Simulation of the visual cortex with laterally connected spiking neural networks

In this paper we present the spiking neural networks (RF-LCSNN) with laterally connected neurons to simulate the visual cortex. The synapses in our model are leaky integrators that sum incoming activation over time with exponential decay. The networks of such neurons can segment multiple objects in a scene by synchronizing neuronal group activity. The architecture and organization of the neural networks have been explained in some detail. Several simulation experiments have been done to show the capability of RF-LCSNN: self-organization and object segmentation of the visual input.