Hallucinations and strong priors
Open accessAbstract
Hallucinations, perceptions in the absence of objectively identifiable stimuli, illustrate the constructive nature of perception. Here, we highlight the role of prior beliefs as a critical elicitor of hallucinations. Recent empirical work from independent laboratories shows strong, overly precise priors can engender hallucinations in healthy subjects and that individuals who hallucinate in the real world are more susceptible to these laboratory phenomena. We consider these observations in light of work demonstrating apparently weak, or imprecise, priors in psychosis. Appreciating the interactions within and between hierarchies of inference can reconcile this apparent disconnect. Data from neural networks, human behavior, and neuroimaging support this contention. This work underlines the continuum from normal to aberrant perception, encouraging a more empathic approach to clinical hallucinations.
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The predictive processing framework explains psychosis and associated alterations in salience processing as a result of aberrant encoding of precision in different regions or circuits.
“This framework explains psychosis and associated alterations in salience processing as a result of aberrant encoding of precision in different regions or circuits (28, 94) (figure 2).”
From Aberrant Salience, Information Processing, and Dopaminergic Signaling in People at Clinical High Risk for Psychosis (2020) · cites this paper as [94]
The ‘Hallucinations and Perception’ and ‘Corollary Discharge’ sections link hallucinations and psychosis-related experiences to the relative precision of priors and sensory information. ‘Neural Network Models of Hallucinations’ also distinguishes dysfunction at different hierarchical levels and in different brain regions. The paper’s account is chiefly about hallucinations, however; the cited passages do not establish the broader claim about psychosis and associated alterations in salience processing. (LLM, conf=0.84)
Experimental — accuracy not yet measuredRelying more on prediction rather than on sensory evidence may create false beliefs that lead to psychosis.
“Relying more on prediction rather than on sensory evidence may create false beliefs that lead to psychosis (16).”
From A Predictive Coding Perspective on Mismatch Negativity Impairment in Schizophrenia (2020) · cites this paper as [16]
In “Hallucinations and Perception” (page unavailable), the paper proposes that predictions outweighing sensory input may produce hallucinations. In “Neural Network Models of Hallucinations” (page unavailable), it links priors about agency to auditory hallucinations in schizophrenia, alongside delusions and other false concepts. It does not say that prediction-driven false beliefs lead to the onset of psychosis. (LLM, conf=0.84)
Experimental — accuracy not yet measuredIn each psychiatric condition, symptoms are linked to particular disturbances in how predictions, prediction errors, or their precision weights are handled in the brain.
“In each case, symptoms are linked to particular disturbances in how predictions, prediction errors, or their precision weights are handled in the brain (32).”
From Predictive coding and neurocomputational psychiatry: a mechanistic framework for understanding mental disorders (2026) · cites this paper as [32]
In ‘Data consistent with the strong prior account’ (page unavailable), the paper links hallucinations in psychosis and Parkinson’s disease to prior expectations and their precision. In ‘Corollary Discharge’ (page unavailable), it also links impaired prediction of self-generated actions to psychotic symptoms. It does not establish a particular disturbance for symptoms in each psychiatric condition; the authors say that distinguishing how underlying pathologies produce different symptoms remains a challenge. (LLM, conf=0.84)
Experimental — accuracy not yet measuredThe more sensory prediction error is generated, the more likely it is that an action or thought has external as opposed internal or endogenous causes.
“This means that the more sensory prediction error is generated, the more likely it is that an action or thought has external as opposed internal or endogenous causes (Frith 2005; Corlett et al. 2019).”
From Consciousness in active inference: Deep self-models, other minds, and the challenge of psychedelic-induced ego-dissolution (2021) · cites this paper as Corlett et al. 2019
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Conséquences psychopathologiques du confinement
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Predictive processing as a systematic basis for identifying the neural correlates of consciousness
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Forms of prediction in the nervous system
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Self-citationAn integrative framework for perceptual disturbances in psychosis
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Delusion Proneness is Linked to a Reduced Usage of Prior Beliefs in Perceptual Decisions
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The neural correlates of hierarchical predictions for perceptual decisions
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“Relying more on prediction rather than on sensory evidence may create false beliefs that lead to psychosis (16).”
BackgroundApical amplification—a cellular mechanism of conscious perception?
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Hallucinations in posttraumatic stress disorder: insights from predictive coding
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“This means that the more sensory prediction error is generated, the more likely it is that an action or thought has external as opposed internal or endogenous causes (Frith 2005; Corlett et al. 2019).”
BackgroundIs prediction nothing more than multi-scale pattern completion of the future?
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Association between failures in perceptual updating and the severity of psychosis in schizophrenia
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Relating glutamate, conditioned, and clinical hallucinations via 1H-MR spectroscopy
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“Predictive coding accounts propose that symptoms such as hallucinations and delusions arise from aberrant precision-weighting of prediction errors—either attributing too much weight to low-level sensory signals or too little to top-down priors (Adams et al. 2013; Corlett et al. 2019; Friston 2016).”
Shaw, A. D., Sumner, R. L., & Berndt, L. C. S. (2026) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2025.1713833 · Cited by 9 · see citing works
“In each case, symptoms are linked to particular disturbances in how predictions, prediction errors, or their precision weights are handled in the brain (32).”
Global Adversities, the Media, and Mental Health
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Paranoid and teleological thinking give rise to distinct social hallucinations in vision
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The generalized Hierarchical Gaussian Filter
Weber, L. A., Waade, P. T., Legrand, N., Møller, A. H., Stephan, K. E., & Mathys, C. (2026) · eLife · doi:10.7554/elife.110174
- Authors
- Corlett, P. R., Horga, G., Fletcher, P. C., Alderson-Day, B., Schmack, K., & Powers, A. R.
- Affiliations
- Yale University (US)
- Columbia University (US)
- University of Cambridge (GB)
- Cold Spring Harbor Laboratory (US)
- Corresponding author
- Corlett, Philip R.
- Venue
- Trends in Cognitive Sciences
- Publisher
- Elsevier BV
- Published
- 2019-02
- Volume
- 23
- Issue
- 2
- Pages
- 114-127
- ISSN
- 1364-6613 (ISSN-L)
- PMC
- PMC6368358
- OpenAlex
- W2905702364
- Cited by
- 534
- References
- 138
- Citations by year
- 2026: 74 · 2025: 76 · 2024: 79 · 2023: 76 · 2022: 69 · 2021: 64 · 2020: 78 · 2019: 16 · 2018: 1 · 2017: 1
- FWCI
- 5.31
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Trends in Cognitive Sciences (publishedVersion, cc-by)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Cold Spring Harbor Laboratory Institutional Repository (Cold Spring Harbor Laboratory) (submittedVersion)
- Durham Research Online (Durham University) (submittedVersion, cc-by)
- Funders
- National Institute of Mental Health (R01MH112887, R21MH116258)
- Wellcome Trust (WT108720)
- Leopoldina–German National Academy of Sciences
- Bernard Wolfe health Neuroscience Fund
- NIMH (R01MH114965)
- Brain and Behavior Research Foundation
- Burroughs Wellcome Fund
- Yale University
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Hallucinations in medical conditions
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Health Sciences › Medicine › Psychiatry and Mental health › Schizophrenia research and treatment
- Keywords
- hallucinations, prior beliefs, prior distributions, perception, psychosis, hierarchical inference, artificial neural networks, neuroimaging
- MeSH terms
- Hallucinations, Humans, Illusions, Nerve Net, Speech Perception
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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