally.

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Area of Science:

  • Neuroscience
  • Motor Control
  • Learning and Memory

Background:

  • Voluntary motor commands result in sensory consequences and subjective utility (reward).
  • Prediction errors arise from discrepancies between predicted and observed motor command consequences.
  • Understanding how these prediction errors drive motor adaptation is crucial.

Purpose of the Study:

  • To investigate the distinct roles of sensory prediction errors and reward prediction errors in motor adaptation.
  • To determine how the quality of sensory feedback influences reliance on different prediction error signals.
  • To explore the generalization patterns and neural changes associated with each type of prediction error.

Main Methods:

  • Utilized a reach adaptation protocol to examine motor command adjustments.
  • Manipulated the quality of sensory feedback to differentiate learning mechanisms.
  • Analyzed changes in motor commands, predicted sensory consequences, and generalization patterns.

Main Results:

  • With high-quality sensory feedback, motor adaptation was primarily driven by sensory prediction errors, leading to broad generalization and updated sensory predictions.
  • As sensory feedback quality degraded, motor adaptation increasingly relied on reward prediction errors, causing local generalization and no change in sensory predictions.
  • A correlation between generalization patterns and sensory remapping suggests individual differences in reliance on prediction error types.

Conclusions:

  • Motor commands adapt based on both sensory and reward prediction errors.
  • Sensory prediction errors are uniquely associated with changes in the neural system that predicts sensory consequences, enabling broad adaptation.
  • The quality of sensory feedback dictates the relative contribution of sensory versus reward prediction errors in motor learning.