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Psychiatric diagnosis and treatment have historically taken a symptom-based approach, with less attention on identifying underlying symptom-producing mechanisms. Recent efforts have illuminated the extent to which different underlying circuitry can produce phenotypically similar symptomatology (e.g. psychosis in bipolar disorder vs schizophrenia). Computational modelling makes it possible to identify and mathematically differentiate behaviorally-unobservable, specific reinforcement-learning (RL) differences in schizophrenia (SZ) patients versus other disorders, likely due to a higher reliance on prediction-error(PE)-driven learning associated with basal ganglia, and under-reliance on explicit value representations associated with OFC.