Object-based attention and prioritization revealed by the temporal order judgment method
Bibliographic record
Abstract
Recent studies suggest that object-based attentional guidance is a result of attentional prioritization. It is proposed that in the absence of an alternative strategy, items appearing on the same object are prioritized over items appearing on a different object (Shomstein & Yantis, 2002; Drummond & Shomstein, 2008). It should be noted, however, that studies providing evidence for attentional prioritization have relied on spatial cuing paradigms. As such it is not clear whether attentional prioritization emerges from spatial orienting or is independent of it. Here, we use a novel method – the temporal order judgment (TOJ) – to examine whether attentional prioritization emerges in the absence of spatial cuing. Participants were presented with two rectangles oriented either horizontally or vertically. Following a 1s preview time two target stimuli were presented on the same or different objects and participants were asked to report which of the two stimuli appeared first. It was observed, using a cueless TOJ paradigm, that items appearing on the same object show visual prior entry effects; same object stimuli are prioritized by the perceptual-attentional system over stimuli that appear on the different object. In the second experiment we examined whether this same-object prior entry effect is automatic or is a default setting that is abandoned in the presence of an alternative strategy. Here we modified the TOJ paradigm to include twice as many trials on which targets appeared on the different-object as those appearing on the same-object. With a 2:1 ratio of different- to same-object trials there was no longer a prior entry effect present for the same- vs. different-object targets. These results provide strong support for the attentional prioritization hypothesis, demonstrating that priorities are determined independent of spatial orienting. Additionally, these experiments introduce a novel paradigm for measuring object-based attentional guidance.
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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 | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".