Principles of Computational Modelling in Neuroscience
$68.00 ( ) USD
- David Sterratt, University of Edinburgh
- Bruce Graham, University of Stirling
- Andrew Gillies, Psymetrix Limited, Edinburgh
- David Willshaw, University of Edinburgh
Adobe eBook Reader
Other available formats:
Looking for an examination copy?
If you are interested in the title for your course we can consider offering an examination copy. To register your interest please contact email@example.com providing details of the course you are teaching.
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 signaling. 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 modeling 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.Read more
- Presents models in the context of the underlying biology and biophysics, enabling readers to engage with and understand their relevance
- Complex mathematical details are highlighted and explained in boxes alongside the main text, so that readers can follow the discussion easily and clearly
- Associated website (www.compneuroprinciples.org) provides sample codes and up-to-date links to external resources, such as simulators and databases
Reviews & endorsements
"Here at last is a book that is aware of my problem, as an experimental neuroscientist, in understanding the maths, the book helps me deal with it with the patience that the team always showed to students and professors alike. I expect it to be as mind expanding as my involvement with its authors was over the years. I only wish I had had the whole book sooner – then my students and post-docs would have been able to understand what I was trying to say and been able to derive the critical tests of the ideas that only the rigor of the mathematical formulation of them could have generated."
Gordon W. Arbuthnott, Okinawa Institute of Science and TechnologySee more reviews
"This is a wonderful, clear and compelling text on mathematically-minded computational modelling in neuroscience. It is beautifully aimed at those engaged in capturing quantitatively, and thus simulating, complex neural phenomena at multiple spatial and temporal scales, from intracellular calcium dynamics and stochastic ion channels, through compartmental modelling, all the way to aspects of development. It takes particular care to define the processes, potential outputs and even some pitfalls of modelling; and can be recommended for containing the key lessons and pointers for people seeking to build their own computational models. By eschewing issues of coding and information processing, it largely hews to concrete biological data, and it nicely avoids sacrificing depth for breadth. It is very suitably pitched as a Master's level text, and its two appendices, on mathematical methods and software resources, will rapidly become dog-eared."
Peter Dayan, University College London
"This book has done a nice job of laying out their strategy or covering major topics in the field of computational neuroscience while maintaining a well-organized structure. It is prepared for both expert and non-expert readers with an elementary background in neuroscience and some high school mathematics. This is a timely, well-written book that provides a comprehensive, in-depth and state-of-the-art coverage of computational modeling in neuroscience. It can serve as an excellent text for a graduate level course in computational neuroscience, as well as a valuable reference for experimental neuroscientists, computational neuroscientists and people working in relevant areas such as neuroinformatics and systems biology."
Li Shen, Briefings in Bioinformatics
Not yet reviewed
Be the first to review
Review was not posted due to profanity×
- Date Published: May 2011
- format: Adobe eBook Reader
- isbn: 9781139037099
- contains: 178 b/w illus. 7 tables
- availability: This item is not supplied by Cambridge University Press in your region. Please contact eBooks.com for availability.
Table of Contents
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
10. The development of the nervous system
Appendix A. Resources
Appendix B. Mathematical methods
Welcome to the resources site
Here you will find free-of-charge online materials to accompany this book. The range of materials we provide across our academic and higher education titles are an integral part of the book package whether you are a student, instructor, researcher or professional.
Find resources associated with this titleYour search for '' returned .
Type Name Unlocked * Format Size
*This title has one or more locked files and access is given only to instructors adopting the textbook for their class. We need to enforce this strictly so that solutions are not made available to students. To gain access to locked resources you either need first to sign in or register for an account.
These resources are provided free of charge by Cambridge University Press with permission of the author of the corresponding work, but are subject to copyright. You are permitted to view, print and download these resources for your own personal use only, provided any copyright lines on the resources are not removed or altered in any way. Any other use, including but not limited to distribution of the resources in modified form, or via electronic or other media, is strictly prohibited unless you have permission from the author of the corresponding work and provided you give appropriate acknowledgement of the source.
If you are having problems accessing these resources please email firstname.lastname@example.org
Instructors have used or reviewed this title for the following courses
- Computation Neuroscience & Neuroengineering
- Computational Cognitive Neuroscience
- Computational Intelligence
- Computational Neurobiology
- Computational Neuroscience
- Dynamics of Biological systems
- Mathematical modeling methods for biological systems
- Methods in Computational Neuroscience
- Molecular Biomechanics
- Neurobiology and Biometrics and Modeling courses
Sorry, this resource is locked
Please register or sign in to request access. If you are having problems accessing these resources please email email@example.comRegister Sign in
You are now leaving the Cambridge University Press website. Your eBook purchase and download will be completed by our partner www.ebooks.com. Please see the permission section of the www.ebooks.com catalogue page for details of the print & copy limits on our eBooks.Continue ×