Reaction time (RT) is one of the most frequently used measures to detect cognitive processes. When tasks require more cognitive processes/resources, reaction is slower. However, RTs may provide only restricted information regarding the temporal characteristics of cognitive processes. Pupils respond reflexively to light but also to cognitive activation. The more cognitive resources a task requires, the more the pupil dilates. However, despite being able to use temporal changes in pupil size (advanced devices measure changes in pupil diameter with sampling rates of above 1000 samples per second), most past studies using pupil dilation have not investigated temporal changes in pupil response. In the current paper, we discuss the advantage of the temporal approach to analyze pupil changes compared to a more traditional perspective, specifically, singular value methods such as mean value and peak amplitude value. Using data from two recent studies conducted in our laboratory, we demonstrate the differences in findings arising from the various analyses. In particular, we focus on the advantage of temporal analysis in detecting hidden effects, investigating temporal characterizations of the effects, and validating the experimental manipulation.

反应时间 (RT) 是最常用的检测认知过程的方法之一。当任务需要更多的认知过程/资源时，反应就会变慢。然而，RT 可能仅提供有关认知过程的时间特征的有限信息。学生对光有反射性反应，也对认知激活有反应。一项任务需要的认知资源越多，瞳孔放大的就越多。然而，尽管能够使用瞳孔大小的时间变化（先进设备以每秒超过 1000 个样本的采样率测量瞳孔直径的变化），但过去大多数使用瞳孔扩张的研究都没有研究瞳孔反应的时间变化。在当前的论文中，我们讨论了与更传统的观点相比，时间方法分析瞳孔变化的优势，具体来说，奇异值法，如平均值和峰值幅度值。使用我们实验室最近进行的两项研究的数据，我们证明了各种分析结果的差异。特别是，我们专注于时间分析在检测隐藏效应、研究效应的时间特征和验证实验操作方面的优势。