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Record W4412094995 · doi:10.1111/psyg.70060

The Neural Correlates of Delusions in Dementia: A Scoping Review

2025· review· en· W4412094995 on OpenAlexafffund
Bryn H. Manns, Karina Atanasiu, Dominique Lumley, M. Mallar Chakravarty, Serge Gauthier, Ian Gold

Bibliographic record

VenuePsychogeriatrics · 2025
Typereview
Languageen
FieldArts and Humanities
TopicMental Health and Psychiatry
Canadian institutionsDouglas Mental Health University InstituteMcGill University
FundersMcGill University
KeywordsDementiaDefault mode networkSalience (neuroscience)PsychiatryPsychologyNeural correlates of consciousnessMEDLINEClinical psychologyIntervention (counseling)MedicineCognitionCognitive psychologyInternal medicineDisease

Abstract

fetched live from OpenAlex

Delusions are common symptoms of dementia and are clinically significant. The objective of this scoping review is to identify possible neural correlates. MEDLINE (OVID), EMBASE (OVID) and Web of Science were searched in December 2020 for the keywords 'delusions' and 'dementia'. Two informal searches were carried out subsequently. Results were limited to those in English. Intervention and study characteristics were extracted using standardised tools. Eighteen published studies, using four distinct experimental methods, were included, and 31 brain regions were identified as correlates of delusions. No region was identified consistently within included studies or found in more than four studies. Despite the range of brain regions identified, a number form part of the default mode network, the salience network or the central executive network. We explore the implications of these findings for understanding delusions in dementia.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.022
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0120.011
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.069
GPT teacher head0.385
Teacher spread0.316 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes2
Has abstractyes

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