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Computational Neuroscience
Mathematical and statistical models have played important roles in neuroscience, especially by describing the electrical activity of neurons recorded individually, or collectively across large networks. As the field moves forward rapidly, new challenges are emerging. For maximal effectiveness, those working to advance computational neuroscience will need to appreciate and exploit the complementary strengths of mechanistic theory and the statistical paradigm.
Science
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Student Directory
None
Suprachiasmatic Nucleus
Based on a conference funded by the National Institutes of Health, this timely book is the most up-to-date and definitive reference on the suprachiasmatic nucleus (SCN), the part of the brain that controls circadian rhythms in mammals. These biological rhythms range from daily fluctuations in metabolism to seasonal and annual cycles. This book comprehensive and incisive review of the SCN covers anatomy and physiology, intrinsic SCN rhythms, circadian rhythms, neuropharmacology, transplants, and development.
Analysis of Neural Data
Continual improvements in data collection and processing have had a huge impact on brain research, producing data sets that are often large and complicated. By emphasizing a few fundamental principles, and a handful of ubiquitous techniques, Analysis of Neural Data provides a unified treatment of analytical methods that have become essential for contemporary researchers. Throughout the book ideas are illustrated with more than 100 examples drawn from the literature, ranging from electrophysiology, to neuroimaging, to behavior. By demonstrating the commonality among various statistical approaches the authors provide the crucial tools for gaining knowledge from diverse types of data. Aimed at experimentalists with only high-school level mathematics, as well as computationally-oriented neuroscientists who have limited familiarity with statistics, Analysis of Neural Data serves as both a self-contained introduction and a reference work.
Dynamical Systems in Neuroscience
Explains the relationship of electrophysiology, nonlinear dynamics, and the computational properties of neurons, with each concept presented in terms of both neuroscience and mathematics and illustrated using geometrical intuition. In order to model neuronal behavior or to interpret the results of modeling studies, neuroscientists must call upon methods of nonlinear dynamics. This book offers an introduction to nonlinear dynamical systems theory for researchers and graduate students in neuroscience. It also provides an overview of neuroscience for mathematicians who want to learn the basic facts of electrophysiology. Dynamical Systems in Neuroscience presents a systematic study of the relati...
Carbonate Sequence Stratigraphy
Hardcover plus Foldouts
Molecular Mechanisms of Signalling and Membrane Transport
Proceedings of the NATO Study Institute on Molecular Mechanisms of Signalling and Targeting, held on the Island of Spetsai, Greece, August 18-30, 1996
Resistance and Persuasion
Resistance and Persuasion is the first book to analyze the nature of resistance and demonstrate how it can be reduced, overcome, or used to promote persuasion. By examining resistance, and providing strategies for overcoming it, this new book generates insight into new facets of influence and persuasion. With contributions from the leaders in the field, this book presents original ideas and research that demonstrate how understanding resistance can improve persuasion, compliance, and social influence. Many of the authors present their research for the first time. Four faces of resistance are identified: reactance, distrust, scrutiny, and inertia. The concluding chapter summarizes the book's ...
