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Stereopsis Outweighs Gravity in the Control of the Eyes

2001· article· en· W1577480873 on OpenAlexafffund
H. Misslisch, Douglas Tweed, Bernhard Hess

Bibliographic record

VenueJournal of Neuroscience · 2001
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsUniversity of Toronto
FundersMedical Research CouncilMedical Research Council CanadaSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungNational Science Foundation
KeywordsVergence (optics)ClockwiseGazeReflexPrimateNeuroscienceEye movementPsychologyNoseAnatomyPhysicsMedicineComputer scienceArtificial intelligenceOpticsRotation (mathematics)Psychoanalysis

Abstract

fetched live from OpenAlex

The eyes are controlled by multiple brain circuits, some phylogenetically old and some new, whose aims may conflict. Old otolith reflexes counterroll the eyes when the head tilts relative to gravity. Newer vergence mechanisms coordinate the eyes to aid stereoptic vision. We show that counterroll hinders stereopsis, weakly when you look into the distance but strongly when you look near. The resolution of this conflict is that counterroll virtually vanishes when monkeys look close, i.e., stereopsis overrides gravity-driven reflexes but only on near gaze. This balance between gyroscopic and stereoptic mechanisms explains many other puzzling features of primate gaze control, such as the weakness of our otolith-ocular reflexes even during far viewing and the strange geometry of the primate counterpitch reflex, which rolls the eyes clockwise when monkeys look leftward while their heads are tipped nose up, but rolls them counterclockwise when the monkeys look rightward, and reverses this pattern when the head is tipped nose down.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.078
GPT teacher head0.340
Teacher spread0.262 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations59
Published2001
Admission routes2
Has abstractyes

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