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The "Motor" in Implicit Motor Sequence Learning: A Foot-stepping Serial Reaction Time Task
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The influence of task outcome on implicit motor learning.

Hyosub E Kim1,2,3,4, Darius E Parvin1,2, Richard B Ivry1,2

  • 1Department of Psychology, University of California, Berkeley, Berkeley, United States.

Elife
|April 30, 2019
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Summary

Task success signals influence sensorimotor adaptation learning. Unexpectedly, hitting the target attenuated implicit motor learning, suggesting task outcome modulates this process differently than previously thought.

Keywords:
adaptationhumanmotor learningneurosciencereachingreward learning

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Area of Science:

  • Neuroscience
  • Motor Control
  • Cognitive Psychology

Background:

  • Task success signals are known to modulate explicit learning in sensorimotor adaptation.
  • The influence of task outcome on implicit motor learning remains less understood.

Purpose of the Study:

  • To investigate how task outcome (hitting or missing a target) affects implicit motor learning during a reaching task.
  • To explore computational models explaining the interaction between task outcome and implicit adaptation.

Main Methods:

  • Participants performed a reaching task with an invariant rotational perturbation.
  • Target size was varied to create conditions where the cursor either hit or missed the target.
  • Computational architectures were evaluated to model the observed learning patterns.

Main Results:

  • Implicit motor learning was significantly attenuated when the cursor successfully hit the target.
  • The findings did not support a model where adaptation runs parallel to a model-free reinforcement process.
  • Task outcome appears to act as a gain modulator or a separate error signal for implicit adaptation.

Conclusions:

  • Task outcome plays a crucial role in modulating implicit sensorimotor adaptation, contrary to prior assumptions focusing on explicit processes.
  • The results suggest a more complex interaction where success signals can actively suppress implicit learning.
  • Further research into computational models is needed to fully elucidate the mechanisms underlying this modulation.