Brain Structure and Function

, Volume 223, Issue 3, pp 1107–1120 | Cite as

Morphological determinants of dendritic arborization neurons in Drosophila larva

  • Sumit Nanda
  • Ravi Das
  • Shatabdi Bhattacharjee
  • Daniel N. Cox
  • Giorgio A. Ascoli
Original Article


Pairing in vivo imaging and computational modeling of dendritic arborization (da) neurons from the fruit fly larva provides a unique window into neuronal growth and underlying molecular processes. We image, reconstruct, and analyze the morphology of wild-type, RNAi-silenced, and mutant da neurons. We then use local and global rule-based stochastic simulations to generate artificial arbors, and identify the parameters that statistically best approximate the real data. We observe structural homeostasis in all da classes, where an increase in size of one dendritic stem is compensated by a reduction in the other stems of the same neuron. Local rule models show that bifurcation probability is determined by branch order, while branch length depends on path distance from the soma. Global rule simulations suggest that most complex morphologies tend to be constrained by resource optimization, while simpler neuron classes privilege path distance conservation. Genetic manipulations affect both the local and global optimal parameters, demonstrating functional perturbations in growth mechanisms.


Neuronal development Molecular neurogenetics Confocal microscopy Morphological reconstructions Computational modeling 



The authors sincerely thank Cox Lab members Sarah G. Clark and Atit A. Patel for the image stack generation; and Ascoli Lab members Griffin Badalamente, Alisha Compton, Anna Lulushi and Margaret Kirtley for help with neuronal reconstructions; Rubén Armañanzas for ideas and brain storming; and Diek Wheeler for critical review of the manuscript. Supported by National institute of Health: NIH NS39600, NIH NS086082, NIH MH086928 and National Science Foundation: NSF DBI1546335 and NSF BCS1663755. Stocks obtained from the Bloomington Drosophila Stock Center (NIH P40OD018537) were used in this study.

Supplementary material

429_2017_1541_MOESM1_ESM.pptx (1.7 mb)
Supplementary material 1 (PPTX 1699 kb)


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Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  • Sumit Nanda
    • 1
  • Ravi Das
    • 2
  • Shatabdi Bhattacharjee
    • 2
  • Daniel N. Cox
    • 2
  • Giorgio A. Ascoli
    • 1
  1. 1.Center for Neural Informatics, Structures, and Plasticity, Krasnow Institute for Advanced StudyGeorge Mason UniversityFairfaxUSA
  2. 2.Neuroscience InstituteGeorgia State UniversityAtlantaUSA

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