Prefrontal Cortical Reactivity and Connectivity Markers Distinguish Youth Depression from Healthy Youth
Bibliographic record
Abstract
Up to 50% of youth with depression do not respond to conventional first-line treatments. However, little research has been conducted on the pathophysiology of youth depression, hindering the identification of more effective treatments. Our goal was to identify neurophysiological markers that differentiate youth with depression from healthy youth and could serve as targets of novel treatments. We hypothesized that youth with depression would exhibit network-specific cortical reactivity and connectivity abnormalities compared with healthy youth. Transcranial magnetic stimulation combined with electroencephalography and magnetic resonance imaging was employed in combination with clinical and behavioral assessments to study cortical reactivity and connectivity in bilateral dorsolateral prefrontal cortex (DLPFC), motor cortex, and inferior parietal lobule, sites linked to the frontoparietal network, sensorimotor network, and default mode network, respectively. In youth depression, greater cortical reactivity was observed specific to the left and right DLPFC stimulation only, which correlated with anhedonia scores. Additionally, the connectivity of the right DLPFC was significantly higher in youth depression. Source reconstruction attributed the observed connectivity dysregulation to regions belonging to the default mode network. The neurophysiological signatures identified in this study have high potential to inform the development of more effective and targeted interventions for the youth depression population.
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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 | 0.016 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".