Risk‐preferring rats make worse decisions and show increased incubation of craving after cocaine self‐administration
Bibliographic record
Abstract
Maladaptive decision-making may play an integral role in the development and maintenance of an addiction. Substance-dependent individuals make riskier choices on the Iowa Gambling Task, and these deficits persist during withdrawal and are predictive of relapse. However, it is unclear from clinical studies whether this cognitive impairment is a cause or consequence of drug use. We trained male Long-Evans rats on the rat Gambling Task, a rodent analogue of the Iowa Gambling Task, to determine how choice preference influenced, and was influenced by, cocaine self-administration, withdrawal and incubation of craving. Rats that exhibited a preference for the risky, disadvantageous options at baseline were uniquely and adversely affected by cocaine self-administration. Risky choice was exacerbated in these rats when decision-making was assessed during the same diurnal period as cocaine self-administration, whereas the choice pattern of optimal decision-makers was unaffected. This decision-making deficit was maintained during 30 days of withdrawal and correlated with greater cue-induced incubation of craving. Risk-preferring rats also made more drug-seeking responses during cocaine self-administration. These data demonstrate that poor decision-making prior to contact with addictive drugs is associated with a pro-addictive behavioural phenotype, characterized by further increased risky choice and heightened responding for drug both during cocaine self-administration and withdrawal. Such findings indicate that the elevated risky decision-making observed in substance-dependent populations is not merely circumstantial, but makes an important contribution to addiction vulnerability and severity that can now be effectively modelled in laboratory rats.
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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) | 0.001 | 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".