Speaker
Description
Auditory Neuropathy Spectrum Disorder (ANSD) is a hearing impairment characterized by abnormal or absent auditory brainstem responses and difficulty understanding speech, especially in noise, while maintaining normal outer hair cell function. Despite this definition, clinical presentation of ANSD is highly variable in practice. Additionally, ANSD has a wide range of underlying pathologies, making it difficult to diagnose without performing electrophysiology. ANSD listeners have worse performance than normal hearing (NH) listeners on psychophysical tasks that require precise temporal resolution. Therefore, using a model featuring physiologically accurate impairments, a test battery of tasks can be identified that distinguishes ANSD from normal hearing, as well as specific ANSD pathologies from each other.Using the Bruce et al. (2018) auditory nerve (AN) model, we proposed that perturbations of vesicle release dynamics are sufficient to accurately portray ANSD resulting from synaptic disorders. Model performance was quantified for modulation detection using a noise carrier, by calculating thresholds over multiple modulation frequencies.Modulation detection thresholds were significantly degraded in the ANSD model compared to NH, mirroring the trend seen in human subjects. Furthermore, threshold details differ between perturbation types, demonstrating that ANSD subtypes with different mechanisms can be distinguished even within the same psychophysical paradigm. Finally, we show that overall thresholds and impact of ANSD perturbation depend on model parameters like spontaneous rate, suggesting that certain types of AN fibers may be resistant to ANSD impairment.These results not only demonstrate the feasibility of modeling ANSD mechanisms and their perceptual consequences, but also suggest that similar methods can be applied to diagnose human patients in the future.