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Record W2792068388 · doi:10.21037/aes.2018.ab068

AB068. Texture density aftereffect can be bidirectional

2018· article· en· W2792068388 on OpenAlexaff
Hua-Chun Sun, Frederick A. A. Kingdom, Curtis L. Baker

Bibliographic record

VenueAnnals of Eye Science · 2018
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsMcGill University
Fundersnot available
KeywordsTexture (cosmology)Adaptation (eye)Density contrastContrast (vision)Artificial intelligenceComputer scienceOpticsPhysicsImage (mathematics)Astrophysics

Abstract

fetched live from OpenAlex

Background: It has been suggested that adaptation to texture density only ever reduces, i.e., never increases, perceived density, implying that density adaptation is ‘uni-directional’ and that texture density is coded as a scalar attribute (Durgin & Huk, 1997). However, we have recently shown that simultaneous density contrast, which describes the effect of a surround texture on the perceived density of a centre region, is ‘bi-directional’—that is, not only do denser surrounds reduce perceived density of the center but sparser surrounds enhance it (Sun, Baker, & Kingdom, 2016). Therefore, we decided to re-examine the directionality of density adaptation. Methods: We measured the density aftereffect in random dot patterns using a 2AFC matching procedure that established a point-of-subjective-equality (PSE) between an adapted test patch and an unadapted match patch. The adaptors and test were presented at the same position, either at top left or bottom right of the fixation. The match was presented at bottom left or top right correspondingly. These positions were fixed within a block and switched between blocks. Then, using sequential presentation, we measured the density aftereffect for a wide range of adaptor and test densities. Results: In the first experiment, we observed a unidirectional density aftereffect when test and match were presented simultaneously as in previous studies. However, when they were presented sequentially, bidirectionality was obtained. This bidirectional aftereffect remained when the presentation order of test and match was reversed (second experiment). In the third experiment, we used sequential presentation to measure the density aftereffect for a wide range of adaptor densities (0–73 dots/deg 2 ) and test densities (1.6, 6.4, and 25.6 dots/deg 2 ). We found bidirectionality for all combinations of adaptor and test densities, consistent with our previous SDC results. Conclusions: In three experiments, we found that density adaptation is bidirectional when the test and match stimuli are presented sequentially. The unidirectional density adaptation reported in previous studies might have been due to effects arising from simultaneous presentation of test and match stimuli. Our evidence again supports the idea that there are density-selective channels in the visual system in line with our previous finding in SDC.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.018
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0180.001

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 head0.141
GPT teacher head0.413
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".

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Citations0
Published2018
Admission routes1
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