Visual speech gestures modulate efferent auditory system
Bibliographic record
Abstract
Visual and auditory systems interact at both cortical and subcortical levels. Studies suggest a highly context-specific cross-modal modulation of the auditory system by the visual system. The present study builds on this work by sampling data from 17 young healthy adults to test whether visual speech stimuli evoke different responses in the auditory efferent system compared to visual non-speech stimuli. The descending cortical influences on medial olivocochlear (MOC) activity were indirectly assessed by examining the effects of contralateral suppression of transient-evoked otoacoustic emissions (TEOAEs) at 1, 2, 3 and 4 kHz under three conditions: (a) in the absence of any contralateral noise (Baseline), (b) contralateral noise + observing facial speech gestures related to productions of vowels /a/ and /u/ and (c) contralateral noise + observing facial non-speech gestures related to smiling and frowning. The results are based on 7 individuals whose data met strict recording criteria and indicated a significant difference in TEOAE suppression between observing speech gestures relative to the non-speech gestures, but only at the 1 kHz frequency. These results suggest that observing a speech gesture compared to a non-speech gesture may trigger a difference in MOC activity, possibly to enhance peripheral neural encoding. If such findings can be reproduced in future research, sensory perception models and theories positing the downstream convergence of unisensory streams of information in the cortex may need to be revised.
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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) | 0.003 | 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".