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Hi - we would advise very strongly against using 6 direction data in bedpost - sorry - This is even more true if you only have one average of your data. The reason for this is that the model used in bedpost has 5 free parameters + the variance of the noise. Therefore, you effectively have 1 degree of freedom to estimate this variance, so not only to do you get a very imprecise estimate of the orientations, but also a very bad estimate of this noise variance. The algorithm knows this, and therefore will give you huge uncertainty on your orientations, so you will get very imprecise tracking indeed - a very bad idea. In general, it is not wise to acquire 6 direction DTI data, given how quick it is to perform a useful DTI scan.. T On 11 Dec 2007, at 17:57, Rajkumar wrote: > Dear FSL Group, > We have just started using FSL 4. So far, we were > only doing > deterministic tractography using DTI images (acquired using 6 > directional > gradient with six repetitions is each direction). Recently we > acquired some > cases with 55 directions, and compared the probabilistic tract from > both 6 > and 55 directions and what we found was that the tracts > (Corticospinal tract, > Arcuate fasciculus, optic radiation, and corpus callosum) with 55 > directions > appeared bigger and more accurate than with 6 directions. Our > questions are, > 1) Can we use the six direction dti data sets to access the > connectivity > based seed classification of cortical and subcortical structures? > 2) Does > increasing the no of samples from 5000 to lets say 10000 help? (or > Please > provide other suggestions) 3) Are our 6 direction DTI data sets > useless for > probabilistic tractography? Thanks. > > > Rajkumar.M.G > Research Associate, > PET Center, > Children's Hospital of Michigan, > Detroit. >