The electric activities of neurons are dependent on the complex electrophysiological condition in neuronal system, and it indicates that the complex distribution of electromagnetic field could be detected in the neuronal system. According to the Maxwell electromagnetic induction theorem, the dynamical behavior in electric activity in each neuron can be changed due to the effect of internal bioelectricity of nervous system (e.g., fluctuation of ion concentration inside and outside of cell). As a result, internal fluctuation of electromagnetic field is established and the effect of magnetic flux across the membrane should be considered during the emergence of collective electrical activities and signals propagation among a large set of neurons. In this paper, the variable for magnetic flow is proposed to improve the previous Hindmarsh–Rose neuron model; thus, a four-variable neuron model is designed to describe the effect of electromagnetic induction on neuronal activities. Within the new neuron model, the effect of magnetic flow on membrane potential is described by imposing additive memristive current on the membrane variable, and the memristive current is dependent on the variation of magnetic flow. The dynamics of this modified model is discussed, and multiple modes of electric activities can be observed by changing the initial state, which indicates memory effect of neuronal system. Furthermore, a practical circuit is designed for this improved neuron model, and this model could be suitable for further investigation of electromagnetic radiation on biological neuronal system.

Model of electrical activity in a neuron under magnetic flow effect

The biological Hodgkin–Huxley model and its simplified versions have confirmed its effectiveness for recognizing and understanding the electrical activities in neurons, and bifurcation analysis is often used to detect the mode transition in neuronal activities. Within the collective behaviors of neurons, neuronal network with different topology is designed to study the synchronization behavior and spatial pattern formation. In this review, the authors give careful comments for the presented neuron models and present some open problems in this field, nonlinear analysis could be effective to further discuss these problems and some results could be helpful to give possible guidance in the field of neurodynamics.

A review for dynamics in neuron and neuronal network

Multiple modes of electrical activities in a new neuron model under electromagnetic radiation

The nervous system is composed of a large number of neurons, and the electrical activities of neurons can present multiple modes during the signal transmission between neurons by changing intrinsic bifurcation parameters or under appropriate external forcing. In this review, the dynamics for neuron, neuronal network is introduced, for example, the mode transition in electrical activity, functional role of autapse connection, bifurcation verification in biological experiments, interaction between neuron and astrocyte, noise effect, coherence resonance, pattern formation and selection in network of neurons. Finally, some open problems in this field such as electromagnetic radiation on electrical activities of neuron, energy consumption in neurons are presented.

A review for dynamics of collective behaviors of network of neurons

Phase synchronization between two neurons induced by coupling of electromagnetic field

Autapse connected to the neuron can change the electric activity of neuron. The effect of autapse on neuronal activity is often described by adding an additive forcing current along a close loop, which is described by a time-delayed feedback on the membrane potential. Neuron often responds to electric autapse forcing sensitively and quickly, while the chemical autapse changes the electric activity of neuron slowly. By applying external forcing, a shift transition of electric activity can be more easily induced by the electric autapse than the chemical autapse. Our results confirm that chemical autapse can enhance and/or suppress the transition of electric activity with excitable or inhibitory type driven by electric autapse, vice versa. It indicates that an appropriate switch-off-on for autapse can make the neuron give different types of response to external forcing. Particularly, cooperation and competition between chemical and electric autapse help neuron response to external forcing in the most reliable way.

Tang Jun

Papers

A review for dynamics of collective behaviors of network of neurons

Transition of electric activity of neurons induced by chemical and electric autapses