Thank you to Andreas and Christian both for your replies - I apologize
that I apparently somehow missed Andreas' very complete and helpful
response. This is exactly what I needed to know!
Many thanks again,
Christina
Christina Hugenschmidt
Doctoral Candidate, Neuroscience Program
Wake Forest University School of Medicine
(336) 716-0972
[log in to unmask]
-----Original Message-----
From: FSL - FMRIB's Software Library [mailto:[log in to unmask]] On
Behalf Of Xi-Nian Zuo
Sent: Monday, June 30, 2008 6:47 AM
To: [log in to unmask]
Subject: Re: [FSL] AW: [FSL] TICA on resting state
Hi, Adreas
Do you mean the TICA described in Damoiseaux 2007 Cerebral Cortex paper
can
not be directly done in MELODIC_GUI? Could you give some further details
about this? Following as you suggested, I firstly transformed my 4d fmri
data to 4d power spectrum data by using AFNI's plugin and then fed them
into
melodic command. However, melodic gave me only two components by using
the
automatic estimation option. What's wrong with my command as follows:
#----------
melodic -i ./.filelist --outdir=Tconcat-pICA3.gica
-mask=mask/finalmask.nii.gz --tr=2.16 --report --bgimage=bgimage.nii.gz
--Opca --Owhite --Omean --Ostats -a concat
#----------??
Any suggestion is deeply appreciated!
Thank you.
xinian
On Wed, 18 Jun 2008 14:30:50 +0200, Andreas Bartsch
<[log in to unmask]> wrote:
>Hi,
>
>it depends what you want but yes, possibly.
>You can use fslspec to get the power spectra of your 4D data prior to
feeding them into TICA. If it runs too slow for you use matlab or R with
the
appropriate import / export.
>>does this mean there is power spectrum information in each voxel?
>Yes.
>>Are networks then identified by shared power spectra?
>Yes.
>>And when group differences are evaluated in contrasts, a significant
difference means that the spatial maps identified within the power
spectrum
for that component are different between groups?
>No!;) It means that the power spectrum of a given component is
attenuated
or augmented, i.e. that there is significantly more (or less) power to
that
very component. It can be due to more / less prominent peaks, phase
shifts,
contaminating frequencies aside from the main peaks ... Note that
quantifying power spectra across subjects is certainly tricky. So what
you
would typically do is to go back to your data and extract the relevant
information (using either fslmaths/meants and / or a formal GLM
testing).
>Hope that helps,
>Cheers-
>Andreas
>
>________________________________
>
>Von: FSL - FMRIB's Software Library im Auftrag von Christina
Hugenschmidt
>Gesendet: Mi 18.06.2008 12:51
>An: [log in to unmask]
>Betreff: [FSL] TICA on resting state
>
>
>
>Hi all (and Christian in particular),
>
>I am interested in running a TICA analysis comparing resting state and
>also video watching between two groups. From reading the posts and
>information on the FSL website, I think I should be using the same
>methodology described in the Damoiseaux 2007 Cerebral Cortex paper,
where
>the data is fourier transformed prior to running the TICA analysis. I
was
>wondering if you could tell me the process used to transform the data
>prior to running the TICA?
>
>I would also like to be sure that I understand exactly what is being
>compared between groups in this analysis. When the data is transformed,
>does this mean there is power spectrum information in each voxel? Are
>networks then identified by shared power spectra? And when group
>differences are evaluated in contrasts, a significant difference means
>that the spatial maps identified within the power spectrum for that
>component are different between groups?
>
>Thanks for any insights you can offer,
>
>Christina
>=======================================================================
=
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