Literature DB >> 17311491

The contribution of covariation to skill improvement is an ambiguous measure: comment on Müller and Sternad (2004).

Jeroen B J Smeets1, Stefan Louw.   

Abstract

It has been proposed that it is possible to decompose changes in variability of human motor behavior into 3 independent components: covariation, task tolerance, and stochastic noise (H. Müller & D. Sternad). The authors simulate learning to throw accurately and show that for this task the proposed analysis does not give an unambiguous answer to the question of what the 3 components contribute to the simulated skill improvement. It is argued that this is caused by the fact that the component covariation depends on the choice of control variables. The authors conclude that it is not possible to distinguish between the 3 components of noise reduction without knowing the controlled variables.

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Year:  2007        PMID: 17311491     DOI: 10.1037/0096-1523.33.1.246

Source DB:  PubMed          Journal:  J Exp Psychol Hum Percept Perform        ISSN: 0096-1523            Impact factor:   3.332


  6 in total

1.  Variability in motor learning: relocating, channeling and reducing noise.

Authors:  R G Cohen; D Sternad
Journal:  Exp Brain Res       Date:  2008-10-25       Impact factor: 1.972

2.  Coordinate dependence of variability analysis.

Authors:  Dagmar Sternad; Se-Woong Park; Hermann Müller; Neville Hogan
Journal:  PLoS Comput Biol       Date:  2010-04-22       Impact factor: 4.475

Review 3.  Motor learning: changes in the structure of variability in a redundant task.

Authors:  Hermann Müller; Dagmar Sternad
Journal:  Adv Exp Med Biol       Date:  2009       Impact factor: 2.622

4.  Ten guidelines for designing motor learning studies.

Authors:  Rajiv Ranganathan; Mei-Hua Lee; Chandramouli Krishnan
Journal:  Braz J Mot Behav       Date:  2022-06

5.  Directionality in distribution and temporal structure of variability in skill acquisition.

Authors:  Masaki O Abe; Dagmar Sternad
Journal:  Front Hum Neurosci       Date:  2013-06-06       Impact factor: 3.169

6.  A Hessian-based decomposition characterizes how performance in complex motor skills depends on individual strategy and variability.

Authors:  Paolo Tommasino; Antonella Maselli; Domenico Campolo; Francesco Lacquaniti; Andrea d'Avella
Journal:  PLoS One       Date:  2021-06-30       Impact factor: 3.240

  6 in total

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