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Hi Maartje That is indeed possible, though a bit complicated. You get the matrix with the cosines via the program spm_filter. If you use the matrix in K.X0 as a user specified regressor, and turn off the normal HP filter by entering inf as the period, you can even make an F-test to se where the filter had an effect. Hope this helps Torben Torben Ellegaard Lund Assistant Professor, PhD The Danish National Research Foundation's Center for Functionally Integrative Neuroscience (CFIN) Aarhus University Aarhus University Hospital Building 30 Noerrebrogade 8000 Aarhus C Denmark Phone: +4589494380 Fax: +4589494400 http://www.cfin.au.dk [log in to unmask] >> help spm_filter Removes low frequency confounds X0 FORMAT [Y] = spm_filter(K,Y) FORMAT [K] = spm_filter(K) K - filter matrix or: K(s) - struct array containing partition-specific specifications K(s).RT - observation interval in seconds K(s).row - row of Y constituting block/partition s K(s).HParam - cut-off period in seconds K(s).X0 - low frequencies to be removed (DCT) Y - data matrix K - filter structure Y - filtered data ________________________________________________________________________ ___ spm_filter implements high-pass filtering in an efficient way by using the residual forming matrix of X0 - low frequency confounds .spm_filter also configures the filter structure in accord with the specification fields if called with one argument ________________________________________________________________________ ___ Copyright (C) 2005 Wellcome Department of Imaging Neuroscience On 24/10/2007, at 13.19, Luijten, M. wrote: > Hi all, > > I am wondering whether and how you can visualize the cosines added > by SPM when you enter a high pass filter. Is it possible to > actually see what spm did? > > Thanks, > Maartje