Vaporized Cannabis Extracts Have Reinforcing Properties and Support Conditioned Drug-Seeking Behavior in Rats
Bibliographic record
Abstract
Recent trends in cannabis legalization have increased the necessity to better understand the effects of cannabis use. Animal models involving traditional cannabinoid self-administration approaches have been notoriously difficult to establish and differences in the drug used and its route of administration have limited the translational value of preclinical studies. To address this challenge in the field, we have developed a novel method of cannabis self-administration using response-contingent delivery of vaporized Δ 9 -tetrahydrocannabinol-rich (CAN THC ) or cannabidiol-rich (CAN CBD ) whole-plant cannabis extracts. Male Sprague-Dawley rats were trained to nose-poke for discrete puffs of CAN THC , CAN CBD , or vehicle (VEH) in daily 1 h sessions. Cannabis vapor reinforcement resulted in strong discrimination between active and inactive operanda. CAN THC maintained higher response rates under fixed ratio schedules and higher break points under progressive ratio schedules compared with CAN CBD or VEH, and the number of vapor deliveries positively correlated with plasma THC concentrations. Moreover, metabolic phenotyping studies revealed alterations in locomotor activity, energy expenditure, and daily food intake that are consistent with effects in human cannabis users. Furthermore, both cannabis regimens produced ecologically relevant brain concentrations of THC and CBD and CAN THC administration decreased hippocampal CB1 receptor binding. Removal of CAN THC reinforcement (but not CAN CBD ) resulted in a robust extinction burst and an increase in cue-induced cannabis-seeking behavior relative to VEH. These data indicate that volitional exposure to THC-rich cannabis vapor has bona fide reinforcing properties and collectively support the utility of the vapor self-administration model for the preclinical assessment of volitional cannabis intake and cannabis-seeking behaviors. SIGNIFICANCE STATEMENT The evolving legal landscape concerning recreational cannabis use has increased urgency to better understand its effects on the brain and behavior. Animal models are advantageous in this respect; however, current approaches typically used forced injections of synthetic cannabinoids or isolated cannabis constituents that may not capture the complex effects of volitional cannabis consumption. We have developed a novel model of cannabis self-administration using response-contingent delivery of vaporized cannabis extracts containing high concentrations of Δ 9 tetrahydrocannabinol (THC) or cannabidiol. Our data indicate that THC-rich cannabis vapor has reinforcing properties that support stable rates of responding and conditioned drug-seeking behavior. This approach will be valuable for interrogating effects of cannabis and delineating neural mechanisms that give rise to aberrant cannabis-seeking behavior.
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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 | 0.001 |
| 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) | 0.000 | 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".