How bad becomes good: A neurocomputational model of affect-informed choice.

Abstract

People often draw on their current affective experience to inform their decisions, yet little is known about the underlying mechanisms of this process. Understanding them has important implications for many big questions in both the affective and decision sciences. Do the same neural circuits that generate affect generate value? What differentiates people who have greater contextual flexibility in their reliance on affect? Do affective choices invoke processes that are distinct from less affective choices? To investigate these questions, we developed a neurocomputational model of affect-informed choice, in which people convert subjective affect into context-sensitive decision value through a process of weighted evidence accumulation. We then tested model predictions by recording electroencephalography and facial electromyography during a novel affective choice paradigm in a sample of racially diverse undergraduate participants (data collected in 2018-2019). In addition to validating our model, we found that generation of affective responses occurs earlier than, and is neurally distinct from, valuation of that affect. Moreover, individual differences in contextual flexibility of affective weighting correlated only with later valuation processes, not earlier affect generation processes. Our results have important theoretical implications for emotion, emotion regulation, and decision making. (PsycInfo Database Record (c) 2024 APA, all rights reserved).