The meningeal–cerebellar axis: a new perspective on cerebellar development
Bibliographic record
Abstract
The cerebellum is a highly organized brain structure best known for its roles in motor control and sensorimotor integration. While cerebellar development has traditionally been attributed to intrinsic genetic programs and local cell-cell interactions, emerging evidence indicates that extrinsic cues particularly signals from the meninges also play a critical role in shaping its maturation. Studies indicate that the meninges release cytokines, chemokines, and growth factors including CXCL12, IGF-1, IL-33, FGF2, TGF-β, and retinoic acid that influence granule cell precursor (GCPs) proliferation, Purkinje cell (PC) maturation, radial glia organization, and synaptic refinement. In addition, meningeal immune cells form a dynamic interface that potentially shapes neuronal positioning and cerebellar circuit formation. Disruption of these signals through genetic mutations, immune dysregulation, or environmental insults lead to impaired foliation, ectopic neuronal migration, and aberrant cerebellar architecture. This review focuses on in vivo findings supporting an emerging concept of the meningeal-cerebellar axis in development. Understanding cerebellar maturation within this broader context offers new perspectives on the origins of neurodevelopmental disorders and points toward novel avenues for therapeutic intervention.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".