Subgenual Cingulate Theta Activity Predicts Treatment Response of Repetitive Transcranial Magnetic Stimulation in Participants With Vascular Depression
Bibliographic record
Abstract
Repetitive transcranial magnetic stimulation (rTMS) is an effective treatment for depression.Increased metabolism in the anterior cingulate cortex (ACC) is a known predictor for antidepressant response.The authors assessed whether increased theta power within the ACC predicts rTMS response in participants with vascular depression.Sixty-five participants were randomized to active or sham rTMS.Outcome was assessed using the Hamilton Depression Rating Scale.Electroencephalography was obtained, and comparisons were made among each group with a normative database using low-resolution electromagnetic tomography.Results suggest that vascular depression participants respond well to rTMS and that increased low-theta power in the subgenual ACC predicts response to rTMS.A modern apparatus of repetitive transcranial magnetic stimulation (rTMS) was developed in Great Britain in 1985. 1 Since then, rTMS has been utilized to provide noninvasive brain stimulation for research and treatment purposes.The most frequent application of rTMS in psychiatry has been as a treatment for major depression, and the first controlled treatment study was published in 1996. 2 Although a large number of studies have suggested that rTMS is efficacious against depression, a recent review found that the efficacy can be quite variable. 3This may be due to the fact that the etiological factors underlying major depression are heterogeneous, causing some forms of depression to respond better to rTMS than others.Repetitive transcranial magnetic stimulation has already been approved as a standard treatment procedure for depression in some countries such as Canada and Israel; however, it has only recently been approved by the Food and Drug Administration in the United States.The term "vascular depression" has been used to describe depression in elderly patients with cerebrovascular disease.A causal relationship between cerebrovascular disease and late-life depression is supported by evidence such as coexistence of depression with hypertension, coronary artery disease, and multiple hyperintensities on brain imaging. 4Patients with latelife depression often have a chronic, treatment resistant course and frequently meet criteria for vascular 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 | 0.001 | 0.003 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".