Re: [HCP-Users] MELODIC denoising vs. released ICA-FIX datasets

Hi - it sounds like maybe it's working fine within the limits of slight differences in mathematical precision between the C++ vs matlab parts of the processing - so the main question would be - have you looked in a viewer at the difference image - e.g. are the voxels with large differences

Re: [HCP-Users] MELODIC denoising vs. released ICA-FIX datasets

I think this is more of a question for the FSL list, but I don't know fsl_glm well enough to say if what you are doing is equivalent or not. Peace, Matt. From: "Ely, Benjamin" > Date: Tuesday, September 27, 2016 at 7:20 PM To: Matt Glasser

Re: [HCP-Users] MELODIC denoising vs. released ICA-FIX datasets

Hi Matt and Greg, Thanks for the feedback! I've looked at the various fix .m files from the current release; based on fix_3_clean.m, I tried the following for a single resting-state run: # highpass filter; sigma of 1000.08 = FWHM of 2355 per Smith et al 2013 NeuroImage, also consistent with

Re: [HCP-Users] ROIs and Betas from Cifti Data

Actually, -cifti-math will output a dlabel file with an improper label table, which will look empty (it is not a proper dlabel file, but it does have the ROI you want in it). You should then use -cifti-change-mapping with -scalar on that output to make it into a viewable ROI file (you could also

Re: [HCP-Users] ROIs and Betas from Cifti Data

If you already have a dlabel file that excludes the things you aren't interested in, you don't need to bother with the -cifti-reduce I described. Since "unlabeled" is generally represented as 0, you can use -cifti-math with 'x > 0' to generate a combined binary ROI from that restricted dlabel

Re: [HCP-Users] ROIs and Betas from Cifti Data

To me, a mask is a binary ROI (1 where the stuff you want is, 0 elsewhere). This is quite different from a label file (lots of different integers). I did not mean for you to run -cifti-reduce on a dlabel file. I was suggesting that you use -cifti-label-to-roi to make a binary ROI from each

Re: [HCP-Users] ROIs and Betas from Cifti Data

The command I was using was : wb_command -cifti-reduce Brodmann_Bilateral_IFG.dlabel.nii MAX Brodmann_Bilateral_IFG_Merged.dscalar.nii Where Brodmann_Bilateral_IFG.dlabel.nii contains two labels. Again, this command does not seem to the production of a label file directly. Thanks On Sep 27,

Re: [HCP-Users] ROIs and Betas from Cifti Data

The easier way is to use -cifti-merge (or wb_shortcuts -cifti-concatenate for simpler syntax), then -cifti-reduce. It is possible to do with -cifti-math, but not as convenient. Tim On Tue, Sep 27, 2016 at 4:37 PM, Michael F.W. Dreyfuss < mid2...@med.cornell.edu> wrote: > Thank you, that

Re: [HCP-Users] ROIs and Betas from Cifti Data

Thank you, that works. Then if I want multiple parcels to be collapsed into a single ROI to make a mask spanning several ROIs that are not considered separate keys, which command would do that. Thank you, Michael On Sep 27, 2016, at 5:26 PM, Timothy Coalson

Re: [HCP-Users] ROIs and Betas from Cifti Data

The easiest way to deal with this is probably to use -cifti-separate to get them as gifti label files, which are each single-hemisphere. The use of the same key/name for both hemispheres was an unfortunate choice, which we intended to avoid in the future. Tim On Tue, Sep 27, 2016 at 4:15 PM,

Re: [HCP-Users] ROIs and Betas from Cifti Data

Thank you, The problem was that the computer I was using before had an older version of workbench. It works on my current computer. As far as using -cifti-label-to-roi How would that work with files like Human.Brodmann09.32k_fs_LR.dlabel.nii where the ROIs in both hemispheres are under the

Re: [HCP-Users] Label Import with -discard-others

For that, you want -cifti-separate, splitting into hemispheres (resulting in left and right label.gii files in this case) is exactly what it does. See my response in the other thread for pulling individual areas out of a parcellation and combining their ROIs. Tim On Tue, Sep 27, 2016 at 2:44

Re: [HCP-Users] ROIs and Betas from Cifti Data

The surface structures in -cifti-separate are much coarser, they represent the cifti file organization, not the parcellation areas. You want CORTEX_LEFT and CORTEX_RIGHT for that command to work. However, the outputs are gifti files, not cifti files - it is a format conversion command, and

Re: [HCP-Users] Label Import with -discard-others

In a related question, if I want to treat hemispheres separately, how can I create a simple hemispheric label file, or split a file like Human.Brodmann09.32k_fs_LR.dlabel.nii into two hemispheres to treat the Brodmann areas of each area separately? Essentially, all of my questions are

[HCP-Users] Label Import with -discard-others

Hello, I have been trying to make a file containing the parcellations for BA44 and BA45 using the Broadmann using the following command: wb_command -cifti-label-import Human.Brodmann09.32k_fs_LR.dlabel.nii BrodmannLabels.txt Brodmann_IFG.dlabel.nii -discard-others Where BrodmannLabels.txt

Re: [HCP-Users] ROIs and Betas from Cifti Data

I can get separate the volumetric part of cifti files with a command like: wb_command -cifti-separate ToyNogo_fdr_palm/ToyNogo_results_merged_tstat.dscalar.nii COLUMN -volume ACCUMBENS_RIGHT R_Acc_Beta.nii.gz -roi R_NAcc_ROI.nii.gz But when I try that on surface data I get the error:

Re: [HCP-Users] ROIs and Betas from Cifti Data

HCP did not have a task that was geared toward response inhibition. Furthermore, although it’s alluring to believe that a single parcel will encapsulate all of response inhibition, it’s doubtful. Why not select a set of parcels in and near IFG, and correct for multiple comparisons? Use a

Re: [HCP-Users] ROIs and Betas from Cifti Data

I agree, that’s why I was checking in to see if there was a sub parcel you had identified as being involved in response inhibition from your tasks, such as flanker. There is a lot of background of IFG being involved in response inhibition, particularly on go/nogo tasks,, so I was wondering if

Re: [HCP-Users] ROIs and Betas from Cifti Data

Hi Michael, Just a reminder to be careful here to avoid issues of circularity/double-dipping.  You indicated that you had a priori hypotheses about IFG involvement, but that doesn’t allow you to then select a particular IFG parcel based on your task activation map.  Ideally, you would