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Neuroinformatics

Erschienen in:

01.09.2009

The Tree-Edit-Distance, a Measure for Quantifying Neuronal Morphology

verfasst von: Holger Heumann, Gabriel Wittum

Erschienen in: Neuroinformatics | Ausgabe 3/2009

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Abstract

The shape of neuronal cells strongly resembles botanical trees or roots of plants. To analyze and compare these complex three-dimensional structures it is important to develop suitable methods. We review the so called tree-edit-distance known from theoretical computer science and use this distance to define dissimilarity measures for neuronal cells. This measure intrinsically respects the tree-shape. It compares only those parts of two dendritic trees that have similar position in the whole tree. Therefore it can be interpreted as a generalization of methods using vector valued measures. Moreover, we show that our new measure, together with cluster analysis, is a suitable method for analyzing three-dimensional shape of hippocampal and cortical cells.

Vorheriger Artikel Spike Train Analysis Toolkit: Enabling Wider Application of Information-Theoretic Techniques to Neurophysiology

Nächster Artikel On Comparing Neuronal Morphologies with the Constrained Tree-edit-distance

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Titel: The Tree-Edit-Distance, a Measure for Quantifying Neuronal Morphology
verfasst von: Holger Heumann
Gabriel Wittum
Publikationsdatum: 01.09.2009
Verlag: Humana Press Inc
Erschienen in: Neuroinformatics / Ausgabe 3/2009
Print ISSN: 1539-2791
Elektronische ISSN: 1559-0089
DOI: https://doi.org/10.1007/s12021-009-9051-4

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