Win-paired cues modulate the effect of dopamine neuron sensitization on decision making and cocaine self-administration: divergent effects across sex
Bibliographic record
Abstract
Abstract Psychostimulant use and engagement with probabilistic schedules of reward both sensitize the mesocorticolimbic dopamine system. Such behaviours may act synergistically to explain the high comorbidity between stimulant use and gambling disorder. The salient audiovisual stimuli of modern electronic gambling may exacerbate the situation. To probe these interactions, we sensitized ventral tegmental area (VTA) dopamine neurons via chronic chemogenetic stimulation while rats learned the rat gambling task in the presence or absence of casino-like cues. The same rats then learned to self-administer cocaine. In a separate cohort, we confirmed that our chemogenetic methods sensitized the locomotor response to cocaine, and potentiated phasic excitability of VTA dopamine neurons through in vivo electrophysiological recordings. In the absence of cues, sensitization promoted risk-taking in both sexes. When rewards were cued, sensitization expedited the development of a risk-preferring phenotype in males, while attenuating cue-induced risk-taking in females. While these results provide further confirmation that VTA dopamine neurons critically modulate risky decision making, they also reveal stark sex differences in the decisional impact which dopaminergic signals exert when winning outcomes are cued. As previously observed, risky decision-making on the cued rGT increased as both males and females learned to self-administer cocaine. The combination of dopamine sensitization and win-paired cues while gambling lead to significantly greater cocaine-taking, but these rats did not show any increase in risky choice as a result. Cocaine and heavily-cued gambles may therefore partially substitute for each other once the dopamine system is rendered labile through sensitization, compounding addiction risk across modalities.
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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) | 0.003 | 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".