Learning reinforces curiosity for related information - Yaniv Abir; Jane Mok; Christopher A. Baldassano; Caroline B. Marvin; Daphna Shohamy (Proceedings of the National Academy of Sciences, 2026)
Human curiosity is dynamic, however the principles governing its fluctuations remain debated. Here, we test two competing hypotheses about how past learning shapes subsequent curiosity and memory. The first, based on the “optimal arousal” theory, proposes that satisfying curiosity reduces subsequent curiosity. The second, grounded in reinforcement learning, suggests that satisfying curiosity strengthens it. To distinguish between these accounts, we analyzed information-seeking decisions from 5,831 participants, who chose whether to wait for answers to a range of questions. We examined how engagement with questions and answers, as well as information prediction errors, influenced subsequent curiosity. Reading satisfying answers increased curiosity compared to reading dissatisfying ones. Critically, this depended on semantic similarity: prior learning enhances subsequent curiosity only when new information is related to previously learned content. These results suggest that curiosity operates as an information-seeking policy learned through reinforcement. Humans may therefore seek information not only to improve future instrumental decisions, but also to learn what to be curious about.