Handbook of Functional MRI Data Analysis

by Russell A. Poldrack, Jeanette Mumford, Thomas M. Nichols

Functional magnetic resonance imaging (fMRI) has become the most popular method for imaging brain function. Handbook for 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.

Genres: Neuroscience, Nonfiction, Psychology, Textbooks, Science, Brain

238 pages, Hardcover

First published June 30, 2011

Reviews

[Kayson Fakhar · Rating 4 out of 5]

Great book for understanding general concepts but sometimes it gets confusing when it comes to describing mathematical formulae

[Nasia Metoki · Rating 5 out of 5]

If you want to learn all about fMRI before going into particualr readings for a particular fMRI issue, then this is the book for you.
Excellent read, super informative, a great step to understanding fMRI and its analysis.

[Karla · Rating 5 out of 5]

A great handbook with straightforward explanations of steps in the fMRI data processing pipeline, ranging from raw data organisation and basics of image processing to reporting and visualization. Even though it explains the basics in very clear writing, I'd say that background knowledge on fMRI designs, statistics and signal processing is essential for following the text. Some parts of the analysis process (e.g. preprocessing and model fitting) are covered in more depth than more complex methods (e.g. machine learning approaches and connectivity analyses), as expected from an introductory handbook. Overall, it could be recommended to students as a complementary material to an fMRI course or grad students working with fMRI.

[Ieva · Rating 4 out of 5]

If you're a neuroscience student considering an fMRI internship, I highly recommend reading this handbook. I was taking an intro to fMRI course and had to read this handbook for class and it was extremely useful!

[Remi Gau · Rating 5 out of 5]

A must read to anyone starting in fMRI analysis

[Teddy · Rating 3 out of 5]

Not bad if you want to get some knowledge everyone knows..

[Ilknur · Rating 4 out of 5]

A good textbook on fundamentals of fmri data processing steps

[Brittany · Rating 5 out of 5]

One of the most comprehensive fMRI books out there. An excellent resource.

[Miao · Rating 4 out of 5]

It is a really good book for beginners to get start with fMRI. To master it, of course you need more practice.