ReviewSchizophrenia bulletin2017
Explaining Delusions: Reducing Uncertainty Through Basic and Computational Neuroscience.
Review in Schizophrenia bulletin, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 3 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
28 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Comprehensive investigation of predictive processing: A cross- and within-cognitive domains fMRI meta-analytic approach.Human brain mapping · 2024Pooled it
- Meta-analysis of human prediction error for incentives, perception, cognition, and action.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2022Pooled it
- Meta-analytic evidence for altered mesolimbic responses to reward in schizophrenia.Human brain mapping · 2018Pooled it
- A review and integration of models on delusion maintenance.Psychological medicine · 2026Review
- The Relationship Between Schizotypy and Latent Inhibition and Conditioned Inhibition.Schizophrenia bulletin open · 2026Article
- Using machine learning to predict persecutory beliefs based on aetiological models of delusions identified in a systematic literature search.Communications psychology · 2025Article
- 20 Years of Aberrant Salience in Psychosis: What Have We Learned?The American journal of psychiatry · 2025Review
- Delusional Unreality and Predictive Processing.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2025Article
- Embracing variability in the search for biological mechanisms of psychiatric illness.Trends in cognitive sciences · 2025Review
- A prefrontal thalamocortical readout for conflict-related executive dysfunction in schizophrenia.Cell reports. Medicine · 2024Article
- Different learning aberrations relate to delusion-like beliefs with different contents.Brain : a journal of neurology · 2024Article
- Lesions to the mediodorsal thalamus, but not orbitofrontal cortex, enhance volatility beliefs linked to paranoia.Cell reports · 2024Article
- Can the Predictive Processing Framework Explain the Persistence of Delusional Beliefs?Schizophrenia bulletin · 2023Article
- Assumed shared belief about conspiracy theories in social networks protects paranoid individuals against distress.Scientific reports · 2023Article
- Belief Updating and Paranoia in Individuals With Schizophrenia.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2022Article
- Reinforcement learning detuned in addiction: integrative and translational approaches.Trends in neurosciences · 2022Review
- Models of Dynamic Belief Updating in Psychosis-A Review Across Different Computational Approaches.Frontiers in psychiatry · 2022Review
- Paranoia and belief updating during the COVID-19 crisis.Nature human behaviour · 2021Article
- Unlocking the reinforcement-learning circuits of the orbitofrontal cortex.Behavioral neuroscience · 2021Article
- Leveraging Basic Science for the Clinic-From Bench to Bedside.JAMA psychiatry · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Delusions, the fixed false beliefs characteristic of psychotic illness, have long defied understanding despite their response to pharmacological treatments (e.g., D2 receptor antagonists). However, it can be challenging to discern what makes beliefs delusional compared with other unusual or erroneous beliefs. We suggest mapping the putative biology to clinical phenomenology with a cognitive psychology of belief, culminating in a teleological approach to beliefs and brain function supported by animal and computational models. We argue that organisms strive to minimize uncertainty about their future states by forming and maintaining a set of beliefs (about the organism and the world) that are robust, but flexible. If uncertainty is generated endogenously, beliefs begin to depart from consensual reality and can manifest into delusions. Central to this scheme is the notion that formal associative learning theory can provide an explanation for the development and persistence of delusions. Beliefs, in animals and humans, may be associations between representations (e.g., of cause and effect) that are formed by minimizing uncertainty via new learning and attentional allocation. Animal research has equipped us with a deep mechanistic basis of these processes, which is now being applied to delusions. This work offers the exciting possibility of completing revolutions of translation, from the bedside to the bench and back again. The more we learn about animal beliefs, the more we may be able to apply to human beliefs and their aberrations, enabling a deeper mechanistic understanding.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.