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Record W4417122739 · doi:10.1177/03010066251394168

Are onscreen cursor movements influenced by the Ebbinghaus illusion? Exploring perception–action interaction in a virtual environment

2025· article· en· W4417122739 on OpenAlexafffund
Ryan W. Langridge, Jonathan J. Marotta

Bibliographic record

VenuePerception · 2025
Typearticle
Languageen
FieldPsychology
TopicAction Observation and Synchronization
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCursor (databases)PerceptionIllusionStimulus (psychology)Visual perceptionAction (physics)Virtual machine

Abstract

fetched live from OpenAlex

The Two-Visual-Streams Hypothesis (TVSH) of vision proposes a functional separation between the perception of a visual stimulus and the control of visually guided action toward that stimulus. This study tested whether the separation of perception and action proposed by the TVSH is also demonstrated when executing visually guided cursor movements toward onscreen targets. Participants used a trackpad to click onscreen circular targets embedded within the Ebbinghaus ("Titchener Circles") illusion and were thus perceived as either larger or smaller than their true size. Participants were more accurate when clicking on the perceived larger target compared to the perceived smaller target, indicating their performance was influenced by their perception of target size (Experiment 1). There was no effect of the illusion when visual feedback of the target was removed at the beginning of the trial (Experiment 2) or removed following a 2-second target-viewing period (Experiment 3). Conclusion: The perceptual features of an onscreen stimulus mediate the guidance of cursor movements toward visible targets. Illusion-based perceptions of target size do not affect actions toward disappeared targets, however. These results contribute to the theoretical principles of the TVSH by testing its predictions in a novel onscreen environment.

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 score0.682
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)0.0050.001

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 head0.084
GPT teacher head0.347
Teacher spread0.263 · 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
Published2025
Admission routes2
Has abstractyes

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