Precision-weighting of cortical unsigned prediction error signals benefits learning, is mediated by dopamine, and is impaired in psychosis

Abstract Recent theories of cortical function construe the brain as performing hierarchical Bayesian inference. According to these theories, the precision of cortical unsigned prediction error (i.e., surprise) signals plays a key role in learning and decision-making, to be controlled by dopamine, and to contribute to the pathogenesis of psychosis. To test these hypotheses, we studied learning with variable outcome-precision in healthy individuals after dopaminergic modulation with placebo, a dopamine receptor agonist bromocriptine or a dopamine receptor antagonist sulpiride (dopamine study n=59), and in patients with early psychosis (psychosis study n=74: 20 participants with First Episode Psychosis, 30 healthy controls and 24 participants with At Risk Mental State attenuated psychotic symptoms). Behavioural computational modelling indicated that precision-weighting of unsigned prediction errors benefits learning in health, and is impaired in psychosis. FMRI revealed coding of unsigned prediction errors relative to their precision in superior frontal cortex (replicated across studies, combined n=133), which was perturbed by dopaminergic modulation, impaired in psychosis, and associated with task performance and schizotypy (schizotypy correlation in 86 healthy volunteers). We conclude that healthy people, but not patients with first episode psychosis, take into account the precision of the environment when updating beliefs. Precision-weighting of cortical prediction error signals is a key mechanism through which dopamine modulates inference and contributes to the pathogenesis of psychosis.