Fluid flow stimulates the hair bundles (HB) of the inner hair cells (IHC) of the cochlea opening the mechano- electric transducer (MET) channels of the IHCs. The resulting current depolarizes the cell body inducing neurotransmitter release and, ultimately, auditory nerve stimulation. The active machinery of the cochlea, driven by motility of outer hair cells (OHC), both tunes the microfluidic excitation of the IHC HBs and provides for nonlinear compression. However, the relative influence of OHC somatic and HB motility on this final fluidic forcing in the cochlea has yet to be conclusively determined. Further, the manner in which the IHC HBs are physically excited, whether by the influence of shear motion of the fluid or by a pressure difference induced pulsatile flow has yet to be determined.
The specific aims of this grant are to develop mathematical models of these phenomenon and rigorously test these hypotheses via comparison to existing experiments and work with our collaborators to devise feasible new experiments to test our predictions. In addition to predicting the response of the cochlea, we emphasize the importance of determine the noise present in the system when no stimulus is present; a computation that sets the lowest sound that can be sensed (as the signal must exceed the noise) ? another test of the models. The overarching goal of this research is to develop a complete fluid-mechanical-electrical model that describes the response of the cochlea to both external acoustic and internal electrical stimulation. If successful, this model will enhance our understanding of failure mechanisms in the cochlea, answering important questions as to the morphological elements of the cochlea that fail and why. Such understanding will improve noninvasive diagnosis of hearing as abnormalities in the response can be linked to specific pathologies. Further, as our model can predict the interaction of electrical and acoustic amplification. Finally, having an understanding of how the cochlea process sound over the entire spectrum will help us to understand how important classes of signals are processed in the cochlea (such as speech and music) and such understanding can lead to better speech processing algorithms or cochlear implant electrical stimulation approaches.
We seek to understand the active processes that are responsible for normal hearing by building mathematical models simulating the behavior of the cochlea, the transducer of the hearing system. By understanding the cochlea well enough to model it, we hope to predict how the cochlea might fail, say in response to loud sound or age, and guide the development of protective approaches or enhanced prosthetics. In addition, a predictive mathematical model will enable the development of new noninvasive tests to better interrogate the health of one's hearing and may enable better speech recognition software or cochlear implant neural stimulation algorithms to be devised.
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