Event-related potential correlates of online monitoring of auditory feedback during vocalization.
Bibliographic record
Abstract
When speakers hear the fundamental frequency (F0) of their voice altered, they shift their F0 in the direction opposite to the perturbation. The neural mechanisms underlying this response are poorly understood. In the present study, event-related potentials (ERPs) were used to examine the neural mechanisms used to detect alterations in auditory feedback during an ongoing utterance. Participants vocalized for 3 s, and heard their auditory feedback shifted by 0, 25, 50, 100, or 200 cents for 100 ms midutterance. In two sessions, participants either vocalized at their habitual pitch, or matched a target pitch. A mismatch negativity (MMN) was observed, with the amplitude positively related to the size of the perturbations. No differences were found between sessions. The F0 compensation response was found to be smaller for 200 cent shifts than 100 cent shifts, and a positivity was observed in the ERPs for a 200 cent shift. This result suggests that a 200 cent shift may be perceived as externally (rather than internally) generated. Thepresence of an MMN, and no earlier (N100) response suggests that the underlying sensory process used to identify and compensate for errors in midutterance may differ from feedback monitoring at utterance onset.
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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 | 0.004 |
| 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".