Use of a Novel EEG-Based Objective Test, the Cognalyzer®, in Quantifying the Strength and Determining the Action Time of Cannabis Psychoactive Effects and Factors that May Influence Them Within an Observational Study Framework
Bibliographic record
Abstract
Current methods to detect recent delta-9-tetrahydrocannabinol (THC) use cannot objectively quantify its psychoactive effects (PE). The Cognalyzer®, an electroencephalography (EEG)-based method, detects and quantifies the strength of THC-induced PE on a scale from 0 to 100%. This study assesses the relationship between the magnitude of Cognalyzer® PE predictions and reported subjective drug effects for 4-h post-cannabis inhalation. Seventy-five participants were enrolled in the study. Prior to ad libitum cannabis inhalation, an EEG recording episode was completed. Immediately after inhalation, the Drug Effects Questionnaire (DEQ) was administered and another EEG recording performed. For 25 participants, the study ended. For 50 participants, assessments were repeated at 30-min intervals for 4 h. EEG files were blinded and analyzed using two versions of the Cognalyzer® algorithm. The relationship between the Cognalyzer® PE level results and the DEQ was assessed using generalized linear models and multiple regression. There were significant PE increases from pre-cannabis for up to 3.5 h. Mean reports of feeling drug effects were > 0 at all post-inhalation time points (p ≤ 0.024). Furthermore, there were significant relationships between the Cognalyzer® PE and self-reported perception of drug effects (p ≤ 0.001). Subgroup analysis showed that Cognalyzer® PE levels were impacted by cannabis use history, subjective ratings of drug effects, oral fluid THC concentration and the cannabis product inhaled. The findings show that the Cognalyzer® can be used to objectively determine the strength of cannabis psychoactive effects that cannabis products create on consumers and how it changes depending on their experience with cannabis. The Cognalyzer® can be used to conduct scientific consumer research to generate trustworthy informational material about the psychoactive experience of cannabis products. For clinical research, the Cognalyzer® can be used to study the pharmacodynamics of cannabinoids or delivery systems, such as nano-emulsifications.
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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 | 0.001 |
| 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".