Substance-Related Disorders Clinical Trial
Official title:
Neural Mechanisms of Cannabinoid-impaired Decision-Making in Emerging Adults
Verified date | March 2024 |
Source | University of Kentucky |
Contact | n/a |
Is FDA regulated | No |
Health authority | |
Study type | Interventional |
Emerging adults are a particularly vulnerable group for experiencing the immediate and potentially lifelong negative impacts of habitual cannabis use, and trends suggest that cannabis use disorder (CUD) will soon escalate in this population. The proposed research will combine clinical pharmacology, non-invasive brain stimulation, and neuroimaging techniques to establish the brain mechanisms of cannabinoid-impaired decision-making processes in emerging adults with CUD. Results from this project will inform CUD prevention/treatment efforts in this high-risk group and address a growing public health concern.
Status | Completed |
Enrollment | 66 |
Est. completion date | December 13, 2023 |
Est. primary completion date | December 13, 2023 |
Accepts healthy volunteers | No |
Gender | All |
Age group | 18 Years to 34 Years |
Eligibility | Inclusion Criteria: - Habitual cannabis use problems - Body Mass Index =30 Exclusion Criteria: - Past or current serious physical or mental health - Sesame seed oil allergy - Irregular health issues identified by the Study Physician - Standard magnetic resonance imaging and transcranial magnetic stimulation exclusion criteria (e.g., metal implants, history of epilepsy, etc.) - Lack of affective form of birth control (females) - Pregnancy (females) |
Country | Name | City | State |
---|---|---|---|
United States | Neurobehavioral Systems Lab of the University of Kentucky College of Medicine | Lexington | Kentucky |
Lead Sponsor | Collaborator |
---|---|
Michael J. Wesley, PhD | National Institute on Drug Abuse (NIDA) |
United States,
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | Alpha Learning Rate | In a Probabilistic Reinforcement Learning Choice (PRLC) task, two stimuli are presented and choosing either could result in a monetary reinforcer, but the reinforcement probabilities of the stimuli differ, and change throughout the task. Individuals attempt to optimize choices according to learned probabilities and track changing probabilities over time.
PRLC performance allows mathematical modeling of trial-by-trial data under "real-world" uncertainty and yields computational parameters, such as the learning rate. Choice data were analyzed using a Rescorla-Wanger learning model with an alpha learning rate, beta inverse temperature, and perseveration global parameters. Model-derived learning rates are indicative of an individual's ability to learn from previous choice outcomes to update future decision-making. For this task, learning rates range from 0-1 with lower values indicative of more optimal learning. |
Measure collected at 2 time points: Baseline (0HR) and Post TMS Administration (3HR) | |
Primary | Self-Report Subjective "High" | A Visual Analogue Scale (VAS) was used to measure the acute subjective effects of THC at varying doses (0mg, 10mg, 30mg). Responses are made for VAS items along a 100-unit scale anchored on the extremes by "Not At All" (0) and "Extremely" (100) with a higher score meaning more of the effect. Participants were instructed to select "Not At All" (0) for all baseline (0HR) measures. Post-TMS administration (real or sham), participant self-reported their subjective "high" on the VAS with higher values indicating a more intense sensation of "high". | Measured 2 times: Baseline (0HR) and 3 hours (3HR) after capsule administration on each drug condition (0mg, 10mg, 30mg) | |
Primary | Elasticity of Demand | Elasticity of Demand was measured by the Cannabis Purchase Task (CPT) where participants are asked how many "hits" of cannabis they would consume at 16 different price points in ascending order ($0-$140). Higher elasticity values indicate a greater sensitivity to changing price points resulting in a reduced demand for "hits" of THC at increasing price points. | Measured 2 times: Baseline (0HR) and Post-TMS (3HR) after THC administration on each drug condition (0mg, 10mg, 30mg). | |
Primary | Working Memory Performance | Working memory (WM), the ability to hold a finite amount of information for a set amount of time, is measured by the N-Back task. Here, participants were presented with a sequence of letters and must indicate when the letter currently being viewed matches the one from N steps earlier in the sequence. The load factor "N" is adjusted between 0, 1, and 2 to adjust the difficulty of the task (0-Back = no WM load, 1-Back = minimal WM load, 2-Back = greater WM load) where a higher score means better memory performance. Outcomes are reported as the Total Accuracy Percentage (Correct Choices/Total Choices) x 100% | Measured 2 times: Baseline (0HR) and Post-TMS (3HR) after THC administration on each drug condition (0mg, 10mg, 30mg). |
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