Hi Anna,

All EVs are filtered to match the filtering of the data, and this includes the confound EVs that are included from PNM.

https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FEAT/FAQ#How_are_motion_parameters_and_other_confound_EV_files_processed_with_respect_to_filtering.3F

So you do not need to do any filtering or pre-runs prior to running PNM.  Just run PNM and then include the output in your FEAT run.

All the best,
Mark


On 4 Aug 2017, at 05:23, Anna Forsyth <[log in to unmask]> wrote:

Hi FSL experts, 

I have a question about the times series you would input into the PNM programme. 

If I am aiming to run a 'Full Analysis' in Feat,  using the output PNM EVs  in the stats tab, and including highpass filtering / smoothing etc in the pre-stats tab, do I need to use for the input into PNM a timeseries that has already had these other preprocessing steps (the highpass filtering) added to it? 

i.e. run FEAT with just the pre-processing tab on then use filtered-func-data from this as the input to the PNM?   

I ask after reading the following:  "If nuisance regressors are obtained before bandpassing and are to be projected out of the data after it is bandpassed, they must be bandpassed by the same filter before the projection"  from Jo HJ, Gotts SJ, Reynolds RC, et al. Effective Preprocessing Procedures Virtually Eliminate Distance-Dependent Motion Artifacts in Resting State FMRI. Journal of applied mathematics. 2013;2013:10.1155/2013/935154. doi:10.1155/2013/935154.

Thank you for any advice you can give me, and hope you're all having lovely days!!

Anna Forsyth


--
Anna Forsyth, BA/BSc (Hons), A.T.C.L
PhD Candidate
School of Pharmacy
Faculty of Medical and Health Sciences
University of Auckland