Quantifying Neuronal Morphology: A Case Study of the Growth Model Approach
نویسندگان
چکیده
Morphological data on two classes of superior colliculus (SC) neurons have quantitatively been analyzed for dendritic shape parameters. Their frequency distributions were used to optimize the parameters of a dendritic growth model which describes dendritic morphology by a stochastic growth process of segment branching and elongation. Model-generated trees have shape properties closely matching the observed ones. The dendritic trees of each of the two classes of SC neurons are represented by a specific set of growth model parameters, thus achieving morphological data compression.
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