Book contents
- Frontmatter
- Contents
- List of abbreviations
- Preface
- Acknowledgements
- Chapter 1 Introduction
- Chapter 2 The basis of electrical activity in the neuron
- Chapter 3 The Hodgkin–Huxley model of the action potential
- Chapter 4 Compartmental models
- Chapter 5 Models of active ion channels
- Chapter 6 Intracellular mechanisms
- Chapter 7 The synapse
- Chapter 8 Simplified models of neurons
- Chapter 9 Networks of neurons
- Chapter 10 The development of the nervous system
- Chapter 11 Farewell
- Appendix A Resources
- Appendix B Mathematical methods
- References
- Index
Appendix A - Resources
Published online by Cambridge University Press: 05 June 2012
- Frontmatter
- Contents
- List of abbreviations
- Preface
- Acknowledgements
- Chapter 1 Introduction
- Chapter 2 The basis of electrical activity in the neuron
- Chapter 3 The Hodgkin–Huxley model of the action potential
- Chapter 4 Compartmental models
- Chapter 5 Models of active ion channels
- Chapter 6 Intracellular mechanisms
- Chapter 7 The synapse
- Chapter 8 Simplified models of neurons
- Chapter 9 Networks of neurons
- Chapter 10 The development of the nervous system
- Chapter 11 Farewell
- Appendix A Resources
- Appendix B Mathematical methods
- References
- Index
Summary
Here is a list of resources related to computational neuroscience modelling. Most of these are resources that, at the time of writing, are available as open source software, but we cannot say for how long they will continue to be available in this way. Please refer to our web site, compneuroprinciples.org, for more up-to-date information.
Simulators
If the solution of a computational model is the evolution of a quantity, such as membrane potential or ionic concentration, over time and space, it constitutes a simulation of the system under study. Often simulated quantities change continuously and deterministically, but sometimes quantities can move between discrete values stochastically to represent, for example, the release of a synaptic vesicle or the opening and closing of an ion channel.
The process of describing and implementing the simulations of complex biophysical processes efficiently is an art in itself. Fortunately, for many of the models described in this book, in particular, models of the electrical and chemical activity of neurons, and to an extent the models of networks, this problem has been solved. An abundance of mature computer simulation packages exists, and the problem is in choosing a package and learning to use it.
- Type
- Chapter
- Information
- Principles of Computational Modelling in Neuroscience , pp. 319 - 327Publisher: Cambridge University PressPrint publication year: 2011