P<sub>D</sub> components and distractor inhibition in visual search: New evidence for the signal suppression hypothesis
Bibliographic record
Abstract
Abstract The hypothesis that salient distractors in visual search are actively suppressed is supported by the fact that these objects elicit PD components believed to be associated with inhibition. This account was challenged by researchers who found that a PD to lateral color singleton distractors was followed by a contralateral negativity, which they interpreted as an N2pc indicative of attentional capture. As this would be at odds with successful distractor suppression, they proposed an alternative lateral‐first serial scanning hypothesis, which assumes that the PD might actually be an N2pc elicited when a lateral context item is selected. We tested this hypothesis by measuring lateralized ERP components to search displays with two lateral and two vertical midline items, including a color singleton and a shape‐defined target. Color singletons triggered PD components not only in blocks where attention was unfocused because target location was unpredictable, but critically also in blocks where targets only appeared on the midline and participants had no reason to attend to lateral items. This is inconsistent with the serial scanning hypothesis and supports the idea that the PD reflects signal suppression. PD components to singleton distractors were followed by a contralateral negativity, which we interpreted as a second PD elicited by nonsalient distractors on the opposite side. Our sequential inhibition account reconciles conflicting results of recent studies and emphasizes the role of inhibitory processes during attentional target selection in visual search.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".