Dopamine Prediction Errors in Reward Learning and Addiction: From Theory to Neural Circuitry

Midbrain dopamine (DA) neurons are proposed to signal reward prediction error (RPE), a fundamental parameter in associative learning models. This RPE hypothesis provides a compelling theoretical framework for understanding DA function in reward learning and addiction. New studies support a causal role for DA-mediated RPE activity in promoting learning about natural reward; however, this question has not been explicitly tested in the context of drug addiction. In this review, we integrate theoretical models with experimental findings on the activity of DA systems, and on the causal role of specific neuronal projections and cell types, to provide a circuit-based framework for probing DA-RPE function in addiction. By examining error-encoding DA neurons in the neural network in which they are embedded, hypotheses regarding circuit-level adaptations that possibly contribute to pathological error signaling and addiction can be formulated and tested. Dopamine neurons presumably encode reward-prediction error, a key parameter in contemporary models of associative learning. In this review, Keiflin and Janak integrate theoretical models and recent experimental findings to examine how drug-induced adaptations could contribute to pathological error signaling and addiction.