A study on self organization of spiking neural network

- Unified processing model for static and dynamic information-

Abstract

This study aims to propose a unified processing model for static information and dynamic information with Spiking Neural Network. We implemented a two-types of a ganglion cell model (P-type, and M-type) to leaky integrate and fire model(leaky-IF) and adopt these model to CNN architecture. Simulated result showed that, P-type model responded to static information (e.g. edges, corners), and M-type model responded to dynamic information (e.g. motion, rotation).