Neural correlates of clinical improvement after deep transcranial magnetic stimulation (DTMS) for treatment-resistant depression: a case report using functional magnetic resonance imaging
Bibliographic record
Abstract
We report the effects of a 4-week trial of deep transcranial magnetic stimulation (DTMS) on depressive and anxious symptoms and brain activity in a patient (Mrs A) with treatment-resistant depression (TRD). The protocol involved a pre- and a post-functional magnetic resonance imaging (fMRI) scan during which Mrs A had to perform a working memory task (i.e., n-back). Her baseline score on the 21-item Hamilton Depression Rating Scale (HAM-D21) was 24, indicating severe depressive symptoms. Immediately after 4 weeks of daily DTMS treatment applied over the left dorsolateral prefrontal cortex (DLPFC), her HAM-D21 score decreased to 13 (a 46% reduction), and 1 month later, it was 12 (a 50% reduction). Moreover, Mrs A's accuracy scores on the n-back task (i.e., 2-back condition) improved from 79% (baseline) to 96% (after DTMS treatment). At the neural level, Mrs A showed significantly increased brain activity in the working memory network (e.g., DLPFC, parietal cortex) during the execution of the 2-back condition after DTMS treatment compared to baseline.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 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".