Principles of Computational Modelling in Neuroscience

Learn to use computational modelling techniques to understand the nervous system at all levels, from ion channels to networks.

David Sterratt (Author), Bruce Graham (Author), Andrew Gillies (Author), Gaute Einevoll (Author), David Willshaw (Author)

9781108716420, Cambridge University Press

Paperback / softback, published 5 October 2023

552 pages
25.3 x 20.2 x 2.8 cm, 1.16 kg

'This book is an invaluable resource for computational neuroscientists, particularly for students starting their doctoral research. The comprehensive coverage, clear prose and extensive examples make it easy for a newcomer with only basic background knowledge to get to grips with a wide variety of complex computational modelling topics as a preparation for starting their own investigations.' Abigail Morrison, RWTH Aachen University

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.

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.

Subject Areas: Genetics [non-medical PSAK]