Thanks, Matthew & Timothy, that gave me some valuable insight, I appreciate that!
All the best, David 2018-05-31 1:37 GMT+02:00 Timothy Coalson <tsc...@mst.edu>: > A bit more explanation: smoothing only spreads signal out, diluting it > with non-signal or unrelated signal, it can't concentrate it "towards" some > other relevant signal in another subject. For any case that has > non-negligible overlap of signals to begin with, smoothing basically just > dilutes the overlap with other nearby things. Thus, if you have one fixed > group ROI to begin with, which nearly all subjects have substantial signal > overlap with, smoothing is only going to hurt you (per-subject ROIs can do > even better, but generating them well is harder). Our preprint paper that > Matt linked to explores this in terms of how much signal from other > cortical areas or other tissues gets mixed in by smoothing (and by > volume-based cortical analysis), but this particular idea of "increasing > overlap" could also be tested by itself without taking crosstalk into > account, and would likely show that until initial overlap gets rather > small, common amounts of smoothing only make the overlap worse. > > By far, the biggest of the useful effects of smoothing is attenuating > noise (and for some things, there are other ways to accomplish this goal - > averaging data across a sizable ROI will be far more effective at reducing > spatial noise, so if that is part of your analysis anyway, you don't get > this benefit from adding smoothing, but you do get the detriments of the > smoothing). If your noise is largely independent per-voxel, then most of > this attenuation occurs at relatively small smoothing amounts anyway. > > Also, be careful about regressing out WM and CSF, if your masks don't > leave sufficient space from cortex, then it can pick up what is basically > the mean gray matter signal, and cause you to accidentally do GSR. > > Tim > > > On Wed, May 30, 2018 at 6:58 AM, Glasser, Matthew <glass...@wustl.edu> > wrote: > >> Indeed that is one of the major fallacies in brain imaging. Have a look >> at this paper in press at PNAS: >> >> https://www.biorxiv.org/content/early/2018/04/23/255620 >> >> Peace, >> >> Matt. >> >> From: David Hofmann <davidhofma...@gmail.com> >> Date: Wednesday, May 30, 2018 at 5:14 AM >> To: Timothy Coalson <tsc...@mst.edu>, Matt Glasser <glass...@wustl.edu> >> Cc: hcp-users <hcp-users@humanconnectome.org> >> Subject: Re: [HCP-Users] Additional smoothing of FIX extended resting >> state data? >> >> Hi all, >> >> thanks for the comments! The idea to smooth the data was based on others >> papers which did not use HCP data though. I always thought that >> smoothing is a "good idea" for group studies in order to account for the >> between-subject variability in the ROI based on the different brain sizes >> and shapes. >> >> The analysis I want to run uses the data from ROIs to calculate >> connectivity between ROIs (DCM). The ROI extraction in SPM uses the >> component that explains the most variance in a PCA. The extraction runs on >> the smoothed volumes. The ROIs are based on some probabilistic atlas (e.g. >> anatomy toolbox). I have about 300 subjects. >> >> I thought the results will be relatively robust for different levels of >> smoothing. But this is not the case. Since the CSF and WM signals have >> been regressed out, I did not assume that this will have influence. >> >> The unsmoothed results look much better though. >> >> greetings >> >> David >> >> 2018-05-30 0:51 GMT+02:00 Timothy Coalson <tsc...@mst.edu>: >> >>> Volumetric smoothing in particular is not advised, as it causes signal >>> from one bank of a sulcus to bleed into the opposite bank. Analyses that >>> average all signal within an ROI should have no benefits (and will have >>> detriments) from smoothing, as the within-ROI averaging itself is a form of >>> smoothing (but with a well-chosen ROI, it won't bring in signal from the >>> opposite sulcal bank, etc, in theory). Is this the kind of ROI analysis >>> you are doing? If so, I wouldn't trust the differences caused by adding >>> volume-based smoothing, because they could be from nearby areas instead. >>> >>> Tim >>> >>> >>> On Tue, May 29, 2018 at 4:24 PM, David Hofmann <davidhofma...@gmail.com> >>> wrote: >>> >>>> Dear all, >>>> >>>> as far as I read in previous posts on the list, spatial smoothing of >>>> the volumetric resting state data is not recommended. But this was >>>> with regard to group ICA. >>>> Would you also recommend not to apply any further spatial smoothing for >>>> the (volumetric) resting state data, when running ROI-based (group) >>>> analysis on multiple subjects? >>>> >>>> Comparing the results of smoothed (4,6, FWHM) and unsmoothed data gives >>>> highly different results in my case, so I'm a bit confused now. >>>> >>>> greetings >>>> >>>> David >>>> >>>> _______________________________________________ >>>> HCP-Users mailing list >>>> HCP-Users@humanconnectome.org >>>> http://lists.humanconnectome.org/mailman/listinfo/hcp-users >>>> >>> >>> >> > _______________________________________________ HCP-Users mailing list HCP-Users@humanconnectome.org http://lists.humanconnectome.org/mailman/listinfo/hcp-users
