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Record W7118259604 · doi:10.1002/alz70856_104872

Individual functional connectivity constraints on spatial progression of tau pathology in Alzheimer's disease

2025· article· en· W7118259604 on OpenAlexaff
Harry H. Behjat, Jacob W. Vogel, Olof Strandberg, Nicola Spotorno, Jonathan Rittmo, Lyduine E. Collij, Alexa Pichet Binette, Yu Xiao, Danielle van Westen, Erik Stomrud, Sebastian Palmqvist, Niklas Mattsson‐Carlgren, Dimitri Van De Ville, Ruben Smith, Oskar H. Hansson, Rik Ossenkoppele

Bibliographic record

VenueAlzheimer s & Dementia · 2025
Typearticle
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsUniversité de MontréalInstitut Universitaire de Gériatrie de Montréal
Fundersnot available
KeywordsTau pathologyDementiaDiseaseFunctional connectivityNeuroimagingAlzheimer's diseaseCognitionCognitive impairment

Abstract

fetched live from OpenAlex

Abstract Background Tau PET patterns show notable spatial heterogeneity across subjects in Alzheimer's disease (AD). In vitro findings suggest that tau may spread ‘prion‐like’ across neuronal connections in an activity‐dependent manner, a hypothesis strengthened by group‐level studies showing association between resting‐state functional connectivity (FC) networks and tau deposition patterns. This hypothesis would be better supported by evidence at the individual level, an investigation that is the focus of this study. Method Structural MRI, resting‐state fMRI, tau‐PET, and amyloid‐β (Aβ)‐PET data from 733 participants aged 50+ from the BioFINDER‐2 study were used: 402 cognitively unimpaired (CU, CSF Aβ+=89), 157 with mild cognitive impairment (MCI), and 174 with AD dementia, with 523 follow‐up tau‐PET scans (323 CU, 109 MCI, 91 AD); individuals with MCI or AD dementia were all CSF Aβ+. fMRI data were pre‐processed, and surface parcellated in subject‐space. To reduce instability in subject‐level estimations while retaining individual information, template FC (CU Aβ‐ group‐average) and each participant's individual FC were used to build an individualised ‘hybrid’ FC; template and subject‐specific regional FC profiles were integrated by statistically estimating the contribution of each in explaining the participant's tau‐PET. FC‐based results were compared against using canonical PET patterns estimated from the distribution of regional PET values across the cohort. Result Hybrid (i.e. individualized) FC explained tau‐PET patterns better than template FC across the continuum (Fig‐1A), which exceeded chance based on null modeling (Fig‐1B). Baseline hybrid FC also explained follow‐up tau‐PET patterns better than template FC (Fig‐1C). For individuals with MCI or AD dementia, hybrid FC alone explained tau better than enforcing canonical tau patterns on everyone (Fig‐2), whereas canonical patterns better explained the data of individuals at early stages of the disease. However, in contrast to tau‐PET patterns, individual Aβ‐PET patterns–for which prion‐like spread hypothesis was not assumed—were not better explained by hybrid FC than by Aβ‐PET canonical patterns (Fig‐3). Conclusion Our results provide compelling implicit evidence in support for the hypothesis of tau spread via communicating neurons at the individual‐level. These findings strengthen the potential of using brain network‐based models for sample stratification in AD clinical trials and prognosis in clinical practice.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.049
GPT teacher head0.302
Teacher spread0.254 · 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
Published2025
Admission routes1
Has abstractyes

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