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Hi, This is certainly a *lot* of components, and you wouldn't normally get this many. The number is affected by the number of timepoints in your data, but also the amount of structured signal/artefact. It might be more helpful to set the dimension (i.e. the number of components) to a smaller value manually (turn the automatic dimensionality estimation off within the Stats tab of the Melodic GUI) and see what you see in the data. If you have strong artefact then it is likely that these will appear clearly in a reduced set of components and that you could use these to denoise the data. All the best, Mark On 30 Apr 2014, at 22:04, Marco Solmi <[log in to unmask]> wrote: > Dear FSL experts, > > I am having some problems with fMRI data with behavioral task that do not show expected results. > I am familiarizing with different preprocessing options; in a subject with a lot of motion I tryed feat with motion_outliers (often runs out of memory-you already clarified this point-thanks!), and ICA exploration with no model within the feat - prestats only(with more than 900 IC detected). > > > The questions are: > How can I deal with more than 900 IC (hand search does not seem feasable-maybe I can increase the false negative-false positive ratio)-how could I chose the IC instead of a manual search? I am rerunning the same with the design matrix specified, should I expect something different from 900 IC? should it be better to run it with the already MCFLIRT motion corrected image? > > Thanks!