A novel memristive neuron model and its energy characteristics

The functional neurons are basic building blocks of the nervous system and are responsible for transmitting information between different parts of the body. However, it is less known about the interaction between the neuron and the field. In this work, we propose a novel functional neuron by introducing a flux-controlled memristor into the FitzHugh-Nagumo neuron model, and the field effect is estimated by the memristor. We investigate the dynamics and energy characteristics of the neuron, and the stochastic resonance is also considered by applying the additive Gaussian noise. The intrinsic energy of the neuron is enlarged after introducing the memristor. Moreover, the energy of the periodic oscillation is larger than that of the adjacent chaotic oscillation with the changing of memristor-related parameters, and same results is obtained by varying stimuli-related parameters. In addition, the energy is proved to be another effective method to estimate stochastic resonance and inverse stochastic resonance. Furthermore, the analog implementation is achieved for the physical realization of the neuron. These results shed lights on the understanding of the firing mechanism for neurons detecting electromagnetic field.