Brain Function Outcomes of Recent and Lifetime Cannabis Use
Notice bibliographique
Résumé
Importance: Cannabis use has increased globally, but its effects on brain function are not fully known, highlighting the need to better determine recent and long-term brain activation outcomes of cannabis use. Objective: To examine the association of lifetime history of heavy cannabis use and recent cannabis use with brain activation across a range of brain functions in a large sample of young adults in the US. Design, Setting, and Participants: This cross-sectional study used data (2017 release) from the Human Connectome Project (collected between August 2012 and 2015). Young adults (aged 22-36 years) with magnetic resonance imaging (MRI), urine toxicology, and cannabis use data were included in the analysis. Data were analyzed from January 31 to July 30, 2024. Exposures: History of heavy cannabis use was assessed using the Semi-Structured Assessment for the Genetics of Alcoholism, with variables for lifetime history and diagnosis of cannabis dependence. Individuals were grouped as heavy lifetime cannabis users if they had greater than 1000 uses, as moderate users if they had 10 to 999 uses, and as nonusers if they had fewer than 10 uses. Participants provided urine samples on the day of scanning to assess recent use. Diagnosis of cannabis dependence (per Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition criteria) was also included. Main Outcomes and Measures: Brain activation was assessed during each of the 7 tasks administered during the functional MRI session (working memory, reward, emotion, language, motor, relational assessment, and theory of mind). Mean activation from regions associated with the primary contrast for each task was used. The primary analysis was a linear mixed-effects regression model (one model per task) examining the association of lifetime cannabis and recent cannabis use on the mean brain activation value. Results: The sample comprised 1003 adults (mean [SD] age, 28.7 [3.7] years; 470 men [46.9%] and 533 women [53.1%]). A total of 63 participants were Asian (6.3%), 137 were Black (13.7%), and 762 were White (76.0%). For lifetime history criteria, 88 participants (8.8%) were classified as heavy cannabis users, 179 (17.8%) as moderate users, and 736 (73.4%) as nonusers. Heavy lifetime use (Cohen d = -0.28 [95% CI, -0.50 to -0.06]; false discovery rate corrected P = .02) was associated with lower activation on the working memory task. Regions associated with a history of heavy use included the anterior insula, medial prefrontal cortex, and dorsolateral prefrontal cortex. Recent cannabis use was associated with poorer performance and lower brain activation in the working memory and motor tasks, but the associations between recent use and brain activation did not survive false discovery rate correction. No other tasks were associated with lifetime history of heavy use, recent use, or dependence diagnosis. Conclusions and Relevance: In this study of young adults, lifetime history of heavy cannabis use was associated with lower brain activation during a working memory task. These findings identify negative outcomes associated with heavy lifetime cannabis use and working memory in healthy young adults that may be long lasting.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».