The cerebellum in Alzheimer’s disease: evaluating its role in cognitive decline
Bibliographic record
Abstract
The cerebellum has long been regarded as essential only for the coordination of voluntary motor activity and motor learning. Anatomical, clinical and neuroimaging studies have led to a paradigm shift in the understanding of the cerebellar role in nervous system function, demonstrating that the cerebellum appears integral also to the modulation of cognition and emotion. The search to understand the cerebellar contribution to cognitive processing has increased interest in exploring the role of the cerebellum in neurodegenerative and neuropsychiatric disorders. Principal among these is Alzheimer's disease. Here we review an already sizeable existing literature on the neuropathological, structural and functional neuroimaging studies of the cerebellum in Alzheimer's disease. We consider these observations in the light of the cognitive deficits that characterize Alzheimer's disease and in so doing we introduce a new perspective on its pathophysiology and manifestations. We propose an integrative hypothesis that there is a cerebellar contribution to the cognitive and neuropsychiatric deficits in Alzheimer's disease. We draw on the dysmetria of thought theory to suggest that this cerebellar component manifests as deficits in modulation of the neurobehavioural deficits. We provide suggestions for future studies to investigate this hypothesis and, ultimately, to establish a comprehensive, causal clinicopathological disease model.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".