Polarity-specific transcranial direct current stimulation disrupts auditory pitch learning
Bibliographic record
Abstract
Transcranial direct current stimulation (tDCS) is attracting increasing interest because of its potential for therapeutic use. While its effects have been investigated mainly with motor and visual tasks, less is known in the auditory domain. Past tDCS studies with auditory tasks demonstrated various behavioral outcomes, possibly due to differences in stimulation parameters, task-induced brain activity, or task measurements used in each study. Further research, using well-validated tasks is therefore required for clarification of behavioral effects of tDCS on the auditory system. Here, we took advantage of findings from a prior functional magnetic resonance imaging study, which demonstrated that the right auditory cortex is modulated during fine-grained pitch learning of microtonal melodic patterns. Targeting the right auditory cortex with tDCS using this same task thus allowed us to test the hypothesis that this region is causally involved in pitch learning. Participants in the current study were trained for 3 days while we measured pitch discrimination thresholds using microtonal melodies on each day using a psychophysical staircase procedure. We administered anodal, cathodal, or sham tDCS to three groups of participants over the right auditory cortex on the second day of training during performance of the task. Both the sham and the cathodal groups showed the expected significant learning effect (decreased pitch threshold) over the 3 days of training; in contrast we observed a blocking effect of anodal tDCS on auditory pitch learning, such that this group showed no significant change in thresholds over the 3 days. The results support a causal role for the right auditory cortex in pitch discrimination learning.
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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) | 0.001 | 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".