Neuroelectric Correlates of Perceptual Awareness During the Auditory Attentional Blink
Bibliographic record
Abstract
BACKGROUND: Perceptual awareness refers to the conscious detection and identification of a sensory event. In electrophysiological studies, it is associated with a modality-specific negative-going event-related potential, which can be observed as early as 100-300 ms after the stimulus onset. METHOD: In this study, we measured neuroelectric brain activity during the auditory attentional blink, comparing brain responses when participants correctly reported both the first (T1) and second (T2) targets versus when only T1 was detected, but T2 was missed. To achieve robust statistical power, we pooled data across six previously published studies for the current analyses. RESULT: Our results revealed that accurately reporting both T1 and T2 elicited greater negativity between 150 and 300 ms over the frontocentral and central scalp areas following T2 onset, compared to trials where T1 was detected but T2 was not. Additionally, a positive displacement, peaking around 800 ms over the central-parietal scalp area, followed the early negativity. Successful detection of both T1 and T2 was also associated with more pronounced alpha suppression, peaking at approximately 500 ms before and 800 ms after T2 onset. CONCLUSIONS: These findings suggest that neural correlates of what we refer to "auditory awareness" occur both before the stimulus sequence and soon after T2 onset. Pre-stimulus difference in alpha power may serve as an indicator of lapses in attention, with greater alpha power reflecting periods when participants are less engaged or off-task.
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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 | 0.003 |
| 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".