Using Transcranial Electrical Stimulation in Audiological Practice: The Gaps to Be Filled
Bibliographic record
Abstract
The effects of transcranial electrical stimulation (tES) approaches have been widely studied for many decades in the motor field, and are well known to have a significant and consistent impact on the rehabilitation of people with motor deficits. Consequently, it can be asked whether tES could also be an effective tool for targeting and modulating plasticity in the sensory field for therapeutic purposes. Specifically, could potentiating sensitivity at the central level with tES help to compensate for sensory loss? The present review examines evidence of the impact of tES on cortical auditory excitability and its corresponding influence on auditory processing, and in particular on hearing rehabilitation. Overall, data strongly suggest that tES approaches can be an effective tool for modulating auditory plasticity. However, its specific impact on auditory processing requires further investigation before it can be considered for therapeutic purposes. Indeed, while it is clear that electrical stimulation has an effect on cortical excitability and overall auditory abilities, the directionality of these effects is puzzling. The knowledge gaps that will need to be filled are discussed.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".