Freesurfer February 2017

freesurfer@nmr.mgh.harvard.edu

162 participants
277 discussions

Multiple comparison question
by neuroimage analyst 02 Feb '17

02 Feb '17

Hi, We extracted volume measures from 7 ROIs in 2 groups and compared a) Mean of each ROI volume between group, and compared independently such as i) whether mean of ROI 1 in group 1 is equal to mean of ROI1 in group 2 ii)whether mean of ROI 2 in group 1 is equal to mean of ROI2 in group 2 and so on b) Plotted the mean ROI volume for 2 independent measures and compared whether the slope between and within group is significantly different. such as i) Slope of ROI1 is positively associated with MoCA , age (grp1) ? ii) Slope of ROI1 is negatively associated with MoCA, age (grp2) ? iii) Slope of ROI1 vs MoCA (grp1) is significantly different than slope of ROI1 vs MoCA (grp2) ? iv) Slope of ROI1 vs MoCA (grp2) is significantly different than slope of ROI2 vs MoCA (grp2) ? Q1) Do we have to perform multiple comparisons for (a) and (b)? Q2) If yes, do we correct across 7 measurements for (a) and 2 measurements for (b) or 7 measurements for both (a) and (b)? There is evidence to both performing and nonperforming multiple comparisons In the literature. Any response (hopefully pointing to a literature) will be greatly appreciated. Thanks Regards --VM

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longitudinal tracula error
by Bárbara Avelar Pereira 02 Feb '17

02 Feb '17

Dear FreeSurfer experts, I’m running tracula on longitudinal data but I’ve encountered the following error at the “trac-all -prep” stage: ERROR: flag ; unrecognized (see below) trac-preproc -c /Documents/TRACULA/TEST/S0001.01_T1/scripts/dmrirc.local -log /Documents/TRACULA/TEST/S0001.01_T1/scripts/trac-all.log -cmd /Documents/TRACULA/TEST/S0001.01_T1/scripts/trac-all.cmd ; trac-preproc -c /Documents/TRACULA/TEST/S0001.01_T2/scripts/dmrirc.local -log /Documents/TRACULA/TEST/S0001.01_T2/scripts/trac-all.log -cmd /Documents/TRACULA/TEST/S0001.01_T2/scripts/trac-all.cmd ; trac-preproc -c /Documents/TRACULA/TEST/S0001.01/scripts/dmrirc.local -log /Documents/TRACULA/TEST/S0001.01/scripts/trac-all.log -cmd /Documents/TRACULA/TEST/S0001.01/scripts/trac-all.cmd ; ERROR: flag ; unrecognized As an example, I defined the parameters in my dmrirc file as: set subjlist = ( S0001.01_T1 \ S0001.01_T2 \ S0004.00_T1 \ S0004.00_T2 ) set baselist = ( S0001.01 \ S0001.01 \ S0004.00 \ S0004.00 ) set dcmlist = ( S0001.01_T1/DTI.nii \ S0001.01_T2/DTI.nii \ S0004.00_T1/DTI.nii \ S0004.00_T2/DTI.nii ) From the mailing list, it seems a similar issue has been fixed in previous updates but I have tried both version 5.3 and 6.0 and still get this error... My tracula directory contains 3 directories per participant: 2 with the *.long.* output for timepoint 1 and 2, and a directory with the base. Including the base gives the error above, but if I take it out, it asks for it: ERROR: cannot find /Documents/TRACULA/TEST/S0001.01 From what I understand, the base is not necessary to run any analysis, but it has to be there anyhow (?): https://www.mail-archive.com/freesurfer@nmr.mgh.harvard.edu/msg45332.html Maybe I am understanding this incorrectly? Since the base is used to create the longitudinal output (*long*), including the aparc+aseg.mgz file, and those are then used in tracula, I thought I could run things without it. I decided to take out the “set baselist” part from the configuration file — this way it seems to run fine (so far). But I assume it’s there for a reason so I’m not sure this is a solution at all... Any help would be much appreciated! Details: 1) freesurfer-Linux-centos6_x86_64-stable-pub-v5.3.0 2) platform: CentOS release 6.8 (Final) 3) Operating system details (kernel name, release, version, etc.): Linux 2.6.32-642.11.1.el6.x86_64 #1 SMP Fri Nov 18 19:25:05 UTC 2016 x86_64 x86_64 x86_64 GNU/Linux

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Cortical thickness from ROI in volume format
by Martin Juneja 01 Feb '17

01 Feb '17

Hi FreeSurfer experts, My goal is to extract cortical thickness of several ROIs, which are in volume space. I am following instructions from this page: https://surfer.nmr.mgh.harvard.edu/fswiki/VolumeRoiCorticalThickness My ROIs and T1 image are in the form of binary mask and are already in same standard space (MNIT1.nii). So following the instructions, I am able to perform until step 3 (I created registration file X.dat using fslregister command to register MNIT1.nii with fslaverage). After that I am using this command: tksurfer fsaverage lh inflated -overlay lh.fsaverage.ROI5.mgh -fthresh 0.5 to make sure that the ROI in surface format is at correct place. But after I run this command I do not see the region anywhere on surface. I tried to view it using FreeView also, its giving me attached image. From FreeView it looks like the ROI is now a brain mask and is all over the brain with a constant value everywhere. I am not sure why this is happening. Next, I have 26 ROIs, 12 on left hemisphere, 12 on right hemisphere and 2 in the midline. Somehow, 11/12 ROIs on left hemisphere and 2 ROIs in the midline are working fine when I view those in tksurfer or FreeView but rest all are showing me value of 1 all over the brain. For left hemisphere and midline ROIs, I am using exactly same steps as mentioned in the instructions but for right hemisphere, I just replaced 'lh' with 'rh' in step 3. Any help would be really appreciated.

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Announcing HCP Course 2017 at UBC in Vancouver June 19-23!
by Jennifer Elam 01 Feb '17

01 Feb '17

We are pleased to announce the *2017 HCP Course: "Exploring the Human Connectome"* <https://store.humanconnectome.org/courses/2017/exploring-the-human-connecto…>, to be held *June 19 – 23, 2017* at the University of British Columbia (UBC) <http://ubcconferences.com/>, in Vancouver, BC, Canada. This is the week before the Organization of Human Brain Mapping (OHBM) annual meeting <http://www.humanbrainmapping.org/i4a/pages/index.cfm?pageID=3734> to be held in downtown Vancouver (about 8 miles away from UBC) June 25-29. This 5-day intensive course will provide training in acquisition, processing, analysis and visualization of whole brain imaging and behavioral data using methods and informatics tools developed by the WU-Minn-Oxford Human Connectome Project (HCP) consortium. The course is designed for investigators who are interested in: - using data collected and distributed from the HCP young adult study - acquiring and analyzing HCP-style imaging and behavioral data at your own institution - processing your own non-HCP data using HCP pipelines and methods - using Connectome Workbench <https://www.humanconnectome.org/software/connectome-workbench.html> tools and sharing data using the BALSA <https://balsa.wustl.edu/> imaging database - learning HCP multimodal neuroimaging analysis methods, including those that combine MEG and MRI data - exploring the HCP MMP 1.0 <http://humanconnectome.org/about/pressroom/nature-article-cortical-brain-ma…> multimodal parcellation brain map and learning about how it can be used in your analyses - positioning yourself to capitalize on HCP-style data being distributed by the Connectome Coordinating Facility (CCF) from forthcoming large-scale projects (e.g., Lifespan HCP development and aging and Connectomes Related to Human Disease projects) Participants will learn how to acquire, analyze, visualize, and interpret data from four major MR modalities (structural MR, resting-state fMRI, diffusion imaging, task-evoked fMRI) plus magnetoencephalography (MEG) and extensive behavioral data. Lectures and labs will provide grounding in neurobiological as well as methodological issues involved in interpreting multimodal data, and will span the range from single-voxel/vertex to brain network analysis approaches. The course is open to students, postdocs, faculty, and industry participants. The course is aimed at both new and current users of HCP data, methods, and tools, and will cover both basic and advanced topics. Prior experience in human neuroimaging or in computational analysis of brain networks is desirable, preferably including some familiarity with FSL <https://fsl.fmrib.ox.ac.uk/fsl/fslwiki> and Freesurfer <https://surfer.nmr.mgh.harvard.edu/> software. For more info and to register visit the HCP Course 2017 website <https://store.humanconnectome.org/courses/2017/exploring-the-human-connecto…>. If you have any questions, please contact us at: hcpcourse@humanconnectome. org We look forward to seeing you in Vancouver! Best, 2017 HCP Course Organizers

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Converstion of Wavefront .obj files into Nifti
by Dev vasu 01 Feb '17

01 Feb '17

Dear all, Could you please suggest me some method where i can possibly convert Wavefront .obj files into Nifti files, is such conversion technically relevant ?. Thanks Vasudev

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[FSFAST] Contrast percent map
by Seung-Goo KIM 01 Feb '17

01 Feb '17

Dear all, I wish to know how “cespct.nii.gz” is computed in selxavg3-sess. I thought it computes something like a relative change like: cespct = (contrast-baseline)/baseline*100, but I cannot figure out what was taken for the baseline. I thought it could be mean beta for constant terms (0-th polynomial) for each run, but my calculation was different from cespct. I would take average intensity for each voxel I would greatly appreciate a detailed explanation how the program computes it. Best regards, -- Seung-Goo KIM

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QDEC - Controlling for gender
by Jennifer Szeto 01 Feb '17

01 Feb '17

Hi Freesurfer experts, I am trying to compare cortical thickness between groups while controlling for age and gender using QDEC. However, gender is not showing up as a covariate variable or a nuisance factor (only showing up as a fixed factor), I am wondering how I could control for gender in this case? Thank you very much, Jen

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Freesurfer February 2017