Cannabinoid Transmission in the Prelimbic Cortex Bidirectionally Controls Opiate Reward and Aversion Signaling through Dissociable Kappa Versus μ-Opiate Receptor Dependent Mechanisms
Bibliographic record
Abstract
Cannabinoid, dopamine (DA), and opiate receptor pathways play integrative roles in emotional learning, associative memory, and sensory perception. Modulation of cannabinoid CB1 receptor transmission within the medial prefrontal cortex (mPFC) regulates the emotional valence of both rewarding and aversive experiences. Furthermore, CB1 receptor substrates functionally interact with opiate-related motivational processing circuits, particularly in the context of reward-related learning and memory. Considerable evidence demonstrates functional interactions between CB1 and DA signaling pathways during the processing of motivationally salient information. However, the role of mPFC CB1 receptor transmission in the modulation of behavioral opiate-reward processing is not currently known. Using an unbiased conditioned place preference paradigm with rats, we examined the role of intra-mPFC CB1 transmission during opiate reward learning. We report that activation or inhibition of CB1 transmission within the prelimbic cortical (PLC) division of the mPFC bidirectionally regulates the motivational valence of opiates; whereas CB1 activation switched morphine reward signaling into an aversive stimulus, blockade of CB1 transmission potentiated the rewarding properties of normally sub-reward threshold conditioning doses of morphine. Both of these effects were dependent upon DA transmission as systemic blockade of DAergic transmission prevented CB1-dependent modulation of morphine reward and aversion behaviors. We further report that CB1-mediated intra-PLC opiate motivational signaling is mediated through a μ-opiate receptor-dependent reward pathway, or a κ-opiate receptor-dependent aversion pathway, directly within the ventral tegmental area. Our results provide evidence for a novel CB1-mediated motivational valence switching mechanism within the PLC, controlling dissociable subcortical reward and aversion pathways.
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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) | 0.001 | 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".