Subcortical resting state functional connectivity as a neural marker of first onset internalizing disorder in high-risk youth
Bibliographic record
Abstract
Background: Research has linked individual differences in resting state functional connectivity (RSFC) of subcortical brain regions to internalizing disorders, but little research has examined if these changes are pre-morbid risk factors. This study examined individual differences in subcortical RSFC as risk factors for the first lifetime onset of an internalizing disorder in youth at familial risk. Methods: Participants (n = 93) were adolescents with a parental history of internalizing disorders, but with no such history themselves. Youth completed resting state fMRI scans, as well as the MINI-Kid and the Youth Self Report internalizing symptoms scale at baseline. The MINI-Kid was completed again at 9 or 18-month follow-up to assess onset of internalizing disorders. Seed-to-whole brain analyses consisted of a multiple regression models controlling for sex, age, in scanner motion, and baseline symptoms. Results: First onsets at follow-up were associated with increased baseline RSFC between the left caudate and the bilateral SMA (pFDR = .002), and between the right nucleus accumbens and the right superior parietal lobule (pFDR = .0003). Conclusion: Altered RSFC of subcortical regions may represent a pre-morbid risk factor for developing a first onset of an internalizing disorder. Results may have implications for understanding the neural bases of internalizing disorders and for early identification and prevention efforts.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.002 | 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".