Statistical Analysis of fMRI Data

Functional magnetic resonance imaging (fMRI), which allows researchers to observeneural activity in the human brain noninvasively, has revolutionized the scientific study of themind. An fMRI experiment produces massive amounts of highly complex data; researchers facesignificant challenges in analyzing the data they collect. This book offers an overview of the mostwidely used statistical methods of analyzing fMRI data. Every step is covered, from preprocessing toadvanced methods for assessing functional connectivity. The goal is not to describe which buttons topush in the popular software packages but to help readers understand the basic underlying logic, theassumptions, the strengths and weaknesses, and the appropriateness of each method. The book coversall of the important current topics in fMRI data analysis, including the relation of the fMRI BOLD(blood oxygen-level dependent) response to neural activation; basic analyses done in virtually everyfMRI article--preprocessing, constructing statistical parametrical maps using the general linearmodel, solving the multiple comparison problem, and group analyses; the most popular methods forassessing functional connectivity--coherence analysis and Granger causality; two widely usedmultivariate approaches, principal components analysis and independent component analysis; and abrief survey of other current fMRI methods. The necessary mathematics is explained at a conceptuallevel, but in enough detail to allow mathematically sophisticated readers to gain more than a purelyconceptual understanding. The book also includes short examples of Matlab code that implement manyof the methods described; an appendix offers an introduction to basic Matlab matrix algebra commands(as well as a tutorial on matrix algebra). A second appendix introduces multivariate probabilitydistributions.

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.