ACTIVE AND NONLINEAR MODELS FOR COCHLEAR MECHANICS

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In order to better understand the hearing process, numerous efforts in cochlear modeling and physiological measurement have been undertaken. Understanding the process of normal auditory function holds the significant promise of assisting in the determination of the causes of hearing loss and tinnitus. Understanding the morphology and function of each component can lead the way to the development of better cochlear prostheses and diagnostic processes for noninvasive determination of disease. Biologically inspired designs for speech recognition and signal processing of non--auditory systems are also possible and could have a significant impact for applications other than hearing. Current research in cochlear mechanics is focussed on determining the source of the enhanced filtering and nonlinear compression seen in in vivo measurements. The hypothesis that an active amplification process is the source of the enhanced filtering has been studied widely since first proposed in 1948. In this grant a comprehensive, efficient numerical strategy for nonlinear and active macroscopic cochlear mechanics is proposed. Through this capability, a virtual laboratory for model testing will be developed capable of incorporating the most general nonlinear models for activity and geometric nonuniformity. Using a hybrid analytic and numeric approach the micromechanics of the Organ of Corti, especially the outer hair cells and their connecting structures, will be included in the global response modeling. These predictions will be compared to in vivo data obtained from physiological experiments. Experimental validation is a central focus of this modeling effort. Close ties to the physiological measurements is important to validate modeling parameters, most importantly the relation of the hypothesized transductions models to the endocochlear potential (or current). Controlled experiments will be used to both identify transducer model parameters (e.g., gains) and to validate/invalidate the hypothesis.