I fully agree with Matt. This is our repeated experience with 'legacy' data that we push through HCP pipelines. Taking cortical signals to the surface results in major gains. Best, Alan
________________________________ From: [email protected] <[email protected]> on behalf of Glasser, Matthew <[email protected]> Sent: Thursday, February 23, 2017 6:27:28 PM To: NEUROSCIENCE tim; Jared P Zimmerman Cc: [email protected] Subject: Re: [HCP-Users] volume-smoothing and volume-parcel-smoothing introducing holes in data There is a substantial loss of benefit to analyzing HCP style data with traditional volume-based approaches. You would be better off reanalyzing the old data using HCP-Style approaches (even old data will benefit substantially from this) than trying to analyze HCP data using traditional approaches. Peace, Matt. From: <[email protected]<mailto:[email protected]>> on behalf of Timothy Coalson <[email protected]<mailto:[email protected]>> Date: Thursday, February 23, 2017 at 4:47 PM To: Jared P Zimmerman <[email protected]<mailto:[email protected]>> Cc: "[email protected]<mailto:[email protected]>" <[email protected]<mailto:[email protected]>> Subject: Re: [HCP-Users] volume-smoothing and volume-parcel-smoothing introducing holes in data wb_command -file-information has a column with a count of inf/NaN values. Since -fix-zeros has an effect, I suspect that some kind of thresholding is going on in fsl_view, rather than the smoothing being the issue. The volume parcel smoothing will output zero values anywhere that you don't have a parcel, so of course it will have that kind of "hole" regardless of the options used. The .nii.gz file is compressed, so being 4.2G doesn't have that much relation to its uncompressed size in memory, and there is also the memory required for coloring information. You can use -volume-merge to pull a single frame from the file so that you can load it in wb_view. Tim On Thu, Feb 23, 2017 at 4:24 PM, Jared P Zimmerman <[email protected]<mailto:[email protected]>> wrote: Thanks for the reply Tim, I’m having trouble getting them to open in wb_view. Running out of memory even when I request 60G, though the files themselves are 4.2G. There’s only 1 overlay in the red-yellow palette there and it’s overplayed over the MNI152_T1_2mm template. I think it looks like multiple overlays because of the parcel smoothing with the FSL structseg restricting the smoothing to cortex, CSF, sub-cortex etc. I don’t think there are NaNs in my data because I used -fixnan 0 in my call to -volume-math when demeaning and normalizing (see below). Is there an easy way to check for NaNs with workbench, or do I have to read it into Matlab? When I do -volume-smoothing with -fix-zeros I don’t get holes but I do get dilation. Guessing I can fix this by including a brain mask with -roi though. That may be sufficient for my needs right now, though I’m confused why that doesn’t fix it with the parcel smoothing. I did use -exclude-outliers 3 3 in calling -volume-reduce to make my mean and stdev images, which I thought would be important for removing background that appear to be 0, but maybe I’m mistaken and this is the source of my problem? demeaning and variance normalization: wb_command -volume-math '(x-mean)/stdev’ \ ${subID}_demean_${run}_hp2000_clean.nii.gz \ -fixnan 0 \ -var x ${run}_hp2000_clean.nii.gz \ -var mean mean_${run}_hp2000_clean.nii.gz -repeat \ -var stdev stdev_${run}_hp2000_clean.nii.gz -repeat Best, Jared On Feb 23, 2017, at 4:17 PM, Timothy Coalson <[email protected]<mailto:[email protected]>> wrote: The -fix-zeros options are basically designed to to dilation into regions of zero values, so you probably shouldn't be using it. Maybe your input data has NaN values in it? That would lead to holes that expand with the smoothing kernel (but should have cube shapes, so it doesn't quite seem to fit your images). I also don't know what causes fslview to draw a "hole", so there might be other possible causes - see what it looks like in wb_view. I'm also not sure exactly what you are overlaying in those images, it almost looks like the first one has more than one image overlaid in the red/yellow palette. Tim On Thu, Feb 23, 2017 at 12:21 PM, Jared P Zimmerman <[email protected]<mailto:[email protected]>> wrote: Hi HCP users, I’m having a problem smoothing volume data with workbench, where both -volume-smoothing and -volume-parcel-smoothing are creating holes in my data. See the attached screenshot for an example. I’ve tried both with and without -fix-zeros and this fixes the holes for -volume-smoothing, however it also seems to dilate my image so that it becomes ~120% the size it should be (image also attached). Parcel smoothing seems to fix the dilation problem, but it still introduces holes in the data regardless of whether the -fix-zero flag is used. For my parcels I’m using FSL’s MNI152_T1_2mm_structseg.nii.gz as a first pass. Any idea as to why these holes are popping up? <Screen Shot 2017-02-23 at 12.53.24 PM.png> <Screen Shot 2017-02-23 at 1.06.49 PM.png> thanks, Jared _______________________________________________ HCP-Users mailing list [email protected]<mailto:[email protected]> http://lists.humanconnectome.org/mailman/listinfo/hcp-users<https://urldefense.proofpoint.com/v2/url?u=http-3A__lists.humanconnectome.org_mailman_listinfo_hcp-2Dusers&d=DwMF-g&c=-dg2m7zWuuDZ0MUcV7Sdqw&r=6xoTHSFAR6_hmigOST8YV4Vdph36uG3jgHMnAe6u7Nw&m=tfF-OLZHiNAkzl19pLWw8lijiMBYKX1VXcDUsgOAdcs&s=GUNbwFyi6QS8msouv7W-I2SWuppgFJqfSF_-EkhFjW8&e=> _______________________________________________ HCP-Users mailing list [email protected]<mailto:[email protected]> http://lists.humanconnectome.org/mailman/listinfo/hcp-users<https://urldefense.proofpoint.com/v2/url?u=http-3A__lists.humanconnectome.org_mailman_listinfo_hcp-2Dusers&d=DwMF-g&c=-dg2m7zWuuDZ0MUcV7Sdqw&r=6xoTHSFAR6_hmigOST8YV4Vdph36uG3jgHMnAe6u7Nw&m=tfF-OLZHiNAkzl19pLWw8lijiMBYKX1VXcDUsgOAdcs&s=GUNbwFyi6QS8msouv7W-I2SWuppgFJqfSF_-EkhFjW8&e=> ________________________________ The materials in this message are private and may contain Protected Healthcare Information or other information of a sensitive nature. 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