Hi Francois,
first of all, thanks for the fast response and help.
I implemented a cluster-based correction for multiple comparisons (similar to the permutation test implemented in freesurfer) and wanted to run it on the statistics extracted from an unconstrained source reconstruction.
In order to deal with the three dipoles estimates at every position, I decided to start with a simple vector norm as approximation, but I was was also interested in the other possibilities (power, PCA, SVD, etc). Your pointer to the scout function helped for this, I can check the code and see how the different methods are implemented.
If you have suggestions or comments, they are always highly welcome. Of course, I am happy to share my code with you if you are interested.
Tim
PS: There was a related post recently in which it was suggested to estimate the null distribution by randomly sampling p-values from a uniform distribution and smoothing appropriately to resemble the smoothness in the original data. However, I could not find whether BS provides a function to estimate the smoothness in the original data?