, Volume 40, Issue 4, pp 310–315 | Cite as

Neuronal Morphology: Shape Characteristics and Models

Proceedings of the International School “Problems of Experimental, Clinical, and Theoretical Neurosciences” (Dnepropetrovsk, Ukraine, May 2–4, 2008)
  • A. SchierwagenEmail author

This paper is focused on quantification (morphometry) and modeling of neuronal morphological complexity. First, computer-aided methods for reconstruction, processing, and analysis of raw morphological data are reviewed. Then, topological and metrical measures are touched upon. Fractal measures (together with the extension of multiscale fractal dimension) are presented more explicitly. Models of neuronal arborizations are differentiated between reconstruction models and growth models (stochastic or mechanistic). The growth model approach is discussed in more detail. The methods presented are applied to several types of neurons and shown to have considerable discriminative power. Recent developments stress the importance of these methods for optimizing virtual neuronal trees in view of functional characteristics of the neurons.


neuronal morphology neuromorphometry fractal analyses growth models 


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Copyright information

© Springer Science+Business Media, Inc. 2008

Authors and Affiliations

  1. 1.Institute for Computer ScienceUniversity of LeipzigLeipzigGermany

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