Design and implementation of Izhikevich spiking neuron model on FPGA

The elementary processing units in brain are neurons which are connected to each other in many shapes and sizes. A typical neuron can be divided into functionally three distinct parts called Dendrites, Soma and Axon. Dendrites play the role of input device that collect signals from other neurons and transmits them to soma. Soma performs a Non-linear operation, i.e. if input exceeds a certain threshold, an output signal is generated. This output signal is taken over by an output device, the Axon, which delivers the signal to other neurons. This is the basic function of a biological neuron. A biological neuron model which is also known as Spiking Neuron Model is a mathematical description of properties of neuron that is to be designed accurately to describe and predict the biological processes. So there comes the concept of modelling and analysis of neurons. Modelling and analysis of neurons was performed by different researchers on First, Second and Third generation of neurons. The Third generation of neurons are also called as spiking neurons. The focus of this work is to present different types of spiking neurons developed by Izhikevich which mathematically supports the properties and resembles the biological neuron. These mathematical model simulations are done in MATLAB. These spiking neurons are modelled using digital logic circuits in Verilog Hardware Description Language (HDL) and simulated in ModelSIM RTL simulator. The design is then implemented in Xilinx FPGA and checked for the functionality.