Cochlear morphology and sound-induced motion of the apical mammalian inner ear
Author(s)
Page, Scott Lawrence![Thumbnail](/bitstream/handle/1721.1/103740/953525187-MIT.pdf.jpg?sequence=3&isAllowed=y)
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Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Advisor
Dennis M. Freeman.
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Extraordinary sensitivity, frequency selectivity, and dynamic range are hallmarks of mammalian hearing. While a variety of cellular and molecular mechanisms are known to be critical to these properties, how the cellular and molecular mechanisms interact to generate the remarkable properties remains unclear. Direct observations of these interacts has proved to be difficult, in large part because the inner ear is fragile and has been difficult to probe with conventional measurement technologies. We have developed an Optical Coherence Tomography (OCT) system to use light to probe both the structure and mechanical responses of the inner ear to sound stimulation. The technique takes advantage of the interference of low coherence sources of light to detect even weakly scattering tissues in the inner ear. By sensing Doppler shifts of light scattered off moving structures in the inner ear, the OCT system can also detect sound-induced motions of cochlear structures with sub-nanometer resolution. This thesis demonstrates the use of the OCT system to study the structure of the inner ears of mice, gerbils, and guinea pigs, as well as the acoustic response of the apical turn of in vitro and in vivo apical mammalian cochleae to low frequency (100 to 1000 Hz) sounds - frequencies that are critical to our understanding of speech.
Description
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016. Cataloged from PDF version of thesis. Includes bibliographical references (pages 103-112).
Date issued
2016Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer SciencePublisher
Massachusetts Institute of Technology
Keywords
Electrical Engineering and Computer Science.