Dynamic inhibitory control prevents salience-driven capture of visual attention.
Bibliographic record
Abstract
The salience-driven selection theory is comprised of three main tenets: (a) the most salient stimulus within a monitored region of the visual field captures attention, (b) the only way to prevent salience-driven distraction is by narrowly focusing attention elsewhere, and (c) all other goal-driven processes are possible only after the most salient item has been attended. Evidence for and against this theory has been provided from two experimental paradigms. Here, event-related potentials (ERPs) recorded in a novel Go/No-Go paradigm disconfirmed all three of tenets of the theory. Participants were instructed to search cyan-item displays for a salient orientation singleton (Go trials) and to ignore randomly intermixed yellow-item displays that could also contain an orientation singleton (No-Go trials). ERP components associated with attentional orienting (posterior contralateral N2; N2pc), distractor suppression (distractor positivity; PD), and stimulus relevance (P2a) were isolated to test predictions stemming from the salience-driven selection theory. On No-Go trials, the salient oddball elicited a PD rather than an N2pc, indicating that it was suppressed, not attended. Moreover, a P2a emerged before the N2pc on Go trials, demonstrating that observers first evaluated the global color of each display and then decided to search for the oddball (Go trials) or to ignore it (No-Go trials). We conclude that goal-driven processes can lead to the prevention of salience-driven attention capture by salient visual objects within the attentional window. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.000 |
| Open science | 0.001 | 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".