Literature DB >> 17925258

Trial-by-trial motor adaptation: a window into elemental neural computation.

Kurt A Thoroughman1, Michael S Fine, Jordan A Taylor.   

Abstract

How does the brain compute? To address this question, mathematical modelers, neurophysiologists, and psychophysicists have sought behaviors that provide evidence of specific neural computations. Human motor behavior consists of several such computations [Shadmehr, R., Wise, S.P. (2005). MIT Press: Cambridge, MA], such as the transformation of a sensory input to a motor output. The motor system is also capable of learning new transformations to produce novel outputs; humans have the remarkable ability to alter their motor output to adapt to changes in their own bodies and the environment [Wolpert, D.M., Ghahramani, Z. (2000). Nat. Neurosci., 3: 1212-1217]. These changes can be long term, through growth and changing body proportions, or short term, through changes in the external environment. Here we focus on trial-by-trial adaptation, the transformation of individually sensed movements into incremental updates of adaptive control. These investigations have the promise of revealing important basic principles of motor control and ultimately guiding a new understanding of the neuronal correlates of motor behaviors.

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Year:  2007        PMID: 17925258     DOI: 10.1016/S0079-6123(06)65023-1

Source DB:  PubMed          Journal:  Prog Brain Res        ISSN: 0079-6123            Impact factor:   2.453


  12 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.  Emotion and reward are dissociable from error during motor learning.

Authors:  Sara B Festini; Stephanie D Preston; Patricia A Reuter-Lorenz; Rachael D Seidler
Journal:  Exp Brain Res       Date:  2016-01-09       Impact factor: 1.972

Review 3.  Neuromechanics of muscle synergies for posture and movement.

Authors:  Lena H Ting; J Lucas McKay
Journal:  Curr Opin Neurobiol       Date:  2008-03-04       Impact factor: 6.627

4.  Contextual cuing contributes to the independent modification of multiple internal models for vocal control.

Authors:  Dwayne Keough; Jeffery A Jones
Journal:  J Neurophysiol       Date:  2011-02-23       Impact factor: 2.714

5.  Trial-to-trial dynamics and learning in a generalized, redundant reaching task.

Authors:  Jonathan B Dingwell; Rachel F Smallwood; Joseph P Cusumano
Journal:  J Neurophysiol       Date:  2012-10-10       Impact factor: 2.714

6.  Recalibration of auditory space following milliseconds of cross-modal discrepancy.

Authors:  David R Wozny; Ladan Shams
Journal:  J Neurosci       Date:  2011-03-23       Impact factor: 6.167

7.  Dynamic modulation of cerebellar excitability for abrupt, but not gradual, visuomotor adaptation.

Authors:  John E Schlerf; Joseph M Galea; Amy J Bastian; Pablo A Celnik
Journal:  J Neurosci       Date:  2012-08-22       Impact factor: 6.167

8.  Control of vocalization at utterance onset and mid-utterance: different mechanisms for different goals.

Authors:  Colin S Hawco; Jeffery A Jones
Journal:  Brain Res       Date:  2009-04-24       Impact factor: 3.252

9.  Individuals with cerebellar degeneration show similar adaptation deficits with large and small visuomotor errors.

Authors:  John E Schlerf; Jing Xu; Nola M Klemfuss; Thomas L Griffiths; Richard B Ivry
Journal:  J Neurophysiol       Date:  2012-11-28       Impact factor: 2.714

10.  Adaptation to random and systematic errors: Comparison of amputee and non-amputee control interfaces with varying levels of process noise.

Authors:  Reva E Johnson; Konrad P Kording; Levi J Hargrove; Jonathon W Sensinger
Journal:  PLoS One       Date:  2017-03-16       Impact factor: 3.240

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