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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
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>> 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