Abnormal dynamic functional connectivity of amygdalar subregions in untreated patients with first-episode major depressive disorder
Bibliographic record
Abstract
BACKGROUND: Accumulating evidence supports the concept of the amygdala as a complex of structurally and functionally heterogeneous nuclei rather than as a single homogeneous structure. However, changes in resting-state functional connectivity in amygdalar subregions have not been investigated in major depressive disorder (MDD). Here, we explored whether amygdalar subregions - including the laterobasal, centromedial (CM) and superficial (SF) areas - exhibited distinct disruption patterns for different dynamic functional connectivity (dFC) properties, and whether these different properties were correlated with clinical information in patients with MDD. METHODS: Thirty untreated patients with first-episode MDD and 62 matched controls were included. We assessed between-group differences in the mean strength of dFC in each amygdalar subregion in the whole brain using general linear model analysis. RESULTS: < 0.05, family-wise error-corrected). We found significant positive correlations between age at onset and the mean positive strength of dFC in the left CM/brainstem in patients with MDD. LIMITATIONS: The definitions of amygdalar subregions were based on a cytoarchitectonic delineation, and the temporal resolution of the fMRI was slow (repetition time = 2 s). CONCLUSION: These findings confirm the distinct dynamic functional pathway of amygdalar subregions in MDD and suggest that the limbic-cortical-striato-pallido-thalamic circuitry plays a crucial role in the early stages of MDD.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".