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Research on the role of affect in decision-making indicates that both predecisional current and expected affective valence predict choice. However, the exact role of current and expected affect for recurrent decision-making is still a matter of debate. We used a generalised mixed effect model to predict gambling responses in an experience-based learning task from ratings of current and expected affective valence. Results indicate that current and expected affective valence interact to predict choice. While expected valence had the biggest effect size, current valence and the interaction still contributed significantly to the prediction of choice. Resolving the interaction showed that participants relied more on the current valence if expectations were unclear or positive. These findings are discussed in the context of dual-process accounts and the affective signalling hypothesis. In conclusion, current and expected valence depend on one another and interact to predict choice in recurrent decision tasks.

Current and expected affective valence interact to predict choice in recurrent decisions