Freesurfer March 2022

freesurfer@nmr.mgh.harvard.edu

86 participants
124 discussions

mri_segment_hypothalamic_subunits error: Illegal instruction 4
by Alice Tao 27 Mar '22

27 Mar '22

External Email - Use Caution Hello FreeSurfer Developers, I'm attempting to use the mri_segment_hypothalamic_subunits tool on subjects that have been analyzed with recon-all as described on the wiki page (https://secure-web.cisco.com/1pXzYS0fndek4-BNAZ4GmvKEawRrGwFtSNJa-z80qhPYpZ…) but I received the following error when I run the mri_segment_hypothalamic_subunits command (mri_segment_hypothalamic_subunits--s): Illegal instruction: 4 Does anyone have any suggestions on how to trouble-shoot this problem? recon-all does not seem to have any issues. 1) FreeSurfer version: freesurfer-darwin-macOS-7.2.0-20210713-aa8f76b 2) Platform: macOS Monterey, version 12.2.1 Thank you! Alice

3 3

qdec analysis error
by David 27 Mar '22

27 Mar '22

External Email - Use Caution Hello FreeSurfer Developers, I have a problem. Can you help me freesurfer version : 6.0.0 Load qdec when I run qdec.table.dat, the data is loaded correctly, but when I design, I choose discrete and continuous factors for analysis The error log is as follows ： ———————————————— Input table: /media/root/Backup_Plus2/new/RECON/qdec/qdec5.table.dat Subj#, SubjID, Data... 1 bd1 d Male 15.000000 8.000000 2 bd2 d Female 19.000000 13.000000 3 bd3 d Male 25.000000 9.000000 4 bd4 d Male 17.000000 12.000000 5 bd5 d Male 16.000000 10.000000 6 bd6 m Female 22.000000 12.000000 7 bd7 d Male 17.000000 11.000000 8 bd8 d Female 19.000000 13.000000 9 bd9 m Female 26.000000 7.000000 10 bd10 m Male 53.000000 15.000000 11 bd11 m Female 56.000000 4.000000 12 bd12 d Female 21.000000 14.000000 13 bd13 m Female 19.000000 12.000000 14 bd14 m Female 32.000000 15.000000 15 bd15 d Male 21.000000 9.000000 16 bd16 d Male 16.000000 10.000000 17 bd17 d Male 15.000000 11.000000 18 bd18 d Female 32.000000 10.000000 19 bd19 d Female 20.000000 15.000000 20 bd20 d Female 17.000000 11.000000 21 bd22 m Male 22.000000 11.000000 22 bd23 m Female 28.000000 6.000000 23 bd24 d Male 26.000000 11.000000 24 bd25 m Female 24.000000 9.000000 25 bd26 m Female 30.000000 6.000000 26 bd27 m Female 20.000000 12.000000 27 bd28 d Female 28.000000 16.000000 28 bd29 m Female 18.000000 12.000000 29 bd30 d Male 21.000000 15.000000 30 bd31 d Female 30.000000 16.000000 31 bd32 d Male 18.000000 11.000000 32 bd33 d Female 16.000000 10.000000 33 bd34 d Male 21.000000 11.000000 34 bd35 d Female 15.000000 10.000000 35 bd36 d Female 16.000000 10.000000 36 bd37 d Male 19.000000 14.000000 37 bd39 d Male 16.000000 10.000000 38 bd40 m Female 20.000000 14.000000 39 bd41 m Female 21.000000 15.000000 40 bd42 d Male 23.000000 9.000000 41 bd43 m Male 27.000000 9.000000 42 bd44 d Female 15.000000 8.000000 43 bd45 m Male 19.000000 9.000000 44 bd46 d Female 16.000000 11.000000 45 bd47 m Female 23.000000 15.000000 46 bd48 m Male 18.000000 13.000000 47 bd49 d Female 22.000000 15.000000 48 bd50 d Female 17.000000 11.000000 49 bd51 d Male 17.000000 10.000000 50 bd52 d Male 27.000000 15.000000 51 bd53 m Male 16.000000 9.000000 52 bd54 d Male 18.000000 12.000000 53 bd55 d Female 18.000000 11.000000 54 bd56 m Female 16.000000 10.000000 55 bd57 d Male 16.000000 9.000000 56 bd58 m Male 22.000000 9.000000 57 bd59 m Male 16.000000 8.000000 58 bd60 d Male 16.000000 9.000000 59 bd61 m Female 18.000000 10.000000 60 bd62 d Female 15.000000 9.000000 61 hc1 h Male 52.000000 7.000000 62 hc2 h Female 24.000000 10.000000 63 hc3 h Male 45.000000 7.000000 64 hc4 h Female 18.000000 13.000000 65 hc5 h Female 19.000000 10.000000 66 hc6 h Female 17.000000 12.000000 67 hc7 h Female 19.000000 7.000000 68 hc8 h Male 48.000000 5.000000 69 hc9 h Female 53.000000 6.000000 70 hc10 h Female 52.000000 15.000000 71 hc11 h Female 19.000000 12.000000 72 hc12 h Female 18.000000 12.000000 73 hc13 h Female 20.000000 12.000000 74 hc14 h Female 18.000000 12.000000 75 hc15 h Female 19.000000 13.000000 76 hc16 h Female 18.000000 11.000000 77 hc17 h Female 19.000000 12.000000 78 hc18 h Female 19.000000 12.000000 79 hc19 h Female 19.000000 12.000000 80 hc20 h Female 19.000000 12.000000 81 hc21 h Female 18.000000 12.000000 82 hc22 h Female 18.000000 12.000000 83 hc23 h Female 18.000000 11.000000 84 hc24 h Female 18.000000 12.000000 85 hc25 h Female 18.000000 12.000000 86 hc26 h Female 18.000000 11.000000 87 hc27 h Female 18.000000 12.000000 88 hc28 h Female 18.000000 12.000000 89 hc29 h Female 18.000000 11.000000 90 hc30 h Male 20.000000 12.000000 91 hc31 h Female 29.000000 17.000000 92 hc32 h Female 16.000000 10.000000 93 hc33 h Female 17.000000 10.000000 94 hc34 h Female 26.000000 14.000000 95 hc35 h Female 24.000000 17.000000 96 hc36 h Female 22.000000 17.000000 97 hc37 h Male 25.000000 17.000000 98 hc38 h Male 24.000000 17.000000 99 hc39 h Male 25.000000 17.000000 1 groups discrete 3 1 d 2 m 3 h 2 gender discrete 2 1 Male 2 Female 3 age continuous 0 4 edu continuous 0 Continuous Factors: Mean: StdDev: ------------------- ----- ------- age 22.293 9.015 edu 11.374 2.827 Number of subjects: 99 Number of factors: 4 (2 discrete, 2 continuous) Number of classes: 6 Number of regressors: 18 ============================================================ Data table loading completed successfully. SUBJECTS_DIR is '/media/root/Backup_Plus2/new/RECON' ERROR: QdecGlmDesign::GenerateContrasts: factor 1 must have 2 levels ninputs = 99 Checking inputs nframestot = 99 Allocing output Done allocing nframes = 99 Writing to /media/root/Backup_Plus2/new/RECON/qdec/Untitled/y.mgh gdfRead(): reading /media/root/Backup_Plus2/new/RECON/qdec/Untitled/qdec.fsgd INFO: DeMeanFlag keyword not found, DeMeaning will NOT be done. Continuous Variable Means (all subjects) 0 age 22.2929 8.96937 1 edu 11.3737 2.81262 Class Means of each Continuous Variable 1 groupsd-genderMale 19.0000 10.8000 2 groupsm-genderMale 24.1250 10.3750 3 groupsh-genderMale 34.1429 11.7143 4 groupsd-genderFemale 19.7647 11.9412 5 groupsm-genderFemale 24.8667 10.6000 6 groupsh-genderFemale 21.4375 11.9688 INFO: gd2mtx_method is dods Reading source surface /media/root/Backup_Plus2/new/RECON/fsaverage/surf/lh.white ERROR: no contrasts specified. Error in Analyze: command failed: mri_glmfit --y /media/root/Backup_Plus2/new/RECON/qdec/Untitled/y.mgh --fsgd /media/root/Backup_Plus2/new/RECON/qdec/Untitled/qdec.fsgd dods --glmdir /media/root/Backup_Plus2/new/RECON/qdec/Untitled --surf fsaverage lh --label /media/root/Backup_Plus2/new/RECON/fsaverage/label/lh.aparc.label —————————————————————————————————————————— I checked the description of .levels on the official website. I can use many categorical factors, but the error message is ERROR: QdecGlmDesign::GenerateContrasts: factor 1 must have 2 levels https://secure-web.cisco.com/1kUfsJNAvGVt8tBXKDcJYuIUu4h1wAq2TNCeY2z4M_AAER… Can I use many categorical factors If I can, how can I solve this mistake

2 1

Negative eTIV
by lqcheng2017 27 Mar '22

27 Mar '22

2 1

Freesurfer mri_convert
by Zoe O'Brien-Moran 27 Mar '22

27 Mar '22

External Email - Use Caution Dear FS Experts I am having continued issues with the mri_normalize function on MPRAGE data I get an error message: 3d normalization pass 1 of 2 error: No such file or directory error: MRInormFindControlPoints: could not find enough control points error: No such file or directory error: MRInormFindControlPoints failed Can you advise on any reason this may be happening?

2 1

Permission denied error from -localGI
by Billah, Tashrif 27 Mar '22

27 Mar '22

It does not exist and cannot be created in a shared cluster. Is there a way to define a different folder for /scratch/tp24093955057547375.load_mgh.m.mgh? =============== Douglas N. Greve Wed, 09 Mar 2022 10:04:31 -0800 Do you have permission to /scratch? Does it exist? =============== Billah, Tashrif Wed, 02 Mar 2022 06:50:41 -0800 Hi all, We are trying to run recon-all with -localGI but running into an unknown permission denied error: $ recon-all -s sub-1001 -localGI ``` make_outer_surface('/path/to/FS_SUBJECTS_DIR/sub-1001/surf/tmp-mris_compute_lgi-lh.pial/lh.pial.filled.mgz',15,'/path/to/FS_SUBJECTS_DIR/sub-1001/surf/tmp-mris_compute_lgi-lh.pial/lh.pial-outer'); exit ================= < M A T L A B (R) > Copyright 1984-2017 The MathWorks, Inc. R2017a (9.2.0.556344) 64-bit (glnxa64) March 27, 2017 >> reading filled volume... /bin/bash: /scratch/tp24093955057547375.load_mgh.m.mgh: Permission denied ERROR: could not open /scratch/tp24093955057547375.load_mgh.m.mgh for reading ERROR: loading /path/to/FS_SUBJECTS_DIR/sub-1001/surf/tmp-mris_compute_lgi-lh.pial/lh.pial.filled.mgz as MGH Struct contents reference from a non-struct array object. Error in make_outer_surface (line 25) volume=vol.vol; >> ERROR: make_outer_surface did not create output file '/path/to/FS_SUBJECTS_DIR/sub-1001/surf/tmp-mris_compute_lgi-lh.pial/lh.pial-outer'! recon-all -s sub-1001 exited with ERRORS at Wed Mar 2 09:02:21 EST 2022 ``` Our MATLAB environment is properly setup and we regularly run other FreeSurfer-MATLAB commands. So I do not think that is causing the issue. Best, Tashrif

2 1

vertexwise correlation between the two maps and atlases in volume (MNI) to surface
by stdp82＠virgilio.it 27 Mar '22

27 Mar '22

External Email - Use Caution Hi list, a) I have two maps, one's of rs-fMRI functional connectivity (by FS-FAST) and one's of receptor density (from a PET-Atlas). Both the maps are in surface space. How can I measure the vertexwise correlation between the two maps? b) How can I move some atlases in volume (MNI) to surface? I have tried to use: mri_vol2surf --src ATLAS_vol.nii --regheader fsaverage --projfrac 0.5 --hemi lh --out ATLAS_surface.nii but the results are inconsistent. Thanks Stefano

2 1

Turning Significant Cluster (sig.cluster.summary or sig.mgh) into binary .nii ROI
by Emily Popa 27 Mar '22

27 Mar '22

External Email - Use Caution Hello, I have been struggling to figure out a way to get the significant results of a freesurfer group analysis (just one significant cluster) from either the sig.cluster.summary or sig.mgh file into a binarized ROI in .nii format. I used mri_glmfit to perform the cortical thickness analysis on sMRI data and found the significant cluster only in the left hemisphere. I tried to follow some instructions I found on the FreeSurfer site, however, at the first step/line below (mri_volsynth) the –delta-crsf input was referred to on the site as the vertex number, but on the –help documentation, it was specified that this input should be: col row slice frame : 0-based. Looking at the cluster summary file, for the significant cluster there is a maximum vertex, but I am not sure if this is the vertex number I should be using. mri_volsynth --template $SUBJECTS_DIR/fsaverage/surf/lh.thickness --pdf delta --delta-crsf 5 9 5 1 --o delta.sm00.mgh mris_fwhm --smooth-only --subject fsaverage --hemi lh --i delta.sm00.mgh --niters 10 --o delta.sm10.mgh mri_binarize --i delta.sm10.mgh --min 10e-5 --o delta.sm10.bin.mgh When trying the first line above for mri_volsynth, I get this error: Segmentation fault: 11 (so I think my input –deta-crsf is likely wrong). If there is a better way to convert this ROI to a mask, please let me know! To give additional context, I am hoping to get a binary mask of this ROI that I can use as a mask for an ASL analysis in FSL (to limit the analysis to this ROI). I plan to do this by registering the binary ROI mask to the FSL standard group template (by using the transformation matrix from registering the fsaverage template to FSL’s standard group template first), and then getting the ROI mask from FSL’s group template space into native ASL space. If this plan sounds reasonable to you, it would also be very helpful to know. I really appreciate your time and help and look forward to hearing back! Best, Emily S. Popa, M.S. Staff Research Associate II, Neuroimaging Pacific Brain Health Center | Pacific Neuroscience Institute Foundation | Providence Saint John’s Health Center 1301 20th St. #250 Santa Monica, CA. 90404 (408) 750-7971 (M) [cid3519*image001.jpg(a)01D7EC78.96AA1AC0]<https://secure-web.cisco.com/1hLjiH2EMqrNb1Aj_EN8nMGnwBm1r3goPYCE5vd4lR-hGE…> [cid3519*image002.jpg(a)01D7EC78.96AA1AC0] <https://secure-web.cisco.com/11wThjE0wBKB7uH7Mdk8M0tt4s97K_cFB0xuOQfaRwID0m…> [cid3519*image003.jpg(a)01D7EC78.96AA1AC0] <https://secure-web.cisco.com/1oGIwvc1noJjNXOvlfvxCGrBAHvKAjS0PHn5htsutbjwTJ…> [cid3519*image004.jpg(a)01D7EC78.96AA1AC0] <https://secure-web.cisco.com/1cMaCmazMIVCk8v3EhpuiTkZaPsebaExskfX49kF6WWp7P…> [cid3519*image005.jpg(a)01D7EC78.96AA1AC0] <https://secure-web.cisco.com/17e7d2R-5gmmayIc-Okzb6HMA5_U4NT4cVQtWz_nLOjiv5…>

2 2

Question about calculation of pial area in DKatlas
by Dongyue Zhou 26 Mar '22

26 Mar '22

External Email - Use Caution Dear FreeSurfer experts: I want to calculate mean pial surface area in DKatlas in individual space.And I know the function read_annotation.m in $FREESURFER_HOME/matlab for loading this atlas.And if I can load sub/surf/?h.area.pial as the area in each vertice and calculate mean pial area by dividing sum PSA of all vertices in one ROI by the number of vertices in this ROI?But why my result is not the same as result in sub/stats/?h.aparc.stats ? Does the column named surface area represent mean PSA in each ROI?Bests,Dongyue

2 1

fMRI-EEG Postdoctoral Position at Albert Einstein COM in NYC
by Mark Wagshul 25 Mar '22

25 Mar '22

External Email - Use Caution Drs. Elyse Sussman and Mark Wagshul, of the Departments of Neuroscience and Radiology at the Albert Einstein College of Medicine in NY, are seeking a full-time postdoctoral research associate to work on an NIH-funded project exploring the neural bases of chemotherapy-induced cognitive deficits in survivors of childhood leukemia. The project uses EEG- and fMRI-based measures of cognitive function to understand the treatment-related deficits in children ages 5-12 years. The position is available starting May 2022; the position is for the duration of the project (March 2025), renewed annually based on performance and funding. Our lab combines advanced event-related potential EEG and functional MRI brain imaging methods to understand cognitive function, and how it is impacted by treatment for cancer. In particular, we use EEG- and MRI-based measures of cognitive tasks to study brain pathways affected by cancer treatment, comparing these measures with standard neuropsychological testing. By combining the superior temporal resolution of EEG with the millimeter spatial resolution of fMRI, along with advanced techniques for extracting effective connectivity (e.g. neural dynamics and causality), we aim to identify the specific cognitive domains and related brain pathways altered by cancer treatment. These studies will ultimately lead to objective measures of brain function which can drive development of better therapy modalities which do not impact cognitive skills in the way that current therapies do. Successful candidates for the position will have a PhD in physics, biomedical engineering, neuroscience or a related discipline, a strong background in either cognitive neuroscience or MRI physics, expertise in image and EEG data processing, as well as data and statistical analysis. Programming experience should include the commonly used packages for image and EEG processing, such as C++, Matlab, and FSL. The candidate should have significant experience in EEG/ERP data collection and analysis methods and/or imaging in a clinical setting and a strong background in the development and/or application of novel methods for human brain imaging, such as DTI/fMRI/structural MRI data analyses. Candidates with experience only in EEG-based or fMRI-based methods will be considered. The candidate will allocate time to both the EEG and MRI labs. Prior experience with auditory-based ERP/fMRI is not necessary, but candidates with such experience will be given preference. A strong work ethic, excellent organizational and communication skills, and ability to work independently is expected. Previous experience working with children in a research setting is a plus. The candidate will be expected to be involved in all aspects of the project, including EEG, image and data analysis, statistical analysis, as well as interfacing with the clinical team. Competitive salary and benefits will be offered based on qualifications. The Gruss MRRC is located on the main campus of the Albert Einstein College of Medicine in Bronx, NY. The Center has a multinuclear 3.0 Tesla Whole Body Philips Elition human system, along with on-site support from a Philips Clinical Scientist, and a 9.4 T Direct Drive Varian animal system. Image processing facilities including a computing cluster, multiple Linux workstations and PCs with imaging and general software installed. Please visit our website for more details (http://secure-web.cisco.com/1pGDF8ABU3mUM3q0mm1bnhU-FyjF46OfHfxWPLuYsMKf3FT…) The Albert Einstein College of Medicine is a leading academic institution, with over $170M in NIH funding. The candidate will have access to state-of-the-art brain imaging (MRI, EEG) and computing facilities. Einstein is one of the nation's premier institutions for medical education, basic research, and clinical investigation. It is home to some 2,000 faculty members, 750 M.D. students, 350 Ph.D. students attending the Sue Golding Graduate Division - including 125 in the combined M.D./Ph.D. program - and 325 postdoctoral investigators training at our Belfer Institute for Advanced Biomedical Studies. More than 7,000 Einstein alumni are among the nation's foremost clinicians, biomedical scientists, and medical educators. Interested candidates should send their CV, a brief statement of their research interests and career goals, and the names and phone numbers of three references to Mark Wagshul (mark.wagshul(a)einsteinmed.edu<mailto:mark.wagshul@einsteinmed.edu>) or Elyse Sussman (elyse.sussman(a)einsteinmed.edu<mailto:elyse.sussman@einsteinmed.edu>). Review of applications will begin immediately and continue until the position is filled. Mark ____________________ Mark Wagshul, PhD Associate Professor Gruss Magnetic Resonance Research Center Albert Einstein College of Medicine Bronx, NY 10461 Ph: 718-430-4011 FAX: 718-430-3399 Email: mark.wagshul(a)einsteinmed.org<mailto:mark.wagshul@einsteinmed.org> [einstein-logo-rgb] This email message and any accompanying attachments may contain privileged information intended only for the named recipient(s). If you are not the intended recipient(s), you are hereby notified that the dissemination, distribution, and or copying of this message is strictly prohibited. If you receive this message in error, or are not the named recipient(s), please notify the sender at the email address above, delete this email from your computer, and destroy any copies in any form immediately.

1 0

Curvature differences between 7T and 3T images
by Samuel Paré 24 Mar '22

24 Mar '22

External Email - Use Caution Hello, We are looking at some of our data acquired on a 7T magnet. We ran recon-all with the “highres” flag. The obtained results for cortical thickness and cortical volume are very comparable to data that we obtain when using 3 T brain images. However, the results for cortical curvature are significantly different from what we get by our 3 T data. I attach the output of mean cortical curvature values using the Destrieux atlas for a 3T and 7T dataset on healthy controls. As you can notice, they differ roughly by a factor of 2. Any explanation for what may cause this large difference? Thanks, Samuel [image: image.png] -- *Samuel Paré, MSc* Laboratoire du développement et plasticité du système visuel École d'optométrie Université de Montréal

1 0

← Newer
1
2
3
4
5
6
7
8
...
13
Older →

2026

2025

2024

2023

2022

2021

2020

2019

2018

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

Freesurfer March 2022