This monograph is devoted to the investigation of the dynamics of FitzHugh–Nagumo neuron models, which play a significant role in theoretical neuroscience, applied mathematics, and engineering. Particular attention is given to the study of signal generation modes in a cluster of coupled neuron-like self-oscillatory systems using analytical, numerical, and experimental approaches. The choice of the FitzHugh–Nagumo model is motivated by its ability to capture essential features of excitable neurons with minimal complexity, making it a convenient and powerful tool for analyzing nonlinear phenomena such as bifurcations, chaos, synchronization, and noise-induced effects. The monograph covers a wide range of topics—from the current state of neurodynamics and classical neuron models to the development and study of mathematical, numerical, and electronic models of interacting neural systems. It presents analytical conditions for the emergence of a two-frequency Hopf bifurcation, as well as numerical simulations and experimental implementations of circuits mimicking neural ensembles. This work was conducted within the framework of the research project AP19677321. The results may be of interest to researchers, graduate students, and engineers working in the fields of neuromorphic computing, biomedical devices, and nonlinear system modeling. The authors would like to express their sincere gratitude to everyone who supported this project and hope that the presented material will serve as a foundation for further research in the field of neurodynamics and complex system modeling