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Thanks, a follow-up question, should we use intensity normalization instead? On Fri, Apr 9, 2010 at 4:40 PM, Stephen Smith <[log in to unmask]> wrote: > Hi - using confounds can indeed help, though we wouldn't recommend global > mean timeseries for this. Better options are confound timeseries from > physiological monitoring, head motion parameters, and timeseries derived > from conservative white matter and CSF masks / voxels. > Cheers. > > > > On 7 Apr 2010, at 16:55, Ciara McCabe wrote: > > Dear FSl > > I have recently completed resting state analysis using the hypothesis driven > approach using featquery to get the timeseries and then using this in the > FEATS as a regressor then group differences > > > Im wondering though if I need to go back and use a global time series as > another regressor in each lower level feat to remove noise such as breathing > etc? > > any help much appreciated > > Thanks > > Ciara > > > > --------------------------------------------------------------------------- > 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 > --------------------------------------------------------------------------- > > > > -- Best Regards Xue, Feng Phd. candidate Major in Developmental Cognitive Neuroscience National Key Laboratory of Cognitive Neuroscience and Learning Beijing Normal University Beijing, China. 100875 Tel: +86-13810154455 web: http://psychbrain.bnu.edu.cn ============================================== Welcome to MuDuo JinSheng BBS @ Beijing Normal University telnet://bbs.mdjs.org http://bbs.mdjs.org