Modulating short-term auditory memory with focal transcranial direct current stimulation applied to the Supramarginal Gyrus
Bibliographic record
Abstract
Abstract Previous studies have shown that transcranial direct current stimulation (tDCS) can affect performance by decreasing regional excitability in a brain region that contributes to the task of interest. To our knowledge, no research to date has found both enhancing and diminishing effects on performance, depending upon which polarity of current is applied. The supramarginal gyrus (SMG) is an ideal brain region for testing tDCS effects because it is easy to identify using the 10-20 EEG coordinate system, and results of neuroimaging studies have implicated the left SMG in short-term memory for phonological and non-phonological sounds. In the present study, we found that applying tDCS to the left SMG affected pitch memory in a manner that depended upon the polarity of stimulation: cathodal tDCS had a negative impact on performance while anodal tDCS had a positive impact. These effects were significantly different from sham stimulation, which did not influence performance; they were also specific to the left hemisphere – no effect was found when applying cathodal stimulation to the right SMG – and were unique to pitch memory as opposed to memory for visual shapes. Our results provide further evidence that the left SMG is a nodal point for short-term auditory storage and demonstrate the potential of tDCS to influence cognitive performance, and to causally examine hypotheses derived from neuroimaging studies.
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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".