Transcranial Magnetic Stimulation and Transcranial Direct Current Stimulation Across Mental Disorders
Bibliographic record
Abstract
Importance: Noninvasive brain stimulation (NIBS) interventions have been shown to be efficacious in several mental disorders, but the optimal dose stimulation parameters for each disorder are unknown. Objective: To define NIBS dose stimulation parameters associated with the greatest efficacy in symptom improvement across mental disorders. Data Sources: Studies were drawn from an updated (to April 30, 2023) previous systematic review based on a search of PubMed, OVID, and Web of Knowledge. Study Selection: Randomized clinical trials were selected that tested transcranial magnetic stimulation (TMS) or transcranial direct current stimulation (tDCS) for any mental disorder in adults aged 18 years or older. Data Extraction and Synthesis: Two authors independently extracted the data. A 1-stage dose-response meta-analysis using a random-effects model was performed. Sensitivity analyses were conducted to test robustness of the findings. This study followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline. Main Outcomes and Measures: The main outcome was the near-maximal effective doses of total pulses received for TMS and total current dose in coulombs for tDCS. Results: A total of 110 studies with 4820 participants (2659 men [61.4%]; mean [SD] age, 42.3 [8.8] years) were included. The following significant dose-response associations emerged with bell-shaped curves: (1) in schizophrenia, high-frequency (HF) TMS on the left dorsolateral prefrontal cortex (LDLPFC) for negative symptoms (χ2 = 9.35; df = 2; P = .009) and TMS on the left temporoparietal junction for resistant hallucinations (χ2 = 36.52; df = 2; P < .001); (2) in depression, HF-DLPFC TMS (χ2 = 14.49; df = 2; P < .001); (3) in treatment-resistant depression, LDLPFC tDCS (χ2 = 14.56; df = 2; P < .001); and (4) in substance use disorder, LDLPFC tDCS (χ2 = 33.63; df = 2; P < .001). The following significant dose-response associations emerged with plateaued or ascending curves: (1) in depression, low-frequency (LF) TMS on the right DLPFC (RDLPFC) with ascending curve (χ2 = 25.67; df = 2; P = .001); (2) for treatment-resistant depression, LF TMS on the bilateral DLPFC with ascending curve (χ2 = 5.86; df = 2; P = .004); (3) in obsessive-compulsive disorder, LF-RDLPFC TMS with ascending curve (χ2 = 20.65; df = 2; P < .001) and LF TMS on the orbitofrontal cortex with a plateaued curve (χ2 = 15.19; df = 2; P < .001); and (4) in posttraumatic stress disorder, LF-RDLPFC TMS with ascending curve (χ2 = 54.15; df = 2; P < .001). Sensitivity analyses confirmed the main findings. Conclusions and Relevance: The study findings suggest that NIBS yields specific outcomes based on dose parameters across various mental disorders and brain regions. Clinicians should consider these dose parameters when prescribing NIBS. Additional research is needed to prospectively validate the findings in randomized, sham-controlled trials and explore how other parameters contribute to the observed dose-response association.
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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 | 0.032 | 0.107 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.010 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".