The cerebellum shrinks faster than normal ageing in <scp>A</scp>lzheimer's disease but not in mild cognitive impairment
Bibliographic record
Abstract
BACKGROUND: While acceleration in age-related cerebral atrophy has been well documented in Alzheimer's disease, the cerebellar contributions to this effect have not been thoroughly investigated. OBJECTIVE: This study investigated cerebellar volume and atrophy rate using magnetic resonance imaging in individuals with normal cognition (CN), mild cognitive impairment (MCI), and Alzheimer's disease (AD). METHODS: Two hundred twenty-nine CN, 398 MCI and 191 AD participants of stage I ADNI database with screening scans were evaluated for cerebellar volume. Of those, 758 individuals with two or more follow-up scans were categorized into stable, converted, and reverted CN, MCI and AD and evaluated for cerebellar atrophy rate. RESULTS: Cerebellar volume was 2.5% larger in CN than in those with AD but there were no differences between CN and MCI and MCI and AD in cross-sectional analysis. Similarly, the atrophy rate was 49% larger in AD and 64% larger in MCI who converted to AD but no difference was detected between CN and MCI. There were no association between education and APOEe4 and cerebellar volume or cerebellar atrophy across the diagnostic groups. CONCLUSION: Cerebellar atrophy contributes to Alzheimer's clinical progression but mostly at the late stage of the disease. However, even in the late stage shrinkage rate is less than the average of the shrinkage in the cerebrum and is not associated with AD moderators. This suggests that cerebellar involvement is secondary to cerebral involvement and can be due to network connection spread regardless of the primary pathology. Hum Brain Mapp, 2017. © 2017 Wiley Periodicals, Inc. Hum Brain Mapp 38:3141-3150, 2017. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc. Hum Brain Mapp 38:3141-3150, 2017. © 2017 Wiley Periodicals, Inc.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".