Evidence for independent peripheral and central age-related hearing impairment.

Deleterious age-related changes in the central auditory nervous system have been referred to as central age-related hearing impairment (ARHI) or central presbycusis. Central ARHI is often assumed to be the consequence of peripheral ARHI. However, it is possible that certain aspects of central ARHI are independent from peripheral ARHI. A confirmation of this possibility could lead to significant improvements in current rehabilitation practices. The major difficulty in addressing this issue arises from confounding factors, such as other age-related changes in both the cochlea and central non-auditory brain structures. Because gap detection is a common measure of central auditory temporal processing, and gap detection thresholds are less influenced by changes in other brain functions such as learning and memory, we investigated the potential relationship between age-related peripheral hearing loss (i.e., audiograms) and age-related changes in gap detection. Consistent with previous studies, a significant difference was found for gap detection thresholds between young and older adults. However, among older adults, no significant associations were observed between gap detection ability and several other independent variables including the pure tone audiogram average, the Wechsler Adult Intelligence Scale-Vocabulary score, gender, and age. Statistical analyses showed little or no contributions from these independent variables to gap detection thresholds. Thus, our data indicate that age-related decline in central temporal processing is largely independent of peripheral ARHI.

Detecting Cochlear Synaptopathy Through Curvature Quantification of the Auditory Brainstem Response.

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.