Top–Down Inhibitory Mechanisms Underlying Auditory–Motor Integration for Voice Control: Evidence by TMS
Bibliographic record
Abstract
The dorsolateral prefrontal cortex (DLPFC) has been implicated in auditory-motor integration for accurate control of vocal production, but its precise role in this feedback-based process remains largely unknown. To this end, the present event-related potential study applied a transcranial magnetic stimulation (TMS) protocol, continuous theta-burst stimulation (c-TBS), to disrupt cortical activity in the left DLPFC as young adults vocalized vowel sounds while hearing their voice unexpectedly shifted upwards in pitch. The results showed that, as compared to the sham condition, c-TBS over left DLPFC led to significantly larger vocal compensations for pitch perturbations that were accompanied by significantly smaller cortical P2 responses. Source localization analyses revealed that this brain activity pattern was the result of reduced activation in the left superior frontal gyrus and right inferior parietal lobule (supramarginal gyrus). These findings demonstrate c-TBS-induced modulatory effects of DLPFC on the neurobehavioral processing of vocal pitch regulation, suggesting that disrupting prefrontal function may impair top-down inhibitory control mechanisms that prevent speech production from being excessively influenced by auditory feedback, resulting in enhanced vocal compensations for feedback perturbations. This is the first study that provides direct evidence for a causal role of the left DLPFC in auditory feedback control of vocal production.
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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".