Browsing by Subject "M-Mode"

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    Polarization-Maintaining Fiber-Based Optical Coherence Tomography on Functional Imaging in Dense Nerve
    (2016-08) Chan, Richard
    The technology and applications of optical coherence tomography (OCT) have been developed rapidly for structural and functional investigations of biological tissues. The use of light yields outstanding resolution and simultaneous measurements from a range of targeted locations without physical contact with tissue. The objective of this thesis was to investigate the feasibility of utilizing polarization-maintaining-fiber (PMF) based OCT to image the microstructure and functional (neural activity) of pike olfactory nerve. A dual-wavelength polarization-sensitive spectral-domain OCT system has been designed and constructed in house for depth-resolved optical recordings. The olfactory nerves dissected from pike were used with or without voltage-sensitive dye staining. M-mode and cross-sectional imaging have been performed to capture transient changes during neural activity. The OCT signals including optical path length variation of the nerve with respect to a reference surface (∆P), intensity change (∆I), and normalized intensity change (∆I/I ̂ ) were assessed for potential indications of neural activity. The results demonstrate that dynamic phase and intensity changes were detected during the compound action potential propagation, which is also recorded together with the OCT data. Software methods such as detrending and bulk motion correction were implemented to stabilize the ∆P response as well as the intensity response. The transient ∆P response and backscattered light intensity were detected by OCT imaging with depth-localization and were consistent and highly correlated to transient neural activity. Monitoring the function during fast and continues cross-sectional imaging revealed ∆P response during action potential propagation, but not before and during the propagation. Thus, the results clearly demonstrated that the PMF OCT system and the signal processing pipeline are capable of acquiring and constructing 2-D cross-sectional images of dynamic neural activity.