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A visual motion detection circuit suggested by Drosophila connectomics

Author

Listed:
  • Shin-ya Takemura

    (Janelia Farm Research Campus, HHMI)

  • Arjun Bharioke

    (Janelia Farm Research Campus, HHMI)

  • Zhiyuan Lu

    (Janelia Farm Research Campus, HHMI
    Dalhousie University, Halifax, Nova Scotia B3H 4R2, Canada)

  • Aljoscha Nern

    (Janelia Farm Research Campus, HHMI)

  • Shiv Vitaladevuni

    (Janelia Farm Research Campus, HHMI)

  • Patricia K. Rivlin

    (Janelia Farm Research Campus, HHMI)

  • William T. Katz

    (Janelia Farm Research Campus, HHMI)

  • Donald J. Olbris

    (Janelia Farm Research Campus, HHMI)

  • Stephen M. Plaza

    (Janelia Farm Research Campus, HHMI)

  • Philip Winston

    (Janelia Farm Research Campus, HHMI)

  • Ting Zhao

    (Janelia Farm Research Campus, HHMI)

  • Jane Anne Horne

    (Dalhousie University, Halifax, Nova Scotia B3H 4R2, Canada)

  • Richard D. Fetter

    (Janelia Farm Research Campus, HHMI)

  • Satoko Takemura

    (Janelia Farm Research Campus, HHMI)

  • Katerina Blazek

    (Janelia Farm Research Campus, HHMI)

  • Lei-Ann Chang

    (Janelia Farm Research Campus, HHMI)

  • Omotara Ogundeyi

    (Janelia Farm Research Campus, HHMI)

  • Mathew A. Saunders

    (Janelia Farm Research Campus, HHMI)

  • Victor Shapiro

    (Janelia Farm Research Campus, HHMI)

  • Christopher Sigmund

    (Janelia Farm Research Campus, HHMI)

  • Gerald M. Rubin

    (Janelia Farm Research Campus, HHMI)

  • Louis K. Scheffer

    (Janelia Farm Research Campus, HHMI)

  • Ian A. Meinertzhagen

    (Janelia Farm Research Campus, HHMI
    Dalhousie University, Halifax, Nova Scotia B3H 4R2, Canada)

  • Dmitri B. Chklovskii

    (Janelia Farm Research Campus, HHMI)

Abstract

Animal behaviour arises from computations in neuronal circuits, but our understanding of these computations has been frustrated by the lack of detailed synaptic connection maps, or connectomes. For example, despite intensive investigations over half a century, the neuronal implementation of local motion detection in the insect visual system remains elusive. Here we develop a semi-automated pipeline using electron microscopy to reconstruct a connectome, containing 379 neurons and 8,637 chemical synaptic contacts, within the Drosophila optic medulla. By matching reconstructed neurons to examples from light microscopy, we assigned neurons to cell types and assembled a connectome of the repeating module of the medulla. Within this module, we identified cell types constituting a motion detection circuit, and showed that the connections onto individual motion-sensitive neurons in this circuit were consistent with their direction selectivity. Our results identify cellular targets for future functional investigations, and demonstrate that connectomes can provide key insights into neuronal computations.

Suggested Citation

  • Shin-ya Takemura & Arjun Bharioke & Zhiyuan Lu & Aljoscha Nern & Shiv Vitaladevuni & Patricia K. Rivlin & William T. Katz & Donald J. Olbris & Stephen M. Plaza & Philip Winston & Ting Zhao & Jane Anne, 2013. "A visual motion detection circuit suggested by Drosophila connectomics," Nature, Nature, vol. 500(7461), pages 175-181, August.
  • Handle: RePEc:nat:nature:v:500:y:2013:i:7461:d:10.1038_nature12450
    DOI: 10.1038/nature12450
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    Cited by:

    1. Shang, Ke-ke & Small, Michael & Yan, Wei-sheng, 2017. "Link direction for link prediction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 767-776.
    2. Toufiq Parag & Anirban Chakraborty & Stephen Plaza & Louis Scheffer, 2015. "A Context-Aware Delayed Agglomeration Framework for Electron Microscopy Segmentation," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-19, May.
    3. Jacqueline Cornean & Sebastian Molina-Obando & Burak Gür & Annika Bast & Giordano Ramos-Traslosheros & Jonas Chojetzki & Lena Lörsch & Maria Ioannidou & Rachita Taneja & Christopher Schnaitmann & Mari, 2024. "Heterogeneity of synaptic connectivity in the fly visual system," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    4. Antoine Allard & M Ángeles Serrano, 2020. "Navigable maps of structural brain networks across species," PLOS Computational Biology, Public Library of Science, vol. 16(2), pages 1-20, February.
    5. Kit D. Longden & Edward M. Rogers & Aljoscha Nern & Heather Dionne & Michael B. Reiser, 2023. "Different spectral sensitivities of ON- and OFF-motion pathways enhance the detection of approaching color objects in Drosophila," Nature Communications, Nature, vol. 14(1), pages 1-22, December.
    6. Saha, Papri & Sarkar, Debasish, 2022. "Allometric scaling of von Neumann entropy in animal connectomes and its evolutionary aspect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 600(C).
    7. Burak Gür & Luisa Ramirez & Jacqueline Cornean & Freya Thurn & Sebastian Molina-Obando & Giordano Ramos-Traslosheros & Marion Silies, 2024. "Neural pathways and computations that achieve stable contrast processing tuned to natural scenes," Nature Communications, Nature, vol. 15(1), pages 1-18, December.
    8. Daniel Soudry & Suraj Keshri & Patrick Stinson & Min-hwan Oh & Garud Iyengar & Liam Paninski, 2015. "Efficient "Shotgun" Inference of Neural Connectivity from Highly Sub-sampled Activity Data," PLOS Computational Biology, Public Library of Science, vol. 11(10), pages 1-30, October.

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