Affect-congruent attention modulates generalized reward expectations

• Published in: PLoS computational biology Vol. 19; no. 12; p. e1011707
• Main Authors: Bennett, Daniel, Radulescu, Angela, Zorowitz, Sam, Felso, Valkyrie, Niv, Yael
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 01.12.2023; Public Library of Science (PLoS)
• Subjects: Affect (Psychology); Analysis; Bias; Biology and Life Sciences; Computer simulation; Computer-generated environments; Emotional behavior; Emotional disorders; Emotions; Eye movements; Generalization, Psychological; Humans; Hypotheses; Methods; Mood disorders; Mood effects (Cognitive biases); Motivation; Pessimism; Physical Sciences; Probability; Reinforcement; Reward; Reward (Psychology); Social Sciences; Tracking; United States
• ISSN: 1553-7358; 1553-734X; 1553-7358
• DOI: 10.1371/journal.pcbi.1011707

Positive and negative affective states are respectively associated with optimistic and pessimistic expectations regarding future reward. One mechanism that might underlie these affect-related expectation biases is attention to positive- versus negative-valence features (e.g., attending to the positive reviews of a restaurant versus its expensive price). Here we tested the effects of experimentally induced positive and negative affect on feature-based attention in 120 participants completing a compound-generalization task with eye-tracking. We found that participants’ reward expectations for novel compound stimuli were modulated in an affect-congruent way: positive affect induction increased reward expectations for compounds, whereas negative affect induction decreased reward expectations. Computational modelling and eye-tracking analyses each revealed that these effects were driven by affect-congruent changes in participants’ allocation of attention to high- versus low-value features of compounds. These results provide mechanistic insight into a process by which affect produces biases in generalized reward expectations.