Visual-Cerebellar Pathways and Their Roles in the Control of Avian Flight
Bibliographic record
Abstract
In this paper, we review the connections and physiology of visual pathways to the cerebellum in birds and consider their role in flight. We emphasize that there are two visual pathways to the cerebellum. One is to the vestibulocerebellum (folia IXcd and X) that originates from two retinal-recipient nuclei that process optic flow: the nucleus of the basal optic root (nBOR) and the pretectal nucleus lentiformis mesencephali (LM). The second is to the oculomotor cerebellum (folia VI-VIII), which receives optic flow information, mainly from LM, but also local visual motion information from the optic tectum, and other visual information from the ventral lateral geniculate nucleus (Glv). The tectum, LM and Glv are all intimately connected with the pontine nuclei, which also project to the oculomotor cerebellum. We believe this rich integration of visual information in the cerebellum is important for analyzing motion parallax that occurs during flight. Finally, we extend upon a suggestion by Ibbotson (2017) that the hypertrophy that is observed in LM in hummingbirds might be due to an increase in the processing demands associated with the pathway to the oculomotor cerebellum as they fly through a cluttered environment while feeding.
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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 | 0.002 | 0.001 |
| 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".