Monocularly-directed attention transiently shifts eye dominance measured by binocular rivalry
Bibliographic record
Abstract
Attention directed to one eye can increase the strength of that eye's contribution to perception. It is known that when probe stimuli appear monocularly in bistable paradigms there is a shift in dominance toward the probed eye. This occurs more quickly when subjects simultaneously perform a task where they attend to the probe stimulus. Here, we investigate transient shifts in attention after presentation of an attended probe stimulus during binocular rivalry. We measure eye dominance using continuously reported rivalry percepts. Binocular rivalry stimuli were cross-oriented gratings presented to each eye. Subjects (n=17) used a joystick to report a continuous measure of dominance during rivalry. In the probe task, subjects judged the symmetry of twelve coloured circles surrounding the rivalry stimulus. We tested an "active" condition (subjects performed the probe task) and a "passive" condition (subjects did not perform the probe task). We tested conditions where probe stimuli were presented to the left eye, right eye, and binocularly (a control). Time courses of the continuously reported percepts were aligned to each attentional cue onset and averaged across subjects. From the average time courses, we find that upon monocular presentation of the probe, dominance transiently shifts toward the probed eye during rivalry. However, this shift does not occur when the probe is binocularly presented, nor when no probe is presented at all. This result suggests that attention can modulate eye dominance at the eye specific level.
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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 | 0.000 |
| 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) | 0.001 | 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".