Refactoring the retina with connectomics

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Publication Type dissertation
School or College School of Medicine
Department Neurology
Author Lauritzen, James Scott
Title Refactoring the retina with connectomics
Date 2013-05
Description It is imperative to obtain a complete network graph of at least one representative retina if we are to fully understand vertebrate vision. Synaptic connectomics endeavors to construct such graphs. Though previously prevented by hardware and software limitations, the creation of customized viewing and analysis software, affordable data storage, and advances in electron imaging platform control now permit connectome assembly and analysis. The optimal strategy for building complete connectomes utilizes automated transmission electron imaging with 2 nm or better resolution, molecular tags for cell identification, open access data volumes for navigation, and annotation with open source tools to build three-dimensional cell libraries, complete network diagrams, and connectivity databases. In a few years, the first retinal connectome analyses reveal that many well-studied cells participate in much richer networks than expected. Collectively, these results impel a refactoring of the inner plexiform layer, while providing proof of concept for connectomics as a game-changing approach for a new era of scientific discovery.
Type Text
Publisher University of Utah
Subject MESH Retina; Connectome; Brain Mapping; Retinal Bipolar Cells; Retinal Neurons; Retinal Cone Photoreceptor Cells; Nerve Net; Microscopy, Electron, Scanning Transmission; Retinal Ganglion Cells; Synaptic Transmission; Neuronal Plasticity; Photoreceptor Cells, Vertebrate; Amacrine Cells; Mesopic Vision
Dissertation Institution University of Utah
Dissertation Name Doctor of Philosophy
Language eng
Relation is Version of Digital reproduction of Refactoring the Retina with Connectomics. Print version available at J. Willard Marriott Library Special Collections.
Rights Management Copyright © James Scott Lauritzen 2013
Format Medium application/pdf
Format Extent 18,191,201 bytes
Source Original in Marriott Library Special Collections.
ARK ark:/87278/s62r710s
Setname ir_etd
ID 197327
Reference URL https://collections.lib.utah.edu/ark:/87278/s62r710s
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