Hi Francois,
The smoothing was meant in the spatial domain. I do smooth the data after projecting to the default anatomy (Colin27), to correct for smaller errors in the spatial alignment.
The overall goal is to correct for multiple comparisons on the cluster-level (as an alternative to FDR). For instance, one can run a permutation test (this is what I implemented) or alternatively do a monte-carlo simulation in which p-values are sampled from a uniform distribution for every vertex (this was suggested here). In the second case, however, the smoothness of the original data and the random samples is vastly different such that found clusters cannot be compared. Thus, the surface with randomly-sampled p-values needs to be smoothed to match the smoothness in the original data. For this, we need to estimate the smoothness in the original data. In Freesurfer, this is accomplished with an AR-1 model.
From the other post on cluster-based corrections in the forum (the one I linked above), I got the impression that an estimation of the smoothness was already implemented in BS:
% generate the smoothing kernel
[surf.W,surf.Y,surf.Z] = tess_smooth_sources(surf.Vertices, surf.VertConn);
However, this function seems to have changed (the number of return parameters is different), and, apart from this, I was unsure whether it performed a smoothness estimate in the first place. Am I right, that it does not? As far as I can see, this function performs the smoothing operation, but does not estimate the smoothness in an existing surface..
Cheers
Tim