Quantifying topological invariants of neuronal morphologies

Lida Kanari, Paweł Dłotko, Martina Scolamiero, Ran Levi, Julian Shillcock, Kathryn Hess, Henry Markram

Research output: Working paper

Abstract

Nervous systems are characterized by neurons displaying a diversity of morphological shapes. Traditionally, different shapes have been qualitatively described based on visual inspection and quantitatively described based on morphometric parameters. Neither process provides a solid foundation for categorizing the various morphologies, a problem that is important in many fields. We propose a stable topological measure as a standardized descriptor for any tree-like morphology, which encodes its skeletal branching anatomy. More specifically it is a barcode of the branching tree as determined by a spherical filtration centered at the root or neuronal soma. This Topological Morphology Descriptor (TMD) allows for the discrimination of groups of random and neuronal trees at linear computational cost.
Original languageEnglish
PublisherArXiv
Pages1-15
Number of pages15
Publication statusSubmitted - 28 Mar 2016

Keywords

  • topological analysis
  • neuronal
  • structures
  • trees
  • morphologies

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    Kanari, L., Dłotko, P., Scolamiero, M., Levi, R., Shillcock, J., Hess, K., & Markram, H. (2016). Quantifying topological invariants of neuronal morphologies. (pp. 1-15). ArXiv. https://arxiv.org/abs/1603.08432