MétaCan
Menu
Back to cohort
Record W2103235065 · doi:10.1080/17588928.2012.658363

The visual P2 is attenuated for attended objects near the hands

2012· article· en· W2103235065 on OpenAlexaff
Cheng Sam Qian, Naseem Al-Aidroos, Greg L. West, Richard A. Abrams, Jay Pratt

Bibliographic record

VenueCognitive Neuroscience · 2012
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPsychologyTask (project management)PerceptionCheckerboardVisual perceptionObject (grammar)Cognitive psychologyCommunicationVisual processingPeripheralPhotic StimulationAudiologyNeuroscienceArtificial intelligenceMedicine

Abstract

fetched live from OpenAlex

Vision is altered when people place their hands near the object they are observing. To investigate the neural processes underlying this effect, we measured electroencephalographic visual-evoked potentials (VEPs) elicited by reversing checkerboards, while participants' hands either surrounded the visual display or rested at their sides. We found the P2 component was attenuated for hand-proximal stimuli, but only when participants attended to the location of the checkerboard. In Experiment 1, participants performed an attention-demanding color-change task that was presented centrally, and the P2 component was attenuated for central, but not peripheral, checkerboards. In Experiment 2, participants performed the attention task in the periphery, and the P2 was attenuated for peripheral, but not central, checkerboards. These results suggest that hand-proximal stimuli benefit from enhanced selective attention at later stages of perceptual processing. The effect only occurs for objects at task-relevant locations, however, even when task-irrelevant locations are physically closer to the hands.

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)0.003
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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.106
GPT teacher head0.379
Teacher spread0.272 · 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

Citations26
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueCognitive NeuroscienceSame topicVisual perception and processing mechanismsFrench-language works237,207