Analysis 1: Simple t-test

(1) Open up a new MEDx session, and then open up a New Folder.

(2) In the New Folder, select Image --> Open Image. In the Open Image dialog box, in the Filter entry box, type in the tutorial directory, followed by Sn*.hdr, e.g.

and then click on the Filter button. This will cause a list of the 84 spatially normalized, spatially smoothed, temporally filtered, motion-corrected image volumes to be made in the Files: pane. Click on the first one, then (leaving the first one selected) scroll down to the last one and press the Shift key. While pressing on the Shift key, click on the last SnSsTfMc image volume, which should be #84. This should cause all 84 SnSsTfMc image volumes to be selected.

(3) In the Open Image dialog box, click on the Apply button. This will load the 84 spatially normalized, spatially smoothed, temporally filtered, motion-corrected scans into MEDx. Note the name of the Group page; it should be New Group.

(4) Also load the Mean image that you created in step 14 of Make a Mean Image Volume and Mask. In the Filter entry box, type in the tutorial directory, followed by M*.hdr, e.g.

and then click on the Filter button. Select the Mean.hdr file, and then click on the Apply button.

stand-alone MEDx tutorial.

This tutorial actually covers many useful MEDx features, and is highly recommended. The only caveat is that it uses an obsolete (I wouldn't even say that it was ever really kosher) statistical method implemented in MEDx, called Critical Threshold, found under Toolbox --> Functional --> Final Significance --> Critical Threshold. Don't use this method. Use Cluster Detection (also under Final Significance) or False Discovery Rate (not implemented in MEDx, but implemented outside of MEDx in my own C code, and also implemented in SPM).

For some information on creating a paradigm file, see this page Creating a Paradigm File.

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