A global attentional scope setting prioritizes faces for conscious detection
Bibliographic record
Abstract
The scope of visual attention is known to affect conscious object perception, with recent studies showing that a global attentional scope boosts holistic face processing, relative to a local scope. Here we show that attentional scope settings can also modulate the availability of information for conscious visual awareness. In an initial experiment, we show that adopting a global attentional scope accelerates conscious detection of initially invisible faces, presented under continuous flash suppression (CFS). Furthermore, face detection time was not modulated by attentional scope in a nonrivalrous control condition, which emulated the experience of CFS without inducing binocular rivalry. In a follow-up experiment, we report an exact replication of the original effect, as well as data suggesting that this effect is specific to upright faces, and is abolished when using both inverted faces and images of houses in an otherwise identical task. Thus, attentional scope settings can modulate the availability of information to conscious awareness, fundamentally altering the contents of our subjective visual experience.
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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 | 0.000 | 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) | 0.000 | 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".