Mu opioid receptors in the habenula : dissecting reward and aversion in addiction
Bibliographic record
Abstract
Mu opioid receptors (MORs) have been extensively studied for their addictive properties that are thought to operate through the control of reward processes. While the importance of MORs in reward is generally attributed to their presence in the mesocorticolimbic circuitry, their role in the medial habenula (MHb), the structure in which MORs are most densely expressed, remains unexplored to date. This is quite surprising given the increasing literature on the habenula’s role in addiction as well as reward/aversion processes. Here we generated a conditional knockout mouse model that lacks MORs solely in the MH band we investigated the contribution of habenular MORs in brain functions and behavioural out comes with emphasis on reward, aversion and cognition. While the performance of our mutant model did not differ in locomotor, analgesic and reward responses to morphine norincognitive tasks compared to control mice, we uncovered a novel role for MORs in aversive states.This is the first report demonstrating that MORs control both somatic and affective aversion specifically at the level of the MHb. Habenular MORs could thus be crucial to the aversive with drawal stage of addiction cycles that is thought to increase craving and prevent success in quitting.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".