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.
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Support is gratefully acknowledged from the US National Institute of Mental Health Silvio Conte Center (1P50MH094271 to J.W.L.), the US National Institutes of Health (NS076467 to J.W.L. and 2R44MH088088-03 to H.P.), the National Science Foundation (OIA-1125087 to H.P., CCF-1217921 to N.S., CCF-1301926 to N.S., IIS-1447786 to N.S., and IIS-1447344 to H.P. and J.W.L.), a Department of Energy Advanced Scientific Computing Research grant (ER26116/DE-SC0008923 to N.S.), Nvidia (H.P.), Oracle (N.S.) and Intel (N.S.).
The authors declare no competing financial interests.
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Lichtman, J., Pfister, H. & Shavit, N. The big data challenges of connectomics. Nat Neurosci 17, 1448–1454 (2014). https://doi.org/10.1038/nn.3837
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