Natural and Drug Rewards Act on Common Neural Plasticity Mechanisms with ΔFosB as a Key Mediator
Bibliographic record
Abstract
Drugs of abuse induce neuroplasticity in the natural reward pathway, specifically the nucleus accumbens (NAc), thereby causing development and expression of addictive behavior. Recent evidence suggests that natural rewards may cause similar changes in the NAc, suggesting that drugs may activate mechanisms of plasticity shared with natural rewards, and allowing for unique interplay between natural and drug rewards. In this study, we demonstrate that sexual experience in male rats when followed by short or prolonged periods of loss of sex reward causes enhanced amphetamine reward, indicated by sensitized conditioned place preference for low-dose (0.5 mg/kg) amphetamine. Moreover, the onset, but not the longer-term expression, of enhanced amphetamine reward was correlated with a transient increase in dendritic spines in the NAc. Next, a critical role for the transcription factor ΔFosB in sex experience-induced enhanced amphetamine reward and associated increases in dendritic spines on NAc neurons was established using viral vector gene transfer of the dominant-negative binding partner ΔJunD. Moreover, it was demonstrated that sexual experience-induced enhanced drug reward, ΔFosB, and spinogenesis are dependent on mating-induced dopamine D1 receptor activation in the NAc. Pharmacological blockade of D1 receptor, but not D2 receptor, in the NAc during sexual behavior attenuated ΔFosB induction and prevented increased spinogenesis and sensitized amphetamine reward. Together, these findings demonstrate that drugs of abuse and natural reward behaviors act on common molecular and cellular mechanisms of plasticity that control vulnerability to drug addiction, and that this increased vulnerability is mediated by ΔFosB and its downstream transcriptional targets.
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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 | 0.000 |
| 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".