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Grey Matter Volume Differences Associated with Extremely Low Levels of Cannabis Use in Adolescence

2019· article· en· W2911110882 on OpenAlexaff
Catherine Orr, Philip A. Spechler, Zhipeng Cao, Matthew D. Albaugh, Bader Chaarani, Scott Mackey, Deepak Cyril D’Souza, Nicholas Allgaier, Tobias Banaschewski, Arun L.W. Bokde, Uli Bromberg, Christian Büchel, Erin Burke Quinlan, Patricia Conrod, Sylvane Desrivières, Herta Flor, Vincent Frouin, Penny Gowland, Andreas Heinz, Bernd Ittermann, Jean‐Luc Martinot, Marie‐Laure Paillère Martinot, Frauke Nees, Dimitri Papadopoulos Orfanos, Tomáš Paus, Luise Poustka, Sabina Millenet, Juliane H. Fröhner, Rajiv Radhakrishnan, Michael N. Smolka, Henrik Walter, Robert Whelan, Günter Schumann, Alexandra Potter, Hugh Garavan

Bibliographic record

VenueJournal of Neuroscience · 2019
Typearticle
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsBaycrest HospitalUniversité de MontréalCentre Hospitalier Universitaire Sainte-JustineUniversity of TorontoHEC Montréal
FundersNational Institute of Biomedical Imaging and BioengineeringNational Center for Advancing Translational SciencesMedical Research CouncilH. Lundbeck A/SSvenska Forskningsrådet FormasNational Institute of Mental HealthGeorgia Clinical and Translational Science AllianceVetenskapsrådetSwinburne University of TechnologyAgence Nationale de la RechercheDeutsche ForschungsgemeinschaftEli Lilly and CompanyScience Foundation IrelandEuropean CommissionNIHR Biomedical Research Centre, Royal Marsden NHS Foundation Trust/Institute of Cancer ResearchSouth London and Maudsley NHS Foundation TrustUniversity of OxfordFondation de FranceBundesministerium für Bildung und ForschungNational Institute for Health and Care ResearchNational Institutes of HealthFondation de l'Avenir pour la Recherche Médicale AppliquéeInstitut National de la Santé et de la Recherche MédicaleEU Joint Programme – Neurodegenerative Disease ResearchKing's College London
KeywordsCannabisPsychologyVoxel-based morphometryEffects of cannabisGrey matterNeurocognitiveCannabinoidNeural correlates of consciousnessCognitionDevelopmental psychologyNeurosciencePsychiatryMedicineInternal medicineMagnetic resonance imagingWhite matter

Abstract

fetched live from OpenAlex

Rates of cannabis use among adolescents are high, and are increasing concurrent with changes in the legal status of marijuana and societal attitudes regarding its use. Recreational cannabis use is understudied, especially in the adolescent period when neural maturation may make users particularly vulnerable to the effects of Δ-9-tetrahydrocannabinol (THC) on brain structure. In the current study, we used voxel-based morphometry to compare gray matter volume (GMV) in forty-six 14-year-old human adolescents (males and females) with just one or two instances of cannabis use and carefully matched THC-naive controls. We identified extensive regions in the bilateral medial temporal lobes as well as the bilateral posterior cingulate, lingual gyri, and cerebellum that showed greater GMV in the cannabis users. Analysis of longitudinal data confirmed that GMV differences were unlikely to precede cannabis use. GMV in the temporal regions was associated with contemporaneous performance on the Perceptual Reasoning Index and with future generalized anxiety symptoms in the cannabis users. The distribution of GMV effects mapped onto biomarkers of the endogenous cannabinoid system providing insight into possible mechanisms for these effects. SIGNIFICANCE STATEMENT Almost 35% of American 10th graders have reported using cannabis and existing research suggests that initiation of cannabis use in adolescence is associated with long-term neurocognitive effects. We understand very little about the earliest effects of cannabis use, however, because most research is conducted in adults with a heavy pattern of lifetime use. This study presents evidence suggesting structural brain and cognitive effects of just one or two instances of cannabis use in adolescence. Converging evidence suggests a role for the endocannabinoid system in these effects. This research is particularly timely as the legal status of cannabis is changing in many jurisdictions and the perceived risk by youth associated with smoking cannabis has declined in recent years.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.146
Threshold uncertainty score0.343

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.040
GPT teacher head0.280
Teacher spread0.239 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations99
Published2019
Admission routes1
Has abstractyes

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