Synchronization of two active ears via binaural coupling
Bibliographic record
Abstract
Abstract The two ears of many non-mammalian vertebrates are acoustically coupled through an interaural cavity. Sounds can hit both the external and internal surfaces of the tympanic membranes, providing mechanical directional sensitivity for sound localization. This coupling may also give rise to binaural synchronization. In other words, each inner ear could influence the function of the other. Previous work in lizards demonstrates that binaural coupling affects the spontaneous otoacoustic emissions (SOAEs) measured at each external auditory meatus, with properties indicative of binaural synchronization. However, it is unclear how binaural coupling and, consequently, synchronization contribute to SOAE generation, which is typically modelled as being localized to an individual ear. We simultaneously measured SOAEs at both ears of green anole lizards ( Anolis carolinensis ) and found robust relationships between them, including evidence that binaural synchronization could not be attributed to one ear uniformly driving the other. Instead, we observed frequency-dependent phase-locking between the two ears, primarily at frequencies where SOAE peaks occurred in both ears. While some pairs of ears were more strongly synchronized than others, we consistently found that binaural coupling could have greater effects on the resulting emissions than the coupling between generators within the same ear. We propose a framework for active hearing that incorporates binaural coupling, accounting for its effects on SOAE generation and sound localization in the green anole.
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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 | 0.001 |
| 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".