The Attentional Blink Impairs Detection and Delays Encoding of Visual Information: Evidence from Human Electrophysiology
Bibliographic record
Abstract
This article explores the time course of the functional interplay between detection and encoding stages of information processing in the brain and the role they play in conscious visual perception. We employed a multitarget rapid serial visual presentation (RSVP) approach and examined the electrophysiological P3 component elicited by a target terminating an RSVP sequence. Target-locked P3 activity was detected both at frontal and parietal recording sites and an independent component analysis confirmed the presence of two distinct P3 components. The posterior P3b varied with intertarget lag, with diminished amplitude and postponed latency at short relative to long lags-an electroencephalographic signature of the attentional blink (AB). Under analogous conditions, the anterior P3a was also reduced in amplitude but did not vary in latency. Collectively, the results provide an electrophysiological record of the interaction between frontal and posterior components linked to detection (P3a) and encoding (P3b) of visual information. Our findings suggest that, although the AB delays target encoding into working memory, it does not slow down detection of a target but instead reduces the efficacy of this process. A functional characterization of P3a in attentive tasks is discussed with reference to current models of the AB phenomenon.
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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) | 0.001 | 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".