Principles of Computational Modelling in Neuroscience
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Product details:
- Edition number 2, Revised
- Publisher Cambridge University Press
- Date of Publication 5 October 2023
- ISBN 9781108483148
- Binding Hardback
- No. of pages544 pages
- Size 262x210x35 mm
- Weight 1350 g
- Language English 501
Categories
Short description:
Learn to use computational modelling techniques to understand the nervous system at all levels, from ion channels to networks.
MoreLong description:
Taking a step-by-step approach to modelling neurons and neural circuitry, this textbook teaches students how to use computational techniques to understand the nervous system at all levels, using case studies throughout to illustrate fundamental principles. Starting with a simple model of a neuron, the authors gradually introduce neuronal morphology, synapses, ion channels and intracellular signalling. This fully updated new edition contains additional examples and case studies on specific modelling techniques, suggestions on different ways to use this book, and new chapters covering plasticity, modelling extracellular influences on brain circuits, modelling experimental measurement processes, and choosing appropriate model structures and their parameters. The online resources offer exercises and simulation code that recreate many of the book's figures, allowing students to practice as they learn. Requiring an elementary background in neuroscience and high-school mathematics, this is an ideal resource for a course on computational neuroscience.
'This new edition builds superbly on its predecessor. Expository excellence and beautifully clear figures remain, whilst extra material has been added throughout. New chapters cover critical topics such as modelling the way that neural signals are measured, and the details of model optimization and selection. Its impressive combination of depth and breadth makes the text perfect source material for a wide variety of courses.' Peter Dayan, Managing Director, Max-Planck Institute for Biological Cybernetics, Tuebingen
Table of Contents:
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.
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