Chapter 23 - Opponent Brain Systems for Reward and Punishment Learning: Causal Evidence From Drug and Lesion Studies in Humans

Abstract

Approaching rewards and avoiding punishments are core principles that govern the adaptation of behavior to the environment. The machine learning literature has proposed formal algorithms to account for how agents adapt their decisions to optimize outcomes. In principle, these reinforcement learning models could be equally applied to positive and negative outcomes, ie, rewards and punishments. Yet many neuroscience studies have suggested that reward and punishment learning might be underpinned by distinct brain systems. Reward learning has been shown to recruit midbrain dopaminergic nuclei and ventral prefrontostriatal circuits. The picture is less clear regarding the existence and anatomy of an opponent system: several hypotheses have been formulated for the neural implementation of punishment learning. In this chapter, we review the evidence for and against each hypothesis, focusing on human studies that compare the effects of neural perturbation, following drug administration and/or pathological conditions, on reward and punishment learning.