A Functional Magnetic Resonance Imaging Study of the Effects of Low Frequency Right Prefrontal Transcranial Magnetic Stimulation in Depression
Bibliographic record
Abstract
The study aimed to explore the biological effects of low-frequency repetitive transcranial magnetic stimulation (LFR-TMS) treatment applied to the right prefrontal cortex, comparing this with the effects of high-frequency left-sided (HFL-TMS) in patients with treatment-resistant depression. Twenty-six patients with treatment-resistant depression were randomized to receive either daily LFR-TMS or HFL-TMS treatment for 3 weeks and underwent functional magnetic resonance imaging during a planning task before and after treatment. Patients responded clinically to both forms of treatment with no difference in the degree of response (F1,24 = 0.65;P > 0.05). Low-frequency repetitive transcranial magnetic stimulation resulted in no overall change in task-related activation. However, responders to LFR-TMS demonstrated a bilateral decrease in activity in middle frontal gyrus. In contrast, HFL-TMS produced an increase in activation in left precuneus with responders showing increased activation in several additional regions. Response to LFR-TMS is associated with a bilateral reduction in frontal activation that does not seem to be a nonspecific effect of treatment and differs from the response to HFL-TMS.
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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".