Networks of Excitable Neurons

Abstract

In this chapter, networks of excitable neurons are discussed. The basic catecholamine neurotransmitters are primary building blocks in such networks and some of their details are presented. A treatment of basic modeling issues that arise in a neural network of computational nodes then follows. It is argued that software and hardware in such a network are linked in irreducible ways and that this knowledge must influence the design of the software architectures used to build neural simulations. Next, the catecholamine abstraction is discussed and the details of a single neuron’s processing are outlined in terms on post synaptic density (PSD) functions. Then, networks of neural objects are outlined in terms of chains of computational nodes with feedforward and feedbackward connections. The node processing at this point is quite simple and is done using sigmoidal calculations based on inputs into the node. The node output is the the sigmoid value. Finally, details of neural processing are given for nodes in a chain.