Podlesnik Christopher A, Sanabria Federico
Department of Pharmacology, University of Michigan Medical School, Ann Arbor, MI 48109-5632, United States.
Behav Processes. 2011 May;87(1):125-34. doi: 10.1016/j.beproc.2010.12.005. Epub 2010 Dec 21.
We assessed the effects of repeated extinction and reversals of two conditional stimuli (CS+/CS-) on an appetitive conditioned approach response in rats. Three results were observed that could not be accounted for by a simple linear operator model such as the one proposed by Rescorla and Wagner (1972): (1) responding to a CS- declined faster when a CS+ was simultaneously extinguished; (2) reacquisition of pre-extinction performance recovered rapidly within one session; and (3) reversal of CS+/CS- contingencies resulted in a more rapid recovery to the current CS- (former CS+) than the current CS+, accompanied by a slower acquisition of performance to the current CS+. An arousal parameter that mediates learning was introduced to a linear operator model to account for these effects. The arousal-mediated learning model adequately fit the data and predicted data from a second experiment with different rats in which only repeated reversals of CS+/CS- were assessed. According to this arousal-mediated learning model, learning is accelerated by US-elicited arousal and it slows down in the absence of US. Because arousal varies faster than conditioning, the model accounts for the decline in responding during extinction mainly through a reduction in arousal, not a change in learning. By preserving learning during extinction, the model is able to account for relapse effects like rapid reacquisition, renewal, and reinstatement.
我们评估了对大鼠食欲性条件接近反应中两个条件刺激(CS+/CS-)进行重复消退和反转的影响。观察到三个结果无法用简单的线性算子模型(如Rescorla和Wagner(1972)提出的模型)来解释:(1)当CS+同时被消退时,对CS-的反应下降得更快;(2)在一个实验环节内,消退前表现的重新习得迅速恢复;(3)CS+/CS-意外情况的反转导致对当前CS-(前CS+)的恢复比对当前CS+更快,同时对当前CS+的表现习得较慢。将一个介导学习的唤醒参数引入线性算子模型以解释这些效应。唤醒介导学习模型充分拟合了数据,并预测了来自第二个实验的数据,该实验使用不同的大鼠,仅评估了CS+/CS-的重复反转。根据这个唤醒介导学习模型,学习通过US引发的唤醒而加速,在没有US的情况下则会减慢。由于唤醒的变化比条件作用更快,该模型主要通过唤醒的降低而非学习的改变来解释消退期间反应的下降。通过在消退期间保留学习,该模型能够解释诸如快速重新习得、恢复和复现等复发效应。