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Computational Neuroscience Journal Club

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If you have a question about this talk, please contact Daniel McNamee .

Hannah Sheahan will cover:

  • The Statistical Determinants of the Speed of Motor Learning
  • Kang He, You Liang, Farnaz Abdollahi, Moria Fisher Bittmann, Konrad Kording, Kunlin Wei
  • PLoS Computational Biology (September 2016)
  • Link to paper

ABSTRACT : 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.

This talk is part of the Computational Neuroscience series.

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