Trait sensitivity to negative feedback determines the intensity of compulsive alcohol seeking and taking in male rats
Bibliographic record
Abstract
BACKGROUND: Alcohol use disorder is one of the most common psychiatric disorders, and it is a leading cause of mortality worldwide. It has been demonstrated previously that people with alcohol use disorder are less sensitive to the negative outcomes of their actions and less able to use negative feedback to guide and adjust their ongoing behaviour. However, far less is known about the aberrant processing of negative feedback before the onset of alcohol use disorder. In this study, we investigated the theoretical claim that sensitivity to negative feedback - as a stable and enduring behavioural trait - can predict vulnerability to the development of compulsive alcohol consumption in rats. METHODS: We trained and tested rats in a series of probabilistic reversal learning tests, and based on this "negative feedback sensitivity screening," we classified each rat as more or less sensitive to negative feedback. Then, in the intermittent-access 2-bottle choice paradigm, we measured alcohol consumption in the animals classified above. In the next step, using the instrumental second-order chained schedule of alcohol reinforcement task, we examined the influence of sensitivity to negative feedback on the development of compulsive alcohol seeking behaviour. Finally, we measured how trait sensitivity to negative feedback affected the extinction and reinstatement of alcohol seeking after a period of abstinence. RESULTS: Trait sensitivity to negative feedback predicted the vulnerability of rats to the development of compulsive alcohol seeking and consumption. We also found significant differences between the more sensitive and less sensitive groups in their propensity to extinguish alcohol seeking behaviours when the alcohol was no longer available. LIMITATIONS: The findings from our study did not answer the question of whether individual differences in sensitivity to negative feedback have a genetic basis or develop in response to postnatal experiences. CONCLUSION: The results of our study suggest that negative feedback sensitivity screening could be used to evaluate individual vulnerability to the development and maintenance of alcohol use disorder.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".