MétaCan
Menu
Back to cohort
Record W2064400011 · doi:10.1167/11.7.14

The magnitude of center-surround facilitation in the discrimination of amplitude spectrum is dependent on the amplitude of the surround

2011· article· en· W2064400011 on OpenAlexafffund
Aaron Johnson, B. Richard, Bruce C. Hansen, Dave Ellemberg

Bibliographic record

VenueJournal of Vision · 2011
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsUniversité de MontréalConcordia University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAmplitudeMagnitude (astronomy)FacilitationCenter (category theory)Spectrum (functional analysis)PhysicsOpticsPsychologyNeuroscienceChemistryQuantum mechanics

Abstract

fetched live from OpenAlex

Recent studies explored the sensitivity of human perception to natural images, in particular the sensitivity of the visual system to discriminate changes in the amplitude spectrum slope. Previous slope discrimination experiments were carried out with stimuli presented either in the fovea or the parafovea/periphery and show that both yield poor discrimination at very steep or relatively shallow slopes. We verified if the well-known center-surround spatial interactions that operate early on in the visual processing stream influence the perception of real-world images. The results show that amplitude slope discrimination is greatly reduced (i.e., flat) when the stimulus is viewed in isolation. However, when a 2° target is placed within a surround containing an amplitude spectrum slope of 1 or 1.3, we see significant facilitation in detecting variations in the slope of the amplitude spectrum, particularly when the target contains an amplitude spectrum slope of 1 and 1.3. The results suggest that our visual system is sensitive to contextual interactions for stimuli that have the characteristics of natural images.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.545
Threshold uncertainty score0.197

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 integrity0.0000.000
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 head0.103
GPT teacher head0.345
Teacher spread0.243 · 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 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

Citations6
Published2011
Admission routes2
Has abstractyes

Explore more

Same venueJournal of VisionSame topicVisual perception and processing mechanismsFrench-language works237,207