TY  - BOOK
AU  - Sterratt,David
TI  - Principles of computational modelling in neuroscience
SN  - 9781139042550
AV  - QP357.5 .P75 2011eb
U1  - 612.801/13 22
PY  - 2011///
CY  - Cambridge, New York
PB  - Cambridge University Press
KW  - Computational neuroscience
KW  - Computer simulation
KW  - Digital computer simulation
KW  - Neural conduction
KW  - Neural transmission
KW  - Models, Neurological
KW  - Computer Simulation
KW  - Neural Conduction
KW  - Synaptic Transmission
KW  - Neurosciences informatiques
KW  - Simulation par ordinateur
KW  - Conduction nerveuse
KW  - Transmission nerveuse
KW  - simulation
KW  - aat
KW  - MEDICAL
KW  - Neuroscience
KW  - bisacsh
KW  - PSYCHOLOGY
KW  - Neuropsychology
KW  - fast
KW  - Electronic books
N1  - Includes bibliographical references (pages 351-381) and index; Cover; Half-title; Title; Copyright; Contents; 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
N2  - "The nervous system is made up of a large number of interacting elements. To understand how such a complex system functions requires the construction and analysis of computational models at many different levels. This book provides a step-by-step account of how to model the neuron and neural circuitry to understand the nervous system at all levels, from ion channels to networks. Starting with a simple model of the neuron as an electrical circuit, gradually more details are added to include the effects of neuronal morphology, synapses, ion channels and intracellular signalling. The principle of abstraction is explained through chapters on simplifying models, and how simplified models can be used in networks. This theme is continued in a final chapter on modelling the development of the nervous system. Requiring an elementary background in neuroscience and some high school mathematics, this textbook is an ideal basis for a course on computational neuroscience"--
UR  - https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=361614
ER  -