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Temporal dynamics of the semantic versus affective representations of valence during reversal learning.

Orit Heimer,Assaf Kron,Uri Hertz

Published 2023 in Cognition

ABSTRACT

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.

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