The impact of cannabis consumption on visual processing
Bibliographic record
Abstract
Abstract Purpose: Cannabis is one of the most widely used recreational drug in Canada. The purpose of this study is to evaluate the effect of cannabis consumption on the visual pathway via non‐invasive, objective electrophysiological testing. Methods: Full field electroretinograms (ffERGs) including photopic negative responses (PhNRs), and visual evoked potentials (VEPs) were recorded in non‐users (control group) and in cannabis users. International Society for Clinical Electrophysiology of Vision (ISCEV) standard clinical protocols were used for all exams. Cannabis users were tested twice: at least 12 h after their last cannabis consumption (chronic group) and 2.5 h following their last consumption (acute group). Results: When comparing the chronic and acute groups via paired t‐tests ( n = 15), there was a statistically significant decrease in (1) the scotopic a‐wave amplitude (chronic −139.8 ± 7.4 μV and acute −114.8 ± 6.8 μV; p = 0.03; stimulus 10.0), (2) PhNR amplitude (chronic −32.2 ± 4.8 μV and acute −26.6 ± 3.1 μV; P = 0.01; stimulus 7 cd•s/m 2 ), and the amplitude of the following two VEP parameters (3) N75 (chronic −2.6 ± 0.9 μV and acute −2.0 ± 1.1 μV; p = 0.04; stimulus 30 min), and (4) N135 (chronic −15.0 ± 1.4 μV and acute −12.3 ± 1.2 μV; p = 0.03; stimulus 15 min). PhNR implicit time was statistically significantly increased when comparing the control (63.4 ± 1.5 ms; n = 18) and the acute (69.1 ± 1.9 ms; n = 15) group ( p = 0.03; stimulus 7 cd•s/m 2 ). There were no statistically significant changes in ffERGs and VEPs between the control and chronic groups. Conclusions: The results of this pilot study suggest that acute use of cannabis temporarily causes a reduction in photoreceptor activity with a downstream decrease in cortical activity. These changes appear to be reversible as there was no difference between the chronic exposure and the control groups.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".