A number of principles of network function are described, including parallelism (the concept that neural computation involves simultaneous interactions of large numbers of neurons), distributed coding (that networks represent information as patterns of activation across neuronal populations rather than activation of single neurons), and incremental learning (a method whereby neural networks "converge" on an optimum distribution of connection weights to perform complex cognitive tasks). These topics have been covered elsewhere (1). The uniqueness of Spitzer’s achievement is his weaving together studies from a range of disciplines—cognitive psychology, animal neurophysiology, and human neuroimaging as well as computer-based neural network simulations—that illuminate these principles in simple and reader-friendly terms. The result is a highly accessible story about the dynamic nature of mind and brain.