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Record W4413901637 · doi:10.1002/brb3.70774

Neural Representations of Neuropsychiatric Symptoms in Alzheimer's Disease Continuum Using Pathology‐Based Functional Connectivity Analysis

2025· article· en· W4413901637 on OpenAlexfundno aff
Taein Lee, Yong Jeong

Bibliographic record

VenueBrain and Behavior · 2025
Typearticle
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchNational Institutes of HealthGenentechIXICOH. Lundbeck A/SServierEisaiMeso Scale DiagnosticsNational Research Foundation of KoreaNational Research FoundationNorthern California Institute for Research and EducationUniversity of Southern CaliforniaPfizerBioClinicaBiogenMinistry of Science and ICT, South KoreaMinistry of Health and WelfareEli Lilly and CompanyU.S. Department of DefenseAlzheimer's Disease Neuroimaging InitiativeNovartis Pharmaceuticals CorporationBristol-Myers SquibbAlzheimer's AssociationFoundation for the National Institutes of Health
KeywordsApathyNeuroimagingFunctional magnetic resonance imagingPositron emission tomographyPsychologyStructural equation modelingDementiaAmyloid (mycology)NeuroscienceAlzheimer's diseaseDiseaseMedicineInternal medicinePathologyMachine learningComputer science

Abstract

fetched live from OpenAlex

OBJECTIVES: Neuropsychiatric symptoms (NPS) in the Alzheimer's disease continuum affect the quality of life for patients and caregivers. Therefore, elucidating the mechanisms of NPS is needed to better understand NPS and enhance patient care. Several studies have investigated them using neuroimaging; however, none have considered the regional coexistence of amyloid-beta and tau pathologies and its association with functional networks. In this study, we aim to identify the neural correlates of NPS considering the molecular and functional levels of neural representation. METHODS: This study included data from amyloid-positive participants in the Alzheimer's Disease Neuroimaging Initiative database with positron emission tomography (PET), functional magnetic resonance imaging, NPS scores, and demographic data within one year and categorized them into groups with or without NPS factors. NPS were assessed using the neuropsychiatric inventory (NPI) and grouped into affective, apathy, hyperactivity, or psychosis factors. Amyloid-beta and tau accumulation measured by PET were compared between groups per region. Differences in functional connectivity of NPS- or NPS-type-specific pathologically altered regions were investigated using seed-to-voxel analysis. Further, a generalized linear model was constructed using the NPI score for each factor as the dependent variable, with functional connectivity strength, tau, and amyloid-beta accumulation as predictors. RESULTS: Significant differences were observed in amyloid-beta and tau accumulation and functional connectivity between groups. The right middle temporal gyrus (rMTG) was associated with the affective factor, and the right parahippocampal and right fusiform gyri were associated with the apathy factor. Moreover, the generalized linear model was able to predict affective factor severity mainly based on the functional connectivity strength between the rMTG and the left supramarginal and angular gyri. CONCLUSIONS: We identified the key regions specific to affective and apathy factors based on the areas with coexistence of amyloid-beta and tau pathologies and the accompanying altered functional connectivity.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation 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 score0.043
Threshold uncertainty score0.649

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.045
GPT teacher head0.322
Teacher spread0.277 · 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 teacher head, 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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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