David Sterratt

Principles of Computational Modelling in Neuroscience (eBook, PDF)

• Format: PDF

Produktbeschreibung

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.

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Produktdetails

• Verlag: Cambridge University Press
• Erscheinungstermin: 30. Juni 2011
• Englisch
• ISBN-13: 9781139037099
• Artikelnr.: 53186515

Autorenporträt

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.

Inhaltsangabe

Preface
Acknowledgements
List of abbreviations 1. Introduction
2. The basis of electrical activity in the neuron
3. The Hodgkin¿Huxley model of the action potential
4. Models of active ion channels
5. Modelling neurons over space and time
6. Intracellular mechanisms
7. The synapse
8. Simplified models of the neuron
9. Networks of neurons
10. Brain tissue
11. Plasticity
12. Development of the nervous system
13. Modelling measurements and stimulation
14. Model selection and optimisation
15. Farewell
References
Index.