Since McCullough and Pitts first published their work on the Binary Decision Neuron much research has been accumulated in the area of neural networks. This work has for the most part centred on network topologies and learning algorithms. The neural networks that have found their way into devices such as handheld PC’s are the fruit of NN research that has spanned 57 years. There is a simplistic beauty in the way that artificial neural networks model the biological foundations of the human thought process, but one piece of the jigsaw puzzle is still missing. We have so far been unable to match the massive parallelness of the human brain. This paper attempts to explain how multithreaded neural networks can be used as a basis for building parallel networks. By studying simple concurrent networks is hoped that significant inroads can be made into a better understanding of how neural network processing can be spread across multiple processors. The paper outlines some biological foundations and introduces some approaches that may be used to recreate software implementations of concurrent artificial neural networks.