二择反应时的序贯抽样模型比较
A comparison of sequential sampling models for two-choice reaction time.
作者信息
Ratcliff Roger, Smith Philip L
机构信息
Department of Psychology, The Ohio State University, Columbus, OH 43210, USA.
出版信息
Psychol Rev. 2004 Apr;111(2):333-67. doi: 10.1037/0033-295X.111.2.333.
The authors evaluated 4 sequential sampling models for 2-choice decisions--the Wiener diffusion, Ornstein-Uhlenbeck (OU) diffusion, accumulator, and Poisson counter models--by fitting them to the response time (RT) distributions and accuracy data from 3 experiments. Each of the models was augmented with assumptions of variability across trials in the rate of accumulation of evidence from stimuli, the values of response criteria, and the value of base RT across trials. Although there was substantial model mimicry, empirical conditions were identified under which the models make discriminably different predictions. The best accounts of the data were provided by the Wiener diffusion model, the OU model with small-to-moderate decay, and the accumulator model with long-tailed (exponential) distributions of criteria, although the last was unable to produce error RTs shorter than correct RTs. The relationship between these models and 3 recent, neurally inspired models was also examined.
作者通过将4种用于二选一决策的顺序采样模型——维纳扩散模型、奥恩斯坦-乌伦贝克（OU）扩散模型、累加器模型和泊松计数器模型——拟合到来自3个实验的反应时间（RT）分布和准确性数据，对它们进行了评估。每个模型都增加了关于试验间证据积累速率、反应标准值和试验间基础RT值的变异性假设。尽管存在大量的模型模拟，但仍确定了一些经验条件，在这些条件下模型会做出明显不同的预测。维纳扩散模型、具有小到中等衰减的OU模型以及具有长尾（指数）标准分布的累加器模型对数据的解释最佳，不过最后一个模型无法产生比正确RT更短的错误RT。还研究了这些模型与最近的3种神经启发模型之间的关系。
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