Classical and Bayesian Inference in fMRI - Advance Image Processing in Magnetic Resonance Imaging - page 528

17

Classical and Bayesian
Inference in fMRI

William D. Penny and Karl J. Friston

CONTENTS

17.1 Introduction............................................................................................541
17.2 Spatial Transformations .........................................................................543
17.2.1 Realignment ............................................................................544
17.2.2 Adjusting for Movement-Related
Effects in fMRI .......................................................................544
17.2.3 Normalization..........................................................................545
17.2.4 Coregistration of Functional and
Anatomical Data .....................................................................545
17.2.5 Spatial Smoothing ...................................................................546
17.3 General Linear Model............................................................................547
17.3.1 Design Matrix .........................................................................547
17.3.2 Contrasts..................................................................................548
17.3.3 Temporal Basis Functions.......................................................549
17.4 Statistical Parametric Mapping..............................................................551
17.4.1 Random Field Theory .............................................................552
17.5 Posterior Probability Mapping ..............................................................553
17.5.1 Empirical Example..................................................................554
17.6 Dynamic Causal Modeling ....................................................................556
17.6.1 Empirical Example..................................................................557
17.7 Conclusion .............................................................................................562
References .........................................................................................................562

17.1 INTRODUCTION

A general issue in the analysis of functional magnetic resonance imaging (fMRI)
data is the relationship between the neurobiological hypothesis one posits and
the statistical models adopted to test that hypothesis. One key distinction is
between functional specialization and integration. Briefly, fMRI was originally
used to provide functional maps showing which regions are specialized for spe-
cific functions, a classic example being the study by Zeki et al. (1) who identified

541