Decomposition of a complex motor skill in learning improves experts' expertise

Author:

Kimoto Yudai1,Hirano Masato,Furuya Shinichi2ORCID

Affiliation:

1. Sony Computer Science Laboratories Inc.

2. Sony Computer Science Laboratories

Abstract

Abstract Complex motor skills involve intricate sequences of movements that require precise temporal coordination across multiple body parts, posing challenges to mastery based on perceived error or reward. One approach that has been widely used is to decompose such skills into simpler, constituent movement elements during the learning process, thereby aligning the task complexity with the learners' capacity for accurate execution. Despite common belief and prevalent adoption, the effectiveness of this method remains elusive. Here we addressed this issue by decomposing a sequence of precisely timed coordination of movements across multiple fingers into individual constituent elements separately during piano practice. The results demonstrated that the decomposition training enhanced the accuracy of the original motor skill, a benefit not achieved through mere repetition of movements alone, specifically when skilled pianists received explicit visual feedback on timing error in the order of milliseconds during training. During the training, the patterns of multi-finger movements changed significantly, suggesting exploration of movements to refine the skill. By contrast, neither unskilled pianists who underwent the same training nor skilled pianists who performed the decomposition training without receiving visual feedback on the error showed improved skill through training. These findings offer novel evidences suggesting that decomposing a complex motor skill, coupled with receiving feedback on subtle movement error during training, further enhances motor expertise of skilled individuals by facilitating exploratory refinement of movements.

Publisher

Research Square Platform LLC

Reference37 articles.

1. Boot, W.R., Ericsson, K.A.: Expertise. In: The Oxford Handbook of Cognitive Engineering. Oxford University Press (2013)

2. Deliberate practice and performance in music, games, sports, education, and professions: a meta-analysis;Macnamara BN;Psychol. Sci.,2014

3. Rethinking expertise: A multifactorial gene-environment interaction model of expert performance;Ullén F;Psychol. Bull.,2016

4. Toward a multifactorial model of expertise: beyond born versus made;Hambrick DZ;Ann. N Y Acad. Sci.,2018

5. Surmounting retraining limits in musicians’ dystonia by transcranial stimulation;Furuya S;Ann. Neurol.,2014

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3