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Detecting Cochlear Synaptopathy Through Curvature Quantification of the Auditory Brainstem Response

Jianxin Bao,Segun Light Jegede,John W Hawks, Bethany Dade,Qiang Guan, Samantha Middaugh,Ziyu Qiu, Anna Levina,Tsung-Heng Tsai

FRONTIERS IN CELLULAR NEUROSCIENCE(2022)

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Abstract
The sound-evoked electrical compound potential known as auditory brainstem response (ABR) represents the firing of a heterogenous population of auditory neurons in response to sound stimuli, and is often used for clinical diagnosis based on wave amplitude and latency. However, recent ABR applications to detect human cochlear synaptopathy have led to inconsistent results, mainly due to the high variability of ABR wave-1 amplitude. Here, rather than focusing on the amplitude of ABR wave 1, we evaluated the use of ABR wave curvature to detect cochlear synaptic loss. We first compared four curvature quantification methods using simulated ABR waves, and identified that the cubic spline method using five data points produced the most accurate quantification. We next evaluated this quantification method with ABR data from an established mouse model with cochlear synaptopathy. The data clearly demonstrated that curvature measurement is more sensitive and consistent in identifying cochlear synaptic loss in mice compared to the amplitude and latency measurements. We further tested this curvature method in a different mouse model presenting with otitis media. The change in curvature profile due to middle ear infection in otitis media is different from the profile of mice with cochlear synaptopathy. Thus, our study suggests that curvature quantification can be used to address the current ABR variability issue, and may lead to additional applications in the clinic diagnosis of hearing disorders.
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Key words
cochlear synaptopathy, hidden hearing loss, noise-induced hearing loss, otitis media, Down syndrome
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