Curvature formation in the visual cortex: How do we sample?
Bibliographic record
Abstract
Background. The circle-polygon illusion produces a polygon percept when a static dark outline circle was pulsed at 2 Hz with a luminance gradient around the inner border. We modify the method of Sakurai (2014) and display arclengths that are 1/8, ¼ , 3/8, ½ , 5/8 , ¾ , 7/8 and 1 (whole) of a circle. We test if different arc lengths, that are fractions of the circumference of the same circle, change the edge length reported. If the edge length does not change with arc length, this implies neurophysiological design that codes for curvature at specific eccentricities in the same manner. Method. Arc lengths (1/8, ¼ , 3/8, ½ , 5/8 , ¾ , 7/8 and 1 (whole) ) of a circle of 4 and 8 deg and eccentricity (0,1,2,4 and 8 deg) were varied in a cross design. Observers (30 online participants; experiment was hosted on Pavlovia) indicated the edge length formed as part of the percept by selecting a edge length from an array of edge lengths shown between 0.105 deg and 2.107 deg. The perceived edge lengths were displayed as a series of twenty line segments built from the equation log(a*b c) such that a=1 and b=0.9. c belonged to the range [1,20] and each value of c gave rise to a unique line segment. Observers reported strength on a scale 1-10. Result. Edge length remained approximately uniform for all arc lengths for a fixed circle size. Strength was strongest for the shortest arc length, gradually decreasing as the arc length increased. Lowest strength was reported for whole circles. This may indicate that the early visual cortex has an affinity for closure and prefers to see shapes as composited closed curves or circles, reporting smaller edge lengths and lower strength for polygonal percepts in the process.
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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 | 0.004 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
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".