Scalable Biologically Inspired Neural Networks with Spike Time Based Learning

This paper describes the software and algorithmic issues involved in developing scalable large-scale biologically inspired spiking neural networks. These neural networks are useful in object recognition and signal processing tasks, but will also be useful in simulations to help understand the human brain. The software is written using object oriented programming and is very general and usable for processing a wide range of sensor data and for data fusion.