Analysis of Neural Data
Robert E. Kass, Carnegie Mellon University;
Uri T. Eden, Boston University;
Emery N. Brown, MIT
Springer International Publishing, 2014
ISBN: 978-1-4939-4078-3;
Language: English
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.
A set of MATLAB files is available for download to produce the figures throughout the book.
