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30132 discussions

web page library to show freesurfer data (mesh and axial, coronal, sagital slices)
by Gonzalo Rojas Costa 10 Apr '19

10 Apr '19

External Email - Use Caution Hi: Do you know any library to show freesurfer data (mesh and axial, coronal, sagittal slices) embedded a web page? Sincerely, Gonzalo Rojas Costa

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regions of Yeo 17 networks in fast
by stdp82＠virgilio.it 10 Apr '19

10 Apr '19

External Email - Use Caution Hi list, I'd like to use the regions included in Yeo 17 networks (https://github.com/ThomasYeoLab/CBIG/tree/master/stable_projects/brain_parc…) in FS-FAST. Which is the command line to be used to create a segmentation in $SUBJECTS_DIR/$subject/mri in the same format as aseg.mgz? (I'd like to use it to run fcseed-config, specify -seg yourseg.mgz -segid). Thanks Stefano

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Image Analyst Position at the Yale Alzheimer's Disease Research Unit
by Adam Mecca 10 Apr '19

10 Apr '19

External Email - Use Caution The Yale University Alzheimer’s Disease Research Unit at Yale University School of Medicine has an opening for a highly qualified and motivated individual to work on research involving the development of analysis techniques integrating human imaging data including PET and fMRI for NIH-funded studies and clinical trials in Alzheimer’s disease. Applicants must have obtained a Master’s Degree or a Bachelor’s Degree with significant experience in neuroimaging analysis. Qualifications: Strong analytical, and programming skills are essential. Experience in fMRI, image analysis, algorithm development, and biological applications is highly desirable. The selected candidate will work under the direction of Drs. Christopher van Dyck and Adam Mecca. The successful candidate should have a Master’s Degree or a Bachelor’s Degree with at least three years of experience in fMRI and/or PET imaging. Application Instructions: Interested individuals should email a CV to adam.mecca(a)yale.edu. Adam Mecca, M.D. Ph.D. Yale School of Medicine, Department of Psychiatry Geriatric Psychiatry and the Alzheimer's Disease Research Unit Tel: (203) 764-8100 Fax: (203) 764-8111

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freesurfer longitudinal issue
by maxime GUILLAUME 10 Apr '19

10 Apr '19

External Email - Use Caution Dear freesurfer experts, I am performing a longitudinal study (2 time points, 1 year apart) in patients with Multiple Sclerosis using freesurfer 6.0. After following the tutorial for the CROSS, the BASE (where I only performed few manual edits of the surfaces) and the LONG steps, I am facing a problem with the results of the longitudinal pipeline: If I overlay the final surfaces of the different time points (the white and pial surfaces of the LONG step) on the BASE template, there are major differences between the two time points (see figure attached). This happened only on a subset of my subjects. One of our collaborators in this study suggested that this might be because the patient was positioned differently in the two time points, in particular with respect to the z axis (and indeed the major differences between the two surfaces are in the topmost area of the brain). Does anybody have experienced the same problem? And how can I correct for it? Thank you in advance for your help. (*in the capture surfaces of the first visit are in yellow and in green for the second visit)

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Creating anatomical ROI's
by Daniel Callow 09 Apr '19

09 Apr '19

External Email - Use Caution Hello, I am trying to create ROI volumes from the hippocampal subfields I get from mri_vol2vol --mov /Volumes/DANIEL/dti_freesurf/dtrecon/${cond}.${subj}/lowb.nii.gz --targ /Volumes/DANIEL/dti_freesurf/diffusion_recons/${subj}.${cond}/mri/lh.hippoAmygLabels-T1.long.v21.HBT.FSvoxelSpace.mgz --inv --interp nearest --o /Volumes/DANIEL/dti_freesurf/dtrecon/${cond}.${subj}/lhipp2diff.nii.gz --reg /Volumes/DANIEL/dti_freesurf/dtrecon/${cond}.${subj}/register.dat --no-save-reg so that I can merge specific hippocampal subfields I want together into a single ROI (like --id 231 and --id 232). However, when looking through the freesurfer options like mri_vol2vol there isn't an option to index to specific segments of the lh.hippoAmygLabels-T1.long.v21.HBT.FSvoxelSpace.mgz volume I have converted into dti space. My plan is to combine the head and body segments and extract average diffusion information from the combined mask. Anything that can help get me in the right direction would be greatly appreciated! *Daniel Callow* *PhD Student, Neuroscience and Cognitive Science* Exercise for Brain Health Lab University of Maryland, College Park *ddcc2442(a)gmail.com <ddcc2442(a)gmail.com>* 443-254-6298

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Post-doctoral Research Position at the Yale Alzheimer's Disease Research Unit
by Adam Mecca 09 Apr '19

09 Apr '19

External Email - Use Caution The Yale University Alzheimer’s Disease Research Unit and the Yale PET Center has an opening for a highly qualified and motivated individual at the post-doctoral level to work on research involving the development of analysis techniques integrating human imaging data including PET and fMRI for NIH-funded studies and clinical trials in Alzheimer’s disease. Applicants must have obtained a Ph.D. in neuroscience, biomedical engineering, or a related field. Qualifications: Strong experimental, analytical, and programming skills are essential. Experience in fMRI, image analysis, algorithm development, and biological applications is highly desirable. The selected candidate will work under the direction of Drs. Christopher van Dyck and Adam Mecca. The successful candidate should have a Ph.D. or an M.D./Ph.D. with at least three years of experience in fMRI and/or PET imaging. Application Instructions: Interested individuals should email a CV to adam.mecca(a)yale.edu. Adam Mecca, M.D. Ph.D. Yale School of Medicine, Department of Psychiatry Geriatric Psychiatry and the Alzheimer's Disease Research Unit Tel: (203) 764-8100 Fax: (203) 764-8111

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Paired Analysis Questions
by brain health 09 Apr '19

09 Apr '19

External Email - Use Caution Dear Dr. Greve: Thank you so much for your time and help. I am working on the Paired Analysis that you suggested. Very appreciated! I am interested if there are different within-group changes in brain structure for an Intervention (PA) and Control (C) group. Does the paired-diff.fsgd file (peek below) look correct? PAC Groups Class Main Variables Group Input sub107 Main PA Input sub112 Main PA Input sub113 Main C Input sub118 Main PA Input sub131 Main C Input sub132 Main C Input sub136 Main C What would be the contrast of interest to include for my question? Just want to make sure I am running the correct model. I am also reading the guide about how to interpret the results of the mri_glmfit commands (e.g., https://surfer.nmr.mgh.harvard.edu/fswiki/mri_glmfit) Is there another guide to follow regarding the output of the Paired Analysis? I appreciate your guidance!

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Problem with calculating significant clusters' values
by Georgina Angelopoulou 09 Apr '19

09 Apr '19

External Email - Use Caution Hello FreeSurfer Developers, I have compared two groups in area, volume and thickness (using mri_glmfit and mri_glmfit-sim) and I want to extract the total value from each significant cluster so that I can run analysis with behavioural variables in SPSS. I have found some previous posts with the following command: mri_segstats --i <pathway to rh.volume.Study.10.mgh> --seg cache.th13.abs.sig.ocn.mgh --excludeid 0 --sumwf ClusterVolumeValues.dat –accumulate. but also the alternative option in --seg cache.th13.abs.y.ocn.dat. Could you please tell me: 1. Which is the correct option for -- seg and what is their difference? 2. I tried to run both option and I get the exact same error: mri_read(): couldn't determine type of file lh.SexStudy_area.glmdir/MN-FM/cache.th13.abs.y.ocn.dat ERROR: loading lh.SexStudy_area.glmdir/MN-FM/cache.th13.abs.y.ocn.dat Any ideas of how to resolve that? 3. Is that command the right one for volume, area and thickness? Thank you in advance, Best, Georgina

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FSFAST group analysis problem: dimension mismatch between y and X
by Keri Woods 08 Apr '19

08 Apr '19

External Email - Use Caution Hi Freesurfer experts I'm having a problem running an FSFAST group analysis. When I try to run the second level GLM, I get the following error: keri@buddha:~/audio_108_no_stc_tau1,5$ mri_glmfit --y ~/audio/all/audio.lh/tones/ces.nii.gz --wls ~/audio/all/audio.lh/tones/cesvar.nii.gz --fsgd 2groups.fsgd --C groupdiff.mtx --surface fsaverage lh --glmdir all_tones_left_glm.wls --nii.gz gdfRead(): reading 2groups.fsgd INFO: gd2mtx_method is dods Reading source surface /home/keri/recon_all/subjects/fsaverage/surf/lh.white Number of vertices 163842 Number of faces 327680 Total area 65416.984375 AvgVtxArea 0.399269 AvgVtxDist 0.721953 StdVtxDist 0.195470 $Id: mri_glmfit.c,v 1.241.2.4 2016/12/08 22:02:40 zkaufman Exp $ cwd /home/keri/audio_108_no_stc_tau1,5 cmdline mri_glmfit.bin --y /home/keri/audio/all/audio.lh/tones/ces.nii.gz --wls /home/keri/audio/all/audio.lh/tones/cesvar.nii.gz --fsgd 2groups.fsgd --C groupdiff.mtx --surface fsaverage lh --glmdir all_tones_left_glm.wls --nii.gz sysname Linux hostname buddha machine x86_64 user keri FixVertexAreaFlag = 1 UseMaskWithSmoothing 1 OneSampleGroupMean 0 y /home/keri/audio/all/audio.lh/tones/ces.nii.gz logyflag 0 usedti 0 FSGD 2groups.fsgd labelmask /home/keri/recon_all/subjects/fsaverage/label/lh.cortex.label maskinv 0 glmdir all_tones_left_glm.wls IllCondOK 0 ReScaleX 1 DoFFx 0 wFile /home/keri/audio/all/audio.lh/tones/cesvar.nii.gz weightinv 1 weightsqrt 1 Creating output directory all_tones_left_glm.wls Loading y from /home/keri/audio/all/audio.lh/tones/ces.nii.gz ... done reading. INFO: gd2mtx_method is dods Saving design matrix to all_tones_left_glm.wls/Xg.dat Computing normalized matrix Normalized matrix condition is 1 Matrix condition is 1.34783 Found 149955 points in label. Pruning voxels by thr: 1.175494e-38 Found 66097 voxels in mask Saving mask to all_tones_left_glm.wls/mask.nii.gz Reshaping mriglm->mask... search space = 31233.070725 ERROR: dimension mismatch between y and X. y has 116 inputs, X has 108 rows. 108 is the number of subjects that I have. I can see that the y file with 116 inputs is /home/keri/audio/all/audio.lh/tones/ces.nii.gz , and checking the dimension of it, it confirms that it is a 4D matrix with the 4th dimension of 116. It seems as if this file is created during isxoconcat-sess, and I have checked and the session ID file being used here has only 108 entries. It appears that 108 subjects are being used in this step, as part of the output is: ninputs = 108 Checking inputs nframestot = 108 Allocing output Done allocing nframes = 108 I think that a source of the error could be the fact that at one time I did have 116 subjects. I've created a new folder, copying in the unpacked files for each subject, and repeating from the preprocessing step, but this doesn't make any difference. Is there are chance that there's a file outside the functional directory that has stored this 116? Any help is greatly appreciated. Best wishes, Keri

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Become an HCP Pipelines pro at HCP Course 2019!
by Jennifer Elam 08 Apr '19

08 Apr '19

External Email - Use Caution *Want to apply tools created by HCP experts to your own neuroimaging data? * *Always wanted to try the HCP Pipelines, but haven't had the time to test them out? * This year's HCP Course July 8 – 12, 2019 in Portland, Oregon is featuring expanded, hands-on sessions to help you discover and use HCP neuroimaging analysis pipelines, which include FreeSurfer. Course attendees will even have the opportunity to try the HCP Pipelines out on their own data! *HCP Pipelines demystified. Hands-on practice. Your data, processed.* We'll cover... - Best practices for high quality image acquisition - Strengths of the HCP's neuroanatomically-driven approach to preprocessing and registration - Unique features of the HCP Pipelines within the growing constellation of open-source neuroimaging analysis tools - Organizing your imaging data to run the pipelines - Diving into the scripts to see what is happening at each step of the processing - Editing the pipeline code and parameters to fit your specific needs - Running the pipelines in a ready to use container and turnkey framework locally or on the cloud to get results - Interfacing pipelines in container turnkey form with the XNAT informatics ecosystem - Tips on how to handle legacy data Plus, understanding HCP processing will put you in a great position to utilize the soon-to-be-released HCP Lifespan Development (ages 5-21) and Aging (ages 35-100+) data and upcoming Connectomes Related to Human Disease projects. For more info visit the <http://store.humanconnectome.org/courses/2019%20%20%20%20%20%20%20%20%20/ex…> HCP Course 2019 website <https://store.humanconnectome.org/courses/2019/exploring-the-human-connecto…>. Register soon, the course is filling up fast! If you have any questions, please contact us at: hcpcourse <hcpcourse(a)humanconnectome.org>@humanconnectome.org <hcpcourse(a)humanconnectome.org> We look forward to seeing you in Portland! Best, 2019 HCP Course Organizers -- Jennifer Elam, Ph.D. Scientific Outreach, Human Connectome Project Washington University School of Medicine Department of Neuroscience, Box 8108 660 South Euclid Avenue St. Louis, MO 63110 314-362-9387 elam(a)wustl.edu www.humanconnectome.org

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