Neuroimaging Signatures and Cognitive Correlates of the Montreal Cognitive Assessment Screen in a Nonclinical Elderly Sample
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The Montreal Cognitive Assessment (MoCA) screen was developed as a brief instrument to identify mild cognitive impairment and dementia among older individuals. To date, limited information is available regarding the neuroimaging signatures associated with performance on the scale, or the relationship between the MoCA and more comprehensive cognitive screening measures. The present study examined performances on the MoCA among 111 non-clinical older adults (ages 51-85) enrolled in a prospective study of cognitive aging. Participants were administered the MoCA, Mini-Mental State Exam (MMSE), and the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). A subset of participants (N = 69) underwent structural 3 T magnetic resonance imaging (MRI) to define the volumes of total frontal gray matter, total hippocampus, T2-weighted subcortical hyperintensities (SH), and total brain volume. The results revealed significant correlations between the total score on the MoCA and total score on the RBANS and MMSE, though the strength of the correlations was more robust between the MoCA and the RBANS. Modest correlations between individual subscales of the MoCA and neuroimaging variables were evident, but no patterns of shared variance emerged between the MoCA total score and neuroimaging indices. In contrast, total brain volume correlated significantly with total score on the RBANS. These results suggest that additional studies are needed to define the significance of MoCA scores relative to brain integrity among an older population.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it