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Rich cell-type-specific network topology in neocortical microcircuitry

Nature Neuroscience volume 20, pages 10041013 (2017) | Download Citation

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Abstract

Uncovering structural regularities and architectural topologies of cortical circuitry is vital for understanding neural computations. Recently, an experimentally constrained algorithm generated a dense network reconstruction of a 0.3-mm3 volume from juvenile rat somatosensory neocortex, comprising 31,000 cells and 36 million synapses. Using this reconstruction, we found a small-world topology with an average of 2.5 synapses separating any two cells and multiple cell-type-specific wiring features. Amounts of excitatory and inhibitory innervations varied across cells, yet pyramidal neurons maintained relatively constant excitation/inhibition ratios. The circuit contained highly connected hub neurons belonging to a small subset of cell types and forming an interconnected cell-type-specific rich club. Certain three-neuron motifs were overrepresented, matching recent experimental results. Cell-type-specific network properties were even more striking when synaptic strength and sign were considered in generating a functional topology. Our systematic approach enables interpretation of microconnectomics 'big data' and provides several experimentally testable predictions.

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Change history

  • 14 June 2017

    In the version of this article initially published online, the number of neurons for layer 6 was given in Figure 1a as 1,2715 instead of 12,715, the single asterisks in the left panels of Figure 4b and Figure 4c should have been double asterisks, and "left" and "right" were reversed in the legend to Figure 4c. The errors have been corrected in the print, PDF and HTML versions of this article.

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Acknowledgements

We thank the members of the Segev Lab for helpful discussions related to this project. We also thank I. Nadav for the image processing. This work was supported by the Gatsby Charitable Foundation and the EPFL-Hebrew University Collaborative Grant, the EPFL support to the Laboratory of Neural Microcircuitry (LNMC), the ETH Domain for the Blue Brain Project (BBP), the Human Brain Project through the European Union Seventh Framework Program (FP7/2007-2013) under grant agreement no. 604102 (HBP) and from the European Union H2020 FET program through grant agreement no. 720270 (HBP SGA1), the Brain Science grant of the Sachs Family and by the ISF Centers of Excellence grants 1789/11 and 2180/15.

Author information

Affiliations

  1. Edmond and Lily Safra Center for Brain Sciences, The Hebrew University, Jerusalem, Israel.

    • Eyal Gal
    • , Michael London
    •  & Idan Segev
  2. Department of Neurobiology, The Hebrew University, Jerusalem, Israel.

    • Eyal Gal
    • , Michael London
    •  & Idan Segev
  3. The Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel.

    • Amir Globerson
  4. Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel.

    • Amir Globerson
  5. Blue Brain Project, École Polytechnique Fédérale de Lausanne (EPFL) Biotech Campus, Geneva, Switzerland.

    • Srikanth Ramaswamy
    • , Michael W Reimann
    • , Eilif Muller
    •  & Henry Markram

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Contributions

E.G. and I.S. conceived the study and wrote the manuscript. E.G. carried out the analysis. M.L. helped in developing the functional small-world analysis. A.G. and M.L. participated in discussions. S.R., M.W.R., E.M. and H.M. developed the in silico microcircuit and provided the respective data.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Eyal Gal or Idan Segev.

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DOI

https://doi.org/10.1038/nn.4576