Binocular rivalry from luminance and contrast
Bibliographic record
Abstract
Binocular rivalry is the phenomenon that when two incompatible images are simultaneously presented, one to each eye, the two images compete with each other to be the dominant percept. Studying the underlying neural mechanisms of binocular rivalry is useful for understanding the mechanisms of interocular inhibition. Levelt's Propositions, a set of four propositions that were originally published over fifty years ago, are not only useful for characterizing the perceptual dynamics of binocular rivalry, but can also provide a metric for assessing the common or differential neural mechanisms of binocular rivalry when diverse stimulus types are used. In the present study, we conducted a series of psychophysics experiments, where we compared the rivalry dynamics of two quite different types of stimuli. Orthogonal gratings, a classic type of rivalry stimulus, were contrasted with luminance patches, a type of rivalry stimulus that is relatively less studied. Our results showed that, similar to the orthogonal gratings, the alternate percepts in luminance-only rivalry were described by the modified Levelt's Propositions, despite the clearly slower alternation rates for luminance patches. However, unlike the mixed percepts observed during transitions between oriented gratings, fusion percepts during luminance rivalry were common, could be lustrous, and obeyed the same Propositions, suggesting a regime of tri-stability. Overall, both types of rivalry are consistent with recent models that posit separate binocular and monocular channels embedded within neural circuits that also accomplish contrast normalization. Finally, luminance rivalry is discussed in the contexts of binocular summation and suppression, as well as Fechner's paradox.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".