White matter and its relationship with cognition in subjective cognitive decline
Bibliographic record
Abstract
INTRODUCTION: Subjective cognitive decline (SCD) is the earliest stage on the continuum toward Alzheimer's disease. This study examined (1) differences in white matter integrity between individuals with SCD and healthy control subjects and (2) how white matter integrity related to memory and executive function. METHODS: Diffusion tensor imaging and neuropsychological assessment data were retrieved from the Alzheimer's Disease Neuroimaging Initiative database for 30 individuals with SCD and 44 control subjects. RESULTS: Results revealed significantly lower white matter integrity in individuals with SCD relative to control subjects in widespread regions, including the bilateral corticospinal tracts, superior and inferior longitudinal fasciculi, fronto-occipital fasciculi, corpus callosum, forceps major and minor, hippocampi, anterior thalamic radiations, and the cerebellum. There was a widespread relationship between diffusion tensor imaging metrics and executive function in SCD, but not healthy control subjects, and no relationship with memory for either group. DISCUSSION: Relatively lower white matter integrity in SCD may be a useful early biomarker for risk of future cognitive decline. Future research should better characterize the SCD group longitudinally and in individuals at risk for Alzheimer's disease.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".