Microstructural white matter changes mediate age‐related cognitive decline on the Montreal Cognitive Assessment (MoCA)
Bibliographic record
Abstract
Although the relationship between aging and cognitive decline is well established, there is substantial individual variability in the degree of cognitive decline in older adults. The present study investigates whether variability in cognitive performance in community-dwelling older adults is related to the presence of whole brain or tract-specific changes in white matter microstructure. Specifically, we examine whether age-related decline in performance on the Montreal Cognitive Assessment (MoCA), a cognitive screening tool, is mediated by the white matter microstructural decline. We also examine if this relationship is driven by the presence of cardiovascular risk factors or variability in cerebral arterial pulsatility, an index of cardiovascular risk. Sixty-nine participants (aged 43-87) completed behavioral and MRI testing including T1 structural, T2-weighted FLAIR, and diffusion-weighted imaging (DWI) sequences. Measures of white matter microstructure were calculated using diffusion tensor imaging analyses on the DWI sequence. Multiple linear regression revealed that MoCA scores were predicted by radial diffusivity (RaD) of white matter beyond age or other cerebral measures. While increasing age and arterial pulsatility were associated with increasing RaD, these factors did not mediate the relationship between total white matter RaD and MoCA. Further, the relationship between MoCA and RaD was specific to participants who reported at least one cardiovascular risk factor. These findings highlight the importance of cardiovascular risk factors in the presentation of cognitive decline in old age. Further work is needed to establish whether medical or lifestyle management of these risk factors can prevent or reverse cognitive decline in old age.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".