Methods in Neuronal Modeling: From Ions to Networks, 2/e (Hardcover)

Description

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.

Christof Koch is Professor of Computation and Neural Systems at the California Institute of Technology and the author of Biophysics of Computation.

 

Table of Contents

Series Foreword

Preface

1   Kinetic Models of Synaptic Transmission

Alain Destexhe, Zachary F. Mainen, and Terrence J. Sejnowski

2   Cable Theory for Dendritic Neurons

Wilfrid Rall and Hagai Agmon-Snir

3   Compartmental Models of Complex Neurons

Idan Segev and Robert E. Burke (appendix by Michael Hines)

4   Multiple Channels and Calcium Dynamics

Walter M. Yamada, Christof Koch, and Paul R. Adams

5   Modeling Active Dendritic Processes in Pyramidal Neurons

Zachary F. Mainen and Terrence J. Sejnowski

6   Calcium Dynamics in Large Neuronal Models

Erik De Schutter and Paul Smolen

7   Analysis of Neural Excitability and Oscillations

John Rinzel and Bard Ermentrout

8   Design and Fabrication of Analog VLSI Neurons

Rodney Douglas and Misha Mahowald

9   Principles of Spike Train Analysis

Fabrizio Gabbiani and Christof Koch

10   Modeling Small Networks

Larry F. Abbott and Eve Marder

11   Spatial and Temporal Processing in Central Auditory Networks

Shihab Shamma

12   Simulating Large Networks of Neurons

Alexander D. Proptopapas, Michael Vanier, and James M. Bower

13   Modeling Feature Selectivity in Local Cortical Circuits

David Hansel and Haim Sompolinsky

14   Numerical Methods for Neuronal Modeling

Michael V. Mascagni and Arthur S. Sherman

References

Contributors

Index