I would guess that you have done image realignment without reslicing, and the
spatial normalisation is incorporating the movement parameters. This would
make what is happening analagous to resampling the realigned images using
nearest neighbour interpolation.
If you translate an image by anything less than 1/2 voxel, then the resampled
images would remain the same if nearest neighbour interpolation is used. At
a 1/2 voxel translation, the resampled image would suddenly be like a 1 voxel
translation. I think that what you are seeing are these sudden jumps.
Best regards,
-John
> This is a question about nearest neighbour interpolation
> used in the process of normalization.
>
> I normalized a functional dataset with this interpolation
> method. The normalized images look fine, but in several
> voxels, there are strange signal behaviors.
>
> The attached jpeg image shows an example. That is a plot of
> a timecourse of one voxel in the grey matter. The signal
> proceeds with small ups and downs for several time points,
> but around the first one-third of the timecourse, it
> suddenly jumps up, and after that it proceeds normally
> again.
>
> Such an odd signal behavior is seen in many other voxels.
> Some show jump-ups, some show drop-downs, and others show
> both. Those voxels seem to be distributed around the whole
> brain randomly.
>
> I tried normalizing the same data set with the other two
> interpolation methods, sinc and bilinear. In these two cases
> no strange signal behaviors were observed.
--
Dr John Ashburner.
Wellcome Department of Cognitive Neurology.
12 Queen Square, London WC1N 3BG, UK.
tel: +44 (0)20 78337491 or +44 (0)20 78373611 x4381
fax: +44 (0)20 78131420
http://www.fil.ion.ucl.ac.uk/~john
mail: [log in to unmask]
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