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Andreas, The 4D fmri timeseries have 230 time points. I looked into the transformed 4D power spectrum and found they have 115 frequency points. Another point, the 4D fmri data were priorly filtered by using a band-pass filter with a internal of 0.01Hz ~ 0.1Hz. Cheers xinian On Mon, 30 Jun 2008 17:54:40 +0200, Andreas Bartsch <[log in to unmask]> wrote: >Hi, >how many time points have you sampled? >Cheers- >Andreas > > >-----Ursprüngliche Nachricht----- >Von: FSL - FMRIB's Software Library im Auftrag von Xi-Nian Zuo >Gesendet: Mo 30.06.2008 12:46 >An: [log in to unmask] >Betreff: 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 >>======================================================================== >========================================================================