Adaptive mode selection of electrical activities in a neuron with a memristive ion channel

From the dynamic point of view, an ion channel for a biology neuron can be estimated by applying an induction coil in a neural circuit, and the influence of the inner and outer magnetic field on the ions' propagation is also estimated. The magnetic field generated by the magnetic flux-controlled memristor (MFCM) is equivalent to that stored in the induction coil. Therefore, the magnetic field in the neural circuit can be estimated using an MFCM. In this work, a neural circuit of the memristive characteristic ion channel is designed by applying an MFCM to replace the inductor branch of a simple neural circuit, and this memristive ion channel can estimate the influence of the magnetic field on the firing patterns of a neuron. The equivalent oscillator equations for the neural circuit and the corresponding energy function are calculated by the Kirchhoff's theorem and the Helmholtz theory, respectively. Furthermore, to explore the adaptive regulation of the electrical activity of the neuron by energy flow, a parameter adaptive growth criterion controlled by energy ratio is designed. The numerical results indicate that the MFCM can effectively simulate the ion channels of biological neurons, the firing modes of a neuron model with an ion memristive channel are adjusted by the magnetic field distribution, and the stochastic resonance of a neuron can be induced under a suitable noise magnetic field. This study would provide guidance for the simulation of neural circuit ion channels.