Circuit implementation of FitzHugh-Nagumo neuron model using Field Programmable Analog Arrays

A simple neuron model, the FitzHugh-Nagumo (FHN) model, is implemented on Field Programmable Analog Arrays (FPAAs). The differential equations of the model is integrated by making arithmetic operations on the reconfigurable voltage model circuits of the FPAAs. The simulation and implementation results demonstrate that FPAA is the viable candidate for the neuron hardware implementation in real time or many orders of magnitude faster.