Suppr超能文献

内隐运动想象能力能否预测伸手纠正效率?对人类运动控制最新模型的一项测试。

Does implicit motor imagery ability predict reaching correction efficiency? A test of recent models of human motor control.

作者信息

Hyde Christian, Wilmut Kate, Fuelscher Ian, Williams Jacqueline

机构信息

School of Psychology, Faculty of Health, Deakin University, Melbourne, Australia.

出版信息

J Mot Behav. 2013;45(3):259-69. doi: 10.1080/00222895.2013.785927.

Abstract

Neurocomputational models of reaching indicate that efficient purposive correction of movement midflight (e.g., online control) depends on one's ability to generate and monitor an accurate internal (neural) movement representation. In the first study to test this empirically, the authors investigated the relationship between healthy young adults' implicit motor imagery performance and their capacity to correct their reaching trajectory. As expected, after controlling for general reaching speed, hierarchical regression demonstrated that imagery ability was a significant predictor of hand correction speed; that is, faster and more accurate imagery performance associated with faster corrections to reaching following target displacement at movement onset. They argue that these findings provide preliminary support for the view that a link exists between an individual's ability to represent movement mentally and correct movement online efficiently.

摘要

有关伸手够物的神经计算模型表明,在运动过程中对动作进行有效且有目的的纠正(例如在线控制)取决于个体生成并监控准确的内部(神经)运动表征的能力。在第一项对此进行实证检验的研究中,作者调查了健康年轻成年人的内隐运动想象表现与其纠正伸手轨迹能力之间的关系。不出所料,在控制了一般的伸手速度后,分层回归表明想象能力是手部纠正速度的一个重要预测指标;也就是说,在运动开始时目标发生位移后,更快、更准确的想象表现与对伸手动作的更快纠正相关。他们认为,这些发现为以下观点提供了初步支持,即个体在脑海中表征运动的能力与在线有效纠正运动之间存在联系。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验