Smoking/Nicotine Affects the Magnitude and Onset of Lateralized Readiness Potentials
Bibliographic record
Abstract
AbstractSmoking/nicotine improves cognitive performance for a variety of tasks. In most cases, reaction time (RT) is generally shorter after smoking/nicotine. While there may be some slight facilitation of stimulus-evaluation processing, most of the RT effects of nicotine appear to take place following the response-selection stage. This study investigated possible effects (in smokers) of smoking/nicotine on response preparation and execution processes using the lateralized readiness potential (LRP). On each trial, a warning stimulus preceded an imperative stimulus by 1.2s. The warning stimulus completely specified the correct response to the imperative stimulus. The study was completed in two morning sessions in which 4 cigarettes were smoked in each session. The nicotine yield of the cigarettes varied between sessions (0.05mg or 1.1mg). Maximum amplitudes of both the stimulus and response-locked LRPs were larger in the 1.1 mg session. For both stimulus- and response-locked LRPs, smoking the 1.1 mg cigarette (but not the 0.05 mg cigarette) shortened onset latency. However, the magnitude of the effect was much larger for the stimulus-locked LRPs, suggesting that response preparation is facilitated by smoking/nicotine to a greater degree than response execution.
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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 | 0.001 |
| 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".