The Chronic Effects of Cannabinoid Use on the Prefrontal Cortex in Adolescence Compared to Adulthood: A Literature Review
Bibliographic record
Abstract
Adolescent cannabis use has become a significant public health concern due to increasing legalization and usage rates. This review examines recent clinical and preclinical research on the effects of chronic cannabis use during adolescence compared to adulthood, with a focus on prefrontal cortex development. Adolescence is a period of development that includes not just sexual development and puberty but also essential brain maturation. This brain development is characterized by gray matter pruning, increases in white matter, and altered development within the endocannabinoid system. Evidence suggests exogenous cannabinoids, such as Delta 9-Tetrahydrocannabinol (Δ⁹THC) and cannabidiol (CBD), can disrupt the normal neurodevelopmental processes in adolescents, particularly in the prefrontal cortex. Previous research, including neuroimaging studies, has found that cannabis use during adolescence is associated with altered cortical thinning patterns, especially accelerated thinning in prefrontal regions involved in executive functions. Earlier onset of use also correlated with pronounced structural alterations. Behaviourally, early use of cannabis is linked to deficits in attention, memory, and executive functions, with conflicting results on whether these factors are reversible after cessation of cannabis use. Rodent models assessed also corroborated the results found in clinical studies, demonstrating THC exposure can induce long-lasting impacts in prefrontal-mediated behaviours and neuroplasticity, which is not seen in adult cannabis users. The endocannabinoid system plays a key role in this neurodevelopment, and the disruption caused by exogenous cannabinoids during adolescence may alter typical development. Proposed mechanisms include possible premature synaptic pruning, disrupted white matter development, and lasting neurochemical imbalances. A previous meta-analysis demonstrated that some structural and functional changes may recover with abstinence; however, early, heavy use appears to risk persistent neurocognitive deficits. Further research is needed to clarify dose-dependent effects and interactions with other substances. Overall, accumulating evidence suggests adolescent cannabis exposure may induce lasting changes in brain structure, function, and behaviour not observed with adult use.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".