We found a match
Your institution may have rights to this item. Sign in to continue.
- Title
Affect-congruent attention modulates generalized reward expectations.
- Authors
Bennett, Daniel; Radulescu, Angela; Zorowitz, Sam; Felso, Valkyrie; Niv, Yael
- Abstract
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. Author summary: Positive affective states are associated with optimistic future expectations, and negative affect is associated with pessimistic future expectations. However, the cognitive mechanisms that underpin these affect-congruent shifts in reward expectations remain unclear. To investigate this question, we focused on feature-based attention, the process by which attention to the different features of a stimulus influences the estimated value of that stimulus. We formulated a new compound generalisation paradigm to investigate how individuals allocate attention to high- versus low-value components of novel compound stimuli, and adopted a multi-method approach combining eye-tracking and computational modelling of behavioural data. Crucially, our central experimental manipulation was a controlled between-subjects laboratory affect induction during the generalisation phase of the task. The results of this study clearly identify feature-based attention as a cognitive mechanism by which affective states influence reward expectations: in positive affective states, participants attended more strongly to high-value cues within compound stimuli (and therefore formed more optimistic reward expectations for the compounds). In negative affective states, the converse was true: participants attended more strongly to low-value cues within compound stimuli, and therefore formed more pessimistic reward expectations for the compounds. These behavioural and modelling findings were separately corroborated by evidence from eye-tracking data.
- Subjects
REWARD (Psychology); EYE tracking; AFFECTIVE neuroscience; ATTENTION; ATTENTIONAL bias; AFFECT (Psychology); STIMULUS &; response (Psychology)
- Publication
PLoS Computational Biology, 2023, Vol 19, Issue 12, p1
- ISSN
1553-734X
- Publication type
Article
- DOI
10.1371/journal.pcbi.1011707