Sivaprakasam, A. | bioRxiv Science

bioRxiv2026

Differentiating the Physiological Signatures of Cochlear Synaptopathy and Inner Hair Cell Damage in a Chinchilla Model

Aging and noise over-exposure lead to complex mixtures of cochlear degradation that impair the structure and function of outer hair cells, inner hair cells (IHCs), and the cochlear nerve. However, IHC damage and cochlear synaptopathy (CS) remain pathologies "hidden" from the audiogram. This study aimed to identify and differentiate the physiological signatures of these two distinct pathologies using promising non-invasive assays: Envelope Following Responses (EFRs), Auditory Brainstem Response (ABRs), Wideband middle-ear reflexes (WB-MEMRs), and Distortion Product Otoacoustic Emissions (DPOAEs). We utilized chinchilla models of carboplatin-induced (CA) IHC damage (N = 4) and temporary threshold shift (TTS) noise-induced CS (N = 4) to compare the physiological signatures of each pathology. While both groups showed unchanged ABR thresholds two weeks after exposure, EFRs, ABR Wave V/I ratios, and MEMRs showed distinct effects of exposure. Despite non-elevated ABR-derived audiometric thresholds after exposure, both CA and TTS exposure resulted in severe in EFR "peakiness", particularly for sharp, short-duty-cycle stimuli and significant elevations in ABR Wave V/I ratios. However, these findings were less-pronounced in the TTS-exposed animals. WB-MEMR amplitudes were decreased with elevated thresholds in both groups; this effect was more pronounced in the TTS group. Opposite trends in DPOAE amplitudes indicated that while both IHC damage and CS result in similar suprathreshold temporal coding deficits, effects on outer-hair-cell integrity and auditory efferent physiology may differ between the two pathologies. Future work and novel diagnostics should aim to distinguish these specific cochlear pathologies in clinical populations, or at the very least consider their overlap. HighlightsO_LIA multi-metric diagnostic approach was used with chinchilla models of inner-hair-cell (IHC) damage and cochlear synaptopathy (CS). C_LIO_LIIHC damage and synaptopathy both cause suprathreshold deficits "hidden" from the audiogram. C_LIO_LIIHC damage results in more severe temporal envelope coding degradation than does synaptopathy. C_LIO_LIA combination of EFR "peakiness", ABR Wave V/I ratio, and Wideband Middle Ear Muscle Reflex (WB-MEMR) appear to be useful measures for profiling IHC damage and CS. C_LI

neuroscience↗

bioRxiv2022

Estimation of cochlear frequency selectivity using a convolution model of forward-masked compound action potentials

Frequency selectivity is a fundamental property of the peripheral auditory system; however, the invasiveness of auditory nerve (AN) experiments limits its study in the human ear. Compound action potentials (CAPs) associated with forward-masking have been suggested as an alternative means to assess cochlear frequency selectivity. Previous methods relied on an empirical comparison of AN and CAP tuning curves in animal models, arguably not taking full advantage of the information contained in forward-masked CAPs. In this work, we seek to provide a direct estimate of the quality factor characterizing AN frequency tuning using many forward-masked CAP responses. The method is based on a convolution model of the CAP that takes into account the masking of AN populations induced by notched-noise maskers with various notch widths and attenuations. The model produces masking patterns that, once convolved by a unitary response, predict forward-masked CAP waveforms. Model parameters, including those characterizing frequency selectivity, are fine-tuned by minimizing waveform prediction errors across the different masking conditions, yielding robust estimates. The method was applied to click-evoked CAPs at the round window of anesthetized chinchillas. The estimated quality factor Q10 as a function of center frequency is shown to closely match the average quality factor obtained from AN-fiber tuning curves, without the need for an empirical correction factor. Beyond the estimation of frequency selectivity, the proposed model proves to be accurate in predicting forward-masked CAP responses, and therefore could be extended to study more complex aspects of cochlear signal processing using a similar experimental approach.

neuroscience↗