Theta band high definition transcranial alternating current stimulation, but not transcranial direct current stimulation, improves associative memory performance
Bibliographic record
Abstract
Associative memory (AM) deficits are common in neurodegenerative disease and novel therapies aimed at improving these faculties are needed. Theta band oscillations within AM networks have been shown to be important for successful memory encoding and modulating these rhythms represents a promising strategy for cognitive enhancement. Transcranial alternating current stimulation (TACS) has been hypothesized to entrain and increase power of endogenous brain rhythms. For this reason, we hypothesized that focal delivery of theta band electrical current, using high-definition TACS, would result in improved AM performance compared to sham stimulation or transcranial direct current stimulation (TDCS). In this pilot study, 60 healthy subjects were randomized to receive high definition TACS, high definition TDCS, or sham stimulation delivered to the right fusiform cortex during encoding of visual associations. Consistent with our hypothesis, improved AM performance was observed in the TACS group, while TDCS had no effect. However, TACS also resulted in improved correct rejection of never seen items, reduced false memory, and reduced forgetting, suggesting the effect may not be specific for AM processes. Overall, this work informs strategies for improving associative memory and suggests alternating current is more effective than direct current stimulation in some contexts.
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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 | 0.000 |
| 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) | 0.002 | 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".