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Record W2168864682 · doi:10.1109/iembs.1990.692065

Cortical Computation Of Motion Energy- Location Of The Squarer

2005· article· en· W2168864682 on OpenAlexafffund
Robert C. Emerson, Michael J. Korenberg, Mark C. Citron

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldNeuroscience
TopicNeural dynamics and brain function
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsVisual cortexThresholdingComputationComputer scienceWhite noiseComputer visionArtificial intelligenceAlgorithmNeuroscienceImage (mathematics)Telecommunications

Abstract

fetched live from OpenAlex

Directionally selective complex cells in the cat's visual cortex compute a modulus or energy term that removes the phase sensitivity of earlier stages processing information from a moving image. We have represented in a cascade model the chain of neurons from retina to cortex as a linear/nonlincar/linear (LNL) sequence of transformations. We use system identification techniques to define the nature of these transformations directly from responses of a cortical complex cell to a single presentation of a white-noise stimulus sequence. The static nonlinearity, N, resembles a gradual full-wave-rectifying, or squaring function, which we believe can be effected by soft-thresholding each of the linear ONand OFF-channel signals and then summing them in the cortex. These connections would provide a mechanism for the squaring operation needed to explain cortical computation of motion energy.

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: Simulation or modeling · 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
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.020
GPT teacher head0.245
Teacher spread0.225 · 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 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

Citations2
Published2005
Admission routes2
Has abstractyes

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