tailieunhanh - Principles of Computational Modelling in Neuroscience

This book is about how to construct and use computational models of specific parts of the nervous system, such as a neuron, a part of a neuron or a network of neurons. It is designed to be read by people from a wide range of backgrounds from the biological, physical and computational sciences. The word ‘model’ can mean different things in different disciplines, and even researchers in the same field may disagree on the nuances of its meaning. For example, to biologists, the term ‘model’ can mean ‘animal model’; to physicists, the standard model is a step towards a complete theory of fundamental particles and interactions. We therefore. | PRINCIPLES of COMPUTATIONAL L w MODELLING in V NEUROSCIENCE This page intentionally left blank Principles of Computational Modelling in Neuroscience The nervous system is made up of a large number of elements that interact in a complex fashion. 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 many 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 provides an ideal basis for a course on computational neuroscience. An associated website providing sample codes and up-to-date links to external resources can be found at . David Sterratt is a Research Fellow in the School of Informatics at the University of Edinburgh. His computational neuroscience research interests include models of learning and forgetting and the formation of connections within the developing nervous system. Bruce Graham is a Reader in Computing Science in the School of Natural Sciences at the University of Stirling. Focusing on computational neuroscience his research covers nervous system modelling at many levels. Andrew Gillies works at Psymetrix Limited Edinburgh. He has been actively involved in computational neuroscience research. David Willshaw is Professor of Computational Neurobiology in the School of Informatics at the University of Edinburgh. His .