Potentially traumatic events and substance use do not predict changes in resting state functional connectivity in early adolescence
Bibliographic record
Abstract
Potentially traumatic events (PTEs) and substance use (SU) are commonly endorsed in early adolescence, a crucial period for neurodevelopment. PTEs and SU are precipitating events in the etiological development of comorbid posttraumatic stress disorder (PTSD) and substance use disorder (SUD). Separately, they have been shown to alter within- and between-network connectivity in the three brain networks posited by Menon’s Theory of Psychopathology: the default mode network (DMN), fronto-parietal network (FPN), and salience network (SN). While comorbid PTSD+SUD in adulthood shows shared neural underpinnings, this is less clear in adolescence. We analyzed the effects of PTEs and SU on resting state functional connectivity (rsFC) in 9-15 year olds from the Adolescent Brain Cognitive Development (ABCD) Study. Fixed effects panel models were fit to assess the effects of PTEs and SU on between-network (FPN-SN rsFC, DMN-SN rsFC, and FPN-DMN rsFC) and within-network (FPN rsFC, SN rsFC, and DMN rsFC) connectivity measured across three timepoints spanning two years. PTEs, SU, and their interaction was not significantly associated with between- and within-network rsFC two years later. No sex specific interactions were observed. Results suggest rsFC changes observed in older adolescents and adults with comorbid PTSD+SUD do not developmentally translate to early adolescents endorsing PTEs+SU. Lack of impact on rsFC may indicate a potential buffer period in which PTEs and SU do not affect rsFC until later in development or after symptom onset following PTEs+SU.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".