Browsing by Subject "Large-scale"

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    Multi-contrast optical coherence tomography for brain imaging and mapping
    (2014-08) Wang, Hui
    Although our knowledge of neuronal function and regional activity has been tremendously enriched in the past decades, coordination of these neurons to form the complex behaviors has yet to be understood. The neuronal pathways (also named connectome) form the structural foundation of the dynamic circuits in the brain. The recent interests in connectome and brainwide database have imposed a pressing need for high-resolution imaging techniques that allows large coverage. This dissertation develops a novel multi-contrast optical coherence tomography (MC-OCT) technique for the application of brainwide imaging and architectural mapping in 3D at high spatiotemporal resolution, with an emphasis on the connective tracts. The image contrasts originate from intrinsic optical properties of the brain tissues in which light propagates, back-scatters, attenuates, and changes its polarization state. Due to a birefringence property of the myelin sheath, MC-OCT specially targets the white matter, with qualitative architecture and quantitative orientation maps produced. The fiber tracts with diameters of a few tens of micrometers are visualized and tracked in 3D. As a further advance, a serial optical coherence scanner (SOCS) integrating the MC-OCT and a Vibratome slicer is realized for large-scale brain imaging and mapping at high resolution. The 3D fiber architecture and fiber orientation in rat brain are reconstructed at a resolution of 15 x 15 x 5.5 µm3. SOCS enables systematic validations of diffusion magnetic resonance imaging (dMRI) at microscopic resolution. A cross-validation in a postmortem human medulla sample shows remarkably good agreement on fiber structures and orientations between the two techniques. In addition, SOCS resolves intricate fiber patterns that are not captured by the dMRI. Taken together, the serial MC-OCT technique has the potential to bridge cross-scale investigations for a hierarchical view of neuroanatomical connections, thus opening intriguing applications in brain mapping and neural disorders.