Hi list,
I am trying to complement a traditional GLM analysis of a rather
lengthy and complex fMRI study with MELODIC results. I am prticularly
interested in components correlating with event timecourses (six
types), which were displayed randomly across subjects. This means that
tensorial ICA is out. I ran individual ICA on all single subjects and
am now identifying correlated maps manually in order to somehow
group-average them later. This is where I need help:
- can I get component numbers correlating with my EVs in an automated
fashion for each subject?
- which data should I feed into a group analysis?
For the latter part, I imagined fslmerge-ing maps that a) belong to
one EV-type and b) show spatial similarity as determined by fslcc,
meaning separate parietal and frontal maps relating to a particular
would not be thrown together (but analysed separately). Then I'd be
runnning randomise on the image stack. But: which data should enter
this set: the raw component from melodic_IC or the probmap? And how
should I deal with subjects not exhibiting a fitting map? Did anyone
perform something similar before?
Thanks for any help,
Cornelius
--
Dr. med. Cornelius J. Werner
Department of Neurology
RWTH Aachen University
Pauwelsstr. 30
52074 Aachen
Germany
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