Correspondence between the alcohol‐<scp>P3</scp> event‐related potential and alcohol reward phenotypes among young adults
Bibliographic record
Abstract
BACKGROUND: Behavioral economic theory suggests that the value of alcohol depends upon elements of the choice context, such that increasing constraints on alternatives (e.g., price) or increasing the benefits of alcohol (e.g., social context) may result in greater likelihood of heavy drinking. The P3 event-related potential elicited by alcohol-related cues, a proposed marker of incentive salience, may be an electrophysiological parallel for behavioral economic alcohol demand. However, these indices have not been connected in prior research, and studies typically do not disaggregate social influences in the context of alcohol cue reactivity. METHOD: The current study recruited heavy drinking young adults (N = 81) who completed measures of alcohol use and alcohol demand, in addition to a 2 (social/nonsocial) × 2 (alcohol/nonalcohol) visual oddball task to elicit the P3. RESULTS: In multilevel models controlling for demographic characteristics, P3 reactivity was greater to alcohol (p < 0.001) and social (p < 0.001) cues than to nonalcohol and nonsocial cues, but without a significant interaction. Higher alcohol consumption (p = 0.02) and lower elasticity of demand (p = 0.01) were associated with greater P3 response to alcohol than nonalcohol cues. CONCLUSIONS: The results highlight a brain-behavior connection that may be an important marker for alcohol reward across units of analysis and may be sensitive to changes in the economic choice contexts that influence the likelihood of alcohol use.
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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) | 0.003 | 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".