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Updated: Jun 12, 2026

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
Published on: February 15, 2017
Aspects of neural plasticity in the central nervous system-II. Numerical classification in neuroanatomy
L F Agnati1, M Zoli, F Benfenati
1Institute of Human Physiology, University of Modena, Via Campi 287, 41100 Modena, Italy.
Abstract:
The possibility of using taxonomic techniques to classify neuronal populations was explored. In particular, coefficients of similarity such as the Canberra metric and the Shannon diversity index were examined. The theoretical work in the field of numerical classification was adapted to the aim of characterizing various brain areas in classes according to their transmitter contents. The study of neuropeptide distribution in 15 brain areas clearly demonstrated that, of these, the hypothalamus is particularly noteworthy due to its higher neuropeptide content.
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