Laboratory for Computational Motor Control, Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, Maryland.
Departments of Integrative Physiology and Mechanical Engineering University of Colorado, Boulder, Colorado.
J Neurophysiol. 2020 Jun 1;123(6):2161-2172. doi: 10.1152/jn.00700.2019. Epub 2020 May 6.
Decisions are made based on the subjective value that the brain assigns to options. However, subjective value is a mathematical construct that cannot be measured directly, but rather is inferred from choices. Recent results have demonstrated that reaction time, amplitude, and velocity of movements are modulated by reward, raising the possibility that there is a link between how the brain evaluates an option and how it controls movements toward that option. Here, we asked people to choose among risky options represented by abstract stimuli, some associated with gain (points in a game), and others with loss. From their choices we estimated the subjective value that they assigned to each stimulus. In probe trials, a single stimulus appeared at center, instructing subjects to make a saccade to a peripheral target. We found that the reaction time, peak velocity, and amplitude of the peripherally directed saccade varied roughly linearly with the subjective value that the participant had assigned to the central stimulus: reaction time was shorter, velocity was higher, and amplitude was larger for stimuli that the participant valued more. Naturally, participants differed in how much they valued a given stimulus. Remarkably, those who valued a stimulus more, as evidenced by their choices in decision trials, tended to move with shorter reaction time and greater velocity in response to that stimulus in probe trials. Overall, the reaction time of the saccade in response to a stimulus partly predicted the subjective value that the brain assigned to that stimulus. Behavioral economics relies on subjective evaluation, an abstract quantity that cannot be measured directly but must be inferred by fitting decision models to the choice patterns. Here, we present a new approach to estimate subjective value: with nothing to fit, we show that it is possible to estimate subjective value based on movement kinematics, providing a modest ability to predict a participant's preferences without prior measurement of their choice patterns.
决策是基于大脑赋予选项的主观价值做出的。然而,主观价值是一个数学概念,不能直接测量,而是通过选择来推断。最近的研究结果表明,反应时间、幅度和运动速度受到奖励的调节,这增加了一种可能性,即大脑评估选项的方式和控制向该选项运动的方式之间存在联系。在这里,我们要求人们在由抽象刺激表示的风险选项之间进行选择,其中一些与收益(游戏中的分数)相关,而另一些则与损失相关。从他们的选择中,我们估计了他们赋予每个刺激的主观价值。在探测试验中,一个单一的刺激出现在中心,指示被试向一个外围目标进行扫视。我们发现,反应时间、峰值速度和指向外围的扫视幅度与被试赋予中心刺激的主观价值大致呈线性关系:被试赋予的价值越高,反应时间越短,速度越快,幅度越大。自然地,被试在给定刺激的价值上存在差异。值得注意的是,那些在决策试验中表现出更看重某个刺激的被试,在探测试验中对该刺激的反应往往具有更短的反应时间和更高的速度。总的来说,对刺激的扫视反应时间在一定程度上预测了大脑赋予该刺激的主观价值。行为经济学依赖于主观评价,这是一种不能直接测量但必须通过拟合决策模型来推断的抽象数量。在这里,我们提出了一种估计主观价值的新方法:不需要拟合,我们表明,根据运动运动学可以估计主观价值,在没有事先测量他们的选择模式的情况下,提供了一种预测参与者偏好的适度能力。