Fundamentals of Data Analysis Methods in Functional MRI - Advance Image Processing in Magnetic Resonance Imaging - page 469

15

Fundamentals of Data
Analysis Methods in
Functional MRI

Elia Formisano, Francesco Di Salle,
and Rainer Goebel

CONTENTS

15.1 Introduction............................................................................................481

15.2 Preprocessing of Functional Time Series..............................................483

15.2.1 Slice Timing Correction..........................................................483

15.2.2 Motion Correction...................................................................484

15.2.3 Spatial and Temporal Filtering ...............................................485

15.3 Statistical Localization of Brain Activation ..........................................488

15.3.1 The GLM.................................................................................489

15.3.1.1 Maps) ......................491

15.3.1.2 Relative Contribution (RC) Maps..........................493
15.3.1.3 Specific Effects, Contrasts (t Maps)......................493
15.4 Selection of Significance Thresholds in fMRI Statistical Maps...........494
15.5 Data-Driven Analysis of Functional Time Series .................................496
15.6 Combining Brain Function and Anatomy .............................................496
15.6.1 Coregistration of Functional and Anatomical Data Sets........496
15.6.2 Spatial Normalization .............................................................497
15.7 Segmentation, Surface Reconstruction, and Morphing.........................498
References .........................................................................................................500

Overall Effects (R

2

Maps, F

15.1 INTRODUCTION

Since its invention in the early 1990s [1-3], functional magnetic resonance imaging
(fMRI) has rapidly assumed a leading role among the techniques used to localize
brain activity. The spatial and temporal resolution provided by state-of-the-art MR
technology and its noninvasive character, which allows multiple studies of the same
subject, are some of the main advantages of fMRI over the other functional neuroim-
aging modalities that are based on changes in blood flow and cortical metabolism [4].
In a typical fMRI study, a measurement session includes (1) the acquisition
of one or multiple time series of “functional” volumes while a subject performs

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