We explore the concept of constructing microscopic electronic neurons that mimic natural brain systems in order to create brain-inspired computational artificial systems. We discuss the essential material and device properties required for these spiking neurons, which can be characterized using impedance spectroscopy and small perturbation equivalent circuit elements. We identify the structural conditions necessary for smooth oscillations, which depend on the dynamics of a conducting system with internal state variables. We emphasize the significance of detecting the Hopf bifurcation, a critical point for achieving spiking behavior, through spectral features of the impedance. The state variables can have diverse physical properties, such as fluids, electronic solids, or ionic organic materials, indicating that functional neurons can be built in various ways. Our findings reveal that the minimal neuron system requires a capacitor, a chemical inductor, and a negative resistance, which can be integrated into the physical response of the device rather than being built from separate circuit elements. Thus, we propose a method to quantify the physical and material properties of devices in order to produce the dynamic properties of neurons that are necessary for a specific computational scheme. We present a novel approach towards building brain-inspired artificial systems and provides insights into the important material and device considerations for achieving spiking behavior in electronic neurons.1,2 (1) Bisquert, J. Hopf bifurcations in electrochemical, neuronal, and semiconductor systems analysis by impedance spectroscopy, Appl. Phys. Rev. 2022, 9, 011318. (2) Bisquert, J. Device physics recipe to make spiking neurons Chemical Physics Reviews 2023, 4, submitted.
