Effects of a dual task on the N100–P200 complex and the early and late Nd attention waveforms
Bibliographic record
Abstract
The roles of N100 and the early and late negative difference (Nd) waveforms in selective attention were investigated with primary simulated flying and secondary dichotic listening tasks. Twenty highly trained participants performed the two tasks together, either while detecting secondary task deviant tones in one ear and ignoring tones in the other ear (dual condition) or while ignoring the tones in both ears (ignore condition). The amplitude of the N100-P200 complex in both the dual-task and ignore conditions was reduced equally in the attended and unattended ear by the introduction of the primary task. In the dual-task condition, the amplitude of the late Nd but not the early Nd was reduced by a combination of the introduction of the primary task and an increase in its difficulty. P300 showed the same amplitude pattern as the late Nd. We propose that the reduction in N100-P200 amplitude reflects an automatic gating mechanism. The dissociation of the early and late Nd suggests that the latter is not modality specific. The question is raised whether the late Nd is more closely associated with P300 than with the early Nd.
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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) | 0.001 | 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 | 0.001 |
| 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".