On target selection as reflected by posterior <scp>ERP</scp> components in feature‐guided visual search
Bibliographic record
Abstract
The N2pc event-related potential is a widely studied ERP component that reflects the covert deployment of visuo-spatial attention to target stimuli displayed laterally relative to fixation. Recently, an analogous ERP component, named N2pcb, has been proposed as a marker of the deployment of visuo-spatial attention to targets displayed on the vertical midline. Two studies that investigated the N2pcb component found analogous results, using however two different algorithms to compute the amplitude of N2pcb. One study subtracted the ipsilateral activity elicited by a lateral target from the bilateral activity elicited by a target displayed on the vertical midline, whereas the other study subtracted the bilateral activity elicited by target-absent displays from the bilateral activity elicited by a target displayed on the vertical midline. Here we show both algorithms estimate properly the N2pc as well as the N2pcb components. In addition, we explored whether the singleton detection positivity (SDP) component, a posterior bilateral positivity temporally concomitant to N2pc recently reported in studies using singleton search, could be observed in the present study in which a target was defined by a combination of features. Given that such component was indeed found using feature search, we named this component posterior processing positivity (PPP), and showed that bilateral activity elicited by target-absent displays is an adequate baseline for its correct isolation.
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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 | 0.004 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".