Freesurfer September 2019

freesurfer@nmr.mgh.harvard.edu

93 participants
143 discussions

Hippocampal Subfields Atlas
by ZZY 25 Sep '19

25 Sep '19

External Email - Use Caution Dear  Doug，      I have a group of multimode MRI data, including functional MRI, T1WI and diffusion MRI. We want to analyze the functional and structual connectivity between the hippocampal subregions.  Now, we have obtained individual-level atlas of hippocampal subfields for each subject by using FREESURFER 6.0 on the T1 image. What should we do next step? How do get a group-level atlas of hippocampal subfields and apply it to functuional and diffusion data?   Best, Zhiyong

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Color scale in TkSurfer and Freeview
by Zhi Li 25 Sep '19

25 Sep '19

External Email - Use Caution Dear Freesurfer experts, May I ask how could I customize the color scale in TkSufer? The default heat scale is blue-red. Could I change it to other colors, such as green-yellow or blue-white-red (like gradient)? Now I know how to customize the color scale in Freeview. The problem is in the 'custom' of Freeview I can not ignore zeros. Actually I'd like to display deactivation/negative value in 'light bule-white', activation/positive value in 'white-light red'. Any suggestions would be much appreciated. Best, lizhi

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Freesurfer vs. CAT12
by Maximo, Jose Omar 25 Sep '19

25 Sep '19

External Email - Use Caution Hi, Recently, I ran an analysis on Freesurfer and found increased cortical thickness on the patients compared to controls. Then, I heard about CAT12 and wanted to see if my results would be robust enough and be replicated using this other software. When I ran the analysis on CAT12, the results look completely different (both increased and decreases). I was not able to see the same clusters on the CAT12 results. I used the same subjects and covariates. I ran recon-all using both T1 and T2 images, whereas in CAT12 you can only use T1 images. Has anyone experimented with both software before? Best, Omar

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issue with lesions
by Sam W 25 Sep '19

25 Sep '19

External Email - Use Caution Hello, I have run recon-all on T1 scans of patients with WM lesions. I noticed however that for some patients the lesion is excluded from aparc.a2009s+aseg.mgz but for other patients it is included (and labelled as non-lesion). Ultimately I'd like to extract a) volume information in WM and b) volume information of the WM lesion. I think I can get the the WM volume from the wmparc.stats file. For the lesion volume I think I can take the WM-hypointensities from the aseg file right? However I noticed that if a lesion is on the right hemisphere, the Right-WM-hypointensities shows 0s in all columns, which cannot be right. I have a mask of the lesion (1s where lesion occurs, 0s elsewhere) in anatomical space, can I use this mask somehow in FS to inform recon-all where the lesion occurs? Thanks in advance! Sam

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Unable to access previous email archives
by Mageshwar Selvakumar 25 Sep '19

25 Sep '19

External Email - Use Caution Dear Freesurfer community, I have not been able to access the mail archives this week. It redirects to Martinos Center and asks me for a NMR Login and password. Is this the same login details we used to subscribe to the mailing list? I tried but my details didn't work. Looking forward for your replies. 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

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Re: [Freesurfer] Command not found
by fsbuild 24 Sep '19

24 Sep '19

External Email - Use Caution Hello Samer, The git bash shell on Windows will not be sufficient to run freesurfer programs on Windows.  Freesurfer is supported on CentOs Linux, Ubuntu Linux and MacOS.  However, some folks use the Ubuntu shell as supported on Windows 10.  This does work once setup in Windows and after some packages have been added to the Ubuntu image.  I have not used the Ubuntu shell on Windows very much, but you can read about installing and using it via the links below. - R. http://www.techken.in/linux/how-to-run-gui-ubuntu-linux-in-windows-10/ https://christopher5106.github.io/admin/2018/02/02/configure-windows-10-for… Samer Muhareb September 24, 2019 at 13:37         External Email - Use Caution        Hello, I am having trouble adding Freesurfer onto my PC. I have the program downloaded, but when I attempt to input a command from the Freesurfer program, it tells me that my command was not found.  This is my first time downloading a program to use in the command line without it being done for me, so I am not super clear on how to go about solving this issue or may have missed a crucial step. I was suggested to add the program onto the path but I am not really sure how to do that.  Any ideas or suggestions will be very helpful! I am using git bash on my windows, if that is helpful Thanks for taking the time to look into this, it is greatly appreciated.  Best,Samer Muhareb  _______________________________________________ Freesurfer mailing list Freesurfer(a)nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer

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Command not found
by Samer Muhareb 24 Sep '19

24 Sep '19

External Email - Use Caution Hello, I am having trouble adding Freesurfer onto my PC. I have the program downloaded, but when I attempt to input a command from the Freesurfer program, it tells me that my command was not found. [image: image.png] This is my first time downloading a program to use in the command line without it being done for me, so I am not super clear on how to go about solving this issue or may have missed a crucial step. I was suggested to add the program onto the path but I am not really sure how to do that. Any ideas or suggestions will be very helpful! I am using git bash on my windows, if that is helpful Thanks for taking the time to look into this, it is greatly appreciated. Best, Samer Muhareb

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Error during processing data. mris_make_surfaces malloc: *** error for object 0x2431900024317: pointer being freed was not allocated.
by Троицкий Антон Александ рович 24 Sep '19

24 Sep '19

External Email - Use Caution Hello FreeSurfer Developers, during the processing of patient data an error occurred. I don’t clearly understand a reason for this error. Technical description of this error is mris_make_surfaces(10174,0x7fffbf9553c0) malloc: *** error for object 0x2431900024317: pointer being freed was not allocated *** set a breakpoint in malloc_error_break to debug 000: dt: 0.0000, sse=991989.1, rms=2.913 021: dt: 0.5000, sse=841468.7, rms=1.605 (44.916%) 022: dt: 0.5000, sse=803776.9, rms=1.267 (21.055%) rms = 1.24, time step reduction 1 of 3 to 0.250... 023: dt: 0.5000, sse=793308.4, rms=1.242 (1.982%) Abort My suggestion is that the error associated with memory allocation and its reading. Is there any suggestion about why it happened and how can I prevent it in the future? Also, I've attached the recon-all.log in case it's of any use. 1) FreeSurfer version: freesurfer-Darwin-OSX-stable-pub-v6.0.0 2) Platform: macOS Sierra 10.12.6 3) uname -a: Darwin mac-2ap023-2.fccho-moscow.ru 16.7.0 Darwin Kernel Version 16.7.0: Thu Jan 11 22:59:40 PST 2018; root:xnu-3789.73.8~1/RELEASE_X86_64 x86_64 4) recon-all.log: see attached

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help! Hippocampal subfield segmentation with FS development version
by Liwen Zhang 24 Sep '19

24 Sep '19

External Email - Use Caution Hello freesurfer experts, I previously applied hippocampal subfield segmentation using FS v.6.0. I am now trying to devide subfields into head/body where applicable using FS development version (latest version). However, I encountered the following problems/quesetions: 1) X represents certain subfield (volume)X_head + X_body (from FS dev) ~= X (from FS v.6.0) What possibly causes this volume discrepancy between FS dev and FS v.6.0? Is the head/body segmentation template in FS dev based on the same ex-vivo template as used in FS v.6.0? 2) Related to 1), subfield volume as obtained from FS v.6.0 generally larger than that from FS dev (not for all subfields though) I processed T1 images with FS v.6.0 and then applied hippocampal segmentation with both FS v.6.0 and FS dev. Any suggestions/comments would be greatly appreicated! Thank you for your time and help in advance! Best, Liwen

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DPABISurf V1.2 Is Released
by YAN Chao-Gan 23 Sep '19

23 Sep '19

External Email - Use Caution Dear Colleagues, We are pleased to announce the release of DPABISurf V1.2! DPABISurf is a surface-based resting-state fMRI data analysis toolbox evolved from DPABI/DPARSF, as easy-to-use as DPABI/DPARSF. DPABISurf is based on fMRIPprep 1.5.0 (Esteban et al., 2018)(RRID:SCR_016216), and based on FreeSurfer 6.0.1 (Dale et al., 1999)(RRID:SCR_001847), ANTs 2.2.0 (Avants et al., 2008)(RRID:SCR_004757), FSL 5.0.9 (Jenkinson et al., 2002)(RRID:SCR_002823), AFNI 20160207 (Cox, 1996)(RRID:SCR_005927), SPM12 (Ashburner, 2012)(RRID:SCR_007037), PALM alpha112 (Winkler et al., 2016), GNU Parallel (Tange, 2011), MATLAB (The MathWorks Inc., Natick, MA, US) (RRID:SCR_001622), Docker (https://docker.com) (RRID:SCR_016445), and DPABI V4.2 (Yan et al., 2016)(RRID:SCR_010501). DPABISurf provides user-friendly graphical user interface (GUI) for pipeline surface-based preprocessing, statistical analyses and results viewing, while requires no programming/scripting skills from the users. <http://www.rfmri.org/dpabi> The DPABISurf pipeline first converts the user specified data into BIDS format (Gorgolewski et al., 2016), and then calls fMRIPprep 1.5.0 docker to preprocess the structural and functional MRI data, which integrates FreeSurfer, ANTs, FSL and AFNI. With fMRIPprep, the data is processed into FreeSurfer fsaverage5 surface space and MNI volume space. DPABISurf further performs nuisance covariates regression (including ICA-AROMA) on the surface-based data (volume-based data is processed as well), and then calculate the commonly used R-fMRI metrics: amplitude of low frequency fluctuation (ALFF) (Zang et al., 2007), fractional ALFF (Zou et al., 2008), regional homogeneity (Zang et al., 2004), degree centrality (Zuo and Xing, 2014), and seed-based functional connectivity. DPABISurf also performs surface-based smoothing by calling FreeSurfer’s mri_surf2surf command. These processed metrics then enters surfaced-based statistical analyses within DPABISurf, which could perform surfaced-based permutation test with TFCE by integrating PALM. Finally, the corrected results could be viewed by the convenient surface viewer DPABISurf_VIEW, which is derived from spm_mesh_render.m. <http://www.rfmri.org/dpabi> DPABISurf is designed to make surface-based data analysis require minimum manual operations and almost no programming/scripting experience. We anticipate this open-source toolbox will assist novices and expert users alike and continue to support advancing R-fMRI methodology and its application to clinical translational studies. DPABISurf is open-source and distributed under GNU/GPL, available with DPABI at http://www.rfmri.org/dpabi. It supports Windows 10 Pro, MacOS and Linux operating systems. You can run it with or without MATLAB. 1. With MATLAB. 1.1. Please go to http://www.rfmri.org/dpabi to download DPABI. 1.2. Add with subfolders for DPABI in MATLAB's path setting. 1.3. Input 'dpabi' and then follow the instructions of the "Install" Button on DPABISurf. 2. Without MATLAB. 2.1. Install Docker. 2.2. Terminal: docker pull cgyan/dpabi 2.3. Terminal: docker run -d --rm -v /My/FreeSurferLicense/Path/license.txt:/opt/freesurfer/license.txt -v /My/Data/Path:/data -p 5925:5925 cgyan/dpabi x11vnc -forever -shared -usepw -create -rfbport 5925 /My/FreeSurferLicense/Path/license.txt: Where you stored the FreeSurferLicense got from https://surfer.nmr.mgh.harvard.edu/registration.html. /My/Data/Path: This is where you stored your data. In Docker, the path is /data. 2.4. Open VNC Viewer, connect to localhost:5925, the password is 'dpabi'. 2.5. In the terminal within the VNC Viewer, input "bash", and then input: /opt/DPABI/DPABI_StandAlone/run_DPABI_StandAlone.sh ${MCRPath} Now please enjoy the StandAlone version of DPABISurf with GUI! If you don't want to run with GUI, you can also call the compiled version of DPABISurf_run. E.g., docker run -it --rm -v /My/FreeSurferLicense/Path/license.txt:/opt/freesurfer/license.txt -v /My/Data/Path:/data cgyan/dpabi /bin/bash /opt/DPABI/DPABI_StandAlone/run_DPABISurf_run_StandAlone.sh ${MCRPath} /data/DPABISurf_Cfg.mat New features of DPABISurf_V1.2_190919 within DPABI_V4.2_190919 (download at http://rfmri.org/dpabi, please also update the docker file by: docker pull cgyan/dpabi): 1. DPABISurf_V1.2_190919 updated. 1.1. A quality control module was added to DPABISurf. Now users can quality control surface reconstruction, EPI to T1 registration and T1 to MNI registration for all the subjects in one HTML file, respectively (based on fmriprep 1.5.0). For volume-based analysis, users can also generate group mask for DPABISurf, and exclude subjects by thresholding coverage and head motion. 1.2. DPABISurf now also output sulcus depth and volume in fsaverage and fsaverage5 spaces for statistical analysis. 1.3. In results organizer of DPABISurf, the redundant files would not be organized now. In addition, the fmriprep and freesurfer files were backed up, while excluding T1 image that may have privacy information such as face. 2. DPABI_VIEW has a new function "Surface View with DPABISurf_VIEW" now. This function will convert the files to fsaverage surface using freesurfer's mri_vol2surf command. Then the results were displayed by calling DPABISurf_VIEW to generate surface-based picture. Tips: 1) For Linux or Mac OS, please start matlab from terminal in order to reach docker in DPABI (e.g., Linux: matlab; Mac: open /Applications/MATLAB_R2018a.app/). 2) Before running DPABISurf_Pipeline, you can test the docker environment by running DPABI->DPABISurf->Utilities->Volume-Surface Projector. If the file can be successfully projected to surface, then the software is all set. References: - Ashburner, J. (2012). SPM: a history. *Neuroimage*, 62(2), 791-800, doi:10.1016/j.neuroimage.2011.10.025. - Avants, B.B., Epstein, C.L., Grossman, M., Gee, J.C. (2008). Symmetric diffeomorphic image registration with cross-correlation: evaluating automated labeling of elderly and neurodegenerative brain. *Med Image Anal*, 12(1), 26-41, doi:10.1016/j.media.2007.06.004. - Cox, R.W. (1996). AFNI: software for analysis and visualization of functional magnetic resonance neuroimages. *Comput Biomed Res*, 29(3), 162-173. - Dale, A.M., Fischl, B., Sereno, M.I. (1999). Cortical surface-based analysis. I. Segmentation and surface reconstruction. *Neuroimage*, 9(2), 179-194, doi:10.1006/nimg.1998.0395. - Esteban, O., Markiewicz, C.J., Blair, R.W., Moodie, C.A., Isik, A.I., Erramuzpe, A., Kent, J.D., Goncalves, M., DuPre, E., Snyder, M., Oya, H., Ghosh, S.S., Wright, J., Durnez, J., Poldrack, R.A., Gorgolewski, K.J. (2018). fMRIPrep: a robust preprocessing pipeline for functional MRI. *Nat Methods*, doi:10.1038/s41592-018-0235-4. - Gorgolewski, K.J., Auer, T., Calhoun, V.D., Craddock, R.C., Das, S., Duff, E.P., Flandin, G., Ghosh, S.S., Glatard, T., Halchenko, Y.O., Handwerker, D.A., Hanke, M., Keator, D., Li, X., Michael, Z., Maumet, C., Nichols, B.N., Nichols, T.E., Pellman, J., Poline, J.B., Rokem, A., Schaefer, G., Sochat, V., Triplett, W., Turner, J.A., Varoquaux, G., Poldrack, R.A. (2016). The brain imaging data structure, a format for organizing and describing outputs of neuroimaging experiments. *Sci Data*, 3, 160044, doi:10.1038/sdata.2016.44. - Jenkinson, M., Bannister, P., Brady, M., Smith, S. (2002). Improved optimization for the robust and accurate linear registration and motion correction of brain images. *Neuroimage*, 17(2), 825-841. - Tange, O. (2011). Gnu parallel-the command-line power tool. *The USENIX Magazine*, 36(1), 42-47. - Winkler, A.M., Ridgway, G.R., Douaud, G., Nichols, T.E., Smith, S.M. (2016). Faster permutation inference in brain imaging. *Neuroimage*, 141, 502-516, doi:10.1016/j.neuroimage.2016.05.068. - Yan, C.G., Wang, X.D., Zuo, X.N., Zang, Y.F. (2016). DPABI: Data Processing & Analysis for (Resting-State) Brain Imaging. *Neuroinformatics*, 14(3), 339-351, doi:10.1007/s12021-016-9299-4. - Zang, Y., Jiang, T., Lu, Y., He, Y., Tian, L. (2004). Regional homogeneity approach to fMRI data analysis. *Neuroimage*, 22(1), 394-400, doi:http://dx.doi.org/10.1016/j.neuroimage.2003.12.030. - Zang, Y.F., He, Y., Zhu, C.Z., Cao, Q.J., Sui, M.Q., Liang, M., Tian, L.X., Jiang, T.Z., Wang, Y.F. (2007). Altered baseline brain activity in children with ADHD revealed by resting-state functional MRI. *Brain Dev*, 29(2), 83-91, doi:10.1016/j.braindev.2006.07.002. - Zou, Q.-H., Zhu, C.-Z., Yang, Y., Zuo, X.-N., Long, X.-Y., Cao, Q.-J., Wang, Y.-F., Zang, Y.-F. (2008). An improved approach to detection of amplitude of low-frequency fluctuation (ALFF) for resting-state fMRI: Fractional ALFF. *Journal of Neuroscience Methods*, 172(1), 137-141, doi: http://dx.doi.org/10.1016/j.jneumeth.2008.04.012. - Zuo, X.-N., Xing, X.-X. (2014). Test-retest reliabilities of resting-state FMRI measurements in human brain functional connectomics: A systems neuroscience perspective. *Neuroscience & Biobehavioral Reviews*, 45, 100-118, doi:http://dx.doi.org/10.1016/j.neubiorev.2014.05.009. Best, Chao-Gan -- Chao-Gan YAN, Ph.D. Professor, Principal Investigator Director, International Big-Data Center for Depression Research Deputy Director, Magnetic Resonance Imaging Research Center Institute of Psychology, Chinese Academy of Sciences 16 Lincui Road, Chaoyang District, Beijing 100101, China - Initiator <http://rfmri.org/DPARSF>DPABI <http://rfmri.org/DPABI> <http://rfmri.org/DPARSF>, <http://dpabi.org>DPARSF <http://rfmri.org/DPARSF>, PRN <http://rfmri.org/PRN> and The R-fMRI Network <http://rfmri.org> (RFMRI.ORG <http://rfmri.org/>) http://rfmri.org/yan http://scholar.google.com/citations?user=lJQ9B58AAAAJ

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Freesurfer September 2019