PLoS Computational Biology (Sep 2016)

The Statistical Determinants of the Speed of Motor Learning.

  • Kang He,
  • You Liang,
  • Farnaz Abdollahi,
  • Moria Fisher Bittmann,
  • Konrad Kording,
  • Kunlin Wei

DOI
https://doi.org/10.1371/journal.pcbi.1005023
Journal volume & issue
Vol. 12, no. 9
p. e1005023

Abstract

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It has recently been suggested that movement variability directly increases the speed of motor learning. Here we use computational modeling of motor adaptation to show that variability can have a broad range of effects on learning, both negative and positive. Experimentally, we also find contributing and decelerating effects. Lastly, through a meta-analysis of published papers, we verify that across a wide range of experiments, movement variability has no statistical relation with learning rate. While motor learning is a complex process that can be modeled, further research is needed to understand the relative importance of the involved factors.