Hi, mh - may be I am wrong here, but from my point of view, high-pass filtering AND detrending is not "necessary". What happens if you zscore/detrend your data without step (4). My guess would be, that this somehow strange effect of negative correlation will disappear.
Bests, Matthias John Clithero schrieb: > Hi, > > Looks like my email with the voxel image is waiting for moderator > approval, so here is my updated response without the picture: > > On Tue, Oct 6, 2009 at 4:39 PM, Yaroslav Halchenko > <[email protected]> wrote: >> On Tue, 06 Oct 2009, John Clithero wrote: >>> The 'wb_file' is func data with the relevant timepoints... it has had >>> some preprocessing done in FSL (motion correction, slice timing, brain >>> extraction). The ROI mask is a whole brain mask. It seems (I hope) >>> that the NiftiDataset is being put together correctly. >> wild guess - may be while doing FSL preprocessing you've done some >> intensity normalization? > Here (sorry if I didn't list them) are the preprocessing options I used in FSL > (1) brain extraction > (2) motion correction > (3) slice-timing correction > (4) high-pass filtering > Added this just now: > As far as I know, FSL does the following (from website and their > course lectures): > "Scale each 4D dataset by a single value to get the overall 4D mean > (dotted line) to be the same" > The intensitiy normalization was off during preprocessing (as FSL recommends). > Is this what you were asking about? > >> >>> This perfect negative correlation occurs even if I feed in arbitrary >>> labels to the NiftiDataset, so there must be some sort of error in how >>> I'm using detrend and/or score?? I am guessing this is my erros since >>> the raw feature data looks fine to me. >>> This perfect negative correlation also occurs after just implementing >>> "zscore" or "detrend", although obviously the values are different. >> so, they aren't present in just loaded dataset but if you do zscore or >> detrend -- they come? > > If I break data in half (A trials vs B trials, or random) before using > zscore or detrend, I generally see strong positive correlation (some > voxels are just more active than others across the experiment...this > makes sense). But, once I use zscore or detrend....then goes to > perfect negative correlation (when looking at meanA vs meanB). > Each voxel after zscore, as it was said early, will have a mean of > zero across all trials...this is true for all the voxels. > >> could you just plot 1 voxel (which later carries perfect correlation) >> before/after detrend? >> > This is waiting for moderator approval, I guess. > Thanks for the help. > > Cheers, > John > > >> -- >> .-. >> =------------------------------ /v\ ----------------------------= >> Keep in touch // \\ (yoh@|www.)onerussian.com >> Yaroslav Halchenko /( )\ ICQ#: 60653192 >> Linux User ^^-^^ [175555] >> >> >> >> _______________________________________________ >> Pkg-ExpPsy-PyMVPA mailing list >> [email protected] >> http://lists.alioth.debian.org/mailman/listinfo/pkg-exppsy-pymvpa >> > > _______________________________________________ > Pkg-ExpPsy-PyMVPA mailing list > [email protected] > http://lists.alioth.debian.org/mailman/listinfo/pkg-exppsy-pymvpa _______________________________________________ Pkg-ExpPsy-PyMVPA mailing list [email protected] http://lists.alioth.debian.org/mailman/listinfo/pkg-exppsy-pymvpa
