Principles of Computational Modelling in Neuroscience

How to use techniques of computational modelling to understand the nervous system at all levels from ion channels to networks.

The nervous system is made up of a large number of interacting elements. To understand how such a complex system functions requires the construction and analysis of computational models at many different levels. This book provides a step-by-step account of how to model the neuron and neural circuitry to understand the nervous system at all levels, from ion channels to networks. Starting with a simple model of the neuron as an electrical circuit, gradually more details are added to include the effects of neuronal morphology, synapses, ion channels and intracellular signalling. The principle of abstraction is explained through chapters on simplifying models, and how simplified models can be used in networks. This theme is continued in a final chapter on modelling the development of the nervous system. Requiring an elementary background in neuroscience and some high school mathematics, this textbook is an ideal basis for a course on computational neuroscience.

Preface; 1. Introduction; 2. The basis of electrical activity in the neuron; 3. The Hodgkin Huxley model of the action potential; 4. Compartmental models; 5. Models of active ion channels; 6. Intracellular mechanisms; 7. The synapse; 8. Simplified models of neurons; 9. Networks; 10. The development of the nervous system; Appendix A. Resources; Appendix B. Mathematical methods; References.

For neuroscientists at all levels and for people from the informational and physical sciences who want to develop computational models of the neuron and neural circuits. It presents the principles of computational neuroscience in a clear and coherent manner, and addresses practical issues that arise in modelling projects.

David Sterratt is a Research Fellow in the School of Informatics at the University of Edinburgh. His computational neuroscience research interests include models of learning and forgetting, and the formation of connections within the developing nervous system.
Bruce Graham is a Reader in Computing Science in the Department of Computing Science and Mathematics at the University of Stirling. Focusing on computational neuroscience, his research covers nervous system modelling at many levels.
Andrew Gillies works at Psymetrix Limited, Edinburgh. He has been actively involved in computational neuroscience research.
David Willshaw is Professor of Computational Neurobiology in the School of Informatics at the University of Edinburgh. His research focuses on the application of methods of computational neurobiology to an understanding of the development and functioning of the nervous system.