Literature DB >> 28954891

High variability impairs motor learning regardless of whether it affects task performance.

Marco Cardis1, Maura Casadio1, Rajiv Ranganathan2,3.   

Abstract

Motor variability plays an important role in motor learning, although the exact mechanisms of how variability affects learning are not well understood. Recent evidence suggests that motor variability may have different effects on learning in redundant tasks, depending on whether it is present in the task space (where it affects task performance) or in the null space (where it has no effect on task performance). We examined the effect of directly introducing null and task space variability using a manipulandum during the learning of a motor task. Participants learned a bimanual shuffleboard task for 2 days, where their goal was to slide a virtual puck as close as possible toward a target. Critically, the distance traveled by the puck was determined by the sum of the left- and right-hand velocities, which meant that there was redundancy in the task. Participants were divided into five groups, based on both the dimension in which the variability was introduced and the amount of variability that was introduced during training. Results showed that although all groups were able to reduce error with practice, learning was affected more by the amount of variability introduced rather than the dimension in which variability was introduced. Specifically, groups with higher movement variability during practice showed larger errors at the end of practice compared with groups that had low variability during learning. These results suggest that although introducing variability can increase exploration of new solutions, this may adversely affect the ability to retain the learned solution. NEW & NOTEWORTHY We examined the role of introducing variability during motor learning in a redundant task. The presence of redundancy allows variability to be introduced in different dimensions: the task space (where it affects task performance) or the null space (where it does not affect task performance). We found that introducing variability affected learning adversely, but the amount of variability was more critical than the dimension in which variability was introduced.

Entities:  

Keywords:  motor learning; null space; redundancy; task space; variability

Mesh:

Year:  2017        PMID: 28954891     DOI: 10.1152/jn.00158.2017

Source DB:  PubMed          Journal:  J Neurophysiol        ISSN: 0022-3077            Impact factor:   2.714


  19 in total

1.  Differential control of task and null space variability in response to changes in task difficulty when learning a bimanual steering task.

Authors:  Rakshith Lokesh; Rajiv Ranganathan
Journal:  Exp Brain Res       Date:  2019-02-09       Impact factor: 1.972

2.  Learning a specific, individual and generalizable coordination function: evaluating the variability of practice hypothesis in motor learning.

Authors:  Matheus M Pacheco; Karl M Newell
Journal:  Exp Brain Res       Date:  2018-09-22       Impact factor: 1.972

Review 3.  A tale of too many tasks: task fragmentation in motor learning and a call for model task paradigms.

Authors:  Rajiv Ranganathan; Aimee D Tomlinson; Rakshith Lokesh; Tzu-Hsiang Lin; Priya Patel
Journal:  Exp Brain Res       Date:  2020-11-10       Impact factor: 1.972

Review 4.  Exploring to learn and learning to explore.

Authors:  Guillaume Hacques; John Komar; Matt Dicks; Ludovic Seifert
Journal:  Psychol Res       Date:  2020-05-10

5.  A Proposed Framework to Describe Movement Variability within Sporting Tasks: A Scoping Review.

Authors:  Jake Cowin; Sophia Nimphius; James Fell; Peter Culhane; Matthew Schmidt
Journal:  Sports Med Open       Date:  2022-06-27

6.  It's Not (Only) the Mean that Matters: Variability, Noise and Exploration in Skill Learning.

Authors:  Dagmar Sternad
Journal:  Curr Opin Behav Sci       Date:  2018-03-01

7.  How does a partner's motor variability affect joint action?

Authors:  Simily Sabu; Arianna Curioni; Cordula Vesper; Natalie Sebanz; Günther Knoblich
Journal:  PLoS One       Date:  2020-10-29       Impact factor: 3.240

8.  Back to reality: differences in learning strategy in a simplified virtual and a real throwing task.

Authors:  Zhaoran Zhang; Dagmar Sternad
Journal:  J Neurophysiol       Date:  2020-11-04       Impact factor: 2.714

9.  Quantitative Assessment of Learning and Retention in Virtual Vocal Function Exercises.

Authors:  Jarrad H Van Stan; Se-Woong Park; Matthew Jarvis; Joseph Stemple; Robert E Hillman; Dagmar Sternad
Journal:  J Speech Lang Hear Res       Date:  2020-12-07       Impact factor: 2.297

10.  Guiding functional reorganization of motor redundancy using a body-machine interface.

Authors:  Dalia De Santis; Ferdinando A Mussa-Ivaldi
Journal:  J Neuroeng Rehabil       Date:  2020-05-11       Impact factor: 4.262

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