Volumetric Changes in Cerebellar Transverse Zones: Age and Sex Effects in Health and Neurological Disorders
Bibliographic record
Abstract
Cerebellar volumetric changes are intricately linked to aging, with distinct patterns across its transverse zones, the functional subdivisions characterized by unique cytoarchitectural and connectivity profiles. Despite research efforts, the cerebellar aging process in health and neurological disorders remains poorly understood. In this study, we investigated the effects of age and sex on total cerebellum, transverse zone, and lobule volumes using MRI data from over 45,000 participants compiled from six neuroimaging datasets. We also propose a framework for estimating cerebellum age as an indicator of cerebellar health. Significant age-dependent volume reductions were observed across transverse zones, with the central zone (CZ; lobules VI and VII) exhibiting the steepest decline in both health and neurological disorders. This finding highlights the CZ's vulnerability to aging and its critical role in cognitive and emotional processing. We also found prominent sex differences in age-dependent volumetric changes. Males exhibited smaller total intracranial volume (TIV)-adjusted cerebellum volume and faster age-dependent volume reduction than females in both health and mild cognitive impairment (MCI), Alzheimer disease (AD), and Parkinson disease (PD). In contrast, females with schizophrenia (SZ) and cocaine use disorder (CUD) revealed faster age-dependent cerebellar volume reduction than males. Patients with MCI, AD, and PD experienced more pronounced atrophy in the posterior (PZ) and nodular (NZ) zones compared to age-matched healthy controls, while SZ patients were characterized by a more prominent reduction in CZ. In CUD, a non-significant volume decline was observed in all zones compared to the controls. Moreover, our framework for estimating cerebellum age revealed a notable difference in cerebellar aging between healthy individuals and neurological patients. Finally, we charted age-dependent changes in cerebellar volume in healthy individuals, focusing on transverse zones capturing the functional subdivisions. These findings underscore the potential of cerebellar volumetric analysis as a biomarker for early detection and monitoring of neurodegenerative and neuropsychiatric disorders. Our novel approach complements and enhances MRI-based analyses, providing essential insights into the pathogenesis of aging, neurodegeneration, and chronic neuropsychiatric conditions.
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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 | 0.002 |
| 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) | 0.001 | 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".