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Sensorimotor priors are effector dependent.

Cong Yin1, Huijun Wang2,3,4,5, Kunlin Wei2,3,4,5

  • 1Capital University of Physical Education and Sports , Beijing , China.

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|May 16, 2019
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Summary
This summary is machine-generated.

The brain

Keywords:
Bayesian theorylearning ratemotor learningprior learningsensorimotor learning

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Area of Science:

  • Neuroscience
  • Motor Control
  • Computational Neuroscience

Background:

  • Sensorimotor tasks integrate sensory feedback with prior information.
  • Traditional Bayesian models often assume effector independence in prior acquisition.
  • Recent research suggests prior construction is complex and context-dependent.

Purpose of the Study:

  • To investigate whether sensorimotor details, specifically the effector used, influence the construction and utilization of priors.
  • To test the validity of naive Bayesian models in sensorimotor learning with varying effectors.

Main Methods:

  • Designed two visuomotor learning tasks differing only in the effector (reaching vs. wrist rotation).
  • Quantitatively analyzed the influence of prior and feedback uncertainty on performance.
  • Compared prior reliance across different effector conditions.

Main Results:

  • Prior and feedback uncertainty influenced performance as predicted by Bayesian statistics.
  • Subjects exhibited differential reliance on prior information based on the effector used.
  • Over-reliance on prior was observed in the typical reaching condition compared to the wrist condition.

Conclusions:

  • The brain does not employ a single, naive Bayesian prior; prior utilization is effector-dependent.
  • Sensorimotor prior learning is influenced by movement context, such as the effector.
  • Existing naive Bayesian models require extension to account for effector-specific prior modulation.