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Record W1974699871 · doi:10.1002/cne.21108

Two optic flow pathways from the pretectal nucleus lentiformis mesencephali to the cerebellum in pigeons (<i>Columba livia</i>)

2006· article· en· W1974699871 on OpenAlexaff
Janelle M.P. Pakan, Douglas R. Wylie

Bibliographic record

VenueThe Journal of Comparative Neurology · 2006
Typearticle
Languageen
FieldNeuroscience
TopicVestibular and auditory disorders
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPretectal areaOptokinetic reflexCerebellumNeuroscienceBiologyMossy fiber (hippocampus)NucleusAnatomyVestibular systemMidbrainCentral nervous system

Abstract

fetched live from OpenAlex

Neurons in the pretectal nucleus lentiformis mesencephali (LM) are involved in the analysis of optic flow. LM provides mossy fiber inputs to folia VI-VIII of the posterior cerebellum and IXcd of the vestibulocerebellum. Previous research has shown that the vestibulocerebellum is involved in visual-vestibular integration supporting gaze stabilization. The function of folia VI-VIII in pigeons is not well understood; however, these folia receive input from a tectopontine system, which is likely involved with analyzing local motion as opposed to optic flow. We sought to determine whether the mossy fiber input from LM to IXcd differs from that to VI-VIII. Fluorescent retrograde tracers were injected into these folia, and the pattern of labeling in LM was observed. Large multipolar neurons were labeled throughout the rostrocaudal extent of LM. There was a clear mediolateral difference: 74.3% of LM neurons projecting to IXcd were located in the lateral subnucleus of LM (LMl), whereas 73.8% of LM neurons projecting to VI-VIII were found in medial LM (LMm). This suggests that the subnuclei of LM have differing roles. In particular, the LMl-IXcd pathway is involved in generating the optokinetic response. We suggest that the pathway from LMm to VI-VIII is integrating optic flow and local motion to support various oculomotor and visuomotor behaviors, including obstacle avoidance during locomotion.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.419
Threshold uncertainty score0.455

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.028
GPT teacher head0.261
Teacher spread0.233 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations40
Published2006
Admission routes1
Has abstractyes

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