Neural engineering computation, representation, and dynamics in neurobiological systems
By Chris Eliasmith, C. H. Anderson


For years, researchers have used the theoretical tools of engineering to know neural systems, but much of this work has been conducted in relative isolation. In Neural Engineering, Chris Eliasmith and Charles Anderson provide a synthesis of the disparate approaches current in computational neuroscience, incorporating ideas from neural coding, neural computation, physiology, communications theory, control theory, dynamics, and applied mathematics. This synthesis, they argue, enables novel theoretical and practical insights into the functioning of neural systems. Such insights are pertinent to experimental and computational neuroscientists and to engineers, physicists, and computer scientists curious about how their quantitative tools related to the brain.