A visual motion detection circuit suggested by Drosophila connectomics (original) (raw)

References

  1. Heisenberg, M. & Wolf, R. Vision in Drosophila. Genetics of Microbehaviour (Springer Verlag, 1984)
    Google Scholar
  2. Laughlin, S. B. Matching coding, circuits, cells, and molecules to signals: General principles of retinal design in the fly’s eye. Prog. Retin. Eye Res. 13, 165–196 (1994)
    CAS Google Scholar
  3. Strausfeld, N. J. & Nässel, D. R. in Handbook of Sensory Physiology (eds Autrum, H. et al.) 1–132 (Springer-Verlag, 1981)
    Google Scholar
  4. Hassenstein, B. & Reichardt, W. Systemtheoretische Analyse der Zeit-, Reihenfolgen- und Vorzeichenauswertung bei der Bewegungsperzeption des Rüsselkäfers Chlorophanus. Z. Naturforsch. B 11, 513–524 (1956)
    Google Scholar
  5. Reichardt, W. in Sensory Communication (ed. Rosenblith, W. A. ) 303–317 (MIT Press, 1961)
    Google Scholar
  6. Barlow, H. B. & Levick, W. R. The mechanism of directionally selective units in rabbit's retina. J. Physiol. (Lond.) 178, 477–504 (1965)
    CAS Google Scholar
  7. Borst, A., Haag, J. & Reiff, D. F. Fly motion vision. Annu. Rev. Neurosci. 33, 49–70 (2010)
    CAS PubMed Google Scholar
  8. Rivera-Alba, M. et al. Wiring economy and volume exclusion determine neuronal placement in the Drosophila brain. Curr. Biol. 21, 2000–2005 (2011)
    CAS PubMed PubMed Central Google Scholar
  9. Meinertzhagen, I. A. & Sorra, K. E. Synaptic organization in the fly’s optic lamina: few cells, many synapses and divergent microcircuits. Prog. Brain Res. 131, 53–69 (2001)
    CAS PubMed Google Scholar
  10. Takemura, S. Y., Lu, Z. & Meinertzhagen, I. A. Synaptic circuits of the Drosophila optic lobe: the input terminals to the medulla. J. Comp. Neurol. 509, 493–513 (2008)
    PubMed PubMed Central Google Scholar
  11. Buchner, E., Buchner, S. & Bülthoff, I. Deoxyglucose mapping of nervous activity induced in Drosophila brain by visual movement. J. Comp. Physiol. A 155, 471–483 (1984)
    Google Scholar
  12. Krapp, H. G. & Hengstenberg, R. Estimation of self-motion by optic flow processing in single visual interneurons. Nature 384, 463–466 (1996)
    ADS CAS PubMed Google Scholar
  13. Joesch, M., Plett, J., Borst, A. & Reiff, D. F. Response properties of motion-sensitive visual interneurons in the lobula plate of Drosophila melanogaster. Curr. Biol. 18, 368–374 (2008)
    CAS PubMed Google Scholar
  14. White, J. G., Southgate, E., Thomson, J. N. & Brenner, S. The structure of the nervous system of the nematode Caenorhabditis elegans. Phil. Trans. R. Soc. Lond. B 314, 1–340 (1986)
    ADS CAS Google Scholar
  15. Kirschfeld, K. in Information Processing in the Visual System of Arthropods (ed. Wehner, R. ) 61–74 (Springer Verlag, 1972)
    Google Scholar
  16. Riehle, A. & Franceschini, N. Motion detection in flies: parametric control over ON–OFF pathways. Exp. Brain Res. 54, 390–394 (1984)
    CAS PubMed Google Scholar
  17. Schuling, F. H., Mastebroek, H. A. K., Bult, R. & Lenting, B. P. M. Properties of elementary movement detectors in the fly Calliphora erythrocephala. J. Comp. Physiol. A 165, 179–192 (1989)
    Google Scholar
  18. Helmstaedter, M., Briggman, K. L. & Denk, W. 3D structural imaging of the brain with photons and electrons. Curr. Opin. Neurobiol. 18, 633–641 (2008)
    CAS PubMed Google Scholar
  19. Chklovskii, D. B., Vitaladevuni, S. & Scheffer, L. K. Semi-automated reconstruction of neural circuits using electron microscopy. Curr. Opin. Neurobiol. 20, 667–675 (2010)
    CAS PubMed Google Scholar
  20. Fischbach, K.-F. & Dittrich, A. P. M. The optic lobe of Drosophila melanogaster. I. A Golgi analysis of wild-type structure. Cell Tissue Res. 258, 441–475 (1989)
    Google Scholar
  21. Song, S., Sjöström, P. J., Reigl, M., Nelson, S. & Chklovskii, D. B. Highly nonrandom features of synaptic connectivity in local cortical circuits. PLoS Biol. 3, e68 (2005)
    PubMed PubMed Central Google Scholar
  22. Varshney, L. R., Chen, B. L., Paniagua, E., Hall, D. H. & Chklovskii, D. B. Structural properties of the Caenorhabditis elegans neuronal network. PLOS Comput. Biol. 7, e1001066 (2011)
    ADS CAS PubMed PubMed Central Google Scholar
  23. Campos-Ortega, J. A. & Strausfeld, N. J. in Information Processing in the Visual Systems of Arthropods (ed. Wehner, R. ) 31–36 (Springer Verlag, 1972)
    Google Scholar
  24. Franceschini, N., Kirschfeld, K. & Minke, B. Fluorescence of photoreceptor cells observed in vivo. Science 213, 1264–1267 (1981)
    ADS CAS PubMed Google Scholar
  25. Douglass, J. K. & Strausfeld, N. J. Anatomical organization of retinotopic motion—sensitive pathways in the optic lobes of flies. Microsc. Res. Tech. 62, 132–150 (2003)
    PubMed Google Scholar
  26. Bausenwein, B., Dittrich, A. P. & Fischbach, K. F. The optic lobe of Drosophila melanogaster. II. Sorting of retinotopic pathways in the medulla. Cell Tissue Res. 267, 17–28 (1992)
    CAS PubMed Google Scholar
  27. Bausenwein, B. & Fischbach, K. F. Activity labeling patterns in the medulla of Drosophila melanogaster caused by motion stimuli. Cell Tissue Res. 270, 25–35 (1992)
    CAS PubMed Google Scholar
  28. Strausfeld, N. J. & Lee, J. K. Neuronal basis for parallel visual processing in the fly. Vis. Neurosci. 7, 13–33 (1991)
    CAS PubMed Google Scholar
  29. Clark, D. A., Bursztyn, L., Horowitz, M. A., Schnitzer, M. J. & Clandinin, T. R. Defining the computational structure of the motion detector in Drosophila. Neuron 70, 1165–1177 (2011)
    CAS PubMed PubMed Central Google Scholar
  30. Joesch, M., Schnell, B., Raghu, S. V., Reiff, D. F. & Borst, A. ON and OFF pathways in Drosophila motion vision. Nature 468, 300–304 (2010)
    ADS CAS PubMed Google Scholar
  31. Rister, J. et al. Dissection of the peripheral motion channel in the visual system of Drosophila melanogaster. Neuron 56, 155–170 (2007)
    CAS PubMed Google Scholar
  32. Schnell, B., Raghu, S. V., Nern, A. & Borst, A. Columnar cells necessary for motion responses of wide-field visual interneurons in Drosophila. J. Comp. Physiol. A 198, 389–395 (2012)
    Google Scholar
  33. Tuthill, J. C., Nern, A., Rubin, G. M. & Reiser, M. B. Contributions of the 12 neuron classes in the fly lamina to motion vision. Neuron 79, 128–140 (2013)
    CAS PubMed PubMed Central Google Scholar
  34. Douglass, J. K. & Strausfeld, N. J. Visual motion-detection circuits in flies: parallel direction-and non-direction-sensitive pathways between the medulla and lobula plate. J. Neurosci. 16, 4551–4562 (1996)
    CAS PubMed PubMed Central Google Scholar
  35. Maisak, M. S. et al. A directional tuning map of Drosophila elementary motion detectors. Nature http://dx.doi.org/10.1038/nature12320 (this issue)
  36. Srinivasan, M. & Dvorak, D. Spatial processing of visual information in the movement-detecting pathway of the fly. J. Comp. Physiol. A 140, 1–23 (1980)
    Google Scholar
  37. Haag, J. & Borst, A. Recurrent network interactions underlying flow-field selectivity of visual interneurons. J. Neurosci. 21, 5685–5692 (2001)
    CAS PubMed PubMed Central Google Scholar
  38. Gouwens, N. W. & Wilson, R. I. Signal propagation in Drosophila central neurons. J. Neurosci. 29, 6239–6249 (2009)
    CAS PubMed PubMed Central Google Scholar
  39. Ashmore, J. F. & Copenhagen, D. R. Different postsynaptic events in two types of retinal bipolar cell. Nature 288, 84–86 (1980)
    ADS CAS PubMed Google Scholar
  40. Mizunami, M. Synaptic rectification model equivalent to the correlation-type movement detector. Biol. Cybern. 64, 1–6 (1990)
    CAS PubMed Google Scholar
  41. Oyster, C. W. & Barlow, H. B. Direction-selective units in rabbit retina: distribution of preferred directions. Science 155, 841–842 (1967)
    ADS CAS PubMed Google Scholar
  42. Kim, I.-J., Zhang, Y., Yamagata, M., Meister, M. & Sanes, J. R. Molecular identification of a retinal cell type that responds to upward motion. Nature 452, 478–482 (2008)
    ADS CAS PubMed Google Scholar
  43. Euler, T., Detwiler, P. B. & Denk, W. Directionally selective calcium signals in dendrites of starburst amacrine cells. Nature 418, 845–852 (2002)
    ADS CAS PubMed Google Scholar
  44. Briggman, K. L., Helmstaedter, M. & Denk, W. Wiring specificity in the direction-selectivity circuit of the retina. Nature 471, 183–188 (2011)
    ADS CAS PubMed Google Scholar
  45. Meinertzhagen, I. & Hanson, T. in The Development of Drosophila Melanogaster Vol. 2 (eds Bate, M. & Martinez Arias, A. ) 1363–1491 (Cold Spring Harbor Laboratory Press, 1993)
    Google Scholar
  46. Blondel, V. D., Guillaume, J. L., Lambiotte, R. & Lefebvre, E. Fast unfolding of communities in large networks. J. Stat. Mech. 2008, P10008 (2008)
    MATH Google Scholar
  47. Eck, N. & Waltman, L. VOS: a new method for visualizing similarities between objects. Adv. Data Anal. 299–306 (2007)
  48. Cardona, A. et al. TrakEM2 software for neural circuit reconstruction. PLoS ONE 7, e38011 (2012)
    ADS MathSciNet CAS PubMed PubMed Central Google Scholar
  49. Scheffer, L., Karsh, B. & Vitaladevuni, S. Automated alignment of imperfect EM images for neural reconstruction. Preprint at http://arXiv.org/abs/1304.6034 (2013)
  50. Canny, J. A computational approach to edge detection. IEEE Trans. Pattern Anal. Mach. Intell. PAMI-8, 679–698 (1986)
    Google Scholar
  51. Martin, D. R., Fowlkes, C. C. & Malik, J. Learning to detect natural image boundaries using local brightness, color, and texture cues. IEEE Trans. Pattern Anal. Mach. Intell. 26, 530–549 (2004)
    PubMed Google Scholar
  52. Soille, P. Morphological Image Analysis: Principles and Applications 2nd edn, 316 (Springer-Verlag New York, 2003)
    MATH Google Scholar
  53. Dollar, P., Tu, Z. & Belongie, S. Supervised learning of edges and object boundaries. IEEE Comp. Soc. Conf. Comp. Vis. Pattern Rec. 2, 1964–1971 (2006)
    Google Scholar
  54. Vitaladevuni, S., Mishchenko, Y., Genkin, A., Chklovskii, D. C. & Harris, K. M. Mitochondria detection in electron microscopy images. Workshop Microscopic Image Anal. Appl. Biol.. http://www.miaab.org/miaab-2008-papers/21-miaab-2008-abstract-05.pdf (2008)
  55. Vincent, L. & Soille, P. Watersheds in digital spaces: an efficient algorithm based on immersion simulations. IEEE Trans. Pattern Anal. Mach. Intell. 13, 583–598 (1991)
    Google Scholar
  56. Mohanta, P. P., Mukherjee, D. P. & Acton, S. T. Agglomerative clustering for image segmentation. Int. Conf. Pattern Rec. 1, 664–667 (2002)
    Google Scholar
  57. Vitaladevuni, S. N. & Basri, R. Co-clustering of image segments using convex optimization applied to EM neuronal reconstruction. IEEE Comp. Soc. Conf. Comp. Vis. Patt. Rec.. http://dx.doi.org/10.1109/CVPR.2010.5539901 2203–2210 (2010)
  58. Kasai, H., Matsuzaki, M., Noguchi, J., Yasumatsu, N. & Nakahara, H. Structure–stability–function relationships of dendritic spines. Trends Neurosci. 26, 360–368 (2003)
    CAS PubMed Google Scholar
  59. Sato, M., Bitter, I., Bender, M. A., Kaufman, A. E. & Nakajima, M. TEASAR: Tree-structure extraction algorithm for accurate and robust skeletons. Eighth Pac. Conf. Comp. Graphics Appl.. http://dx.doi.org/10.1109/PCCGA.2000.883951 281–287, 449 (2000)

Download references