Models of affective decision-making: how do feelings predict choice?

Intuitively, how we feel about potential outcomes will determine our decisions. Indeed, one of the most influential theories in psychology, Prospect Theory, implicitly assumes that feelings govern choice. Surprisingly, however, we know very little about the rules by which feelings are transformed into decisions. Here, we characterize a computational model that uses feelings to predict choice. Not only does the model perform better than existing value based models, it also redefines some of their core assumptions. We reveal in three independent samples that, contrary to conventional wisdom, losses do not have a larger impact on explicit feelings than gains. Rather, loss feelings are weighted more when making a decision. It are these relative weights that explain individual differences in decision making. The results provide new insights into how feelings are utilized to reach a decision.