- Series: MIT Press
- Hardcover: 352 pages
- Publisher: The MIT Press; 1 edition (March 11, 2011)
- Language: English
- ISBN-10: 0262015048
- ISBN-13: 978-0262015042
- Product Dimensions: 7 x 0.6 x 9 inches
- Shipping Weight: 1.5 pounds (View shipping rates and policies)
- Average Customer Review: 4 customer reviews
- Amazon Best Sellers Rank: #314,423 in Books (See Top 100 in Books)
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Statistical Analysis of fMRI Data (MIT Press) 1st Edition
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This book covers all major fMRI analyses with a level of mathematical depth that is appropriate for cognitive and brain scientists with some background in statistics. The author has the rare ability of explaining complex issues using intuitive and engaging prose. The perfect balance between conceptual intelligibility and mathematical rigor makes this an ideal textbook for undergraduate and graduate courses.(Roberto Cabeza, Professor of Psychology and Neuroscience, Duke University)
Understanding the complexities associated with the generation of brain function images is essential, but this information is often difficult to obtain. This lovely new book by Ashby is a major step in meeting that need. I recommend it with enthusiasm to new initiates to imaging as well as seasoned veterans.(Marcus Raichle, Professor of Radiology, Neurology, Neurobiology, and Biomedical Engineering at Washington University in St Louis)
About the Author
F. Gregory Ashby is Professor and Chair in the Department of Psychology and former Director of the Brain Imaging Center at the University of California, Santa Barbara.
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Top customer reviews
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In an effort to improve my own understanding of the field, and to train my post-docs and PhD students, I have carefully looked at every related textbook in the field. This book is on a class of its own and is a MUST read for every serious student of fMRI.
The book carries the reader through a precise but highly readable analysis of the statistical issues associated with analyzing fMRI data, from basic issues such as preprocessing, to an outstanding four chapter discussion of 'connectivity methods' and 'multivariate approaches'. To top it all, the book includes multiple snipets of MATLAB code that greatly add to the reader's understanding of the subject.
Overall, the book is an example of how methods should be disseminated in this highly technical area to an area that spans a wide range of mathematical backgrounds.
Everybody in my lab is getting a copy of this!
Prof. of Neuroscience & Economics