Simultaneous Regularity Contrast and Luminance Polarity
Bibliographic record
Abstract
Texture regularity, for example, the repeating pattern of a carpet, brickwork, or tree bark, is a ubiquitous feature of the visual world. The perception of regularity has generally been studied using multi-element textures whose regularity is manipulated by the addition of random jitter to the elements' nominal positions. Here, we investigate the selectivity of regularity perception for the luminance contrast polarities of the elements. Our psychophysical tool was simultaneous regularity contrast, or SRC, the phenomenon in which the perceived regularity of a central test texture is shifted away from that of the surrounding regularity. Stimuli were composed of arrays of dark and/or white Gaussian elements. Surround and center test textures consisted of either the same ("congruent") or opposite ("incongruent") polarities. In addition, we tested a "mixed" condition consisting of a random mixture of polarities in both the surround and test. The perceived regularity of the test was measured using a match stimulus with the same polarity dimension as the test. The regularity of the match stimulus was adjusted on each trial using a forced-choice staircase procedure and the point-of-subjective equality between the match and test regularities was estimated from the resulting psychometric functions. SRC was observed in both congruent and incongruent conditions, but with the mixed condition, the perceived regularity of the test was shifted toward rather than away from the surround regularity, an example of assimilation, not contrast. The analysis revealed no significant difference in the magnitude of SRC between the congruent and incongruent conditions, suggesting that SRC could be mediated solely by polarity agnostic mechanisms, although there are other possible explanations for the "null" result. However, trend analysis using a non-linear (sigmoidal-shaped) function indicated a significant difference between the congruent and incongruent conditions, which, together with the mixed polarity results, suggests the presence of at least some polarity selective mechanisms. Previous reports have suggested that regularity perception is encoded by the "peakedness" in the distribution of spatial-frequency-tuned linear filter responses. We modelled SRC quantitatively by incorporating peakedness with spatial-frequency-selective surround inhibition and found that the model gave a good account of the SRC data. Possible reasons for the assimilation effect-with the mixed polarity condition are discussed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".