Transcranial Magnetic Stimulation Markers of Antidepressant Treatment in Adolescents With Major Depressive Disorder
Bibliographic record
Abstract
BACKGROUND: The goal of this study was to examine baseline transcranial magnetic stimulation measures of cortical inhibition and excitability in depressed patients and characterize their longitudinal posttreatment changes. METHODS: Fifteen adolescents (age 13-17 years) with moderate to severe major depressive disorder and 22 healthy controls (age 9-17) underwent single- and paired-pulse transcranial magnetic stimulation and clinical assessments. Transcranial magnetic stimulation measures included short-interval intracortical inhibition (2 and 4 milliseconds), long-interval intracortical inhibition (100, 150, and 200 milliseconds), cortical silent period, and intracortical facilitation (10, 15, and 20 milliseconds). Ten participants with major depressive disorder initiated antidepressant treatment or had dose adjustments. These participants were reassessed after treatment. Depression symptom severity was measured with the Children's Depression Rating Scale, Revised. Robust regression modeling compared healthy and depressed adolescents at baseline. Relationships between changes in cortical inhibition and changes in depressive symptom severity were assessed in the depressed adolescents receiving antidepressant treatment. RESULTS: Our results revealed that at baseline, short-interval intracortical inhibition-2 was significantly reduced (Padj = .01) in depressed participants, suggesting impaired cortical inhibition compared with healthy controls. At follow-up, improvement in Children's Depression Rating Scale, Revised scores correlated with improvement in short-interval intracortical inhibition-4 amplitude (greater inhibition) after antidepressant treatment (R2 = 0.63; P = .01). CONCLUSIONS: These results suggest that cortical inhibition measures may have promise as biomarkers in adolescents treated for 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 | 0.002 |
| 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) | 0.001 | 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".