Cognitively defined Alzheimer's dementia subgroups have distinct atrophy patterns
Bibliographic record
Abstract
Abstract INTRODUCTION We sought to determine structural magnetic resonance imaging (MRI) characteristics across subgroups defined based on relative cognitive domain impairments using data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and to compare cognitively defined to imaging‐defined subgroups. METHODS We used data from 584 people with Alzheimer's disease (AD) (461 amyloid positive, 123 unknown amyloid status) and 118 amyloid‐negative controls. We used voxel‐based morphometry to compare gray matter volume (GMV) for each group compared to controls and to AD‐Memory. RESULTS There was pronounced bilateral lower medial temporal lobe atrophy with relative cortical sparing for AD‐Memory, lower left hemisphere GMV for AD‐Language, anterior lower GMV for AD‐Executive, and posterior lower GMV for AD‐Visuospatial. Formal asymmetry comparisons showed substantially more asymmetry in the AD‐Language group than any other group ( p = 1.15 × 10 −10 ). For overlap between imaging‐defined and cognitively defined subgroups, AD‐Memory matched up with an imaging‐defined limbic predominant group. DISCUSSION MRI findings differ across cognitively defined AD subgroups.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".