Cortical and Subcortical Grey Matter Abnormalities in White Matter Hyperintensities and Subsequent Cognitive Impairment
Bibliographic record
Abstract
Grey matter (GM) alterations may contribute to cognitive decline in individuals with white matter hyperintensities (WMH) but no consensus has yet emerged. Here, we investigated cortical thickness and grey matter volume in 23 WMH patients with mild cognitive impairment (WMH-MCI), 43 WMH patients without cognitive impairment, and 55 healthy controls. Both WMH groups showed GM atrophy in the bilateral thalamus, fronto-insular cortices, and several parietal-temporal regions, and the WMH-MCI group showed more extensive and severe GM atrophy. The GM atrophy in the thalamus and fronto-insular cortices was associated with cognitive decline in the WMH-MCI patients and may mediate the relationship between WMH and cognition in WMH patients. Furthermore, the main results were well replicated in an independent dataset from the Alzheimer's Disease Neuroimaging Initiative database and in other control analyses. These comprehensive results provide robust evidence of specific GM alterations underlying WMH and subsequent cognitive impairment.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".