Evidence map›Paper›PMID 42238072›Full record

ArticleArXiv2026

Computational Auditory Periphery Models: the Return of the Rodent.

Morgan Thienpont, F Deloche, S Keshishzadeh, D Kiselev, J Bourien, J-L Puel, B N Buran, N Bramhall, S Verhulst

Abstract readPreprint
In one paragraph

Article in ArXiv, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors.

Morgan ThienpontHearing Technology @ WAVES Team, Department of Information Technology, Ghent University, Ghent, Belgium.
F DelocheHearing Technology @ WAVES Team, Department of Information Technology, Ghent University, Ghent, Belgium.
S KeshishzadehHearing Technology @ WAVES Team, Department of Information Technology, Ghent University, Ghent, Belgium.
D KiselevInstitute for Neurosciences Montpellier, University of Montpellier, Montpellier, France.
J BourienInstitute for Neurosciences Montpellier, University of Montpellier, Montpellier, France.
J-L PuelInstitute for Neurosciences Montpellier, University of Montpellier, Montpellier, France.
B N BuranOregon Hearing Research Center (OHRC), Department of Otolaryngology - Head & Neck Surgery, Oregon Health & Science University, Portland, Oregon, USA.
N BramhallVA National Center for Rehabilitative Auditory Research (NCRAR), Veterans Affairs Portland Health Care System, Portland, OR, USA.
S VerhulstHearing Technology @ WAVES Team, Department of Information Technology, Ghent University, Ghent, Belgium.

Funding

Mouse, Man, and Machine: Combining Model Systems to Develop a Biomarker for Cochlear Deafferentation in Humans (Administrative Supplement)R01DC020423 · NIDCD · OREGON HEALTH & SCIENCE UNIVERSITY · PI Naomi Bramhall · 2022 to 2026
$3.3M
NIDCD NIH HHS R01 DC020423
6 · The paper itself

Abstract

Animal experiments have provided many insights on auditory function, notably in cases of sensorineural hearing loss (SNHL). However, it is not always clear how these findings translate to the human auditory system, especially in clinically relevant contexts. Cross-species computational models of the auditory periphery can help bridge the gap between non-invasive human diagnostics and experimental evidence from animal studies. In this work we adapted a one-dimensional (1-D) nonlinear cochlear transmission-line (TL) model designed for the human auditory periphery (Verhulst et al., 2018) to mouse and gerbil, enabling a single computational framework for cross-species research on SNHL. Species-specific anatomical and physiological parameters - including basilar membrane (BM) length and width, stapes area, middle-ear transfer functions, and characteristic-frequency range - were adjusted to match each species' auditory periphery and hearing range. Other cochlear parameters were calibrated to reproduce realistic cochlear tuning and compressive growth. The adapted mouse and gerbil models were validated against experimental species-specific BM velocity level-growth characteristics, auditory-nerve (AN) tuning curves, and distortion-product otoacoustic emissions (DPOAEs). Simulated AN outputs reasonably matched empirical measurements, including realistic AN thresholds and frequency selectivity. However, the discrepancy between simulations and measurements became larger for cochlear sections closer to the base or apex. Simulations of auditory nerve synaptopathy reproduced observed differences in recorded auditory brainstem and envelope following responses from mice and gerbils with cochlear synaptopathy. However, OHC individualization of the mouse model based on DPOAEs failed to faithfully reproduce individual measured data, although inter-group differences in OHC damage were captured. Our findings demonstrate that biophysically grounded auditory periphery models can be translated across species while preserving realistic sound-coding properties and pathophysiological alterations. This approach refines the interpretation of animal data in specific hypotheses of human hearing, facilitates the development of new stimuli to test in rodents, and may enable in silico investigations of OHC loss, synaptopathy, and their functional consequences.

Identifiers

PMID42238072
PMCPMC13229084

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LicenceCC BY-NC-ND
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.