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Record W2018699129 · doi:10.1167/9.5.9

Low-level mechanisms may contribute to paradoxical motion percepts

2009· article· en· W2018699129 on OpenAlexaff
Craig Aaen‐Stockdale, Benjamin Thompson, Pi‐Chun Huang, R. F. Hess

Bibliographic record

VenueJournal of Vision · 2009
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsMcGill University
FundersGoddard Space Flight Center
KeywordsStimulus (psychology)PsychologyAudiologySecond-order stimulusCounterintuitiveMotion perceptionNeuroscienceVisual perceptionPerceptionCognitive psychologyPhysicsMedicine

Abstract

fetched live from OpenAlex

A recent series of experiments demonstrated a surprising deterioration of visual motion discrimination with increasing stimulus size for stimuli of high contrast. This counterintuitive finding was explained as a result of surround suppression in visual area V5. Equally paradoxical was the finding that older observers showed better performance than younger observers. This second result was explained as an age-related reduction in surround suppression due to changes in GABA-mediated inhibition. Using an opponent motion stimulus, we find an analogous effect and also find that this effect is much reduced in older observers, to the point where they perform better than younger observers. Our long duration stimulus should be beyond the range at which surround-suppressed neurons in V5 are preferentially activated. Having normalized our stimuli relative to contrast threshold, we show that our results can be entirely explained by the relative contrast of the stimulus and speculate that contrast sensitivity may play a role in previously reported results. Our older observers' data similarly can be explained by the relative contrast of the stimulus. The difference between older and younger observers appears to be a result of a weakening of spatial summation at high contrast in younger observers, perhaps caused by earlier saturation of motion mechanisms.

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)0.001
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 score0.365
Threshold uncertainty score0.449

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.060
GPT teacher head0.368
Teacher spread0.308 · 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

Citations17
Published2009
Admission routes1
Has abstractyes

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