Effect of Attention on the Initiation of Binocular Rivalry
Bibliographic record
Abstract
Recent studies suggest that attention is necessary for perceptual alternations in binocular rivalry. It has been shown that attention plays a role in not only accelerating but also even enabling perceptual fluctuation in ongoing phase of binocular rivalry. In this study, we tested whether attention also plays a role in suppressing a rival stimulus in its initial phases by measuring proportions of mixed dominance. We hypothesized that when attention is directed toward the location of rival stimuli prior to their presentation, the proportion of mixed dominance is lower than when attention is directed away from that location because of attentional facilitation. However, we found that the proportion of mixed dominance did not differ depending on the locus of attention, although we adopted well-established experimental paradigms for manipulating spatial attention. This result suggests that attention is not a determining factor in establishing initial perceptual dominance in binocular rivalry.
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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 | 0.001 | 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) | 0.000 | 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 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".