Thursday, April 3, 2025
4/3/2025
Understanding the physiological roles of MOC efferent pathways for hearing in noise - This proposal investigates the underlying mechanisms of the medial olivocochlear (MOC) efferent system, focusing on its role in anti-masking and the impact of hearing loss on its input and output pathways. To leverage the potential benefits of the MOC system in hearing aids, it is essential to study the specific neural mechanisms within the MOC system and how they are altered by hearing loss. The MOC system dynamically adjusts cochlear gain based on multiple input pathways, including two major inputs from the inferior colliculus (IC) and the cochlear nucleus (CN). While the CN input has been extensively studied, the IC input remains less explored. IC cells in the midbrain are sensitive to low-frequency fluctuations (modulations) in auditory-nerve (AN) responses, potentially conveying spectral information encoded within these fluctuations. Computational modeling from my PhD thesis showed that this distinct information provided by the IC input to the MOC system can explain auditory phenomena that cannot be fully accounted for by considering only the CN input. The complexity and lack of detailed physiological data on MOC inputs, particularly from higher-level projections such as the IC, underscore the need for innovative physiological methods and approaches. To address this issue, this proposal outlines three specific aims, each involving novel physiological methods to isolate and manipulate individual MOC pathways. The goal is to create a comprehensive dataset that significantly enhances our understanding of the MOC efferent pathways. In Aim 1, we will explore the role of the IC input to the MOC system by varying modulation frequency within a forward-masking paradigm, while simultaneously recording transient-evoked otoacoustic emissions (TEOAEs) and envelope following responses (EFRs) to track MOC-induced changes in cochlear gain and neural responses, respectively. This will provide a detailed evaluation of the MOC efferent system, focusing specifically on the role of the IC input. Aim 2 will investigate the relative role of the CN input to the MOC system by using a temporary threshold shift (TTS) noise exposure animal model of cochlear synaptopathy, which will isolate the wide-dynamic range CN pathway while leaving the IC input relatively unaffected. Finally, Aim 3 will examine the effects of sensorineural hearing loss (SNHL) on MOC output projections to the outer hair cells (OHCs) by measuring how neural coding is influenced with and without efferent electrical stimulation in both hearing-loss and normal-hearing animals. I have developed a computational model of the MOC efferent system that integrates both CN and IC inputs during my PhD, which guides the design and interpretation of our measurements. The proposed experiments will significantly advance our understanding of the MOC system’s role in listening in noise and the broader effects of SNHL. These findings will have implications for enhancing hearing-aid algorithms. The physiological training gained through these aims will synergize with my computational background to provide a strong foundation for my career as an independent researcher exploring translational issues related to listening in noise.
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