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Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
Published on: February 15, 2017
New classification methods of branching patterns
Abstract:
Binary branching patterns are described in this paper by their topological structure. The statistical properties of these structures appear to be highly dependent on their growth patterns. As such, observed trees may be used for testing growth models. This paper describes three options in the construction of frequency distributions of topological parameters and their corresponding probability distributions, arising from the terminal and segmental growth models. The construction of these distributions makes the analysis of observed tree structures possible in those experimental conditions where small numbers of observations or differing sizes of trees would form serious obstacles to alternative analytical procedures.
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