Randomized, crossover, sham-controlled, double-blind study of transcranial direct current stimulation of left DLPFC on executive functions
Bibliographic record
Abstract
BACKGROUND: Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation technique commonly used to modulate cognitive functions; so-called "anodal" stimulation is considered to increase cortical excitability while "cathodal" stimulation is presumed to have the opposite result. Yet, a growing number of recent studies question the robustness of this polarity-dependent effect, namely because of the important inter-individual variability with regards to tDCS modulatory effects. A plausible reason for this heterogenous response may lay in task impurity issues in the evaluation of cognitive functions. OBJECTIVE: To address the question of task impurity the NIH-Examiner, a neuropsychological test battery that uses latent variables, which assess the common variance across multiple measures of a given concept, was administered to 24 healthy individuals following tDCS. This battery contains 11 tasks and provides latent variables for general executive functioning, fluency, cognitive control and working memory. METHODS: Anodal, cathodal, and sham stimulation (20 minutes, 1.5 mA) was administered over left dorsolateral prefrontal cortex and right supra-orbital area in a randomized, crossover, sham-controlled, double blind protocol. RESULTS: Factorial scores and task performance indices of executive function were not modulated by tDCS. CONCLUSIONS: Offline tDCS has limited impact on executive functions at both the task and factorial levels. This suggests that reducing task impurity does not increase the effectiveness of tDCS in modulating cognitive functions.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".