Mood-elevating effects of d-amphetamine and incentive salience: the effect of acute dopamine precursor depletion.
Bibliographic record
Abstract
OBJECTIVE: Midbrain dopamine transmission is thought to regulate responses to rewarding drugs and drug-paired stimuli; however, the exact contribution, particularly in humans, remains unclear. In the present study, we tested whether decreasing dopamine synthesis, as produced by acute phenylalanine/tyrosine depletion (APTD), would alter responses to the stimulant drug, d-amphetamine. METHODS: On 3 separate days, 14 healthy men received d-amphetamine (0.3 mg/kg, given orally) plus a nutritionally balanced amino acid mixture, the phenylalanine/tyrosine-deficient mixture or the phenylalanine/tyrosine-deficient mixture followed by the immediate dopamine precursor, L-DOPA (Sinemet, 2 x 100 mg/25 mg). Responses to these treatments were assessed with visual analog scales, the Profile of Mood States, and a computerized Go/No-Go task. RESULTS: d-Amphetamine elicited its prototypical subjective effects, but these were not altered by APTD. In comparison, APTD significantly increased commission errors on the Go/No-Go task and did so uniquely in conditions where subjects were rewarded for making correct responses; this effect of APTD was prevented by L-DOPA. CONCLUSIONS: Together these results support the hypothesis that, in healthy men, dopamine is not closely linked to euphorogenic effects of abused substances but does affect the salience of reward-related cues and the ability to respond to them preferentially.
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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) | 0.001 | 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".