 |
 |
Thanks a lot! One more question: In my first MELODIC run which came up with 300 components, if I am too last to re-run it with dimension reduction, can I just inspect the first 30 components and remove noise components (because they accounted for 40% variance)? 2012/9/27 Stephen Smith <[log in to unmask]> > -d 50 > > -------------------- > Stephen M. Smith, Professor of Biomedical Engineering > Associate Director, Oxford University FMRIB Centre > > FMRIB, JR Hospital, Headington, > Oxford. OX3 9 DU, UK > +44 (0) 1865 222726 (fax 222717) > [log in to unmask] > http://www.fmrib.ox.ac.uk/~steve > ---------------------- > > On 27 Sep 2012, at 13:18, Benjamin Kay <[log in to unmask]> wrote: > > > Depends on exactly what you're trying to do, but that would be a good > start. Hmmm... I'm suprised this option hasn't percolated into the Melodic > GUI. > > > > On Thursday, September 27, 2012 08:08:34 you wrote: > >> Hi Ben, > >> > >> Is it > >> > >> melodic -i filtered_func_data -n 50 -o filtered_func_data.ca > >> > >> ? > >> > >> Thanks. > >> > >> Mark > >> > >> 2012/9/27 Benjamin Kay <[log in to unmask]> > >> > >>> Why are you generating 300 components? That's way too many for > >>> interpretation! I'm guessing you let MELODIC try to pick the number of > >>> components automatically. I have found that this often fails for group > ICA > >>> with less-than-pristine datasets. Try using the -n option to limit the > >>> number of components to around 50 (or a # of your choice). As I recall, > >>> this will discard all but the most 50 relevant PCA components prior to > >>> running ICA. > >>> > >>> On Wednesday, September 26, 2012 21:59:14 you wrote: > >>>> Hi, > >>>> > >>>> I believe this might be a simple question but I've checked previous > >>> lists but still can not find answer...... > >>>> > >>>> I am a new user of MELODIC and try to use its output data to remove > >>> artefact in my subject's FMRI data. I did FSL's FEAT analysis and > selected > >>> MELODIC analysis in Pre-stats in one subject's long-run FMRI data (a > >>> complex cognition task containing 800 volumes). Report of FEAT > Pre-stats > >>> showed that the translation of this subject is less than 1.5 mm. In > MELODIC > >>> report, it produced 300 independent components, which retains about > 85% of > >>> total variability. The first ~30 components captured about 40% of the > >>> variance across the entire functional data. > >>>> > >>>> Is the number reasonable? The problem is, it will be grueling to go > >>> through these 300 ICs to remove noise components! Could I just check > the > >>> first ~30 components to remove noise? > >>>> > >>>> > >>>> Thanks for any help. > >>>> > >>>> Mark > >>>> > >>> > >> > > >