Comparative Neuromorphology of Purkinje Neurons Across Species
Bibliographic record
Abstract
Neuromorphology of cells vary both across and within species, the differences of which contribute to a variety of cellular functions. Purkinje cells (PCs) in the cerebellum play a key role in the fine tuning of motor control and movement, and are characterized by their large soma and distinctive pattern of dendritic branching. However, outside of few selected taxa, the neuromorphology of PCs have not been well characterized. Here, we investigate PC neuromorphology in a representative reptile (leopard gecko), mammal (laboratory mouse), and bird (domestic chicken). Using a modified Golgi‐Cox protocol, differences in PC neuromorphology were quantified using Sholl and branched structure analyses. While PCs in all species demonstrated elaborate patterns of dendritic arborization, we quantified species‐specific differences in both cell size and branching complexity. The average dendritic length of PCs in geckos and mice were comparable, while those of chickens were almost twice as long. Chicken PCs are also characterized by a greater dendritic diameter and dendritic volume. Mouse and chicken PCs were significantly more complex than those of geckos, based on the number of dendritic terminals. Taken together, our findings demonstrate that even within the same cell type, there is considerable neuromorphological variation between species, potentially related to aspects of phylogeny, ecology, and functional morphology. Support or Funding Information Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery Grants 400358 to MKV and 2019‐04989 to CDCB
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".