Freesurfer

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30084 discussions

Tracula 7.1.1 - trac-all - stat
by Fanny Noury 12 Jul '21

12 Jul '21

External Email - Use Caution Hello FreeSurfer Developers, I am just started to use "the trac-all -stat" command of Tracula 7.1.1 to reconstruct a mean tract for each pathway for all the subjects of a group. Several files are created for each pathway in the "stat" directory. What are the differences between these two files created for the AF, MD AD and RD diffusion parameters : - TRACTNAME_PP.avg33_mni_bbr.**.txt - TRACTNAME_PP.avg33_mni_bbr.**_Avg.txt Thank You very much for your help. Best Regards, F. Noury ----------------------------------------- Fanny NOURY, Ph.D Associate Pr. Rennes 1 University LTSI UMR INSERM 1099 Université de Rennes 1 Campus Villejean - RDC Bât. 5 CS 34317 35043 Rennes Cedex France

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Re: [Freesurfer] Developer login
by fsbuild 12 Jul '21

12 Jul '21

External Email - Use Caution Hello Zachary, Sending some info to your private email shortly. - R. On Jul 12, 2021, at 16:33, Zachary Wickliffe <zswickliffe(a)gmail.com> wrote:        External Email - Use Caution        Hey there, setting up virtualbox to run freesurfer and it's asking for a developer login. Can you help?Thank you,Zachary Wickliffe+1-727-871-1733zswickliffe(a)gmail.comOn Mon, Jul 12, 2021, 4:28 PM Zachary Wickliffe <zswickliffe(a)gmail.com> wrote:Hey there, setting up virtualbox to run freesurfer and it's asking for a developer login. Can you help?Thank you,Zachary Wickliffe+1-727-871-1733zswickliffe@gmail.com_______________________________________________Freesurfer mailing listFreesurfer@nmr..mgh.harvard.eduhttps://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer

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Re: [Freesurfer] Developer login
by Zachary Wickliffe 12 Jul '21

12 Jul '21

External Email - Use Caution Hey there, setting up virtualbox to run freesurfer and it's asking for a developer login. Can you help? Thank you, Zachary Wickliffe +1-727-871-1733 zswickliffe(a)gmail.com On Mon, Jul 12, 2021, 4:28 PM Zachary Wickliffe <zswickliffe(a)gmail.com> wrote: > Hey there, setting up virtualbox to run freesurfer and it's asking for a > developer login. Can you help? > > Thank you, > > Zachary Wickliffe > +1-727-871-1733 > zswickliffe(a)gmail.com >

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Re: [Freesurfer] mri_glmfit DOSS
by Dr. Cornelius Kronlage 12 Jul '21

12 Jul '21

External Email - Use Caution Thank you for your reply! Using DOSS is precisely what I was trying to do, but mri_glmfit doesn't let me. I worked around by creating the design matrix in matlab and specify it to mri_glmfit directly, but I was wondering whether this might be bug in the parsing of the FSGD file. As a minimal example to reproduce, see the attached file. Trying to run mri_glmfit (doesn't even need more input specified), I get: $ mri_glmfit --fsgd dosstest.fsgd doss gdfRead(): reading dosstest.fsgd INFO: DeMeanFlag keyword not found, DeMeaning will NOT be done. Continuous Variable Means (all subjects) 0 C 32.1111 8.50417 1 D 0.555556 0.496904 2 E 5.44444 3.49956 Class Size and Means of each Continuous Variable 1 A 1 50.0000 1.0000 4.0000 2 B 8 29.8750 0.5000 5.6250 ERROR: Class A has 1 members. With 3 variables and using DODS, you need at least 4 members dosstest.fsgd: GroupDescriptorFile 1 Title DOSSTest DOSS Class A Class B Variables C D E Input SUBJECT1 A 50 1 4 Input SUBJECT2 B 30 0 12 Input SUBJECT3 B 29 0 5 Input SUBJECT4 B 31 1 3 Input SUBJECT5 B 20 1 4 Input SUBJECT6 B 42 1 6 Input SUBJECT7 B 33 0 11 Input SUBJECT8 B 30 0 1 Input SUBJECT9 B 24 1 3 Concerning demeaning: I am only going to use a contrast vector for differences in intercept between the groups [-1 1 0 0 0] and had the understanding that demeaning would't be necessary in this case. Am I mistaken or is there other reasons to do this especially for eTIV? Thank you very much and with best wishes, Cornelius > Date: Fri, 9 Jul 2021 14:05:31 -0400 > From: "Douglas N. Greve" <dgreve(a)mgh.harvard.edu> > Subject: Re: [Freesurfer] mri_glmfit DOSS > > You cannot use a DODS in this design as it tries to fit an offset and a > slope for each class, which can't be done when the class has only one > member. Try using DOSS instead. You should probably demean and rescale > the eTIV to be between 0 and 1. > > On 6/29/2021 11:19 AM, Dr. Cornelius Kronlage wrote: > > > > ????????External Email - Use Caution > > > > Dear freesurfers, > > > > for a morphometry study, I am comparing a single subject at a time to > > a group of controls. I would like to include age, gender (as a > > continuous variable for the sake of simplicity) and eTIV as ?nuisance? > > regressors in the GLM. The FSGD looks like this: > > > > GroupDescriptorFile 1 > > ?? ?Title SUBJECT1_vs_allControls > > ?? ?Class Test > > ?? ?Class Controls > > ?? ?Variables Age Gender eTIV > > > > Input SUBJECT1 Test 50 1 1497422.2500 > > Input SUBJECT2 Controls 30 0 1709039.536815 > > Input SUBJECT3 Controls 29 0 1423097.816203 > > Input SUBJECT4 Controls 31 1 1524690.026713 > > ... > > > > When I try to run mri_glmfit I get the following error even though I > > specify DOSS: > > > > $ mri_glmfit --fsgd SUBJECT1_vs_allControls.fsgd doss [...] > > > > gdfRead(): reading SUBJECT1_vs_allControls.fsgd > > WARNING: variable 1 is "Gender" which is often a discrete factor > > ? The proper way to handle discrete factors is to create classes. > > ? See https://secure-web.cisco.com/1pPOfqP7ALbHwAeCTJZowgLS8JJNUeA6-Z2RJlgx_6oCnQ… > > INFO: DeMeanFlag keyword not found, DeMeaning will NOT be done. > > Continuous Variable Means (all subjects) > > 0 Age 28.6875 6.36611 > > 1 Gender 0.46875 0.499022 > > 2 eTIV 1.51444e+06 125811 > > Class Size and Means of each Continuous Variable > > 1 Test? 1? 50.0000?? 1.0000 1497422.2500 > > 2 Controls 31? 28.0000?? 0.4516 1514993.8589 > > ERROR: Class Test has 1 members. With 3 variables and using DODS, you > > need at least 4 members > > > > How do I get mri_glmfit to use DOSS, or do I have to specify the > > design matrix by hand in this case? > > > > Thank you! > > > > Best wishes > > Cornelius > > > >

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Ill-Conditioned/Badly Scaled Matrix Error
by Lurie, Lucy 11 Jul '21

11 Jul '21

External Email - Use Caution Hello I am trying to a whole brain analysis with one group and five covariates. I am getting an error that the design matrix may be ill-conditioned or badly scaled. I checked over the fsgd file in TextEdit and it seems to be formatted correctly. I am using Freesurfer version 5.3.0 and my platform is macOS Big Sur version 11.4. I would appreciate any help further troubleshooting this error. Thank you! ERROR: matrix is ill-conditioned or badly scaled, condno = 13065 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 lh.eig_cgORCE_baselineORCE_teenCG.thickness.10.mgh --fsgd eig_cgORCE_baselineORCE_teenCG.fsgd dods --C eig_cgORCE3042_slope.mtx --C eig_cgORCEbaseline_slope.mtx --C eig_teenCGqual_slope.mtx --surf fsaverage lh --cortex --glmdir lh.eig_cgORCE_baselineORCE_teenCGagesex.glmdir 2. The FSGD file (if using one) 3. And the design matrix Design matrix ------------------ 1.000 0.000 16.660 2.950 2.200 0.000; 1.000 0.000 16.960 1.900 2.600 0.000; 1.000 0.000 17.390 2.450 2.800 0.000; 1.000 1.000 17.130 2.300 2.500 0.000; 1.000 1.000 16.980 2.400 2.300 0.000; 1.000 0.000 17.690 2.200 2.900 0.000; 1.000 1.000 16.870 2.750 2.900 1.000; 1.000 0.000 17.570 2.550 1.700 0.000; 1.000 0.000 17.130 2.150 1.928 0.000; 1.000 1.000 17.650 2.750 2.200 0.000; 1.000 1.000 17.210 2.450 2.500 1.000; 1.000 0.000 15.610 3.100 1.565 1.000; 1.000 0.000 16.440 2.650 2.300 0.000; 1.000 1.000 17.350 2.400 2.600 0.000; 1.000 0.000 16.800 1.600 1.400 0.000; 1.000 1.000 17.980 2.200 2.300 1.000; 1.000 1.000 16.890 2.800 1.600 1.000; 1.000 0.000 16.760 1.100 1.300 0.000; 1.000 1.000 16.790 2.500 1.400 0.000; 1.000 1.000 16.620 2.900 2.800 0.000; 1.000 1.000 16.500 2.500 1.200 0.000; 1.000 1.000 16.290 2.700 3.200 0.500; 1.000 0.000 16.440 3.100 2.500 1.000; 1.000 0.000 17.540 2.100 2.100 1.000; 1.000 1.000 16.810 1.900 2.600 1.000; 1.000 0.000 17.110 2.650 2.400 0.000; 1.000 1.000 16.520 2.000 2.300 0.000; 1.000 1.000 16.520 3.100 3.400 1.000; 1.000 0.000 16.320 3.300 2.800 0.500; 1.000 0.000 16.380 3.200 1.900 1.000; 1.000 0.000 16.570 2.800 2.000 0.000; 1.000 1.000 16.250 2.200 1.600 0.000; 1.000 1.000 16.820 2.900 2.600 1.000; 1.000 0.000 16.580 2.600 2.800 0.000; 1.000 1.000 16.730 2.850 3.150 0.000; 1.000 0.000 16.310 2.600 1.900 0.000; 1.000 1.000 17.010 1.700 2.400 0.000; 1.000 1.000 16.360 3.200 3.200 0.000; 1.000 1.000 16.490 2.400 1.525 0.000; 1.000 0.000 16.300 2.400 1.450 1.000; 1.000 0.000 16.060 2.200 1.300 0.000; 1.000 1.000 16.600 2.200 2.000 0.000; 1.000 0.000 16.720 3.300 2.500 0.000; 1.000 1.000 16.160 2.300 2.200 0.000; 1.000 1.000 16.140 2.800 1.850 0.000; 1.000 1.000 16.550 3.100 2.950 1.000; 1.000 1.000 17.300 3.450 2.700 1.000; 1.000 0.000 16.940 3.000 2.200 1.000; 1.000 1.000 16.550 2.700 2.850 0.000; 1.000 0.000 17.170 3.000 2.900 1.000; 1.000 0.000 17.150 2.800 2.450 0.000; 1.000 0.000 16.650 3.100 1.900 0.500; 1.000 0.000 16.070 2.700 2.900 1.000; 1.000 1.000 16.720 1.800 1.450 1.000; 1.000 0.000 16.150 2.900 1.000 0.000; 1.000 1.000 16.120 2.400 2.200 1.000; 1.000 1.000 17.540 2.600 2.600 0.000; 1.000 1.000 16.840 2.900 1.100 0.000; 1.000 1.000 15.790 3.100 1.600 1.000; 1.000 1.000 16.430 2.800 1.500 0.000; 1.000 0.000 16.390 3.300 2.700 1.000; 1.000 0.000 16.480 3.350 3.000 0.000; 1.000 1.000 16.930 3.000 1.000 0.000; 1.000 1.000 15.550 2.200 2.600 0.000; 1.000 1.000 17.080 2.900 1.500 0.000; 1.000 0.000 16.850 2.500 2.200 0.500; 1.000 1.000 16.700 2.200 1.800 0.000; 1.000 1.000 15.930 2.600 2.000 1.000; 1.000 1.000 16.080 2.600 1.200 0.500; 1.000 0.000 16.130 3.150 1.400 1.000; 1.000 1.000 16.250 3.100 1.400 1.000; 1.000 0.000 16.040 3.250 3.200 1.000; 1.000 0.000 16.040 3.500 2.900 1.000; 1.000 0.000 16.070 1.400 1.000 1.000; 1.000 0.000 16.550 3.200 2.300 1.000; 1.000 0.000 16.120 2.800 2.000 0.500; 1.000 1.000 16.450 3.150 1.400 1.000; 1.000 0.000 15.910 3.400 1.600 1.000; 1.000 1.000 15.700 3.000 2.400 1.000; Best, Lucy Lurie (she/her/hers) Doctoral Student, Clinical Psychology Department of Psychology and Neuroscience University of North Carolina at Chapel Hill CIRCLE Lab<https://secure-web.cisco.com/18i_Rf4fzTTcqPA2OQAm3_CnM6qhNKl6D-xG6RO1PJGAuL…>

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Freesurfer longitudinal stream error
by Susanne Gellißen 09 Jul '21

09 Jul '21

External Email - Use Caution Dear FreeSurfer Developers, I am processing MRI data using the freesurfer processing stream with two timepoints. I already executed the individual freesurfer-processing for each subject and timepoint and also the recon-all -base step. All finished without errors. When running the recon-all -long command, the processing stream exits at the same step in the script for all subjects and timepoints. I cannot identify a particular error message (ony at the end the script says exited with errors and no stats files are produced). I am using freesurfer 7.1.1 on an iMAc with macOS Catalina. Please find attached the recon-all log files for the longitudinal streams (2 folders with “long” in the foldername) as well as for the preparation steps. Thank you. --------------------------------------------------- PD Dr. med. Susanne Gellißen Department of Diagnostic and Interventional Neuroradiology University Medical Center Hamburg-Eppendorf Martinistraße 52, 20246 Hamburg E-mail: s.siemonsen(a)uke.de -- _____________________________________________________________________ Universitätsklinikum Hamburg-Eppendorf; Körperschaft des öffentlichen Rechts; Gerichtsstand: Hamburg | http://secure-web.cisco.com/1HvVVbdMRr6qAu-L5y0c3HUFOZFKnzwzd2mFmsc4xoj1PMv… Vorstandsmitglieder: Prof. Dr. Burkhard Göke (Vorsitzender), Joachim Prölß, Prof. Dr. Blanche Schwappach-Pignataro, Marya Verdel _____________________________________________________________________ SAVE PAPER - THINK BEFORE PRINTING

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Visualizing specific cortical parcels in Desikan Killiany atlas
by Ellen Ji 09 Jul '21

09 Jul '21

External Email - Use Caution Dear experts, I have a basic visualization question. I would like to create a surface brain figure with specific cortical parcels colored. Similar to https://secure-web.cisco.com/1DryTPj2WrD-LULa8TF6HVh2xwKTLAaWDFvIpAUrs4z6O2… but not with ALL parcels in the atlas selected. I know that I can go into a subject folder and load this freeview -f surf/lh.pial:annot=aparc.annot in order to see the entire Desikan Killiany atlas. However, I would like to select 4-5 rois. What's the best way to do this? It won't be related to any results and doesn't need to be from a particular subject's brain (can also be fsaverage). It's purely to highlight some cortical parcels for visualisation purposes. Thanks, Ellen

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Transformation Applied to T1.mgz during recon-all
by Alexander Rockhill 09 Jul '21

09 Jul '21

External Email - Use Caution -----BEGIN PGP SIGNED MESSAGE----- Hash: SHA256 Hello, I am trying to replicate the processing steps that occur between when a T1 is given as input to recon-all and the T1.mgz that is stored in the $SUBJECTS_DIR/$SUBJECT/mri directory for mne-bids and dealing with mne's internal dependency on the surface RAS coordinate frame. It is my impression that 1) the image is resampled to 256 x 256 x 256 and then 2) the image is reoriented to head-first supine aka LIA aka scanner space. But when I replicate these steps using nibabel, the affine is off by a rotation and translation: T1.mgz ------ [[ -1. , -0.00000015, -0.00000003, 132.77600098], [ 0.00000003, 0.00000001, 1. , -94.00223541], [ -0.00000002, -1.00000012, -0.00000001, 149.55487061], [ 0. , 0. , 0. , 1. ]] orig resampled and translated ----------------------------- [[ -0.99995208, -0.00905184, 0.00373623, 164.44344257], [ 0.00337327, 0.03978604, 0.99920255, -98.49012464], [ 0.00919327, -0.9991672 , 0.03975359, 141.93864847], [ 0. , 0. , 0. , 1. ]] orig to T1.mgz transform affine ------------------------------- [[ 0.99995203, -0.00337331, -0.00919312, -30.68693093], [ 0.0037362 , 0.99920251, 0.03975359, -1.8476189 ], [ 0.00905186, -0.03978605, 0.99916736, 2.32735433], [ 0. , 0. , 0. , 1. ]] Since there are off-diagonal entries in the last affine, I assume there is some kind of rotation, and since there are non-zero entries in the last column, I assume there is some kind of translation as well. I am not sure what either of those would be from so any advice or help would be appreciated. Alex Rockhill PhD Candidate University of Oregon -----BEGIN PGP SIGNATURE----- Version: BCPG v1.65 iQEcBAABCgAGBQJg4hyMAAoJEOCF7T6SI2rb0VcH/2S6Bs16Bg0hreKYLugx4H2e /gr6eZ06VQa/9+JJZSmX19/eRyQLMfnK823LfUoEl9XqU7HN2PVDi7/5h+cbrw77 2qofJU2r70lADXlP9H82kf90N4enym1Yqem+q1K02QQrNqgs9kjkolQ9npiCkOv7 gqnS6DKf0zWOvptxGErzSqZxQAsyIYV2VBIctWzcUa+Sr5l49hYWg67HTz4W0C1k iLUSXnL40jk6xCGbG56y3nv44O1jDyxWQZ+5mOaDK9wANu48Ym60akTnNXY8BktQ p8KVlzw6OVC2mT89ReXwYoMtUPUIqrpMpVXxdpifqhBPwOFj/ICiaMeE/J/bMKc= =ijvn -----END PGP SIGNATURE-----

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setwdelay error 1 weight
by Marilena Wilding 09 Jul '21

09 Jul '21

External Email - Use Caution Dear Freesurfers, for my FIR model I’d like to use the -setwdelay option in the mkcontrast-sess command. My command looks like this: mkcontrast-sess \ -analysis FIR_group_20-lh -contrast global-v-local \ -a 2 -c 1 \ -setwdelay When I run this the promt appears for the delay weights. But when I enter them, I always get an error: mkcontrast-sess -analysis FIR_group_20.lh -contrast global-v-local -a 2 -c 1 -setwdelay INFO: Found 2 Non-Null Conditions INFO: Found 29 Delays Condition Weights: -1.00000000000000000000 1.00000000000000000000 ################################### ### Enter 29 Delay Weights (Return) 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ERROR: entered 1 weights, needed 29 I'm entering 29 values (I want to include only the first seven TPs) but apparently only 1 value is detected. Could you please help me? I'm really out of ideas here. Thanks a lot in advance! Marilena

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What is the relationship between qdec results and aparc.stats?
by Satoko KINA 09 Jul '21

09 Jul '21

External Email - Use Caution Hello Freesurfer Developers, As a result of whole-brain analysis using qdec, specific regions with significant differences between the two groups were depicted (e.g., paracentral cortical thickness). Based on this result, we compared the paracentral region on the Desikan-killiany atlas from aparc.stats between the two groups, and found significant differences not only in CT but also in items rejected by qdec (e.g., curv). How should we interpret this result? Which result is more reliable? Can we consider the result of the analysis focused on a narrow region of each ROI as a more detailed result because qdec is a whole brain analysis? I am not familiar with statistics, so please forgive me if this is a misguided question. Thank you for help! Satoko

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