Hi all,
recently we had a question on this mailbase, that has not been answered
yet:
We wish to analyse data parametrically. We acquired five fMRI runs per
subject (8 subjects).
Task level was varied from run to run. We are interested in the main
task effect as well as in
correlation of the BOLD signal with task level.
So far we analysed our data by building one single long fMRI run by
chaining together
all five runs/subject.
Then we applied a set of three orthogonalized basic functions
(boxcar/first and second order).
For each of this covariates a contrast image was calculated on the first
level.
For group analysis, we performed a one sample t-test over the
corresponding contrast images of all 8 subjects.
Our quesions are:
1) Is this a valid approach?
2) Would it be any better to perform parametric analysis by calculating
contrast images for each
run (=level)/subject on the first level and then calculating a 'simple
(linear) regression' over the
five level-subject-specific contrast images (total 40) on the second
level?
3) What is the appropriate analysis for the catagorical effect
(irrespective of task level modulation)
when applying approach 2 ?
(one contrast image including all 5 levels/subject on the first level
or five contrast images/subject entered into one (big) t-test)
Hope my question is not too confusing.
TIA
Peter
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