Handbook of Functional MRI Data Analysis
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.
Dr. Russell A. Poldrack is the director of the Imaging Research Center and professor of
Psychology and Neurobiology at the University of Texas at Austin. He has published more than
100 articles in the field of cognitive neuroscience, in journals including Science, Nature, Neuron,
Nature Neuroscience, and PNAS. He is well known for his writings on how neuroimaging can be
used to make inferences about psychological function, as well as for his research using fMRI and
other imaging techniques to understand the brain systems that support learning and memory,
decision making, and executive function.
Dr. Jeanette A. Mumford is a research assistant professor in the Department of Psychology
at the University of Texas at Austin. Trained in biostatistics, her research has focused on the
development and characterization of new methods for statistical modeling and analysis of fMRI
data. Her work has examined the impact of different group modeling strategies and developed
new tools for modeling network structure in resting-state fMRI data. She is the developer of the
fmriPower software package, which provides power analysis tools for fMRI data.
Dr. Thomas E. Nichols is the head of Neuroimaging Statistics at the University of Warwick,
United Kingdom. He has been working in functional neuroimaging since 1992, when he joined
the University of Pittsburgh’s PET facility as programmer and statistician. He is known for his
work on inference in brain imaging, using both parametric and nonparametric methods, and he
is an active contributor to the FSL and SPM software packages. In 2009 he received the Wiley
Young Investigator Award from the Organization for Human Brain Mapping in recognition for his
contributions to statistical modeling and inference of neuroimaging data.
