Familial risk of major mood disorders and brain functional connectivity in the default mode, cognitive executive, and salience networks
Bibliographic record
Abstract
BACKGROUND: Mood disorders, including depressive and bipolar disorders, begin in late adolescence to early adulthood, tend to run in families, and present early with subthreshold symptoms. They have been associated with differential connectivity in 3 core networks: the default mode network (DMN), cognitive executive network (CEN), and salience network (SN), but it remains unclear whether differences in connectivity in the DMN, CEN, and SN are associated with familial risk for mood disorders. METHODS: We recruited youth aged 9-19 years, including offspring of parents with major depressive or bipolar disorders (familial high risk [FHR]) and offspring of parents with no mood disorder (controls) for a resting-state functional magnetic resonance imaging study. We tested associations between family history of major mood disorders and connectivity within and between the DMN, CEN, and SN. RESULTS: We included 215 youth: 126 at FHR with a mean age of 13.38 (standard deviation [SD] 2.91) years and 79 controls with a mean age of 13.17 (SD 2.67) years. Mean connectivity in the DMN (β = 0.003, 95% confidence interval [CI] -0.023 to 0.029), CEN (β = -0.009, 95% CI, -0.070 to 0.089), and SN (β = -0.010, 95% CI -0.071 to 0.051) in the FHR group was similar to that of controls. Moreover, DMN, CEN, and SN connectivity was not significantly associated with depressive symptoms. LIMITATIONS: Given that brain connectivity changes over the developmental period, longitudinal studies would improve understanding of how this change occurs in familial risk groups to identify critical time periods for intervention or prevention of mood disorders. CONCLUSION: Connectivity within and between the DMN, CEN, and SN is not a neural indicator of familial risk for major mood disorders.
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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 | 0.001 | 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) | 0.001 | 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".