The big data challenges of connectomics
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Shavit_The big.pdf
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Author(s)
Pfister, Hanspeter
Lichtman, Jeff W.
Shavit, Nir N.
Date Issued
October 2014
Journal
Nature Neuroscience
Publisher
Nature Publishing Group
Citation
Lichtman, Jeff W, Hanspeter Pfister, and Nir Shavit. “The Big Data Challenges of Connectomics.” Nat Neurosci 17, no. 11 (October 28, 2014): 1448–1454.
Version
Author's final manuscript
Abstract
The structure of the nervous system is extraordinarily complicated because individual neurons are interconnected to hundreds or even thousands of other cells in networks that can extend over large volumes. Mapping such networks at the level of synaptic connections, a field called connectomics, began in the 1970s with a the study of the small nervous system of a worm and has recently garnered general interest thanks to technical and computational advances that automate the collection of electron-microscopy data and offer the possibility of mapping even large mammalian brains. However, modern connectomics produces 'big data', unprecedented quantities of digital information at unprecedented rates, and will require, as with genomics at the time, breakthrough algorithmic and computational solutions. Here we describe some of the key difficulties that may arise and provide suggestions for managing them.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
https://doi.org/10.1038/nn.3837
