Taking rapid and intermittent cocaine infusions enhances both incentive motivation for the drug and cocaine-induced gene regulation in corticostriatal regions
Bibliographic record
Abstract
ABSTRACT A goal in addiction research is to distinguish forms of neuroplasticity that are involved in the transition to addiction from those involved in mere drug taking. Animal models of drug self-administration are essential in this context. Here, we compared in male rats two cocaine self-administration procedures that differ in the extent to which they evoke addiction-like behaviours. We measured both incentive motivation for cocaine using progressive ratio procedures, and cocaine-induced c- fos mRNA expression, a marker of neuronal activity. Rats self-administered intravenous cocaine (0.25 mg/kg/infusion) for seven daily 6-hour sessions. One group had intermittent access (IntA; 6 minutes ON, 26 minutes OFF x 12) to rapid infusions (delivered over 5 seconds). This models the temporal kinetics of human cocaine use and produces robust addiction-like behaviour. The other group had Long access (LgA) to slower infusions (90 seconds). This produces high levels of intake without promoting robust addiction-like behaviour. LgA-90s rats took twice as much cocaine as IntA-5s rats did, but IntA-5s rats showed greater incentive motivation for the drug. Following a final self-administration session, we quantified c- fos mRNA expression in corticostriatal regions. Compared to LgA-90s rats, IntA-5s rats had more cocaine-induced c- fos mRNA in the orbitofrontal and prelimbic cortices and the caudate-putamen. Thus, a cocaine self-administration procedure (intermittent intake of rapid infusions) that promotes increased incentive motivation for the drug also enhances cocaine-induced gene regulation in corticostriatal regions. This suggests that increased drug-induced recruitment of these regions could contribute to the neural and behavioural plasticity underlying the transition to addiction.
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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) | 0.001 | 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".