Direction discrimination thresholds in binocular, monocular, and dichoptic viewing: Motion opponency and contrast gain control
Bibliographic record
Abstract
Purpose: The present study investigated the binocular organization of motion opponency and its relation to contrast gain control. Method: We measured luminance contrast thresholds for discriminating direction of motion for drifting Gabor patterns (target) presented on counter-phase flickering Gabor patterns (pedestal; equivalent to the superposition of two Gabors drifting in opposite directions). There were four presentation conditions. (i) Binocular: all stimuli were presented to both eyes, (ii) Monocular: all stimuli were presented to the same one eye, (iii) Dichoptic: the target was presented to one eye while the pedestal was presented to the other eye, (iv) Half-binocular: the target was presented to one eye while pedestals were presented to both eyes. In addition, we tested an increment-and-decrement condition, in which the target increased contrast for one direction of movement, but decreased it by the same amount for the opposite moving component of the pedestal. The decrement was either in the same eye as the increment, or in the other eye. Results and Discussion: Threshold-versus-pedestal-contrast (TvC) functions showed a dipper shape: thresholds decreased and then increased with pedestal contrast. At low pedestal contrasts, there was binocular summation: binocular thresholds were lower than monocular. But at high pedestal contrasts there was little difference between them. The ‘dip’ was smaller for dichoptic presentation than for other presentations. Thresholds were similar for monocular and half-binocular presentations at low pedestal contrasts, but half-binocular thresholds became higher and closer to dichoptic thresholds as pedestal contrast increased. The added decremental target lowered thresholds by about a factor of 2, compared with half-binocular, when the decrement was in the same eye as the increment, or the opposite eye. Several models fit to the data strongly suggest that motion opponency and contrast gain control operate at a binocular level of processing.
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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 | 0.000 |
| 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".