The envelope following response (EFR) has been proposed as a non-invasive marker of synaptopathy in animal models. However, its amplitude is affected by the spread of basilar-membrane excitation and other coexisting sensorineural hearing deficits. This study aims to (i) improve frequency specificity of the EFR by introducing a derived-band EFR (DBEFR) technique and (ii) investigate the effect of lifetime noise exposure, age and outer-hair-cell (OHC) damage on DBEFR magnitudes. Additionally, we adopt a modelling approach to validate the frequency-specificity of the DBEFR and test how different aspects of sensorineural hearing loss affect peripheral generators. The combined analysis of simulations and experimental data proposes that the DBEFRs extracted from the [2-6]-kHz frequency band is a sensitive and frequency-specific measure of synaptopathy in humans. Individual variability in DBEFR magnitudes among listeners with normal audiograms was explained by their self-reported amount of experienced lifetime noise-exposure and corresponded to amplitude variability predicted by synaptopathy. Older listeners consistently had reduced DBEFR magnitudes in comparison to young normal-hearing listeners, in correspondence to how age-induced synaptopathy affects EFRs and compromises temporal envelope encoding. Lastly, OHC damage was also seen to affect the DBEFR magnitude, hence this marker should be combined with a sensitive marker of OHC-damage to offer a differential diagnosis of synaptopathy in listeners with impaired audiograms.

Over the past decades, different types of auditory models have been developed to study the functioning of normal and impaired auditory processing. Several models can simulate frequency-dependent sensorineural hearing loss (SNHL) and can in this way be used to develop personalized audio-signal processing for hearing aids. However, to determine individualized SNHL profiles, we rely on indirect and noninvasive markers of cochlear and auditory-nerve (AN) damage. Our progressive knowledge of the functional aspects of different SNHL subtypes stresses the importance of incorporating them into the simulated SNHL profile, but has at the same time complicated the task of accomplishing this on the basis of noninvasive markers. In particular, different auditory-evoked potential (AEP) types can show a different sensitivity to outer-hair-cell (OHC), inner-hair-cell (IHC), or AN damage, but it is not clear which AEP-derived metric is best suited to develop personalized auditory models. This study investigates how simulated and recorded AEPs can be used to derive individual AN- or OHC-damage patterns and personalize auditory processing models. First, we individualized the cochlear model parameters using common methods of frequency-specific OHC-damage quantification, after which we simulated AEPs for different degrees of AN damage. Using a classification technique, we determined the recorded AEP metric that best predicted the simulated individualized cochlear synaptopathy profiles. We cross-validated our method using the data set at hand, but also applied the trained classifier to recorded AEPs from a new cohort to illustrate the generalizability of the method.

Aging, noise exposure, and ototoxic medications lead to cochlear synapse loss in animal models. As cochlear function is highly conserved across mammalian species, synaptopathy likely occurs in humans as well. Synaptopathy is predicted to result in perceptual deficits including tinnitus, hyperacusis, and difficulty understanding speechin-noise. The lack of a method for diagnosing synaptopathy in living humans hinders studies designed to determine if noise-induced synaptopathy occurs in humans, identify the perceptual consequences of synaptopathy, or test potential drug treatments. Several physiological measures are sensitive to synaptopathy in animal models including auditory brainstem response (ABR) wave I amplitude. However, it is unclear how to translate these measures to synaptopathy diagnosis in humans. This work demonstrates how a human computational model of the auditory periphery, which can predict ABR waveforms and distortion product otoacoustic emissions (DPOAEs), can be used to predict synaptic loss in individual human participants based on their measured DPOAE levels and ABR wave I amplitudes. Lower predicted synapse numbers were associated with advancing age, higher noise exposure history, increased likelihood of tinnitus, and poorer speech-in-noise perception. These findings demonstrate the utility of this modeling approach in predicting synapse counts from physiological data in individual human subjects.

AbstractThe envelope following response (EFR) has been proposed as a non-invasive marker of synaptopathy in animal models. However, its amplitude is affected by the spread of basilar-membrane excitation and other coexisting sensorineural hearing deficits. This study aims to (i) improve frequency specificity of the EFR by introducing a derived-band EFR (DBEFR) technique and (ii) investigate the effect of lifetime noise exposure, age and outer-hair-cell (OHC) damage on DBEFR magnitudes. Additionally, we adopt a modelling approach to validate the frequency-specificity of the DBEFR and test how different aspects of sensorineural hearing loss affect peripheral generators. The combined analysis of simulations and experimental data proposes that the DBEFRs extracted from the [2-6]-kHz frequency band is a sensitive and frequency-specific measure of synaptopathy in humans. Individual variability in DBEFR magnitudes among listeners with normal audiograms was explained by their self-reported amount of experienced lifetime noise-exposure and corresponded to amplitude variability predicted by synaptopathy. Older listeners consistently had reduced DBEFR magnitudes in comparison to young normal-hearing listeners, in correspondence to how age-induced synaptopathy affects EFRs and compromises temporal envelope encoding. Lastly, OHC damage was also seen to affect the DBEFR magnitude, hence this marker should be combined with a sensitive marker of OHC-damage to offer a differential diagnosis of synaptopathy in listeners with impaired audiograms.

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