Computational reinforcement learning, reward (and punishment), and dopamine in psychiatric disorders.

ABSTRACT: In the DSM-5, psychiatric diagnoses are made based on self-reported symptoms and clinician-identified signs. Though helpful in choosing potential interventions based on the available regimens, this conceptualization of psychiatric diseases can limit basic science investigation into their underlying causes. The reward prediction error (RPE) hypothesis of dopamine neuron function posits that phasic dopamine signals encode the difference between the rewards a person expects and experiences. The computational framework from which this hypothesis was derived, temporal difference reinforcement learning (TDRL), is largely focused on reward processing rather than punishment learning. Many psychiatric disorders are characterized by aberrant behaviors, expectations, reward processing, and hypothesiz

SUBMITTER: Liebenow B 

PROVIDER: S-EPMC9630918 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature