Reyes Marcelo Bussotti, Buhusi Catalin V
Department of Neurosciences, Medical University of South Carolina, Charleston, SC, United States.
Department of Neurosciences, Medical University of South Carolina, Charleston, SC, United States; Department of Psychology, USTAR BioInnovations Center, Utah State University, Logan, UT, United States.
Behav Processes. 2014 Jan;101:32-7. doi: 10.1016/j.beproc.2013.09.008. Epub 2013 Oct 5.
The processes involved in the acquisition of simultaneous temporal processing are currently less understood. For example, it is unclear whether scalar property emerges early during simultaneous temporal acquisition. Using an information-processing model which accounts for the amount of information that each temporal process provides in regard to reward time, we predicted that scalar property would emerge early during the acquisition process, but that subjects should take about 27% longer (more trials) to acquire the long duration than the short duration. To evaluate these predictions, we performed individual-trials analyses to identify changes in timing behavior when rats simultaneously acquire two criterion durations, either 10s and 20s (group 10/20) or 20s and 40s (group 20/40). To analyze the individual trials we used a change-point algorithm to identify changes in rats' wait time. For each individual rat, and for each criterion duration, analyses indicated that simultaneous temporal acquisition is characterized by a sudden change in waiting to a wait-time proportional to the associated criterion. The results failed to indicate group differences in regard to the number of trials it takes for the change in wait-time to occur, but that in both groups, it took longer (more trials) to acquire the long duration than the shorter one, not significantly different from the theoretical prediction. These results are discussed in the framework of an information-processing model informing both associative and temporal learning, thus providing a bridge between the two fields. This article is part of a Special Issue entitled: Associative and Temporal Learning.
目前,人们对同时进行时间处理的获取过程了解较少。例如,尚不清楚标量属性是否在同时进行时间获取的早期就出现。我们使用一个信息处理模型,该模型考虑了每个时间过程在奖励时间方面提供的信息量,预测标量属性会在获取过程的早期出现,但与获取短持续时间相比,受试者获取长持续时间的时间应长约27%(试验次数更多)。为了评估这些预测,我们进行了个体试验分析,以确定大鼠同时获取两个标准持续时间(10秒和20秒,即10/20组;或20秒和40秒,即20/40组)时定时行为的变化。为了分析个体试验,我们使用了一种变点算法来识别大鼠等待时间的变化。对于每只大鼠和每个标准持续时间,分析表明,同时进行时间获取的特征是等待突然变化为与相关标准成比例的等待时间。结果未能表明等待时间变化所需试验次数的组间差异,但在两组中,获取长持续时间比获取短持续时间花费的时间更长(试验次数更多),与理论预测无显著差异。这些结果在一个为联想学习和时间学习提供信息的信息处理模型框架内进行了讨论,从而在这两个领域之间架起了一座桥梁。本文是名为“联想学习和时间学习”的特刊的一部分。