Re: [HCP-Users] Grand Mean Intensity Normalization

We consider those “intermediate” files and thus they aren’t part of our released packages or “CinaBox” disks. So, this could be rather challenging. You would need to use “REST” calls into the ConnectomDB database directly to pull down the files for each run. Perhaps you could describe why

Re: [HCP-Users] Grand Mean Intensity Normalization

Jacobian wasn’t used for the 3T fMRI data. Also the bias field correction was non-optimal. These are the files that you would want: 1) ${StudyFolder}/${Subject}/${fMRIName}/BiasField.2.nii.gz 2) ${StudyFolder}/${Subject}/${fMRIName}/rfMRI_REST1_LR_nonlin.nii.gz 3)

Re: [HCP-Users] Grand Mean Intensity Normalization

Hi Matt and Michael, Thank you both for your helpful replies. If I wanted to back-calculate the original mean of the rfMRI image after bias field and Jacobian correction, do you know what the appropriate files would be to do this? Looking at the HCP data/intensity normalization script, I

Re: [HCP-Users] Grand Mean Intensity Normalization

Just to expand on this, since I think I might know why you are asking. The grand mean is computed on the brain masked volume timeseries, after bias field correction and jacobian modulation is first applied – see the end of IntensityNormalization.sh, which is called as the final step in

Re: [HCP-Users] Grand Mean Intensity Normalization

1) The overall mean of each scan is 1, this is not done voxelwise (e.g. like a bias correction would be). 2) Unfortunately this information is not saved. I don¹t think fslmaths outputs it, perhaps it could be back computed from some intermediate files. Peace, Matt. On 4/11/18, 2:21 PM,

Re: [HCP-Users] gradient nonlinearity correction question

That code uses trilinear interpolation by default, but you can output a warpfield and use splines which should be much crisper. Peace, Matt. On 4/11/18, 11:59 AM, "hcp-users-boun...@humanconnectome.org on behalf of Kristian Loewe"

[HCP-Users] Grand Mean Intensity Normalization

Dear HCP Experts, I am currently using the temporally preprocessed rfMRI data in the S900 release (aka rfMRI_REST?_??_Atlas_hp2000_clean.dtseries.nii). According to the Smith 2013 NeuroImage paper, it sounds like the images I am using have all received global intensity normalization prior to

Re: [HCP-Users] Human-Macaque deformation map in wb_view?

In Caret5: * Select File Menu -> Save Data File * In the Save Data File Dialog, set the File Type to GIFTI Functional File (*.func.gii) * Change the File Name so that it ends in “.func.gii” (may want to click the File Name button to choose the name with a file selection dialog) * Verify that the

Re: [HCP-Users] gradient nonlinearity correction question

Hi Steve, > Hi - no, in my experience running the post-hoc correction should > look virtually identical to the on-scanner correction. Thanks! At least it's clear then that I should keep looking into this. > Note that this will not be the case for 2D (eg EPI) data because > on-scanner can only

Re: [HCP-Users] gradient nonlinearity correction question

Hi Joo-won, I am not sure, which one looks more anatomically reasonable. The scanner-corrected one looks a little bit more crisp compared to the offline-corrected, which appears a little more smooth by comparison. Perhaps this could have something to do with the interpolation algorithm used?

Re: [HCP-Users] gradient nonlinearity correction question

Hi - no, in my experience running the post-hoc correction should look virtually identical to the on-scanner correction. Note that this will not be the case for 2D (eg EPI) data because on-scanner can only be done 2D - so that won't match post-hoc 3D correction. Cheers. > On 11 Apr 2018, at

Re: [HCP-Users] gradient nonlinearity correction question

Hi Michael, Thanks for the suggestion! By default, we are using the 3D correction on the scanner. But I applied the 2D correction to the ND data set separately to see what it looks like. The result is different from both the 3D-scanner-correction and the offline-correction but looks

[HCP-Users] Reprocessed 7T fMRI data released + S1200 updates

News from the Human Connectome Project (HCP) April 11, 2018 The HCP consortium is pleased to announce the release of fully reprocessed 7T fMRI data for 184 HCP-Young Adult (HCP-YA) subjects for download on ConnectomeDB. The rerelease corrects the error in the 7T

Re: [HCP-Users] Human-Macaque deformation map in wb_view?

Hi Saad, Not that I am aware of. Probably better to generate distortion maps (e.g. isotropic and anisotropic strains). Matt. On 4/11/18, 10:28 AM, "hcp-users-boun...@humanconnectome.org on behalf of Saad Jbabdi"

Re: [HCP-Users] gradient nonlinearity correction question

Hi Kristian, Which one looks more reasonable, online or offline correction for subject data? On my data, dicom header (0019, 1014) contains table position. Best, Joo-won On 4/11/18, 9:31 AM, "Kristian Loewe" wrote: Hi Joo-won and Keith, I don't think

Re: [HCP-Users] gradient nonlinearity correction question

One thought: Are you sure you are using the “3D” (and not the “2D”) correction on the scanner? -- Michael Harms, Ph.D. --- Associate Professor of Psychiatry Washington University School of Medicine Department of Psychiatry, Box 8134