Proceedings of the Annual Meeting of the Cognitive Science Society

Discrete emotions are known to elicit changes in decision-making. Previous research has found that affect biases response times and the perception of evidence for choices, among other key factors of decision-making. However, little is known how affect influences the specific cognitive mechanisms that underlie decision-making. We investigated these mechanisms by fitting a hierarchical reinforcement-learning decision diffusion model to participant choice data. Following the collection of baseline decision-making data, participants took part in a writing exercise to generate neutral or discrete emotions. Following the writing exercise, participants made additional decisions. We found that exposure to discrete emotions modulates decision-making through several mechanisms including rates of learning and evidence accumulation, separation of decision thresholds, and sensitivity to noise. Furthermore, we found that exposure to each of the four discrete emotions modulated decision-making differently. These findings integrate learning and decision process models to expand on previous research and elucidate processes of affective decision-making.