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HiOn 23 Jul 2014, at 13:28, Paul Beach <[log in to unmask]> wrote: > Stephen, > > Thank you for your advice. > > I figured that I would try and regress out the confounders and perform individual ICA exploration using FEAT. This step would be performed on data that have been pre-processed through WM/CSF regression (and obviously the motion correction performed in fsl_motion_outliers). that's OK as an exploratory approach - however, normally if you are going to apply both ICA cleanup and confound-regressor cleanup, we would recommend running the ICA first. > > Would you also suggest using FIX after doing this, or is that overkill? same answer - ICA+FIX is logically the same as ICA cleanup with manual artefact component identification > > Also, as for training the FIX classifier: since I have AD and healthy control subjects, should I use equal numbers of both groups in the 10 or so training subjects? Yes I would think so. Cheers. > > > Thanks again > > > On Wed, Jul 23, 2014 at 4:43 AM, Stephen Smith <[log in to unmask]> wrote: > Hi > > On 22 Jul 2014, at 17:03, Paul Beach <[log in to unmask]> wrote: > >> FSL experts and users, >> >> I'm working toward an ICA analysis on healthy controls and AD patients for the first time and thus I am very interested in making sure I appropriately deal with motion confounds. >> >> I've been looking through past message board correspondence on this topic and I can't seem to find anything too conclusive wrt just when/where to include the fsl_motion_outliers output as a confound EV (specifically using the Power (2012) methodology). >> >> It seems like the most recent discussion about this topic suggested doing so at the single subject level, PRIOR to doing any group ICA/dual-regression steps (i.e. doing a single-subject melodic run and including the output in the post-stats model/contrast). Is this correct? > > Nearly - though I would recommend that if your main analysis is group-ICA followed by dual regression, then you should do within-subject cleanup - either using FIX, or regressing out confounds like motion-outliers, etc. > >> Some of the messages also discuss interest in developing a melodic-based classifier to automatically pick out/remove motion-based components. This is yet to be incorporated in FSL, correct? > > This is FIX, which is released as an FSL "plugin" now. > > Cheers. > > >> >> What are other folks doing to address this issue? >> >> >> Thanks >> -- >> Paul Beach >> DO/PhD candidate - Year VI >> Michigan State University >> - College of Osteopathic Medicine >> - Neuroscience Program >> - MSU Cognitive and Geriatric Neurology Team (CoGeNT) > > > --------------------------------------------------------------------------- > Stephen M. Smith, Professor of Biomedical Engineering > Associate Director, Oxford University FMRIB Centre > > FMRIB, JR Hospital, Headington, Oxford OX3 9DU, UK > +44 (0) 1865 222726 (fax 222717) > [log in to unmask] http://www.fmrib.ox.ac.uk/~steve > --------------------------------------------------------------------------- > > Stop the cultural destruction of Tibet > > > > > > > > -- > Paul Beach > DO/PhD candidate - Year VI > Michigan State University > - College of Osteopathic Medicine > - Neuroscience Program > - MSU Cognitive and Geriatric Neurology Team (CoGeNT) --------------------------------------------------------------------------- Stephen M. Smith, Professor of Biomedical Engineering Associate Director, Oxford University FMRIB Centre FMRIB, JR Hospital, Headington, Oxford OX3 9DU, UK +44 (0) 1865 222726 (fax 222717) [log in to unmask] http://www.fmrib.ox.ac.uk/~steve --------------------------------------------------------------------------- Stop the cultural destruction of Tibet