Divergent mesolimbic dopamine circuits support alcohol-seeking triggered by discrete cues and contexts
Bibliographic record
Abstract
ABSTRACT Discrete and contextual cues that predict alcohol trigger alcohol-seeking. However, the extent to which context influences alcohol-seeking triggered by discrete cues, and the neural mechanisms underlying these responses, are not well known. We show that, relative to a neutral context, a context associated with alcohol persistently elevated alcohol-seeking triggered by a discrete cue, and supported higher levels of priming-induced reinstatement. Alcohol-seeking triggered by a discrete cue in a neutral context was reduced by designer receptor-mediated inhibition of ventral tegmental area (VTA) dopamine neurons in TH::Cre rats. Inhibiting terminals of VTA dopamine neurons in the nucleus accumbens (NAc) core reduced alcohol-seeking triggered by a discrete cue, irrespective of context, whereas inhibiting VTA dopamine terminals in the NAc shell selectively reduced the elevation of alcohol-seeking triggered by a discrete cue in an alcohol context. This dissociation highlights unique roles for divergent mesolimbic dopamine circuits in alcohol-seeking driven by discrete and contextual environmental cues.
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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 | 0.001 |
| 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".