Enhanced frontal activation underlies sparing from the attentional blink: Evidence from human electrophysiology
Bibliographic record
Abstract
Using the ERP method, we examined the processing operations elicited by stimuli that appear within the same temporal attention window. Forty subjects searched for letter targets among digit distractors displayed in rapid serial visual presentation (RSVP). ERPs were examined under conditions where a single target was embedded among distractors and compared to those recorded when two consecutive targets were embedded among distractors. Standard and independent component analyses revealed two temporally and topographically distinct ERP responses, a midfrontal P3a component peaking at about 300 ms followed by a midparietal P3b component peaking at about 450 ms. With minimal latency variations, the frontal P3a was amplified when elicited by two consecutive targets relative to a single target. The parietal P3b response was also amplified when elicited by two consecutive targets compared to a single target but, in contrast to P3a, it was also associated with a substantially longer time course. These results provide evidence for the involvement of frontal brain regions in the close-to-concurrent selection of two consecutive targets displayed in RSVP, and of posterior brain regions in the serial encoding of targets in visual working memory. The present findings are discussed in relation to current models of temporal gating of attention and the attentional blink effect.
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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 | 0.001 |
| 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) | 0.003 | 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".