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Updated: Aug 1, 2026

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
Published on: February 15, 2017
Visualization of density relations in large-scale neural networks
1Center for Molecular and Behavioral Neuroscience, Rutgers, The State University of New Jersey, Newark 07102, USA.
Abstract:
The topological organization of interfacing neuronal populations in the basal forebrain of rats was investigated in 3D by using computational methods for extracting information about the spatial distribution of cell densities and density relations. We claim that numerical and spatial constraints imposed by these methods may help to define neuronal clusters in this brain area where simple two-dimensional histology failed to reveal such an arrangement. Neuronal clusters have been suggested in many brain regions as sites of integrative operations. Taking advantage of computerized data acquisition methods in the 3D reconstruction of large cell populations we introduced four basic methods to visualize density relations on simple and combined cell markers: Differential Density 3D Scatter Plot, Iso-relational Scatter plot, Iso-density Surface Rendering and Iso-relational Surface Rendering. These methods are described and exemplified on a 3D neuronal database acquired from mapping different chemically or hodologically defined cell populations in serial sections of the rat basal forebrain.
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