Amplitude modulation of DPOAEs by acoustic stimulation of the contralateral ear
Bibliographic record
Abstract
CONCLUSION: Otoacoustic emissions generated by outer hair cells (OHCs) are influenced by stimulation of the contralateral ear via a neural pathway involving the olivo-cochlear efferent system. This is often referred to as a contralateral 'suppression reflex', but we suggest that such a term is inappropriate since distortion product otoacoustic emissions (DPOAEs) can be both enhanced and suppressed, and there is continuous modulation with no threshold effects. OBJECTIVE: To characterize the continuous amplitude modulation of DPOAEs by contralateral sound stimulation. MATERIALS AND METHODS: In an animal model (chinchilla), DPOAEs were recorded in real time from one ear during presentation of acoustic stimuli to the opposite ear. RESULTS: DPOAE amplitude is suppressed by an increase in contralateral stimulation, and enhanced by a decrease in same, i.e. the emissions are continuously modulated by activity in the opposite ear. The input-output function shows a linear relationship to this system over a 40-50 dB range of contralateral stimulus levels. After a neural delay time of approximately 25 ms, DPOAE amplitude closely follows contralateral amplitude signals up to modulation frequencies of approximately 20 Hz. Thus, stimuli to one ear continually modulate the OHC system (and therefore the biomechanical amplification) of the contralateral cochlea.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".