Much research focuses on the question of how information is
processed in nervous systems, from the level of individual ionic
channels to large-scale neuronal networks, and from "simple"
animals such as sea slugs and flies to cats and primates. New
interdisciplinary methodologies combine a bottom-up experimental
methodology with the more top-down-driven computational and
modeling approach. This book serves as a handbook of computational
methods and techniques for modeling the functional properties of
single and groups of nerve cells.The contributors highlight several
key trends: (1) the tightening link between analytical/numerical
models and the associated experimental data, (2) the broadening of
modeling methods, at both the subcellular level and the level of
large neuronal networks that incorporate real biophysical
properties of neurons as well as the statistical properties of
spike trains, and (3) the organization of the data gained by
physical emulation of the nervous system components through the use
of very large scale circuit integration (VLSI) technology.The field
of neuroscience has grown dramatically since the first edition of
this book was published nine years ago. Half of the chapters of the
second edition are completely new; the remaining ones have all been
thoroughly revised. Many chapters provide an opportunity for
interactive tutorials and simulation programs. They can be accessed
via Christof Koch's Website.Contributors: Larry F. Abbott, Paul R.
Adams, Hagai Agmon-Snir, James M. Bower, Robert E. Burke, Erik de
Schutter, Alain Destexhe, Rodney Douglas, Bard Ermentrout, Fabrizio
Gabbiani, David Hansel, Michael Hines, Christof Koch, Misha
Mahowald, Zachary F. Mainen, Eve Marder, Michael V. Mascagni,
Alexander D. Protopapas, Wilfrid Rall, John Rinzel, Idan Segev,
Terrence J. Sejnowski, Shihab Shamma, Arthur S. Sherman, Paul
Smolen, Haim Sompolinsky, Michael Vanier, Walter M. Yamada.
General
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