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With contributions from more than 40 renowned experts, Modeling in the Neurosciences: From Ionic Channels to Neural Networks is essential for those interested in neuronal modeling and quantitative neiroscience. Focusing on new mathematical and computer models, techniques and methods, this monograph represents a cohesive and comprehensive treatment of various aspects of the neurosciences from the biophysical, cellular and netwrok levels. Many state-of-the-art examples are presented as to how mathematical and computer modeling can contribute to the understanding of mechanisms and systems in the neurosciences. Each chapter also includes suggestions of possible refinements for future modeling in this rapidly changing and expanding field. This book will benefit and inspire the advanced modeler, and give the beginner sufficient confidence to model a wide selection of neuronal systems at the biophysical, cellular and network levels.
R.R. Poznanski
Introduction to modelling in the neurosciences; statistical analysis of ionic channel current fluctuations; physiological and statistical approaches to modelling of synaptic responses; natural variability in the geometry of dendritic branching patterns; mathematical analysis of a multiple equivalent cylinder model; methods in modelling passive dendritic trees with tapering dendrites; the Lanczos procedure for generating equivalent cables; parameter estimation algorithms for the Shunt cable model; estimation of cable parameters for neurons with dendro-dendritic gap junctions; information processing by electrotonic networks of the outer retina; ionic current modelling of neurons in the outer retina; ephaptic interaction between neurons; the example of the hippocampus; numerical modelling of neocortical pyramid cells; some problems arising in models of conduction in excitable dendrites; model analysis of bistable dendrites with wind-up; nonlinear dynamics of a simplified neuron model; modelling the dynamics of associative neural networks; perspective on the analysis and synthesis of morphologically realistic neural.
