Work

Trial-by-trial learning signatures in self-reported affect that require introspection and are orthogonal to social choice.

Year: 2025

Type: article

Abstract: = 1,806; U.S. online samples), we probe affective prediction errors to document and dissect a core analogy: Learning reflected in decreasing (affective) prediction errors over time. We found that decreases in affective prediction errors depended on introspection, as prior experience with a task absent affective reports did not yield the same decreases (Experiment 1). A task manipulation forcing participants to alter their choices showed increased affective prediction errors, ruling out simple response alignment (i.e., to report feeling "as predicted"; Experiment 2). Decreases in affective prediction errors transferred across structurally similar tasks (i.e., stealing vs. giving money; Experiment 3) and affective measures (i.e., from pride or guilt to valence; Experiment 4). Although affective prediction errors often tracked with social choice behavior overall, their absolute decrease over time did not. In sum, we present evidence for convergence (i.e., learning and transfer) and divergence (i.e., introspection dependence and predictive epiphenomenality) between affective prediction errors and conventional prediction errors. Implications for affective measures as a proxy for subjective value are discussed. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

Source: Emotion

DOI: 10.1037/emo0001623

Authors: Marius C. Vollberg, David Sander, Todd A. Hare

Institutions: University of Zurich, University of Geneva

Language: English

Topic: Neural and Behavioral Psychology Studies

Subfield: Cognitive Neuroscience

Field: Neuroscience

Domain: Life Sciences

Open Access status: green

Funder: Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung

Award: Computational principles of affect in social learning and decision making