Who Is Talking to Whom: Synaptic Partner Detection in Anisotropic Volumes of Insect Brain

  • Anna Kreshuk
  • Jan Funke
  • Albert Cardona
  • Fred A. Hamprecht
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9349)


Automated reconstruction of neural connectivity graphs from electron microscopy image stacks is an essential step towards large-scale neural circuit mapping. While significant progress has recently been made in automated segmentation of neurons and detection of synapses, the problem of synaptic partner assignment for polyadic (one-to-many) synapses, prevalent in the Drosophila brain, remains unsolved. In this contribution, we propose a method which automatically assigns pre- and postsynaptic roles to neurites adjacent to a synaptic site. The method constructs a probabilistic graphical model over potential synaptic partner pairs which includes factors to account for a high rate of one-to-many connections, as well as the possibility of the same neuron to be pre-synaptic in one synapse and post-synaptic in another. The algorithm has been validated on a publicly available stack of ssTEM images of Drosophila neural tissue and has been shown to reconstruct most of the synaptic relations correctly.


Circuit reconstruction graphical model electron microscopy 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Andres, B., Kroeger, T., Briggman, K.L., Denk, W., Korogod, N., Knott, G., Koethe, U., Hamprecht, F.A.: Globally Optimal Closed-surface Segmentation for Connectomics. In: Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds.) ECCV 2012, Part III. LNCS, vol. 7574, pp. 778–791. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  2. 2.
    Becker, C., Ali, K., Knott, G., Fua, P.: Learning Context Cues for Synapse Segmentation in EM Volumes. In: Ayache, N., Delingette, H., Golland, P., Mori, K. (eds.) MICCAI 2012, Part I. LNCS, vol. 7510, pp. 585–592. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  3. 3.
    Cardona, A., Saalfeld, S., Preibisch, S., Schmid, B., Cheng, A., Pulokas, J., Tomancak, P., Hartenstein, V.: An integrated micro- and macroarchitectural analysis of the Drosophila brain by computer-assisted serial section electron microscopy. PLoS Biology 8(10) (January 2010)Google Scholar
  4. 4.
    Funke, J., Andres, B., Hamprecht, F.A., Cardona, A., Cook, M.: Efficient automatic 3D-reconstruction of branching neurons from EM data. In: Proceedings of CVPR (2012)Google Scholar
  5. 5.
    Funke, J., et al.: Candidate Sampling for Neuron Reconstruction from Anisotropic Electron Microscopy Volumes. In: Golland, P., Hata, N., Barillot, C., Hornegger, J., Howe, R. (eds.) MICCAI 2014, Part I. LNCS, vol. 8673, pp. 17–24. Springer, Heidelberg (2014)Google Scholar
  6. 6.
    Gerhard, S., Funke, J., Julien, M., Cardona, A., Fetter, R.: Segmented anisotropic ssTEM dataset of neural tissue,
  7. 7.
    Helmstaedter, M., Mitra, P.P.: Computational methods and challenges for large-scale circuit mapping. Current Opinion in Neurobiology 22(1), 162–169 (2012)CrossRefGoogle Scholar
  8. 8.
    Huang, G.B., Jain, V.: Deep and Wide Multiscale Recursive Networks for Robust Image Labeling. In: Proceedings of ICLR (2014)Google Scholar
  9. 9.
    Jagadeesh, V., Anderson, J., Jones, B., Marc, R., Fisher, S., Manjunath, B.S.: Synapse Classification and Localization in Electron Micrographs. Pattern Recognition Letters (2013)Google Scholar
  10. 10.
    Kaynig, V., Knowles-barley, S., Jones, T.R.: Large-Scale Automatic Reconstruction of Neuronal Processes from Electron Microscopy Images. arxiv:1303.7186v1 (2013)Google Scholar
  11. 11.
    Knott, G., Marchman, H., Wall, D., Lich, B.: Serial section scanning electron microscopy of adult brain tissue using focused ion beam milling. The Journal of Neuroscience 28(12), 2959–2964 (2008)CrossRefGoogle Scholar
  12. 12.
    Kreshuk, A., Köthe, U., Pax, E., Bock, D.D., Hamprecht, F.A.: Automated Detection of Synapses in Serial Section Transmission Electron Microscopy Image Stacks. PLoS One 9, 2 (2014)Google Scholar
  13. 13.
    Kreshuk, A., Straehle, C.N., Sommer, C., Koethe, U., Cantoni, M., Knott, G., Hamprecht, F.A.: Automated detection and segmentation of synaptic contacts in nearly isotropic serial electron microscopy images. PloS One 6(10), e24899 (2011)Google Scholar
  14. 14.
    Lichtman, J.W., Pfister, H., Shavit, N.: The big data challenges of connectomics. Nature Neuroscience 17(11), 1448–1454 (2014)CrossRefGoogle Scholar
  15. 15.
    Liu, T., Jones, C., Seyedhosseini, M., Tasdizen, T.: A modular hierarchical approach to 3D electron microscopy image segmentation. Journal of Neuroscience Methods 226, 88–102 (2014)CrossRefGoogle Scholar
  16. 16.
    Nunez-Iglesias, J., Kennedy, R., Parag, T., Shi, J., Chklovskii, D.B.: Machine Learning of Hierarchical Clustering to Segment 2D and 3D Images. PloS One 8(8), e71715 (2013)Google Scholar
  17. 17.
    Plaza, S.M.: Focused Proofreading: Efficiently Extracting Connectomes from Segmented EM Images. arXiv:1409.1199v1 (2014)Google Scholar
  18. 18.
    Plaza, S.M., Parag, T., Huang, G.B., Olbris, D.J., Saunders, M.A., Rivlin, P.K.: Annotating Synapses in Large EM Datasets. arXiv:1409.1801v2 (2014)Google Scholar
  19. 19.
    Roncal, W.G., Kaynig-Fittkau, V., Kasthuri, N., Berger, D., Vogelstein, J.T., Fernandez, L.R., Lichtman, J.W., Vogelstein, R.J., Pfister, H., Hager, G.D.: Volumetric Exploitation of Synaptic Information using Context Localization and Evaluation. arXiv:1403.3724 (2014)Google Scholar
  20. 20.
    Sommer, C., Straehle, C., Kothe, U., Hamprecht, F.A.: Ilastik: Interactive learning and segmentation toolkit. In: Proceedings of ISBI (2011)Google Scholar
  21. 21.
    Vazquez-Reina, A., Gelbart, M., Huang, D., Lichtman, J., Miller, E., Pfister, H.: Segmentation fusion for connectomics. In: Proceedings of ICCV (2011)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Anna Kreshuk
    • 1
    • 3
  • Jan Funke
    • 2
  • Albert Cardona
    • 3
  • Fred A. Hamprecht
    • 1
  1. 1.HCI/IWRUniversity of HeidelbergHeidelbergGermany
  2. 2.Institute of NeuroinformaticsUZH/ETH ZurichZurichSwitzerland
  3. 3.HHMI Janelia Research CampusAshburnUSA

Personalised recommendations