Freesurfer

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30089 discussions

Getting stats file from nii.gz Yeo atlas for FEF
by Catherine Joe 17 May '18

17 May '18

External Email - Use Caution Hello everyone, I am having a bit of trouble extracting stats data (such as gray matter volume etc) from a particular FEF nifti file I generated from the Yeo Atlas 17 networks. I tried using mri_convert --in_stats <in volume><out volume> but the information given is really just the TE, TR, TI etc and not actually the information such as gray matter volume, surface area, number of voxels etc. What would be your advice to proceed from here? Is there another type of command I should be looking at? Thank you all in advance. Kind regards, Catherine

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FS Longitudinal Two Stage Model
by Evelyn Medawar 16 May '18

16 May '18

External Email - Use Caution Dear FS community, I got a question about the Longitudinal Two Stage Model for the following command put into Freesurfer v 6.0: long_mris_slopes --qdec ./qdec/long.qdec.table.dat --meas thickness --hemi lh --do-avg --do-rate --do-pc1 --do-spc --do-stack --do-label --time years --qcache fsaverage The first subject is running smoothly, but then the following ERROR message pops up: =============================================================================== SUBJECT template_09440.22 Intersecting Within-Subject Cortex Label cp /data/pt_nro186_lifeupdate/preprocessing/FREESURFER/FREESURFER_long/09440.22_VERIO.long.template_09440.22/label/lh.cortex.label /data/pt_nro186_lifeupdate/preprocessing/FREESURFER/FREESURFER_long/template_09440.22/label/lh.long.cortex.label mris_label_calc intersect /data/pt_nro186_lifeupdate/preprocessing/FREESURFER/FREESURFER_long/09440.22_SKYRA.long.template_09440.22/label/lh.cortex.label /data/pt_nro186_lifeupdate/preprocessing/FREESURFER/FREESURFER_long/template_09440.22/label/lh.long.cortex.label /data/pt_nro186_lifeupdate/preprocessing/FREESURFER/FREESURFER_long/template_09440.22/label/lh.long.cortex.label mris_label_calc: malloc.c:2394: sysmalloc: Assertion `(old_top == initial_top (av) && old_size == 0) || ((unsigned long) (old_size) >= MINSIZE && prev_inuse (old_top) && ((unsigned long) old_end & (pagesize - 1)) == 0)' failed. ERROR -6 : mris_label_calc intersect did not work? It seems that the labelling step at the intersection does not work (the result of the copying is an empty file). Has anybody any idea why that would be the case? Thank you a lot! Evelyn Medawar

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FS_Fast preproc-sess - bbregister misalignment
by Patrycja Naumczyk 16 May '18

16 May '18

External Email - Use Caution Hi All, I'm running FS v. 5.3 on Gentoo Linux. I made a study, where all subjects during one session had T1, resting-state and task-based fMRI. I processed all anatomical data through standard recon-all (it worked well), and the task-based fMRI through FS-FAST - which also generated fine results. Now I wanted to look into the rs-fMRI with functional connectivity. I made a separate directory tree for this purpose (in order not to mess task and rest data), and unfortunately the bbregister doesn't handle the registration during preproc-sess properly. Misalignment is big and covers all runs. BBR-sums of all of participants (N=39) exceed 0.8 (some of them exceed 1.0). What's interesting is that bbregister previously managed the task-based fMRI data well (with no BBR-sum exceeding 0.8). I double checked the data for any i.e. conversion/orientation faults, but found none. The command for preprocessing was identical in rs-fMRI and task-based fMRI: preproc-sess -sf <sessid> -d <ProjectDirectory> -surface fsaverage lhrh -mni305 -fwhm 5 -per-run -fsd bold I attach exemplary register log file from rs-fMRI subject registration (BBRsum=0.9704). This subject's task-based fMRI BBR-sum was 0.55. My question is - what may be the cause of such a discrepancy between registration of two functional runs taken one by one (the rs-fMRI preceded the task based)? Does anyone have an idea how to fix the problem? Best regards, Patrycja

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Problem with template longitudinal pipeline
by Binnewies, Julia 16 May '18

16 May '18

External Email - Use Caution Dear FreeSurfer experts, We are trying to run FreeSurfer v5.3 on our longitudinal imaging data using the longitudinal pipeline. We first processed both time points cross-sectionally. The output of this step looks fine for both time points. We then performed step 2: creation of a template from both time points and step 3: longitudinally processing both time points. All steps run without errors, but the output of steps 2 and 3 look abnormal (please see images attached), so there appears to be something wrong in the creation of the template. We also have some subjects with data from only one timepoint and ran the longitudinal pipeline for these subjects as well (as was recommended on the wiki) and the output of steps 2 and 3 look fine for these subjects, so there appears to be an issue in creating the template based on both time points. The acquisition parameters at both time points are the same as far as we know. There is nine years between both measurements, and most of our subjects are between 50 and 60 years old at the second measurement. We have attached the recon.all.log file for one of our subjects. We hope you have some suggestions what the problem might be and how we could check this. Many thanks in advance for your help! Kind regards, Julia Binnewies & Laura van Velzen Dit e-mailbericht is uitsluitend bestemd voor de geadresseerde. Als dit bericht niet voor u bestemd is, wordt u verzocht dit aan de afzender te melden en het bericht te vernietigen. Het is niet toegestaan de inhoud van dit bericht verder te verspreiden of te gebruiken. Voor meer informatie over GGZ inGeest: www.ggzingeest.nl. Denk aan het milieu voordat u deze e-mail print.

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ICV adjustment of volumes in longitudinal pipeline
by Tamir Eisenstein 15 May '18

15 May '18

External Email - Use Caution Hello Freesurfer experts, If I want to analyze the volume difference of regions (2 time points) after performing all the 3 steps of the longitudinal pipeline, do I need to adjust each volume in the "long" directories to its specific "tp.long" ICV or are the data of the two "long" directories already "adjusted" to the template and there is no need for the specific time-point ICV adjustment? Thanks! Tamir

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Longitudinal LME cluster value extraction
by Emmanuel Nwosu 15 May '18

15 May '18

External Email - Use Caution Dear FreeSurfer experts, Am analysing longitudinal structural data with the LME model algorithm. I will like to map the significant cluster after analysing the data to all subjects at all time points, extract the values for all and perform further statistical analyses. Please how do I go about extracting the cluster value from all subjects at all time points? Any help will be appreciated. Kind regards Emmanuel

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Problem with template longitudinal pipeline
by Laura van Velzen 15 May '18

15 May '18

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Longitudinal data from different sequences and scanners
by James Gullickson 15 May '18

15 May '18

All, Our lab is working with longitudinal (two time points) data from a cohort of around 130 individuals. We are attempting to make comparisons between time points 1 and 2 on measures like total brain volume, ventricular volume, ventricle-brain-ratio, and cortical thickness. However, we have run into an issue--we are seeing net increases in cortical thickness and total brain volume over time (which seems biologically implausible, given our age range of ~30-60 yrs old). We think it may have something to do with the fact that the T1w data from each time point was acquired with slightly different parameters and on different scanners, possibly leading to a rounding error in quantification of volumes/thickness. Timepoint 1 data are 1.0mm isotropic and were acquired on a 3T Siemens Tim Trio with 12ch headcoil. Timepoint 2 data are 0.8mm isotropic and were acquired on the same scanner, but which went through an upgrade to a Prisma Fit between timepoints, using a 32ch coil. Currently we have been comparing data from the cross sectional stream. We would like to use the longitudinal stream if that would improve results, but we saw this post that cautioned against it: https://www.mail-archive.c om/freesurfer(a)nmr.mgh.harvard.edu/msg52992.html What would be your recommendation for comparing this data longitudinally? Any thoughts on why we are seeing net increases in volume/thickness, and how to avoid that? One idea we had was perhaps degrading each image by rigid co-registration and then bringing each image into the halfway space between the two (as FSL's SIENA does). Thanks, James

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correlation analysis
by Raffaele Dubbioso 15 May '18

15 May '18

External Email - Use Caution Dear Freesurfer team, I'm working on correlation between fMRI data and a clinical score. Since such fMRI data correlate also with cortical thickness, I'd like to regress out this variable (cortical thickness). How can I write my fsgd file and command line mri_glmfit ? Thank you very much for your help Best regards Raffaele Dubbioso -- _______________________________________________ Raffaele Dubbioso, MD, PhD University Federico II of Naples Department of Neurosciences, Reproductive Sciences and Odontostomatology. Via Sergio Pansini, 5 80131 Napoli, ITALY phone: +39-0817464579 fax: +39-0817462667

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Neuroimaging postdoc position available at the University of Michigan
by Martijn Muller 15 May '18

15 May '18

*Research Fellow - Multimodal neuroimaging of Parkinson’s disease* A Research Fellow position is available immediately at the Functional Neuroimaging, Cognitive, and Mobility Laboratory, Department of Radiology, University of Michigan, Ann Arbor, MI, USA. Our laboratory specializes in clinical, mobility, cognition, and multimodal neuroimaging studies of Parkinson's disease and is directed by Drs. Nicolaas Bohnen, MD, PhD (Director) and Martijn Muller, PhD (Co-director). We are looking for a post-doctoral candidate to conduct and interpret multimodal and voxel-based imaging analyses of structural, functional MRI and PET datasets to address clinical research questions in patients with Parkinson’s disease. The applicant will also participate in the development of a new neuroimaging and clinical database with incorporated imaging analysis pipeline processing routines. Applicants must have completed a graduate degree (PhD) with relevant experience in multimodal imaging. The applicant must have experience in radiology/radiological sciences, signal processing, functional MRI and diffusion tensor imaging, the use of neuroimaging software packages such as SPM, Freesurfer, Matlab, and FSL. Experience in network-based methods, such as graph theory, would be highly desirable. Additional roles include leadership and active participation in project management activities including the administration of research projects, as well as some teaching sessions and supervision of students. Fluency in English conversation and team work skills to work in a multidisciplinary environment are important. This position will require self-initiative and the ability to work independently without close supervision. Send a brief letter of interest that describes how current skills fit with the required skills for this position, current curriculum vitae, names and contact information of three references to: Dr. Martijn Muller at mtmuller at umich.edu. Compensation of this limited term position will be commensurate with experience and includes health benefits. The University of Michigan is an equal opportunity/affirmative action employer. If applicable, this offer is contingent on your securing valid immigration status and work authorization before your expected start date and maintaining your valid immigration status and work authorization throughout your employment. University of Michigan Health System conducts background screening and pre-employment drug testing on job candidates upon acceptance of a contingent job offer and may use a third party administrator to conduct background screenings. Background screenings are performed in compliance with the Fair Credit Report Act.

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