The hedonic response to cigarette smoking is proportional to dopamine release in the human striatum as measured by positron emission tomography and [<sup>11</sup>C]raclopride
Bibliographic record
Abstract
Positron emission tomography and [11C]raclopride were used to assess the dopaminergic response to cigarette smoking in ten smokers. Nicotine-deprived smokers were scanned twice on separate days. In one condition, participants smoked their usual brand of cigarettes while in the scanner and in the other condition they remained nicotine abstinent. On each day, subjects monitored the hedonic properties of their experience as well as their levels of craving. Initial analyses revealed no significant differences between the conditions in [11C]raclopride binding potential (BP) in the caudate, putamen, or ventral striatum. Because previous research suggested that drug-induced dopamine transmission is related to levels of craving and/or hedonic drug effects, the relationship between these variables and [11C]raclopride BP was examined. Craving levels were reduced by smoking but were not systematically related to BP change. However, the hedonic response to smoking was correlated with BP reduction in the caudate (P < 0.001) and posterior putamen (P < 0.05) but not in the ventral striatum. Post hoc analyses revealed that only five of the ten smokers reported mood-elevating effects in response to the smoking procedure. In these subjects, smoking was associated with decreased [11C]raclopride BP in the caudate. On the other hand, among subjects that reported a diminished mood response to smoking there was an increase in BP in the caudate and putamen. These results suggest that pleasurable drug experiences are associated with increased dopamine transmission in the dorsal striatum while unpleasant experiences may be related to decreased dopamine release in this region.
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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 | 0.000 |
| 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".