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Face fMRI data

As another, more sophisticated example, consider the data from a repetition priming experiment performed using event-related fMRI. Briefly, this is a 2\(\times\)2 factorial study with factors “fame” and “repetition” where famous and non-famous faces were presented twice against a checkerboard baseline (for more details, see (Henson et al. 2002)). The subject was asked to make fame judgements by making key presses. There are thus four event-types of interest; first and second presentations of famous and non-famous faces, which we denote N1, N2, F1 and F2. The experimental stimuli and timings of events are shown the next two figures.

Face repetition paradigm: There were 2 presentations of 26 Famous and 26 Nonfamous Greyscale photographs, for 0.5s each, randomly intermixed. The minimal Stimulus Onset Asynchrony (SOA)=4.5s, with probability 2/3 (ie 1/3 null events). The subject made one of two right finger key presses denoting whether or not the subject thought the face was famous.
Time series of events.

Images were acquired using continuous Echo-Planar Imaging (EPI) with TE=40ms, TR=2s and 24 descending slices (64\(\times\)64 3\(\times\)3 mm\(^2\)), 3mm thick with a 1.5mm gap. The data archive is available from the SPM website. This contains 351 Analyze format functional images sM03953_0005_*.{hdr,img} of dimension 64\(\times\)64\(\times\)24 with 3\(\times\)3\(\times\)4.5 mm\(^3\) voxels. A structural image is also provided in Analyze format (sM03953_0007.{hdr,img}).

To analyse the data, first create a new directory DIR eg. C:\data\face_rep, in which to place the results of your analysis. Then create 3 subdirectories (i) jobs, (ii) categorical, (iii) parametric and (iv) bayesian. As the analysis proceeds these directories will be filled with job-specification files, design matrices and models estimated using classical or Bayesian methods.

As well as the classical/Bayesian distinction we will show how this data can be analysed from a parametric as well as a categorical perspective. We will look at the main effects of fame and repetition and in the parametric analysis we will look at responses as a function of “lag”, that is, the number of faces intervening between repetition of a specific face.

Start up MATLAB, enter your jobs directory and type spm fmri at the MATLAB prompt. SPM will then open in fMRI mode with three windows (1) the top-left or “Menu” window, (2) the bottom-left or “Interactive” window and (3) the right-hand or “Graphics” window. Analysis then takes place in three major stages (i) spatial pre-processing, (ii) model specification, review and estimation and (iii) inference. These stages organise the buttons in SPM’s base window.

The SPM base window comprises three sections (i) spatial pre-processing, (ii) model specification, review and estimation and (iii) inference.