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Record W2955511002

Visuomotor mental rotation is mediated by a serial process of response substitution

2010· article· en· W2955511002 on OpenAlexaffabout
Kristina A. Neely, Matthew Heath

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSpatial Cognition and Navigation
Canadian institutionsWestern University
Fundersnot available
KeywordsMental rotationTask (project management)PsychologyPerceptionRotation (mathematics)Point (geometry)Visual perceptionAudiologyCommunicationCognitive psychologyMathematicsComputer scienceComputer visionCognitionGeometry
DOInot available

Abstract

fetched live from OpenAlex

In the visuomotor mental rotation (VMR) task, participants point to a location that deviates from a visual cue by a predetermined angle. This task elicits slower reaction times (RT) than standard tasks wherein the visual cue is spatially compatible with the movement goal. RTs are reduced when the standard and VMR responses elicit a degree of dimensional overlap (i.e., 0° and 5°) or when the transformation involves a perceptually familiar angle (i.e., 90° or 180°; Neely & Heath, submitted). One caveat to this finding, however, is that past work examined standard and VMR responses in separate blocks of trials. Thus, RT differences between tasks not only reflect the computational demands of the transformations, but also the temporal cost of visuomotor inhibition. The present work used a randomized task design to isolate the magnitude of the RT difference between standard and VMR tasks across a range of equally spaced angles. Between-task difference scores were least for small (i.e., 30°) and perceptually familiar (i.e., 90 and 180°) angles relative to large and less familiar angles (i.e., 60, 120, 150, and 210°). This finding suggests RTs reflect the time required to prepare and inhibit an automatic motor response to the visual cue and then compute the requisite transformations for the response. Moreover, the rate at which the response is prepared is influenced by the angular disparity between standard and VMR responses and the perceptual familiarity of the transformation angle.Acknowledgments: This research was supported by NSERC as well a Graduate Thesis Award from The University of Western Ontario.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.778

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 head0.005
GPT teacher head0.242
Teacher spread0.237 · 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 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

Citations0
Published2010
Admission routes2
Has abstractyes

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