Amygdala-hippocampus connectivity and childhood depressive symptoms: subnuclei insights and self-concept roles
Bibliographic record
Abstract
Amygdala-hippocampal connectivity is a promising area of study for an understanding of the neurobiological mechanisms of depression. In this study, we examined the association between amygdala-hippocampal connectivity and depressive symptoms in children with a specific focus on the subnuclei level. We then examined whether self-concept mediated brain-behavior associations. Resting-state functional magnetic resonance imaging (fMRI) was performed at age 7.5 years (N = 319), followed by self-reported depressive symptoms and self-concept between ages 8.5 and 10.5 years, using the Children's Depression Inventory (CDI-2) and Piers-Harris Children's Self-Concept Scale (PHCSC) respectively. We conducted multiple regression analyses to examine the associations between the amygdala-hippocampus resting-state functional connectivity (RSFC) and CDI scores, first at the whole-region level and subsequently at the subnuclear level. Mediation analyses were then performed to explore the mediating role of self-concept in these brain-behavior associations. We observed a significant association between left amygdala-anterior hippocampus connectivity and CDI total scores, primarily driven by the left superficial amygdala. Further exploration at sub-symptomatic levels highlighted an association with negative cognition. Finally, self-concept mediated the association between left amygdala-anterior hippocampus connectivity and depressive symptoms in children. This study provided valuable insights into the associations among amygdala-hippocampal subnuclei connectivity, childhood depressive symptoms, and self-concept. Diminished left superficial amygdala-anterior hippocampus connectivity may serve as an early biomarker to identify depressive symptoms, particularly in children with negative cognition problems.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".