A chaotic memristive Hindmarsh-Rose neuron with hybrid offset boosting

In recent years, memristor has been widely introduced into neuronal models to simulate magnetically induced currents. However, there are relatively few studies on electric field stimulation of neuronal models. This paper presents a 4D memristive Hindmarsh-Rose (HR) neuron model that introduces a sinusoidal function memristor and electric field variables, which can produce heterogeneous multistability and homogeneous multistability. More interestingly, six modes of offset boosting can be triggered in the neuronal model by varying the electric field coupling coefficients, the first three of which are parameter-dependent two-dimensional offset boosting modes, and the second three are initial-value-dependent offset-boosting modes. Notably, homogeneous multistability can also combined with the offset-boosting, and then iterating cubic infinitely many attractors. This model presents a model where multiple offset boosting is freely controllable for the first time. Finally, the theoretical analysis is verified by digital circuits on a RISC-V platform.