Freesurfer January 2021

freesurfer@nmr.mgh.harvard.edu

98 participants
132 discussions

Group Analysis Question
by Swanson,Clayton 15 Jan '21

15 Jan '21

External Email - Use Caution Hi Freesurfer Team, I am performing an analysis on 23 HC and 26 people with MS and I would like to perform the stats appropriately. I would like to control for (or regress out) age and sex. Therefore, I created my FSGD file which has 4 classes (HC_Male, HC_Female, MS_Male, MS_Female) with age being the only variable. My contrast for this analysis is: 0.5 -0.5 0.5 -0.5 0 0 0 0. Lastly, I want to run a permutation analysis, so I set it up like this: #!/bin/tcsh setenv study $argv[1] foreach meas (thickness volume) foreach hemi (lh rh) foreach smoothness (10) foreach dir ({$hemi}.{$meas}.{$study}.{$smoothness}.glmdir) mri_glmfit-sim \ --glmdir {$dir} \ --perm 1000 1.3 pos \ --cwp 0.05 \ --2spaces \ --overwrite end end end end After running the permutation, my next steps were to view the results in Freeview with the command [ freeview -f $SUBJECTS_DIR/fsaverage/surf/lh.inflated:overlay=perm.th13.pos.sig.cluster.mgh ] because it’s my understanding that would overlay the cluster-wise corrected map and the view I get is an entirely yellow hemisphere. However, there are no significant clusters when viewing the perm.th13.pos.sig.cluster.summary, so I am a bit confused. Also, when I look at the uncorrected results with the sig.mgh file there are a number of spots on the hemisphere. Does this result mean that there are no cortical thickness differences between HC and MS when controlling for Age and Sex? Or does this result mean something different? What could be the next analysis steps I could perform? My goals are to assess cortical thickness differences between HC and MS. Thanks for any help you can provide, Clayton ________________________________ Clayton Swanson MS Graduate Research Assistant & PhD Candidate Sensorimotor Neuroimaging Laboratory Colorado State University Office: (970) 491-6160 Clayton.Swanson(a)colostate.edu<mailto:Clayton.Swanson@colostate.edu> (He/Him)

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Qdec crash while analysis almost finished
by chenbh35＠mail.sysu.edu.cn 15 Jan '21

15 Jan '21

External Email - Use Caution Hi, dear Freesurfer experts, I recently came across an invalid Freesurfer license key error while using v5.3, and I tried apply for another license key, it just sent me the same license key as I have apply before. Then I put the licence file to /usr/local/freesurfer and has changed the name to .license as well. But it still doesn't work. Owing to the version I used last time was v6.0, so I reinstall a v6.0 and use the same license file. But here comes the new problem, when the analysis almost finished, qdec just crash and disappear, parts of the contents in the command window are: """""""""""""""""""""" Writing results lh-Avg-Intercept-thickness maxvox sig=1e+10 F=3846.45 at index 14 0 0 seed=1611502349 lh-Diff-PCE-CON-Intercept-thickness maxvox sig=3.52355 F=15.3058 at index 11472 0 0 seed=1611502349 mri_glmfit done ninputs = 2 Checking inputs nframestot = 2 Allocing output Done allocing nframes = 2 Writing to /media/lava/DATA/ESSAY/FirstWave/qdec/Untitled/contrasts.sig.mgh -------------------------------------------------------------------------- ERROR: Invalid FreeSurfer license key found in license file /usr/local/freesurfer/license.txt If you are outside the NMR-Martinos Center, go to http://secure-web.cisco.com/1l89yx4rr6CbgxQdMiHeY9D8oLAHswLvN7Y1eaaby-Qvn6B… to get a valid license file (it's free). If you are inside the NMR-Martinos Center, make sure to source the standard environment. """"""""""""""""""""""" I wonder what was the question? Appreciate for any suggestions.

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Open Ph.D. position
by Rosalia Dacosta Aguayo 14 Jan '21

14 Jan '21

External Email - Use Caution The Institut d’Investigació en Atenció Primària Jordi Gol i Gurina is looking to cover *a Ph.D. position *for the Grenssap Group (led by Dra. Concepció Violán). This is a multidisciplinary team formed by medical doctors, nurses, statisticians, pharmacist, psychologist- and junior researchers. The main research lines of the group are (1) Evaluation of the use of Primary Care services, programs and interventions; (2) Evaluation of drug use; (3) Community interventions to reduce the effect of health issues; (4) Health Services Research: classification of multimorbidity patterns, implications of multimorbidity for the health services, validation and improvement of current information systems in PC and validation of questionnaires. Grenssap group information https://secure-web.cisco.com/186oGLgiF4R4PrU_gPjsxFfnddSX0mMyppqzVvMVC9Yqwe… Essential Selection Criteria: · Bachelor’s Degree in Statistics or Mathematics. · Experience in data management and statistical analysis. · Good understanding of the English language. Responsibilities: · Management of big databases. · Statistical and methodological assessment of projects: design, sample size calculation, analysis plan, data analysis and presentation of results. · Database creation, cleaning and restructuring. Quality control and validation of data. Desirable Selection Criteria: · Experience in research projects using electronic health records databases. · Participation in research projects within the health sciences, particularly regarding the design and analysis of cohort and case-control studies. · Experience in the development of analytical projects: design and plan of analysis, data capture and preparation, statistical analysis, validation and presentation of results, sample size calculation for complex samples. · Expertise in statistical programmes and data analyses: SPSS, Stata, R and/or other programmes. · Experience in the management and cleaning of databases (packages in R *plyr*, *bash programming* of Linux, Python). · Experience in primary care research. · Knowledge of the Catalan language. · Knowledge of the Spanish language. · Ability to contribute to the team and active participation in discussions. Open to acquire new skills and knowledge. · Problem-solving skills, self-sufficient. · Dynamic, active involvement in the projects, innovative. Easily adaptable to different working conditions and technologies. · Based on the characteristics and academic merits of the candidate, he/she will be able to enter a PhD program. Contract Type: *Hours*: 40 hours/week *Salary*: Based on hours/week and experience (junior/senior) *Contract*: Fixed term/Service *Location*: Barcelona, IDIAPJGol headquarters *Start*: May 2020 *Duration*: 1 year with a possibility of extension *Selection Process:* *Send your applications to:* Applicants should register on the IDIAPJGol website (work with us/open calls) or via the following link: *LINK TO REGISTRATION* <https://secure-web.cisco.com/1SD7eUwMZaUUBUFEPDk1UHFfU3bGkz9c_fVGc1vWQbxUIi…> *Until**: May 1, 2020* Final candidates will be interviewed. * CONTACT: rdacostaa(a)gmail.com <rdacostaa(a)gmail.com>* Evaluation of final candidates: Will be conducted in accordance to the Selection Process Manual of the IDIAPJGol (IT-085) available in our website. The contract will follow the applicable agreement and the current statutes of workers. The selection process will follow the principles of merit, equality and capacity and will adjust to the characteristics and requirements needed to carry out the responsibilities specified in the job offer. The contract will not take effect if the merits alleged in the cv cannot be documented. In compliance with the GDPR (EU) and the Organic Law 3/2018, December 5, regarding the protection of personal data and digital rights, we inform you that your email address and other personal data provided by yourself will be automatically included in our database for the selection process. Once the selection process finishes (for whichever cause), your data will be eliminated. The IDIAPJGol is responsible for the processing of data and the Data Protection Officer is Mr. Josuè Sallent Ribes (dpd(a)ticsalutsocial.cat) The applicant can exercise at any moment their rights of access, rectification, cancellation, opposition, data portability, right to be forgotten and limitation of processing in accordance with current regulations.

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3D reconstruction of brain MRI
by Fleur GAUDFERNAU 14 Jan '21

14 Jan '21

External Email - Use Caution Dear all, I have just started using Freesurfer. I have an issue when trying to perform volumetric reconstruction from MRI files. Sorry if my question is naive. Data description: for each subject, 3 DICOM folders, each one containing 2D MRI slices along one axis. (I also have them in nifti format.) Goal: volume reconstruction to obtain a single 3D volume of the subject brain. What I did: recon-all -all -i path/to/mri_axial.nii -i path/to/mri_coronal.nii -i path/to/mri_sagittal.nii -s subject Error message: inputs have mismatched dimensions! 512 x 512 x 50 / 512 x 512 x 14 / 512 x 512 x 22 (The mismatched dimensions being totally normal, considering the number of slices along each axis does not have to be the same.) However, if I use recon-all on only 1 of the 3 files, it works perfectly. I think I misunderstood the use of recon-all: it does not really perform volume reconstruction, i.e. transforming 3 series of 2D slices into a single 3D volume? If not, could someone tell me which software can perform this task? (So far the only one I know, NiftyMIC, is dedicated to fetal brain MRIs - but the task remains the same). Thanks in advance, Fleur Gaudfernau

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Re: [Freesurfer] Segmentation Fault During mri_convert running FS 5.0
by Dowling, Kevin Francis 14 Jan '21

14 Jan '21

Hi Dr. Greve, Thanks so much for your reply. I ran the command as instructed (bolded) in 5.0 (and again in 5.3 for comparison, since that ran fine in my earlier troubleshooting efforts) and have placed the terminal outputs below. In 5.0 the output I received in the terminal: (nmr-stable5.0-env) mri_convert /autofs/cluster/deplin/chris/data/Selected_Scans/3800033/MPRAGE/003/MEMPRAGE.nii deleteme.mgz mri_convert /autofs/cluster/deplin/chris/data/Selected_Scans/3800033/MPRAGE/003/MEMPRAGE.nii deleteme.mgz $Id: mri_convert.c,v 1.166.2.6 2010/11/24 15:19:30 nicks Exp $ reading from /autofs/cluster/deplin/chris/data/Selected_Scans/3800033/MPRAGE/003/MEMPRAGE.nii... Segmentation fault (core dumped) And in 5.3 this was the result, which seemed to run normally: (nmr-stable53-env) mri_convert /autofs/cluster/deplin/chris/data/Selected_Scans/3800033/MPRAGE/003/MEMPRAGE.nii deleteme.mgz mri_convert /autofs/cluster/deplin/chris/data/Selected_Scans/3800033/MPRAGE/003/MEMPRAGE.nii deleteme.mgz $Id: mri_convert.c,v 1.179.2.7 2012/09/05 21:55:16 mreuter Exp $ reading from /autofs/cluster/deplin/chris/data/Selected_Scans/3800033/MPRAGE/003/MEMPRAGE.nii... TR=2530.00, TE=0.00, TI=0.00, flip angle=0.00 i_ras = (-0.101076, -0.994877, 0.0017413) j_ras = (-0.0677184, 0.0051337, -0.997691) k_ras = (-0.992571, 0.10096, 0.0678903) writing to deleteme.mgz... Thank you very much for your help, and for any thoughts you might have. Kind regards, Kevin Date: Tue, 12 Jan 2021 15:45:37 +0000 From: "Greve, Douglas N.,Ph.D." <DGREVE(a)mgh.harvard.edu<mailto:DGREVE@mgh.harvard.edu>> Subject: Re: [Freesurfer] Segmentation Fault During mri_convert running FS 5.0 To: "freesurfer(a)nmr.mgh.harvard.edu<mailto:freesurfer@nmr.mgh.harvard.edu>" <freesurfer(a)nmr.mgh.harvard.edu<mailto:freesurfer@nmr.mgh.harvard.edu>> Message-ID: <63bb4542-e9df-d7cc-926b-0731b60098a2(a)mgh.harvard.edu<mailto:63bb4542-e9df-d7cc-926b-0731b60098a2@mgh.harvard.edu>> Content-Type: text/plain; charset="utf-8" For some reason, it is not capturing the terminal output in the log files. Can you just run mri_convert /autofs/cluster/deplin/chris/data/Selected_Scans/3800033/MPRAGE/003/MEMPRAGE.nii deleteme.mgz and send me the terminal output? On 1/2/2021 2:23 PM, Dowling, Kevin Francis wrote: Hello FreeSurfer experts, We have some old clinical structural data we processed using version 5.0 and had extensively edited manually. We?re now hoping to re-process the data in version 5 to regenerate copies of the subjects that are free of manual edits. So far (because of the below core dump error), I?ve tried doing this two ways, first by running recon-all -autorecon-all -clean -s <subject> on copies of our manually edited data and, secondly, by using from the original, unaltered MPRAGE files and running recon-all -i ./path/to/MEMPRAGE.nii -s <subject> (which fails before we would then run recon-all -autorecon-all -s <subject>). In both cases I?ve run into an error I never encountered when last working with this data 2 years ago in version 5. Specifically I get a ?Segmentation fault (core dumped)? when mri_convert is invoked. I?ve enclosed a copy of the recon-all.log and recon-all.error files as attachments and provided the specific commands that seem to trigger the core dump below (from recon-all.error f ile). I looked on the mail archive but I wasn?t able to find any answers. I?m running version 5.0 (as that is the version our manually edited data was processed in): setenv USE_STABLE_5_0_0 source /usr/local/freesurfer/nmr-stable50-env build stamp: freesurfer-Linux-centos4_x86_64-stable-v5.0.0-20110319 I?m running Red Hat Enterprise Linux Release 6.7 (Santiago) The specific commands that appear to be causing the (Segmentation fault) core dump in each of the two different cases are below (taken from recon error log): When running: recon-all -i ./path/to/MEMPRAGE.nii -s <subject> the error occurs with.. mri_convert /autofs/cluster/deplin/chris/data/Selected_Scans/3800033/MPRAGE/003/MEMPRAGE.nii /autofs/cluster/roffman2/users/RPDR_FromRaw_No_Edits/00033/mri/orig/001.mgz When running: recon-all -autorecon-all -clean -s <subject> the error occurs with.. mri_convert /autofs/cluster/roffman2/users/RPDR_No_Manual_Edits/00033_E/mri/rawavg.mgz /autofs/cluster/roffman2/users/RPDR_No_Manual_Edits/00033_E/mri/orig.mgz --conform Notably, when I tried running the same commands (bolded above) in version 5.3 (source/usr/local/freesurfer/nmr-stable53-env) they both exit without errors, leading me to wonder if this is a software-version interaction issue. (In case it has any bearing, I?m running all of this while ssh?d into the Martinos servers.) I suspect I may have missed something very simple, but I would be very grateful for any suggestions for how I might try to overcome this issue. I?m happy to provide clarification or any additional information that may be helpful. Thank you, Kevin Kevin F. Dowling Per-Diem Clinical Research Coordinator Brain Genomics Laboratory Department of Psychiatry Massachusetts General Hospital MD/PhD Candidate University of Pittsburgh & Carnegie Mellon University MSTP _______________________________________________ Freesurfer mailing list Freesurfer(a)nmr.mgh.harvard.edu<mailto:Freesurfer@nmr.mgh.harvard.edu><mailto:Freesurfer@nmr.mgh.harvard.edu> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer -------------- next part -------------- An HTML attachment was scrubbed... URL: http://mail.nmr.mgh.harvard.edu/pipermail/freesurfer/attachments/20210112/1… Kevin F. Dowling Per-Diem Clinical Research Coordinator Brain Genomics Laboratory Department of Psychiatry Massachusetts General Hospital MD/PhD Candidate University of Pittsburgh & Carnegie Mellon University MSTP

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matrix is ill-conditioned or badly scaled
by Julie Ottoy 14 Jan '21

14 Jan '21

External Email - Use Caution Hi freesurfer experts, I am trying to run a GLM fit between cortical thickness and some other continuous marker. My cortical thickness were stacked before using the mris_preproc and surf2surf commands. I have an FSGD file with the same subjects as used during the stacking of the thickness maps, but I added a new continuous regressor (my independent variable of interest). However, some subjects have a missing value for this regressor, so I added NaN. This makes me run into the following error. When I replace the NaN values by random numbers in the FSGD, it all runs fine. M = [ ... 1.00000 0.99577 0.70711 0.98278 0.97547 -0.97111 nan 0.99577 1.00000 0.70628 0.97775 0.97819 -0.95833 nan 0.70711 0.70628 1.00000 0.68252 0.70488 -0.70032 nan 0.98278 0.97775 0.68252 1.00000 0.95399 -0.96466 nan 0.97547 0.97819 0.70488 0.95399 1.00000 -0.92863 nan -0.97111 -0.95833 -0.70032 -0.96466 -0.92863 1.00000 nan nan nan nan nan nan nan nan ] Normalized matrix condition is 1e+08 Design matrix ------------------ <design matrix> ERROR: matrix is ill-conditioned or badly scaled, condno = 1e+08 -------------------------------- Possible problem with experimental design: Check for duplicate entries and/or lack of range of continuous variables within a class. I made sure that my FSGD file does not have any weird characters, so i applied the cat fsgd.txt | sed 's/\r/\n/g' > new.fsgd.txt, but this also didn't help. Thank you for your help, Julie

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parcellation-based connectome viewing in freeview.
by Octavian Lie 13 Jan '21

13 Jan '21

External Email - Use Caution Dear All, I have a destrieux-based connectome weight matrix, and wanted to see the edge weights between parcels as color-coded activations in freeview, something like the attached fig. I think that would be possible, if able to transform the weights txt file (symmetric matrix, it could be a .dat file) into an .mgh file to overlay it in freeview. Please let me know if it can be done, and how to, or there is another way. Thank you, Octavian

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freesurfer flag for multiple edited volumes
by Dincer, Aylin 13 Jan '21

13 Jan '21

External Email - Use Caution Hello FreeSurfer Experts, If I need to manually edit both the brainmask.mgz and the wm.mgz in a FreeSurfer, what are the recommended flags when rerunning recon-all with the edits (-all, -autorecon2, etc)? Or is it recommended to run an edited volume through recon-all one at a time (i.e. editing the brainmask.mgz first, running recon-all using autorecon2-pial flag, editing the wm.mgz afterwards, then running recon-all again with autorecon2-wm)? Thank you for the help! Aylin ________________________________ The materials in this message are private and may contain Protected Healthcare Information or other information of a sensitive nature. If you are not the intended recipient, be advised that any unauthorized use, disclosure, copying or the taking of any action in reliance on the contents of this information is strictly prohibited. If you have received this email in error, please immediately notify the sender via telephone or return mail.

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Post-Doctoral position available in human neuroimaging and sensory testing at the University of Minnesota School of Dentistry
by Estephan Moana Filho 13 Jan '21

13 Jan '21

External Email - Use Caution *POSITION OVERVIEW* The Division of TMD & Orofacial Pain (OFP) at the University of Minnesota School of Dentistry (UMN SOD) is seeking a highly motivated Post-Doctoral Associate in the field of human neuroimaging and sensory testing for an NIH/NIDCR funded project studying brain-related mechanisms in painful temporomandibular disorders (TMD). The focus of this position will be on acquisition and analysis of neuroimaging data, as well as performing quantitative sensory (QST) and endogenous pain modulation (EPM) testing. This project is led by Dr. Estephan J. Moana-Filho, a dentist-scientist within the TMD & OFP division, who provides clinical care to OFP patients and is interested in expanding the knowledge about brain mechanisms in OFP conditions with a focus on painful TMD. The methods to be used include multimodal magnetic resonance imaging (MRI) based on the Human Connectome Project (HCP) sequences (structural, resting and stimulus-evoked BOLD fMRI, diffusion) combined with sensory testing and psychosocial/behavioral measures (QST, EPM, questionnaires, clinical measures, etc.). Our goal is to further our understanding of brain structural and functional networks involved in sensory processing, and potentially underlying central sensitization features present in painful TMD. *Duties and Responsibilities*: The Post-Doctoral Associate’s responsibilities will include, but are not limited to: 1. Implement multimodal MRI data analysis pipelines (structural and functional connectivity, stimulus-evoked fMRI, diffusion-based tractography and volumetry/cortical thickness measures) based on the HCP pre-processing pipelines (Glasser et al., 2013). 2. Perform sensory/EPM testing in human participants following standardized protocol (Rolke et al., 2006) 3. Acquire neuroimaging data following the HCP neuroimaging approach (Glasser et al., 2016), including stimulus-evoked fMRI. 4. Model and analyze complex datasets including neuroimaging, sensory and clinical data. *Required qualifications*: 1. PhD in neuroscience, biomedical engineering, oral biology, psychology, cognitive science, or a related field. 2. Strong proficiencies with one or more major neuroimaging software suites (e.g., FSL, Freesurfer, Connectome workbench, AFNI, SPM, etc.) and Unix/Linux environment. Familiarity with R, Python, and/or Matlab programming languages is a plus*.* 3. Quantitative and statistical skills, including strong programming skills and comfort with diverse computing environments such as high-performance computing systems. 4. Comfortable with interacting with human participants. 5. Demonstrated ability to complete projects as evidenced by first-author publication(s). 6. Proficient writing skills, motivated and driven to publish in peer-reviewed journals. In addition to these requirements, the ideal candidate should have a passion for self-learning, be inquisitive, critical problem-solving skills and initiative to seek out the resources necessary to achieve the project’s goals. The Moana-Filho lab is part of a vibrant pain research community at the UMN, with access to several resources including: · The Center of Magnetic Resonance Research (CMRR), a world class MRI research center with several research dedicated MRI scanners including three 3T Prisma, 7T and 10.5T human scanners. · The UMN Minnesota Supercomputing Institute (MSI), an interdisciplinary research resource supporting high-performance computing services. The latest MSI’s system is among the top 10 university-owned supercomputers in the nation, with a peak performance of over 670 Tflops and an additional 105 Tflops from a dedicated GPU subsystem. Its main cluster is also equipped with 40 high memory nodes to accommodate large memory requirements. These memory nodes feature 1 TB of memory and large solid state drives for ultra-high performance input/output. All systems are connected to high-performance parallel storage systems, with a current capacity of approximately 3 PBytes. MSI staff manage and operate these resources, offering full support to users in developing and optimizing workflows. Applications will be reviewed on an ongoing basis. Funding is available as a one-year appointment with the possibility of extension. Salary will be competitive and commensurate with experience. In case of any questions, please feel free to contact Dr. Moana-Filho (moana004 at umn dot edu <moana004(a)umn.edu>). To apply, click on “External Applicants” under the banner “Apply now!” and search for Job Opening 337497: https://humanresources.umn.edu/content/find-job

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mri_glmfit-sim error with no csd files generated
by Na, Xiaoxu 13 Jan '21

13 Jan '21

External Email - Use Caution Dear Freesurfer Experts, I've all the subjects successfully done recon-all, lgi before coming to the group analysis. The following group analysis will use the 10mm smoothing as generated in previous recon-all. Mris_preproc were implemented successfully and mri_glmfit as well. However, while coming to the mri_glmfit-sim, it showed done finally, but when going back to the directory, I found out no csd files have ever been generated, and this was reported as well during the mri_glmfit-sim run. Please kindly see the log as below for details. The error was reported in the middle, so I changed it into red. It's quite appreciated it you may help on this. Thanks a lot! $ mri_glmfit-sim \ > --glmdir s/lh.area.g2v3gaCSHQ.10.glmdir \ > --cache 4 neg \ > --cwp 0.05 \ > --2spaces cmdline mri_glmfit --y sAnalysis/lh.area.g2v3gaCSHQ.10.mgh --fsgd sAnalysis/g2v3gaCSHQ.fsgd --C sAnalysis/g1g2.sscorewithBMI.mtx --surf fsaverage lh --cortex --glmdir sAnalysis/lh.area.g2v3gaCSHQ.10.glmdir SURFACE: fsaverage lh log file is sAnalysis/lh.area.g2v3gaCSHQ.10.glmdir/cache.mri_glmfit-sim.log cd /home/xiaoxu/8YearOldNiiB1 /home/xiaoxu/freesurfer/bin/mri_glmfit-sim --glmdir sAnalysis/lh.area.g2v3gaCSHQ.10.glmdir --cache 4 neg --cwp 0.05 --2spaces mri_glmfit-sim 7.1.0 Tue Jan 5 15:11:00 CST 2021 Linux xnVMUbuntu18 5.4.0-58-generic #64~18.04.1-Ubuntu SMP Wed Dec 9 17:11:11 UTC 2020 x86_64 x86_64 x86_64 GNU/Linux xiaoxu setenv SUBJECTS_DIR /home/xiaoxu/8YearOldNiiB1 FREESURFER_HOME /home/xiaoxu/freesurfer Original mri_glmfit command line: cmdline mri_glmfit --y sAnalysis/lh.area.g2v3gaCSHQ.10.mgh --fsgd sAnalysis/g2v3gaCSHQ.fsgd --C sAnalysis/g1g2.sscorewithBMI.mtx --surf fsaverage lh --cortex --glmdir sAnalysis/lh.area.g2v3gaCSHQ.10.glmdir DoSim = 0 UseCache = 1 DoPoll = 0 DoPBSubmit = 0 DoBackground = 0 DiagCluster = 0 gd2mtx = dods fwhm = 20.731766 CSD /home/xiaoxu/freesurfer/average/mult-comp-cor/fsaverage/lh/cortex/fwhm21/neg/th40/mc-z.csd mri_surfcluster --in sAnalysis/lh.area.g2v3gaCSHQ.10.glmdir/g1g2.sscorewithBMI/sig.mgh --mask sAnalysis/lh.area.g2v3gaCSHQ.10.glmdir/mask.mgh --cwsig sAnalysis/lh.area.g2v3gaCSHQ.10.glmdir/g1g2.sscorewithBMI/cache.th40.neg.sig.cluster.mgh --sum sAnalysis/lh.area.g2v3gaCSHQ.10.glmdir/g1g2.sscorewithBMI/cache.th40.neg.sig.cluster.summary --ocn sAnalysis/lh.area.g2v3gaCSHQ.10.glmdir/g1g2.sscorewithBMI/cache.th40.neg.sig.ocn.mgh --annot aparc --cwpvalthresh 0.05 --o sAnalysis/lh.area.g2v3gaCSHQ.10.glmdir/g1g2.sscorewithBMI/cache.th40.neg.sig.masked.mgh --no-fixmni --csd-out sAnalysis/lh.area.g2v3gaCSHQ.10.glmdir/csd/all.cache.th40.neg-g1g2.sscorewithBMI.csd --csd /home/xiaoxu/freesurfer/average/mult-comp-cor/fsaverage/lh/cortex/fwhm21/neg/th40/mc-z.csd --csdpdf sAnalysis/lh.area.g2v3gaCSHQ.10.glmdir/g1g2.sscorewithBMI/cache.th40.neg.pdf.dat --vwsig sAnalysis/lh.area.g2v3gaCSHQ.10.glmdir/g1g2.sscorewithBMI/cache.th40.neg.sig.voxel.mgh --vwsigmax sAnalysis/lh.area.g2v3gaCSHQ.10.glmdir/g1g2.sscorewithBMI/cache.th40.neg.sig.voxel.max.dat --oannot sAnalysis/lh.area.g2v3gaCSHQ.10.glmdir/g1g2.sscorewithBMI/cache.th40.neg.sig.ocn.annot --bonferroni 2 --surf white Merging CSD files ERROR: could not open sAnalysis/lh.area.g2v3gaCSHQ.10.glmdir/csd/all.cache.th40.neg-g1g2.sscorewithBMI.csd Creating CDFs from CSD files csd->threshsign = -1 thsign = neg, id = -1 version 7.1.0 hemi = lh srcid = sAnalysis/lh.area.g2v3gaCSHQ.10.glmdir/g1g2.sscorewithBMI/sig.mgh srcsubjid = fsaverage srcsurf = white srcframe = 0 thsign = neg thmin = 4 thmax = -1 fdr = -1 minarea = 0 Bonferroni = 2 xfmfile = talairach.xfm nth = -1 outid = sAnalysis/lh.area.g2v3gaCSHQ.10.glmdir/g1g2.sscorewithBMI/cache.th40.neg.sig.masked.mgh MGH ocnid = sAnalysis/lh.area.g2v3gaCSHQ.10.glmdir/g1g2.sscorewithBMI/cache.th40.neg.sig.ocn.mgh MGH sumfile = sAnalysis/lh.area.g2v3gaCSHQ.10.glmdir/g1g2.sscorewithBMI/cache.th40.neg.sig.cluster.summary subjectsdir = /home/xiaoxu/8YearOldNiiB1 FixMNI = 0 Found 148772 vertices in mask Found 148772 vertices in mask Found 148772 points in clabel. ------------- XFM matrix (RAS2RAS) --------------- /home/xiaoxu/8YearOldNiiB1/fsaverage/mri/transforms/talairach.xfm 1.00000 0.00000 0.00000 0.00000; 0.00000 1.00000 0.00000 0.00000; 0.00000 0.00000 1.00000 0.00000; 0.00000 0.00000 0.00000 1.00000; ---------------------------------------------------- Reading source surface /home/xiaoxu/8YearOldNiiB1/fsaverage/surf/lh.white Done reading source surface Reading annotation /home/xiaoxu/8YearOldNiiB1/fsaverage/label/lh.aparc.annot mri_surfcluster supposed to be reproducible but seed not set reading colortable from annotation file... colortable with 36 entries read (originally /autofs/space/terrier_001/users/nicks/freesurfer/average/colortable_desikan_killiany.txt) Computing metric properties Loading source values number of voxels in search space = 148772 Done loading source values (nvtxs = 163842) overall max = 2.5813 at vertex 86764 overall min = -4.50366 at vertex 40067 surface nvertices 163842 metric props tot surface area 65417.000000 group_avg_vtxarea_loaded 1 masked surface area 75952.695312 Computing voxel-wise significance CSDpvalMaxSigMap(): found 8194/163842 above 0, max=-0.96614 Adjusting threshold for 1-tailed test. If the input is not a -log10(p) volume, re-run with --no-adjust. thminadj = 3.69897 Searching for Clusters ... thmin=4.000000 (3.698970), thmax=-1.000000 (-1), thsignid=-1, minarea=0.000000 Found 2 clusters Max cluster size 296.333069 Pruning by CW P-Value 0.05 Saving thresholded output to sAnalysis/lh.area.g2v3gaCSHQ.10.glmdir/g1g2.sscorewithBMI/cache.th40.neg.sig.masked.mgh Saving cluster numbers to sAnalysis/lh.area.g2v3gaCSHQ.10.glmdir/g1g2.sscorewithBMI/cache.th40.neg.sig.ocn.mgh Saving cluster pval sAnalysis/lh.area.g2v3gaCSHQ.10.glmdir/g1g2.sscorewithBMI/cache.th40.neg.sig.cluster.mgh Constructing output annotation Writing annotation sAnalysis/lh.area.g2v3gaCSHQ.10.glmdir/g1g2.sscorewithBMI/cache.th40.neg.sig.ocn.annot mri_segstats --seg sAnalysis/lh.area.g2v3gaCSHQ.10.glmdir/g1g2.sscorewithBMI/cache.th40.neg.sig.ocn.mgh --exclude 0 --i sAnalysis/lh.area.g2v3gaCSHQ.10.mgh --avgwf sAnalysis/lh.area.g2v3gaCSHQ.10.glmdir/g1g2.sscorewithBMI/cache.th40.neg.y.ocn.dat --sum /tmp/mri_glmfit-sim.junk.53691 7.1.0 cwd cmdline mri_segstats --seg sAnalysis/lh.area.g2v3gaCSHQ.10.glmdir/g1g2.sscorewithBMI/cache.th40.neg.sig.ocn.mgh --exclude 0 --i sAnalysis/lh.area.g2v3gaCSHQ.10.mgh --avgwf sAnalysis/lh.area.g2v3gaCSHQ.10.glmdir/g1g2.sscorewithBMI/cache.th40.neg.y.ocn.dat --sum /tmp/mri_glmfit-sim.junk.53691 sysname Linux hostname xnVMUbuntu18 machine x86_64 user xiaoxu whitesurfname white UseRobust 0 Loading sAnalysis/lh.area.g2v3gaCSHQ.10.glmdir/g1g2.sscorewithBMI/cache.th40.neg.sig.ocn.mgh Loading sAnalysis/lh.area.g2v3gaCSHQ.10.mgh Voxel Volume is 1 mm^3 Generating list of segmentation ids Found 2 segmentations Computing statistics for each segmentation Reporting on 1 segmentations Using PrintSegStat Computing spatial average of each frame 0 Writing to sAnalysis/lh.area.g2v3gaCSHQ.10.glmdir/g1g2.sscorewithBMI/cache.th40.neg.y.ocn.dat mri_segstats done mri_convert sAnalysis/lh.area.g2v3gaCSHQ.10.glmdir/g1g2.sscorewithBMI/cache.th40.neg.sig.cluster.mgh sAnalysis/lh.area.g2v3gaCSHQ.10.glmdir/g1g2.sscorewithBMI/cache.th40.neg.sig.cluster.mgh --frame 0 mri_convert sAnalysis/lh.area.g2v3gaCSHQ.10.glmdir/g1g2.sscorewithBMI/cache.th40.neg.sig.cluster.mgh sAnalysis/lh.area.g2v3gaCSHQ.10.glmdir/g1g2.sscorewithBMI/cache.th40.neg.sig.cluster.mgh --frame 0 reading from sAnalysis/lh.area.g2v3gaCSHQ.10.glmdir/g1g2.sscorewithBMI/cache.th40.neg.sig.cluster.mgh... TR=0.00, TE=0.00, TI=0.00, flip angle=0.00 i_ras = (-1, 0, 0) j_ras = (0, 0, -1) k_ras = (0, 1, 0) keeping frame 0 writing to sAnalysis/lh.area.g2v3gaCSHQ.10.glmdir/g1g2.sscorewithBMI/cache.th40.neg.sig.cluster.mgh... Tue Jan 5 15:11:00 CST 2021 Tue Jan 5 15:11:03 CST 2021 mri_glmfit-sim done Below is the mri_glmfit log. 7.1.0 cwd /home/xiaoxu/8YearOldNiiB1 cmdline mri_glmfit --y sAnalysis/lh.area.g2v3gaCSHQ.10.mgh --fsgd sAnalysis/g2v3gaCSHQ.fsgd --C sAnalysis/g1g2.sscorewithBMI.mtx --surf fsaverage lh --cortex --glmdir sAnalysis/lh.area.g2v3gaCSHQ.10.glmdir sysname Linux hostname xnVMUbuntu18 machine x86_64 user xiaoxu FixVertexAreaFlag = 1 UseMaskWithSmoothing 1 OneSampleGroupMean 0 y /home/xiaoxu/8YearOldNiiB1/sAnalysis/lh.area.g2v3gaCSHQ.10.mgh logyflag 0 usedti 0 FSGD sAnalysis/g2v3gaCSHQ.fsgd labelmask /home/xiaoxu/8YearOldNiiB1/fsaverage/label/lh.cortex.label maskinv 0 glmdir sAnalysis/lh.area.g2v3gaCSHQ.10.glmdir IllCondOK 0 ReScaleX 1 DoFFx 0 Creating output directory sAnalysis/lh.area.g2v3gaCSHQ.10.glmdir Loading y from /home/xiaoxu/8YearOldNiiB1/sAnalysis/lh.area.g2v3gaCSHQ.10.mgh ... done reading. INFO: gd2mtx_method is dods Saving design matrix to sAnalysis/lh.area.g2v3gaCSHQ.10.glmdir/Xg.dat Computing normalized matrix Normalized matrix condition is 4709.02 Matrix condition is 1e+08 Found 149955 points in label. Pruning voxels by thr: 1.175494e-38 Found 148772 voxels in mask Saving mask to sAnalysis/lh.area.g2v3gaCSHQ.10.glmdir/mask.mgh Reshaping mriglm->mask... search space = 73961.671829 DOF = 59 Starting fit and test Fit completed in 0.0714833 minutes Computing spatial AR1 on surface Residual: ar1mn=0.997889, ar1std=0.000967, gstd=8.803970, fwhm=20.731766 Writing results g1g2.sscorewithBMI MRImask(): AllowDiffGeom = 1 maxvox sig=-4.50366 F=20.3419 at index 40067 0 0 seed=1610329800 mri_glmfit done Regards, Xiaoxu ---------------------------------------------------------------------- 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. 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Freesurfer January 2021