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.
This mentored career development award (K01) will enable Dr. Michael J. Wesley to achieve his long-term goal of becoming an independent investigator with a clinical research program examining cannabis use disorder (CUD) in emerging adults, which is a current NIDA funding priority. Dr. Wesley is a new Assistant Professor at the University of Kentucky (UK) College of Medicine. The activities proposed in this award build on Dr. Wesley's background in neuroimaging and drug abuse research and will allow him to accomplish these specific short-term objectives: Become an expert in (1) clinical pharmacology and (2) non-invasive brain stimulation research, and enhance/develop his (3) knowledge of the responsible conduct of research, (4) skills for scientific communication and grant writing, and (5) ability to manage an independent research program. UK has numerous faculty and projects focused on drug abuse research and is an ideal environment for Dr. Wesley to successfully complete this award. Dr. Wesley has assembled a stellar mentoring team consisting of Dr. Josh Lile (Mentor), who runs a successful NIH-funded clinical pharmacology research program at UK and Drs. Mark George (Co-Mentor) and Colleen A. Hanlon of the Brain Stimulation Laboratory at the Medical University of South Carolina, Together they will guide and oversee Dr. Wesley's training in clinical pharmacology, brain stimulation, and scientific communication and grant writing. Dr. Wesley has proposed to engage in a series of formal classes, lab exchanges, and research seminars/meetings that will assist him in accomplishing the objectives of this award. The proposed research project is novel, innovative, and rigorous. It will combine the acute administration of Δ9-tetrahydrocannabinol (THC), the main psychoactive ingredient in cannabis, with brain stimulation and neuroimaging to examine the role of the dorsal lateral prefrontal cortex (DLPFC) and connected brain areas in drug-impaired decision-making processes. Specifically, transcranial magnetic stimulation (TMS) will be used to raise or lower DLPFC functionality following the administration THC in randomized, double-blind, placebo- and sham-controlled experiments. Aim 1 will test the hypotheses that excitatory TMS (raising DLPFC functionality) will attenuate the impairing effects of THC on study outcomes. Aim 2 will test the hypotheses that inhibitory TMS (lowering DLPFC functionality) will enhance the impairing effects of THC on study outcomes. Results from this project will improve the investigator's understanding of the mechanisms involved in cannabis-impaired decision-making, which will inform CUD management and address a growing public health concern.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
BASIC_SCIENCE
Masking
SINGLE
Enrollment
66
Individuals will receive placebo dose and sham TMS.
Individuals will receive 10mg dose and sham TMS.
Individuals will receive 30mg dose and sham TMS.
Individuals will receive placebo and real TMS.
Individuals will receive10mg THC and real TMS. Intervention type: Other (combination device/drug intervention)
Individuals will receive 30mg THC and real TMS. Intervention type: Other (combination device/drug intervention)
Neurobehavioral Systems Lab of the University of Kentucky College of Medicine
Lexington, Kentucky, United States
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.
Time frame: Measure collected at 2 time points: Baseline (0HR) and Post TMS Administration (3HR)
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".
Time frame: Measured 2 times: Baseline (0HR) and 3 hours (3HR) after capsule administration on each drug condition (0mg, 10mg, 30mg)
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.
Time frame: Measured 2 times: Baseline (0HR) and Post-TMS (3HR) after THC administration on each drug condition (0mg, 10mg, 30mg).
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%
Time frame: Measured 2 times: Baseline (0HR) and Post-TMS (3HR) after THC administration on each drug condition (0mg, 10mg, 30mg).
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