Surround induction with orientation modulated textures
Bibliographic record
Abstract
It is well known that the apparent contrast of a luminance-modulated (LM) test grating is reduced in the presence of a surrounding LM grating, a phenomenon sometimes termed “contrast-contrast”. Rather less is known about surround induction with texture gratings. In particular one might expect that with texture gratings that are defined by modulations in local orientation, termed orientation-modulated (OM) gratings, the perceived amplitude of a test might be enhanced by surround gratings lower in amplitude, on the grounds that OM amplitude might be encoded through OM amplitude-selective channels. We tested this idea using vertically oriented 0.5 cpd square-wave OM gratings constructed from dense arrays of 6.0 cpd Gabor micropatterns. The surrounds were 12 deg and the central tests 4 deg in diameter, resulting in respectively 6 and 2 cycles of modulation. We tested both in-phase and opposite-phase spatial test-surround relationships with various combinations of surround and test amplitudes. A two-interval-forced-choice procedure was employed to determine the point-of-subjective equality between the test amplitude and an adjustable matching pattern with a zero-amplitude surround. When the surrounds were higher in amplitude than the test, we found that perceived test amplitude was suppressed, as with luminance contrast grating. However, we found very little evidence of enhancement of tests higher in amplitude that their surrounds. We conclude that OM amplitude is likely encoded as a scalar dimension like luminance contrast and as with luminance contrast is subject to inhibition from surrounding OM gratings.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".