Processing of visual signals related to self-motion in the cerebellum of pigeons
Bibliographic record
Abstract
In this paper I describe the key features of optic flow processing in pigeons. Optic flow is the visual motion that occurs across the entire retina as a result of self-motion and is processed by subcortical visual pathways that project to the cerebellum. These pathways originate in two retinal-recipient nuclei, the nucleus of the basal optic root (nBOR) and the nucleus lentiformis mesencephali, which project to the vestibulocerebellum (VbC) (folia IXcd and X), directly as mossy fibers, and indirectly as climbing fibers from the inferior olive. Optic flow information is integrated with vestibular input in the VbC. There is a clear separation of function in the VbC: Purkinje cells in the flocculus process optic flow resulting from self-rotation, whereas Purkinje cells in the uvula/nodulus process optic flow resulting from self-translation. Furthermore, Purkinje cells with particular optic flow preferences are organized topographically into parasagittal "zones." These zones are correlated with expression of the isoenzyme aldolase C, also known as zebrin II (ZII). ZII expression is heterogeneous such that there are parasagittal stripes of Purkinje cells that have high expression (ZII+) alternating with stripes of Purkinje cells with low expression (ZII-). A functional zone spans a ZII± stripe pair. That is, each zone that contains Purkinje cells responsive to a particular pattern of optic flow is subdivided into a strip containing ZII+ Purkinje cells and a strip containing ZII- Purkinje cells. Additionally, there is optic flow input to folia VI-VIII of the cerebellum from lentiformis mesencephali. These folia also receive visual input from the tectofugal system via pontine nuclei. As the tectofugal system is involved in the analysis of local motion, there is integration of optic flow and local motion information in VI-VIII. This part of the cerebellum may be important for moving through a cluttered environment.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".