Literature DB >> 22228797

Adaptation to sensory-motor reflex perturbations is blind to the source of errors.

Todd E Hudson1, Michael S Landy.   

Abstract

In the study of visual-motor control, perhaps the most familiar findings involve adaptation to externally imposed movement errors. Theories of visual-motor adaptation based on optimal information processing suppose that the nervous system identifies the sources of errors to effect the most efficient adaptive response. We report two experiments using a novel perturbation based on stimulating a visually induced reflex in the reaching arm. Unlike adaptation to an external force, our method induces a perturbing reflex within the motor system itself, i.e., perturbing forces are self-generated. This novel method allows a test of the theory that error source information is used to generate an optimal adaptive response. If the self-generated source of the visually induced reflex perturbation is identified, the optimal response will be via reflex gain control. If the source is not identified, a compensatory force should be generated to counteract the reflex. Gain control is the optimal response to reflex perturbation, both because energy cost and movement errors are minimized. Energy is conserved because neither reflex-induced nor compensatory forces are generated. Precision is maximized because endpoint variance is proportional to force production. We find evidence against source-identified adaptation in both experiments, suggesting that sensory-motor information processing is not always optimal.

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Year:  2012        PMID: 22228797      PMCID: PMC3267976          DOI: 10.1167/12.1.4

Source DB:  PubMed          Journal:  J Vis        ISSN: 1534-7362            Impact factor:   2.240


  34 in total

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Authors:  R A Scheidt; J B Dingwell; F A Mussa-Ivaldi
Journal:  J Neurophysiol       Date:  2001-08       Impact factor: 2.714

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Journal:  Nature       Date:  2004-01-15       Impact factor: 49.962

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Authors:  David Whitney; David A Westwood; Melvyn A Goodale
Journal:  Nature       Date:  2003-06-19       Impact factor: 49.962

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Authors:  David W Franklin; Udell So; Mitsuo Kawato; Theodore E Milner
Journal:  J Neurophysiol       Date:  2004-06-16       Impact factor: 2.714

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Authors:  Toshitaka Kimura; Patrick Haggard; Hiroaki Gomi
Journal:  J Neurosci       Date:  2006-09-06       Impact factor: 6.167

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Journal:  J Neurosci       Date:  1994-05       Impact factor: 6.167

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Authors:  J R Lackner; P Dizio
Journal:  J Neurophysiol       Date:  1994-07       Impact factor: 2.714

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Journal:  Brain Res       Date:  1984-10-08       Impact factor: 3.252

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Authors:  L M Optican; F A Miles
Journal:  J Neurophysiol       Date:  1985-10       Impact factor: 2.714

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Authors:  L M Nashner
Journal:  Exp Brain Res       Date:  1976-08-27       Impact factor: 1.972

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  1 in total

1.  Did I do that? Detecting a perturbation to visual feedback in a reaching task.

Authors:  Elon Gaffin-Cahn; Todd E Hudson; Michael S Landy
Journal:  J Vis       Date:  2019-01-02       Impact factor: 2.240

  1 in total

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