Handbook of Functional MRI Data Analysis
Cambridge University Press, 8/22/2011
EAN 9780521517669, ISBN10: 0521517664
Hardcover, 288 pages, 26.1 x 18.4 x 1.9 cm
Language: English
Functional magnetic resonance imaging (fMRI) has become the most popular method for imaging brain function. Handbook of Functional MRI Data Analysis provides a comprehensive and practical introduction to the methods used for fMRI data analysis. Using minimal jargon, this book explains the concepts behind processing fMRI data, focusing on the techniques that are most commonly used in the field. This book provides background about the methods employed by common data analysis packages including FSL, SPM and AFNI. Some of the newest cutting-edge techniques, including pattern classification analysis, connectivity modeling and resting state network analysis, are also discussed. Readers of this book, whether newcomers to the field or experienced researchers, will obtain a deep and effective knowledge of how to employ fMRI analysis to ask scientific questions and become more sophisticated users of fMRI analysis software.
1. Introduction
2. Image processing
3. Preprocessing
4. Normalization
5. Statistical modeling
6. Statistical modeling
group analysis
7. Statistical inference
8. Connectivity
9. Visualization
10. Machine learning
Appendix A. GLM intro/review
Appendix B. Data organization and management
Appendix C. Image formats.
'Wow! Very often in neuroimaging a title has little relationship to what follows. That is clearly not the case with Handbook of Functional MRI Data Analysis by Poldrack, Mumford, and Nichols. This relatively slender volume is all that a handbook should be: it's crafted by true experts in the field, it's structured so that a newcomer can understand a method's strengths and weaknesses, but it also contains meaty information useful to experts. The book touches on all of the major analytical approaches current in the field and, while I don't agree with every choice the authors make, their advice is always well-conceived. This will be a standard reference on every neuroimager's shelf.' Steven Petersen, Washington University, St. Louis