Freesurfer

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16 participants
30084 discussions

tkregister2 - horizontal and coronal inverted in the functional only
by Ilaria Sani 08 Feb '16

08 Feb '16

Dear All, I have a functional and a T1 registered, but they are not in anatomical coordinates. I put the anatomical in the desired position by using tkregister2. I was hoping to use the output reg file to re-position the functional as well. I got an unexpected output! The functional looks reoriented BUT, coronal is horizontal, horizontal is coronal and sagittal is 90deg rotated. How did it happen and how can I fix the problem? Thanks, Ilaria

2 2

matrix is ill-conditioned or badly scaled, condno = 27492.1
by Nabin Koirala 07 Feb '16

07 Feb '16

Dear Freesurfer forum, 'I am trying to run qdec analysis for a group of subjects to see if correlation exists but I am getting this error only for this particular set of data but could not figure out what is exactly wrong with it. Your suggestion would be greatly appreciated. Following is the terminal output for the process: .......... Saving design matrix to /g/f/h/s/freesurfer/subjects/qdec/Untitled/Xg.dat Normalized matrix condition is 27492.1 Design matrix ------------------ 1.000 0.408; 1.000 0.417; 1.000 0.417; 1.000 0.405; 1.000 0.412; 1.000 0.412; 1.000 0.411; 1.000 0.417; 1.000 0.405; 1.000 0.406; 1.000 0.402; 1.000 0.419; 1.000 0.413; 1.000 0.413; -------------------------------- ERROR: matrix is ill-conditioned or badly scaled, condno = 27492.1 -------------------------------- Possible problem with experimental design: Check for duplicate entries and/or lack of range of continuous variables within a class. If you seek help with this problem, make sure to send: 1. Your command line: mri_glmfit --y /g/f/h/s/freesurfer/subjects/qdec/Untitled/y.mgh --fsgd /g/f/h/s/freesurfer/subjects/qdec/Untitled/qdec.fsgd dods --glmdir /g/f/h/s/freesurfer/subjects/qdec/Untitled --surf fsaverage lh --label /g/f/h/s/freesurfer/subjects/fsaverage/label/lh.aparc.label --C /g/f/h/s/freesurfer/subjects/qdec/Untitled/contrasts/lh-Avg-Intercept-thickness.mat --C /g/f/h/s/freesurfer/subjects/qdec/Untitled/contrasts/lh-Avg-thickness-alpha1-Cor.mat 2. The FSGD file (if using one) 3. And the design matrix above Error in Analyze: command failed: mri_glmfit --y /g/f/h/s/freesurfer/subjects/qdec/Untitled/y.mgh --fsgd /g/f/h/s/freesurfer/subjects/qdec/Untitled/qdec.fsgd dods --glmdir /g/f/h/s/freesurfer/subjects/qdec/Untitled --surf fsaverage lh --label /g/f/h/s/freesurfer/subjects/fsaverage/label/lh.aparc.label --C /g/f/h/s/freesurfer/subjects/qdec/Untitled/contrasts/lh-Avg-Intercept-thickness.mat --C /g/f/h/s/freesurfer/subjects/qdec/Untitled/contrasts/lh-Avg-thickness-alpha1-Cor.mat Many thanks in advance. Regards, Nabin

3 5

mri_vol2surf Averaging with exclusion of specific values
by Gardumi Anna (PSYCHOLOGY) 07 Feb '16

07 Feb '16

Dear FreeSurfer expert, I would like to project my maps from the "original" functional space (2.5mm iso, same format as COPE images from FSL) to inflated FreeSurfer surfaces (created from 1.0mm MPRAGE image with recon-all pipeline) excluding voxels with a specific value (e.g. 0) from the averaging procedure of the projection. The reason for this is that I have non-continuous maps (i.e. map values are defined only for some voxels; voxels for which map value is not defined will have 0 as value). Is there a way to perform the projection excluding voxels with a specific value from the averaging of the projection? Thank you in advance for any help! Anna As complementary information: My maps have discrete values (between -10 and 10) and at the moment I am using the following command: mri_vol2surf --mov DiscreteMap.nii --reg $REGMAT --hemi lh --projfrac-avg 0 1 0.2 --interp nearest --o DiscreteMap _InFS_projAvg02_SurfLh.mgh However, in this way the resulting surface map will have values biased by including in the average also the 0 values which in reality represents voxels not included in the map.

3 6

selxavg3-sess problem: SVD input matrix contains NaN
by Mcnorgan, Christopher 07 Feb '16

07 Feb '16

Hi, I'm attempting an inaugural run through the FS pipeline on some event-related data collected over 6 runs. I'm not sure if this makes any difference, but the experiment is self-paced, and the events are of varying duration (it's a lexical decision task, and participants can take up to 4 seconds to respond but typically respond between 600 - 800ms, with an exponentially-decreasing jittered ITI between trials). When I run selxavg3-sess on this single participant, the following error is generated: /********************************** Saving X matrix to /home/kali/fMRI/LDT/1001_001/bold/LDT.sm6.lh/Xtmp.mat Error using svd Input to SVD must not contain NaN or Inf. Error in cond (line 35) s = svd(A); Error in fast_selxavg3 (line 279) XCond = cond(XtX); >> ------------------------------------------ ERROR: fast_selxavg3() failed\n *******************************************/ If I open up the generated .mat file, I see the several rows/columns of the XtX matrix are indeed populated with NaN. We tried running the mkanalysis-sess a couple different ways, getting the same error, though our different parameter selections for mkanalysis-sess lead to different XtX matrices, so I suspect that this might be the source of the problem. Unfortunately, I have no insight into what the root of the problem might be. The .par files used have the event durations set to the reaction times for each trial, and the -refeventdur value is set to the mean reaction time Thanks for any help anyone might be able to give me

2 1

generate .mgz file from DICOM
by Kan Ding 07 Feb '16

07 Feb '16

Hi, I am having trouble to generate .mgz file from DICOM. However, I was able to run the same code with NIFTI file. What did I do wrong? Thanks for your help. Kan NUA502608:300T1 kding$ ls 30100000-0.dcm 30100000-27.dcm 30100000-1.dcm 30100000-28.dcm 30100000-10.dcm 30100000-29.dcm 30100000-100.dcm 30100000-3.dcm 30100000-101.dcm 30100000-30.dcm 30100000-102.dcm 30100000-31.dcm 30100000-103.dcm 30100000-32.dcm 30100000-104.dcm 30100000-33.dcm 30100000-105.dcm 30100000-34.dcm 30100000-106.dcm 30100000-35.dcm 30100000-107.dcm 30100000-36.dcm 30100000-108.dcm 30100000-37.dcm 30100000-109.dcm 30100000-38.dcm 30100000-11.dcm 30100000-39.dcm 30100000-110.dcm 30100000-4.dcm 30100000-111.dcm 30100000-40.dcm 30100000-112.dcm 30100000-41.dcm 30100000-113.dcm 30100000-42.dcm 30100000-114.dcm 30100000-43.dcm 30100000-115.dcm 30100000-44.dcm 30100000-116.dcm 30100000-45.dcm 30100000-117.dcm 30100000-46.dcm 30100000-118.dcm 30100000-47.dcm 30100000-119.dcm 30100000-48.dcm 30100000-12.dcm 30100000-49.dcm 30100000-120.dcm 30100000-5.dcm 30100000-121.dcm 30100000-50.dcm 30100000-122.dcm 30100000-51.dcm 30100000-123.dcm 30100000-52.dcm 30100000-124.dcm 30100000-53.dcm 30100000-125.dcm 30100000-54.dcm 30100000-126.dcm 30100000-55.dcm 30100000-127.dcm 30100000-56.dcm 30100000-128.dcm 30100000-57.dcm 30100000-129.dcm 30100000-58.dcm 30100000-13.dcm 30100000-59.dcm 30100000-130.dcm 30100000-6.dcm 30100000-131.dcm 30100000-60.dcm 30100000-132.dcm 30100000-61.dcm 30100000-133.dcm 30100000-62.dcm 30100000-134.dcm 30100000-63.dcm 30100000-135.dcm 30100000-64.dcm 30100000-136.dcm 30100000-65.dcm 30100000-137.dcm 30100000-66.dcm 30100000-138.dcm 30100000-67.dcm 30100000-139.dcm 30100000-68.dcm 30100000-14.dcm 30100000-69.dcm 30100000-140.dcm 30100000-7.dcm 30100000-141.dcm 30100000-70.dcm 30100000-142.dcm 30100000-71.dcm 30100000-143.dcm 30100000-72.dcm 30100000-144.dcm 30100000-73.dcm 30100000-145.dcm 30100000-74.dcm 30100000-146.dcm 30100000-75.dcm 30100000-147.dcm 30100000-76.dcm 30100000-148.dcm 30100000-77.dcm 30100000-149.dcm 30100000-78.dcm 30100000-15.dcm 30100000-79.dcm 30100000-150.dcm 30100000-8.dcm 30100000-151.dcm 30100000-80.dcm 30100000-152.dcm 30100000-81.dcm 30100000-153.dcm 30100000-82.dcm 30100000-154.dcm 30100000-83.dcm 30100000-155.dcm 30100000-84.dcm 30100000-156.dcm 30100000-85.dcm 30100000-157.dcm 30100000-86.dcm 30100000-158.dcm 30100000-87.dcm 30100000-159.dcm 30100000-88.dcm 30100000-16.dcm 30100000-89.dcm 30100000-160.dcm 30100000-9.dcm 30100000-17.dcm 30100000-90.dcm 30100000-18.dcm 30100000-91.dcm 30100000-19.dcm 30100000-92.dcm 30100000-2.dcm 30100000-93.dcm 30100000-20.dcm 30100000-94.dcm 30100000-21.dcm 30100000-95.dcm 30100000-22.dcm 30100000-96.dcm 30100000-23.dcm 30100000-97.dcm 30100000-24.dcm 30100000-98.dcm 30100000-25.dcm 30100000-99.dcm 30100000-26.dcm NUA502608:300T1 kding$ recon-all -i 30100000-0.dcm -s 300 Subject Stamp: freesurfer-Darwin-lion-stable-pub-v5.3.0 Current Stamp: freesurfer-Darwin-lion-stable-pub-v5.3.0 INFO: SUBJECTS_DIR is /Users/kding/desktop/data/TBIE/TBIET1/300T1 Actual FREESURFER_HOME /Applications/freesurfer Darwin nua502608.dhcp.swmed.org 14.5.0 Darwin Kernel Version 14.5.0: Tue Sep 1 21:23:09 PDT 2015; root:xnu-2782.50.1~1/RELEASE_X86_64 x86_64 /Users/kding/desktop/data/TBIE/TBIET1/300T1/300 \n mri_convert /Users/kding/desktop/data/TBIE/TBIET1/300T1/30100000-0.dcm /Users/kding/desktop/data/TBIE/TBIET1/300T1/300/mri/orig/001.mgz \n mri_convert /Users/kding/desktop/data/TBIE/TBIET1/300T1/30100000-0.dcm /Users/kding/desktop/data/TBIE/TBIET1/300T1/300/mri/orig/001.mgz $Id: mri_convert.c,v 1.179.2.7 2012/09/05 21:55:16 mreuter Exp $ reading from /Users/kding/desktop/data/TBIE/TBIET1/300T1/30100000-0.dcm... Starting DICOMRead2() dcmfile = /Users/kding/desktop/data/TBIE/TBIET1/300T1/30100000-0.dcm dcmdir = /Users/kding/desktop/data/TBIE/TBIET1/300T1 WARNING: tag ImageNumber not found in /Users/kding/desktop/data/TBIE/TBIET1/300T1/30100000-0.dcm WARNING: tag image orientation not found in /Users/kding/desktop/data/TBIE/TBIET1/300T1/30100000-0.dcm Ref Series No = 18976 ERROR: bits = 0 not supported. Send email to freesurfer(a)nmr.mgh.harvard.edu<mailto:freesurfer@nmr.mgh.harvard.edu> Darwin nua502608.dhcp.swmed.org 14.5.0 Darwin Kernel Version 14.5.0: Tue Sep 1 21:23:09 PDT 2015; root:xnu-2782.50.1~1/RELEASE_X86_64 x86_64 recon-all -s 300 exited with ERRORS at Thu Feb 4 15:53:19 CST 2016 For more details, see the log file /Users/kding/desktop/data/TBIE/TBIET1/300T1/300/scripts/recon-all.log To report a problem, see http://surfer.nmr.mgh.harvard.edu/fswiki/BugReporting ________________________________ UT Southwestern Medical Center The future of medicine, today.

2 1

Volume analysis in native space vs. mni305 space
by Rodriguez-Thompson, Anais 07 Feb '16

07 Feb '16

Hi FreeSurfer experts, I'm in the process of switching over our first-level analyses from being run in native space to being run in fsaverage/mni305 space. Looking at the first-levels on an individual subject level, the volume analyses look fairly different (cortical signal especially is lost in the mni305 analysis). I've attached a couple of slides with images comparing the two volume analyses. My commands for the mni305 analysis are... Pre-processing: preproc-sess -s GDDA001 -surface fsaverage lhrh -mni305 -fwhm 5 -per-run -d $SUBJECTS_DIR -fsd bold -so siemens Mkanalysis: mkanalysis-sess -analysis SIRP_LoadRegression_Stable5.3_012616_sm5_mni305 -mni305 2 -fwhm 5 -paradigm slopepar -event-related -fsd bold -runlistfile runlistfile -tpef tpef_1.5mm.txt -timewindow 20 -TER 2 -nconditions 9 -gammafit 2.25 1.25 -refeventdur 2 -per-run -TR 2 -stc siemens -force Mkcontrast: mkcontrast-sess -analysis SIRP_LoadRegression_Stable5.3_012616_sm5_mni305 -contrast 2vFix -a 2 -c 0 My commands for the native space analysis are... Preprocessing: preproc-sess -s GDDA001 -fwhm 5 -per-run -d $SUBJECTS_DIR -fsd bold Mkanalysis: mkanalysis-sess -analysis SIRP_LoadRegression_Stable5_050514 -TR 2 -paradigm slopepar -event-related -runlistfile runlistfile -tpef tpef_1.5mm.txt -native -fwhm 5 -timewindow 20 -TER 2 -nconditions 9 -gammafit 2.25 1.25 -refeventdur 2 Mkcontrast: mkcontrast-sess -analysis SIRP_LoadRegression_Stable5_050514 -contrast 2vFix -a 2 -c 0 I have a couple of questions regarding the differences between the two analyses. First, why is so much of the signal robustness from the native space volume analysis lost in the mni305 analysis? Second, why are the voxel sizes so different between the two analyses (with the native space analysis having a much larger voxel size)? Thanks, Anais

2 2

spot checking results
by Krieger, Donald N. 07 Feb '16

07 Feb '16

Dear List, I have run recon-all -all on the same scan on two different machines likely running two different versions of Linux but in any case the runs were done with different numbers of cores. I haven't done anything fancy to compare that the results are identical except for some spot checks of individual files with md5sum. label/lh.BA4a.label shows up the same on both. mri/wmparc.mgz does not. Your comments would be welcome. Is there something about the non-ascii files, e.g. wmparc.mgz, which would make them show different checksums, e.g. inclusion of a processing time or some such? Do you have experience or suggestions for convincing ourselves that we are getting the same answers on different machines? ??? Thanks - Don

3 2

To use a ROI.label as seed in FS-FAST
by stdp82＠virgilio.it 07 Feb '16

07 Feb '16

Hi list, I would like to use as seed in FS-FAST a ROI.label which I have drawn on a cluster in tksurfer.How can I do it?Should I use mri_label2vol? Thanks. Stefano

2 1

Paired analysis FSFAST
by Thục Trinh 07 Feb '16

07 Feb '16

Hello, I'm working on group analysis in fMRI activation using FSFAST. I tend to test whether any significant changed in fMRI activation within group across two time points ( pre-training vs post). I ran first level already. I still confuse about the concat data and the mri_glmfit command. Here are the command lines, I'm wondering if it runs exactly what I want it to do. -- idlist Input NCP140005_1 Input NCP140005_2 Input NCP140012_1 Input NCP140012_2 Input NCP140071_1 Input NCP140071_2 Input NCP140079_1 Input NCP140079_2 Input NCP140082_1 Input NCP140082_2 Input NCP140543_1 Input NCP140543_2 Input NCP140556_1 Input NCP140556_2 Input NCP140558_1 Input NCP140558_2 -- concat data isxconcat-sess -sf idlist -analysis work.sm5.lh -contrast con-v-arrow -o group2 -- FSGD file GroupDescriptorFile 1 Title Con-arrow Gr2 Class Defi Input NCP140005 Defi Input NCP140012 Defi Input NCP140071 Defi Input NCP140079 Defi Input NCP140082 Defi Input NCP140543 Defi Input NCP140556 Defi Input NCP140558 Defi -- run glm analyisis mri_glmfit --glmdir lh.paired.gr2-diff --y ces.nii --fsgd con-arrow_group2.fsgd --C mean.mat -- content in matrix contrast C = [ 1 0 ] Thank you, Trinh

2 1

Planum temporale measurement
by Adam David Felton 07 Feb '16

07 Feb '16

Hello, I checked the listserv history, but couldn't find an answer to my question: With the 2009 parcellation scheme, 1) does the planum temporale parcellation include the posterior ascending ramus (which Destrieux et al. 2010 seems to imply) and 2) does the planum temporale include the posterior descending ramus? Thank you! Adam

3 2

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