Heimer Orit, Kron Assaf, Hertz Uri
Department of Psychology, University of Haifa, Haifa, Israel.
Department of Psychology, University of Haifa, Haifa, Israel.
Cognition. 2023 Jul;236:105423. doi: 10.1016/j.cognition.2023.105423. Epub 2023 Mar 16.
Valence, the representation of a stimulus in terms of good or bad, plays a central role in models of affect, value-based learning theories, and value-based decision-making models. Previous work used Unconditioned Stimulus (US) to support a theoretical division between two different types of valence representations for a stimulus: the semantic representation of valence, i.e., stored accumulated knowledge about the value of the stimulus, and the affective representation of valence, i.e., the valence of the affective response to this stimulus. The current work extended past research by using a neutral Conditioned Stimulus (CS) in the context of reversal learning, a type of associative learning. The impact of expected uncertainty (the variability of rewards) and unexpected uncertainty (reversal) on the evolving temporal dynamics of the two types of valence representations of the CS was tested in two experiments. Results show that in an environment presenting the two types of uncertainty, the adaptation process (learning rate) of the choices and of the semantic valence representation is slower than the adaptation of the affective valence representation. In contrast, in environments with only unexpected uncertainty (i.e., fixed rewards), there is no difference in the temporal dynamics of the two types of valence representations. Implications for models of affect, value-based learning theories, and value-based decision-making models are discussed.
效价,即刺激在好坏方面的表征,在情感模型、基于价值的学习理论和基于价值的决策模型中起着核心作用。先前的研究使用无条件刺激(US)来支持对刺激的两种不同类型效价表征的理论划分:效价的语义表征,即存储的关于刺激价值的累积知识,以及效价的情感表征,即对该刺激的情感反应的效价。当前的研究通过在反转学习(一种联想学习类型)的背景下使用中性条件刺激(CS)扩展了以往的研究。在两个实验中测试了预期不确定性(奖励的变异性)和意外不确定性(反转)对CS的两种效价表征的演变时间动态的影响。结果表明,在呈现两种不确定性的环境中,选择和语义效价表征的适应过程(学习率)比情感效价表征的适应过程慢。相比之下,在只有意外不确定性(即固定奖励)的环境中,两种效价表征的时间动态没有差异。讨论了对情感模型、基于价值的学习理论和基于价值的决策模型的启示。