Dear SPMers,
After reading spm mailbase, I am still unclear about whether one should
model baseline explicitly and the resulting difference in activation maps.
Suppose I have a box-car experiment with two conditions A and B.
Under each condition I have two factors 1 and 2. A1 is the (assumed)
baseline.
I could specify an overspecified design matrix with D1=[A1 A2 B1 B2 mean]
or a design matrix with D2=[A2 B1 B2 mean] which models baseline
implicitly.
My understanding is that with design matrix D1, the contrast [-1 1 0 0 0] is
equivalent to the contrast [1 0 0 0] for design matrix D2. I did both for
the same
data set. The resulting activation maps were different. It seems to me that
the
design which explicitly models the baseline tends to produce more
conservative
activation maps. Is my observation right? If so, why?
Secondly I understand that with D1, I can test for interaction between A and
B using
the contrast [1 -1 -1 1 0]. I am not sure what contrast I should use for D2
to test for interaction.
I did try [-1 -1 1 0], but again the resulting activation map is different
from that obtained
using D1. I suppose this contrast is probably not the right one. What
contrast should
I use to test interaction in this case without explicitly include A1 in the
design matrix?
I would also be very grateful if someone could explain what SPM does when
the
design matrix is overspecified like D1 above, i.e., if the rank of D1 is 4,
deos SPM still
try to estimate the 5 parameters for each voxel?
Many thanks.
Ying
Dr. Ying Zheng
Dept of Psychiatry
University of Sheffield
U.K.
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