Thesis Proposal: Honghua Guan
Jul 6 @ 12:30 pm
Thesis Proposal: Honghua Guan

Note: This is a virtual presentation. Here is the link for where the presentation will be taking place.

Title: High-throughput Optical Explorer in Freely-behaving Rodents

Abstract: One critical goal for neuroscience is to explore the mechanisms underlying neuronal information processing. A suitable brain imaging tool is of great significance to be capable of recording clear neuronal signals over prolonged periods. Among different imaging modalities, multiphoton microscopy becomes the choice for in vivo brain applications owing to its subcellular resolution, optical sectioning and deep penetration. The current experimental routine, however, requires head-fixation of animals during data acquisition. This configuration will inevitably introduce unwanted stress and limit many behavior studies such as social interaction. The scanning two-photon fiberscope is a promising technical direction to bridge this gap. Benefiting from its ultra-compact design and light-weight, it is an ideal optical brain imaging modality to assess dynamic neuronal activities in freely-behaving rodents with subcellular resolution. One significant challenge with the compact scanning two-photon fiberscope is its suboptimal imaging throughput due to the limited choices of miniature optomechanical components.

In this project, we present a compact multicolor two-photon fiberscope platform. We achieve three-wavelength excitation by synchronizing the pulse trains from a femtosecond OPO and its pump. The imaging results demonstrate that we can excite several different fluorescent proteins simultaneously with an optimal excitation efficiency. In addition, we propose a deep neural network (DNN) based solution that significantly improves the imaging frame rate with minimal loss in image quality. This innovation enables 10-fold speed enhancement for the scanning two-photon fiberscope, making it feasible to perform video-rate (26 fps) two-photon imaging in freely-moving mice with excellent imaging resolution and SNR that were previously not possible.

Committee Members

  • Xingde Li, Department of Biomedical Engineering
  • Mark Foster, Department of Electrical and Computer Engineering
  • Jing U. Kang, Department of Electrical and Computer Engineering
  • Israel Gannot, Department of Electrical and Computer Engineering
  • Hui Lu, Department of Pharmacology and Physiology, George Washington University
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