Before revision:  We develop and analyze features of individual neurons to investigate changes in architectonic differentiation and present a novel high-performance, automated tree-ensemble method trained on data manually labeled by three human investigators. From the location and basic measures of neurons, more complex features are developed and used in machine learning models for automatic segmentation of cortical layers.
After revision:  We develop and analyze features of individual neurons to investigate changes in architectonic differentiation and present a novel high-performance, automated framework for neuron-level histological image analysis. Local tissue and cell descriptors such as density, neuron size and other measures are used for development of more complex neuron features used in machine learning models for automatic segmentation of cortical layers.