I thought readers of bionet.neuroscience might be interested in this
book. For more information, please visit
http://mitpress.mit.edu/0262050714/ Thank you!
Best,
David
Neural Engineering
Computation, Representation, and Dynamics in Neurobiological Systems
Chris Eliasmith and Charles H. Anderson
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 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 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.
The authors present three principles of neural engineering based on the
representation of signals by neural ensembles, transformations of these
representations through neuronal coupling weights, and the integration
of control theory and neural dynamics. Through detailed examples and
in-depth discussion, they make the case that these guiding principles
constitute a useful theory for generating large-scale models of
neurobiological function. oftware package written in MatLab for use with
their methodology, as well as examples, course notes, exercises,
documentation, and other material, are available on the Web.
Chris Eliasmith is Assistant Professor in the Department of Philosophy
and the Department of Systems Design Engineering at the University of
Waterloo. Charles H. Anderson is Research Professor in the Department of
Anatomy and Neurobiology and the Department of Physics at Washington
University, St. Louis.
"In this brilliant volume, Eliasmith and Anderson present a novel
theoretical framework for understanding the functional organization and
operation of nervous systems, from the cellular level to the level of
large-scale networks."
--John P. Miller, Center for Computational Biology, University of
Montana
7 x 9, 376 pp., 104 illus., cloth, ISBN 0-262-05071-4
Computational Neuroscience series
A Bradford Book