Characterizing cochlear hearing impairment using advanced electrophysiological methods

The healthy auditory system is able to enable successful communication in complex acoustical scenarios with high levels of background noise. Such everyday life communication, also in more quiet acoustic situations, occurs at supra-threshold sound levels. However, the gold-standard current diagnostic method (i.e., pure-tone audiometry) assesses hearing thresholds; that is, the minimum intensity of sound that a given patient can perceive at a particular frequency of interest. The patient's individual audiogram defines whether he or she is considered as being a normal-hearing or a hearing-impaired listener. Legislation regarding sound exposure (e.g., work health) depends on this diagnostic test, having consequently a huge social impact. It is broadly accepted among the hearing scientific community that the evaluation of hearing thresholds does not fully characterize damage in the peripheral hearing system. For instance, invasive non-human animal physiological studies have shown that pure-tone audiometry is not much sensitive to damage in auditory nerve cell bodies, auditory nerve fiber synapses and inner hair cells; but it indicated well outer hair cell damage. It is thought then, that novel diagnostic methods capable of detecting all the tiny dysfunctions that today remain hidden are needed. Continuing with the work started during my PhD, I intend to use electrophysiological methods in human listeners, but also in non-human mammals in collaboration with other animal physiology labs, to study supra-threshold hearing processing. Similar electrophysiological studies performed in parallel in different species can be complemented with more invasive physiological measurements in animal models and behavioral experiments in human listeners. Computational modeling can be used to assist on the analysis of the electrophysiological results, and to relate the findings in different species. As a starting project, a mouse version of a currently available phenomenological computational model of the auditory nerve is already under execution.


Gerard Encina-Llamas
DTU Health Tech
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