Subjects

Abstract

How does the mammalian retina detect motion? This classic problem in visual neuroscience has remained unsolved for 50 years. In search of clues, here we reconstruct Off-type starburst amacrine cells (SACs) and bipolar cells (BCs) in serial electron microscopic images with help from EyeWire, an online community of ‘citizen neuroscientists’. On the basis of quantitative analyses of contact area and branch depth in the retina, we find evidence that one BC type prefers to wire with a SAC dendrite near the SAC soma, whereas another BC type prefers to wire far from the soma. The near type is known to lag the far type in time of visual response. A mathematical model shows how such ‘space–time wiring specificity’ could endow SAC dendrites with receptive fields that are oriented in space–time and therefore respond selectively to stimuli that move in the outward direction from the soma.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

References

  1. 1.

    & Seeing things in motion: models, circuits, and mechanisms. Neuron 71, 974–994 (2011)

  2. 2.

    , & Direction selectivity in the retina: symmetry and asymmetry in structure and function. Nature Rev. Neurosci. 13, 194–208 (2012)

  3. 3.

    , & Directionally selective calcium signals in dendrites of starburst amacrine cells. Nature 418, 845–852 (2002)

  4. 4.

    , , & A dendrite-autonomous mechanism for direction selectivity in retinal starburst amacrine cells. PLoS Biol. 5, e185 (2007)

  5. 5.

    et al. The first stage of cardinal direction selectivity is localized to the dendrites of retinal ganglion cells. Neuron 79, 1078–1085 (2013)

  6. 6.

    , , & Cone contacts, mosaics, and territories of bipolar cells in the mouse retina. J. Neurosci. 29, 106–117 (2009)

  7. 7.

    , , & Spikes in mammalian bipolar cells support temporal layering of the inner retina. Curr. Biol. 23, 48–52 (2013)

  8. 8.

    , , & Two-photon imaging of nonlinear glutamate release dynamics at bipolar cell synapses in the mouse retina. J. Neurosci. 33, 10972–10985 (2013)

  9. 9.

    , & Wiring specificity in the direction-selectivity circuit of the retina. Nature 471, 183–188 (2011)

  10. 10.

    et al. Galaxy Zoo: morphologies derived from visual inspection of galaxies from the Sloan Digital Sky Survey. Mon. Not. R. Astron. Soc. 389, 1179–1189 (2008)

  11. 11.

    et al. Predicting protein structures with a multiplayer online game. Nature 466, 756–760 (2010)

  12. 12.

    Reconstruct: a free editor for serial section microscopy. J. Microsc. 218, 52–61 (2005)

  13. 13.

    & Labeling images with a computer game. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems 319–326 (ACM, 2004)

  14. 14.

    et al. Connectomic reconstruction of the inner plexiform layer in the mouse retina. Nature 500, 168–174 (2013)

  15. 15.

    Synaptic organization of starburst amacrine cells in rabbit retina: analysis of serial thin sections by electron microscopy and graphic reconstruction. J. Comp. Neurol. 309, 40–70 (1991)

  16. 16.

    & Refractoriness and neural precision. J. Neurosci. 18, 2200–2211 (1998)

  17. 17.

    & Fast and slow contrast adaptation in retinal circuitry. Neuron 36, 909–919 (2002)

  18. 18.

    & Model of human visual-motion sensing. J. Opt. Soc. Am. A 2, 322–341 (1985)

  19. 19.

    & Spatiotemporal energy models for the perception of motion. J. Opt. Soc. Am. A 2, 284–299 (1985)

  20. 20.

    in Sensory Communication (ed. ) 303–317 (MIT Press, 1961)

  21. 21.

    & The mechanism of directionally selective units in rabbit’s retina. J. Physiol. (Lond.) 178, 477–504 (1965)

  22. 22.

    , & Adaptation of response transients in fly motion vision. II: model studies. Vision Res. 43, 1311–1324 (2003)

  23. 23.

    , & Continuous vesicle cycling in the synaptic terminal of retinal bipolar cells. Neuron 17, 957–967 (1996)

  24. 24.

    , & Direction selectivity in a model of the starburst amacrine cell. Vis. Neurosci. 21, 611–625 (2004)

  25. 25.

    & in Single Neuron Computation (eds , & ) Ch. 13 347–76 (Academic San Diego, 1992)

  26. 26.

    , , & Cation–chloride cotransporters mediate neural computation in the retina. Proc. Natl Acad. Sci. USA 100, 16047–16052 (2003)

  27. 27.

    & Symmetric interactions within a homogeneous starburst cell network can lead to robust asymmetries in dendrites of starburst amacrine cells. J. Neurophysiol. 96, 471–477 (2006)

  28. 28.

    & The synaptic mechanism of direction selectivity in distal processes of starburst amacrine cells. Neuron 51, 787–799 (2006)

  29. 29.

    , , , & Molecular identification of a retinal cell type that responds to upward motion. Nature 452, 478–482 (2008)

  30. 30.

    et al. A directional tuning map of Drosophila elementary motion detectors. Nature 500, 212–216 (2013)

  31. 31.

    et al. A visual motion detection circuit suggested by Drosophila connectomics. Nature 500, 175–181 (2013)

  32. 32.

    & Cortex: Statistics and Geometry of Neuronal Connectivity 2nd edn (Springer Berlin, 1998)

  33. 33.

    , & Deriving physical connectivity from neuronal morphology. Biol. Cybern. 88, 210–218 (2003)

  34. 34.

    , & A quantitative map of the circuit of cat primary visual cortex. J. Neurosci. 24, 8441–8453 (2004)

  35. 35.

    & Neurogeometry and potential synaptic connectivity. Trends Neurosci. 28, 387–394 (2005)

  36. 36.

    , & Mechanisms and circuitry underlying directional selectivity in the retina. Nature 420, 411–414 (2002)

  37. 37.

    et al. Spatially asymmetric reorganization of inhibition establishes a motion-sensitive circuit. Nature 469, 407–410 (2010)

  38. 38.

    , , & Development of asymmetric inhibition underlying direction selectivity in the retina. Nature 469, 402–406 (2011)

  39. 39.

    The Wisdom of Crowds (Anchor, 2005)

  40. 40.

    , , , & in Advances in Neural Information Processing Systems 22. 1865–1873 (2009)

  41. 41.

    et al. Convolutional networks can learn to generate affinity graphs for image segmentation. Neural Comput. 22, 511–538 (2010)

  42. 42.

    et al. in Advances in Neural Information Processing Systems 25. 2852–2860 (2012)

  43. 43.

    , , , & Excitatory synaptic inputs to mouse on-off direction-selective retinal ganglion cells lack direction tuning. J. Neurosci. 34, 3976–3981 (2014)

  44. 44.

    , & CNS: a GPU-Based Framework for Simulating Cortically-Organized Networks Tech. Rep. MIT-CSAIL-TR-2010–013/CBCL-286 (MIT, 2010)

  45. 45.

    , & The major cell populations of the mouse retina. J. Neurosci. 18, 8936–8946 (1998)

  46. 46.

    Map Projections–A working Manual 1395 (USGPO, 1987)

Download references

Acknowledgements

This research was made possible by funding from the Gatsby Charitable Foundation, the Howard Hughes Medical Institute, the Human Frontier Science Program, an anonymous donor, and the National Institutes of Health. K.L. was supported by a Samsung Scholarship. Support from the AWS Research Grants Program gave EyeWire global reach through Amazon Cloudfront. We thank K. Briggman for providing the e2198 data set. J. Mutch created the CNS framework on which CNPKG is based. D. Jia, R. Shearer, and B. Warne assisted in early stages of software development, and W. Silversmith with recent modifications. R. Prentki, L. Trawinski, M. Sorek, A. Ostojic, C. David, R. Avery, S. Temple, A. Bost, M. Greenstein and M. Evans worked in the laboratory to reconstruct neurons, and the first six also served as GrimReaper and hosted EyeWire competitions. Additional reconstructions were provided by R. Han, M. Gavrin, G. Lu, A. Ortiz and D. Udvary. All were trained by R. Prentki, who also created training videos for EyeWirers. We are grateful to A. Norton for 3D renderings, and to E. Almeida for EyeWire graphics. We acknowledge discussions with T. Baden, M. Berry, B. Borghuis, A. Borst, E. J. Chichilnisky, D. Chklovskii, D. Clark, J. Demb, T. Euler, M. Helmstaedter, A. Huberman, S. Lee, R. Masland, J. Sanes and Z. Zhou.

Author information

Author notes

    • Jinseop S. Kim
    •  & Matthew J. Greene

    These authors contributed equally to this work.

    • Mark Richardson
    • , Srinivas C. Turaga
    •  & H. Sebastian Seung

    Present addresses: 601 N 42nd Street, Seattle, Washington 98103, USA (M.R.); Princeton Neuroscience Institute and Computer Science Deptartment, Princeton, New Jersey 08544, USA (H.S.S.); Gatsby Computational Neuroscience Unit, London WC1N 3AR, UK (S.C.T.).

Affiliations

  1. Brain & Cognitive Sciences Department, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA

    • Jinseop S. Kim
    • , Matthew J. Greene
    • , Kisuk Lee
    • , Mark Richardson
    • , Srinivas C. Turaga
    • , Michael Purcaro
    • , Matthew Balkam
    • , Amy Robinson
    •  & H. Sebastian Seung
  2. Electrical Engineering and Computer Science Department, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA

    • Aleksandar Zlateski
  3. Qualcomm Research, 5775 Morehouse Drive, San Diego, California 92121, USA

    • Bardia F. Behabadi
    •  & Michael Campos
  4. Max-Planck Institute for Medical Research, D-69120 Heidelberg, Germany

    • Winfried Denk

Consortia

  1. the EyeWirers

    https://eyewire.org

Authors

  1. Search for Jinseop S. Kim in:

  2. Search for Matthew J. Greene in:

  3. Search for Aleksandar Zlateski in:

  4. Search for Kisuk Lee in:

  5. Search for Mark Richardson in:

  6. Search for Srinivas C. Turaga in:

  7. Search for Michael Purcaro in:

  8. Search for Matthew Balkam in:

  9. Search for Amy Robinson in:

  10. Search for Bardia F. Behabadi in:

  11. Search for Michael Campos in:

  12. Search for Winfried Denk in:

  13. Search for H. Sebastian Seung in:

Contributions

J.S.K. created algorithms, software and procedures for crowd intelligence and learning, and applied them to generate neuron reconstructions. J.S.K. and M.J.G. classified bipolar cells. M.J.G. analysed contact and co-stratification, aided by code from A.Z. and input from W.D. H.S.S. devised the model with help from B.F.B. and M.C. S.C.T. trained the convolutional network. M.P. and M.B. implemented software and algorithms created by A.Z. for interactive segmentation and 3D visualization, with guidance from S.C.T. M.R. created the EyeWire game and M.B. its data infrastructure. K.L. quantified EyeWirer accuracy and learning. A.R. mobilized and studied the EyeWire community. EyeWirers reconstructed neurons and built extensions to EyeWire. H.S.S. wrote the paper with help from J.S.K., M.J.G. and A.R.

Competing interests

W.D. receives license income for SBEM technology from Gatan Inc.

Corresponding author

Correspondence to H. Sebastian Seung.

Extended data

Supplementary information

PDF files

  1. 1.

    Supplementary Information

    This file contains Supplementary Equations showing detailed derivation of the mathematical model of direction selectivity, calculation of the direction selectivity index for a special case that does not depend on the detailed forms of the filters, comparison with experiments, and cable theory estimate of dendritic conduction time. It also contains Supplementary Notes, which include EyeWire demographics, community structure, competitions, and list of EyeWirers who reconstructed SACs.

Videos

  1. 1.

    Off SAC with BC2 and BC3a axons.

    Off SAC with BC2 and BC3a axons. Off SAC in red, BC2 axon in yellow, and BC3a axon in blue.

About this article

Publication history

Received

Accepted

Published

DOI

https://doi.org/10.1038/nature13240

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.