Methods in Neuronal Modeling

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.