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Title: Structural and functional diversity of densely reconstructed cells in the mouse visual system
Authors: Bae, J. Alexander
Advisors: Seung, H. Sebastian
Contributors: Electrical Engineering Department
Keywords: Connectomics
Deep learning
Electron microscopy
Two-photon imaging
Subjects: Neurosciences
Electrical engineering
Computer science
Issue Date: 2022
Publisher: Princeton, NJ : Princeton University
Abstract: Brain circuit is composed of a number of components, neurons, where each component makes thousands of synaptic connections. To understand the brain, we need to consider not only the complete map of the components but also the functional characteristics of the components. 3D electron microscopy (EM) after two-photon calcium imaging has become a powerful approach to acquire structural and functional information of individual neurons on the same population of neurons. Due to a significant progress in image analysis pipeline for dense reconstruction of EM volumes, it is now feasible to study detailed morphology and connectivity of all cells in a given volume, which can be scaled up to near cubic millimeter volume. Many of the manual steps in the pipeline had to be automated for the scale-up, including the defect detection in EM images. First, we analyze anatomical and functional information of mouse retinal ganglion cells, which are the output neurons of the retina sending information to the cortex. We suggest structural organization of dendrites of ganglion cell types in the inner plexiform layer and varying functional properties of different types. Then, we move on to the primary visual cortex and describe how the connectivity relates to the trial-to-trial variability in visual function of layer 2/3 pyramidal cells. Lastly, we expand the analysis to a near cubic millimeter volume to understand the complete connectivity of individual neurons. Moreover, we propose how we can relate structure with function for neurons with rather complete morphology and connectivity, which could serve as building blocks for understanding the visual system.
Alternate format: The Mudd Manuscript Library retains one bound copy of each dissertation. Search for these copies in the library's main catalog:
Type of Material: Academic dissertations (Ph.D.)
Language: en
Appears in Collections:Electrical Engineering

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