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Measuring and Modeling Morphology: How Dendrites Take Shape

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Computational Systems Neurobiology

Abstract

Neuronal processes grow under a variety of constraints, both immediate and evolutionary. Their pattern of growth provides insight into their function. This chapter begins by reviewing morphological metrics used in analyses and computational models. Molecular mechanisms underlying growth and plasticity are then discussed, followed by several types of modeling approaches. Computer simulation of morphology can be used to describe and reproduce the statistics of neuronal types or to evaluate growth and functional hypotheses. For instance, models in which branching is probabilistically determined by diameter produce realistic virtual dendrites of most neuronal types, though more complicated statistical models are required for other types. Virtual dendrites grown under environmental and/or functional constraints are also discussed, offering a broad perspective on dendritic morphology.

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Authors and Affiliations

  1. Center for Neural Informatics, Structures, & Plasticity; and Molecular Neuroscience Department, Krasnow Institute for Advanced Study, MS2A1 George Mason University, Fairfax, Fairfax, VA, 22030, USA

    Todd A. Gillette & Giorgio A. Ascoli

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  1. Todd A. Gillette
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  2. Giorgio A. Ascoli
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Editors and Affiliations

  1. European Bioinformatics Institute, EMBL-Outstation-Hinxton, Wellcome Trust Genome Campus, Welcome-Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, United Kingdom

    N. Le Novère

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Gillette, T.A., Ascoli, G.A. (2012). Measuring and Modeling Morphology: How Dendrites Take Shape. In: Le Novère, N. (eds) Computational Systems Neurobiology. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-3858-4_13

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