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Record W2896117347 · doi:10.1016/j.jalz.2018.06.2873

F4‐03‐02: INCREASED ATROPHY IN THE DEFAULT MODE NETWORK IS ASSOCIATED WITH DEVELOPMENT OF DELUSIONS IN ALZHEIMER'S DISEASE

2018· article· en· W2896117347 on OpenAlexaff
Winnie Qian, Colleen P. Millikin, Zahinoor Ismail, Eric E. Smith, David G. Muñoz, Tom A. Schweizer, Corinne E. Fischer

Bibliographic record

VenueAlzheimer s & Dementia · 2018
Typearticle
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsUniversity of TorontoUniversity of ManitobaUniversity of CalgarySt. Michael's Hospital
Fundersnot available
KeywordsPrecuneusPosterior cingulateDefault mode networkPsychologyDelusionAtrophyAlzheimer's diseaseLingual gyrusAudiologyCognitionNeuroimagingSuperior frontal gyrusDelusional disorderMiddle frontal gyrusNeuroscienceDiseasePsychiatryMedicineInternal medicinePsychosis

Abstract

fetched live from OpenAlex

Approximately one in every three patients with Alzheimer's disease(AD) develops delusions, which are associated with greater cognitive and functional impairments, increased caregiver burden, and higher mortality rates compared to their non-delusional counterparts. Neuroimaging studies have not yet reached a consensus regarding the regions responsible for delusions, as several distributed areas have been inconsistently implicated. This suggests that delusions are associated with deficits in neural networks. The current study assessed the longitudinal brain changes following the development of delusions in AD, and contrasted the findings with a comparable non-delusional group. We also compared the two cohorts at the pre-delusional and post-delusional scans. Data were obtained from the National Alzheimer's Coordinating Center (NACC) database. Fifty-four AD patients were analyzed, including 19 who were non-delusional at baseline and developed delusions during follow-up(AD+D) and 35 who did not develop delusions over follow-up(AD-D). Utilizing voxel-based morphometry, the gray matter changes between the last non-delusional MRI scan was compared to the first delusional scan in the AD+D group, and changes were assessed in the AD-D group over a similar period. Baseline and follow-up brain differences between the cohorts were also examined. There were no significant differences in demographics, cognitive status, or time between scans between AD+D and AD-D groups (Table 1). Comparing post- to pre-delusional scans in the AD+D group, there were significant atrophy in the precuneus, inferior parietal lobules, posterior cingulate cortex, medial frontal gyrus, and medial temporal gyrus, which are nodes of the default mode network(DMN). The AD-D group, on the other hand, did not exhibit any significant atrophy over the same period. Prior to delusional onset, the AD+D group showed greater volume in the DMN nodes compared to AD-D. At the post-delusional scan, AD+D was characterized by lower frontal volume compared to AD-D. The development of delusions appeared to correspond to atrophy of regions within the DMN. Delusions may be an in vivo marker of DMN functional dysconnectivity. Abnormalities in DMN connectivity have been implicated in several neuropsychiatric disorders, including AD and schizophrenia. Our findings suggest that alternative brain network modulating therapies may be used to target delusions in AD.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.042
GPT teacher head0.275
Teacher spread0.233 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2018
Admission routes1
Has abstractyes

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