Digital Implementation of the Retinal Spiking Neural Network under Light Stimulation

Abstract

The visual system is one of the most important pathways of obtaining information for human being and other animals. The retina is responsible for initial processing of visual information and transmitting signals to the second processing system by using the spiking activity patterns. This paper implements a retinal spiking neural network based on field-programmable gate array (FPGA), and uses different scopes of light stimulation to stimulate the digital retinal network and induce different spiking activities. The retina neural network contains 96 neurons, which uses Hodgkin-Huxley type neuron model to build neural network using three-layer feedforward neural network structure. The neural network is implemented using Cyclone IV EP4CE115 FPGA, and uses OV7620 camera to obtain external signals. The state machine control the input information of the retina system, and the firing patterns are finally displayed on oscilloscope device. Experimental results show that the proposed digital retinal network can generate the dual-peak response of the retinal ganglion cells. This work is meaningful for the design of the retina prostheses and is helpful for the investigation of the underlying mechanisms of the retinal activities.