Two routes to suppression of signals in color vision
Bibliographic record
Abstract
There are at least two routes to psychophysical cross-orientation suppression prior to binocular summation of the signal in achromatic vision: (1) a monoptic, non-adaptable sub-cortical pathway and (2) a dichoptic, adaptable interocular pathway (Baker et al., Neuroscience, 146, 2007). Here we test psychophysically whether cross orientation masking (XOM) in color vision (Medina & Mullen, JOV 9(3), 2009) has gain-control pathways that are separable from achromatic responses or whether chromatic and achromatic responses interact. Methods: Detection threshold vs contrast (TvC) masking functions were measured for red-green isoluminant, horizontal Gabor targets overlaid with achromatic vertical Gabor masks. We tested for XOM under a range of spatiotemporal conditions (0.375, 0.75 & 1.5 cpd; 2 & 8 Hz), and with the chromatic test and achromatic mask presented under monoptic, dichoptic, and binocular viewing conditions. Results: We find that: (1) there is little or no cross orientation masking of color by achromatic contrast under monoptic or binocular conditions at any of the spatio-temporal frequencies tested, although some facilitation may occur; (2) there is significant dichoptic XOM, when mask and test are present to different eyes, which increases with mask contrast; (3) the dichoptic XOM is greater at low temporal frequencies (2 Hz) than high (8Hz). Conclusion: The significant inter-ocular cross orientation suppression of color by luminance contrast indicates that gain control pools at this level are unselective for chromaticity. Our results support a two-stage contrast normalization model with both a monocular and a dichoptic stage prior to binocular summation: the within eye, monocular stage of suppression is selective for color contrast whereas the inter-ocular second stage, revealed under dichoptic conditions, has color-achromatic interactions. This differential effect provides evidence for at least two distinct sites for suppressive gain control in color vision. Meeting abstract presented at VSS 2012
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".