Literature DB >> 23596337

Cerebellar motor learning: are environment dynamics more important than error size?

Tricia L Gibo1, Sarah E Criscimagna-Hemminger, Allison M Okamura, Amy J Bastian.   

Abstract

Cerebellar damage impairs the control of complex dynamics during reaching movements. It also impairs learning of predictable dynamic perturbations through an error-based process. Prior work suggests that there are distinct neural mechanisms involved in error-based learning that depend on the size of error experienced. This is based, in part, on the observation that people with cerebellar degeneration may have an intact ability to learn from small errors. Here we studied the relative effect of specific dynamic perturbations and error size on motor learning of a reaching movement in patients with cerebellar damage. We also studied generalization of learning within different coordinate systems (hand vs. joint space). Contrary to our expectation, we found that error size did not alter cerebellar patients' ability to learn the force field. Instead, the direction of the force field affected patients' ability to learn, regardless of whether the force perturbations were introduced gradually (small error) or abruptly (large error). Patients performed best in fields that helped them compensate for movement dynamics associated with reaching. However, they showed much more limited generalization patterns than control subjects, indicating that patients rely on a different learning mechanism. We suggest that patients typically use a compensatory strategy to counteract movement dynamics. They may learn to relax this compensatory strategy when the external perturbation is favorable to counteracting their movement dynamics, and improve reaching performance. Altogether, these findings show that dynamics affect learning in cerebellar patients more than error size.

Entities:  

Keywords:  cerebellar ataxia; dynamics; error size; motor learning

Mesh:

Year:  2013        PMID: 23596337      PMCID: PMC3727069          DOI: 10.1152/jn.00745.2012

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


  34 in total

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5.  Motor adaptation as a process of reoptimization.

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6.  Persistence of motor memories reflects statistics of the learning event.

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Journal:  J Neurophysiol       Date:  2009-06-03       Impact factor: 2.714

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  31 in total

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2.  Brain-computer interface: current and emerging rehabilitation applications.

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3.  The cerebellum does more than sensory prediction error-based learning in sensorimotor adaptation tasks.

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Journal:  J Neurophysiol       Date:  2017-06-21       Impact factor: 2.714

4.  Blocking trial-by-trial error correction does not interfere with motor learning in human walking.

Authors:  Andrew W Long; Ryan T Roemmich; Amy J Bastian
Journal:  J Neurophysiol       Date:  2016-02-24       Impact factor: 2.714

5.  Formation of model-free motor memories during motor adaptation depends on perturbation schedule.

Authors:  Jean-Jacques Orban de Xivry; Philippe Lefèvre
Journal:  J Neurophysiol       Date:  2015-02-11       Impact factor: 2.714

6.  Neural correlates of adaptation to gradual and to sudden visuomotor distortions in humans.

Authors:  Susen Werner; Christoph F Schorn; Otmar Bock; Nina Theysohn; Dagmar Timmann
Journal:  Exp Brain Res       Date:  2014-01-22       Impact factor: 1.972

7.  Perturbation schedule does not alter retention of a locomotor adaptation across days.

Authors:  Sara J Hussain; Susanne M Morton
Journal:  J Neurophysiol       Date:  2014-03-19       Impact factor: 2.714

8.  Fast but fleeting: adaptive motor learning processes associated with aging and cognitive decline.

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Journal:  J Neurosci       Date:  2014-10-01       Impact factor: 6.167

9.  Impaired Feedforward Control and Enhanced Feedback Control of Speech in Patients with Cerebellar Degeneration.

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Journal:  J Neurosci       Date:  2017-08-23       Impact factor: 6.167

10.  State-Based Delay Representation and Its Transfer from a Game of Pong to Reaching and Tracking.

Authors:  Guy Avraham; Raz Leib; Assaf Pressman; Lucia S Simo; Amir Karniel; Lior Shmuelof; Ferdinando A Mussa-Ivaldi; Ilana Nisky
Journal:  eNeuro       Date:  2017-12-26
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