Statistical Analysis of fMRI Data, Second Edition
A guide to all aspects of experimental design and data analysis for fMRI experiments, completely revised and updated for the second edition.
Functional magnetic resonance imaging (fMRI), which allows researchers to observe neural activity in the human brain noninvasively, has revolutionized the scientific study of the mind. An fMRI experiment produces massive amounts of highly complex data for researchers to analyze. This book describes all aspects of experimental design and data analysis for fMRI experiments, covering every step—from preprocessing to advanced methods for assessing functional connectivity—as well as the most popular multivariate approaches. The goal is not to describe which buttons to push in the popular software packages but to help researchers understand the basic underlying logic, the assumptions, the strengths and weaknesses, and the appropriateness of each method.
The field of fMRI research has advanced dramatically in recent years, in both methodology and technology, and this second edition has been completely revised and updated. Six new chapters cover experimental design, functional connectivity analysis through the methods of psychophysiological interactions and beta-series regression, decoding using multi-voxel pattern analysis, dynamic causal modeling, and representational similarity analysis. Other chapters offer new material on recently discovered problems related to head movements, the multivariate GLM, meta-analysis, and other topics. All complex derivations now appear at the end of the relevant chapter to improve readability. A new appendix describes how to build a design matrix with effect coding for group analysis. As in the first edition, MATLAB code is provided with which readers can implement many of the methods described.
Downloadable instructor resources available for this title: a file of figures in the book
Hardcover$60.00 X | £50.00 ISBN: 9780262042680 568 pp. | 7 in x 9 in 106 b&w illus.
Understanding the complexities associated with the generation of brain function images is essential, but this information is often difficult to obtain. This lovely new edition of the book by Greg Ashby is a major step in meeting that need. I recommend it with enthusiasm to new initiates to imaging as well as seasoned veterans.
Alan A. & Edith L. Wolff Distinguished Professor in Medicine, Mallinckrodt Institute of Radiology, Washington University of Medicine
This book covers all major fMRI analyses with a level of mathematical depth appropriate for readers with some background in statistics. This is an ideal textbook for both undergraduate and graduate courses. The new edition is even better than the first, including new chapters on topics such as functional connectivity, multivoxel pattern analyses, and representational similarity analyses.
Professor of Psychology and Neuroscience, Duke University