Enhancement of luminance sensitivity by chromatic pedestals - a model of nonlinear parvocellular luminance processing
Bibliographic record
Abstract
Perceptual interactions between red-green (RG) color and luminance contrast offer insight into how these attributes are jointly encoded by parvocellular neurons of the LGN and their cortical targets. Here we show that the enhancement of luminance sensitivity by RG chromatic pedestals can be accounted for by a model in which luminance is computed cortically from the rectified outputs of parvocellular-like units. We used uniform luminance patch stimuli (4 deg diameter, 300 ms duration) presented foveally, superimposed on RG, luminance and a range of combined color-luminance pedestals of varying intensities. In a 2-interval task, subjects (n=3) identified which stimulus had the luminance increment. We also tested RG pedestals peripherally (8 deg horizontally) using an equivalent spatial 2AFC task. Every pedestal tested reduced luminance thresholds at some intensity. The form of facilitation varied with pedestal chromaticity, with chromatic pedestals having an effect at lower pedestal contrasts. Our model predicts this chromatic tuning from the cone-opponency of parvocellular-like units. The outputs of L- and M-cone center units are rectified then summed in a luminance mechanism with an expansive output nonlinearity. Rectification prevents cancellation of L-M opponent signals, allowing RG pedestals to interact with luminance signals at the later nonlinear stage. Notably, the effects pedestals had on luminance sensitivity were not predictable from their visibility. Foveally, chromatic pedestals were visible at contrasts much lower than those that influenced luminance, unlike luminance pedestals, which had an effect near their detection threshold. In the periphery, RG pedestal detection thresholds increased by a factor of 4 or more, but the site of facilitation changed less, such that RG pedestals had an effect near their detection threshold. This dissociation suggests that the mechanisms mediating pedestal facilitation, though chromatically tuned, are distinct from those limiting chromatic detection.
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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 | 0.000 |
| 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) | 0.001 | 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".