Quantifying topological invariants of neuronal morphologies

Resource type
Authors/contributors
Title
Quantifying topological invariants of neuronal morphologies
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.
Publication
arXiv:1603.08432 [cs, math, q-bio]
Date
2016-03-28
Accessed
2019-11-22T19:59:32Z
Library Catalog
Extra
ZSCC: 0000005 arXiv: 1603.08432
Notes
Comment: 10 pages, 5 figures, conference or other essential info
Citation
Hess, K., Kanari, L., Dłotko, P., Scolamiero, M., Levi, R., Shillcock, J., & Markram, H. (2016). Quantifying topological invariants of neuronal morphologies. ArXiv:1603.08432 [Cs, Math, q-Bio]. Retrieved from http://arxiv.org/abs/1603.08432
BIOLOGY, NEUROSCIENCE & PSYCHOLOGY
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