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Qdec-correction for multiple comparison
by John Anderson 06 Jul '16

06 Jul '16

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Seed based volume output to surface
by Taha Abdullah 06 Jul '16

06 Jul '16

Good Afternoon Freesurfers, I am running a seed-based connectivity for one individual subject. The seed is in the L_parahippocampus. I have followed the steps outlined in FSFast walkthrough. Below is a list of my commands. Mind you that I was trying to keep my analysis as simple as possible before delving deeper into it. I have a question on the sig.nii.gz output. Please see at the end. preproc-sess -s taha_brain -fwhm 0 -surface self lhrh -mni305-2mm -fsd resting_scans -per-run fcseed-config -segid 1016 -fcname L_parahipp -fsd resting_scans -mean -cfg mean.L_parahipp.config -overwrite -fillthresh 1 fcseed-sess -s taha_brain -cfg mean.L_parahipp.config mkanalysis-sess -analysis L_parahipp_seed.surf.lh -surface self lh -fwhm 0 -notask -taskreg L_parahipp 1 -fsd resting_scans -TR 0.555 -mcextreg -polyfit 2 -per-run selxavg3-sess -s taha_brain -a L_parahipp_seed.surf.lh Output files /home/tabdullah/Project/Sess01/fsd/L_parahipp_seed.surf.lh/L_parahipp/sig.nii.gz amongst others *Is there a way to convert the volume to a surface and then extract per vertex the sig value?* I used tmri_vol2surf see below: mri_vol2surf --mov ./sig.nii.gz --reg /home/tabdullah/resting_state_1/taha_brain/resting_scans/001/register.dof6.dat --trgsubject taha_brain --interp nearest --projfrac 0.5 --hemi lh --o /home/tabdullah/sig.mgh --noreshape --cortex I tried using mris_convert -c mris_convert -c ./sig.mgh /usr/local/freesurfer/subjects/taha_brain/surf/lh.white sig.asc The last column is all zeros. I am not entirely sure what I am doing wrong here, it is probably somewhere in the last two commands. Possibly using mri_segstats or mri_read.m? Any help would be greatly appreciated. Apologize in advance for the long email. -- Taha Abdullah Department of Physiology Northwestern University Feinberg School of Medicine Masters of Science Physiology and Biophysics, Georgetown University 2015 Work: (312)-503-0413

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Design Matrix Creation
by Timothy Hendrickson 06 Jul '16

06 Jul '16

Freesurfer Support, Thank you for your support with my previous line of questions regarding design matrix creation. I have manually created another design matrix and want to ensure that I designed it correctly. An example of my FSGD file is as follows below: Class SITE 1-Male-Control Class SITE 1-Male-PATIENT Class SITE 1-Female-Control Class SITE 1-Female-PATIENT Class SITE 2-Male-Control Class SITE 2-Male-PATIENT Class SITE 2-Female-Control Class SITE 2-Female-PATIENT Class SITE 3-Male-Control Class SITE 3-Male-PATIENT Class SITE 3-Female-Control Class SITE 3-Female-PATIENT Class SITE 4-Male-Control Class SITE 4-Male-PATIENT Class SITE 4-Female-Control Class SITE 4-Female-PATIENT Variables age_at_scan total_intracranial_volume study site levels = 1, 2, 3, 4 gender levels = Male, Female diagnosis levels = PATIENT, Control age_at_scan = covariate age total_intracranial_volume = covariate total intracranial volume What I would ideally like to do is: 1) Take into account offset differences amongst diagnosis, gender, and study site. 2) Allowing a difference in age slope, and total intracranial volume slope amongst the diagnosis and gender levels. 3) Modeling the age slope and total intracranial volume slope as the same for the study site levels. Let's image that the first participant is from site 1, Male, and control, and is 12 and has a TIV of 30,000. The second participant is from site 2, Female, and PATIENT, and is 14, and has a TIV of 25,000. My understanding of the design matrix would be as follows: 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 0 0 30000 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 14 0 0 0 25000 -Tim >Yes, create your matrix manually. > >Those matrix lines are not quite right. The ages are in the correct >column, but you need a 1 somewhere in columns 1-8 to indicate the class >(ie, site/dx) that the subject is in. On 05/26/2016 12:57 PM, Timothy Hendrickson wrote: > Hi Doug, > > Thank you for such a prompt response. Just to be clear you are > recommending that I manually create the matrix file right? > > If so I want to ensure that I am understanding how to design the > matrix file properly. > > Let's imagine that the first participant is a control and is 13 and > the second is a patient and is 15. My understanding is that the matrix > file would be as follows: > 0 0 0 0 0 0 0 0 13 0 > 0 0 0 0 0 0 0 0 0 15. > > -Tim > Previous correspondences are below: > > You'll need a regressor for each of the 8 classes you describe below. > You can use mri_glmfit to generate this (Xg.dat file) > You'll need two more regressors for age, one for each diagnosis. If a > subject (ie, row) is a control then the two values will be AGE 0. If the > subject of the row is a patient, then the two values will be 0 AGE. You > can then set up a Controls-Patients age (ie, interaction between dx and > age) contrast like > [0 0 0 0 0 0 0 0 1 -1] > On 05/24/2016 02:30 PM, Timothy Hendrickson wrote: > > > > Freesurfer Support, > > > > I'd like to create a design matrix for a group analysis outside of the > > DODS and DOSS models. I understand that in order to do this the -X > > flag must be used. However, I have been unable to find examples of how > > to do this. > > > > I am hoping to reveal a difference in thickness or gyrification > > amongst a clinical population. The data set contains two factors: > > diagnosis, and study site and one covariate: age. Diagnosis has two > > levels: controls, and patients. Study site has four levels, one level > > for each location the data has been collected from. > > > > What I would ideally like to do is: > > > > 1) Take into account offset differences amongst diagnosis and study site. > > > > 2) Allowing a difference in age slope amongst the diagnosis levels > > > > 3) Modeling the age slope as the same for the study site levels > > > > My FSGD file is designed as follows > > > > Class SITE 1-Control > > Class SITE 1-PATIENT > > Class SITE 2-Control > > Class SITE 2-PATIENT > > Class SITE 3-Control > > Class SITE 3-PATIENT > > Class SITE 4-Control > > Class SITE 4-PATIENT > > Variables age_at_scan > > > > study site levels = 1,2,3 and 4 > > diagnosis levels = PATIENT and Control > > age_at_scan = covariate age > > > > Any advice would be greatly appreciated. > > > > Respectfully, > > > > Tim > > > > -- > > Timothy Hendrickson > > Department of Psychiatry > > University of Minnesota > > Mobile: 507-259-3434 <tel:507-259-3434> (texts okay)

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FSFAST- Cerebellum
by Sabin Khadka 06 Jul '16

06 Jul '16

Hi all, I am trying to extract mean time series BOLD data using FSFAST from Cortical ROIs + sub cortical ROIs and cerebellum. preproc-sess -s rest210 -fsd bold -surface fsaverage lhrh -mni305 -fwhm 6 -per-run -stc odd mri_segstats --annot fsaverage lh aparc --i rest210/bold/001/fmcpr.odd.sm6.fsaverage.lh.nii.gz --excludeid 1000 --excludeid 1004 --avgwf CorticalTimeSeries_lh.txt mri_segstats --annot fsaverage rh aparc --i rest210/bold/001/fmcpr.odd.sm6.fsaverage.rh.nii.gz --excludeid 2000 --excludeid 2004 --avgwf CorticalTimeSeries_rh.txt and for cortical time series mri_segstats --seg fsaverage/mri.2mm/aseg.mgz --ctab /opt/freesurfer/FreeSurferColorLUT.txt --id 10 --id 11 --id 12 --id 13 --id 17 --id 18 --id 26 --id 49 --id 50 --id 51 --id 52 --id 53 --id 54 --id 58 --i rest210/bold/001/fmcpr.odd.sm6.mni305.2mm.nii.gz --avgwf subCorticalTimeSeries.txt But I am not sure on how exactly to extract time series from cerebellar regions. So if I want to extract time series from regions as described in Buckner et.al 2011. Could I just use mri_segstats for the labels 601-628 in FreeSurferCololLUT.txt? If not could you please direct me to processes that I can use. Cheers, Sabin Khadka

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Intensity stats question
by Sabrina Yu 06 Jul '16

06 Jul '16

Hello, I have a couple of questions about the wmparc.stats file generated. What volume is the data based on? Has the intensity of the volume been corrected? I just need the average voxel intensity over the ROIs, but am unsure if this intensity is based on an intensity normalized brain volume. Is it possible to change the input volume for wmparc.stats to orig.mgz? Thank you in advance.

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Applying the lta transformation to PET image | mri_coreg | mri_segstats
by Pradeep 06 Jul '16

06 Jul '16

Hello All, I am trying to extract the SUV values a PET image mri_segstats --seg wmparc.mgz --sum petsuv.segstats.dat --i rPET --ctab-default since rPET is supposed to be coregistered to MRI, I did the following mri_coreg --s MRI --mov PET --lta mri_coreg.lta which did not generate the coregistered image but just transformation. Is there a way to generate this image or to just input the mri_coreg.lta as a flag to mri_segstats? Thanks, Pradeep

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Unsupported slice timing pattern 5 in version 5.3.0
by Leonardo Tozzi 06 Jul '16

06 Jul '16

To Whom it may concern, I have tried to run the recon-all pipeline on some T1 data and have encountered the following error: nifti1Read(): unsupported slice timing pattern 5 I have browsed the previous threads about it and it appears that it should have been fixed in version 5.3 but that is the version I run and the error is still there. The data has been converted to NIFTI from DICOM using MRIcron and I don't have access to the original DICOMs. I have seen that someone posted a modified version of nifti1Read() in the past and I was wondering if it was still available. I am running Freesurfer 5.3.0 on MacOSX El Capitan 10.11.3. Would you have any suggestions on how to proceed? Thank you very much. Yours faithfully, Leonardo Tozzi, MD PhD Student Trinity College Institute of Neuroscience College Green, Dublin 2 Ireland

2 1

Not able to find file in gtmseg
by Lee Subin Kristine 06 Jul '16

06 Jul '16

Dear FreeSurfer experts, Hello, I am trying to use Freesurfer's (developmental version) PVE correction tool and I haveone question. The data to be PVE-corrected are some preprocessed PET data downloaded from the Alzheimer's DIsease Neuroimaging Initiative (ADNI) database. Basiclly, the dynamic PET images have been co-registered to one another, averaged, and spatially normalized to a common space. Now I am trying to apply PVE-correction. It seems from your answers here (https://www.mail-archive.com/freesurfer@nmr.mgh.harvard.edu/msg43435.html)<https://www.mail-archive.com/freesurfer@nmr.mgh.harvard.edu/msg43435.html>that you run the following commands: (1) gtmseg (2) bbregister (3) mri_gtmpvc (4) mri_glmfit When I enter gtmseg --s subject such as below ('Desktop/forFSsubin_2' is location of the subject MRI and '019_S_4835_N3m_cub_ACPC.nii' is the filename) ~/Desktop/forFSsubin_2$ gtmseg --s 019_S_4835_N3m_cub_ACPC.nii I get: ERROR: cannot find 019_S_4835_N3m_cub_ACPC.nii I have changed directory to the folder where the subject MRI file is, and I have typed the subject's filename correctly, but it keeps saying the subject file cannot be found. Any ideas on what is wrong here? Any help would be appreciated. Thank you in advance. Regards, Subin

2 1

convert from MNI152 to native space
by Leila Reddy 06 Jul '16

06 Jul '16

Hi, I have a binary mask from the WFU_Pickatlas. I think this mask in in the MNI152 space (when I load_nifti in Matlab I get dimensions of [91 109 91]. I would like to convert this mask into the native space of each subject. I tried the following command but the results do not look right in Freeview: mri_vol2vol --mov mask_MNI152.nii --targ bold/005/f.nii.gz --o mask_in_Native.nii --mni152reg The overlay of the mask on f.nii in Freeview is mostly outside the brain. How can I go about this step? Thanks for your help,Leila

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Hippocampal subfields segmentation - what is the voxel size of the input?
by Fernando Pasquini Santos 06 Jul '16

06 Jul '16

Dear, I have a doubt regarding the input T1 image used for the Hippocampal Subfield segmentation in Freesurfer 6.0 - https://surfer.nmr.mgh.harvard.edu/fswiki/HippocampalSubfields In this documentation it says that I can use a standard 1mm T1 image or the same standard 1mm T1 image with an additional scan. However, I want to use a 0.7mm T1 image as input, with an additional T2 scan. When I run the program with it, the output images (nu.mgz and orig.mgz) are downsampled to 1mm voxel size. So, I don't know if this happens just because of the recon-all program or if the segmentation is being done in the downsampled T1 image or in the original 0.7mm. By reading the article "A computational atlas of the hippocampal formation using ex vivo, ultra-high resolution MRI: Application to adaptive segmentation of in vivo MRI" I saw that, in the methods section, the algorithm is used to segment 0.6mm T1 images. But is this possible to do in the Freesurfer package? Obviously, doing the segmentation directly on 0.7mm data would be better than a downsampled version to 1mm... Thanks, Fernando Pasquini Santos PhD student in Dynamic Systems fernandosantos(a)pitt.edu fernando.pasquini.santos(a)usp.br

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