Neural Engineering: Computation, Representation, and Dynamics in Neurobiological Systems

Neural Engineering: Computation, Representation, and Dynamics in Neurobiological Systems

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For years, researchers have used the theoretical tools of engineering to understand neural systems, but much of this work has been conducted in relative isolation. In this text, Chris Eliasmith and Charles Anderson provide a synthesis of the disparate approaches in computational neuroscience, incorporating ideas from neural coding, neural computation, physiology, communications theory, control theory, dynamics, and probability theory. 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 interested in how their quantitative tools relate to the brain.