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Record W3191739868 · doi:10.1016/j.visres.2021.07.013

First- and second-order transformational apparent motion rely on common shape representations

2021· article· en· W3191739868 on OpenAlexafffund
Kevin Hartstein, Sharif Saleki, Kirsten Ziman, Patrick Cavanagh, Peter U. Tse

Bibliographic record

VenueVision Research · 2021
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsYork University
FundersDepartment of Psychological and Brain Sciences, Dartmouth CollegeCanada First Research Excellence FundNational Science Foundation
KeywordsPerceptLuminanceStimulus (psychology)IllusionPsychologyOptical illusionCommunicationCognitive psychologyArtificial intelligencePsychophysicsComputer visionPerceptionMotion perceptionComputer scienceMathematicsMotion (physics)Neuroscience

Abstract

fetched live from OpenAlex

When one figure is replaced with another that overlaps its spatial location, observers perceive an illusory, continuous shape change of the original object, a phenomenon known as transformational apparent motion (TAM). The current study investigated the extent to which TAM depends on a common, high-level shape representation that is independent of the shape-defining attribute. Specifically, we tested whether TAM is perceived similarly for both first- and second-order objects, defined by luminance and texture contrast, respectively. A compelling motion percept was observed in second-order TAM displays that was comparable to that seen in first-order TAM displays. Importantly, TAM for both stimulus classes showed the same pattern over a range of stimulus onset asynchronies. These results support the high-level shape account, indicating that TAM is driven by segmentation mechanisms that rely on high-level shape information rather than low-level visual characteristics.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.240
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.200
GPT teacher head0.466
Teacher spread0.266 · 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.

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

Citations1
Published2021
Admission routes2
Has abstractyes

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