A DUAL-CIRCUIT CAUSAL MODEL OF BRAIN STIMULATION TARGETS FOR DEPRESSION
Bibliographic record
Abstract
This systematic review and meta-analysis aimed to evaluate the efficacy of non-invasive brain stimulation (NIBS) in the treatment of neurodevelopmental disorders (NDDs), focusing on Autism Spectrum Disorder (ASD), Attention Deficit Hyperactivity Disorder (ADHD), intellectual disorders, learning disorders, motor disorders, and Tourette and tic related disorders across various age groups.Following a pre-registered protocol (PROSPERO: CRD42022384498) and adhering to the PRISMA guidelines, a comprehensive search of five databases (Embase, Central, PsycInfo, PubMed/Medline, and Scopus) was conducted.Out of 23 identified studies, 15 were included in the meta-analysis.Qualitative risk of bias assessment revealed ten studies with low risk, one with high risk, and some concerns for the remaining twelve.In the quantitative analysis, transcranial magnetic stimulation (TMS) demonstrated a statistically significant overall cognitive improvement in ADHD compared to sham (Hedge's g = 0.71, 95% CI: 0.16 to 1.26, p = 0.01), while transcranial direct current stimulation (tDCS) showed a statistically significant overall cognitive improvement in ASD compared to sham (Hedge's g = 0.76, 95% CI: 0.12 to 1.40, p = 0.02).No publication bias was observed in either analysis.Despite promising results, the limited number of studies and concerns about bias underscore the need for further research on NIBS for NDDs.This review emphasizes the significance of standardized methodology and comparable outcome measures in future trials and stresses the value of replicating evidence for potentially effective treatment protocols.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".