I. Introduction
Freeman K-sets form a hierarchy of neuron populations models and correspond to a mesoscopic (intermediate) approach between the microscopic activity of individual neurons and the macroscopic activity of the brain [1], [2]. A hierarchy of models is constructed from a basic unit representing a population of thousands of neurons, modeled by an ordinary differential equation (ODE). From this base unit, networks of greater neural complexity are constructed (Fig. 1).