Dear FSL experts,
I know that similar questions have been asked before, but I could not
find a suitable solution for my problem.
I have data from 30 subjects who all underwent 3 fMRI sessions, each
with two identical runs with a classical blocked motor task. The three
sessions were not equally spaced in time, but exactly at weeks 0, 4
and 12. The group is also quite heterogeneous in terms of age and
there is an important behavioural measure obtained at each timepoint.
Between timepoint 1 and 2 there is an intervention that has an
immediate impact on timepoint 2, but not on timepoint 3 (this is
strong and biologically valid assumption). The intervention also
significantly affects the behavioural measure.
Assuming I have already averaged the two identical runs in each
session in a middle-level analysis (fixed effects in FEAT), I am now
interested in a) average activation per session adjusted for age, b)
the effect of my behavioural score adjusted for age, c) intra-subject
("paired") differences related to the intervention adjusted for any
linear effect of time.
For the purpose I have thought about several designs for FEAT, but I
have serious doubts regarding their validity. I would appreciate any
correction or comment.
1) Average adjusted for age
I assume that the safest way is to run separate group analyses per
session with the same age covariate (EV 1 group mean, EV 2 demeaned
covariate). However, is it possible to run one analysis with 3 EVs
(one per session) to model the means and a 1 EV for age covariate
(similar to a two-group comparison with covariate)? Such design would
expect a constant effect of age, which can make sense.
2) Covariate adjusted for age
Again, I could analyse each session separately. However, I would be
also interested in the average effect of the covariate across all
three sessions. First, I thought that I can expand the previous design
(3 EVs for means, 1 EV for age) by adding an extra EV for the demeaned
covariate. Unlike age, the covariate differs both between and
within-subject, but it definitely shows some consistent changes across
sessions. Therefore I also considered that it might be worthwhile to
combine it with the third model below.
3) Effect of treatment and time
This one is tough. I thought the tripled T-test from the FSL website
(https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/GLM#Single-Group.2C_Three_Measurements_.28.22Tripled_T-Test.22.29)
could be an option, but my measurements are not equally spaced in
time, which probably violates the assumptions for such design.
Instead, I thought I could model the treatment effect and the time
with the following design:
Input EV1 EV2 EV3 ... EVN+2
1 -0.33 -5.33 1 0 0 ...
2 -0.33 -5.33 0 1 0 ...
...
30 -0.33 -5.33 0 0 0 ...
31 0.67 -1.33 1 0 0 ...
...
60 0.67 -1.33 0 0 0 ...
61 -0.33 6.67 1 0 0 ...
...
90 -0.33 6.67 0 0 0 ...
Contrasts
Treatment 1 0 0 ... F-test
-Treatment -1 0 0 ...
Time 0 1 0 ... F-test
-Time 0 -1 0 ...
where EV1 models the effect of treatment (assumed in the second
timepoint only, modelled as 0 and 1s and demeaned), EV2 models the
time linearly (values 0 4 and 12 demeaned). Is this model OK given my
hypotheses? Feat does not complain about the matrix being rank
deficient. Moreover, can I add the behavioural covariate
(orthogonalised or not) as an additional EV? I know that adding the
age covariate will make the design rank deficient.
Thanks in advance for any help!
Cheers
Pavel
BTW: Did anyone consider creating a library with "validated" designs
for FSL? The GLM website does not seem to cover all possible cases,
not even some of those discussed in this forum.
--
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-- MUDr. Pavel Hok
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-- Laboratoř funkční magnetické rezonance
-- Neurologická klinika
-- Lékařská fakulta
-- Univerzita Palackého v Olomouci
-- Fakultní nemocnice Olomouc
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-- Laboratory of functional magnetic resonance imaging
-- Department of Neurology
-- Faculty of Medicine and Dentistry
-- Palacky University Olomouc
-- University Hospital Olomouc
-- Czech Republic
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