Visual Performance and Cortical Atrophy in Vision-Related Brain Regions Differ Between Older Adults with (or at Risk for) Alzheimer’s Disease
Bibliographic record
Abstract
BACKGROUND: Visual impairment is associated with deficits in cognitive function and risk for cognitive decline and Alzheimer's disease (AD). OBJECTIVE: The purpose of this study was to characterize the degree of visual impairment and explore the association thereof with cortical atrophy in brain regions associated with visual processing in individuals with (or at risk for) AD. METHODS: Using the Comprehensive Assessment of Neurodegeneration and Dementia (COMPASS-ND) dataset, we analyzed vision and brain imaging data from three diagnostic groups: individuals with subjective cognitive decline (SCD; N = 35), mild cognitive impairment (MCI; N = 74), and mild AD (N = 30). We used ANCOVAs to determine whether performance on reading acuity and contrast sensitivity tests differed across diagnostic groups. Hierarchical regression analyses were applied to determine whether visual performance predicted gray matter volume for vision-related regions of interest above and beyond group membership. RESULTS: The AD group performed significantly worse on reading acuity (F(2,138) = 4.12, p < 0.01, ω2 = 0.04) compared to the SCD group and on contrast sensitivity (F(2,138) = 7.6, p < 0.01, ω2 = 0.09) compared to the SCD and MCI groups, which did not differ from each other. Visual performance was associated with volume in some vision-related structures beyond clinical diagnosis. CONCLUSION: Our findings demonstrate poor visual performance in AD and that both group membership and visual performance are predictors of cortical pathology, consistent with the idea that atrophy in visual areas and pathways contributes to the functional vision deficits observed in AD.
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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 | 0.000 | 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) | 0.002 | 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".