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  • Perspective
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Cellular-resolution connectomics: challenges of dense neural circuit reconstruction

Nature Methods volume 10, pages 501–507 (2013)Cite this article

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Neuronal networks are high-dimensional graphs that are packed into three-dimensional nervous tissue at extremely high density. Comprehensively mapping these networks is therefore a major challenge. Although recent developments in volume electron microscopy imaging have made data acquisition feasible for circuits comprising a few hundreds to a few thousands of neurons, data analysis is massively lagging behind. The aim of this Perspective is to summarize and quantify the challenges for data analysis in cellular-resolution connectomics and describe current solutions involving online crowd-sourcing and machine-learning approaches.

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Figure 1: Density of neuronal circuits and minimal resolution requirements.
Figure 2: Minimal circuit dimensions.
Figure 3: Volume electron microscopy techniques for cellular connectomics and their spatial resolution and scope.
Figure 4: Manual and automated reconstruction challenges in electron microscopy–based connectomics.
Figure 5: Imaging and analysis times illustrating the analysis gap in cellular connectomics.

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Acknowledgements

I am grateful to the members of my laboratory for many fruitful discussions, specifically to K.M. Boergens, Y. Buckley, F. Isensee, N. Marahori, A. Mohn and H. Wissler for help with generating figures, and E. Dow for discussions concerning game development. I thank M. Berning, K.M. Boergens, E. Dow and A. Schaefer for helpful comments on the manuscript.

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  1. Structure of Neocortical Circuits Group, Max Planck Institute of Neurobiology, Munich-Martinsried, Germany

    Moritz Helmstaedter

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Correspondence to Moritz Helmstaedter.

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Helmstaedter, M. Cellular-resolution connectomics: challenges of dense neural circuit reconstruction. Nat Methods 10, 501–507 (2013). https://doi.org/10.1038/nmeth.2476

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