Diverse Community Structures in the Neuronal-Level Connectome of the Drosophila Brain

  • Chi-Tin ShihEmail author
  • Yen-Jen Lin
  • Cheng-Te Wang
  • Ting-Yuan Wang
  • Chih-Chen Chen
  • Ta-Shun Su
  • Chung-Chuang LoEmail author
  • Ann-Shyn ChiangEmail author
Original Article


Drosophila melanogaster is one of the most important model animals in neurobiology owing to its manageable brain size, complex behaviour, and extensive genetic tools. However, without a comprehensive map of the brain-wide neural network, our ability to investigate brain functions at the systems level is seriously limited. In this study, we constructed a neuron-to-neuron network of the Drosophila brain based on the 28,573 fluorescence images of single neurons in the newly released FlyCircuit v1.2 ( database. By performing modularity and centrality analyses, we identified eight communities (right olfaction, left olfaction, olfactory core, auditory, motor, pre-motor, left vision, and right vision) in the brain-wide network. Further investigation on information exchange and structural stability revealed that the communities of different functions dominated different types of centralities, suggesting a correlation between functions and network structures. Except for the two olfaction and the motor communities, the network is characterized by overall small-worldness. A rich club (RC) structure was also found in this network, and most of the innermost RC members innervated the central complex, indicating its role in information integration. We further identified numerous loops with length smaller than seven neurons. The observation suggested unique characteristics in the information processing inside the fruit fly brain.


Drosophila Neural networks Connectome Community Centrality 



This work was supported by the Aim for the Top University Project of the Ministry of Education, and by the Higher Education Sprout Project funded by the Ministry of Science and Technology and Ministry of Education in Taiwan.

Author Contributions

CTS, CCL, and ASC designed the study. CTS, YJL, CTW, TYW, CCC, and TSS performed the analysis. CTS and CCL wrote the manuscript. ASC provided the data.

Compliance with Ethical Standards

Competing Interests

The author(s) declare no competing interests.

Supplementary material

12021_2019_9443_MOESM1_ESM.pdf (3.1 mb)
ESM 1 (PDF 3.06 Mb)


  1. Albert, R., & Barabasi, A. L. (2002). Statistical mechanics of complex networks. Reviews of Modern Physics, 74(1), 47–97.CrossRefGoogle Scholar
  2. Azevedo, F. A. C., Carvalho, L. R. B., Grinberg, L. T., Farfel, J. M., Ferretti, R. E. L., Leite, R. E. P., et al. (2009). Equal numbers of neuronal and nonneuronal cells make the human brain an isometrically scaled-up primate brain. The Journal of Comparative Neurology, 513, 532–541. Scholar
  3. Bahlmann, K., So, P. T., Kirber, M., Reich, R., Kosicki, B., McGonagle, W., & Bellve, K. (2007). Multifocal multiphoton microscopy (MMM) at a frame rate beyond 600 Hz. Optics Express, 15, 10991–10998.CrossRefGoogle Scholar
  4. Barrat, A., Barthelemy, M., Pastor-Satorras, R., & Vespignani, A. (2004). The architecture of complex weighted networks. Proceedings of the National Academy of Sciences of the United States of America, 101(11), 3747–3752. Scholar
  5. Bassett, D. S., & Bullmore, E. (2006). Small-world brain networks. Neuroscientist, 12(6), 512–523. Scholar
  6. Bewersdorf, J., Pick, R., & Hell, S. W. (1998). Multifocal multiphoton microscopy. Optics Letters, 23, 655–657.CrossRefGoogle Scholar
  7. Bota, M., Dong, H. W., & Swanson, L. W. (2003). From gene networks to brain networks. Nature Neuroscience, 6(8), 795–799. Scholar
  8. Bota, M., Sporns, O., & Swanson, L. W. (2015). Architecture of the cerebral cortical association connectome underlying cognition. Proceedings of the National Academy of Sciences of the United States of America, 112(16), E2093–E2101. Scholar
  9. Brandes, U. (2001). A faster algorithm for betweenness centrality. Journal of Mathematical Sociology, 25(2), 163–177.CrossRefGoogle Scholar
  10. Brin, S., & Page, L. (1998). The anatomy of a large-scale hypertextual web search engine. Paper presented at the seventh international world-wide web conference, Brisbane, AustraliaGoogle Scholar
  11. Bullmore, E., & Sporns, O. (2009). Complex brain networks: Graph theoretical analysis of structural and functional systems [Research Support, N.I.H., Extramural research support, Non-U.S. Gov't. Review]. Nature Reviews Neuroscience, 10(3), 186–198. Scholar
  12. Chiang, A. S., Lin, C. Y., Chuang, C. C., Chang, H. M., Hsieh, C. H., Yeh, C. W., Shih, C. T., Wu, J. J., Wang, G. T., Chen, Y. C., Wu C. C., Chen, G. Y., Ching, Y. T., Lee, P. C., Lin, C. Y., Lin, H. H., Wu, C. C., Hsu, H. W., Huang, Y. A., Chen, J. Y., Chiang, H. J., Lu, C. F., Ni, R. F., Yeh, C. Y., & Hwang, J. K. (2011). Three-dimensional reconstruction of brain-wide wiring networks in Drosophila at single-cell resolution. [Research Support, Non-U.S. Gov't]. Current Biology, 21(1), 1–11. Scholar
  13. Cleland, T. A., & Linster, C. (2005). Computation in the olfactory system. Chemical Senses, 30, 801–813. Scholar
  14. Denk, W., & Horstmann, H. (2004). Serial block-face scanning electron microscopy to reconstruct three-dimensional tissue nanostructure. PLOS Biology, 2, e329. Scholar
  15. Fagiolo, G. (2007). Clustering in complex directed networks. Physical Review E, 76(2), 026107.CrossRefGoogle Scholar
  16. Fornito, A., Zalesky, A., & Bullmore, E. (2016). Fundamentals of brain network analysis (1st ed.). San Diego: Academic.Google Scholar
  17. Gămănuţ, R., Kennedy, H., Toroczkai, Z., Ercsey-Ravasz, M., Van Essen, D. C., Knoblauch, K., et al. (2018). The mouse cortical connectome, characterized by an ultra-dense cortical graph, maintains specificity by distinct connectivity profiles. Neuron, 97(3), 698–715.e610. Scholar
  18. Guimera, R., & Amaral, L. A. N. (2005). Functional cartography of complex metabolic networks. Nature, 433(7028), 895–900.CrossRefGoogle Scholar
  19. Harriger, L., van den Heuvel, M. P., & Sporns, O. (2012). Rich club organization of macaque cerebral cortex and its role in network communication. PLoS One, 7(9), e46497. Scholar
  20. Helmstaedter, M. (2013). Cellular-resolution connectomics: Challenges of dense neural circuit reconstruction. Nature Methods, 10, 501–507. Scholar
  21. Hilgetag, C. C., & Goulas, A. (2016). Is the brain really a small-world network? Brain Structure and Function, 221(4), 2361–2366. Scholar
  22. Homberg, U. (2008). Evolution of the central complex in the arthropod brain with respect to the visual system. Arthropod Structure and Development, 37(5), 347–362. Scholar
  23. Huang, Y.-C., Wang, C.-T., Su, T.-S., Kao, K.-W., Lin, Y.-J., Chuang, C.-C., et al. (2019). A single-cell level and connectome-derived computational model of the Drosophila brain. Frontiers in Neuroinformatics, 12, 99. Scholar
  24. Huisken, J., Swoger, J., Bene, F. D., Wittbrodt, J., & Stelzer, E. H. K. (2004). Optical sectioning deep inside live embryos by selective plane illumination microscopy. Science, 305, 1007–1009. Scholar
  25. Jefferis, G. S. X. E., Marin, E. C., Stocker, R. F., & Luo, L. (2001). Target neuron prespecification in the olfactory map of Drosophila. Nature, 414, 204–208. Scholar
  26. Jorgenson, L. A., Newsome, W. T., Anderson, D. J., Bargmann, C. I., Brown, E. N., Deisseroth, K., et al. (2015). The BRAIN initiative: Developing technology to catalyse neuroscience discovery. Philosophical Transactions: Biological Sciences, 370, 20140164. Scholar
  27. Kaiser, M. (2015). Neuroanatomy: Connectome connects fly and mammalian brain networks. Current Biology, 25(10), R416–R418. Scholar
  28. Kaiser, M., & Hilgetag, C. C. (2004). Edge vulnerability in neural and metabolic networks. Biological Cybernetics, 90(5), 311–317. Scholar
  29. Kashiwadani, H., Sasaki, Y. F., Uchida, N., & Mori, K. (1999). Synchronized oscillatory discharges of mitral/tufted cells with different molecular receptive ranges in the rabbit olfactory bulb. Journal of Neurophysiology, 82, 1786–1792.CrossRefGoogle Scholar
  30. Knox, J. E., Harris, K. D., Graddis, N., Whitesell, J. D., Zeng, H., Harris, J. A., et al. (2018). High resolution data-driven model of the mouse connectome. bioRxiv.
  31. Krashes, M. J., Keene, A. C., Leung, B., Armstrong, J. D., & Waddell, S. (2007). Sequential use of mushroom body neuron subsets during Drosophila odor memory processing. Neuron, 53(1), 103–115. Scholar
  32. Landhuis, E. (2017). Neuroscience: Big brain, big data. Nature, 541, 559–561. Scholar
  33. Lee, P. C., Chuang, C. C., Chiang, A. S., & Ching, Y. T. (2012). High-throughput computer method for 3D neuronal structure reconstruction from the image stack of the Drosophila brain and its applications. PLoS Comput Biol, 8(9), e1002658. Scholar
  34. Lee, Y. H., Lin, Y. N., Chuang, C. C., & Lo, C. C. (2014). SPIN: A method of skeleton-based polarity identification for neurons. Neuroinformatics, 12(3), 487–507. Scholar
  35. Levoy, M., Ng, R., Adams, A., Footer, M., & Horowitz, M. (2006) Light Field Microscopy (SIGGRAPH '06, ACM, New York),
  36. Lichtman, J. W., Livet, J., & Sanes, J. R. (2008). A technicolour approach to the connectome. Nature Reviews Neuroscience, 9, 417–422. Scholar
  37. Lin, C. Y., Chuang, C. C., Hua, T. E., Chen, C. C., Dickson, B. J., Greenspan, R. J., & Chiang, A. S. (2013a). A comprehensive wiring diagram of the protocerebral bridge for visual information processing in the Drosophila brain. Cell Reports, 3(5), 1739–1753. Scholar
  38. Lin, H. H., Chu, L. A., Fu, T. F., Dickson, B. J., & Chiang, A. S. (2013b). Parallel neural pathways mediate CO2 avoidance responses in Drosophila. Science, 340(6138), 1338–1341. Scholar
  39. Lin, Y.-N., Chang, P.-Y., Hsiao, P.-Y., & Lo, C.-C. (2014). Polarity-specific high-level information propagation in neural networks. Frontiers in Neuroinformatics, 8, 27. Scholar
  40. Lo, C.-C., & Chiang, A.-S. (2016). Toward whole-body connectomics. Journal of Neuroscience, 36, 11375–11383. Scholar
  41. Markram, H. (2012). The human brain project. Scientific American, 306(6), 50–55.CrossRefGoogle Scholar
  42. Mayerich, D., Abbott, L., & McCORMICK, B. (2008). Knife-edge scanning microscopy for imaging and reconstruction of three-dimensional anatomical structures of the mouse brain. Journal of Microscopy, 231, 134–143. Scholar
  43. Mi, Y., Liao, X., Huang, X., Zhang, L., Gu, W., Hu, G., et al. (2013). Long-period rhythmic synchronous firing in a scale-free network. Proceedings of the National Academy of Sciences, 110, E4931–E4936. Scholar
  44. Milo, R., Shen-Orr, S., Itzkovitz, S., Kashtan, N., Chklovskii, D., & Alon, U. (2002). Network motifs: Simple building blocks of complex networks. Science, 298(5594), 824–827. Scholar
  45. Morgan, J. L., & Lichtman, J. W. (2013). Why not connectomics? Nature Methods, 10, 494–500. Scholar
  46. Muller, L., Destexhe, A., & Rudolph-Lilith, M. (2014). Brain networks: Small-worlds, after all? New Journal of Physics, 16(10), 105004. Scholar
  47. Newman, M. E. J. (2006). Modularity and community structure in networks. Proceedings of the National Academy of Sciences of the United States of America, 103(23), 8577–8582. Scholar
  48. Newman, M. E. J. (2010). Networks: An introduction. Oxford: Oxford University Press.CrossRefGoogle Scholar
  49. Olsen, S. R., & Wilson, R. I. (2008). Lateral presynaptic inhibition mediates gain control in an olfactory circuit. Nature, 452, 956–960. Scholar
  50. Pastrana, E. (2013). Focus on mapping the brain. Nature Methods, 10, 481–481. Scholar
  51. Peng, H., Ruan, Z., Long, F., Simpson, J. H., & Myers, E. W. (2010). V3D enables real-time 3D visualization and quantitative analysis of large-scale biological image data sets. Nature Biotechnology, 28(4), 348–353. Scholar
  52. Planchon, T. A., Gao, L., Milkie, D. E., Davidson, M. W., Galbraith, J. A., Galbraith, C. G., & Betzig, E. (2011). Rapid three-dimensional isotropic imaging of living cells using Bessel beam plane illumination. Nature Methods, 8, 417–423. Scholar
  53. Plaza, S. M., Scheffer, L. K., & Chklovskii, D. B. (2014). Toward large-scale connectome reconstructions. Current Opinion in Neurobiology, 25, 201–210. Scholar
  54. Rubinov, M., & Sporns, O. (2010). Complex network measures of brain connectivity: Uses and interpretations. Neuroimage, 52(3), 1059–1069. Scholar
  55. Scannell, J. W., Blakemore, C., & Young, M. P. (1995). Analysis of connectivity in the cat cerebral cortex. Journal of Neuroscience, 15(2), 1463–1483. Scholar
  56. Schneider-Mizell, C. M., Gerhard, S., Longair, M., Kazimiers, T., Li, F., Zwart, M. F., et al. (2016). Quantitative neuroanatomy for connectomics in Drosophila. Elife, 5.
  57. Shih, C.-T., Sporns, O., Yuan, S.-L., Su, T.-S., Lin, Y.-J., Chuang, C.-C., Wang, T. Y., Lo, C. C., Greenspan, R. J., & Chiang, A. S. (2015). Connectomics-based analysis of information flow in the Drosophila brain. Current Biology, 25, 1249–1258. Scholar
  58. Sporns, O., NetLibrary 10th Shared Collection, & Perpetual eBook Collection. (2011). Networks of the brain (pp. 1 online resource (xi, 412 p., [418] p. of plates)). Cambridge, MA: MIT Press.Google Scholar
  59. Sporns, O., Tononi, G., & Kotter, R. (2005). The human connectome: A structural description of the human brain. PLoS Computational Biology, 1(4), e42. Scholar
  60. Stocker, R. F. (1994). The organization of the chemosensory system in Drosophila melanogaster: A rewiew. Cell and Tissue Research, 275, 3–26. Scholar
  61. Su, T.-S., Lee, W.-J., Huang, Y.-C., Wang, C.-T., & Lo, C.-C. (2017). Coupled symmetric and asymmetric circuits underlying spatial orientation in fruit flies. Nature Communications, 8(1), 139–115. Scholar
  62. Triphan, T., Poeck, B., Neuser, K., & Strauss, R. (2010). Visual targeting of motor actions in climbing Drosophila. Current Biology, 20(7), 663–668. Scholar
  63. Watts, D. J. (1999). Small worlds: The dynamics of networks between order and randomness. Princeton: Princeton University Press.CrossRefGoogle Scholar
  64. Watts, D. J., & Strogatz, S. H. (1998). Collective dynamics of 'small-world' networks. Nature, 393(6684), 440–442. Scholar
  65. Wessnitzer, J., & Webb, B. (2006). Multimodal sensory integration in insects--towards insect brain control architectures. Bioinspiration & Biomimetics, 1(3), 63–75. Scholar
  66. Wu, C. L., Shih, M. F., Lai, J. S., Yang, H. T., Turner, G. C., Chen, L., & Chiang, A. S. (2011). Heterotypic gap junctions between two neurons in the Drosophila brain are critical for memory. Current Biology, 21(10), 848–854. Scholar
  67. 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. Scholar
  68. Zingg, B., Hintiryan, H., Gou, L., Song, M. Y., Bay, M., Bienkowski, M. S., Foster, N. N., Yamashita, S., Bowman, I., Toga, A. W., & Dong, H. W. (2014). Neural networks of the mouse neocortex. Cell, 156(5), 1096–1111. Scholar

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© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Applied PhysicsTunghai UniversityTaichungTaiwan
  2. 2.National Center for High-performance ComputingHsinchuTaiwan
  3. 3.Brain Research CenterNational Tsing Hua UniversityHsinchuTaiwan
  4. 4.Institute of Systems NeuroscienceNational Tsing Hua UniversityHsinchuTaiwan
  5. 5.Institute of Biotechnology and Department of Life ScienceNational Tsing Hua UniversityHsinchuTaiwan
  6. 6.Department of Biomedical Science and Environmental BiologyKaohsiung Medical UniversityKaohsiungTaiwan
  7. 7.Graduate Institute of Clinical Medical ScienceChina Medical UniversityTaichungTaiwan
  8. 8.Institute of Molecular and Genomic MedicineNational Health Research InstitutesZhunanTaiwan
  9. 9.Kavli Institute for Brain and MindUniversity of California at San DiegoLa JollaUSA

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