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Record W2020862067 · doi:10.1167/11.11.959

A perception-action dissociation revealed through the interaction with blurred stimuli

2011· article· en· W2020862067 on OpenAlexaff
F. Colino, John de Grosbois, Dazhi Cheng, Katharine Brewster, Gordon Binsted

Bibliographic record

VenueJournal of Vision · 2011
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPerceptionStimulus (psychology)ScalingLuminanceComputer visionGaussian blurArtificial intelligenceVisual perceptionComputer sciencePsychologyPattern recognition (psychology)CommunicationMathematicsImage processingCognitive psychologyImage restorationNeuroscienceImage (mathematics)Geometry

Abstract

fetched live from OpenAlex

In the perception-action model of vision (Milner & Goodale, 1995), information is passed from lower visual (e.g. V1) areas into two processing streams: a dorsal stream mediating visually guided movement, and a ventral stream mediating object identification and awareness. Information processed prior to the bifurcation should therefore be available to both streams. This experiment examined how the quality of a luminance edge (processed at V1) would influence perception and action. A grasping task, and a perceptual size-matching task were performed under full-vision (FV) and 2-s delayed vision (DV). Stimuli varied in size (3), and edge-blur (4). Edges were blurred using a 2D Gaussian-filter. Maximum-grip-aperture (MGA) was the size-estimate for grasping, while perceptual-estimates (PE) required participants to estimate the size of stimuli by adjusting the size of a comparison stimulus. It was predicted that, the visual streams would use the same edge information, and thus motor and perceptual judgements would behave in a similar manner under both FV and DV. PE and MGA increased with increases of stimulus size, and decreased with increasing degree of blur. An analysis of the rate of scaling to size across conditions revealed that PES scaled at a higher rate to changes in size than MGA. Scaling based upon level of blur exhibited a two-way interaction between task and visual condition. MGA blur-scaling was not altered by DV, whereas PES blur-scaling became significantly more shallow. This violated the expectation that under DV, an increase in similarity between motor and perceptual responses would be found. Since PES became less influenced by edge blur following a delay while MGA scaling remained unchanged, there is evidence that the perception/action systems hold different representations of certain stimulus properties. Thus, the two-visual streams appear to generate their own representations of edge location even though similar edge information is available to both.

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)0.005
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 score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.144
GPT teacher head0.400
Teacher spread0.256 · 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

Citations0
Published2011
Admission routes1
Has abstractyes

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