Dear Jessica,

I recognise those paragraphs so think that I should reply!

I would just point out to begin with that this analysis was performed a
little while ago (we used SPM99 as you can see) - this was the best approach
we could think of at the time. Essentially we used the 'normalisation'
options in SPM99 to register all the B0 images to an EPI template. The .mat
files describing these transformations were then applied to the MD and FA
maps.

Once this is done, running an analysis with SPM is quite simple. For example
in SPM5 one could use 'PET', 'Basic models' then 'multiple regression'. If
you are interested in each cognitive score separately (ie not covarying for
one cognitive variable in the analysis of another) then enter a cognitive
score, age, other nuisance variables as 'covariates', with one model for
each cognitive measure, estimate the model and then set a contrast of +1/-1
as appropriate in the contrast manager for the variable of interest.

But of course the previous mails on statistical assumptions are correct. We
assumed that in each voxel FA was normally distributed across subjects and
this did not look too unreasonable on plotting the data. There has certainly
been some discussion about how suitable SPM is specifically for DTI data and
specific problems with voxel-beased analysis with DTI (I would have to
suggest referring to the DTI experts about this..)

Non-parametric stats are also now possible.

The quality of normalisation also needs to be considered as in DTI you would
be interested in the co-registration of white matter tracts/ internal
structure as well as the cortical sulci.

To answer your q about whether only SPM can be used, my understanding is
that the fMRIb software can also be used for voxel-based analysis and there
is a lot of material about DTI analysis on that mailing list. Also see

Smith SM et al. Tract-based spatial statistics: voxelwise analysis of
multi-subject diffusion data. Neuroimage 2006

Hope this helps and does not contain too many errors!

Mike



-----Original Message-----
From: SPM (Statistical Parametric Mapping) [mailto:[log in to unmask]] On
Behalf Of <Jessica> <Galgano>
Sent: Montag, 31. Juli 2006 18:15
To: [log in to unmask]
Subject: [SPM] In need of DTI help

Hello SPM experts!

I am in desperate need of some help. If you have 3 different
cognitive scores that were
measured from 3 different cognitive tasks, can you then correlate
these scores with each pixel's FA value (DTI output) in the DTI
brain map? Could this be done using only SPM? If so, can someone
explain how?

Thank you!
Jessica, NY

"Voxel-based correlational analysis. For each slice position,
analysis of the DTI data produces mean diffusivity, FA, and T2-
weighted images, which are identical in anatomic position. The
first step in image processing involved stripping of the skull and
dura using an automated algorithm22 (Brain Extraction Tool; Oxford
Centre for Functional Magnetic Resonance Imaging of the
Brain; http://www.fmrib.ox.ac.uk/fsl/bet/index.html). For each
subject,
the T2-weighted images were then fitted to a symmetric
echo-planar MRI brain template using a 12-parameter, affine
normalization
algorithm from Statistical Parametric Mapping23 (SPM
99, Functional Imaging Laboratory, Institute of Neurology,
University
College London, UK; http//www.fil.ion.ucl.ac.uk/spm). A
symmetric echo-planar template was used. An identical transformation
was then applied to the mean diffusivity and FA images.
This was repeated for all subjects so that a full set of DT images
was produced, all fitted to an identical template. All of the
normalized
images were reviewed visually to ensure that there were
no obvious registration errors. The normalized images were then
smoothed using an isotropic Gaussian filter (full width half maximum
4 mm). This process reduces the impact of small errors in
registration by recalculating the intensity at each voxel based on a
weighted mean of intensity at that voxel and surrounding voxels."