Augmenting glutamatergic, but not dopaminergic, activity in the nucleus accumbens shell disrupts responding to a discrete alcohol cue in an alcohol context
Bibliographic record
Abstract
Discrete alcohol cues and contexts are relapse triggers for people with alcohol use disorder exerting particularly powerful control over behaviour when they co-occur. Here, we investigated the neural substrates subserving the capacity for alcohol-associated contexts to elevate responding to an alcohol-predictive conditioned stimulus (CS). Specifically, rats were trained in a distinct 'alcohol context' to respond by entering a fluid port during a discrete auditory CS that predicted the delivery of alcohol and were familiarized with a 'neutral context' wherein alcohol was never available. When conditioned CS responding was tested by presenting the CS without alcohol, we found that augmenting glutamatergic activity in the nucleus accumbens (NAc) shell by microinfusing α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) reduced responding to an alcohol CS in an alcohol, but not neutral, context. Further, AMPA microinfusion robustly affected behaviour, attenuating the number, duration and latency of CS responses selectively in the alcohol context. Although dopaminergic inputs to the NAc shell were previously shown to be necessary for CS responding in an alcohol context, here, chemogenetic excitation of ventral tegmental area (VTA) dopamine neurons and their inputs to the NAc shell did not affect CS responding. Critically, chemogenetic excitation of VTA dopamine neurons affected feeding behaviour and elevated c-fos immunoreactivity in the VTA and NAc shell, validating the chemogenetic approach. These findings enrich our understanding of the substrates underlying Pavlovian responding for alcohol and reveal that the capacity for contexts to modulate responding to discrete alcohol cues is delicately underpinned by the NAc shell.
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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".