Li Xiaodong, Su Ruixin, Chen Yilin, Yang Tianming
CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Neuroscience, Chinese Academy of Sciences, Shanghai 200031, China; University of Chinese Academy of Sciences, Beijing 100049, China.
CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Neuroscience, Chinese Academy of Sciences, Shanghai 200031, China.
Cell Rep. 2023 Mar 28;42(3):112232. doi: 10.1016/j.celrep.2023.112232. Epub 2023 Mar 15.
Decision making often depends on vague information that leads to uncertainty, which is a quantity contingent not on choice but on probability distributions of sensory evidence and other cognitive variables. Uncertainty may be computed in parallel and interact with decision making. Here, we adapt the classic random-dot motion direction discrimination task to allow subjects to indicate their uncertainty without having to form a decision first. The subjects' choices and reaction times for perceptual decisions and uncertainty responses are measured, respectively. We then build a value-based model in which decisions are based on optimizing value computed from a drift-diffusion process. The model accounts for key features of subjects' behavior and the variation across the individuals. It explains how the addition of the uncertainty option affects perceptual decision making. Our work establishes a value-based theoretical framework for studying uncertainty and perceptual decisions that can be readily applied in future investigations of the underlying neural mechanism.
决策通常依赖于模糊信息，这会导致不确定性，不确定性是一个并非取决于选择而是取决于感官证据和其他认知变量的概率分布的量。不确定性可以并行计算，并与决策相互作用。在这里，我们改编了经典的随机点运动方向辨别任务，使受试者能够在无需先做出决策的情况下表明他们的不确定性。分别测量了受试者在感知决策和不确定性反应方面的选择和反应时间。然后，我们构建了一个基于价值的模型，其中决策基于优化从漂移扩散过程计算出的价值。该模型解释了受试者行为的关键特征以及个体间的差异。它解释了添加不确定性选项如何影响感知决策。我们的工作建立了一个基于价值的理论框架，用于研究不确定性和感知决策，该框架可很容易地应用于未来对潜在神经机制的研究。
