Segregation of caffeine reward and aversion in the rat nucleus accumbens shell versus core
Bibliographic record
Abstract
Caffeine, the most commonly consumed psychoactive drug in the world, is readily available in dietary sources, including soft drinks, chocolate, tea and coffee. However, little is known about the neural substrates that underlie caffeine's rewarding and aversive properties and what ultimately leads us to seek or avoid caffeine consumption. Using male Wistar rats in a place conditioning procedure, we show that systemic caffeine at a low intraperitoneal dose of 2 mg/kg (or 100 µM injected directly into the rostral, but not caudal, portion of the ventral tegmental area) produced conditioned place preferences. By contrast, high doses of systemic caffeine at 10 and 30 mg/kg produced conditioned place aversions. These aversions were not recapitulated by a caffeine analog restricted to the periphery. Both caffeine reward and aversion were blocked by systemic D1-like receptor antagonism using SCH23390, while systemic D2-like receptor antagonism with eticlopride had smaller effects on caffeine motivation. Most important, we demonstrated that pharmacological blockade of dopamine receptors using α-flupenthixol injected into the nucleus accumbens shell, but not core, blocked caffeine-conditioned place preferences. Conversely, α-flupenthixol injected into the nucleus accumbens core, but not shell, blocked caffeine-conditioned place aversions. Thus, our findings reveal two dopamine-dependent and functionally dissociable mechanisms for processing caffeine motivation, which are segregated between nucleus accumbens subregions. These data provide novel evidence for the roles of the nucleus accumbens subregions in mediating approach and avoidance behaviours for caffeine.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".