Dopamine release in ventral striatum during Iowa Gambling Task performance is associated with increased excitement levels in pathological gambling
Bibliographic record
Abstract
AIMS: Gambling excitement is believed to be associated with biological measures of pathological gambling. Here, we tested the hypothesis that dopamine release would be associated with increased excitement levels in Pathological Gamblers compared with Healthy Controls. DESIGN: Pathological Gamblers and Healthy Controls were experimentally compared in a non-gambling (baseline) and gambling condition. MEASUREMENTS: We used Positron Emission Tomography (PET) with the tracer raclopride to measure dopamine D 2/3 receptor availability in the ventral striatum during a non-gambling and gambling condition of the Iowa Gambling Task (IGT). After each condition participants rated their excitement level. SETTING: Laboratory experiment. PARTICIPANTS: 18 Pathological Gamblers and 16 Healthy Controls. FINDINGS: Pathological Gamblers with dopamine release in the ventral striatum had significantly higher excitement levels than Healthy Controls despite lower IGT performance. No differences in excitement levels and IGT performance were found between Pathological Gamblers and Healthy Controls without dopamine release. Pathological Gamblers showed a significant correlation between dopamine release and excitement level, while no such interaction was found in Healthy Controls. CONCLUSIONS: In pathological gamblers dopamine release in the ventral striatum appears to be associated with increased excitement levels despite lower IGT performance. The results might suggest a 'double deficit' function of dopamine in pathological gambling, where dopamine release reinforces maladaptive gambling through increasing excitement levels, reducing inhibition of risky decisions, or a combination of both. These findings may have implications for the understanding of dopamine in pathological gambling and other forms of 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".