Effects of online prefrontal transcranial alternating current stimulation in the alpha and theta frequency bands on latent-variable measures of executive functions
Bibliographic record
Abstract
Executive functions (EFs) are high-level cognitive processes essential for adaptive, goal-directed behavior. They are supported by oscillatory neural activity, particularly in the alpha and theta frequency bands, across local and distributed brain networks involving prefrontal regions. Previous studies have used transcranial alternating current stimulation (tACS) to modulate such activity and have reported significant performance improvement on EF tasks. However, most relied on single-task scores as outcome measures, which may reflect not only domain-general executive functioning but also task-specific or lower-level processes. This double-blind sham-controlled within-subject study examined the effects of online prefrontal tACS at alpha (10 Hz) and theta (6 Hz) frequencies on EF performance, measured via latent-variable scores that capture shared variance across multiple EF tasks, in healthy individuals ( n = 24). Outcome measures were derived using the NIH EXAMINER battery, yielding latent scores for four EF components (common EF, cognitive control, working memory, and fluency) as well as task scores. Linear mixed models revealed significantly higher common EF and cognitive control scores during alpha-tACS, with large effect sizes, and smaller, more limited stimulation effects on task scores. Exploratory analyses suggested biological sex-specific response to stimulation, with alpha-tACS effects observed primarily in females. These findings support a causal role for prefrontal alpha-band oscillations in EFs and underscore the value of latent-variable measures of executive functioning in neuromodulation research. • Online prefrontal alpha-tACS improved executive functions in healthy adults. • Effects were observed for common EF and cognitive control components. • No effects on fluency and working memory components were observed. • Effects were found mainly on latent-variable measures compared to task scores. • Theta-tACS did not significantly modulate executive 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 | 0.000 | 0.001 |
| 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".