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Record W2059084582 · doi:10.1167/9.6.11

Short- and long-term plasticity of eye position information: Examining perceptual, attentional, and motor influences on perisaccadic perception

2009· article· en· W2059084582 on OpenAlexafffund
A. C. Kis, Vaughan W.A. Singh, Matthias Niemeier

Bibliographic record

VenueJournal of Vision · 2009
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsThe Scarborough HospitalYork UniversityUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPerceptSaccadic maskingSaccadeEye movementPerceptionPsychologySmooth pursuitCognitive psychologyNeuroscience

Abstract

fetched live from OpenAlex

Spatial vision requires information about eye position to account for eye movements. But integrating eye position information and information about objects in the world is imperfect and can lead to transient misperceptions around the time of saccadic eye movements most likely because the signals are prone to temporal errors making it difficult to tell when the retinas move relative to when retinal images move. To clarify where this uncertainty comes from, in four experiments we examined influences of eye posture, attentional cueing, and trial history on perisaccadic misperceptions. We found evidence for one longer-term modulation of perisaccadic shift that evolved over the time of the test session due to biased eye posture. Another, short-term influence on perisaccadic shift was related to eye posture during preceding trials or the direction of the preceding saccade. Both perceptual effects could not be explained with visual delays, influences of attention or changes in saccade metrics. Our data are consistent with the idea that perisaccadic shift is caused by neural representations of eye position or space that are plastic and that arise from non-motor, extraretinal mechanisms. This suggests a perceptual system that continuously calibrates itself in response to changes in oculomotor and muscle systems to reconstruct a stable percept of the world.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.989
Threshold uncertainty score0.376

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)0.0000.000

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 head0.050
GPT teacher head0.349
Teacher spread0.299 · 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 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

Citations13
Published2009
Admission routes2
Has abstractyes

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