SILC Business School, Shanghai University, Shanghai, People's Republic of China.
Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA.
Proc Biol Sci. 2023 Feb 8;290(1992):20221593. doi: 10.1098/rspb.2022.1593.
Neurocognitive theories of value-based choice propose that people additively accumulate choice attributes when making decisions. These theories cannot explain the emergence of complex multiplicative preferences such as those assumed by prospect theory and other economic models. We investigate an mechanism, according to which attention to attributes (like payoffs) depends on other attributes (like probabilities) attended to previously. We formalize this mechanism using a Markov attention model combined with an accumulator decision process, and test our model on eye-tracking and mouse-tracking data in risky choice. Our tests show that interactive attention is necessary to make good choices, that most participants display interactive attention and that allowing for interactive attention in accumulation-based decision models improves their predictions. By equipping established decision models with sophisticated attentional dynamics, we extend these models to describe complex economic choice, and in the process, we unify two prominent theoretical approaches to studying value-based decision making.
基于价值的选择的神经认知理论提出,人们在做出决策时会累加选择属性。这些理论无法解释复杂的乘法偏好的出现,如前景理论和其他经济模型所假设的偏好。我们研究了一种机制,根据这种机制,对属性(如收益)的注意力取决于之前注意到的其他属性(如概率)。我们使用马尔可夫注意模型结合累积决策过程来形式化这个机制,并在风险选择中的眼动追踪和鼠标追踪数据上测试我们的模型。我们的测试表明,交互注意对于做出好的选择是必要的,大多数参与者表现出交互注意,并且允许在基于累积的决策模型中进行交互注意可以提高它们的预测。通过为既定的决策模型配备复杂的注意力动态,我们将这些模型扩展到描述复杂的经济选择,并且在这个过程中,我们将两种研究基于价值的决策的突出理论方法统一起来。