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Poster Session C: Friday, August 15, 2:00 – 5:00 pm, de Brug & E‑Hall

Correspondence between reinforcement learning phenotypes and transdiagnostic clinical symptomatology across development

Noam Goldway¹, Nora Harhen, Qingqing Yang², Sophia Nielsen, Levi Solomyak, Sam Zorowitz, Gal Shoval, Eran Eldar, Yael Niv³, Catherine Hartley⁴; ¹King's College London, University of London, ²Ohio State University, Columbus, ³Princeton University, ⁴New York University

Presenter: Noam Goldway

Adolescence is marked by neurocognitive changes and heightened vulnerability to psychiatric disorders. Yet, it remains unclear how age-related changes in learning processes known to contribute to adult psychopathology may contribute to the emergence of psychiatric symptoms. In a sample of 889 individuals aged 10–25, we related reinforcement learning computational phenotypes to psychopathology measured along multiple dimensions of dysfunction. Participants completed three learning tasks targeting sensitivity to positive versus negative outcomes, Pavlovian bias (automatic/innate versus instrumental/arbitrary), and model-based control (goal-directed planning). Factor analysis of self-report questionnaires identified four symptom dimensions: rumination, physiological anxiety, impulsivity/dysregulation, and anhedonia. Symptom expression varied with age, and each symptom domain demonstrated a distinct computational signature.

Topic Area: Memory, Spatial Cognition & Skill Learning

Extended Abstract: Full Text PDF