The Central Nervous System can be considered as an aggregate of neurons specialized in both the transmission and transfomation of information. Information here has been used for many purposes, but the most important one is probably to generate a representation of the "extenal" world that allows the organism to react properly to changes in its extenal environment. These functions range from such basic ones as detection of changes that may lead to tissue damage and eventual destruction of the organism and the implementation of avoidance reactions to more elaborate representations of the extemal world implying recognition of shapes, sounds and textures as the basis of planned action or even reflection. The question is, how can we hope to understand the complexity inherent in this range of functionalities? One of the distinguishing features of the last two decades has been the availability of computational power that has impacted the many areas of science concerned with this question. An effort has been made within this book to cross boundaries and to have active scientists from different backgrounds and disciplines explain the basic principles which guide their investigations with the hope that this will lay the basis for a future collaborative effort to understand the principles of neural networks.