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Record W2007213401 · doi:10.1167/15.7.4

From orientations to objects: Configural processing in the ventral stream

2015· review· en· W2007213401 on OpenAlexafffund
Hugh R. Wilson, Frances Wilkinson

Bibliographic record

VenueJournal of Vision · 2015
Typereview
Languageen
FieldNeuroscience
TopicFace Recognition and Perception
Canadian institutionsYork University
FundersCanadian Institutes of Health Research
KeywordsReceptive fieldNeurophysiologyFunctional magnetic resonance imagingArtificial intelligencePsychologyObject (grammar)HierarchyIllusory contoursNeuroscienceVisual fieldCognitive neuroscience of visual object recognitionVisual systemDorsumCurse of dimensionalityPsychophysicsPattern recognition (psychology)Computer scienceVisual cortexComputer visionPerceptionBiologyAnatomyOptical illusion

Abstract

fetched live from OpenAlex

The ventral or form vision hierarchy comprises a sequence of cortical areas in which successively more complex visual attributes are extracted, beginning with contour orientations in V1 and culminating in face and object representations at the highest levels. In addition, ventral areas exhibit increasing receptive field diameter by a factor of approximately three from area to area, and conversely neuron density decreases. We argue here that this is consistent with configural combination of adjacent orientations to form curves or angles, followed by combination of these to form descriptions of object shapes. Substantial data from psychophysics, functional magnetic resonance imaging (fMRI), and neurophysiology support this organization, and computational models consistent with it have also been proposed. We further argue that a key to the role of the ventral stream is dimensionality reduction in object representations.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.003

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 head0.150
GPT teacher head0.451
Teacher spread0.300 · 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 designNot applicable
Domainnot available
GenreReview

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
Published2015
Admission routes2
Has abstractyes

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