The big data challenges of connectomics

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. Access through

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CONTENT BEING VIEWED BY OTHERS SYCONN2: DENSE SYNAPTIC CONNECTIVITY INFERENCE FOR VOLUME ELECTRON MICROSCOPY Article Open access 24 October 2022 TOWARDS A BIOLOGICALLY ANNOTATED BRAIN

CONNECTOME Article 17 October 2023 BRAINTACO: AN EXPLORABLE MULTI-SCALE MULTI-MODAL BRAIN TRANSCRIPTOMIC AND CONNECTIVITY DATA RESOURCE Article Open access 14 June 2024 REFERENCES *

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& Brigmann, K.) (Academic Press, in the press). Download references ACKNOWLEDGEMENTS 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.). AUTHOR INFORMATION Author notes * Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge,

Massachusetts, USA. AUTHORS AND AFFILIATIONS * Department of Molecular and Cellular Biology, Harvard University, Cambridge, Massachusetts, USA Jeff W Lichtman * Center for Brain Science,

Harvard University, Cambridge, Massachusetts, USA Jeff W Lichtman & Hanspeter Pfister * School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, USA

Hanspeter Pfister * Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA Nir Shavit Authors * Jeff W Lichtman View

author publications You can also search for this author inPubMed Google Scholar * Hanspeter Pfister View author publications You can also search for this author inPubMed Google Scholar * Nir

Shavit View author publications You can also search for this author inPubMed Google Scholar CORRESPONDING AUTHOR Correspondence to Jeff W Lichtman. ETHICS DECLARATIONS COMPETING INTERESTS

The authors declare no competing financial interests. RIGHTS AND PERMISSIONS Reprints and permissions ABOUT THIS ARTICLE CITE THIS ARTICLE 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 Download citation * Received: 31 July 2014 * Accepted: 10 September 2014 * Published: 28

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