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 an...

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Detalles Bibliográficos
Autor principal: Kass, Robert E. (-)
Autor Corporativo: SpringerLink (-)
Otros Autores: Eden, Uri T., Brown, Emery N.
Formato: Libro electrónico
Idioma:Inglés
Publicado: New York, NY : Springer New York 2014.
Colección:Springer series in statistics.
Springer eBooks.
Acceso en línea:Conectar con la versión electrónica
Ver en Universidad de Navarra:https://innopac.unav.es/record=b32913436*spi
Descripción
Sumario: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.
Descripción Física:XXV, 648 p., 135 il., 17 il. col
Formato:Forma de acceso: World Wide Web.
ISBN:9781461496021