Busemeyer Jerome R, Jessup Ryan K, Johnson Joseph G, Townsend James T
Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN 47405, USA.
Neural Netw. 2006 Oct;19(8):1047-58. doi: 10.1016/j.neunet.2006.05.043. Epub 2006 Sep 18.
Diffusion processes, and their discrete time counterparts, random walk models, have demonstrated an ability to account for a wide range of findings from behavioural decision making for which the purely algebraic and deterministic models often used in economics and psychology cannot account. Recent studies that record neural activations in non-human primates during perceptual decision making tasks have revealed that neural firing rates closely mimic the accumulation of preference theorized by behaviourally-derived diffusion models of decision making. This article bridges the expanse between the neurophysiological and behavioural decision making literatures specifically, decision field theory [Busemeyer, J. R. & Townsend, J. T. (1993). Decision field theory: A dynamic-cognitive approach to decision making in an uncertain environment. Psychological Review, 100, 432-459], a dynamic and stochastic random walk theory of decision making, is presented as a model positioned between lower-level neural activation patterns and more complex notions of decision making found in psychology and economics. Potential neural correlates of this model are proposed, and relevant competing models are also addressed.
扩散过程及其离散时间对应物——随机游走模型，已证明能够解释行为决策中的一系列发现，而经济学和心理学中常用的纯代数和确定性模型往往无法解释这些发现。最近在非人类灵长类动物进行感知决策任务期间记录神经激活的研究表明，神经放电率紧密模仿了行为衍生的决策扩散模型所理论化的偏好积累。本文特别弥合了神经生理学和行为决策文献之间的差距，具体而言，决策场理论[Busemeyer, J. R. & Townsend, J. T. (1993). 决策场理论：不确定环境中决策的动态认知方法。《心理学评论》，100，432 - 459]，一种动态且随机的决策随机游走理论，被作为一个介于较低层次神经激活模式与心理学和经济学中更复杂决策概念之间的模型呈现出来。文中提出了该模型潜在的神经关联，并讨论了相关的竞争模型。
