Freesurfer

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AABC Release 2 of more longitudinal HCP-Aging & AABC Data
by Jennifer Elam 28 Jan '26

28 Jan '26

External Email - Use Caution *AABC Release 2 of more longitudinal HCP-Aging & AABC Data * The Aging Adult Brain Connectome (AABC) consortium is pleased to announce its second release of imaging and non-imaging phenotypic data on the *ConnectomeDB powered by BALSA <https://secure-web.cisco.com/1XxcWoohRobuw1WSCh6edBdaGxyD_rp1GlemcFbF_8jlSX…>* platform. AABC Release 2 includes 632 additional sessions collected on participants from targeted groups newly recruited for AABC and more longitudinal visit data and followups (up to visit 4) from HCP-Aging (HCA) participants. It is inclusive of the previous AABC 1 Release. AABC is a longitudinal follow-on study to the HCA study of typically aging participants ages 36-90+. AABC has recruited ~950 participants (legacy HCA and new) for two additional longitudinal visits, collecting up to four timepoints per participant to generate within-participant brain trajectories over spans of up to 10 years, enabling examination of vulnerability and resilience factors related to cognitive decline. AABC Release 2 includes cross-sectional (V1) and longitudinal (V2, V3, V4) 3T MR scans and non-imaging phenotypic data from 1396 typically aging adults (ages 36-90+) in the *HCP-Aging* and *AABC* projects. This includes data for 1396 V1, 915 V2, 471 V3, and 96 V4 sessions (total = 2878). It includes preprocessed and unprocessed imaging data for all included modalities (structural, high-res hippocampal T2 [unprocessed only], resting state fMRI, task fMRI, diffusion, and ASL) from 1390 participants in 2789 imaging visits. It also contains non-imaging data collected over a broad range of domains at imaging visits and in remote follow up surveys (non-imaging events). See *session breakdowns by study and visit/event <https://secure-web.cisco.com/1Ofguj5c8lU0m74FZoyTK636BZvRWBKivB_ywzv82i4vra…>* . *Release 2 Highlights:* - Preprocessed and unprocessed structural MRI, resting state fMRI, task fMRI, diffusion MRI, ASL, and high-res hippocampal T2 [unprocessed only] data in modality-specific "HCP package" datasets downloadable from BALSA (see below). - Most users should access *Preprocessed Recommended *fMRI data that have been cleaned of spatially and temporally specific structured noise and precisely aligned across subjects by multimodal cortical surface registration (MSMAll) using HCP pipelines <https://secure-web.cisco.com/1aacJvW1mdHImrMoNlsjQrehkTIWQkvMzctNAfsV9nqCzE…> that have been developed specifically for HCP-style data. - 3T Multi-modal Imaging Derived Phenotypes (IDPs) for released participant sessions available in CSV (zip archives in IDPs tab) and Connectome Workbench-compatible CIFTI imaging package formats. - 7 T Magnetic Resonance Spectroscopy (MRS) brain metabolite data are available for 282 participant visits. - Non-imaging behavioral and biomeasure data available for released participant sessions and follow up events. - Core Variables, high interest primary variables and summary scores, including MRS brain metabolites, can be viewed and filtered in the BALSA UI (use Column Selector to add, Export CSV to download all Core Variables or selected subset). - >3,000 Extended (XL) variables, including item-level and follow up event variables, for all participant events available in a comprehensive spreadsheet. See Data Dictionary <https://secure-web.cisco.com/1w4WLQASL7dgUjowrLA8VjSQ7qcqVF_OOAecYbXSr4cxpd…> for descriptions of included variables. - NIH Toolbox raw and score data for in-person visits are available as spreadsheets/zip archive. - Visualization instructions and HCA1798 group average template data for visualizing HCP pipelines output, including IDPs, in Connectome Workbench wb_view. *Get Access and Download the data: *Get started by *Registering for BALSA <https://secure-web.cisco.com/1ABz6nrHeh7ZY5Ld4JgxvDpDxuqcrXwViuNH3SssZ7jJh8…>*, click on the “ConnectomeDB” tab, and agree to the AABC Data Use Terms. An academic, non-profit, or government email address is required to agree to the AABC Data Use Terms and access the data. To download imaging data, you must 1) install *Aspera Connect <https://secure-web.cisco.com/1p324dA-654tn2LU5RMwFk65I2EC6rLjVBaKSkVvXw-xBH…>* (*scroll down to “IBM Aspera client-deployed software” to find Aspera Connect download links*) and 2) an Aspera Connect plugin for your browser (available from Firefox, Chrome, Safari, etc.). Set Preferences>Transfers in Aspera Connect to a directory with sufficient space for large downloads. Use the Column Selector and Export CSV to view, filter on, and download all or subsets of Core Variables for selected subjects. To download the full non-imaging data, click the Files tab and Download under AABC_Release2_Non-imaging_Data-XL.csv. *Join the Community.* If you are actively using HCP data and tools, we encourage you to join and be active in the *HCP-Users Google group <https://secure-web.cisco.com/1j4HC4mBHaSeH8_MLgylhkjZx2ucjxd5dcQPzIN-bPYM-6…>*, so that you can tune in to technical discussions on issues that may be of interest. Once you have joined (posts from nonmembers are moderated to control spam), post questions to *hcp-users(a)humanconnectome.org <hcp-users(a)humanconnectome.org>*. *Share your Analyses.* As you work with AABC data and prepare your work for publication, we encourage you to use *Connectome Workbench <https://secure-web.cisco.com/1UksVOQxCxXN1PSTD8_iZe0FH8nhqNyabpAFfqrgZIUGzw…>* to prepare your figures as scenes and *upload your scenes as a BALSA dataset <https://secure-web.cisco.com/188H9BkiEI_P6I5P_y380WASXc34AB_Sd3NhkG0D6zxkkD…>* that can be linked from your publication. Don’t forget to cite the *HCA and AABC grants <https://secure-web.cisco.com/1RaBEYH46916aUctXV_85CuHdH1TMaqlcjbKYOvFi8x2ZQ…>* and *BALSA <https://secure-web.cisco.com/1Kt_PfcOWm9-dzMelOgh3-pR4S8ZnTQqKtnFPm3gsk8EMQ…>* in your manuscript! *Stay Tuned!* In coming months, we will be working on improvements to ConnectomeDB powered by BALSA to enable additional ways to transfer data via command line and other transfer services we are exploring. We will announce updates on the HCP-Users group! Best, AABC Consortium -- Jennifer Elam, Ph.D. Scientific Outreach, Human Connectome Project Washington University School of Medicine Department of Neuroscience 660 South Euclid Avenue St. Louis, MO 63110 elam(a)wustl.edu http://secure-web.cisco.com/1bLLYhhcdC_J57LMgAzFLkNi-KlCY6dxwIXHFcQbEgJ-ydM…

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Editing segmentation output from SuperSynth
by Paine, Isabel 28 Jan '26

28 Jan '26

External Email - Use Caution Hi, I am new to FreeSurfer and have been testing the new SuperSynth tool on ex vivo chimpanzee scans. The segmentation output is generally good, but the cerebellum white/gray matter is often mistaken as cerebral white/gray matter. How can I manually edit the segmentations and recalculate volumes? Thanks! Isabel -- *Isabel Paine *(she/her) Neuroscience PhD Candidate Hof Lab <https://secure-web.cisco.com/12vWcbyCY5P0ckWnU8cN-d7Qo7iUhB7t-1PwYJ7s4zFUK9…> Icahn School of Medicine at Mount Sinai

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Talairach transformation
by Serena Tang 27 Jan '26

27 Jan '26

External Email - Use Caution Hi there, I just had a question about the Talairach matrix calculated during the recon-all processing. Is that matrix calculated with an affine transformation? And how many DOF is default? I couldn't find information on it in talairach_avi or the other pages on the Talairach function. Also just to clarify, the talairach function doesn't convert to Talairach coordinates or some average of MNI and Talairach, but rather MNI specifically, is that correct? Thank you, Serena *---* *Serena Tang* *UC Berkeley / UCSF joint Bioengineering PhD Program* *serenatang(a)berkeley.edu <serenatang(a)berkeley.edu> | (201)-238-9861*

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Re: Bug Report: Typo in surfreg script (FreeSurfer 7.4.1)
by fsbuild 26 Jan '26

26 Jan '26

External Email - Use Caution A fix was made in 09/2024 and was subsequently in the Freesurfer 8.0.0 (02/2025) and 8.1.0 (07/2025) releases which you can download from,https://secure-web.cisco.com/1a_cLCaihbBr4j3zAtLN867XJeh4MYOVKCUkQ-FlY… R. On 1/23/26 03:34, Ben Sinclair (ben.sinclair(a)monash.edu) wrote:         External Email - Use Caution         Dear FreeSurfer Development Team, I'm reporting a typo in the surfreg command that causes registration operations to fail with an error, though the actual registration completes successfully. **Bug Details:** - File: /apps/freesurfer/7.4.1/freesurfer/bin/surfreg - Line: 107 - Current: set fsaorig = $FREESURFER/subjets/fsaverage/mri/orig.mgz - Should be: set fsaorig = $FREESURFER/subjects/fsaverage/mri/orig.mgz **Impact:** When running surfreg with the --no-annot flag (as recommended in the error messages for FreeSurfer 7.4.1), the command completes the registration successfully but then fails on the post-processing mris_convert step with: "error: mghRead(/apps/freesurfer/7.4.1/freesurfer/subjets/fsaverage/mri/orig.mgz, -1): could not open file" This causes the command to return a non-zero exit code even though the primary registration file (e.g., lh.fsaverage_sym.sphere.reg) is created correctly. **Reproduction:** surfreg --s <subject_id> --t fsaverage_sym --lh --no-annot **Version:** FreeSurfer 7.4.1 Thank you for your work on FreeSurfer. Please let me know if you need any additional information. Cheers Ben

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Stimulated-echo diffusion-MRI dataset
by Aganj, Iman 24 Jan '26

24 Jan '26

Dear all, I am pleased to introduce a new public dataset of human brain stimulated-echo diffusion-MRI images, which we recently acquired with a long diffusion time of 1 second at the Martinos Center, Massachusetts General Hospital. The dataset contains images from 10 healthy volunteers and an ex vivo brain hemisphere. MPRAGE T1 and standard diffusion-MRI images are also included. Data repository: https://www.nitrc.org/projects/ste Article describing the dataset (see Section 2.4.2): http://doi.org/10.1002/mrm.70258 Best regards, Iman Aganj

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Manual editing strategy for longitudinal pipeline (FS 8.0.0) following QC
by Keller, Lara 23 Jan '26

23 Jan '26

External Email - Use Caution Dear FreeSurfer Community, We are currently processing volumetric data from a longitudinal study (adolescent patients with anorexia nervosa vs. healthy controls, 2–3 time points) using FreeSurfer 8.0.0 and the standard longitudinal pipeline (recon-all -long <tpNid> <templateid> -all). We performed Quality Control (QC) directly on the longitudinal outputs, rating the segmentation for each region individually. Based on this QC, we identified several areas requiring manual correction due to significant overestimation. (We are aware that manual corrections should be reserved for cases with substantial segmentation inaccuracies....) According to the FreeSurfer documentation, manual edits should ideally be performed on the cross-sectional runs and the base template rather than the longitudinal files themselves. Upon inspecting our data, we observed a few conflicting points: * Cross-sectional and base accuracy: In many cases, the segmentation in the cross-sectional outputs and the base images actually appears more accurate than in the longitudinal outputs, despite the perceived higher resolution of the latter. * Lack of "Edit-Trigger": So, in several instances, the specific areas we flagged as problematic in the longitudinal output look fine in both the cross-sectional images and the base template. If there is nothing to "fix" in the earlier stages, re-running the longitudinal pipeline is unlikely to change the erroneous longitudinal output. This leaves us with a methodological dilemma: Our current QC (identifying errors) is based on the longitudinal output. If we shift to editing cross-sectional images, we would essentially need to redo the QC for those runs, even though they already appear superior to the final product. What is the recommended procedure in this case? Should we proceed with manual edits directly on the longitudinal outputs despite the documentation’s warnings? Any insights or recommendations on the best practice for this scenario would be greatly appreciated. Furthermore, we are questioning whether the application of a longitudinal pipeline is appropriate for our specific study population. Our sample includes adolescents undergoing normative neurodevelopmental processes, alongside patients with Anorexia Nervosa who exhibit significant brain volume reductions (approximately 5%) in the acute stage, followed by substantial recovery at follow-up. We are concerned that these pronounced morphological changes and the resulting high variance could potentially bias the creation of the within-subject base template, possibly affecting the accuracy of the longitudinal registration. Best regards, Lara

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mri_gtmpvc --rbv segmentation fault
by Finn, Quentin 22 Jan '26

22 Jan '26

External Email - Use Caution Freesurfer Experts, I am trying to run mri_gtmpvc with the --rbv option, but am unable to progress, I always get a simple error immediately upon running: Segmentation fault (core dumped) The command I am running is this: mri_gtmpvc --i FS_SPACE_pet.nii --reg-identity --psf 3.5 --no-rescale --seg ${SUBJECTS_DIR}/subject1/mri/gtmseg.mgz --default-seg-merge --auto-mask 1 .01 --o subject1_gtmpvcRBV.output --rbv Things I have tried: 1. If I remove the --rbv tag, the command runs as expected. 2. If I run with the --rbv-res option, I still receive the error, even if I set the voxel resolution to a huge value e.g. 8 or 16. 3. My local machine has 32gb of RAM. If I try to run the command on our HPC cluster, I get the same error even when requesting 128gb of memory and 8 threads, using --threads 8. I am running freesurfer-linux-centos7_x86_64-7.4.1-20230613-7eb8460 on RHEL 9. The HPC cluster may have a slightly different version but has the same behavior. Any thoughts on what I might be doing wrong here? Thanks so much! Houston Methodist. Leading Medicine. Houston Methodist Hospital has been named the Best Hospital in Texas for patient care and quality for the 14th year in a row by U.S. News & World Report. We are proud to be a top-ranked hospital in the country, and nationally ranked in 10 specialties. For more than 100 years, we have been honored to provide you with the highest quality care possible. That’s the difference between practicing medicine and leading it. For you. houstonmethodist.org<https://secure-web.cisco.com/1KTL7A4yEQ5clPW8oZVvsq9QYrOmDR-YQLqrx4-VSB3l6w…> x.com/MethodistHosp<https://secure-web.cisco.com/163MCj27y4cYACfAhgyJ_wYOBv5wLUh36rxTuuAh2HNdBx…> facebook.com/HoustonMethodist<https://secure-web.cisco.com/1WtFhEzwI7gPA7DJiQN5d3z6iprygJQ-FEn-Kw4R5WzhhO…> ***CONFIDENTIALITY NOTICE*** This e-mail is the property of Houston Methodist and/or its relevant affiliates and may contain restricted and privileged material for the sole use of the intended recipient(s). Any review, use, distribution or disclosure by others is strictly prohibited. If you are not the intended recipient (or authorized to receive for the recipient), please contact the sender and delete all copies of the message. Thank you.

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TRACULA error: Could not find thalamic nuclei segmentation despite present
by Simone Cauzzo 22 Jan '26

22 Jan '26

External Email - Use Caution Dear support I'm running the following command in Freesurfer 7.4: trac-all -nocorr -noqa -intra -tensor -inter -prior -debug -dontrun -c config_tracula.txt I get the following error ERROR: Could not find thalamic nuclei segmentation in /nfsd/biopetmri4/Users/CauzzoOPA/FS_RECON/subjOPAPD01/mri/ ERROR: Thalamic nuclei segmentation is strongly recommended to use ERROR: for tracts that terminate in or travel near the thalamus ERROR: If there is good reason not to use it, set usethalnuc = 0 And this happens despite in that folder there are these files: thal_t1_fl.FSspace.mgz thal_t1_fl.thalamus.t2.stripped.bfcorr.mgz thal_t1_fl.thalamus.t2.mgz ThalamicNuclei.v13.thal_t1_fl.FSvoxelSpace.mgz ThalamicNuclei.v13.thal_t1_fl.volumes.txt ThalamicNuclei.v13.thal_t1_fl.mgz then why isn't it finding the thalamic segmentation? I paste below the full output of the command Thank you ###################################### INFO: SUBJECTS_DIR is /nfsd/biopetmri4/Users/CauzzoOPA/FS_RECON INFO: Diffusion root is /nfsd/biopetmri4/Users/CauzzoOPA/prove/tracula/res Actual FREESURFER_HOME /nfsd/opt/FSL/freesurfer-7.4.0 trac-preproc -c /nfsd/biopetmri4/Users/CauzzoOPA/prove/tracula/res/subjOPAPD01/scripts/dmrirc.local -log /nfsd/biopetmri4/Users/CauzzoOPA/prove/tracula/res/subjOPAPD01/scripts/trac-all.log -cmd /nfsd/biopetmri4/Users/CauzzoOPA/prove/tracula/res/subjOPAPD01/scripts/trac-all.cmd -dontrun -debug INFO: -dontrun flag is in effect so subsequent commands may not have accurate arguments! #------------------------------------- /nfsd/opt/FSL/freesurfer-7.4.0//bin/trac-preproc #------------------------------------- #@# DWI set selection Thu Jan 22 11:38:27 CET 2026 ln -sf dwi.nii.gz /nfsd/biopetmri4/Users/CauzzoOPA/prove/tracula/res/subjOPAPD01/dmri/data.nii.gz ln -sf dwi.bvecs /nfsd/biopetmri4/Users/CauzzoOPA/prove/tracula/res/subjOPAPD01/dmri/bvecs ln -sf dwi.bvals /nfsd/biopetmri4/Users/CauzzoOPA/prove/tracula/res/subjOPAPD01/dmri/bvals #------------------------------------- #@# Intra-subject registration Thu Jan 22 11:38:27 CET 2026 bbregister --s subjOPAPD01 --init-fsl --dti --6 --mov /nfsd/biopetmri4/Users/CauzzoOPA/prove/tracula/res/subjOPAPD01/dmri/lowb.nii.gz --reg /nfsd/biopetmri4/Users/CauzzoOPA/prove/tracula/res/subjOPAPD01/dmri/xfms/diff2anatorig.bbr.lta lta_convert --inlta /nfsd/biopetmri4/Users/CauzzoOPA/prove/tracula/res/subjOPAPD01/dmri/xfms/diff2anatorig.bbr.lta --invert --outlta /nfsd/biopetmri4/Users/CauzzoOPA/prove/tracula/res/subjOPAPD01/dmri/xfms/anatorig2diff.bbr.lta mri_convert /nfsd/biopetmri4/Users/CauzzoOPA/FS_RECON/subjOPAPD01/mri/aparc+aseg.mgz /nfsd/biopetmri4/Users/CauzzoOPA/prove/tracula/res/subjOPAPD01/dlabel/anatorig/aparc+aseg.nii.gz mri_binarize --i /nfsd/biopetmri4/Users/CauzzoOPA/prove/tracula/res/subjOPAPD01/dlabel/anatorig/aparc+aseg.nii.gz --min .5 --dilate 4 --erode 2 --o /nfsd/biopetmri4/Users/CauzzoOPA/prove/tracula/res/subjOPAPD01/dlabel/anatorig/aparc+aseg_mask.nii.gz ERROR: Could not find thalamic nuclei segmentation in /nfsd/biopetmri4/Users/CauzzoOPA/FS_RECON/subjOPAPD01/mri/ ERROR: Thalamic nuclei segmentation is strongly recommended to use ERROR: for tracts that terminate in or travel near the thalamus ERROR: If there is good reason not to use it, set usethalnuc = 0 ################################################ Simone Cauzzo

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Postdoc position at MGH: Brainstem neuroimaging in Alzheimer's disease
by Jacobs, Heidi I.,PHD 20 Jan '26

20 Jan '26

The Athinoula A. Martinos Center for Biomedical Imaging, located within the Department of Radiology at Massachusetts General Hospital (MGH) and Harvard Medical School (HMS) in Boston, Massachusetts, has an opening for a highly qualified postdoctoral individual to work with Dr. Heidi Jacobs. The Jacobs lab is focused on improving the early detection and early treatment of Alzheimer’s disease. The lab focuses on the neuromodulatory subcortical nuclei, in particular the locus coeruleus, using a variety of approaches, including 7T MRI, PET imaging, pupil measurements, physiological recording, blood-based markers, cognitive assessments and non-invasive vagus nerve stimulation. This project is focused on the functional balance between the brainstem and cortex in relation to pathological changes in preclinical Alzheimer’s disease. This project will require combining fMRI and PET-data from existing datasets with computational modeling approaches. The Jacobs Lab consists of a multidisciplinary team of two instructors, four postdocs, two PhD-students, two clinical research coordinators and one project manager. The work in this project will be performed at the Athinoula A. Martinos Center for Biomedical Imaging, Charlestown Navy Yard. The candidate will be part of ongoing collaborations and work in a stimulating and inspiring environment. Our research group values open communication, motivation, optimism, mutual respect, teamwork, and innovative thinking. Dr. Jacobs is highly committed to individualized mentoring to help trainees achieve the most out of their postdoctoral candidature and to move forward in their career. At a minimum, the training environment will include professional development, one-on-one meetings, group lab meetings, frequent seminars and journal clubs, opportunities to present their work at national and international scientific conferences (i.e. Human Amyloid Imaging, Alzheimer’s Association International Conference), collaborations with partners within and outside MGH, and manuscript preparation for publication in high-impact journals. In addition, Dr. Jacobs has a strong funding record and will strongly encourage and provide mentorship in grant applications. Requirements: Candidates should hold a Ph.D. in Cognitive Neuroscience, Computational Neuroscience, bio/medical physics, Neuroimaging, Psychology (Biological), or a related discipline. Strong analytical, quantitative, and programming skills, along with experience in complex fMRI modeling, are essential, as is the ability to relate neuroimaging findings within a pathobiological framework of neurodegenerative diseases. The candidate should be highly motivated, a strong communicator, possess internal drive to learn independently, but also be comfortable with working as part of a larger collaborative team. A real necessity is a passion for science, strong scientific writing and organizational skills, and a positive attitude. Experience in Alzheimer’s disease or aging research would be beneficial. Apply: The successful candidate will have joint appointments at MGH and HMS. If interested, please send your CV, letter describing interests, background, major achievements, skills, goals and contact information for three professional references. Please send application materials to Dr. Heidi Jacobs, Associate Professor of Radiology, at hjacobs(a)mgh.harvard.edu<mailto:hjacobs@mgh.harvard.edu> ___________________________________________ Heidi Jacobs, PhD Associate Professor of Radiology Massachusetts General Hospital | Harvard Medical School Department of Radiology Athinoula A. Martinos Center for Biomedical Imaging 149 13th Street Charlestown, MA 02129 hjacobs(a)mgh.harvard.edu www.heidijacobs.org<http://www.heidijacobs.org> Learn about what we do and why: https://shorturl.at/fEFa8 [A blue and black logo Description automatically generated] [signature_3581815700] Social media: Linkedin: https://www.linkedin.com/in/heidijacobs/ Bluesky: https://bsky.app/profile/heidijacobslab.bsky.social [Please note: I might send an email out of office hours, at weekends or during holidays. This suits me – but doesn’t mean I expect you to do the same]

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Re: mri_cc segmentation fault: Possibly due to M5 silicon incompatibility?
by fsbuild 19 Jan '26

19 Jan '26

External Email - Use Caution I’m not sure where the output comes from listing Freesurfer 5.3.0 in your previous email.  The recon-log seems to indicate you are actually running 8.1.0. But I do not expect Freesurfer 5.3.0 Intel binaries to run under the Rosetta emulation environment on a silicon Mac.  Even if it does run, since the M5 Mac OS and CPU architecture are different, your floating point results for any subject would likely not match results from any previous runs on an Intel processor. Before setting up the Freesurfer environment, I would explicitly run the bash shell,  $ bash$ export FREESURFER_HOME=/Applications/freesurfer/8.1.0$ source $FREESURFER_HOME/SetUpFreeSurfer.sh I would then copy any subject data you want to process into a directory like your home ($HOME) where you do not need any special permission to write to (see below).  The idea is to not modify the Freesurfer distribution by placing your own subject data there. $ cd… you are now in your home directory denoted by $HOME ...$ mkdir subjects$ cd subjects…. copy in subject data you want to process .. $ export SUBJECTS_DIR=$HOME/subjects$ ls $SUBEJCTS_DIR… you should see your data … Processing T1 and/or large images may not work on the silicon Mac unless you have at least 32G of physical RAM on the machine.  Even then it may not work because changes to the recon-all pipeline commands include python code which may require more (virtual) RAM than the memory management can handle.   The recon-all log says 22G of RAM are in use and there 1.5G of RAM free.  I’m assuming you are not running any other apps that cache data in RAM, browsers, etc. A workaround for this is to tell recon-all to revert back to the previous version of some pipeline commands by setting the environment variable FS_V8_XOPTS=0 on the recon-all command line, $ export FS_V8_XOPTS=0 && recon-all -i T1.nii.gz -s Pt01 -maskbfs -all The downside to this is the recon-all command will take longer to finish. Finally, if you continue to run into errors, you could try downloading and installing a current development build from,https://secure-web.cisco.com/14KJLuygmcYT1tDR1pvEv7VcSpwbhj7rIiogbQnrS… Please keep in mind we do not recommend development builds for long term/ongoing work since they may be unstable. So to summarize ..1) try using the bash shell to run commands (and set SUBJECTS_DIR differently)2) see if a recon-all can complete using export FS_V8_XOPTS=0 && recon-all …3) if the above does not resolve your errors, try a more recent development build - R. On Jan 17, 2026, at 12:47, Ajay Peddada <ajay.peddada(a)gmail.com> wrote:

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