> i'm not quite clear on what you mean - should i select the higher level
> COPEx.feat directory and NOT select the 'convert PE/COPE to %' and take the mean
> value produced then divide this by the baseline level?
That's exactly right, yes.
> what exactly do you mean
> by baseline level from the first level?
The _easiest_ thing to do is just assume that the baseline level is 10000
(as first-level data is grand-mean scaled to that)
Probably the _best_ thing to do is:
- in each first-level featdir, do
avwmaths filtered_func_data -Tmean filtered_func_data_mean
- upsample all of those to standard space using flirt and
- average all of those across feat runs to get an average baseline image.
> do i get this by running Featquery on
> one of my first level (single session) directories and selecting
> filtered_func_data and 'convert PE/COPE to %'? and then taking the mean value
> for filtered_func_data given in the output. but since i have 5 lower level
> directories (from my 5 sessions) is the mean of the filtered_func_data from one
> session sufficient or do i need the average from all 5?
> thanks again
> In message <[log in to unmask]>
> FSL - FMRIB's Software Library <[log in to unmask]> writes:
> > Hi - yes, at the moment these % changes don't make sense at higher level,
> > as the "baseline level" used to convert PE or COPE into a % doesn't mean
> > anything useful in the 2nd-level input data (which is COPEs from first
> > level, not image data). Therefore you would need to convert the non-% data
> > yourself by going back to the first-level baseline levels. Sorry!
> > Cheers.
> > On Wed, 17 Nov 2004, Jane Aspell wrote:
> > > Hi all
> > >
> > > I'm trying to get % change values out of Featquery and am having some
> > > trouble - the output gives me mean values of 2000-4000! I'm running
> > > Featquery on the results of a higher level analysis - a fixed effects
> > > analysis which combined 5 sessions for a single subject - so am selecting
> > > something.gfeat/copeX.feat directories.
> > > It was suggested to me that my mask (a retinotopic map) could be including
> > > voxels outside of the brain and this could be causing the huge values, but
> > > when i tried eroding the mask it made almost no difference.
> > > When i run Featquery on the first level directories from single sessions I
> > > get mean values around 0.2, which seems reasonable.
> > > any idea what the problem is? my experiment was a simple block design.
> > >
> > > many thanks,
> > >
> > > Jane Aspell
> > >
> > Stephen M. Smith DPhil
> > Associate Director, FMRIB and Analysis Research Coordinator
> > Oxford University Centre for Functional MRI of the Brain
> > John Radcliffe Hospital, Headington, Oxford OX3 9DU, UK
> > +44 (0) 1865 222726 (fax 222717)
> > [log in to unmask] http://www.fmrib.ox.ac.uk/~steve
> Dr Jane Aspell
> Department of Experimental Psychology, University of Oxford,
> South Parks Road, Oxford, OX1 3UD
> tel: +44 (0)1865-281606
Stephen M. Smith DPhil
Associate Director, FMRIB and Analysis Research Coordinator
Oxford University Centre for Functional MRI of the Brain
John Radcliffe Hospital, Headington, Oxford OX3 9DU, UK
+44 (0) 1865 222726 (fax 222717)
[log in to unmask] http://www.fmrib.ox.ac.uk/~steve