Predictive processing accounts of psychosis: Bottom-up or top-down disruptions, where do we stand?

Predictive processing has revolutionised cognitive neuroscience, offering a comprehensive computational framework for understanding normative behaviour and psychiatric illness. This narrative review evaluates the role of predictive processing in understanding psychosis, revisiting the seminal work of Sterzer and colleagues (2018) seven years later. It consolidates recent experimental evidence on the alteration of priors and sensory likelihoods across different stages of psychosis, in an attempt to reconcile top-down and bottom-up accounts. It evaluates predictive processing alterations across the continuum of psychosis, from non-clinical psychotic experiences to high-risk and first-episode psychosis, to schizophrenia, exploring the explanatory potential of predictive processing as a transdiagnostic framework. We discuss the translational potential of predictive processing, including its use as a biomarker and in therapeutic interventions. We emphasize the need for standardised paradigms and longitudinal studies to advance predictive processing theories in clinical practice. By offering a unified theoretical perspective, this review aims to inspire further research into the neuro-computational mechanisms underlying psychosis and enhance our understanding of psychiatric disorders.