, Volume 13, Issue 4, pp 487–499 | Cite as

BlastNeuron for Automated Comparison, Retrieval and Clustering of 3D Neuron Morphologies

  • Yinan Wan
  • Fuhui Long
  • Lei Qu
  • Hang Xiao
  • Michael Hawrylycz
  • Eugene W. Myers
  • Hanchuan PengEmail author
Original Article


Characterizing the identity and types of neurons in the brain, as well as their associated function, requires a means of quantifying and comparing 3D neuron morphology. Presently, neuron comparison methods are based on statistics from neuronal morphology such as size and number of branches, which are not fully suitable for detecting local similarities and differences in the detailed structure. We developed BlastNeuron to compare neurons in terms of their global appearance, detailed arborization patterns, and topological similarity. BlastNeuron first compares and clusters 3D neuron reconstructions based on global morphology features and moment invariants, independent of their orientations, sizes, level of reconstruction and other variations. Subsequently, BlastNeuron performs local alignment between any pair of retrieved neurons via a tree-topology driven dynamic programming method. A 3D correspondence map can thus be generated at the resolution of single reconstruction nodes. We applied BlastNeuron to three datasets: (1) 10,000+ neuron reconstructions from a public morphology database, (2) 681 newly and manually reconstructed neurons, and (3) neurons reconstructions produced using several independent reconstruction methods. Our approach was able to accurately and efficiently retrieve morphologically and functionally similar neuron structures from large morphology database, identify the local common structures, and find clusters of neurons that share similarities in both morphology and molecular profiles.


Neuron comparison Neuron morphology Tree matching Neuron reconstruction 



This work was supported primarily by the Janelia Research Campus of HHMI and the Allen Institute for Brain Science. Lei Qu was also partially supported by Chinese Natural Science Foundation Project (61201396, 61301296, 61377006, U1201255); Scientific Research Foundation for the Returned Overseas Chinese Scholars, State Education Ministry; Technology Foundation for Selected Overseas Chinese Scholar, Ministry of Personnel of China. We thank Zhi Zhou for providing some neuron reconstructions for testing in Fig. 8.


  1. Altschul, S. F., et al. (1990). Basic local alignment search tool. Journal of Molecular Biology, 215, 403–410.CrossRefPubMedGoogle Scholar
  2. Ascoli, G. A., et al. (2001). Generation, description and storage of dendritic morphology data. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 356, 1131–1145.CrossRefPubMedPubMedCentralGoogle Scholar
  3. Ascoli, G. A., Donohue, D. E., & Halavi, M. (2007). NeuroMorpho.Org: a central resource for neuronal morphologies, The. Journal of Neuroscience, 27, 9247–9251.CrossRefPubMedGoogle Scholar
  4. Basu, S., Condron, B., & Acton, S. T. (2011). Path2Path: Hierarchical path-based analysis for neuron matching. In Biomedical imaging: From nano to macro, 2011 I.E. international symposium on (pp. 996–999). IEEE.Google Scholar
  5. Belongie, S., & Malik, J. (2000). Matching with shape contexts. IEEE Workshop on Content-Based Access of Image and Video Libraries. Proceedings, 20–26.Google Scholar
  6. Bille, P. (2005). A survey on tree edit distance and related problems. Theoretical Computer Science, 337, 217–239.CrossRefGoogle Scholar
  7. Bustos, B., et al. (2005). Feature-based similarity search in 3D object databases. ACM Computing Surveys, 37, 345–387.CrossRefGoogle Scholar
  8. Cannon, R. C., et al. (1998). An on-line archive of reconstructed hippocampal neurons. Journal of Neuroscience Methods, 84, 49–54.CrossRefPubMedGoogle Scholar
  9. Cardona, A., et al. (2010). Identifying neuronal lineages of Drosophila by sequence analysis of axon tracts. The Journal of Neuroscience : The Official Journal of the Society for Neuroscience, 30, 7538–7553.CrossRefGoogle Scholar
  10. Chiang, A. S., Lin, C. Y., Chuang, C. C., Chang, H. M., Hsieh, C. H., Yeh, C. W., & Hwang, J. K. (2011). Three-dimensional reconstruction of brain-wide wiring networks in Drosophila at single-cell resolution. Current Biology, 21(1), 1–11.CrossRefPubMedGoogle Scholar
  11. Chklovskii, D. B., Vitaladevuni, S., & Scheffer, L. K. (2010). Semi-automated reconstruction of neural circuits using electron microscopy. Current Opinion in Neurobiology, 20, 667–675.CrossRefPubMedGoogle Scholar
  12. Costa, M., et al. (2014). NBLAST: Rapid, sensitive comparison of neuronal structure and construction of neuron family databases. bioRxiv, 006346.Google Scholar
  13. Denk, W., & Horstmann, H. (2004). Serial block-face scanning electron microscopy to reconstruct three-dimensional tissue nanostructure. PLoS Biology, 2, e329.CrossRefPubMedPubMedCentralGoogle Scholar
  14. Dumitriu, D., Cossart, R., Huang, J., & Yuste, R. (2007). Correlation between axonal morphologies and synaptic input kinetics of interneurons from mouse visual cortex. Cerebral Cortex, 17(1), 81–91.CrossRefPubMedGoogle Scholar
  15. Ganglberger, F., et al. (2014). Structure-based neuron retrieval across Drosophila brains. Neuroinformatics, 12, 423–434.CrossRefPubMedGoogle Scholar
  16. Gillette, T.A., & Ascoli, G.A. (2015). Topological characterization of neuronal arbor morphology via sequence representation. I. Motif analysis (in press).Google Scholar
  17. Gillette, T.A., Hosseini, P., & Ascoli, G.A. (2015). Topological characterization of neuronal arbor morphology via sequence representation. II. Global alignment (in press).Google Scholar
  18. Heumann, H., & Wittum, G. (2009). The tree-edit-distance, a measure for quantifying neuronal morphology. Neuroinformatics, 7(3), 179–190.CrossRefPubMedGoogle Scholar
  19. Hu, M. (1962). Visual-pattern recognition by moment invariants. IRE Transactions on Information Theory 8, 179-&.Google Scholar
  20. Jacobs, G. A., & Theunissen, F. E. (2000). Extraction of sensory parameters from a neural map by primary sensory interneurons. The Journal of Neuroscience : The Official Journal of the Society for Neuroscience, 20, 2934–2943.Google Scholar
  21. Jefferis, G. S., et al. (2007). Comprehensive maps of Drosophila higher olfactory centers: spatially segregated fruit and pheromone representation. Cell, 128, 1187–1203.CrossRefPubMedPubMedCentralGoogle Scholar
  22. Koene, R. A., et al. (2009). NETMORPH: a framework for the stochastic generation of large scale neuronal networks with realistic neuron morphologies. Neuroinformatics, 7, 195–210.CrossRefPubMedGoogle Scholar
  23. Lo, C. H., & Don, H. S. (1989). 3-D moment forms - their construction and application to object identification and positioning. IEEE Transactions on Pattern Analysis, 11, 1053–1064.CrossRefGoogle Scholar
  24. Mayerich, D., et al. (2012). NetMets: software for quantifying and visualizing errors in biological network segmentation. BMC Bioinformatics, 13(Suppl 8), S7.PubMedPubMedCentralGoogle Scholar
  25. Ming, X., et al. (2013). Rapid reconstruction of 3D neuronal morphology from light microscopy images with augmented rayburst sampling. PLoS One, 8, e84557.CrossRefPubMedPubMedCentralGoogle Scholar
  26. Peng, H., et al. (2010). V3D enables real-time 3D visualization and quantitative analysis of large-scale biological image data sets. Nature Biotechnology, 28, 348–353.CrossRefPubMedPubMedCentralGoogle Scholar
  27. Peng, H., Chung, P., Long, F., Qu, L., Jenett, A., Seeds, A. M., & Simpson, J. H. (2011). BrainAligner: 3D registration atlases of Drosophila brains. Nature Methods, 8(6), 493–498.CrossRefPubMedPubMedCentralGoogle Scholar
  28. Peng, H., Roysam, B., & Ascoli, G. A. (2013). Automated image computing reshapes computational neuroscience. BMC Bioinformatics, 14(1), 293.CrossRefPubMedPubMedCentralGoogle Scholar
  29. Peng, H., Bria, A., Zhou, Z., Iannello, G., & Long, F. (2014). Extensible visualization and analysis for multidimensional images using Vaa3D. Nature Protocols, 9(1), 193–208.CrossRefPubMedGoogle Scholar
  30. Peng, H., Meijering, E., & Ascoli, G. (2015) From DIADEM to BigNeuron. NeuroInformatics. doi: 10.1007/s12021-015-9270-9.
  31. Schnabel, R., Wahl, R., & Klein, R. (2007). Efficient RANSAC for point-cloud shape detection. In Computer graphics forum (26(2), 214–226). Blackwell Publishing Ltd.Google Scholar
  32. Scorcioni, R., Polavaram, S., & Ascoli, G. A. (2008). L-Measure: a web-accessible tool for the analysis, comparison and search of digital reconstructions of neuronal morphologies. Nature Protocols, 3(5), 866–876.CrossRefPubMedPubMedCentralGoogle Scholar
  33. Sebastian, T. B., Klein, P. N., & Kimia, B. B. (2003). On aligning curves. IEEE Transactions on Pattern Analysis, 25, 116–125.CrossRefGoogle Scholar
  34. Tschirren, J., et al. (2005). Matching and anatomical labeling of human airway tree. IEEE Transactions on Medical Imaging, 24, 1540–1547.CrossRefPubMedPubMedCentralGoogle Scholar
  35. Wang, Y., et al. (2011). A broadly applicable 3-D neuron tracing method based on open-curve snake. Neuroinformatics, 9, 193–217.CrossRefPubMedGoogle Scholar
  36. Xiao, H., & Peng, H. (2013). APP2: automatic tracing of 3D neuron morphology based on hierarchical pruning of a gray-weighted image distance-tree. Bioinformatics, 29(11), 1448–1454.CrossRefPubMedPubMedCentralGoogle Scholar
  37. Zhang, K., & Shasha, D. (1989). Simple fast algorithms for the editing distance between trees and related problems. SIAM Journal on Computing, 18(6), 1245–1262.CrossRefGoogle Scholar
  38. Zhao, T., Xie, J., Amat, F., Clack, N., Ahammad, P., Peng, H., & Myers, E. (2011). Automated reconstruction of neuronal morphology based on local geometrical and global structural models. Neuroinformatics, 9(2–3), 247–261.CrossRefPubMedPubMedCentralGoogle Scholar
  39. Zheng, Q., et al. (2010). Consensus skeleton for non-rigid space-time registration. Computer Graphics Forum, 29, 635–644.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Yinan Wan
    • 1
  • Fuhui Long
    • 1
    • 2
  • Lei Qu
    • 1
    • 4
  • Hang Xiao
    • 1
  • Michael Hawrylycz
    • 2
  • Eugene W. Myers
    • 1
    • 3
  • Hanchuan Peng
    • 1
    • 2
    Email author
  1. 1.Janelia Research CampusHoward Hughes Medical InstituteAshburnUSA
  2. 2.Allen Institute for Brain ScienceSeattleUSA
  3. 3.Max Planck Institute of Molecular Cell Biology and GeneticsDresdenGermany
  4. 4.Key Laboratory of Intelligent Computation and Signal Processing, Ministry of EducationAnhui UniversityHefeiChina

Personalised recommendations