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Record W2060476108 · doi:10.1167/13.9.1007

Action Influences Object Perception

2013· article· en· W2060476108 on OpenAlexaff
David Chan, Mary A. Peterson, Morgan D. Barense, Jay Pratt

Bibliographic record

VenueJournal of Vision · 2013
Typearticle
Languageen
FieldPsychology
TopicAction Observation and Synchronization
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPerceptionStimulus (psychology)PsychologyAction (physics)CommunicationVisual processingCognitive psychologyNeurosciencePhysics

Abstract

fetched live from OpenAlex

Proximal hand posture biases activity in the magnocellular (M) visual pathway (Gozli et al., 2012; Goodhew et al., in press). We tested whether this is due to having visual stimuli in the "action space" of the hands by making use of the finding that low spatial frequency images are rapidly identified through "gist" processing arising from the M-pathway (Kveraga, 2007). In Experiment 1, we paired low and high spatial frequencies images with either a proximal or distal hand posture and had participants indicate whether the objects were larger or smaller than a prototypical shoebox. Participants responded faster to low spatial frequency images paired with a proximal hand posture. No differences were found with distal hand posture. In Experiment 2, we manipulated proximal hand postures such that hands were either action oriented with palms in (palms toward the stimuli) or non-action oriented with palms out (palms away from the stimuli). In Experiment 3 we used one proximal hand posture (palms in) only but manipulated the type of visual stimuli such that they were either action oriented (easily grasped) or non-action oriented (not easily grasped). The results of Experiments 2 and 3 demonstrated that when action was primed (whether through hand posture or stimulus type) there was an advantage for low spatial frequency images. Overall, these experiments show that rapid "gist" object perception is due to M pathway activity, and that this processing is influenced by action-based hand positions. Meeting abstract presented at VSS 2013

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.898
Threshold uncertainty score1.000

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0100.001

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 head0.046
GPT teacher head0.384
Teacher spread0.338 · 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; both teacher heads agree on what is shown here.

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
Published2013
Admission routes1
Has abstractyes

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