Cortical sources of the auditory attentional blink
Bibliographic record
Abstract
Attentional blink (AB) refers to the situation where correctly identifying a target impairs the processing of a subsequent probe in a sequence of stimuli. Although the AB often coincides with a modulation of scalp-recorded cognitive event-related potentials (ERPs), the neural sources of this effect remain unclear. In two separate experiments, we used classical LORETA analysis recursively applied (CLARA) to estimate the neural sources of ERPs elicited by an auditory probe when it immediately followed an auditory target (i.e., AB condition), when no auditory target was present (i.e., no-AB condition), and when the probe followed an auditory target but occurred outside of the AB time window (i.e., no-AB condition). We observed a processing deficit when the probe immediately followed the target, and this auditory AB was accompanied by reduced P3b amplitude. Contrasting brain electrical source activity from the AB and no-AB conditions revealed reduced source activity in the medial temporal region as well as in the temporoparietal junction (extending into inferior parietal lobe), ventromedial prefrontal cortex, left anterior thalamic nuclei, mammillary body, and left cerebellum. The results indicate that successful probe identification following a target relies on a widely distributed brain network and further support the suggestion that the auditory AB reflects the failure of the probe to reach short-term consolidation.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".