Examining the relationship between prenatal depression, amygdala-prefrontal structural connectivity and behaviour in preschool children
Bibliographic record
Abstract
Abstract Prenatal depression is a common, underrecognized, and undertreated condition with negative consequences on child behaviour and brain development. Neurological dysfunction of the amygdala, cingulate cortex and hippocampus are associated with the development of depression and stress disorders in youth and adults. Although prenatal depression is associated with both child behaviour and neurological dysfunction, the relationship between these variables remains unclear. In this study, fifty-four mothers completed the Edinburgh Depression Scale (EDS) during the second and third trimester of pregnancy and 3 months postpartum. Their children’s behaviour was assessed using the Child Behaviour Checklist (CBCL), and the children had diffusion magnetic resonance imaging (MRI) at age 4.1 +/− 0.8 years. Associations between prenatal depressive symptoms, child behaviour, and child brain structure were investigated. Third trimester EDS scores were associated with altered white matter in the amygdala-frontal tract and the cingulum, controlling for postpartum depression. Externalizing behaviour was sexually differentiated in the amygdala-frontal pathway. Altered structural connectivity between the amygdala and frontal cortex mediated the relationship between third trimester maternal depressive symptoms and child externalizing behaviour in males, but not females. These findings suggest that altered brain structure is a possible mechanism via which prenatal depressive symptoms can impact child behaviour, highlighting the importance of both recognition and intervention in prenatal depression.
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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".