Suppr超能文献

用力情况、成功与否以及未使用情况决定了手臂的选择。

Effort, success, and nonuse determine arm choice.

作者信息

Schweighofer Nicolas, Xiao Yupeng, Kim Sujin, Yoshioka Toshinori, Gordon James, Osu Rieko

机构信息

Biokinesiology and Physical Therapy, University of Southern California, Los Angeles, California;

Neuroscience Graduate Program, University of Southern California, Los Angeles, California; and.

出版信息

J Neurophysiol. 2015 Jul;114(1):551-9. doi: 10.1152/jn.00593.2014. Epub 2015 May 6.

Abstract

How do humans choose one arm or the other to reach single targets in front of the body? Current theories of reward-driven decisionmaking predict that choice results from a comparison of "action values," which are the expected rewards for possible actions in a given state. In addition, current theories of motor control predict that in planning arm movements, humans minimize an expected motor cost that balances motor effort and endpoint accuracy. Here, we test the hypotheses that arm choice is determined by comparison of action values comprising expected effort and expected task success for each arm, as well as a handedness bias. Right-handed subjects, in either a large or small target condition, were first instructed to use each hand in turn to shoot through an array of targets and then to choose either hand to shoot through the same targets. Effort was estimated via inverse kinematics and dynamics. A mixed-effects logistic-regression analysis showed that, as predicted, both expected effort and expected success predicted choice, as did arm use in the preceding trial. Finally, individual parameter estimation showed that the handedness bias correlated with mean difference between right- and left-arm success, leading to overall lower use of the left arm. We discuss our results in light of arm nonuse in individuals' poststroke.

摘要

人类如何选择一只手臂去够身体前方的单个目标?当前关于奖励驱动决策的理论预测,选择是由“动作值”的比较产生的,动作值是给定状态下可能动作的预期奖励。此外,当前的运动控制理论预测,在规划手臂运动时,人类会将预期的运动成本最小化,该成本平衡了运动努力和终点准确性。在这里,我们测试以下假设:手臂选择是通过比较包括每只手臂的预期努力和预期任务成功率的动作值以及利手偏差来确定的。右利手受试者,在大目标或小目标条件下,首先被指示依次用每只手穿过一系列目标,然后选择任意一只手穿过相同的目标。通过逆运动学和动力学估计努力程度。混合效应逻辑回归分析表明,正如预测的那样,预期努力和预期成功率都能预测选择,前一次试验中使用的手臂也是如此。最后,个体参数估计表明,利手偏差与右臂和左臂成功率的平均差异相关,导致左臂的总体使用频率较低。我们根据个体中风后的手臂不用现象来讨论我们的结果。

相似文献

1
5
Evidence for right-hand feeding biases in a left-handed population.左撇子人群中存在右手喂食偏好的证据。
Laterality. 2015 May;20(3):287-305. doi: 10.1080/1357650X.2014.961472. Epub 2014 Sep 26.
10
Manifold reaching paradigm: how do we handle target redundancy?多流拓展范式:我们如何处理目标冗余?
J Neurophysiol. 2011 Oct;106(4):2086-102. doi: 10.1152/jn.01063.2010. Epub 2011 Jul 6.

引用本文的文献

2
Reaching vigor tracks learned prediction error.达到活力追踪学习到的预测误差。
bioRxiv. 2025 Mar 25:2025.03.24.645035. doi: 10.1101/2025.03.24.645035.
5
Reaching Distance Influences Perceptual Decisions.可及距离影响感知决策。
Eur J Neurosci. 2025 Feb;61(3):e70006. doi: 10.1111/ejn.70006.

本文引用的文献

1
Rapid prediction of biomechanical costs during action decisions.行动决策过程中生物力学成本的快速预测。
J Neurophysiol. 2014 Sep 15;112(6):1256-66. doi: 10.1152/jn.00147.2014. Epub 2014 Jun 3.
2
Motor effort alters changes of mind in sensorimotor decision making.运动努力改变感觉运动决策中的思维变化。
PLoS One. 2014 Mar 20;9(3):e92681. doi: 10.1371/journal.pone.0092681. eCollection 2014.
6
Quantifying arm nonuse in individuals poststroke.量化脑卒中后个体的手臂不使用情况。
Neurorehabil Neural Repair. 2013 Jun;27(5):439-47. doi: 10.1177/1545968312471904. Epub 2013 Jan 25.
8
Sensorimotor performance asymmetries predict hand selection.感觉运动性能的不对称性预测手的选择。
Neuroscience. 2013 Jan 3;228:349-60. doi: 10.1016/j.neuroscience.2012.10.046. Epub 2012 Oct 27.
10
Making decisions through a distributed consensus.通过分布式共识做出决策。
Curr Opin Neurobiol. 2012 Dec;22(6):927-36. doi: 10.1016/j.conb.2012.05.007. Epub 2012 Jun 8.

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