Stimulus- and Response-locked Posterior Contralateral Negativity Bisect Cognitive Operations in Visual Search
Bibliographic record
Abstract
We explored the flow of information during visual search by examining activity indexing visual attention (N2pc) and the subsequent processing of the selected objects in visual short-term memory (SPCN) time-locked to stimulus presentation and to the motor response. We measured event-related activity at posterior sites (PO7/PO8) for 96 participants during a simple visual search task. A response-locked posterior contralateral negativity (RLpcN) was observed with a scalp distribution similar to that of the N2pc and SPCN. The RLpcN was compared with the stimulus-locked activity (N2pc and SPCN) across experimental manipulations (targets were either closer or farther from fixation in visual space, and the response was either more frequent [75%] or less frequent [25%]) and across response speeds (EEG data were separated into tertiles by RT both within-subjects and between-subjects). The leading edge and early portion of the RLpcN appeared to reflect the initial deployment of attention (N2pc), whereas the later portion (up to peak amplitude) reflected subsequent processing of visual information (SPCN). SPCN and RLpcN also had similar modulations in amplitude for both analyses. Moreover, whereas very small N2pc and SPCN onset latency differences were observed when data were separated into tertiles by RT, there were large onset differences for the RLpcN, with earlier RLpcN onsets for longer RTs, suggesting that RT variance is in large determined by processing after the initial deployment of attention. The results show how we can bisect processing responsible for variations in RT relative to the onset of visual spatial attention.
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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".