Abstract

Positive overgeneralization -- the tendency to generalize from specific successes to broad expectations of future reward -- has been linked to vulnerability to mania. Because positive overgeneralization has primarily been assessed using self-report measures, we have limited insight into the underlying cognitive process. Here, we introduce a behavioral paradigm designed to quantify how learned value generalizes to novel stimuli. We quantify individual generalization profiles by fitting psychometric functions to choice data. In an online transdiagnostic study (N=163), we show that task-based breadth of reward generalization is associated with both higher self-reported positive overgeneralization and subclinical bipolar symptoms. To provide a computational account of positive overgeneralization, we implement a reinforcement-learning model in which self-efficacy modulates the influence of anticipated future value during learning. We show that increasing this modulation reproduces the broader value propagation observed empirically. Together, these findings provide a behavioral and computational framework for studying positive overgeneralization, and suggest a mechanistic pathway by which success-related shifts in value representations may bias learning in ways relevant to bipolar risk.