This book summarizes in some detail the ideas, techniques and results developed in the last 5-6 years in the physics community about the collective properties of large assemblies of neurons. The subject has been, and still is, a source of great excitement among physicists the world over and new original ideas are generated incessantly. This enthusiasm has produced a wealth of new concepts and new detailed results which has not gone unnoticed outside physics departments. Biologists have begun to ask themselves whether the properties that physics anticipates in neural networks can indeed be observed and whether they provide useful theoretical guides for the empirical investigation of brain activity; computer scientists would not rule out these ideas as candidates for coherent parallel processing; psychologists and neurologists have been expecting some new useful metaphors for interpreting behavioral disfunction; cognitive scientists study the new concepts in their continued struggle with the elusiveness of processes of mind, even on the most elementary levels; and technologists have added, of course, Attractor Neural Networks to the list of future industries for sale.

One explanation for this impact of the study of neural networks seems to be in the type of new concepts that have been generated. They appear plausible upon introspection and they are based on elements with biological flavor. Another attraction is the clarity, the wealth and the detail provided by the quantitative analysis of the properties of such networks.