Acute naltrexone does not remediate fronto‐striatal disturbances in alcoholic and alcoholic polysubstance‐dependent populations during a monetary incentive delay task
Bibliographic record
Abstract
There is a concerted research effort to investigate brain mechanisms underlying addiction processes that may predicate the development of new compounds for treating addiction. One target is the brain's opioid system, because of its role in the reinforcing effects of substances of abuse. Substance-dependent populations have increased numbers of the mu opioid receptor (MOR) in fronto-striatal regions that predict drug relapse, and demonstrate disturbances in these regions during the processing of non-drug rewards. Naltrexone is currently licensed for alcohol and opiate dependence, and may remediate such disturbances through the blockade of MORs in fronto-striatal reward circuitry. Therefore, we examined the potential acute modulating effects of naltrexone on the anticipation of, and instrumental responding for, non-drug rewards in long-term abstinent alcoholics, alcoholic poly substance-dependent individuals and controls using a monetary incentive delay (MID) task during a randomized double blind placebo controlled functional MRI study. We report that the alcoholic poly substance-dependent group exhibited slower and less accurate instrumental responding compared to alcoholics and controls that was less evident after acute naltrexone treatment. However, naltrexone treatment was unable to remediate disturbances within fronto-striatal regions during reward anticipation and 'missed' rewards in either substance-dependent group. While we have not been able to identify the underlying neural mechanisms for improvement observed with naltrexone in the alcoholic poly-substance dependent group, we can confirm that both substance-dependent groups exhibit substantial neural deficits during an MID task, despite being in long-term abstinence.
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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) | 0.002 | 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".