Dear SPM users,

We have problems with a simple activation task for two groups: patients
and healthy controls. We are using a block-design with alternating rest
and activation condition (Tr=3s, 100 measurements, 10 measurements per
epoch). Everything was preprocessed and put in one big statistical
matrix. The individual contrasts show that the healthy controls have
activation in brain regions where the patients don't activate. I get
corresponding results when I set up contrasts like 0 0 0 0 1 1 1 1 where
all patients are set to one and the controls are set to zero and vice
versa. Also contrasts like -1 -1 -1 -1 1 1 1  1 seem to give me good
results for interaction. Now, is this method valid?

When I do a second level analysis with the individual contrast images
(what information contain these images anyway ?????) with a two-sample
t-test or with one-sample t-tests for each group I get really strange
results. Suddenly the patients are activating more then the controls in
brain regions where not even one patient activated individually. Things
change again dramatically (and get even stranger) when I use
proportional scaling in the first level analysis. Now I would like to
know, what exactly the second - level analysis tells me and whether it
is valid just to work with the first level analysis.

Thanks in advance,

Wolfgang


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Wolfgang Weber - Fahr
zi-mannheim, Mannhheim, Germany
email.: [log in to unmask]



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