Fundamental properties of the N2pc as an index of spatial attention: Effects of masking.
Bibliographic record
Abstract
Masking is an important tool in many paradigms used to study the cognitive architecture. The N2pc is an electrophysiological event-related potential (ERP) that has been used as a tool to study the deployment of visual spatial attention. The aim of this paper was to study the effects of masking on the N2pc. Two stimuli were presented on the screen, one to left and one to right of fixation, and subjects reported the identity of one of them. The targets could be discriminated both by their category (letters vs. digit) and by their colour (pink vs. green). Backward masking was produced by presenting a second pair of bilateral stimuli after the offset of the first pair. The second pair of stimuli consisted of characters of the same colour and category as in the first pair. Forward masking was produced by using the very same stimuli as in the backward masking condition, but by instructing subjects to report the second stimulus. The forward mask trials had longer response times compared to no-mask trials, and backward mask trials had even longer response times, and also a higher error rate. Although the different masking procedures lead to clear behavioural effects, the N2pc was not affected, suggesting that the deployment of visual spatial attention, per se, was not affected by pattern masking. A sustained posterior contralateral negativity (SPCN) following the N2pc was also found (300 ms post-target, and beyond), and the amplitude of the SPCN was strongly modulated by the number of presented stimuli and the duration of the SPCN was positively correlated with RT in the behavioural task. We hypothesize that the SPCN reflects neural activity associated with the passage of information through visual short-term memory.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".