Children With Dystonia Can Learn a Novel Motor Skill: Strategies That are Tolerant to High Variability

IEEE Transactions on Neural Systems and Rehabilitation Engineering : a Publication of the IEEE Engineering in Medicine and Biology Society
Virginia Way Tong ChuDagmar Sternad

Abstract

Children with dystonia are characterized by highly variable and seemingly uncontrolled movements. An important question for any rehabilitative effort is whether these children can learn and improve their performance. This study compared children with dystonia due to cerebral palsy, typically developing children, and healthy adults in their ability to acquire a novel sensorimotor skill. Using a virtual setup, subjects threw a virtual ball tethered to a post to hit a virtual target. Multiple combinations of release angle and velocity of the arm at ball release could achieve a target hit-the task was redundant and afforded solutions with different sensitivity to variability. Subjects performed 200 trials for two target locations that presented different types of redundancy. We hypothesized that children with dystonia develop strategies that are tolerant to their high variability. Estimating this variability highlighted the insufficiency of traditional outcome measures. Therefore, additional analyses of data distributions and of ball release timing were applied. Results showed that: 1) children with dystonia reduced their performance error despite their high variability; 2) this improvement was brought about by finding error-tolera...Continue Reading

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Citations

Aug 5, 2016·PLoS Computational Biology·Christopher J HassonDagmar Sternad
Feb 28, 2018·Scientific Reports·Anna SadnickaJoseph M Galea
Oct 2, 2017·The Journal of the Acoustical Society of America·Jarrad H Van StanDagmar Sternad
Mar 7, 2020·Journal of Neuroengineering and Rehabilitation·Helga HaberfehlnerAnnemieke I Buizer
Jan 20, 2020·Biological cybernetics·Gergely BuzaTamas Insperger
Nov 5, 2020·Journal of Neurophysiology·Zhaoran Zhang, Dagmar Sternad
Jul 24, 2018·Current Opinion in Behavioral Sciences·Dagmar Sternad

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