Literature DB >> 35858450

Motor learning without movement.

Olivia A Kim1, Alexander D Forrence2, Samuel D McDougle2,3.   

Abstract

Prediction errors guide many forms of learning, providing teaching signals that help us improve our performance. Implicit motor adaptation, for instance, is thought to be driven by sensory prediction errors (SPEs), which occur when the expected and observed consequences of a movement differ. Traditionally, SPE computation is thought to require movement execution. However, recent work suggesting that the brain can generate sensory predictions based on motor imagery or planning alone calls this assumption into question. Here, by measuring implicit motor adaptation during a visuomotor task, we tested whether motor planning and well-timed sensory feedback are sufficient for adaptation. Human participants were cued to reach to a target and were, on a subset of trials, rapidly cued to withhold these movements. Errors displayed both on trials with and without movements induced single-trial adaptation. Learning following trials without movements persisted even when movement trials had never been paired with errors and when the direction of movement and sensory feedback trajectories were decoupled. These observations indicate that the brain can compute errors that drive implicit adaptation without generating overt movements, leading to the adaptation of motor commands that are not overtly produced.

Entities:  

Keywords:  forward model; mental imagery; predictive coding; supervised learning

Mesh:

Year:  2022        PMID: 35858450      PMCID: PMC9335319          DOI: 10.1073/pnas.2204379119

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   12.779


  65 in total

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3.  Internal models in the cerebellum.

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6.  Explicit and implicit contributions to learning in a sensorimotor adaptation task.

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Review 7.  The Rules of Cerebellar Learning: Around the Ito Hypothesis.

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8.  Movements during sleep reveal the developmental emergence of a cerebellar-dependent internal model in motor thalamus.

Authors:  James C Dooley; Greta Sokoloff; Mark S Blumberg
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9.  Reexposure to a sensorimotor perturbation produces opposite effects on explicit and implicit learning processes.

Authors:  Guy Avraham; J Ryan Morehead; Hyosub E Kim; Richard B Ivry
Journal:  PLoS Biol       Date:  2021-03-05       Impact factor: 8.029

10.  Climbing fibers encode a temporal-difference prediction error during cerebellar learning in mice.

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Journal:  Nat Neurosci       Date:  2015-11-09       Impact factor: 24.884

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  1 in total

1.  Motor learning without movement.

Authors:  Olivia A Kim; Alexander D Forrence; Samuel D McDougle
Journal:  Proc Natl Acad Sci U S A       Date:  2022-07-19       Impact factor: 12.779

  1 in total

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