Statistical Techniques for Neuroscientists
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An ideal introduction to statistical neurocomputing, this book examines current statistical methods for solving emerging problems in neuroscience. These methods have been applied to data involving multichannel neural spike train, spike sorting, blind source separation, functional and effective neural connectivity, spatiotemporal modeling, and multimodal neuroimaging technique. It provides an overview of various methods being applied to specific research areas of neuroscience. The book emphasizes statistical principles and their software. It includes examples and experimental data so that readers can understand the principles and master the methods.…mehr

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Produktbeschreibung
An ideal introduction to statistical neurocomputing, this book examines current statistical methods for solving emerging problems in neuroscience. These methods have been applied to data involving multichannel neural spike train, spike sorting, blind source separation, functional and effective neural connectivity, spatiotemporal modeling, and multimodal neuroimaging technique. It provides an overview of various methods being applied to specific research areas of neuroscience. The book emphasizes statistical principles and their software. It includes examples and experimental data so that readers can understand the principles and master the methods.
Autorenporträt
Young K. Truong, PhD, is a professor in the Department of Biostatistics at the University of North Carolina at Chapel Hill, USA. He earned his BS in mathematics with Baccalaureate Honors at the University of Washington, Seattle, in 1978 and his MA (1980) and PhD (1985) degrees in statistics from the University of California, Berkeley, USA. He has published extensively, is the recipient of many prestigious awards, and is an often-invited professional speaker and presenter.