The Binary Images of Aspiny Neurons from the Human Neostriatum: Cluster Classification Using Parameters of Monofractal Analysis

Abstract

The striatum (i.e. neostriatum) is one of the principal components of the basal ganglia. It is complex structure which consists of the three nuclei. Human striatum neurons firstly can be visually classified into two types (spiny and aspiny), but further classification recognizes two subgroups of spiny, and three subgroups of aspiny neurons. The original goal of this study is to confirm or improve the existing division of striatal neurons using two main techniques of cluster analysis. A total of 175 two dimensional images of aspiny neurons have been captured by the light microscope, and recorded with accompanying digital camera. Specialized public software Image J has been used for both image reconstruction and measurement. Each binary image of the neuron have been quantified with apparent parameters of monofractal analysis. Hierarchical cluster analysis and k-cluster method classified two existing groups of aspiny cells into three classes. Moreover, the morphometric difference in all groups between two functional different nuclei were reported. To the best of our knowledge, the presence of neuronal types in the adult human neostriatum has thus far been established and described mainly with Euclidean parameters. Thus, the present study, quantifies cells with monofractal parameters only. In the present study, only two types of aspiny neurons were used. But two techniques of cluster analysis found three groups of neurons. This results need to be verified with same classification technique, but using different computational parameters. Finally, the present study offer vague conclusion regarding difference in cell types between two cores of dorsal lamina.