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

J Haarsma,G K Murray,T J Spencer,H Ziauddeen,I Goodyer,P C Fletcher,C Miller,T Katthagen,J D Griffin,K M J Diederen,H J Taverne

doi:10.1038/s41380-020-0803-8

Abstract

Recent theories of cortical function construe the brain as performing hierarchical Bayesian inference. According to these theories, the precision of prediction errors plays a key role in learning and decision-making, is controlled by dopamine and contributes to the pathogenesis of psychosis. To test these hypotheses, we studied learning with variable outcome-precision in healthy individuals after dopaminergic modulation with a 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 prediction errors benefits learning in health and is impaired in psychosis. FMRI revealed coding of unsigned prediction errors, which signal surprise, 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). In contrast to our previous work, we did not observe significant precision-weighting of signed prediction errors, which signal valence, in the midbrain and ventral striatum in the healthy controls (or patients) in the psychosis study. 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.

Highlights

A common theme in contemporary theories of brain function, ranging from perception [1] to reinforcementThese authors contributed : K
In this study we aimed to investigate if precision weighting of signed and unsigned prediction error signals is altered in psychosis
We found that unsigned prediction errors are coded in the superior frontal cortex (SFC), where the unsigned prediction error signal is coded relative to the precision of environmental outcomes; that the degree of precision-weighting benefits learning, is mediated by dopamine, is perturbed in FEP, and relates to schizotypy in a health

Summary

Introduction

A common theme in contemporary theories of brain function, ranging from perception [1] to reinforcement. Large unsigned prediction errors signal that the brain’s model of the world is inaccurate, thereby increasing the amount that is learned from new information This can be achieved in various ways, including a non-Bayesian approach by using a dynamic learning rate parameter [22, 23] or a Bayesian approach by decreasing the precision of prior beliefs [24, 25] across different levels in the hierarchy so that new sensory information has more of an impact on learning [2]. In these hierarchical models both signed and unsigned prediction errors are weighted by their precision. We examined how individual differences in computational learning signals and brain precision-weighting signals relate to clinical psychosis, and psychotic-like thinking in health (schizotypy)

Methods

G H Performance error per condition and group

Results

Discussion

Compliance with ethical standards