Baseline markers of cortical excitation and inhibition predict response to theta burst stimulation treatment for youth depression
Bibliographic record
Abstract
Theta burst stimulation (TBS), a specific form of repetitive transcranial magnetic stimulation (TMS), is a promising treatment for youth with Major Depressive Disorder (MDD) who do not respond to conventional therapies. However, given the variable response to TBS, a greater understanding of how baseline features relate to clinical response is needed to identify which patients are most likely to benefit from this treatment. In the current study, we sought to determine if baseline neurophysiology, specifically cortical excitation and/or inhibition, is associated with antidepressant response to TBS. In two independent open-label clinical trials, youth (aged 16-24 years old) with MDD underwent bilateral dorsolateral prefrontal cortex (DLPFC) TBS treatment. Clinical trial one and two consisted of 10 and 20 daily sessions of bilateral DLPFC TBS, respectively. At baseline, single-pulse TMS combined with electroencephalography was used to assess the neurophysiology of 4 cortical sites: bilateral DLPFC and inferior parietal lobule. Measures of cortical excitation and inhibition were indexed by TMS-evoked potentials (i.e., P30, N45, P60, N100, and P200). Depression severity was measured before, during and after treatment completion using the Hamilton Rating Scale for Depression-17. In both clinical trials, the baseline left DLPFC N45 and P60, which are believed to reflect inhibitory and excitatory mechanisms respectively, were predictors of clinical response. Specifically, greater (i.e., more negative) N45 and smaller P60 baseline values were associated with greater treatment response to TBS. Accordingly, cortical excitation and inhibition circuitry of the left DLPFC may have value as a TBS treatment response biomarker for youth with MDD.Clinical trial 1 registration number: NCT02472470 (June 15, 2015).Clinical trial 2 registration number: NCT03708172 (October 17, 2018).
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".