Title from publisher's bibliographic system (viewed on 05 Oct 2015).

Introduction -- Image processing basics -- Preprocessing fMRI data -- Spatial normalization -- Statistical modeling: single subject analysis -- Statistical modeling: group analysis -- Statistical inference on images -- Modeling brain connectivity -- Multivoxel pattern analysis and machine learning -- Visualizing, localizing, and reporting fMRI data -- Review of general linear model -- Data organization and management -- Image formats.

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.