Evidence-based umbrella review of cognitive effects of prefrontal tDCS
Bibliographic record
Abstract
Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation technique, which has been increasingly used as an investigational tool in neuroscience. In social and affective neuroscience research, the prefrontal cortex has been primarily targeted, since this brain region is critically involved in complex psychobiological processes subserving both Șhotș and Școldș domains. Although several studies have suggested that prefrontal tDCS can enhance neuropsychological outcomes, meta-analyses have reported conflicting results. Therefore, we aimed to assess the available evidence by performing an umbrella review of meta-analyses. We evaluated the effects of prefrontal active vs sham tDCS on different domains of cognition among healthy and neuropsychiatric individuals. A MeaSurement Tool to Assess Systematic Reviews 2 was employed to evaluate the quality of meta-analyses, and the GRADE system was employed to grade the quality of evidence of every comparison from each meta-analysis. PubMed/MEDLINE, PsycINFO and the Cochrane Database of Systematic Reviews were searched, and 11 meta-analyses were included resulting in 55 comparisons. Only 16 comparisons reported significant effects favoring tDCS, but 13 of them had either very low or low quality of evidence. Of the remaining 39 comparisons which reported non-significant effects, 38 had either very low or low quality of evidence. Meta-analyses were rated as having critically low and low quality. Among several reasons to explain these findings, the lack of consensus and reproducibility in tDCS research is discussed.
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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 | 0.015 | 0.051 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.014 | 0.016 |
| Bibliometrics | 0.017 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".