Dear Jessica,
do I understand you correctly that you have 3 different behavioural scores
per subject and want to find whether there are areas in FA maps of a
group of subjects where anisotropy changes in relation to the behaviour
scores? If so, yes this is technically possible with SPM - however you
need to consider that FA is a quantity limited to a range between 0 and 1.
Correlating this with arbitrary unlimited scores will not give
meaningful results, but you should be fine with e.g. percent-range scores.
Volkmar
On Mon, 31 Jul 2006, <Jessica> <Galgano> wrote:
> 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."
>
>
--
Volkmar Glauche
-
Department of Neurology [log in to unmask]
Universitaetsklinikum Freiburg Phone 49(0)761-270-5331
Breisacher Str. 64 Fax 49(0)761-270-5416
79106 Freiburg
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