Freesurfer July 2020

freesurfer@nmr.mgh.harvard.edu

96 participants
160 discussions

Recon-all 5.3.0 failing and I can't see the error message
by Ian 02 Jul '20

02 Jul '20

External Email - Use Caution I have attached the log - is there any chance you could tell me what the problem is? Thanks, Ian --

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Re: [Freesurfer] How can I create a grey matter volume in Matlab?
by Franziska Klein 02 Jul '20

02 Jul '20

External Email - Use Caution Hello again, unfortunately, nobody is responding. . Until now I am able to create meshes from the freesurfer output files with the isosurface() and read_surf() functions from a MATLAB based toolbox . However, I still do not know with which combinations of the outputs of recon-all I could create a grey matter only mask. My goal is to get subject specific channel MNI coordinates projected onto the cortex (grey matter). My solution at the moment is to simply use the pial surfaces (rh.pial and lh.pial), however, I am not sure if this is sufficient. Any thoughts or ideas maybe? Thanks, Franziska ________________________________ Von: Franziska Klein Gesendet: Mittwoch, 27. Mai 2020 11:05 An: freesurfer(a)nmr.mgh.harvard.edu Betreff: How can I create a grey matter volume in Matlab? Dear freesurfer user, due to the Covid 19 situation I am working in home office with a windows computer and can not run any freesurfer functions (installing a virtual box is not really an option). For all my subjects I do already have all output files from recon all. In the output, I found a wm.mgz but unfortunately there is no gm.mgz. Is it somehow possible to create a grey matter volume by using the recon all output in combination with Matlab? Thank you and kind regards, Franziska ------------------------------------------ Franziska Klein, M.Sc. Neurocognition and Functional Neurorehabilitation Group Neuropsychology Lab Department of Psychology University of Oldenburg D-26111 Oldenburg Germany Office: A7 0-066 Phone: +49-441-798-4947 Fax: +49-441-798-5522

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Bounding box dimensions for mri_cvs_register (MNI space)
by Elizabeth Haris 02 Jul '20

02 Jul '20

External Email - Use Caution Hi guys, I have a couple of queries regarding the output dimensions for mri_cvs_register. 1. If I am registering my images to MNI space, can the command give me a 2mm image, or will I only get a 1mm image which I then need to convert into a 2mm? I am currently getting a 1mm image and resampling it to a 2mm image afterwards (for fMRI analysis), using the following commands, and wanted to double check the procedure: * CVS command: mri_cvs_register --mov <subjID> --mni * FSL command: flirt -in <final_CVSmorphed_tocvs_avg35_inMNI152_norm.nii> \ -ref < final_CVSmorphed_tocvs_avg35_inMNI152_norm.nii > -applyisoxfm 2.0 -nosearch \ -out <subject_MNI_2mm.nii> 1. I also noticed that when I resample the image this way, though its dimensions are 2mm^3 the voxels in the bounding box are different to the voxels in my 2mm^3 functional image preprocessed in FSL (FS: 128^3 vs FSL: 109 91 109). * Is this a problem? * If so, is there a way to rectify this? Many thanks! Liz

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Longitudinal pipeline in pediatric sample with TIV difference
by Jose Pariente 02 Jul '20

02 Jul '20

External Email - Use Caution Hello Freesurfers experts, I have a pediatric sample and I wanted to use the longitudinal pipeline (the time acquisitions are 8 years apart and age range is from 6 years to 17). I saw that longitudinal pipeline assumes that TIV doesn't change, which in my sample is not true, but in Forums I saw that it can be done if you check that the average template and the images are well segmented. Is there something that can help me to determine this? For instance, a certain difference in eTIV between post and pre acquisition? Thanks, Jose Pariente

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Two research assistant positions
by Osher, David E. 01 Jul '20

01 Jul '20

External Email - Use Caution RESEARCH ASSISTANT We are recruiting 2 technical research assistants in the Cognition and Brain Circuitry Laboratory of Dr. David Osher at the Ohio State University. Primary duties for both positions include: conducting neuroscience research on the functional and structural architecture of the human brain, and its role in cognition; programming, running, and analyzing behavioral and brain-imaging experiments using functional magnetic resonance imaging (fMRI), diffusion weighted imaging (DWI), functional connectivity, and behavioral assessments; scoring and coding data; performing statistical analyses using programs such as, MATLAB, Python, and shell scripting; recruiting research participants; maintaining participant databases; developing outreach letters. Positions are available for one year with the possibility of extension based on satisfactory performance and availability of funds. Required qualifications include: Bachelor's degree in psychology, neuroscience, cognitive science, computer science, data science, engineering, physics, or math; conduct of social science research is required; experience in a social science research capacity. Highly desired: strong mathematical, statistical, and coding skills (e.g., MATLAB, Python, shell scripting); strong interpersonal skills for interacting with a diverse group of people; strong organizational skills. This position is an excellent opportunity for individuals considering future graduate studies in cognitive and computational neuroscience. We are seeking an aspiring, self-motivated researcher with strong coding/programming skills who is excited about the brain, cognitive neuroscience, and/or clinical disorders and demonstrates evidence of a serious interest in a career in the field. If you are interested in being considered for these positions, please apply online at https://www.jobsatosu.com, under job listing #459935 (100%) and/or #459934 (75%) and submit a current CV and names of three references. If you have questions about the position or the lab, please contact Dr. David Osher at osher.6(a)osu.edu<mailto:osher.6@osu.edu> The Ohio State University is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation or identity, national origin, disability status, or protected veteran status.

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POSTDOC POSITION - modeling the functional and structural architecture of the visual system
by Osher, David E. 01 Jul '20

01 Jul '20

External Email - Use Caution POSTDOCTORAL SCHOLAR We are recruiting a Post Doctoral Scholar in the Cognition and Brain Circuitry Laboratory of Dr. David Osher at the Ohio State University. The Post Doctoral Scholar will plan, design, and conduct research using computational models to investigate the functional and structural architecture of the brain. This position is available for one year with the possibility of extension based on satisfactory performance and availability of funds. Required qualifications include Ph.D. in cognitive neuroscience, psychology, or related field; research experience in neuroimaging methods (magnetic resonance imaging (MRI), functional magnetic resonance imaging (fMRI), diffusion-weighted (DWI,) and/or functional connectivity). Desired qualifications include proficiency in coding; interest in any or all of the following: understanding the functional and structural architecture of the brain, computational modeling of individual differences in brain and behavior (especially in attention and perception), training and neural plasticity, and computational models of the human visual system. If you are interested in being considered for this position, please apply online at https://www.jobsatosu.com, under job listing #459936 and submit a current CV and names of three references. If you have questions about the position or the lab, please contact Dr. David Osher at osher.6(a)osu.edu<mailto:osher.6@osu.edu> OSU is located in Columbus, Ohio and is home to a vibrant community of cognitive neuroscientists, computational modelers, and vision scientists in the Psychology Department and Center for Cognitive and Brain Sciences. Postdocs will have access to state-of-the-art MRI and EEG facilities located inside the Psychology building. The Ohio State University is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation or identity, national origin, disability status, or protected veteran status.

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Longitudinal Stream Problem
by Danielian, Laura (NIH/NINDS) [E] 01 Jul '20

01 Jul '20

External Email - Use Caution Hi, I’ve finished processing a data set that included longitudinal data and I’m having a problem with a small percentage of the longitudinal timepoints. To review what I’ve done, I edited all of the individual (cross-sectional) timepoints until the wm and pial surfaces were correct, then created the base and edited that until it looked good, and then created the longitudinal files for each cross-sectional timepoint. Most of these did not need editing and some needed slight edits to either wm or brainmask which corrected the longitudinal surfaces. However, in a small handful of cases, the wm/pial surfaces were so distorted that editing would not fix the problem. In these cases, longitudinal surfaces were very different from both the original cross-section and base. I’ve tried to attach a file that shows an example – it might only affect a small portion of the brain but in these cases I don’t think I could edit it to improve the surfaces. In the example I attached, red/blue are from the long file and pink/lt blue are from the base. Do you have any suggestions for why this might be happening and how to fix it? I’m running v6.0. Thanks! Laura Danielian

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How much recon editing is appropriate?
by Wakim, Kathryn-Mary 01 Jul '20

01 Jul '20

External Email - Use Caution Hi everyone! Quick question. For my specific analysis, I’m most interested in the values given in the aseg.stats file. I’m comparing gray matter volumes from specific ROIs between patients and healthy controls. Thus, the outcome measures I will be reporting are things like: left caudate volume is 75 +- 11 units for controls, 52 +- 6 unit for patients. I am not particularly interested in each subject’s individual 3D reconstruction. For each subject, I have verified that tal registrations, pial surface boundaries, and WM segmentation boundaries are roughly accurate based on a quick assessment, e.g. no gross image registration errors have been made. Given that the reconstruction itself is not of interest, is it still advised to make edits to the recons in order correct small inaccuracies? Thanks so much or your help! Best, Kamy

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Sub-cortical areas and other atlases
by Martin Juneja 01 Jul '20

01 Jul '20

External Email - Use Caution Hello experts, I am following these instructions https://surfer.nmr.mgh.harvard.edu/fswiki/FsTutorial/GroupAnalysis to analyze the association between IQ and whole brain cortical thickness of brain areas (which by default uses Desikan atlas of 34 regions). I was wondering how: (1). To do the similar analysis to identify sub-cortical regions which show significant association between thickness and IQ. (2). To use other atlases here i.e., replace Desikan atlas with 7 or 17 network Yeo atlas to identify which network shows the association with IQ. I know how to extract thickness etc from sub-cortical areas (i.e., aseg stats) and use Yeo atlas outside these instructions, but I am not sure how to do this in above described instructions i.e., replace Desikan with sub-cortical and Yeo atlases etc. Any help would be really appreciated. Thanks !

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error for input volume
by N Saf 01 Jul '20

01 Jul '20

External Email - Use Caution Dear Freesurfer experts, I've tried to perform an autorecon1 for a patient's brain MRI(T1). There are some dark regions in white matter areas. an error has occurred which I've attached the corresponding log file here as well as the raw nii data. I wonder if there is any approach to let me do the recon-all analysis for this case. Any help would be very appreciated and thank you for your time. All best wishes, Nazanin khameh1.nii <https://drive.google.com/file/d/1IDdju6AzqktTanDhbDd543BuchTWEcNS/view?usp=…>

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Freesurfer July 2020