Chapter 40 - Analysis of fMRI Time Series: Linear Time-Invariant Models, Event-Related fMRI, and Optimal Experimental Design

Abstract

This chapter focuses on issues specific to the analysis of functional magnetic resonance imaging (fMRI) data. It extends the generalized linear model (GLM) introduced in to linear time-invariant (LTI) systems, in which the blood oxygenation level dependent (BOLD) signal is modelled by neuronal causes that are expressed via a haemodynamic response function (HRF). This chapter begins with an introduction of the concepts of temporal basis functions, temporal filtering of fMRI data, and models of temporal autocorrelation. Then it describes the application of these ideas to event-related models, including issues relating to the temporal resolution of fMRI. Event-related fMRI (efMRI) is simply the use of fMRI to detect responses to individual trials, in a manner analogous to the time-locked event-related potentials (ERPs) recorded with EEG. This chapter also discusses the efficiency of fMRI experimental designs, as a function of the interstimulus interval and ordering of stimulus types. Furthermore, this chapter turns to the discussion of some of the concepts introduced in the preceding sections with an example dataset from a single-subject event-related fMRI experiment.