Freesurfer November 2013

freesurfer@nmr.mgh.harvard.edu

120 participants
198 discussions

Re: [Freesurfer] help with save_nifti
by Leila Reddy 22 Nov '13

22 Nov '13

Hi Doug, Thanks for your reply. I have the problem even if I use MRIread and MRIwrite. But I have done a little more digging following your suggestions. Basically, there are differences in the output of mri_vol2surf (that I should have spotted earlier), as well as differences in the header information. I highlight the differences below, and I have put the detailed outputs of mri_vol2surf at the end in case you still need to look at it. I think the clearest way of explaining the different outcomes is as follows.: 1) mri_vol2surf performed on a nifti volume generated by Nibabel. Nothing done in Matlab. mri_vol2surf ouput: "Number of source voxels hit = 22587". "niiRead(): NIFTI_UNITS_UNKNOWN, assuming mm" Results looks fine in tksurfer (i.e., I have a distribution of voxel values in the Configure Overlay window). If I look at the nifti header, hdr.volres= [2.0000e+10 2.0000e+10 2.0000e+10] and several other fields (e.g., vox2ras etc) also have the same magnitude. In addition, hdr.niftihdr.dim'=[3 76 76 93 1 1 1 1] 2) The Nibabel nifti is opened in matlab with MRIread and immediately saved with MRIwrite. Nothing else is done to the data in Matlab. Output of MRIread=WARNING: xyz units code 0 is unrecognized Rescaling NIFTI: slope = 1, intercept = 0 mri_vol2surf output: "Number of source voxels hit = 1". Nothing about NIFTI_UNITS (note the header is the same as in 1 above). Rest of mri_vol2surf output is exactly as for #1 above. The header values are as above except hdr.niftihdr.dim'=[4 76 76 93 1 1 1 1] 3) The Nibabel nifti is opened in matlab with MRIread. The 3d volume is saved with MRIwrite but with the header information from a FSFAST created nifti. mri_vol2surf says "Number of source voxels hit = 22587". hdr.volres=[2 2 2] and other fields have values of the same order. hdr.niftihdr.dim'=[4 76 76 93 1 1 1 1] I don't know if I have focused on the relevant header information here so I also attach the headers from steps 1-3 above. Thanks a lot for your help and time on this. I will often have to go back and forth between python functions and Matlab/FS-FAST scripts so this will be very useful. Leila Detailed output of mri_vol2surf with fsfast header (#3 above): mri_vol2surf --src fs_hdr.nii --hemi rh --out_type mgh --float2int round --o fshdr-rh.mgh --projfrac 0.5 --trgsubject fsaverage --regheader fsaverage srcvol = fs_hdr.nii srcreg unspecified srcregold = 0 srcwarp unspecified surf = white hemi = rh trgsubject = fsaverage surfreg = sphere.reg ProjFrac = 0.5 thickness = thickness reshape = 0 interp = nearest float2int = round GetProjMax = 0 INFO: float2int code = 0 Done loading volume Computing registration from header. Using /APPLICATIONS/freesurfer/subjects/fsaverage/mri/orig.mgz as target reference. Reading surface /APPLICATIONS/freesurfer/subjects/fsaverage/surf/rh.white Done reading source surface Reading thickness /APPLICATIONS/freesurfer/subjects/fsaverage/surf/rh.thickness Done Mapping Source Volume onto Source Subject Surface 1 0.5 0.5 0.5 using old Done mapping volume to surface Number of source voxels hit = 22587 Writing to fshdr-rh.mgh Dim: 163842 1 1 Detailed output of mri_vol2surf with nibabel header (after opening and saving in matlab) (#2 above): mri_vol2surf --src test.nii --hemi rh --out_type mgh --float2int round --o test-rh.mgh --projfrac 0.5 --trgsubject fsaverage --regheader fsaverage srcvol = test.nii srcreg unspecified srcregold = 0 srcwarp unspecified surf = white hemi = rh trgsubject = fsaverage surfreg = sphere.reg ProjFrac = 0.5 thickness = thickness reshape = 0 interp = nearest float2int = round GetProjMax = 0 INFO: float2int code = 0 Done loading volume Computing registration from header. Using /APPLICATIONS/freesurfer/subjects/fsaverage/mri/orig.mgz as target reference. Reading surface /APPLICATIONS/freesurfer/subjects/fsaverage/surf/rh.white Done reading source surface Reading thickness /APPLICATIONS/freesurfer/subjects/fsaverage/surf/rh.thickness Done Mapping Source Volume onto Source Subject Surface 1 0.5 0.5 0.5 using old Done mapping volume to surface Number of source voxels hit = 1 Writing to test-rh.mgh Dim: 163842 1 1

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comparing left and right cortical thickness
by Jacobs H (NP) 22 Nov '13

22 Nov '13

Dear FreeSurfers, Is it possible to compare left and right cortical thickness patterns, vertex-wise? Thanks Heidi ================================================ Dr. Heidi Jacobs Postdoc researcher Faculty of Health, Medicine and Life Sciences School for Mental Health and Neurosciences Division Cognitive Neuropsychiatry and Clinical Neurosciences Alzheimer Center Limburg h.jacobs(a)maastrichtuniversity.nl www.maastrichtuniversity.nl www.heidijacobs.nl Dr. Tanslaan 12, 6229 ET Maastricht P.O. Box 616, 6200 MD Maastricht, The Netherlands T +31 43 38 84 090 F +31 43 38 84 092 ================================================

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problem feeding design matrix to mri_glmfit
by Laura M. Tully 21 Nov '13

21 Nov '13

Hello freesurfers, I'm trying to run mri_glmfit between groups analysis (patients vs. controls) with gender, age, medication (continuous), and duration of illness as covariates. Because the control group have values of zeros for medication and duration of illness (which results in an illconditioned matrix), I have created my own design matrix so that controls do not have a column for medication or duration of illness and am feeding this matrix into mri_glmfit instead of the fsgd file. However, this seems to cause a problem with the --y input; when I try to run mri_glmfit, i get an error message "error in uncompressing" - I'm not quite sure what this means, perhaps I did something wrong in creating the design matrix? See the full output below. I've also attached the design matrix, contrast file, and the original fsgd (which results in the ill conditioned matrix). Best, Laura. *Command line: * mri_glmfit --y lh_grpDiffs_thickness10.mgh --X new_mat_files/X_lh_grp_thick_med_dur.mat --C Contrast1B_grp_Diffs_HCvsSZ_Med_Dur.mtx --surf fsaverage lh --cortex --glmdir lh.grp_diffs_thickness_med_dur_112013.glmdir --illcond *Output:* Reading source surface /ncf/snp/04/SCORE/freesurfer_analysis/fsaverage/surf/lh.white Number of vertices 163842 Number of faces 327680 Total area 65416.648438 AvgVtxArea 0.399267 AvgVtxDist 0.721953 StdVtxDist 0.195470 $Id: mri_glmfit.c,v 1.196.2.6 2011/05/05 20:54:25 greve Exp $ cwd /ncf/snp/04/SCORE/freesurfer_analysis/glm_analysis cmdline mri_glmfit --y lh_grpDiffs_thickness10.mgh --X new_mat_files/X_lh_grp_thick_med_dur.mat --C Contrast1B_grp_Diffs_HCvsSZ_Med_Dur.mtx --surf fsaverage lh --cortex --glmdir lh.grp_diffs_thickness_med_dur_112013.glmdir --illcond sysname Linux hostname ncfws13.rc.fas.harvard.edu machine x86_64 user ltully FixVertexAreaFlag = 1 UseMaskWithSmoothing 1 OneSampleGroupMean 0 y /ncf/snp/04/SCORE/freesurfer_analysis/glm_analysis/lh_grpDiffs_thickness10.mgh logyflag 0 X new_mat_files/X_lh_grp_thick_med_dur.mat usedti 0 labelmask /ncf/snp/04/SCORE/freesurfer_analysis/fsaverage/label/lh.cortex.label maskinv 0 glmdir lh.grp_diffs_thickness_med_dur_112013.glmdir IllCondOK 1 ReScaleX 1 DoFFx 0 Creating output directory lh.grp_diffs_thickness_med_dur_112013.glmdir Loading y from /ncf/snp/04/SCORE/freesurfer_analysis/glm_analysis/lh_grpDiffs_thickness10.mgh MatrixReadTxT: could not scan value [1][1] File exists ERROR: in uncompressing MATFILE5: 0 x 0, type 0, imagf 0, name '' File exists unsupported matlab format 0 (unknown) File exists Saving design matrix to lh.grp_diffs_thickness_med_dur_112013.glmdir/Xg.dat *** glibc detected *** mri_glmfit: double free or corruption (out): 0x000000003b1279c0 *** ======= Backtrace: ========= /lib64/libc.so.6[0x3229470d7f] /lib64/libc.so.6(cfree+0x4b)[0x32294711db] mri_glmfit[0x99fea2] mri_glmfit[0x5bcbe3] mri_glmfit[0x433608] mri_glmfit[0x433802] mri_glmfit[0x40f2f7] /lib64/libc.so.6(__libc_start_main+0xf4)[0x322941d994] mri_glmfit(__gxx_personality_v0+0x172)[0x40b2ba] ======= Memory map: ======== 00400000-00b86000 r-xp 00400000 00:00 0 00b86000-00c86000 ---p 00b86000 00:00 0 00c86000-26a08000 rwxp 00c86000 00:00 0 35b4b000-3d4fa000 rwxp 35b4b000 00:00 0 [heap] 3229000000-322901c000 r-xp 00000000 fd:00 557272 /lib64/ld-2.5.so 322901c000-322921c000 ---p 322901c000 00:00 0 322921c000-322921d000 r-xp 0001c000 fd:00 557272 /lib64/ld-2.5.so 322921d000-322921e000 rwxp 0001d000 fd:00 557272 /lib64/ld-2.5.so 3229400000-322954d000 r-xp 00000000 fd:00 557376 /lib64/libc-2.5.so 322954d000-322974d000 ---p 0014d000 fd:00 557376 /lib64/libc-2.5.so 322974d000-3229751000 r-xp 0014d000 fd:00 557376 /lib64/libc-2.5.so 3229751000-3229752000 rwxp 00151000 fd:00 557376 /lib64/libc-2.5.so 3229752000-3229757000 rwxp 3229752000 00:00 0 3229800000-3229882000 r-xp 00000000 fd:00 557399 /lib64/libm-2.5.so 3229882000-3229a81000 ---p 00082000 fd:00 557399 /lib64/libm-2.5.so 3229a81000-3229a82000 r-xp 00081000 fd:00 557399 /lib64/libm-2.5.so 3229a82000-3229a83000 rwxp 00082000 fd:00 557399 /lib64/libm-2.5.so 3229c00000-3229c02000 r-xp 00000000 fd:00 557398 /lib64/libdl-2.5.so 3229c02000-3229e02000 ---p 00002000 fd:00 557398 /lib64/libdl-2.5.so 3229e02000-3229e03000 r-xp 00002000 fd:00 557398 /lib64/libdl-2.5.so 3229e03000-3229e04000 rwxp 00003000 fd:00 557398 /lib64/libdl-2.5.so 322a000000-322a014000 r-xp 00000000 fd:00 557401 /lib64/libz.so.1.2.3 322a014000-322a213000 ---p 00014000 fd:00 557401 /lib64/libz.so.1.2.3 322a213000-322a214000 rwxp 00013000 fd:00 557401 /lib64/libz.so.1.2.3 322a400000-322a416000 r-xp 00000000 fd:00 557391 /lib64/libpthread-2.5.so 322a416000-322a615000 ---p 00016000 fd:00 557391 /lib64/libpthread-2.5.so 322a615000-322a616000 r-xp 00015000 fd:00 557391 /lib64/libpthread-2.5.so 322a616000-322a617000 rwxp 00016000 fd:00 557391 /lib64/libpthread-2.5.so 322a617000-322a61b000 rwxp 322a617000 00:00 0 322f000000-322f00d000 r-xp 00000000 fd:00 557370 /lib64/libgcc_s-4.1.2-20080825.so.1 322f00d000-322f20d000 ---p 0000d000 fd:00 557370 /lib64/libgcc_s-4.1.2-20080825.so.1 322f20d000-322f20e000 rwxp 0000d000 fd:00 557370 /lib64/libgcc_s-4.1.2-20080825.so.1 3237200000-32372e6000 r-xp 00000000 fd:00 3309621 /usr/lib64/libstdc++.so.6.0.8 32372e6000-32374e5000 ---p 000e6000 fd:00 3309621 /usr/lib64/libstdc++.so.6.0.8 32374e5000-32374eb000 r-xp 000e5000 fd:00 3309621 /usr/lib64/libstdc++.so.6.0.8 32374eb000-32374ee000 rwxp 000eb000 fd:00 3309621 /usr/lib64/libstdc++.so.6.0.8 32374ee000-3237500000 rwxp 32374ee000 00:00 0 3239600000-3239609000 r-xp 00000000 fd:00 557404 /lib64/libcrypt-2.5.so 3239609000-3239808000 ---p 00009000 fd:00 557404 /lib64/libcrypt-2.5.so 3239808000-3239809000 r-xp 00008000 fd:00 557404 /lib64/libcrypt-2.5.so 3239809000-323980a000 rwxp 00009000 fd:00 557404 /lib64/libcrypt-2.5.so 323980a000-3239838000 rwxp 323980a000 00:00 0 2b1225c45000-2b1225c48000 rwxp 2b1225c45000 00:00 0 2b1225c69000-2b1225c6d000 rwxp 2b1225c69000 00:00 0 2b1225c6d000-2b1225ca2000 r-xs 00000000 fd:00 3703836 /var/run/nscd/dbC3ggnz (deleted) 2b1225d6d000-2b12952bb000 rwxp 2b1225d6d000 00:00 0 7fff44349000-7fff44362000 rwxp 7ffffffe5000 00:00 0 [stack] 7fff443cb000-7fff443ce000 r-xp 7fff443cb000 00:00 0 [vdso] ffffffffff600000-ffffffffffe00000 ---p 00000000 00:00 0 [vsyscall] Aborted -- -- Laura M. Tully, PhD Post-Doctoral Fellow in Psychiatry UC Davis Imaging Research Center 4701 X Street, Sacramento, CA 95817 Phone: (916) 734-7927 Fax: (916) 734-8750 Alumnus of Social Neuroscience & Psychopathology Lab, Harvard University ltully(a)fas.harvard.edu Follow me on twitter: @tully_laura -- *Confidentiality Notice:* This e-mail message, including any attachments, is for the sole use of the intended recipient(s) and may contain confidential and privileged information. Any unauthorized review, use, disclosure or distribution is prohibited. If you are not the intended recipient, please contact the sender by reply e-mail and destroy all copies of the original message. -- -- Laura M. Tully, PhD Post-Doctoral Fellow in Psychiatry UC Davis Imaging Research Center 4701 X Street, Sacramento, CA 95817 Phone: (916) 734-7927 Fax: (916) 734-8750 Alumnus of Social Neuroscience & Psychopathology Lab, Harvard University ltully(a)fas.harvard.edu Follow me on twitter: @tully_laura -- *Confidentiality Notice:* This e-mail message, including any attachments, is for the sole use of the intended recipient(s) and may contain confidential and privileged information. Any unauthorized review, use, disclosure or distribution is prohibited. If you are not the intended recipient, please contact the sender by reply e-mail and destroy all copies of the original message.

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Destrieux atlas in FSL
by Kirstie Whitaker 21 Nov '13

21 Nov '13

Hi Freesurfer and FSL communities, Firstly, I apologise for the double posting. I suspect there are experts in both groups that can help me. I'd like to be able to visualise the Destrieux atlas that freesurfer uses at the same time as my MNI standard space results in FSL. Is that possible? I'm afraid I've not been successful in my search of the mailing list archives. Thank you for your help. Kirstie -- Kirstie Whitaker, PhD Research Associate tel: +44 7583 535 307 Department of Psychiatry University of Cambridge Herchel Smith Building Robinson Way Cambridge CB2 0SZ

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optseq2 for a (sparse) 1-back task
by Chris McNorgan 21 Nov '13

21 Nov '13

Hi all, I figured I would have some luck tapping expertise on using optseq2 in this mailing list. There are 8 trials times 8 conditions in an event-related design. We are using a 1-back task just to keep participants paying attention. Thus, we are not attempting to match the number of 1-back-yes and 1-back-no trials. In fact, ideally we would have exactly 1 1-back-yes trial for each of the 8 conditions. The plan would be to arrive at a paradigm schedule where, for each of the 8 conditions, there is at least 1 set of consecutive trials for that condition. In this way, if we use only 7 stimuli, then the consecutive trials can use the same item, and that would constitute the 1-back-yes event for that condition as in: 1 a1.bmp 2 b1.bmp 0 NULL 3 c1.bmp 2 b2.bmp <-- 0 NULL 2 b2.bmp <--first instance of consecutive events from same condition assigned same item to create a 1-back-yes event The problem is that I have not discovered any means within optseq to enforce the criterion that at two consecutive events are from the same condition for all 8 conditions. The best I can do is create a large enough pool of paradigm files, and sort through them in the hopes of finding several that meet this requirement. Can optseq2 be forced to meet this requirement, either as a normal command line switch, or else through some clever condition labeling trickery? Thanks, Chris

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paired analysis question
by Govindarajan, Koushik Athreya 21 Nov '13

21 Nov '13

Hi all, I am trying to compute differences between 2 runs of my same set of subjects (repeatability) using the steps from the paired analysis wiki page. After I finish the mris_preproc and the mri_surf2surf steps, when I do the glmfit, should I be using the osgm option ? Since it is the same subject, I do not need the age variable as mentioned in the 2nd fsgd file. If I should still be using the 2nd fsgd file and not osgm, what would my contrast file look like? Thanks for the help Koushik

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RAS, MNI305, Talairach, MNI-Talairach?
by Anita van Loenhoud 21 Nov '13

21 Nov '13

Hi all, I find myself getting quite confused about different coordinates systems. Is the following correct (when viewing in TkSurfer): RAS=MNI Talairach=MNI305 (they are all the same?) Talairach= (non linear) conversion from MNI305 Thanks, Anita

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help with save_nifti
by Leila Reddy 21 Nov '13

21 Nov '13

Hi, I am trying to save a nifti file using save_nifti. I'm running into a strange problem that I describe below. I have a nifti file (subj_mask.nii) created by a colleague using Nibabel (http://nipy.sourceforge.net/nibabel/) This volume is in the MNI305 space. Step1: In a first step I wanted to convert this volume to the fsaverage surface format. To do that I used : mri_vol2surf --src subj_mask.nii --hemi rh --out_type mgh --float2int round --o blah9-rh.mgh --projfrac 0.5 --trgsubject fsaverage --regheader fsaverage. I load it in tksurfer and when I do view-> configure->overlay, I see a range of values (as expected) and am able to set the min and max thresholds as I want. Step 2: In a second step I loaded this nifti file into matlab using load_nifti and had to alter the volume a little bit as below: hdr=load_nifti('subj_mask.nii'); vol=hdr.vol; vol(find(vol<4))=0; hdr.vol=vol; save_nifti(hdr,'new_mask.nii'). I convert the volume to fsaverage surface space as before but when I view it in tksurfer I am not able to set a min and max threshold with configure->overlay. Instead, there is no distribution of values plotted in the configure overlay window and I get the following error message: % ERROR updating histo: impossible limits (min 0.55556 >= max 0.55556) for axis "x" I finally managed to solve this problem by loading the header information from a FS-FAST created nifti: hdr_fsfast = load_nifti('bold/analysis.mni/mask.nii.gz'); hdr_fsfast.vol=vol; save_nifti(hdr_fsfast,'new_mask.nii'). Now I am able to see the distribution of values in the configure overlay window and am able to set the thresholds. The headers for FS-FAST and Nibabel generated niftis are indeed slightly different but why do I not have the problem in step 1 when I use the Nibabel file, but only in step 2 after I use save_nifti with the Nibabel header ? I use the load_nifti and save_nifti commands very often (and haven't had problems before because I was only using FS-FAST generated files) so I would really appreciate it if someone could point out what is going on so that I understand what to do in future. Thanks, Leila

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converting cortical labels into volumetric ROIs
by Mojdeh Zamyadi 21 Nov '13

21 Nov '13

Hi all, I want to convert the cortical labels I get in freeSurfer to volumetric ROIs in the subject space and I've followed the steps mentioned in: http://brainybehavior.com/neuroimaging/2010/05/converting-cortical-labels-f… except since I'm interested in lobe mapping I've changed the first commands, more specifically these are the different command I've run: 1. mri_annotation2label --subject P2 --hemi lh --outdir freeSurfer_Results/P2/labels/ --lobesStrict freeSurfer_Results/P2/labels/freeSurfer_lobes 2. mri_annotation2label --hemi lh --subject P2 --outdir freeSurfer_Results/P2/labels/ --annotation freeSurfer_Results/P2/labels/lh.freeSurfer_lobes.annot 3. tkregister2 --mov freeSurfer_Results/P2/mri/rawavg.mgz --noedit --s P2 --regheader --reg freeSurfer_Results/P2/register.dat 4. mri_label2vol --label freeSurfer_Results/P2/labels/lh.parietal.label --temp freeSurfer_Results/P2/mri/rawavg.mgz --subject P2 --hemi lh --o freeSurfer_Results/P2/labels/lh.parietal.nii.gz --proj frac 0 1 .1 --fillthresh 1 --reg freeSurfer_Results/P2/register.dat the issue I have now is that the final ROI I get (e.g. "lh.parietal.nii.gz") looks like a series of disconnected points! I was wondering how I can get a smooth (i.e. filled) volumetric ROI? Thanks, -Mojdeh

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[freesurfer]Cohen'd effect size map
by 陈骥 21 Nov '13

21 Nov '13

> > Dear freesurfer experts > > > In qdec I use the DODS degsin to obtain the thickness difference between my two groups with age ,gender as nuisance.Then I want to get the effect size map instead of report the significance level. In freesurfer wiki I found that we can obtain the effect size map via gamma/sqrt(gammavar*Npilot), where Npilot is the number subjects in the pilot study.While I have two groups,one control group with 25 subjects and one patient group with 25 subjects too,I doubt that which number I should use ,the number of patient group subjects 25 or for the whole subjects across groups 50 to repalce the Npilot in the equation? And then I look for previous relevant topic in the freesurfer mail list, found that doug suggested that we can get the effect size just use gamma/rstd, I tried for that but found completely different result between I use the equation of gamma/sqrt(gammavar*Npilot), which equation should I use for I want to get the Cohen'd effect size map? Thank you in advance for your helps! Ji Chen

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Freesurfer November 2013