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Record W2021530477 · doi:10.1167/2.7.222

Center-surround effects on orientation discrimination with visual noise stimuli

2010· article· en· W2021530477 on OpenAlexaff
Nicole D. Anderson, Kathryn M. Murphy, Dennis Jones

Bibliographic record

VenueJournal of Vision · 2010
Typearticle
Languageen
FieldPsychology
TopicColor perception and design
Canadian institutionsMcMaster University
Fundersnot available
KeywordsStimulus (psychology)Orientation (vector space)PsychophysicsCommunicationArtificial intelligencePsychologyMathematicsComputer scienceGeometryNeuroscienceCognitive psychologyPerception

Abstract

fetched live from OpenAlex

Physiological and behavioural evidence suggests that responses to a target stimulus can be modulated by context. In the orientation domain, parallel elements in the surround can suppress responses to a center target, whereas orthogonal elements have less or no effect. We investigated the influence of contextual orientation information using a stimulus in which the amount of oriented signal was varied independent of contrast. Oriented elements within the pattern were drawn with a particular grey level for a limited spatial extent, and then randomly switched to a new grey level. Oriented centers (2 deg) were presented in the context of either a parallel or orthogonal surround. The subjects' task was to discriminate oriented centers from unoriented noise centers in a 2IFC task. With a uniform grey surround, only 12% orientation signal was required for accurate discrimination. With a strong parallel surround, twice as much oriented signal was required. This effect was reduced when the orientation strength of the surround signal was reduced or when a gap separated the center and surround. Thresholds were also elevated with an unoriented noise surround. When the surround signal was orthogonal, thresholds were not different from thresholds with a uniform grey surround. These results are consistent with previous physiological and behavioural results that suggest orientation information is pooled across a local spatial region in an orientation-specific manner.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.962
Threshold uncertainty score0.704

Codex and Gemma teacher scores by category

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 head0.020
GPT teacher head0.382
Teacher spread0.362 · 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 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

Citations0
Published2010
Admission routes1
Has abstractyes

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