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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