Hearing Health and Physiology Laboratory

 

​The Hearing Health and Physiology Laboratory studies why people complain of having hearing loss or difficulty hearing, especially conversations in noisy environments. We aim to understand pathologies and diseases of the auditory system and develop new clinical tools to diagnose these pathologies so that better treatment can be provided for people suffering from hearing loss.

We collaborate with the Audiology Signal Processing Laboratory and Communications Engineering Laboratory and depend on the Center for Perception and Communication in Children for support in conducting our experiments.

Our current study is trying to help people who feel they have difficulties hearing in noisy environments but may have “normal hearing" or mild hearing loss when diagnosed with standard hearing tests at the doctor's office or audiology clinic.

Participate in Our Research Studies

Do you have difficulty hearing or trouble understanding conversations in noisy backgrounds? AND/OR do you have normal hearing or mild hearing loss? Participate in a study to help understand hearing loss and develop new tests for hearing!

If you are interested in participating in our studies, please sign up here to join our list of research volunteers or contact Dr. Aryn Kamerer or a member of the research team at auditory.processing@boystown.org.

Sign up to join the Boys Town National Research Hospital database to receive information for studies from all departments.

For Clinicians and Scientists

The Hearing Health and Physiology Lab is interested in the development of clinical tools that differentiate pathologies of the cochlea and that characterize perceptual consequences of such damage. Electrophysiology is an effective, yet underutilized approach to diagnose cochlear pathology. The potential for expanding these tools for both research and clinical use is immense, however, more research must be done on linking pathology to physiology and physiology to perception.

A recent survey by Koerner, Papesh, & Gallun (2020) found over two-thirds of audiologists encounter at least one patient per month with reported communication difficulties despite having normal or near normal pure-tone thresholds and speech recognition scores, while a quarter of audiologists encountered said patients at least 4 times per month. These patients leave the clinic deflated; their concerns not validated. Only one in three leave their appointment satisfied with their diagnosis and only one in three are recommended hearing interventions. We are working on develop a short, sensitive, supplemental battery of measures for patients whose self-reported hearing loss cannot be accounted for by the standard clinical battery, and one that does not require training, excessive time, or special equipment.

Standard audiometry is a poor estimator of site-of-lesion along the auditory pathway. The standard clinical battery is not sensitive to cochlear pathologies such as outer hair cell loss at the extreme base of the cochlea (Hunter et al., 2020; Monson et al., 2019), inner hair cell dysfunction (Lobarinas et al., 2013; 2016), auditory nerve damage (Liberman et al., 2016); or auditory brainstem pathologies (Jerger & Jerger, 1974). Metrics derived from auditory evoked potentials (AEP) are excellent candidates to supplement audiometry in patients with complaints of hearing difficulty and normal thresholds (Bramhall et al., 2019; Le Prell, 2019; Suresh & Krishnan, 2020). Unfortunately, the method of extracting data from responses is through visual determination of peaks and troughs in the waveform. This task is time-consuming, requires training, and can be difficult in noisy data or when waves overlap in time. Modeling AEP morphology is a lesser-used approach but one that could provide more information than algorithms that mimic the visual-determination process or that merely detect the presence of a response (Elberling, 1979; Valderrama et al., 2014). The Hearing Health and Physiology Laboratory developed a model of short-latency AEPs that extracts more information than visual-determination, and does so instantaneously (Kamerer et al., 2020), and is currently being used by scientists in the Eaton-Peabody laboratories at Massachusetts Eye & Ear to analyze animal AEP data for hidden pathologies.