Lateralized hippocampal volume increase following high‐frequency left prefrontal repetitive transcranial magnetic stimulation in patients with major depression
Bibliographic record
Abstract
Aim Repetitive transcranial magnetic stimulation (rTMS) has been applied as a treatment for patients with treatment‐resistant depression in recent years, and a large body of evidence has demonstrated its therapeutic efficacy through stimulating neuronal plasticity. The aim of this study was to investigate structural alterations in the hippocampus (HIPP) and amygdala (AM) following conventional rTMS in patients with depression. Methods Twenty‐eight patients with depression underwent 10 daily 20‐Hz left prefrontal rTMS over 2 weeks. The left dorsolateral prefrontal cortex (DLPFC) was identified using magnetic resonance imaging‐guided neuronavigation prior to stimulation. Magnetic resonance imaging scans were obtained at baseline and after the completion of rTMS sessions. The therapeutic effects of rTMS were evaluated with the 17‐item Hamilton Depression Rating Scale (HAM‐D17), and the volumes of the HIPP and AM were measured by a manual tracing method. Results Statistical analyses revealed a significant volume increase in the left HIPP (+3.4%) after rTMS but no significant volume change in the AM. No correlation was found between the left HIPP volume increase and clinical improvement, as measured by the HAM‐D17. Conclusion The present study demonstrated that conventional left prefrontal rTMS increases the HIPP volume in the stimulated side, indicating a remote neuroplastic effect through the cingulum bundle.
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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 | 0.000 |
| 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".