Chronic exposure to a gambling-like schedule of reward predictive stimuli can promote sensitization to amphetamine in rats
Bibliographic record
Abstract
Addiction is considered to be a brain disease caused by chronic exposure to drugs. Sensitization of brain dopamine (DA) systems partly mediates this effect. Pathological gambling (PG) is considered to be a behavioral addiction. Therefore, PG may be caused by chronic exposure to gambling. Identifying a gambling-induced sensitization of DA systems would support this possibility. Gambling rewards evoke DA release. One episode of slot machine play shifts the DA response from reward delivery to onset of cues (spinning reels) for reward, in line with temporal difference learning principles. Thus, conditioned stimuli (CS) play a key role in DA responses to gambling. In primates, DA response to a CS is strongest when reward probability is 50%. Under this schedule the CS elicits an expectancy of reward but provides no information about whether it will occur on a given trial. During gambling, a 50% schedule should elicit maximal DA release. This closely matches reward frequency (46%) on a commercial slot machine. DA release can contribute to sensitization, especially for amphetamine. Chronic exposure to a CS that predicts reward 50% of the time could mimic this effect. We tested this hypothesis in three studies with rats. Animals received 15 × 45-min exposures to a CS that predicted reward with a probability of 0, 25, 50, 75, or 100%. The CS was a light; the reward was a 10% sucrose solution. After training, rats received a sensitizing regimen of five separate doses (1 mg/kg) of d-amphetamine. Lastly they received a 0.5 or 1 mg/kg amphetamine challenge prior to a 90-min locomotor activity test. In all three studies the 50% group displayed greater activity than the other groups in response to both challenge doses. Effect sizes were modest but consistent, as reflected by a significant group × rank association (ϕ = 0.986, p = 0.025). Chronic exposure to a gambling-like schedule of reward predictive stimuli can promote sensitization to amphetamine much like exposure to amphetamine itself.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| 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".