Memristor is a nonlinear electronic component with memory properties, it is widely used in a
variety of nonlinear circuits for extensive adaptive control and model description of neural …

Diffusive intracellular and extracellular ions induce a gradient electromagnetic field that
regulates membrane potential, and energy injection from external stimuli breaks the energy …

The study of dynamics on artificial neurons and neuronal networks is of great significance to
understand brain functions and develop neuromorphic systems. Recently, memristive …

Since the Lorenz chaotic system was discovered in 1963, the construction of chaotic
systems with complex dynamics has been a research hotspot in the field of chaos. Recently …

The magnetic induction effects have been emulated by various continuous memristive
models but they have not been successfully described by a discrete memristive model yet …

Memristors can be employed to mimic biological neural synapses or to describe
electromagnetic induction effects. To exhibit the threshold effect of electromagnetic …

Abstract The biological Hodgkin–Huxley model and its simplified versions have confirmed its
effectiveness for recognizing and understanding the electrical activities in neurons, and …

Dynamical modeling of nervous systems is of fundamental importance in many scientific
fields containing the topics relative to computational neuroscience and biophysics. Many …

Neurons can exhibit abundant electrical activities due to physical effects of various
electrophysiology environments. The electromagnetic induction flows can be triggered by …

In the presence of external stimuli and electromagnetic radiation (EMR), biological neurons
can exhibit different firing patterns and switch to appropriate firing modes because of …