Book contents
- Frontmatter
- Contents
- Preface
- Acknowledgments
- 1 A tour of the NEURON simulation environment
- 2 The modeling perspective
- 3 Expressing conceptual models in mathematical terms
- 4 Essentials of numerical methods for neural modeling
- 5 Representing neurons with a digital computer
- 6 How to build and use models of individual cells
- 7 How to control simulations
- 8 How to initialize simulations
- 9 How to expand NEURON's library of mechanisms
- 10 Synaptic transmission and artificial spiking cells
- 11 Modeling networks
- 12 hoc, NEURON's interpreter
- 13 Object-oriented programming
- 14 How to modify NEURON itself
- Appendix A1 Mathematical analysis of IntFire4
- Appendix A2 NEURON's built-in editor
- Epilogue
- Index
Preface
Published online by Cambridge University Press: 01 September 2010
- Frontmatter
- Contents
- Preface
- Acknowledgments
- 1 A tour of the NEURON simulation environment
- 2 The modeling perspective
- 3 Expressing conceptual models in mathematical terms
- 4 Essentials of numerical methods for neural modeling
- 5 Representing neurons with a digital computer
- 6 How to build and use models of individual cells
- 7 How to control simulations
- 8 How to initialize simulations
- 9 How to expand NEURON's library of mechanisms
- 10 Synaptic transmission and artificial spiking cells
- 11 Modeling networks
- 12 hoc, NEURON's interpreter
- 13 Object-oriented programming
- 14 How to modify NEURON itself
- Appendix A1 Mathematical analysis of IntFire4
- Appendix A2 NEURON's built-in editor
- Epilogue
- Index
Summary
I promise nothing complete; because any human thing supposed to be complete, must for that very reason infallibly be faulty.
Who should read this book?
This book is about how to use the NEURON simulation environment to construct and apply empirically based models of neurons and neural networks. It is written primarily for neuroscience investigators, teachers, and students, but readers with a background in the physical sciences or mathematics who have some knowledge about brain cells and circuits and are interested in computational modeling will also find it helpful. The emphasis is on the most productive use of NEURON as a means for testing hypotheses that are founded on experimental observations, and for exploring ideas that may lead to the design of new experiments. Therefore the book uses a problem-solving approach, with many working examples that readers can try for themselves.
What this book is, and is not, about
Formulating a conceptual model is an attempt to capture the essential features that underlie some particular function. This necessarily involves simplification and abstraction of real-world complexities. Even so, one may not necessarily understand all implications of the conceptual model. To evaluate a conceptual model it is often necessary to devise a hypothesis or test in which the behavior of the model is compared against a prediction.
- Type
- Chapter
- Information
- The NEURON Book , pp. xvii - xviiiPublisher: Cambridge University PressPrint publication year: 2006