Title |
Refactoring the retina with connectomics |
Publication Type |
dissertation |
School or College |
School of Medicine |
Department |
Neurology |
Author |
Lauritzen, James Scott |
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 |
application/pdf |
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 |