Pavlovian conditioning-induced hallucinations result from overweighting of perceptual priors
Open accessAbstract
Neural mechanisms for hallucinations: Pairing a stimulus in one modality (vision) with a stimulus in another (sound) can lead to task-induced hallucinations in healthy individuals. After many trials, people eventually report perceiving a nonexistent stimulus contingent on the presence of the previously paired stimulus. Powers et al. investigated how different groups of volunteers and patients respond to this conditioning paradigm. They used behavior, neuroimaging, and computational modeling to dissect the effect of perceptual priors versus sensory evidence on such induced hallucinations. People who are more prone to hear voices were more susceptible to the induced auditory hallucinations. The network of brain regions that was active during the conditioned hallucinations resembled the network observed during clinical symptom capture in individuals who hallucinate while in a brain scanner. Science , this issue p. 596
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People with hallucinations had strong perceptual priors that were not present in psychotic patients who did not hallucinate and who may have had weak priors.
“Powers et al. (2017) found that people with hallucinations had strong perceptual priors that were not present in psychotic patients who did not hallucinate and who, indeed, may have had weak priors (74).”
From The Predictive Coding Account of Psychosis (2018) · cites this paper as [74]
The paper’s discussion (page not provided) says that stronger perceptual beliefs and prior weighting distinguished participants with hallucinations from those without; its four groups included psychotic patients who did not hear voices. It does not establish that this non-hallucinating psychotic group had weak perceptual priors. Its suggestion of a possible weak prior concerns volatility and psychosis more broadly, not that group specifically. (LLM, conf=0.84)
Experimental — accuracy not yet measuredThe presence of strong priors and their immunity to updating were associated with strong insula and hippocampal responses respectively.
“The presence of strong priors and their immunity to updating were associated with strong insula and hippocampal responses respectively (74).”
From The Predictive Coding Account of Psychosis (2018) · cites this paper as [74]
The supplied passage labeled Abstract (page unavailable) reports greater anterior insula parameter estimates in participants with hallucinations and links hallucinations to stronger perceptual priors. It also links hippocampal responses to belief updating, but does not say that resistance to updating was associated with stronger hippocampal responses; the reduced sensitivity to changing contingencies was reported for participants with psychosis. (LLM, conf=0.83)
Experimental — accuracy not yet measuredUsing a model of hierarchical Bayesian inference, researchers could link schizophrenia to an overly strong reliance on perceptual priors.
“and link schizophrenia to an overly strong reliance on perceptual priors [9].”
From How Do Expectations Shape Perception? (2018) · cites this paper as [9]
The Abstract (page not supplied) describes a hierarchical perceptual model and reports stronger prior weighting in participants who heard voices. That finding held regardless of psychotic-illness diagnosis, so the paper does not establish overly strong perceptual priors as a feature of schizophrenia generally. (LLM, conf=0.88)
Experimental — accuracy not yet measuredComputational modelling indicates that patients with hallucinations have more heavily weighted priors than non-hallucinators, and that this is associated with striatal dopamine function.
“Auditory hallucinations are a common psychotic symptom and computational modelling indicates that patients with hallucinations have more heavily weighted priors than non-hallucinators (97, 98), and that this is associated with striatal dopamine function (97).”
From Aberrant Salience, Information Processing, and Dopaminergic Signaling in People at Clinical High Risk for Psychosis (2020) · cites this paper as [98]
The modelling results in the indexed copy (section labelled Abstract; page unavailable) say the prior-weighting parameter distinguished hallucinators from non-hallucinators. The paper reports caudate activation during conditioned hallucinations, but does not establish an association between prior weighting and striatal dopamine function. That part of the claim is unsupported. (LLM, conf=0.88)
Experimental — accuracy not yet measuredHealthy controls show aberrant precision-weighting, as well as aberrant frontostriatal prediction error signalling associated with psychotic-like experiences.
“Moreover, HC show aberrant precision-weighting, as well as aberrant frontostriatal PE signalling associated with psychotic-like experiences (98, 103).”
From Aberrant Salience, Information Processing, and Dopaminergic Signaling in People at Clinical High Risk for Psychosis (2020) · cites this paper as [98]
The section labelled Abstract (page unavailable) reports that prior weighting distinguished participants with hallucinations from those without, and includes a voice-hearing control group without a diagnosed illness. It does not establish aberrant weighting in healthy controls generally. Its imaging results describe regions engaged during conditioned hallucinations, not aberrant frontostriatal prediction-error signalling associated with psychotic-like experiences. (LLM, conf=0.86)
Experimental — accuracy not yet measured
Schizophrenia can be cast as a disorder of belief updating: the filters that should correct false beliefs via error signals are themselves corrupted, leaving aberrant beliefs unchecked.
“In summary, schizophrenia can be cast as a disorder of belief updating: the filters that should correct false beliefs via error signals are themselves corrupted, leaving aberrant beliefs (paranoia, hallucinations) unchecked (38).”
From Predictive coding and neurocomputational psychiatry: a mechanistic framework for understanding mental disorders (2026) · cites this paper as [38]
The paper’s modeling passages (section labeled Abstract; page unavailable) report stronger perceptual priors in participants with hallucinations and reduced sensitivity to changing contingencies in participants with psychosis. That supports a belief-updating account of hallucinations and psychosis, but the paper does not establish that corrupted error-signal filters leave false beliefs or paranoia unchecked across schizophrenia generally. (LLM, conf=0.86)
Experimental — accuracy not yet measuredSuch models permit priors that bias perception toward unstructured noise or volatility, making genuine signals harder to identify.
“Such models also permit priors that bias perception toward unstructured noise or volatility, making genuine signals harder to identify (12, 38).”
From Predictive coding and neurocomputational psychiatry: a mechanistic framework for understanding mental disorders (2026) · cites this paper as [38]
The indexed copy’s main-text passages (labeled Abstract; page unavailable) report that stronger perceptual priors accompanied reports of tones that were absent, and that voice-hearing groups had low perceptual sensitivity. They do not describe priors biasing perception toward unstructured noise; the volatility finding instead concerns participants with psychosis failing to recognize changing stimulus contingencies. The claim’s proposed mechanism for making genuine signals harder to identify is therefore more specific than the paper supports. (LLM, conf=0.82)
Experimental — accuracy not yet measuredThe impact of priors on perception may be enhanced in those with hallucinations.
“However, recent neural data suggest that they do (72, 73), and that the impact of priors on perception may be enhanced in those with hallucinations (74–76).”
From The Predictive Coding Account of Psychosis (2018) · cites this paper as [74]
People who hear voices were found to be more susceptible to conditioning-induced hallucinations, and Bayesian modeling showed stronger perceptual priors.
“Recently, people who hear voices were found to be more susceptible to conditioning-induced hallucinations, and accordingly, modeling in a Bayesian framework showed stronger perceptual priors (74).”
From The Predictive Coding Account of Psychosis (2018) · cites this paper as [74]
Patients with auditory hallucinations put more weight on predictions than on sensory evidence when compared with healthy individuals.
“Several studies reported that patients with auditory hallucinations put more weight on predictions than on sensory evidence when compared with healthy individuals (14, 15).”
From A Predictive Coding Perspective on Mismatch Negativity Impairment in Schizophrenia (2020) · cites this paper as [14]
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Paranoid and teleological thinking give rise to distinct social hallucinations in vision
Castiello, S., Ongchoco, J. D. K., van Buren, B., Scholl, B. J., & Corlett, P. R. (2024) · Communications Psychology · doi:10.1038/s44271-024-00163-9 · Cited by 6 · see citing works
Self-citationTargeted neural network interventions for auditory hallucinations: Can TMS inform DBS?
Taylor, J. J., Krystal, J. H., D'Souza, D. C., Gerrard, J. L., & Corlett, P. R. (2018) · Schizophrenia Research · doi:10.1016/j.schres.2017.09.020 · Cited by 5 · see citing works
Self-citationThe 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
Self-citationClosed-form predictive coding via hierarchical Gaussian filters
Baskakovs, A., Estebe, S., Enevoldsen, K., Nielbo, K., Mathys, C., & Legrand, N. (2026) · arXiv · doi:10.48550/arxiv.2605.20293
“…prediction-error semantics, and individually fittable parameters has made the framework a reference in cognitive neuroscience [Lawson et al., 2017, Powers et al., 2017, Mikus et al., 2025], with open-source implementations such as PyHGF [Legrand et al., 2024] distributed via TAPAS [Frässle et…”
Self-citation
- Authors
- Powers, A. R., Mathys, C., & Corlett, P. R.
- Affiliations
- Yale University (US)
- Scuola Internazionale Superiore di Studi Avanzati (IT)
- Corresponding author
- Corlett, P. R.
- Venue
- Science
- Published
- 2017-08-11
- Volume
- 357
- Issue
- 6351
- Pages
- 596-600
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- PMC
- PMC5802347
- OpenAlex
- W2744535290
- Cited by
- 684
- References
- 30
- Citations by year
- 2026: 64 · 2025: 76 · 2024: 71 · 2023: 71 · 2022: 74 · 2021: 85 · 2020: 97 · 2019: 71 · 2018: 59 · 2017: 16
- FWCI
- 38.16
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- Zurich Open Repository and Archive (University of Zurich) (acceptedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- SDL (submittedVersion)
- MPG.PuRe (Max Planck Society) (submittedVersion)
- Zurich Open Repository and Archive (University of Zurich) (submittedVersion)
- Zurich Open Repository and Archive (University of Zurich)
- Funders
- National Institutes of Health (award309038, UL1 TR000142)
- National Institute of Mental Health (award309037, 5T32MH019961, award309043, 5R01MH067073-09)
- NARSAD (award308859)
- IMHRO (award308860)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Hallucinations in medical conditions
- Health Sciences › Medicine › Psychiatry and Mental health › Schizophrenia research and treatment
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Keywords
- voice hearing, auditory hallucinations, classical conditioning, perceptual priors, top-down cognitive control, treatment seeking, perceptual learning, computational modeling of perception
- MeSH terms
- Acoustic Stimulation, Adult, Brain, Computer Simulation, Conditioning, Classical, Female, Hallucinations, Hearing, Humans, Male, Models, Neurological, Nerve Net, Perception, Photic Stimulation, Psychotic Disorders, Voice, Neuroimaging
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