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Record W4386242746 · doi:10.1167/jov.23.9.5818

Action-response mode modulates go/no-go decision accuracy

2023· article· en· W4386242746 on OpenAlexaff
Philipp Kreyenmeier, Miriam Spering, Jolande Fooken

Bibliographic record

VenueJournal of Vision · 2023
Typearticle
Languageen
FieldNeuroscience
TopicMotor Control and Adaptation
Canadian institutionsQueen's UniversityUniversity of British Columbia
Fundersnot available
KeywordsAction (physics)PerceptionSensory systemComputer scienceEye movementMovement (music)PsychologyAffect (linguistics)Motion (physics)Presentation (obstetrics)CommunicationArtificial intelligenceCognitive psychologyNeuroscienceMedicine

Abstract

fetched live from OpenAlex

Crossing a busy intersection requires a rapid decision whether to go or not. Decision accuracy generally improves over time, with longer accumulation of visual motion information. However, the time available to accumulate sensory information may be constrained by the complexity and movement time of the required action. This factor is rarely accounted for in perceptual decision-making studies, which typically rely on simple button presses as indicators of decision outcome. Here we ask whether action-response modes (manual button press vs. interceptive hand movement) directly affect the accuracy and timing of a go/no-go decision. We recorded eye and hand movements of n=10 human observers while they viewed a small disc moving toward a goal. The target disappeared 100, 200, or 300 ms after onset and observers had to indicate whether the target would miss (no-go decision required) or pass (go decision required) the goal by either inhibiting a response, or by executing a button press or interceptive hand movement, respectively. Decision accuracy increased with increasing target presentation duration, confirming that longer sensory accumulation improves decision accuracy. Across presentation durations, decision accuracy was significantly higher and less variable when observers indicated their decision by pressing a button, compared to when they manually intercepted the target. To compensate for different movement execution times, observers initiated their hand movements ~270 ms earlier and intercepted ~70 ms later when manually intercepting the target compared to pressing the button. These results indicate that observers had less time to form their decisions when performing goal-directed hand movements compared when they simply had to press a button. We propose that the more complex planning and execution of the interceptive hand movement competes with decision formation. Our results highlight critical differences in sensorimotor decision processes between simple button press and more complex hand movement tasks.

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)0.006
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 score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.054
GPT teacher head0.366
Teacher spread0.312 · 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
Published2023
Admission routes1
Has abstractyes

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