Effects of various cannabinoid ligands on choice behaviour in a rat model of gambling
Bibliographic record
Abstract
It is estimated that 0.6-1% of the population in the USA and Canada fulfil the Diagnostic and Statistical Manual of Mental Disorders, 5th ed. (DSM-5) criteria for gambling disorders (GD). To date, there are no approved pharmacological treatments for GD. The rat gambling task (rGT) is a recently developed rodent analogue of the Iowa gambling task in which rats are trained to associate four response holes with different magnitudes and probabilities of food pellet rewards and punishing time-out periods. Similar to healthy human volunteers, most rats adopt the optimal strategies (optimal group). However, a subset of animals show preference for the disadvantageous options (suboptimal group), mimicking the choice pattern of patients with GD. Here, we explored for the first time the effects of various cannabinoid ligands (WIN 55,212-2, AM 4113, AM 630 and URB 597) on the rGT. Administration of the cannabinoid agonist CB1/CB2 WIN 55,212-2 improved choice strategy and increased choice latency in the suboptimal group, but only increased perseverative behaviour, when punished, in the optimal group. Blockade of CB1 or CB2 receptors or inhibition of fatty-acid amide hydrolase did not affect rGT performance. These results suggest that stimulation of cannabinoid receptors could affect gambling choice behaviours differentially in some subgroups of subjects.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".