An expansive, cone-specific nonlinearity enabling the luminance motion system to process color-defined motion
Bibliographic record
Abstract
To conclude that there is a dedicated color motion system, the hypothesis that the luminance motion pathway is processing color motion due to some nonlinearity must be rejected. Many types of nonlinearities have been considered. Cavanagh and Anstis (1991) considered interunit variability in equiluminance, but they found that adding a color-defined modulation to a luminance-defined drifting modulation increased the contribution to motion. This color contribution to motion cannot be due to interunit variability in equiluminance alone because such a luminance artifact would increase the effective luminance contrast for some luminance-sensitive units and decrease it for the others, resulting in no additional contribution to motion on average. Cavanagh and Anstis considered this color contribution to motion as evidence of a dedicated color motion system, but here we show that such a color contribution to motion varies with the phase difference between the luminance and color modulations, which would not be expected if luminance- and color-defined motion were processed separately. Specifically, the contribution to motion was greater when the luminance and color modulations were aligned (i.e., 0 degrees or 180 degrees phase difference), than when they were not (90 degrees or 270 degrees phase difference). Such a luminance-color phase interaction was also observed when spatially interleaving luminance and color information, which suggests that the interaction occurs after some spatial integration (i.e., not at the photoreceptors). To our knowledge, this luminance-color phase interaction cannot be explained by any previously considered nonlinearity. However, it can be explained by an expansive nonlinearity occurring before the summation of the L- and M-cone pathways (i.e., before ganglion cells) and after some spatial integration (i.e., after the photoreceptors). We conclude that there is a nonlinearity that has not been considered before, enabling some color motion processing by the luminance motion system.
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 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 | 0.000 |
| 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".