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本文引用的文献

1
An extra dimension to decision-making in animals: the three-way trade-off between speed, effort per-unit-time and accuracy.动物决策的一个额外维度:速度、单位时间的努力与准确性之间的三方权衡。
PLoS Comput Biol. 2014 Dec 18;10(12):e1003937. doi: 10.1371/journal.pcbi.1003937. eCollection 2014 Dec.
2
Context-dependent urgency influences speed-accuracy trade-offs in decision-making and movement execution.情境依赖的紧迫性会影响决策和动作执行中的速度-准确性权衡。
J Neurosci. 2014 Dec 3;34(49):16442-54. doi: 10.1523/JNEUROSCI.0162-14.2014.
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On the challenges and mechanisms of embodied decisions.论具身决策的挑战与机制
Philos Trans R Soc Lond B Biol Sci. 2014 Nov 5;369(1655). doi: 10.1098/rstb.2013.0479.
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Motor costs and the coordination of the two arms.运动成本与双臂的协调性。
J Neurosci. 2014 Jan 29;34(5):1806-18. doi: 10.1523/JNEUROSCI.3095-13.2014.
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Vigor of movements and the cost of time in decision making.动作活力与决策时间成本。
J Neurosci. 2014 Jan 22;34(4):1212-23. doi: 10.1523/JNEUROSCI.2798-13.2014.
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The basal ganglia, the ideal machinery for the cost-benefit analysis of action plans.基底神经节,行动计划成本效益分析的理想机制。
Front Neural Circuits. 2013 Jul 22;7:121. doi: 10.3389/fncir.2013.00121. eCollection 2013.
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A model of reward- and effort-based optimal decision making and motor control.基于奖励和努力的最优决策和运动控制模型。
PLoS Comput Biol. 2012;8(10):e1002716. doi: 10.1371/journal.pcbi.1002716. Epub 2012 Oct 4.
8
Load emphasizes muscle effort minimization during selection of arm movement direction.负荷强调在选择手臂运动方向时最小化肌肉用力。
J Neuroeng Rehabil. 2012 Oct 4;9:70. doi: 10.1186/1743-0003-9-70.
9
Evidence for hyperbolic temporal discounting of reward in control of movements.控制运动中奖励的双曲线时间折扣的证据。
J Neurosci. 2012 Aug 22;32(34):11727-36. doi: 10.1523/JNEUROSCI.0424-12.2012.
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Reduction of metabolic cost during motor learning of arm reaching dynamics.手臂运动动力学的运动学习过程中代谢成本的降低。
J Neurosci. 2012 Feb 8;32(6):2182-90. doi: 10.1523/JNEUROSCI.4003-11.2012.

决策与运动控制中努力的一种表现形式。

A Representation of Effort in Decision-Making and Motor Control.

作者信息

Shadmehr Reza, Huang Helen J, Ahmed Alaa A

机构信息

Laboratory for Computational Motor Control, Department of Biomedical Engineering, Johns Hopkins School of Medicine, 410 Traylor Building, 720 Rutland Avenue, Baltimore, MD 21205, USA.

Neuromechanics Laboratory, Department of Integrative Physiology, University of Colorado, 354 UCB, Boulder, CO 80309-0354, USA.

出版信息

Curr Biol. 2016 Jul 25;26(14):1929-34. doi: 10.1016/j.cub.2016.05.065. Epub 2016 Jun 30.

DOI:10.1016/j.cub.2016.05.065
PMID:27374338
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7912535/
Abstract

Given two rewarding stimuli, animals tend to choose the more rewarding (or less effortful) option. However, they also move faster toward that stimulus [1-5]. This suggests that reward and effort not only affect decision-making, they also influence motor control [6, 7]. How does the brain compute the effort requirements of a task? Here, we considered data acquired during walking, reaching, flying, or isometric force production. In analyzing the decision-making and motor-control behaviors of various animals, we considered the possibility that the brain may estimate effort objectively, via the metabolic energy consumed to produce the action. We measured the energetic cost of reaching and found that, like walking, it was convex in time, with a global minimum, implying that there existed a movement speed that minimized effort. However, reward made it worthwhile to be energetically inefficient. Using a framework in which utility of an action depended on reward and energetic cost, both discounted in time, we found that it was possible to account for a body of data in which animals were free to choose how to move (reach slow or fast), as well as what to do (walk or fly, produce force F1 or F2). We suggest that some forms of decision-making and motor control may share a common utility in which the brain represents the effort associated with performing an action objectively via its metabolic energy cost and then, like reward, temporally discounts it as a function of movement duration.

摘要

给定两种有奖励的刺激,动物倾向于选择奖励更多(或更省力)的选项。然而,它们也会更快地朝着那个刺激移动[1 - 5]。这表明奖励和努力不仅影响决策,还会影响运动控制[6, 7]。大脑是如何计算一项任务的努力需求的呢?在这里,我们考虑了在行走、伸手够物、飞行或等长力量产生过程中获取的数据。在分析各种动物的决策和运动控制行为时,我们考虑了大脑可能通过产生动作所消耗的代谢能量来客观估计努力的可能性。我们测量了伸手够物的能量消耗,发现和行走一样,它在时间上呈凸形,有一个全局最小值,这意味着存在一个使努力最小化的运动速度。然而,奖励使得在能量利用上低效变得值得。使用一个行动效用取决于奖励和能量消耗(两者都随时间贴现)的框架,我们发现有可能解释这样一组数据,即动物可以自由选择如何移动(慢或快地伸手够物)以及做什么(行走或飞行,产生力F1或F2)。我们认为某些形式的决策和运动控制可能共享一种共同的效用,在这种效用中,大脑通过动作的代谢能量成本客观地表示与执行一个动作相关的努力,然后像奖励一样,根据运动持续时间在时间上对其进行贴现。