Asserting that previous notions about the best methods of modeling the nervous system are wrong, and particularly that non-analytic methods such as the compartmental approach only generate a false sense of biological realism and are especially inappropriate for modeling large circuits of neurons, explores some of the newer avenues of theoretical work towards more powerfully realistic models. The methods were chosen as inspirational examples for experienced modelers or researchers, rather than to be comprehensive or even representative. The topics include the statistical analysis of ionic channel current fluctuations, parameter estimation algorithms for the shunt cable model, syncytial integration in the outer retina, the numerical modeling of neocortical pyramid cells, and the dynamics of associative memory networks. Annotation c. by Book News, Inc., Portland, Or.
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.
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