Temporal Lobe Epilepsy Alters Auditory-motor Integration For Voice Control
Bibliographic record
Abstract
Temporal lobe epilepsy (TLE) is the most common drug-refractory focal epilepsy in adults. Previous research has shown that patients with TLE exhibit decreased performance in listening to speech sounds and deficits in the cortical processing of auditory information. Whether TLE compromises auditory-motor integration for voice control, however, remains largely unknown. To address this question, event-related potentials (ERPs) and vocal responses to vocal pitch errors (1/2 or 2 semitones upward) heard in auditory feedback were compared across 28 patients with TLE and 28 healthy controls. Patients with TLE produced significantly larger vocal responses but smaller P2 responses than healthy controls. Moreover, patients with TLE exhibited a positive correlation between vocal response magnitude and baseline voice variability and a negative correlation between P2 amplitude and disease duration. Graphical network analyses revealed a disrupted neuronal network for patients with TLE with a significant increase of clustering coefficients and path lengths as compared to healthy controls. These findings provide strong evidence that TLE is associated with an atypical integration of the auditory and motor systems for vocal pitch regulation, and that the functional networks that support the auditory-motor processing of pitch feedback errors differ between patients with TLE and healthy controls.
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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 | 0.001 |
| 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".