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Conneconomics: The Economics of Dense, Large-Scale, High-Resolution Neural Connectomics

Adam H. Marblestone, Evan R. Daugharthy, Reza Kalhor, Ian D. Peikon, Justus M. Kebschull, Seth L. Shipman, Yuriy Mishchenko, Jehyuk Lee, David A. Dalrymple, Bradley M. Zamft, Konrad P. Kording, Edward S. Boyden, Anthony M. Zador, George M. Church
doi: https://doi.org/10.1101/001214
Adam H. Marblestone
1Biophysics Program, Harvard Univ., Boston, MA, USA
2Wyss Institute for Biologically Inspired Engineering at Harvard Univ., Boston, MA, USA
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Evan R. Daugharthy
2Wyss Institute for Biologically Inspired Engineering at Harvard Univ., Boston, MA, USA
3Dept. of Genetics, Harvard Medical School, Boston, MA, USA
4Dept. of Systems Biology, Harvard Medical School, Boston, MA, USA
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Reza Kalhor
2Wyss Institute for Biologically Inspired Engineering at Harvard Univ., Boston, MA, USA
3Dept. of Genetics, Harvard Medical School, Boston, MA, USA
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Ian D. Peikon
9Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
10Watson School of Biological Sciences, Cold Spring Harbor, NY, USA
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Justus M. Kebschull
9Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
10Watson School of Biological Sciences, Cold Spring Harbor, NY, USA
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Seth L. Shipman
2Wyss Institute for Biologically Inspired Engineering at Harvard Univ., Boston, MA, USA
3Dept. of Genetics, Harvard Medical School, Boston, MA, USA
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Yuriy Mishchenko
5Dept. of Engineering, Toros University, Mersin, Turkey
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Jehyuk Lee
2Wyss Institute for Biologically Inspired Engineering at Harvard Univ., Boston, MA, USA
3Dept. of Genetics, Harvard Medical School, Boston, MA, USA
4Dept. of Systems Biology, Harvard Medical School, Boston, MA, USA
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David A. Dalrymple
11Nemaload, San Francisco, CA, USA
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Bradley M. Zamft
3Dept. of Genetics, Harvard Medical School, Boston, MA, USA
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Konrad P. Kording
6Depts. of Physical Medicine and Rehabilitation and of Physiology, Northwestern Univ. Feinberg School of Medicine, Chicago, IL, USA
7Sensory Motor Performance Program, The Rehabilitation Institute of Chicago, Chicago, IL, USA
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Edward S. Boyden
8Depts. of Brain and Cognitive Sciences and of Biological Engineering, MIT, Cambridge, MA, USA
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Anthony M. Zador
9Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
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George M. Church
1Biophysics Program, Harvard Univ., Boston, MA, USA
2Wyss Institute for Biologically Inspired Engineering at Harvard Univ., Boston, MA, USA
3Dept. of Genetics, Harvard Medical School, Boston, MA, USA
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Abstract

We analyze the scaling and cost-performance characteristics of current and projected connectomics approaches, with reference to the potential implications of recent advances in diverse contributing fields. Three generalized strategies for dense connectivity mapping at the scale of whole mammalian brains are considered: electron microscopic axon tracing, optical imaging of combinatorial molecular markers at synapses, and bulk DNA sequencing of trans-synaptically exchanged nucleic acid barcode pairs. Due to advances in parallel-beam instrumentation, whole mouse brain electron microscopic image acquisition could cost less than $100 million, with total costs presently limited by image analysis to trace axons through large image stacks. It is difficult to estimate the overall cost-performance of electron microscopic approaches because image analysis costs could fall dramatically with algorithmic improvements or large-scale crowd-sourcing. Optical microscopy at 50–100 nm isotropic resolution could potentially read combinatorially multiplexed molecular information from individual synapses, which could indicate the identifies of the pre-synaptic and post-synaptic cells without relying on axon tracing. An optical approach to whole mouse brain connectomics may therefore be achievable for less than $10 million and could be enabled by emerging technologies to sequence nucleic acids in-situ in fixed tissue via fluorescent microscopy. Strategies relying on bulk DNA sequencing, which would extract the connectome without direct imaging of the tissue, could produce a whole mouse brain connectome for $100k–$1 million or a mouse cortical connectome for $10k–$100k. Anticipated further reductions in the cost of DNA sequencing could lead to a $1000 mouse cortical connectome.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted April 21, 2014.
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Conneconomics: The Economics of Dense, Large-Scale, High-Resolution Neural Connectomics
Adam H. Marblestone, Evan R. Daugharthy, Reza Kalhor, Ian D. Peikon, Justus M. Kebschull, Seth L. Shipman, Yuriy Mishchenko, Jehyuk Lee, David A. Dalrymple, Bradley M. Zamft, Konrad P. Kording, Edward S. Boyden, Anthony M. Zador, George M. Church
bioRxiv 001214; doi: https://doi.org/10.1101/001214
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Conneconomics: The Economics of Dense, Large-Scale, High-Resolution Neural Connectomics
Adam H. Marblestone, Evan R. Daugharthy, Reza Kalhor, Ian D. Peikon, Justus M. Kebschull, Seth L. Shipman, Yuriy Mishchenko, Jehyuk Lee, David A. Dalrymple, Bradley M. Zamft, Konrad P. Kording, Edward S. Boyden, Anthony M. Zador, George M. Church
bioRxiv 001214; doi: https://doi.org/10.1101/001214

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