Literature DB >> 17615136

Trial-by-trial transformation of error into sensorimotor adaptation changes with environmental dynamics.

Michael S Fine1, Kurt A Thoroughman.   

Abstract

Humans can rapidly change their motor output to make goal-directed reaching movements in a new environment. Theories that describe this adaptive process have long presumed that adaptive steps scale proportionally with error. Here we show that while performing a novel reaching task, participants did not adopt a fixed learning rule, but instead modified their adaptive response based on the statistical properties of the movement environment. We found that as the directional bias of the force distribution shifted from strongly biased to unbiased, participants transitioned from an adaptive process that scaled proportionally with error to one that adapted to the direction, but not magnitude, of error. Participants also modified their response as the likelihood of the perturbation changed; as the likelihood decreased from 80 to 20% of trials, participants adopted an increasingly disproportional strategy. We propose that people can rapidly switch between learning processes within minutes of experiencing a novel environment.

Entities:  

Mesh:

Year:  2007        PMID: 17615136     DOI: 10.1152/jn.00196.2007

Source DB:  PubMed          Journal:  J Neurophysiol        ISSN: 0022-3077            Impact factor:   2.714


  48 in total

1.  Environmental experience within and across testing days determines the strength of human visuomotor adaptation.

Authors:  Jennifer A Semrau; Amy L Daitch; Kurt A Thoroughman
Journal:  Exp Brain Res       Date:  2011-12-06       Impact factor: 1.972

2.  How does the motor system correct for errors in time and space during locomotor adaptation?

Authors:  Laura A Malone; Amy J Bastian; Gelsy Torres-Oviedo
Journal:  J Neurophysiol       Date:  2012-04-18       Impact factor: 2.714

3.  The nervous system uses nonspecific motor learning in response to random perturbations of varying nature.

Authors:  Kunlin Wei; Daniel Wert; Konrad Körding
Journal:  J Neurophysiol       Date:  2010-09-22       Impact factor: 2.714

4.  Natural error patterns enable transfer of motor learning to novel contexts.

Authors:  Gelsy Torres-Oviedo; Amy J Bastian
Journal:  J Neurophysiol       Date:  2011-09-28       Impact factor: 2.714

5.  Characteristics of Implicit Sensorimotor Adaptation Revealed by Task-irrelevant Clamped Feedback.

Authors:  J Ryan Morehead; Jordan A Taylor; Darius E Parvin; Richard B Ivry
Journal:  J Cogn Neurosci       Date:  2017-02-14       Impact factor: 3.225

6.  Hemispheric specialization for movement control produces dissociable differences in online corrections after stroke.

Authors:  Sydney Y Schaefer; Pratik K Mutha; Kathleen Y Haaland; Robert L Sainburg
Journal:  Cereb Cortex       Date:  2011-08-30       Impact factor: 5.357

7.  Flexible explicit but rigid implicit learning in a visuomotor adaptation task.

Authors:  Krista M Bond; Jordan A Taylor
Journal:  J Neurophysiol       Date:  2015-04-08       Impact factor: 2.714

8.  Changes in performance monitoring during sensorimotor adaptation.

Authors:  Joaquin A Anguera; Rachael D Seidler; William J Gehring
Journal:  J Neurophysiol       Date:  2009-07-15       Impact factor: 2.714

9.  Uncertainty of feedback and state estimation determines the speed of motor adaptation.

Authors:  Kunlin Wei; Konrad Körding
Journal:  Front Comput Neurosci       Date:  2010-05-11       Impact factor: 2.380

10.  Effect before cause: supramodal recalibration of sensorimotor timing.

Authors:  James Heron; James V M Hanson; David Whitaker
Journal:  PLoS One       Date:  2009-11-05       Impact factor: 3.240

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