The Greenwood function shows close alignment with pitch perceived by cochlear implant patients with long, flexible electrode arrays and fine-structure stimulation
Bibliographic record
Abstract
Introduction: The natural, tonotopic frequency distribution of the inner ear is typically described by the Greenwood function, which logarithmically projects the audible frequency spectrum onto the intracochlear basilar membrane. Recent developments in cochlear implant (CI) programming aim to improve sound quality and music perception through consideration of the frequency distribution as described by the Greenwood function when assigning frequency bands to the individual contacts of the electrode array. This approach is commonly referred to as anatomy-based fitting (ABF). However, empirical validation of the Greenwood function to accurately describe pitch as perceived by CI users is lacking. Methods: Twelve CI patients with single-sided deafness (SSD) participated in the study. A pitch matching task was conducted at four different appointments and with two different fitting maps (standard and ABF). At each test appointment, participants were asked to set the frequency of a pure tone presented through a loudspeaker to the pitch perceived when stimulated with the single contacts of the CI electrode array. The cochlear anatomy of the patients was reconstructed based on clinical imaging to derive the location of the stimulating contacts relative to the basilar membrane, allowing for the comparison of the pitch perceived by the patients to the frequency suggested by the Greenwood function for each stimulating contact. Results: In general, subjective pitch percepts were found to agree well with the frequency suggested by the Greenwood function independent of subject, contact, or applied fitting map. Differences between pitch matches and Greenwood were found to be not statistically significant. At least part of the outcomes of previous studies reporting a basal frequency shift can be explained by the tonotopic mapping functions applied within these studies. Discussion: The present results suggest that the Greenwood function is well-suited for representing the tonotopic frequency distribution not only for normal hearing subjects but for CI recipients as well. Further advances in frequency mapping should also take the neural health of the cochlea into account, allowing for additional individualization of frequency mapping in CIs.
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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 | 0.001 | 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) | 0.006 | 0.001 |
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".