Memristor-based model of neuronal excitability and synaptic potentiation.

In this manuscript, we investigate the memristor-based implementation of neuronal ion channels in a mathematical model and an experimental circuit for a neuronal oscillator. We used a FitzHugh-Nagumo equation system describing neuronal excitability. Non-linearities introduced by the voltage-gated ion channels were modeled using memristive devices.

Stochastic Memristive Interface for Neural Signal Processing.

We propose a memristive interface consisting of two FitzHugh-Nagumo electronic neurons connected via a metal-oxide (Au/Zr/ZrO(Y)/TiN/Ti) memristive synaptic device. We create a hardware-software complex based on a commercial data acquisition system, which records a signal generated by a presynaptic electronic neuron and transmits it to a postsynaptic neuron through the memristive device. We demonstrate, numerically and experimentally, complex dynamics, including chaos and different types of neural synchronization.