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亮度辨别任务中反应时间和准确性的扩散模型解释:拟合真实数据与无法拟合虚假但似真的数据

A diffusion model account of response time and accuracy in a brightness discrimination task: fitting real data and failing to fit fake but plausible data.

作者信息

Ratcliff Roger

机构信息

Department of Psychology, Northwestern University, Evanston, Illinois 60208, USA.

出版信息

Psychon Bull Rev. 2002 Jun;9(2):278-91. doi: 10.3758/bf03196283.

Abstract

A brightness discrimination experiment was performed to examine how subjects decide whether a patch of pixels is "bright" or "dark," and stimulus duration, brightness, and speed versus accuracy instructions were manipulated. The diffusion model (Ratcliff, 1978) was fit to the data, and it accounted for all the dependent variables: mean correct and error response times, the shapes of response time distributions for correct and error responses, and accuracy values. Speed-accuracy manipulations affected only boundary separation (response criteria settings) in the model. Drift rate (the rate of accumulation of evidence) in the diffusion model, which represents stimulus quality, increased as a function of stimulus duration and stimulus brightness but asymptoted as stimulus duration increased from 100 to 150 msec. To address the argument that the diffusion model can fit any pattern of data, simulated patterns of plausible data are presented that the model cannot fit.

摘要

进行了一项亮度辨别实验,以研究受试者如何判断一块像素是“亮”还是“暗”,并对刺激持续时间、亮度以及速度与准确性指令进行了操控。将扩散模型(拉特克利夫,1978年)与数据进行拟合,该模型解释了所有因变量:平均正确和错误反应时间、正确和错误反应的反应时间分布形状以及准确性值。速度 - 准确性操控仅影响模型中的边界分离(反应标准设置)。扩散模型中的漂移率(证据积累速率)代表刺激质量,它随刺激持续时间和刺激亮度的增加而增加,但当刺激持续时间从100毫秒增加到150毫秒时趋于平稳。为了回应扩散模型可以拟合任何数据模式这一观点,展示了该模型无法拟合的合理数据模拟模式。

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