Cerebral correlates of salient prediction error for different rewards and punishments

Learning to predict rewarding and aversive outcomes is based on the comparison between predicted and actual outcomes (prediction error: PE). Recent electrophysiological studies reported that during a Pavlovian procedure some dopamine neurons code a classical PE signal while a larger population of dopaminergic neurons reflect a "salient" prediction error (SPE) signal, being excited both by unpredictable aversive events and by rewards. Yet, it is still unclear whether specific human brain structures receiving afferents from dopaminergic neurons code a SPE and whether this signal depends upon reinforcer type. Here, we used a model-based functional magnetic resonance imaging approach implementing a reinforcement learning model to compute the PE while subjects underwent a Pavlovian conditioning procedure with 2 types of rewards (pleasant juice and monetary gain) and 2 types of punishments (aversive juice and aversive picture). The results revealed that activity of a brain network composed of the striatum, anterior insula, and anterior cingulate cortex covaried with a SPE for appetitive and aversive juice. Moreover, amygdala activity correlated with a SPE for these 2 reinforcers and for aversive pictures. These results provide insights into the neurobiological mechanisms underlying the ability to learn stimuli-rewards and stimuli-punishments contingencies, by demonstrating that the network reflecting the SPE depends upon reinforcement's type.