Multiple perspectives on the hardware implementations of biological neuron models and programmable design aspects

Abstract

A few individual design examples of programmable device-based biological neuron model implementations are available in the literature, but there is no comprehensive study that examines analog and digital programmable design examples of frequently studied biological neuron model implementations. The aim of this paper is to present a comparative study about programmable and reconfigurable implementations of the FitzHugh--Nagumo, Izhikevich, and Hindmarsh--Rose neuron models. Since field programmable analog array (FPAA) and field programmable gate array (FPGA) devices offer several advantages such as flexible design possibilities, reduction of the complexity of design, real-time modification, and software control for programmable and reconfigurable implementations of neuron models and neural structures, they are preferred in these implementations as analog and digital programmable devices. Experimental results agree with the numerical simulations and verify the design effectiveness of FPAA- and FPGA-based implementations.