Principles of Computational Modelling in Neuroscience

This textbook provides a step-by-step approach to modelling neurons and neural circuitry, using computational techniques to understand the nervous system. It covers neuronal morphology, synapses, ion channels, and intracellular signalling, with additional examples and case studies on specific modelling techniques. Online resources offer exercises and simulation code for students to practice.

Format: Paperback / softback
Length: 544 pages
Publication date: 05 October 2023
Publisher: Cambridge University Press

This comprehensive textbook provides a step-by-step approach to modelling neurons and neural circuitry, enabling students to employ computational techniques to gain a deep understanding of the nervous system at various levels. Throughout the text, case studies are used to illustrate fundamental principles, making it an engaging and accessible resource for students.

Beginning with a simple model of a neuron, the authors gradually introduce neuronal morphology, synapses, ion channels, and intracellular signalling. This fully updated new edition includes additional examples and case studies on specific modelling techniques, offering suggestions on how to best utilize this book. Additionally, new chapters have been added to cover topics such as plasticity, modelling extracellular influences on brain circuits, modelling experimental measurement processes, and selecting appropriate model structures and their parameters.

To enhance learning, the online resources include exercises and simulation code that recreate many of the book's figures, allowing students to practice as they acquire knowledge. Requiring an elementary background in neuroscience and high-school mathematics, this textbook serves as an ideal resource for courses on computational neuroscience. By leveraging computational approaches, students can gain a deeper insights into the complex workings of the nervous system and contribute to the field of neuroscience.

Weight: 1180g
Dimension: 204 x 255 x 34 (mm)
ISBN-13: 9781108716420
Edition number: 2 Revised edition