Multiplier-less and compact FPGA implementation of Mihalas-Niebur neuron

The modified Mihalas-Niebur neuron model suitable for a compact digital implementation is presented. Based on the modified model, a multiplier-less and compact Mihalas-Niebur neuron that uses word-length optimization and bitwise shifting operators for the multiplication was designed and implemented on an FPGA. The simulation results show that the proposed neuron successfully produces all 20 prominent spiking patterns with a few FPGA resources used.