Flank facilitation for isoluminant chromatic stimuli
Bibliographic record
Abstract
It is well established that the detection of a luminance-defined Gabor is improved if measured in the presence of two high contrast aligned flanking Gabors (Polat and Sagi, Vis. Res., 1993) and this is termed flank facilitation. Here we investigate whether this facilitation occurs for isoluminant chromatic stimuli. We measured the effect of flank facilitation for achromatic and chromatic Gabors, (0.75 cpd, 1 octave bandwidth). Stimuli isolated either the S-cone opponent mechanism, the L/M cone opponent mechanism, or the achromatic mechanism. We used a 2AFC paradigm with a double staircase to measure, in a blocked design, the detection threshold of a central Gabor target presented alone and in the presence of two flanking Gabors. Three conditions were investigated: 1) target and flanks all of the same color and spatial phase, 2) target and flanks of the same color but different phase (180 degrees), 3) target and flanks of different colors. Results were collected for 3 different target-flank distances (2, 3, 6 ?) in three subjects. A facilitation effect occurred when the target and flanks were the same color and same phase and its magnitude decreased as the target-flank distance increased., There was no facilitation in the out of phase conditions for achromatic or chromatic stimuli. A weaker and inconsistent facilitation effect was found in crossed (i.e. achromatic/chromatic) conditions. A comparable degree of flank facilitation occurs in both achromatic and chromatic mechanisms that exhibits phase dependence. There is no consistent cross interaction between color and luminance mechanisms.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".