Circular inference: mistaken belief, misplaced trust

- Predictive coding has emerged as the dominant framework for perception and motor control.
- Belief propagation is a more general mechanism for inference in neural networks.
- Impairments in the neural excitation/inhibition ratio generate aberrant beliefs.
- This pathological form of belief propagation is named circular inference.
- Circular inference predicts hallucinations, delusions and reduced susceptibility to illusions in schizophrenia.

At the clinical level, psychosis can be formalized as the formation of aberrant beliefs or percepts and has been proposed to result from disruptions in the excitation/inhibition (E/I) balance in cortical microcircuitry. However, these two conceptual approaches toward psychosis have yet to be correlated. Here, we review recent empirical and computational studies that enable an integrated understanding of how the brain may generate beliefs along a spectrum ranging from normal to pathology. We mainly focus on hierarchical predictive coding and circular inference. We will expose how these two frameworks may account for hallucinations, delusions, and reduced susceptibility to illusions, and we will additionally critically discuss their respective strengths and weaknesses as well as potential future research directions.