01988nam a22002898i 4500001001600000003000700016008004100023020001800064020001800082035002000100041000800120082001900128100002900147245010600176264007100282300003800353336002600391337002600417338003600443500001300479520097600492650003201468856005501500932003201555596000601587949010501593CR9780511975899UkCbUP101011s2011||||enk o ||1 0|eng|d a9780511975899 a9780521877954 a(Sirsi) a792573 aeng00a612.801/132221 aSterratt, David,eauthor10aPrinciples of computational modelling in neuroscienceh[E-Book] /cDavid Sterratt [and three others]. 1aCambridge :bCambridge University Press,c2011e(CUP)fCUP20200108 a1 online resource (xi, 390 pages) atextbtxt2rdacontent acomputerbc2rdamedia aonline resourcebcr2rdacarrier aenglisch aThe 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. 0aComputational neuroscience.40uhttps://doi.org/10.1017/CBO9780511975899zVolltext aCambridgeCore (Order 30059) a1 aXX(792573.1)wAUTOc1i792573-1001lELECTRONICmZBrNsYtE-BOOKu8/1/2020xUNKNOWNzUNKNOWN1ONLINE