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30097 discussions

FW: Correcting for both hemispheres in thickness analysis using a PFC mask
by Gold, Andrea (NIH/NIMH) [F] 24 Aug '16

24 Aug '16

Hi, I have a question about correcting for 2 hemispheres in a thickness analysis using a PFC mask. Here are the steps I ran: 1) I ran the analysis in qdec without a mask. 2) I found the mri_glmfit.log file from step 1 and cut out the mri_glmfit command that runs the analysis and replaced ³label² option with path to our mask: cmdline mri_glmfit --y /gpfs/gsfs3/users/EDAN/freesurfer/subjects/readyForGroupAnalysis/healthy_vs _anxious/qdec/Thickness_LH_sm10_Dichtomous_n151/y.mgh --fsgd /gpfs/gsfs3/users/EDAN/freesurfer/subjects/readyForGroupAnalysis/healthy_vs _anxious/qdec/Thickness_LH_sm10_Dichtomous_n151/qdec.fsgd dods --glmdir /gpfs/gsfs3/users/EDAN/freesurfer/subjects/readyForGroupAnalysis/healthy_vs _anxious/qdec/Thickness_LH_sm10_Dichtomous_n151 --surf fsaverage lh --label /gpfs/gsfs3/users/EDAN/freesurfer/buckner_data/tutorial_subjs/fsaverage/lab el/labels/PFC_mask_8ROIs_LH --C /gpfs/gsfs3/users/EDAN/freesurfer/subjects/readyForGroupAnalysis/healthy_vs _anxious/qdec/Thickness_LH_sm10_Dichtomous_n151/contrasts/lh-Avg-Intercept- thickness.mat --C /gpfs/gsfs3/users/EDAN/freesurfer/subjects/readyForGroupAnalysis/healthy_vs _anxious/qdec/Thickness_LH_sm10_Dichtomous_n151/contrasts/lh-Diff-anxiousyo uth-healthyyouth-Intercept-thickness.mat 3) I then ran mri_glmfit-sim: mri_glmfit-sim --glmdir ./Thickness_LH_sm10_Dichtomous_n151 --sim mc-z 10000 1.3 mc-z.1p3.abs --sim-sign abs Question: I am 99% the mri_glmfit-sim command does not correct for both hemispheres. Is it possible to figure out if the cluster survives correction for 2 hemis based on the cluster summary file (attached) from steps 1-3 above?: # ClusterNo Max VtxMax Size(mm^2) MNIX MNIY MNIZ CWP CWPLow CWPHi NVtxs Annot 1 2.480 124922 479.68 -7.2 29.0 -16.8 0.00440 0.00360 0.00530 887 medialorbitofrontal Thanks! Andrea -- Andrea Gold, Ph.D. Section on Development and Affective Neuroscience National Institute of Mental Health Room 201, Bldg. 15K, MSC 2670 Bethesda, MD 20892-2670 Phone: 301-827-9804 Fax: 301-402-2010 Email: andrea.gold(a)nih.gov <applewebdata://D38F487B-BA2B-4BF6-A9C4-96248AB2BE51/andrea.gold@nih.gov>

2 1

PET surface sampling
by Jonathan DuBois 24 Aug '16

24 Aug '16

Hi, I’m trying to use the PETsurfer Pipeline to perform BP analysis, but I’m not sure at which point in the pipeline to sample the data to the surface and what registration to use? I tried running the pipeline using dynamic kinetic modeling as described here: http://surfer.nmr.mgh.harvard.edu/fswiki/PetSurfer <http://surfer.nmr.mgh.harvard.edu/fswiki/PetSurfer>, and then used the following command to try and sample the BP map the surface: mri_vol2surf --hemi lh --projfrac .5 --out_type mgh --cortex --mov mrtm2/bp.nii.gz --reg aux/bbpet2anat.lta --o lh.bp_pf5.mgh But got the following error: ERROR: source volume is neither source nor target of the registration I also tried sampling the mrtm2/bp.nii.gz to the orig.mgz volume space and then to the surface using: mri_vol2vol --mov mrtm2/bp.nii.gz --reg aux/bbpet2anat.lta --o mrtm2/bp_2anat.nii.gz --targ $SUBJECTS_DIR/subject1/mri/orig.mgz; mri_vol2surf --hemi lh --projfrac .5 --out_type mgh --cortex --mov mrtm2/bp_2anat.nii.gz --regheader subject1 --o lh.bp_pf5.mgh This worked, although the surface file did not have any values… Could you please let me know what is the best way to sample the data to the surface, and if it should be down prior to mri_glmfit or after. Thanks Jonathan

2 1

which CUDA version driver to use
by Karamfil Bahchevanov 24 Aug '16

24 Aug '16

Dear Freesurfers, I'd like to experiment with faster proceesing, in fact I'd like to try CUDA. However there are several possible drivers for my quadro K2000. I'm not sure which one to choose. Should I install the latest 7.5. version, or use the older version 6, or even older? I'm not sure if the latest will run with freesurfer smoothly. Here is my system: Xeon e5-1620, QUADRO K2000 I'm running Freesurfer v5.3 on CentOS 6.8, kernel 2.6.32-642.1.1.el6.x86_64. Thank you, KMB

3 3

Fs 6.0 dev version update
by Vaz pandolfo, Renata 24 Aug '16

24 Aug '16

Dear FS experts, I downloaded the FS 6.0 dev version for Linux on 11.08.2016 and now I see that there is a new version since the 14th of August. I ran about 20 recon-alls with the 11.08 version and now I am wondering if there were any major changes between that and the new one, and if so, whether I should rerun anything. I am assuming that having the newest version is always better, but I would rather check if it is necessary before downloading the new one and rerunning all the recon-alls. Thanks! Renata Ps.: I am using the hippocampal subfields flag and checking the volumes of the subregions of the hippocampus.

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ROI-based laminar BOLD analysis
by James Wilks 24 Aug '16

24 Aug '16

Dear FreeSurfer team, My name is Alex Wilks, an undergrad in the fMRI lab at the University of Michigan. We are trying to learn the ropes of FreeSurfer so that we may be able to perform high resolution fMRI analysis across multiple cortical layers. So far, I have understood how to generate intermediate layers between the pial and white surfaces of the cortex, however, I’ve hit a roadblock in performing ROI analysis on specific regions of the brain to analyze the amplitude of the BOLD signal across the layers. I was going through your published article titled “Laminar analysis of 7 T BOLD using an imposed spatial activation pattern in human V1” and I believe that the steps you used to collect the data in the “ROI analysis” subsection of your article are what we would like to repeat. Could you walk me through the steps you took to study the BOLD response as a function of cortical depth? Respectfully, Alex Wilks

1 0

dmri_poistats
by Alshikho, Mohamad J. 24 Aug '16

24 Aug '16

Dear Freesurfer experts, I would like to inquire about the tool "dmri_poistats" https://surfer.nmr.mgh.harvard.edu/fswiki/PoistatsOverview. This tool is included as a beta release ( in FS5.3 and FS 6.0). In literature review I found colleagues used the version 1.4 of this tool. e.g. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2780023/ Kindly, I have the following two questions: 1. What is the final release of this tool? 2. I have DWI images and no T1 images are available. Is it reliable to do tractography for the corticospinal tract using this tool? Thank you for any advice! Mohamad

2 3

output description
by Vaz pandolfo, Renata 24 Aug '16

24 Aug '16

Dear FS experts, Is there a complete list of all output files followed by their description? The one I can find online seems to be incomplete (and/or out of date): https://surfer.nmr.mgh.harvard.edu/fswiki/ReconAllOutputFiles#A-allOutputFi… For example, the volumes brain.mgz and brainmask.mgz.If I would like to quickly check what the difference between them is, where should I look? Thank you! Renata

1 0

Using Freesurfer for skull stripping then reorienting images to use in FSL
by saraizad＠alumni.ubc.ca 23 Aug '16

23 Aug '16

Hello, We are using freesurfer to skull strip T1 images on a high-motion pediatric sample. We want to use freesurfer to get brain-only images and then do further analysis using FSL. The problem is that, in freesurfer, the images are in a different orientation than those in FSL. For example, the same brain extracted image in freesurfer seems to be rotated a bit more to the left than the image extracted in FSL. QUESTION: Does anyone with freesurfer or FSL knowledge know how to convert the freesurfer’s brain-only images so that we can use them in FSL for ICA (both group and individual) as well as TBSS and Tractography ( back on freesurfer)? Thank you for your time and expertise. Cheers, Sara

1 0

TRACULA: narrow probability distributions
by Newbold, Dillan 23 Aug '16

23 Aug '16

Dear Anastasia, I’ve been looking at a lot of Tracula path.pd files and I’ve found that some probability distributions are only a single voxel wide, similar to the path.map file. The few none-zero voxels in these path.pd files have very high probability values. When an isosurface is generated for these tracts, it looks like a short thin blob somewhere in the usual tract distribution. I’ve seen descriptions in the archives of similar “short thin tracts,” but, from what I have seen, no one has offered a satisfying explanation for why these occur. What I think is happening in these tracts is that a maximum-probability (or local maximum) path is found during a burn-in iteration and all following perturbations of that path are rejected. Since the probability value in the path.pd is equal to the number of sample paths intersecting that voxel, finding a local maximum early on results in a small number of very high-probability voxels. Consistent with this explanation, I’ve found that this issue occurs more frequently when nburnin is set to 1000 (default = 200). A similar issue can occur if a local maximum is found early during the sample iterations, and this results in a path.pd file containing a small number of voxels with very high values surrounded by a larger area of low-value voxels. When a 20% threshold is applied, the result is the same as when a local maximum occurs during a burn-in iteration. Does my understanding of this issue seem correct? None of this would be a problem if my only aim were to find the single path with the maximum a posteriori probability, but I’m concerned that the average and weighted_average sats for these tracts will be less accurate. Since these distributions include small fractions of the number of voxels included in most tract distributions, is it likely that the average and weighted_average stats from these narrow distributions are less representative of the whole tract and more subject to random noise? Given these concerns, what type of overall path statistics do you think is most descriptive of a tract? Also, do you feel that higher nburnin and nsample values should lead to superior results? I would have thought this to be the case, but now it seems to me that setting either of these values too high will result in narrow probability distributions and bad statistics. Thank you, Dillan

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TRACULA: narrow probability distribution
by Newbold, Dillan 23 Aug '16

23 Aug '16

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