Evidence map›Paper›PMID 33676820›Full record

ReviewSchizophrenia research2022

Rethinking delusions: A selective review of delusion research through a computational lens.

Brandon K Ashinoff, Nicholas M Singletary, Seth C Baker, Guillermo Horga

Abstract readReview
In one paragraph

Review in Schizophrenia research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

30 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Metacognitive training (MCT) for psychosis: a systematic review and grade recommendations.European psychiatry : the journal of the Association of European Psychiatrists · 2025
    Pooled it
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Brandon K AshinoffDepartment of Psychiatry, Columbia University, 1051 Riverside Drive, New York, NY, USA; New York State Psychiatric Institute, 1051 Riverside Drive, New York, NY, USA.
Nicholas M SingletaryDepartment of Psychiatry, Columbia University, 1051 Riverside Drive, New York, NY, USA; New York State Psychiatric Institute, 1051 Riverside Drive, New York, NY, USA.
Seth C BakerDepartment of Psychiatry, Columbia University, 1051 Riverside Drive, New York, NY, USA; New York State Psychiatric Institute, 1051 Riverside Drive, New York, NY, USA.
Guillermo HorgaDepartment of Psychiatry, Columbia University, 1051 Riverside Drive, New York, NY, USA; New York State Psychiatric Institute, 1051 Riverside Drive, New York, NY, USA. Electronic address: HorgaG@nyspi.columbia.edu.

Funding

Training in Schizophrenia and Psychotic Disorders: From Animal Models to PatientsT32MH018870 · NIMH · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI Guillermo Horga, Christoph Kellendonk · 1988 to 2026
$9.8M
Deficient Belief Updating as a Convergent Computational Mechanism of PsychosisR01MH114965 · NIMH · NEW YORK STATE PSYCHIATRIC INSTITUTE DBA RESEARCH FOUNDATION FOR MENTAL HYGIENE, INC · PI HORGA, GUILLERMO · 2018 to 2022
$3.6M
Individualized risk prediction in persons at clinical high-risk for psychosis using neuromelanin-sensitive MRI.R01MH117323 · NIMH · NEW YORK STATE PSYCHIATRIC INSTITUTE DBA RESEARCH FOUNDATION FOR MENTAL HYGIENE, INC · PI HORGA, GUILLERMO · 2018 to 2022
$3.3M
NIMH NIH HHS R01 MH114965NIMH NIH HHS R01 MH117323NIMH NIH HHS T32 MH018870
6 · The paper itself

Abstract

Delusions are rigid beliefs held with high certainty despite contradictory evidence. Notwithstanding decades of research, we still have a limited understanding of the computational and neurobiological alterations giving rise to delusions. In this review, we highlight a selection of recent work in computational psychiatry aimed at developing quantitative models of inference and its alterations, with the goal of providing an explanatory account for the form of delusional beliefs in psychosis. First, we assess and evaluate the experimental paradigms most often used to study inferential alterations in delusions. Based on our review of the literature and theoretical considerations, we contend that classic draws-to-decision paradigms are not well-suited to isolate inferential processes, further arguing that the commonly cited 'jumping-to-conclusion' bias may reflect neither delusion-specific nor inferential alterations. Second, we discuss several enhancements to standard paradigms that show promise in more effectively isolating inferential processes and delusion-related alterations therein. We further draw on our recent work to build an argument for a specific failure mode for delusions consisting of prior overweighting in high-level causal inferences about partially observable hidden states. Finally, we assess plausible neurobiological implementations for this candidate failure mode of delusional beliefs and outline promising future directions in this area.

Indexed as

DelusionsPsychotic DisordersHumansBeads taskComputational psychiatryDelusionsInferencePsychosisSchizophrenia

Identifiers

PMID33676820
PMCPMC8413395

What OpenQuestion holds

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Read underepoch 390

Registered trials

None linked

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.