Reservoir computing shows partial statistical dynamics prediction of two coupled stochastic FitzHugh-Nagumo neurons

We train a reservoir computing-based echo state network to predict the stochastic dynamics of two coupled FitzHugh-Nagumo neurons excited by external Gaussian noise. We describe the design principles of the echo state network and the coupled oscillator network. Results show that prediction quality of the dynamics of each neuron varies despite their high coupling strength.