EEG biomarkers acquired during a short, straight-line simulated drive to predict impairment from cannabis intoxication.

OBJECTIVE: As cannabis use becomes more widely accepted, there is growing interest in its effects on brain function, specifically how it may impact daily functional activities such as driving, operating machinery, and other safety-related tasks. There are currently no validated methods for quantifying impairment from acute cannabis intoxication. The objective of this study was to identify neurophysiological correlates associated with driving simulator performance in subjects who were acutely intoxicated with cannabis. These signatures could help create an EEG-based profile of impairment due to acute cannabis intoxication. METHODS: Each subject completed a three-visit study protocol. Subjects were consented and screened on the first visit. On the second and third visits, subjects were administered either 500 mg of cannabis with 6.7% delta-9-tetrahydrocannabinol (THC) or placebo using a Volcano© Digit Vaporizer in a counterbalanced fashion. EEG was acquired from subjects as they performed a series of neurocognitive tasks and an approximately 45-minute simulated drive that included a rural straight-away absent of any other cars or obstacles during the final 10 minutes.EEG data was acquired using a STAT X24 wireless sensor headset during a simulated driving scenario from 10 subjects during the THC and placebo visits. Metrics of driving performance were extracted from the driving simulator and synchronized with EEG data using a common clock. RESULTS: A within-subjects analysis showed that the standard deviation of lane position (SDLP) was significantly worse and heart rate was elevated during the dosed visit compared to the placebo visit. Consistent with our prior findings, EEG power in the Theta frequency band (4-7 Hz) in the dosed condition was significantly decreased from the placebo condition. Theta power was negatively correlated with the SDLP driving performance metric, while there were no significant correlations between any EEG measure and SDLP in the placebo condition. CONCLUSIONS: These results, in combination with prior work on the effect of cannabis intoxication during neurocognitive tasks, suggest that neurophysiological signatures associated with acute cannabis intoxication are robust and consistent across tasks, and that these signatures are significantly correlated with impaired performance in a driving simulator. Taken together, EEG data acquired during a short neurocognitive testbed and during a simulated drive may provide specific profiles of impairment associated with acute cannabis intoxication. Further research is needed to establish the impaired cognitive processes associated with these EEG biomarkers.

Impact of cannabis and low alcohol concentration on divided attention tasks during driving.

OBJECTIVE: To assess divided-attention performance when driving under the influence of cannabis with and without alcohol. Three divided-attention tasks were performed following administration of placebo, cannabis, and/or alcohol. METHODS: Healthy adult cannabis users participated in 6 sessions, receiving combinations of cannabis (placebo/low-THC/high-THC) and alcohol (placebo/active) in randomized order, separated by washout periods of ≥1 week. At 0.5 hours post-dosing, participants performed simulator drives in the University of Iowa National Advanced Driving Simulator (NADS-1), a full vehicle cab simulator with a 360° horizontal field of view and motion base that provides realistic feedback. Drives contained repeated instances of three tasks: a side-mirror task (reaction to a triangle appearing in the side-mirrors), an artist-search task (select a specified artist from a navigable menu on the vehicle's console), and a message-reading task (read aloud a message displayed on the console). Blood THC and breath alcohol concentration (BrAC) were interpolated using individual power curves from samples collected approximately 0.17, 0.42, 1.4, and 2.3 hours post-dose. Driving measures during tasks were compared to equal-duration control periods occurring just prior to the task. Performance shifts, task completion, and lane departures were modeled relative to blood THC and BrAC using mixed-effects regression models. RESULTS: Each 1 µg/L increase in blood THC concentration predicted increased odds of failing to complete the artist-search task (OR: 1.05, 95% CI: 1.01-1.11, p = 0.046), increased odds of selecting at least one incorrect response (OR: 1.05, 95% CI: 1.00-1.09, p = 0.041), declines in speed during the side-mirror task (0.005 m/s, 95% CI: 0.001-0.009, p = 0.023), and longer lane departure durations during the artist-search task (0.74% of task-period, 95% CI: 0.12-1.36 p = 0.020). BrAC (approximately 0.05%) was not associated with task performance, though each 0.01 g/210 L increase predicted longer departure durations during the side-mirror task (1.41% of task-period, 95% CI: 0.08-2.76, p = 0.040) and increased standard deviation of lane position in the message-reading task (0.61 cm, 95% CI: 0.14-1.08, p = 0.011). CONCLUSIONS: With increasing medical and legal cannabis use, understanding the impact of acute cannabis use on driving performance, including divided-attention, is essential. These data indicate that impaired divided-attention performance is a safety concern.