Jozefowiez Jeremie, Polack Cody W, Machado Armando, Miller Ralph R
Université Lille Nord de France, France; Universidade do Minho, Portugal.
State University of New York at Binghamton, United States.
Behav Processes. 2014 Jan;101:81-8. doi: 10.1016/j.beproc.2013.07.023. Epub 2013 Sep 9.
To contrast the classic version of the Scalar Expectancy Theory (SET) with the Behavioral Economic Model (BEM), we examined the effects of trial frequency on human temporal judgments. Mathematical analysis showed that, in a temporal bisection task, SET predicts that participants should show almost exclusive preference for the response associated with the most frequent duration, whereas BEM predicts that, even though participants will be biased, they will still display temporal control. Participants learned to emit one response (R[S]) after a 1.0-s stimulus and another (R[L]) after a 1.5-s stimulus. Then the effects of varying the frequencies of the 1.0-s and 1.5-s stimuli were assessed. Results were more consistent with BEM than with SET. Overall, this research illustrates how the impact of non-temporal factors on temporal discrimination may help us to contrast associative models such as BEM with cognitive models such as SET. Deciding between these two classes of models has important implications regarding the relations between associative learning and timing. This article is part of a Special Issue entitled: Associative and Temporal Learning.
为了对比标量期望理论（SET）的经典版本与行为经济模型（BEM），我们研究了试验频率对人类时间判断的影响。数学分析表明，在时间二分任务中，SET预测参与者应该几乎完全偏好与最频繁持续时间相关的反应，而BEM预测，尽管参与者会有偏差，但他们仍将表现出时间控制。参与者学会在1.0秒的刺激后发出一种反应（R[S]），在1.5秒的刺激后发出另一种反应（R[L]）。然后评估改变1.0秒和1.5秒刺激频率的影响。结果与BEM比与SET更一致。总体而言，本研究说明了非时间因素对时间辨别力的影响如何有助于我们将诸如BEM的联想模型与诸如SET的认知模型进行对比。在这两类模型之间做出决定对于联想学习和计时之间的关系具有重要意义。本文是名为：联想与时间学习的特刊的一部分。
