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Connectomic reconstruction of the inner plexiform layer in the mouse retina

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  • Moritz Helmstaedter

    (Max-Planck Institute for Medical Research, D-69120 Heidelberg, Germany
    Present addresses: Max-Planck Institute of Neurobiology, D-82152 Martinsried, Germany (M.H.); National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland 20892, USA (K.L.B.); Gatsby Computational Neuroscience Unit, London WC1N 3AR, UK (S.C.T.); Howard Hughes Medical Institute, Janelia Farm Research Campus, Ashburn, Virginia 20147, USA (V.J.).)

  • Kevin L. Briggman

    (Max-Planck Institute for Medical Research, D-69120 Heidelberg, Germany
    Present addresses: Max-Planck Institute of Neurobiology, D-82152 Martinsried, Germany (M.H.); National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland 20892, USA (K.L.B.); Gatsby Computational Neuroscience Unit, London WC1N 3AR, UK (S.C.T.); Howard Hughes Medical Institute, Janelia Farm Research Campus, Ashburn, Virginia 20147, USA (V.J.).)

  • Srinivas C. Turaga

    (Howard Hughes Medical Institute, Massachusetts Institute of Technology
    Present addresses: Max-Planck Institute of Neurobiology, D-82152 Martinsried, Germany (M.H.); National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland 20892, USA (K.L.B.); Gatsby Computational Neuroscience Unit, London WC1N 3AR, UK (S.C.T.); Howard Hughes Medical Institute, Janelia Farm Research Campus, Ashburn, Virginia 20147, USA (V.J.).)

  • Viren Jain

    (Howard Hughes Medical Institute, Massachusetts Institute of Technology
    Present addresses: Max-Planck Institute of Neurobiology, D-82152 Martinsried, Germany (M.H.); National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland 20892, USA (K.L.B.); Gatsby Computational Neuroscience Unit, London WC1N 3AR, UK (S.C.T.); Howard Hughes Medical Institute, Janelia Farm Research Campus, Ashburn, Virginia 20147, USA (V.J.).)

  • H. Sebastian Seung

    (Howard Hughes Medical Institute, Massachusetts Institute of Technology)

  • Winfried Denk

    (Max-Planck Institute for Medical Research, D-69120 Heidelberg, Germany)

Abstract

Comprehensive high-resolution structural maps are central to functional exploration and understanding in biology. For the nervous system, in which high resolution and large spatial extent are both needed, such maps are scarce as they challenge data acquisition and analysis capabilities. Here we present for the mouse inner plexiform layer—the main computational neuropil region in the mammalian retina—the dense reconstruction of 950 neurons and their mutual contacts. This was achieved by applying a combination of crowd-sourced manual annotation and machine-learning-based volume segmentation to serial block-face electron microscopy data. We characterize a new type of retinal bipolar interneuron and show that we can subdivide a known type based on connectivity. Circuit motifs that emerge from our data indicate a functional mechanism for a known cellular response in a ganglion cell that detects localized motion, and predict that another ganglion cell is motion sensitive.

Suggested Citation

  • Moritz Helmstaedter & Kevin L. Briggman & Srinivas C. Turaga & Viren Jain & H. Sebastian Seung & Winfried Denk, 2013. "Connectomic reconstruction of the inner plexiform layer in the mouse retina," Nature, Nature, vol. 500(7461), pages 168-174, August.
    • Handle: RePEc:nat:nature:v:500:y:2013:i:7461:d:10.1038_nature12346
    DOI: 10.1038/nature12346
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    Cited by:

    1. Zhe Li & Yi Wang & Kesheng Wang, 2020. "A data-driven method based on deep belief networks for backlash error prediction in machining centers," Journal of Intelligent Manufacturing, Springer, vol. 31(7), pages 1693-1705, October.
    2. Andrew Jo & Sercan Deniz & Suraj Cherian & Jian Xu & Daiki Futagi & Steven H. DeVries & Yongling Zhu, 2023. "Modular interneuron circuits control motion sensitivity in the mouse retina," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
    3. Stefano Recanatesi & Gabriel Koch Ocker & Michael A Buice & Eric Shea-Brown, 2019. "Dimensionality in recurrent spiking networks: Global trends in activity and local origins in connectivity," PLOS Computational Biology, Public Library of Science, vol. 15(7), pages 1-29, July.
    4. Ilya Belevich & Merja Joensuu & Darshan Kumar & Helena Vihinen & Eija Jokitalo, 2016. "Microscopy Image Browser: A Platform for Segmentation and Analysis of Multidimensional Datasets," PLOS Biology, Public Library of Science, vol. 14(1), pages 1-13, January.
    5. Chad P. Grabner & Daiki Futagi & Jun Shi & Vytas Bindokas & Katsunori Kitano & Eric A. Schwartz & Steven H. DeVries, 2023. "Mechanisms of simultaneous linear and nonlinear computations at the mammalian cone photoreceptor synapse," Nature Communications, Nature, vol. 14(1), pages 1-19, December.
    6. Alex D Herbert & Antony M Carr & Eva Hoffmann, 2014. "FindFoci: A Focus Detection Algorithm with Automated Parameter Training That Closely Matches Human Assignments, Reduces Human Inconsistencies and Increases Speed of Analysis," PLOS ONE, Public Library of Science, vol. 9(12), pages 1-33, December.
    7. 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.
    8. Karl Friedrichsen & Jen-Chun Hsiang & Chin-I Lin & Liam McCoy & Katia Valkova & Daniel Kerschensteiner & Josh L. Morgan, 2024. "Subcellular pathways through VGluT3-expressing mouse amacrine cells provide locally tuned object-motion-selective signals in the retina," Nature Communications, Nature, vol. 15(1), pages 1-19, December.
    9. Munir Husein & Il-Yop Chung, 2019. "Day-Ahead Solar Irradiance Forecasting for Microgrids Using a Long Short-Term Memory Recurrent Neural Network: A Deep Learning Approach," Energies, MDPI, vol. 12(10), pages 1-21, May.
    10. Adam Mani & Xinzhu Yang & Tiffany A. Zhao & Megan L. Leyrer & Daniel Schreck & David M. Berson, 2023. "A circuit suppressing retinal drive to the optokinetic system during fast image motion," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    11. David Swygart & Wan-Qing Yu & Shunsuke Takeuchi & Rachel O. L. Wong & Gregory W. Schwartz, 2024. "A presynaptic source drives differing levels of surround suppression in two mouse retinal ganglion cell types," Nature Communications, Nature, vol. 15(1), pages 1-20, December.
    12. Andrew Jo & Sercan Deniz & Jian Xu & Robert M. Duvoisin & Steven H. DeVries & Yongling Zhu, 2023. "A sign-inverted receptive field of inhibitory interneurons provides a pathway for ON-OFF interactions in the retina," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    13. Héctor Acarón Ledesma & Jennifer Ding & Swen Oosterboer & Xiaolin Huang & Qiang Chen & Sui Wang & Michael Z. Lin & Wei Wei, 2024. "Dendritic mGluR2 and perisomatic Kv3 signaling regulate dendritic computation of mouse starburst amacrine cells," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    14. Jen-Chun Hsiang & Ning Shen & Florentina Soto & Daniel Kerschensteiner, 2024. "Distributed feature representations of natural stimuli across parallel retinal pathways," Nature Communications, Nature, vol. 15(1), pages 1-20, December.

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