Picture 1 of 1

Principles of Computational Modelling in Neuroscience by Bruce Graham, Andrew Gillies, Gaute Einevoll, David Willshaw and David Sterratt (2023, Trade Paperback)

Great Book Prices Store (365019)

98.1% positive feedback

Price:

$85.49

Free shipping

Estimated delivery Wed, Dec 24 - Mon, Jan 5

Returns:

14 days returns. Buyer pays for return shipping. If you use an eBay shipping label, it will be deducted from your refund amount.

Condition:

Brand New

Principles of Computational Modelling in Neuroscience, Paperback by Sterratt, David; Graham, Bruce; Gillies, Andrew; Einevoll, Gaute; Willshaw, David, ISBN 1108716423, ISBN-13 9781108716420, Brand New, Free shipping in the US

About this product

Product Identifiers

PublisherCambridge University Press

ISBN-101108716423

ISBN-139781108716420

eBay Product ID (ePID)6060638302

Product Key Features

Number of Pages544 Pages

Publication NamePrinciples of Computational Modelling in Neuroscience

LanguageEnglish

Publication Year2023

SubjectLife Sciences / Genetics & Genomics

FeaturesRevised

TypeTextbook

Subject AreaScience

AuthorBruce Graham, Andrew Gillies, Gaute Einevoll, David Willshaw, David Sterratt

FormatTrade Paperback

Dimensions

Item Height1.1 in

Item Length10 in

Item Width8 in

Additional Product Features

Edition Number2

Intended AudienceCollege Audience

LCCN2023-014949

Dewey Edition22

Reviews'This new edition builds superbly on its predecessor. Expository excellence and beautifully clear figures remain, whilst extra material has been added throughout. New chapters cover critical topics such as modelling the way that neural signals are measured, and the details of model optimization and selection. Its impressive combination of depth and breadth makes the text perfect source material for a wide variety of courses.' Peter Dayan, Managing Director, Max-Planck Institute for Biological Cybernetics, Tuebingen

IllustratedYes

Dewey Decimal612.80113

Table Of ContentPreface; 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.

Edition DescriptionRevised edition

SynopsisTaking 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., Providing a step-by-step and practical account of how to model neurons and neural circuitry, this textbook is designed for advanced undergraduate and postgraduate students of computational neuroscience as well as for researchers in neuroscience and related sciences wishing to apply computational approaches to interpret data and make predictions.

LC Classification NumberRC343