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Predictive processing accounts of psychosis: bottom-up or top-down disruptions

Nature Mental Health volume 4, pages 60–84 (2026)Cite this article

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Abstract

Predictive processing has revolutionized cognitive neuroscience, offering a comprehensive computational framework for understanding normative behavior and psychiatric illness. This narrative Review evaluates the role of predictive processing in understanding psychosis, revisiting the seminal work of Sterzer and colleagues. 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 (that is, overly precise priors/noisy sensations) and bottom-up (that is, noisy priors/overly precise sensations) 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 standardized 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.

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Fig. 1: Bayesian accounts for psychosis.
Fig. 2: Categorization of empirical studies in Table 1 as supporting top-down or bottom-up accounts.
Fig. 3: Categorization of studies as implicit or explicit and perceptual or cognitive across authors.

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Author notes

  1. These authors contributed equally: Marta I. Garrido, Franziska Knolle.

Authors and Affiliations

  1. Melbourne School of Psychological Sciences, The University of Melbourne, Melbourne, Victoria, Australia

    Isabella Goodwin & Marta I. Garrido

  2. Neuroscience of Addiction and Mental Health Program, Healthy Brain and Mind Research Centre, Faulty of Health Sciences, Australian Catholic University, Melbourne, Victoria, Australia

    Isabella Goodwin

  3. Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK

    Kelly M. J. Diederen

  4. Institute of Cognitive Neuroscience, University College London, London, UK

    Emily J. Hird

  5. Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA

    Veith Weilnhammer

  6. Graeme Clark Institute for Biomedical Engineering, The University of Melbourne, Melbourne, Victoria, Australia

    Marta I. Garrido

  7. Department of Neuroradiology, School of Medicine and Health, Technical University of Munich, Munich, Germany

    Franziska Knolle

  8. School of Medicine and Health, TUM Neuroimaging Center, Technical University Munich, Munich, Germany

    Franziska Knolle

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Contributions

I.G., K.M.J.D., E.J.H., V.W., M.I.G. and F.K. contributed to the conceptualization of the structure and content of the manuscript, contributed written sections and reviewed all sections. M.I.G. created Fig. 1. F.K. created Fig. 3, and I.G. created Fig. 2 and Tables 1, 2.

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Correspondence to Marta I. Garrido.

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Goodwin, I., Diederen, K.M.J., Hird, E.J. et al. Predictive processing accounts of psychosis: bottom-up or top-down disruptions. Nat. Mental Health 4, 60–84 (2026). https://doi.org/10.1038/s44220-025-00558-5

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