Principles of computational modelling in neuroscience
著者
書誌事項
Principles of computational modelling in neuroscience
Cambridge University Press, 2011
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注記
Includes bibliographical references (p. [351]-381) and index
Other authors: Bruce Graham, Andrew Gillies and David Willshaw
内容説明・目次
内容説明
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.
目次
- 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.
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