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Cellular response to texture and form defined by motion in area 19 of the cat

2000· article· en· W2074176598 on OpenAlexafffund
Paul S. Khayat, Dave Saint‐Amour, Stéphane Molotchnikoff, Franco Leporé, Jean‐Paul Guillemot

Bibliographic record

VenueEuropean Journal of Neuroscience · 2000
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsUniversité du Québec à MontréalUniversité de Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBar (unit)Texture (cosmology)CATSSensitivity (control systems)Materials sciencePhysicsArtificial intelligenceComputer scienceMedicineInternal medicineImage (mathematics)

Abstract

fetched live from OpenAlex

The present study examined the neuronal sensitivity in area 19 of the cat to a motion-defined bar and to texture. Sensitivity was tested in normal, lesioned (areas 17-18) and split-chiasm cats using a kinematogram, as well as a textured bar drifting on a uniform light background and a light bar drifting on a stationary textured background. Texture density was varied. The results indicate that almost all cells of area 19 recorded in the three groups of cats responded to a motion-defined bar or to its edges. Texture density influenced the responses in that the discharge rate increased as density decreased. However, the majority of cells were sensitive to the highest texture density kinematogram. Moreover, the neural responses of all cats were either independent of the density of the textured bar or background, or were modulated by it. These results show that cells in area 19 can signal the presence of a kinetic bar and that the density of either the textured bar, the background or both can influence figure-ground detection. The results are interpreted with respect to how various inputs influence the function of area 19.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
Research integrity0.0000.000
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 head0.044
GPT teacher head0.273
Teacher spread0.230 · 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 designObservational
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

Citations11
Published2000
Admission routes2
Has abstractyes

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