Application of cluster analysis in morphological characteristics of neurons - ZHANG Jing; DENG Shi-huai; GUO Hang; SHEN Fei; GU Wei-gang; LI Yuan-wei (浙江大学学报. 农业与生命科学版)
Base on the data for three dimensional (3D) coordinate of 49 neurons, 16 morphological parameters were obtained by calculation. According to the factor analysis of the morphological parameters, three major characteristics, including dimension, degree of divergence and growths were obtained and chosen for classification. ward's method was applied in the system cluster analysis. The results showed that the neurons could be classified into 5 grades, including motoneuron, bipolar interneuron, cone neuron, multipolar interneuron and tripolar interneuron, when the Euclidean distance was about 1.5; additionally, the development degree of neurons affected the classification results of sensory neuron, tripolar interneuron and multipolar interneuron morphology, therefore, in the process of classification in morphology, it should be used mature neurons to avoid to cause interference.