Dear  all,

I have a couple of hopefully simple questions in case somebody could help:

(a) I normalise a high-resolution EPI image to the EPI template, to obtain parameters that are then used to normalize the fMRI time-series.
My questions are:
(1) In writing the normalized time-series, are there any arguments in favour of maintaining the default [2 2 2] voxelsize, or in favour of using the native voxelsize [3.75 3.75.3.3] of my images?
(2) When it comes to the stats, if I have used the [2 2 2] voxelsize, then the FWHM=[8 8 8] should be generally adequate for smoothing; if I used the [3.75 3.75.3.3] would that mean that I might need to use a higher FWHM?

(b) Just to double check: I have defined a matlabbatch structure, which I have placed in a for-loop changing the input for each subject (I couldn’t work out how to use the one provided, so I improvised a bit). It works fine, but I would just like to double check if I might have missed anything obvious (e.g. in setting up any defaults). This is what I have done – does it seem OK to you?

 
%set defaults
spm('defaults','fmri')
spm_jobman('initcfg')

Begin for-loop going over subjects

Define matlabbatch inputs

spm_jobman('serial', matlabbatch)

End for-loop



Many thanks for your help!

Yannis


--
Yannis Paloyelis, M.Sc.
PhD Student
Office C3.18 (P080)
MRC Social Genetic and
Developmental Psychiatry Centre
Institute of Psychiatry,
King's College London
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SE5 8AF London
Tel. +44-20-7848-5403
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