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Dear Jack, > I suspect that I misunderstood some basics about PPI > (psychophysiological interaction). Thanks to your file (spm_regions), > a small patch of an activated region under one contrast has been > extracted. 11 subjects, scanned twice for a memory task: retrieval vs > Lecture (R-L). A slightly different task has been asked between > session n?1 and 2 (target vs context T-C). > > First performing R-L Extracting a small region using spm_regions > Multiplying it with the T-C regressor (centered) Putting all (Y, Y.*T-C, > T-C) as covariate of interest. > > I thought that Y and T-C should explain all the variance of the little > region that was taken (their contrast have been set to 0). In fact, > this region persist to be activated (in fact it is the only part of it > that still activated) ! How should I interpret that ? The activity of > this region is potentiated by is own activity under the factor T-C ? > Could it be explained by the fact that the 1rst eigenvector was taken > ? Yes indeed. If Y was the voxel-specific activity no PPI would have been found. > (By the way, I heard about some concern on the number of observation > NO - number of scan - for a given number of variable NV - nbr of > voxel. Is it true that NV should still greater than NO (I haven't > found it in my book yet) ? Since my region only contain 26 vx and there > is about 550 scans, could the use of the simple mean be more reliable > ?). No there is no restriction on the number of voxels. Note that the mean is like an eigenvariate of an eigenimage with a uniform loading. > A (last) question about the way to specify a regressor : I intend to > specify sessions too when performing this PPI. However I must than give > 22 regressors *3 (3 for each session). Is there a simplest way to do > that ? SPM99 (final release) has tried to rationalize the GUI for fMRI designs. I am afraid however that session-specific regressor that are different (e.g. as in PPIs) will have to be entered individually. With very best wishes - Karl %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%