Depression, marijuana use and early‐onset marijuana use conferred unique effects on neural connectivity and cognition
Bibliographic record
Abstract
OBJECTIVE: Marijuana (MJ) use is common. Research shows risks for psychiatric illnesses, including major depressive disorder (MDD) and cognitive deficits with MJ use, particularly early-onset use. We investigated cognitive function, functional connectivity, and genetic risk with MDD alone and combined with MJ use, and differences between early-vs. late-onset/non-MJ use in youth. METHOD: A total of 74 youth in four groups were studied: healthy control, MDD, frequent MJ use and current/past MDD plus frequent MJ use. Psychiatric symptoms, cognitive performance and demographics were measured. Default mode network (DMN) brain connectivity was determined. Risk alleles in six genes of interest were evaluated. RESULTS: DMN differences among groups in reward-processing and motor control regions were found; the effects of MJ use and MDD were distinct. Early-onset MJ use was associated with lower IQ and hyperconnectivity within areas of the DMN. Early-onset MJ use was associated with the BDNF risk allele. CONCLUSIONS: Cognitive deficits linked with early-onset MJ use were present within several years after MJ use began and may result from, predispose to, or share a common cause with early-onset MJ use. The DMN was affected by MDD, MJ and their combination, as well as by early-onset MJ use. BDNF carrier state may predispose to early-onset MJ use.
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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) | 0.001 | 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".