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High-Resolution Synaptic Connectomics

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New Techniques in Systems Neuroscience

Part of the book series: Biological and Medical Physics, Biomedical Engineering ((BIOMEDICAL))

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Abstract

High-speed, high-resolution connectomics enables unambiguous mapping of synapses, gap junctions, adherens junctions, and other forms of adjacency among neurons in complex neural systems such as brain and retina. This chapter reviews the motivations for generating complete network architectures; the technologies available for large-scale network acquisition, visualization, and analysis; the fusion of molecular markers with a high-resolution ultrastructure; new networks and organelles discovered by ultrastructural connectomics; and new technological advances needed to expand the applications of connectomics.

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Acknowledgments

We thank the National Institutes of Health (EY02576, EY015128, and EY014800), National Science Foundation (0941717), the Thome Foundation, and Research to Prevent Blindness for support. We also thank Shoeb Mohammed for software development, and Hope Morrison, John Vo Hoang, and Noah Nelson for annotation.

Author information

Authors and Affiliations

  1. Department of Ophthalmology, University of Utah School of Medicine, 84132, Salt Lake City, UT, USA

    Robert E. Marc, Bryan W. Jones, Crystal Sigulinsky, James R. Anderson & J. Scott Lauritzen

Authors
  1. Robert E. Marc
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  2. Bryan W. Jones
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  3. Crystal Sigulinsky
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  4. James R. Anderson
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  5. J. Scott Lauritzen
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Corresponding author

Correspondence to Robert E. Marc .

Editor information

Editors and Affiliations

  1. Dept. Of Neurobiology and Anatomy, University of Utah, Salt Lake City, Utah, USA

    Adam D. Douglass

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© 2015 Springer International Publishing Switzerland

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Marc, R., Jones, B., Sigulinsky, C., Anderson, J., Lauritzen, J. (2015). High-Resolution Synaptic Connectomics. In: Douglass, A. (eds) New Techniques in Systems Neuroscience. Biological and Medical Physics, Biomedical Engineering. Springer, Cham. https://doi.org/10.1007/978-3-319-12913-6_1

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