Design and implementation of Hodgkin and Huxley spiking neuron model on FPGA

Abstract

The rudimentary cells of the central nervous system are the neurons which are connected to each other. An ordinary neuron consists of three different parts Dendrites, Soma and Axon. Each part is having its role in transferring the information. The connection between the neurons can be either Dendrite-Axon or Dendrite-Dendrite or Axon-Axon. Dendrites have the pivotal role in collecting the signals from other neurons and transmitting them to soma which implies that the dendrites act as an input device to the neuron. Soma performs a Non-linear operation, i.e. if input exceeds a certain threshold, an output signal is generated. The Axon performs the role of an output device which takes the processed signal from soma and transmitting it to the 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 objective of this work is to implement different types of spiking neuron models developed by Hodgkin and Huxley which is a biological model. The spiking neuron model simulations are done in MATLAB and they are modelled using digital logic circuits in Verilog Hardware Description Language (HDL) and simulated in ModelSIM RTL simulator. These models are then implemented in Xilinx FPGA and checked for the functionality.