Freesurfer April 2018

freesurfer@nmr.mgh.harvard.edu

118 participants
177 discussions

Problems Extending the Pial Surface
by Saum Naderi 12 May '18

12 May '18

External Email - Use Caution Hi guys, I'm having some trouble extending the pial surface of my bm volume. I am aware that the general procedure for extending the pial is to extend the wm first and the pial will follow. However, is it possible to extend the pial surface without affecting the wm boundary? Thanks, Saum

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mri_vol2surf
by Abdullah Ishaque 09 May '18

09 May '18

External Email - Use Caution Hi, It's my first time using FreeSurfer and I'd like some guidance regarding some of my steps. I'm attempting to perform myelin mapping as outlined in the paper by Righart (2017) Ann Neurol. Overall, I want to calculate myelin maps from each subject, sample them from the mid-cortical level to create cortical myelin surface maps, and perform vertexwise and ROI based analyses. Here's what I've done so far: 1. recon-all for all the subjects 2. Used bbregister to register the native T2 scans to the conformed T1 scans using this command: bbregister --s C01 --mov C01_T2.nii --init-fsl --reg register.dat --t2 (my understanding here is that this generates the .dat file that has the transformation to register the T2 image to the conformed orig.mgz file from subject C01) 3. Applied the register.dat file to the native T2 using mri_vol2vol --mov C01_T2.nii --o T2_conformed.mgz --fstarg --reg register.dat (this registers the T2 to the orig.mgz file in the conformed space) The next step for me is to perform mri_vol2surf. My question here is, which file should I select for the --srcreg flag and what should the --trgsubject input be? Secondly, am I on the right track to complete the analysis i.e., correct file types and my understanding of the steps? Clarifications regarding these questions and any suggestions for further directions will be very helpful! Let me know. Thanks!

4 7

Non-parametric correlation between FC and neuropsychological/volumetric outcomes
by stdp82＠virgilio.it 08 May '18

08 May '18

Hi list, which the best way to perform a whole-brain correlation of the FC assessed by FS-FAST with the volumetic or neuropsychological outcomes? Please note that my question is specifically addressed to those factors (neuropsycholgical scores or volume of seed) did not show a normal distribution and that cannot be trasformed. Thanks Kind regards Stefano

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Query regarding creation of atlas directly from probabilistic information
by Mageshwar Selvakumar 07 May '18

07 May '18

External Email - Use Caution Dear All and Bruce, This mail is on top of the query I had a couple of weeks back where I misinterpreted that I had binary mask of each structure as individual nifti volume files but on closer look, the nifti files had the probability that the structure is present at that certain location. On looking into the freesurfer website, I came across this documentation of creation of Atlas, https://surfer.nmr.mgh.harvard.edu/fswiki/SurfaceLabelAtlas SurfaceLabelAtlas - Free Surfer Wiki<https://surfer.nmr.mgh.harvard.edu/fswiki/SurfaceLabelAtlas> Overview. This document provides an overview of two related topics: How the FreeSurfer pipeline automatically labels a subject's regions (producing an annotation file) by comparing the subject's curvature data to an "atlas" ("gcs") file. surfer.nmr.mgh.harvard.edu In this documentation the process is done by looping through N subjects to get the probability information, and these subjects are registered to the registration template derived from average of reference templates. I would like to know if I could use these probability information directly and since the atlas information is already in the MNI152 space, can I use the registration template which is already available with freesurfer, and if yes, can someone guide me on which registration files I must use. Secondly, I tried using mri_vol2surf and tried to convert the volume data to a surface data before creating labels, but on doing so I had errors when creating labels from the surface files. To convert into volume I ran the below code: *mri_vol2surf --mov ID076_LL_PHGa_l_HvOx_prob.mgz --ref ID076_LL_PHGa_l_HvOx_prob.mgz --out ID076_LL_PHGa_l_HvOx_prob_surf.mgz --hemi lh --mni152reg --projdist-max -2 0 .1 --reshape --interp nearest* Then I to convert this surface file into label I ran *mri_cor2label --i ID080_CPuP_l_HvOx_prob_surf.mgz --l area1.label --id 076* And I got the error *Found 0 label voxels ERROR: found no voxels matching id 76* But the process runs fine if I run the mri_cor2label on the volume file. It would be nice if someone can help me out on where I'm going wrong here. Thank you, Kind regards Mageshwar Selvakumar, M.Sc Department of Pharmakologische Bildgebung und Bildanalyse Friedrich Alexander Universität Erlangen Nürnberg Office: Fahrstr. 17, 91054 Erlangen Phone: + 49-9131-8522898

3 5

Motion Parameter on the Cortical Surface
by Pfannmoeller, Joerg Peter 07 May '18

07 May '18

Dear all, in fMRI analyses the translation of the the brains center and the rotation of the associated coordinate system are determined. Did anybody of you ever write a tool to determine the corresponding motion of the cortical surfaces? What I mean is the total shift due to translation and rotation for each time point in the fMRI time series and for each point on the white matter or pial surface. Yours Joerg

2 1

vertex wise cortical thickness within ROIs
by Fujiwara, Hisako 07 May '18

07 May '18

External Email - Use Caution Hello FreeSurfer Developers, I'm attempting to compute absolute cortical thickness for each vertices within anatomical ROIs using apac.annot. I have successfully output the whole brain vertex wise cortical thickness using: mris_convert -c <subject>/surf/?h.thickness <subject>/surf/?h.org <subject>/surf/?hthickenss.asc Since this creates huge numbers (> e.g., 140,000) for each hemisphere for each participants, I would like to narrow out focus on the specific ROIs for relevant to our study? Is this achievable to add options to do? Thank you for your help in advance. Best regards, Hisako

3 4

fmriprep to fsfast interface
by Boggess, Matthew Jozsef 07 May '18

07 May '18

Hello, I've been working on taking the outputs of the fmriprep BOLD preprocessing tool (https://fmriprep.readthedocs.io/en/latest/index.html) and coercing them into the fsfast structure so that first levels can be run with mkanalysis-sess and selxavg3b-sess. It's been a bit trickier than anticipated and I was hoping to get some help verifying my current approach (attached to this email). Question 1: fmriprep outputs the preprocessed BOLD data in the T1 space (mni305 is not an option). However, the typical spatial normalization workflow uses a registration matrix from the bold to T1 to transform to talairach. Is there a way to do this transformation without having to specify a registration matrix given the functional data is already in the T1 space? My current approach is to use mri_convert with the --apply_transform flag pointing to the talairach.xfm registration matrix in the subject's recon folder, but I am not sure if this is a reasonable workaround. Question 2: fsfast normally calculates the global mean value of the raw data to be used for intensity normalization. However, with fmriprep I only have access to the preprocessed data in T1 space. Would extracting the global mean value for intensity normalization from the preprocessed BOLD in T1 space be valid? Question 3: Is there a way to do first levels in the native subcortical space? If so, what is the filename structure expected (maybe mni305.2mm gets replaced with the subject name as with the surface data)? I've only seen examples transforming to mni305 space, but ideally an option would be to just transfer the preprocessed BOLD in T1 space and run first levels staying in the native T1 space. Thanks for your help! Matt

3 6

wmparc.mgz transformation
by Rongxiang Tang 07 May '18

07 May '18

External Email - Use Caution Dear All, I would like to transform individual wmparc.mgz into MNI space for each of my subjects. I have tried using this command:mri_vol2vol --targ /data/mri/wmparc.mgz --mov /usr/local/fsl/data/standard/MNI152_T1_2mm.nii.gz --inv --reg /usr/local/freesurfer/subjects/fsaverage/mri/transforms/reg.mni152.2mm.dat --o test.mgz However, when I compare this output file with my FSL normalized functional data (MNI space), they didn't really match well - not a one-to one exact match (orientation slightly different), although the dimension and space are all in MNI 2mm. Do I need to use bbregister or other commands to transform it better? Thanks!Catherine

2 1

Comparison between T1 only recon-all and T1 + FLAIR recon-all
by O'Shea,Andrew 03 May '18

03 May '18

External Email - Use Caution Hello, In the past we have only used the T1 image as input for recon-all. However, we are now also acquiring a FLAIR image and were thinking of using both for new studies. Does anyone have any data on the differences/advantages of using FLAIR images with the FLAIRpial command? Any input would be greatly appreciated. Thanks! Andrew O'Shea, MSc. Clinical Research Coordinator II Woods Lab Center for Cognitive Aging and Memory McKnight Brain Institute Department of Clinical and Health Psychology College of Public Health and Health Professions University of Florida Phone (Office): (352) 294-5827 Phone (Cell): (586) 899-2771 Email: aoshea(a)phhp.ufl.edu

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Call for Papers: Connectomics in NeuroImaging Workshop at MICCAI 2018, Granada (Spain)
by Islem Rekik 30 Apr '18

30 Apr '18

External Email - Use Caution Hello Colleagues, The attached call for full-length papers flyer provides information about the 2nd International Workshop on Connectomics in NeuroImaging (*CNI 2018*), which will be held in parallel with the 21st International Conference on Medical Image Computing and Computer-assisted Intervention (MICCAI 2018) in Granada Spain. CNI 2018 is a full day workshop that will take place September 20th, 2018. Our topics of interest cover (but are not limited to): (1) New developments in connectome construction from different imaging modalities, (2) Development of data driven techniques to identify biomarkers in connectome data, (3) Brain network modeling and formal conceptual models of connectome data, (4) Machine learning algorithms and connectome data analysis, and (5) Evaluation and validation of connectome models. If you have research that fits into the scope of our workshop detailed on our website ( http://munsellb.people.cofc.edu/cni.html) we encourage you to submit a paper or an abstract! *** Why submit to the CNI workshop? *** - Three great keynote speakers, presentations and poster sessions with accompanying power pitches will provide you with ample opportunity for exchanges and discussions; - There will be an INCF sponsored Best Paper Award; - Accepted papers will be published in an LNCS proceedings and will be invited to submit to a special issue journal; - Discuss your science and collaborate with international computational neuroscientists and clinicians in an intimate setting. *** Full length paper submission *** Paper submission deadline, June 11 via https://cmt3.research.microsof t.com/CNI2018 *Download flyer using*: http://basira-lab.com/wp-content/uploads/2018/04/CNI-MICCAI-2018.tiff <http://basira-lab.com/wp-content/uploads/2018/04/CNI-MICCAI-2018.tiff> For more information visit http://munsellb.people.cofc.edu/cni.html *** Full length important dates *** Submission deadline: 11:59 PM PST, June 11th, 2018 Notification of acceptance: July 2nd, 2018 Camera-ready deadline: 11:59 PST, July 16th, 2018 Workshop date: Sept. 20th, 2018 *Also, if you know other colleagues that may be interested in submitting a full length paper, please feel free to pass along our workshop information to them. * We look forward to your participation! If you have any additional questions, please contact Brent Munsell ( munsellb(a)cofc.edu) or Ai Wern Chung (aiwern.chung(a)childrens.harvard.edu) ========================= CNI 2018 Chairs Islem Rekik, University of Dundee Ai Wern Chung, Boston Children's Hospital, Harvard Medical School Markus Schirmer, Harvard Medical School Guorong Wu, University of North Carolina, Chapel Hill Brent Munsell, College of Charleston

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Freesurfer April 2018