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arxiv: 2605.19070 · v2 · pith:RMGTX7AHnew · submitted 2026-05-18 · 🧬 q-bio.NC

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
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S. Verhulst
This is my paper

Pith reviewed 2026-05-21 07:39 UTC · model grok-4.3

classification 🧬 q-bio.NC
keywords computational cochlear modelcross-species auditory peripherysensorineural hearing lossrodent basilar membraneauditory nerve tuningouter hair cell damagedistortion product otoacoustic emissions
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The pith

A single nonlinear cochlear model adapts from humans to mice and gerbils by changing only anatomical parameters and reproduces realistic sound coding plus hearing-loss effects.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The authors start with a one-dimensional nonlinear transmission-line model built for the human ear and modify it for two rodent species simply by inserting each animal's measured basilar-membrane length and width, stapes area, middle-ear transfer function, and frequency range. After a modest recalibration of the remaining cochlear parameters, the same framework produces basilar-membrane velocity growth, auditory-nerve tuning curves, and distortion-product otoacoustic emissions that line up with published rodent data. When the model is run with simulated cochlear synaptopathy, it also captures the distinct changes in auditory-brainstem and envelope-following responses seen experimentally in mice versus gerbils. The work therefore supplies one computational scaffold that can move experimental findings from rodent ears into human diagnostic contexts without rewriting the underlying biophysics for each species.

Core claim

By adjusting only species-specific anatomical and physiological parameters (basilar-membrane length and width, stapes area, middle-ear transfer functions, and frequency range) plus limited calibration of the remaining cochlear parameters, a single 1-D nonlinear cochlear transmission-line model originally written for humans can be translated to mouse and gerbil while preserving realistic tuning, compression, auditory-nerve output, and the signature changes produced by sensorineural hearing loss.

What carries the argument

The 1-D nonlinear cochlear transmission-line model, which propagates traveling waves along the basilar membrane with active outer-hair-cell feedback and is retuned by swapping in species-specific geometry and middle-ear filters.

If this is right

  • The same model code can be used to run parallel simulations of sensorineural hearing loss in humans, mice, and gerbils without rewriting the core equations.
  • Simulated auditory-nerve spike trains from the adapted rodent models can be compared directly with non-invasive human tests such as auditory brainstem responses.
  • Differences in how mice and gerbils respond to cochlear synaptopathy can be explored inside one consistent computational environment.
  • Group-level outer-hair-cell damage patterns are captured even when individual-animal predictions remain imperfect.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • The approach could be tested on additional mammals to see whether the same limited set of anatomical swaps continues to suffice.
  • If the model remains stable across species, it becomes possible to run virtual experiments that combine rodent synaptic counts with human clinical waveforms.
  • Clinicians might eventually use outputs from the rodent-adapted version to interpret why some patients show preserved distortion products yet elevated thresholds.

Load-bearing premise

That changing only a handful of measured anatomical dimensions and then calibrating the rest of the cochlear parameters is enough to keep the model's tuning, compression, and hearing-loss behavior realistic in each new species.

What would settle it

A direct comparison showing that the model's predicted auditory-nerve thresholds or distortion-product levels in the basal or apical turns fall outside the range of experimental measurements by more than the reported inter-animal variability.

Figures

Figures reproduced from arXiv: 2605.19070 by B. N. Buran, D. Kiselev, F. Deloche, J. Bourien, J.-L. Puel, Morgan Thienpont, N. Bramhall, S. Keshishzadeh, S. Verhulst.

Figure 1
Figure 1. Figure 1: Schematic overview of the computational auditory model Diagram showing the main components of the human auditory periphery model (Verhulst et al., 2018) for simulating normal or hearing loss affected auditory responses at multiple stages along the auditory pathway with: EC = ear canal, OAE = otoacoustic emissions, IHC = inner hair cell, AN = auditory nerve, FFT = Fast Fourier Transform, EFR = envelope foll… view at source ↗
Figure 2
Figure 2. Figure 2: Animal dataset ABRs and EFRs a) Experimental click ABRs (W1) of the gerbil reference dataset pre and post kainic acid (KA) administration. b) Experimental click ABRs (W1, W3, and W5) of the reference control mouse dataset. (c) Reference envelope-following responses (EFRs) to a rectangular amplitude-modulated (RAM) pure tone stimulus for the mouse and gerbil populations. (c) RAM EFRs measured in gerbils usi… view at source ↗
Figure 3
Figure 3. Figure 3: DPOAEs and synapse count of the mouse dataset Animal data showing the average and 2.5 and 97.5 percentile intervals of distortion-product otoacoustic emission (DPOAE) levels of three mice groups, a) young control, b) age, and c) age + noise exposed, for an intensity level of 55 dB SPL for f1 and 65 dB SPL for f2. The ratio of f2 to f1 is 1.2. The DP-level is defined as the sound pressure level (dB SPL) mea… view at source ↗
Figure 4
Figure 4. Figure 4: Functional changes in auditory model hearing range a) Relationship between tonotopic frequency and fractional distance from the base of the cochlea for each species as defined by the species-specific Greenwood function b) Gain profile of the middle - ear filter for each species compared to data from literature, i.e. rescaled stapes velocity relative to ear canal pressure for gerbil and forward cochlear pre… view at source ↗
Figure 5
Figure 5. Figure 5: Auditory nerve fiber distributions Number of auditory nerve fibres (ANFs) of the high- (HSR), medium- (MSR), and low-spontaneous-rate (LSR) types per inner hair cell (IHC) as a function of characteristic frequency (CF) in the three normal-hearing models: (a) human, (b) gerbil, and (c) mouse. . . tribution is described. 2.2.7. AN, CN and IC The contributions of the AN, CN, and IC to the summed EFR are weigh… view at source ↗
Figure 6
Figure 6. Figure 6: RAM EFR stimulus Rectangular-amplitude-modulated pure tone (RAM) stimulus. This stimulus is used to measure the envelope-following response (EFR). RAMEFR = X 4 k=1 Mfk , fk = fm · k (33) The modulation depth and duty cycle were 100%, and 25%, respectively. Note that for simulations, there is no noise-floor correction. 3. Model Validation 3.1. BM response [PITH_FULL_IMAGE:figures/full_fig_p030_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: BM velocity growth curves Model and experimental basilar membrane (BM) responses: BM output velocity as a function of input intensity at the BM location corre￾sponding to each characteristic frequency (CF), illustrating compressive growth. Pure-tone stimuli were presented at the following CFs: (a) 0.5, 1, and 4 kHz for human; (b) 4, 20, and 40 kHz for gerbil (experimental data from (He et al., 2022)); and … view at source ↗
Figure 8
Figure 8. Figure 8: Tuning curves and thresholds Tuning curves based on high–spontaneous-rate (HSR) auditory nerve fibres in the gerbil (a) and mouse (b) models, shown together with experimental data. Gerbil model thresholds are compared to behavioral thresholds from Ryan (1976), and mouse model thresholds are compared to behavioral thresholds from Birch et al. (1968); Ehret (1974) for the CBA/J and NMRI mouse strains, respec… view at source ↗
Figure 9
Figure 9. Figure 9: Measured and simulated tuning curves Simulated and measured auditory nerve fibre (ANF) tuning in the a) gerbil and b) mouse for a high–spontaneous-rate fiber with a characteristic frequency of approximately 4 and 17 kHz for gerbil and 10 and 30 kHz for mice. Gerbil measurements from (Kiselev, 2025; Taberner et al., 2005) . . 3.3. DPOAEs DPOAEs for the three mouse populations are available for comparison an… view at source ↗
Figure 10
Figure 10. Figure 10: Simulated mouse NH DPOAEs Simulated DPOAE levels for normal￾hearing mice are compared with the average measured DPOAE levels, as well as the minimum and maximum values from the control group. DPOAEs were measured using stimulus levels of 55 dB SPL for f1 and 65 dB SPL for f2, with a fixed frequency ratio of f2/f1 = 1.2. The DP-level is defined as the sound pressure level (dB SPL) measured at the frequency… view at source ↗
Figure 11
Figure 11. Figure 11: DPOAEs simulations Simulated and measured mouse DPOAE levels for the control, aged, and noise exposed + aged groups. The simulated DPOAEs were rescaled linearly to fit within the measured range of DPOAEs using this formula 34. a) f2 = 5.64 kHz b) f2 = 45.24 kHz, the latter is also the frequency for which intergroup differences are largest. DPOAEs were measured using stimulus levels of 55 dB SPL for f1 and… view at source ↗
Figure 12
Figure 12. Figure 12: ABR simulations Comparison of simulated and measured click auditory brainstem response (ABR) amplitudes and latencies for gerbil (left column) and mouse (right column). Panels (a)–(c) show the Wave 1 (W1), Wave 3 (W3), and Wave 5 (W5) amplitude–level functions for gerbil, comparing the model output (orange) with published peak-to-peak measurements for condensation clicks (black markers; (Burkard et al., 1… view at source ↗
Figure 13
Figure 13. Figure 13: ABR as a function of frequency Simulated and measured ABR peak amplitudes (70 dB SPL) for waves W-1 (a), W-3 (b), and W-5 (c) as a function of stimulus frequency (4–64 kHz). Green symbols and solid lines represent simulated amplitudes, whereas black symbols and dashed lines represent measured amplitudes. Each subpanel corresponds to one ABR wave and uses a consistent marker shape across figures (W-1: circ… view at source ↗
Figure 14
Figure 14. Figure 14: Individualized ABRs Comparison of simulated and measured auditory brain￾stem response (ABR) amplitudes gerbil and mouse. Panels (a) shows the Wave 1 (W1) amplitude–level functions for normal hearing (NH), and synaptopathic (SYN) gerbil click ABRs, comparing the model output (full lines) with published (intermittent lines) peak￾to-peak measurements for condensation clicks in gerbils before and after kainic… view at source ↗
Figure 15
Figure 15. Figure 15: RAM EFRs a) Measured and simulated gerbil EFR (envelope following re￾sponse) magnitudes for a RAM (rectangular amplitude modulated) stimulus with a carrier frequency of 4 kHz and a modulation frequency of 116 Hz at 70 dB SPL. For the exper￾imentally measured gerbils there is a control and a kainic acid (KA) treated group, the simulated EFRs contain a normal hearing and a synaptopathic (SYN) group for whic… view at source ↗
read the original 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 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 1-D nonlinear cochlear transmission-line model designed for the human auditory periphery 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 frequency range - were adjusted to match each species' auditory periphery and hearing range. Other cochlear parameters were calibrated to reproduce realistic cochlear tuning and compression. The adapted mouse and gerbil models were validated against experimental BM velocity level-growth characteristics, auditory-nerve (AN) tuning curves, and 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 cochlear synaptopathy reproduced observed differences in recorded auditory brainstem and envelope following responses from mice and gerbils with SNHL. OHC individualization of the mouse model based on DPOAEs failed to faithfully reproduce individual measurements, although intergroup differences in OHC damage were captured. Our findings demonstrate that biophysically grounded auditory models can be translated across species while preserving realistic sound-coding properties and pathophysiological alterations.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

3 major / 1 minor

Summary. The paper adapts a 1-D nonlinear cochlear transmission-line model from human to mouse and gerbil by adjusting species-specific anatomical parameters (BM length/width, stapes area, middle-ear transfer functions, frequency range) and calibrating remaining cochlear parameters to match tuning and compression. Models are validated against BM velocity growth, AN tuning curves, and DPOAEs, with simulations of synaptopathy reproducing ABR and EFR differences in SNHL. The central claim is that biophysically grounded models can be translated across species while preserving realistic sound-coding properties and pathophysiological alterations, despite noted larger discrepancies near base/apex and failure of OHC individualization to match individual DPOAEs.

Significance. If the central claim holds after addressing validation gaps, the work provides a unified computational framework for cross-species SNHL research, enabling better translation of rodent experimental findings to human diagnostics. The reproduction of intergroup SNHL response differences is a strength, but the approach's generality depends on demonstrating that calibration does not embed non-scalable compensations.

major comments (3)
  1. [Abstract] Abstract: the claim of translation 'while preserving realistic sound-coding properties' across the full cochlea is load-bearing but undermined by the explicit statement that 'the discrepancy between simulations and measurements became larger for cochlear sections closer to the base or apex.' This systematic mismatch tests whether adjusting only the listed species-specific parameters plus calibration suffices without further revisions, as required by the weakest assumption.
  2. [Abstract] Abstract (validation and OHC individualization): calibration of cochlear parameters to reproduce realistic tuning and compression precedes comparison of simulated AN outputs and DPOAEs to data. This raises a circularity risk for the independence of the validation, particularly since AN tuning and compression overlap with calibration targets; the manuscript must clarify what aspects were held out for truly independent testing.
  3. [Abstract] Abstract (OHC individualization): failure to reproduce individual DPOAE measurements (while capturing intergroup differences) indicates that the single-framework translation may not extend to individual pathophysiological variations without additional species-specific tuning, which directly challenges the claim that parameter adjustments alone preserve realistic alterations.
minor comments (1)
  1. [Abstract] Abstract: quantitative metrics (e.g., RMSE, correlation coefficients, or error bars on threshold matches) would strengthen the 'reasonably matched' description and allow readers to assess the practical significance of the base/apex discrepancies.

Simulated Author's Rebuttal

3 responses · 0 unresolved

We thank the referee for the constructive comments on our manuscript. We address each major point below, indicating where revisions will be made to improve clarity and precision.

read point-by-point responses

  1. Referee: [Abstract] Abstract: the claim of translation 'while preserving realistic sound-coding properties' across the full cochlea is load-bearing but undermined by the explicit statement that 'the discrepancy between simulations and measurements became larger for cochlear sections closer to the base or apex.' This systematic mismatch tests whether adjusting only the listed species-specific parameters plus calibration suffices without further revisions, as required by the weakest assumption.

    Authors: We agree that the noted increase in discrepancy toward the base and apex is a genuine limitation of the 1-D model and qualifies the scope of our central claim. The mid-cochlear regions, where most auditory information is encoded, show good agreement with data. We will revise the abstract to state that the adapted models preserve realistic sound-coding properties within the primary hearing range of each species, while explicitly acknowledging larger mismatches at the extremes. This revision will also reference the systematic nature of the mismatch to address the concern about whether parameter adjustments alone suffice. revision: yes

  2. Referee: [Abstract] Abstract (validation and OHC individualization): calibration of cochlear parameters to reproduce realistic tuning and compression precedes comparison of simulated AN outputs and DPOAEs to data. This raises a circularity risk for the independence of the validation, particularly since AN tuning and compression overlap with calibration targets; the manuscript must clarify what aspects were held out for truly independent testing.

    Authors: We acknowledge the risk of circularity and will add a dedicated paragraph in the Methods section that separates calibration targets from validation metrics. Calibration was limited to average tuning sharpness (Q10) and compression slopes at a small set of characteristic frequencies; held-out tests include full AN threshold curves across the entire frequency range, BM velocity growth functions at multiple locations, and DPOAE input-output curves from independent experimental cohorts not used in parameter fitting. We will list these held-out elements explicitly to demonstrate independence. revision: yes

  3. Referee: [Abstract] Abstract (OHC individualization): failure to reproduce individual DPOAE measurements (while capturing intergroup differences) indicates that the single-framework translation may not extend to individual pathophysiological variations without additional species-specific tuning, which directly challenges the claim that parameter adjustments alone preserve realistic alterations.

    Authors: The referee is correct that individual OHC damage patterns could not be recovered from DPOAEs without further per-animal adjustments. However, the model still reproduces the direction and magnitude of group-level differences in ABR and EFR between normal-hearing and synaptopathy cohorts, which is the primary translational goal. We will revise the abstract and add a short discussion paragraph clarifying that the framework preserves realistic pathophysiological alterations at the population level; we do not claim individual-level fidelity without supplementary tuning. This distinction does not require new species-specific parameters beyond those already described. revision: partial

Circularity Check

1 steps flagged

Calibration to tuning/compression makes AN tuning and DPOAE matches partly non-independent

specific steps
  1. fitted input called prediction [Abstract]
    "Other cochlear parameters were calibrated to reproduce realistic cochlear tuning and compression. The adapted mouse and gerbil models were validated against experimental BM velocity level-growth characteristics, auditory-nerve (AN) tuning curves, and DPOAEs. Simulated AN outputs reasonably matched empirical measurements, including realistic AN thresholds and frequency selectivity."

    Parameters are fitted to produce realistic tuning and compression; the subsequent claim that simulated AN outputs match empirical tuning curves and frequency selectivity therefore partly reflects the calibration target rather than an independent prediction of sound-coding properties.

full rationale

The paper adjusts species-specific anatomy then calibrates remaining cochlear parameters explicitly to reproduce realistic tuning and compression. It then validates the same models against AN tuning curves (frequency selectivity) and DPOAEs, reporting that outputs 'reasonably matched' data. Because the calibration target overlaps with the validation metrics, the reported preservation of realistic sound-coding properties reduces in part to the fitting process rather than an independent first-principles prediction. Discrepancies grow at base/apex and OHC individualization fails, but the central cross-species translation claim still rests on this calibrated match. No self-citation load-bearing or self-definitional loops were found; the circularity is limited to the fitted-input pattern.

Axiom & Free-Parameter Ledger

1 free parameters · 1 axioms · 0 invented entities

The approach rests on the premise that a single 1-D nonlinear transmission-line framework remains valid after species-specific retuning; calibration steps introduce fitted parameters whose independence from validation data is not quantified in the abstract.

free parameters (1)
  • remaining cochlear parameters for tuning and compression
    Calibrated to reproduce realistic cochlear tuning and compression after species-specific anatomical adjustments.
axioms (1)
  • domain assumption The original human 1-D nonlinear cochlear transmission-line model structure is appropriate for cross-species adaptation with only parameter retuning.
    Invoked when the human model is directly adapted to mouse and gerbil without structural changes.

pith-pipeline@v0.9.0 · 5864 in / 1273 out tokens · 28363 ms · 2026-05-21T07:39:07.468099+00:00 · methodology

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