Freesurfer

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30065 discussions

Re: [Freesurfer] Demeaning covariates correctly?
by Douglas N. Greve 06 Mar '18

06 Mar '18

Yes, you have done everything correctly. QDEC takes your table.dat file and creates an FSGD file. It is possible to specify in the FSGD file whether to do demeaning or not by including a keyword. It does not find that keyword and so does not do demeaning. But you've already done demeaning so it does not matter. > > > On 03/06/2018 09:54 AM, Avideh Gharehgazlou wrote: >> >> Hi experts, >> >> >> I'm using QDEC to look at between group differences in LGI. According >> to a previous post I demeaned my covariates (age and surface area) >> inputted in my qdec.table.dat file by subtracting each value (i.e. >> each age) by the mean of all participant's ages and dividing it by >> the standard deviation of all participant's ages. When I upload >> qdec.table.dat file onto QDEC, it states the following: >> >> >> MeanSTD >> >> Age -01 >> >> Surface area 01 >> >> >> Assuming that I did demean covariates appropriately, I proceeded with >> stats analysis. However, when I click "analyze" on QDEC, the >> following messages appear in the command window which concerned me if >> I have correctly demeaned for my covariate variables or not: >> >> >> INFO: DeMeanFlag keyword not found, DeMeaning will NOT be done. >> >> Continuous Variable Means (all subjects) >> >> 0 Age -3.88583e-08 0.997616 >> >> 1 SA 2.47776e-08 0.997616 >> >> Class Means of each Continuous Variable >> >> 1 diagnosisTD0.02160.1167 >> >> 2 diagnosisADHD-0.0528-0.2850 >> >> Again, at the end of the analysis: >> >> >> INFO: NOT demeaning continuous variables >> >> Continuous Variable Means (all subjects) >> >> 0 Age -2.75051e-08 0.997616 >> >> 1 SA 1.94509e-07 0.997616 >> >> Class Means of each Continuous Variable >> >> 1 diagnosisTD 0.02160.1167 >> >> 2 diagnosisADHD-0.0528-0.2850 >> >> >> Will you please tell me if I have correctly demeaned my covariates or >> not? If not, will you please tell me how I Can do this? >> >> >> Thanks so much, >> >> >> Avi >> >> >> >> >> CONFIDENTIALITY NOTICE: This e-mail message, including any >> attachments, is for the sole use of the intended recipient(s) and may >> contain confidential and privileged information. Any unauthorized >> review, use, disclosure or distribution is prohibited. If you are not >> the intended recipient, please contact the sender by reply e-mail and >> destroy all copies of the original message. >> >> AVIS DE CONFIDENTIALITÉ : Ce message électronique, ainsi que tout >> fichier qui y est joint, est reserve à l'usage exclusif du >> destinataire visé et peut contenir des renseignements confidentiels >> et privilégiés. Toute lecture, utilisation, divulgation ou >> distribution non autorisée est interdite. Si vous n'êtes pas le >> destinataire visé, veuillez en aviser l'expéditeur par retour de >> courriel et détruire toutes les copies du message original. >> >> >> _______________________________________________ >> Freesurfer mailing list >> Freesurfer(a)nmr.mgh.harvard.edu >> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer >

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Clarification on interpreting results
by Avideh Gharehgazlou 06 Mar '18

06 Mar '18

Hi, I have a 2 questions regarding properly interpreting results from QDEC. Will you please clarify the following for me? 1. What is the difference between stats table generated after correcting for multiple comparisons (i.e. monte carlo), vs the stats table generated after clicking "find clusters and go to max"? Results from which stats table should be reported? After searching on the web, I am still unclear about what exactly "find clusters and go to max" button does... and whether these are corrected results or not? 2. My understanding is that "CWP" column in stats table represents p-values of each cluster. However, when I manually convert values in the "max" column (which I assume are freesurfer p-values reported in -log(10)), I get different p-values than what are listed in "CWP" column for each cluster. Again, my question is whether I should report "CWP" values as my p-values or convert manually myself and report those? I would really appreciate your help! Thanks so much, Avi CONFIDENTIALITY NOTICE: This e-mail message, including any attachments, is for the sole use of the intended recipient(s) and may contain confidential and privileged information. Any unauthorized review, use, disclosure or distribution is prohibited. If you are not the intended recipient, please contact the sender by reply e-mail and destroy all copies of the original message. AVIS DE CONFIDENTIALITÉ : Ce message électronique, ainsi que tout fichier qui y est joint, est reserve à l'usage exclusif du destinataire visé et peut contenir des renseignements confidentiels et privilégiés. Toute lecture, utilisation, divulgation ou distribution non autorisée est interdite. Si vous n'êtes pas le destinataire visé, veuillez en aviser l'expéditeur par retour de courriel et détruire toutes les copies du message original.

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freeview for FS-FAST results
by stdp82＠virgilio.it 06 Mar '18

06 Mar '18

Hi list, is it possible to avoid the clusters < 5 voxels using freeview for FS-FAST results (mni.305) obtained after running mri_glmfit-sim --glmdir my-glm.wls --grf? Thanks Kind regards Stefano

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Demeaning covariates correctly?
by Avideh Gharehgazlou 06 Mar '18

06 Mar '18

Hi experts, I'm using QDEC to look at between group differences in LGI. According to a previous post I demeaned my covariates (age and surface area) inputted in my qdec.table.dat file by subtracting each value (i.e. each age) by the mean of all participant's ages and dividing it by the standard deviation of all participant's ages. When I upload qdec.table.dat file onto QDEC, it states the following: Mean STD Age -0 1 Surface area 0 1 Assuming that I did demean covariates appropriately, I proceeded with stats analysis. However, when I click "analyze" on QDEC, the following messages appear in the command window which concerned me if I have correctly demeaned for my covariate variables or not: INFO: DeMeanFlag keyword not found, DeMeaning will NOT be done. Continuous Variable Means (all subjects) 0 Age -3.88583e-08 0.997616 1 SA 2.47776e-08 0.997616 Class Means of each Continuous Variable 1 diagnosisTD 0.0216 0.1167 2 diagnosisADHD -0.0528 -0.2850 Again, at the end of the analysis: INFO: NOT demeaning continuous variables Continuous Variable Means (all subjects) 0 Age -2.75051e-08 0.997616 1 SA 1.94509e-07 0.997616 Class Means of each Continuous Variable 1 diagnosisTD 0.0216 0.1167 2 diagnosisADHD -0.0528 -0.2850 Will you please tell me if I have correctly demeaned my covariates or not? If not, will you please tell me how I Can do this? Thanks so much, Avi CONFIDENTIALITY NOTICE: This e-mail message, including any attachments, is for the sole use of the intended recipient(s) and may contain confidential and privileged information. Any unauthorized review, use, disclosure or distribution is prohibited. If you are not the intended recipient, please contact the sender by reply e-mail and destroy all copies of the original message. AVIS DE CONFIDENTIALITÉ : Ce message électronique, ainsi que tout fichier qui y est joint, est reserve à l'usage exclusif du destinataire visé et peut contenir des renseignements confidentiels et privilégiés. Toute lecture, utilisation, divulgation ou distribution non autorisée est interdite. Si vous n'êtes pas le destinataire visé, veuillez en aviser l'expéditeur par retour de courriel et détruire toutes les copies du message original.

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Fwd: Question-optseq2
by Mora Alvarez, Maria 06 Mar '18

06 Mar '18

Hi, I’m interested in using optseq2 to optimize my experiment, but I wonder if the software was programmed for optimizing experiments such as the Attention network test, where some cues are presented before the stimuli (See below) [cid:D6F85C6A-6306-43C5-801E-54C09C00A93D] Ref. Fan et al Neuroimage 2005 Thank you very much and warm regards, Maria Mora

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Re: [Freesurfer] analysing scans other than brain
by Antonin Skoch 06 Mar '18

06 Mar '18

Dear Matyas, this (not brain-specific) R package will be maybe more suitable for your purpose: http://onlinelibrary.wiley.com/doi/10.1111/2041-210X.12035/full https://cran.r-project.org/web/packages/geomorph/index.html I generally would recommend to rather look for packages used in community of anthropologists or evolutional biologists. Antonin Hi Matyas we have online tutorials on our wiki and data you can download. Not sure how easy it will be though - a lot of what we do is brain specific Bruce On Mon, 5 Mar 2018, Matyas Varga wrote: Dear Bruce, Thank you for your quick reply. I think that whatever software I am going to use, it will require some coding as most similar software are brain specific. I use Matlab on a regular basis, and am happy to learn c in order to complete this project. My ultimate aim is to create a software or adapt an existing one for use on feet, for podiatrist and researchers. I was wondering if you could give me some suggestions as to where to start this using Free Surfer? Thank you. Best Regards Matyas Varga School of Health Sciences Research University of Brighton Aldro Building, 49 Darley Road Eastbourne, BN20 7UR -----Original Message----- From: freesurfer-boun...(a)nmr.mgh.harvard.edu [mailto:freesurfer-boun...@nmr.mgh.harvard.edu] On Behalf Of Bruce Fischl Sent: 05 March 2018 17:05 To: Freesurfer support list <freesurfer(a)nmr.mgh.harvard.edu> Subject: Re: [Freesurfer] analysing scans other than brain Hi Matyas it is possible, but will be a fair amount of work, probably including some c coding since many of our tools are brain-specific cheers Bruce On Mon, 5 Mar 2018, Matyas Varga wrote: Dear Free Surfer, I was wondering if it was possible to analyse (surface-based morphometry and SPM) NOT brain scans. I am doing my PhD looking at how the shape of children’s feet change as they get older (2-7 years old). I will use a 3D scanner which will provide me with a mesh of triangles of the foot and I am considering to create average age group foot shapes and compare them using surface based morphometry and SPM. I will obviously have to create my own foot ”atlas”. I was wondering if this was possible in Free Surfer? Please let me know if it is possible or if you have any suggestions if it is not. Thank you. Best Regards Matyas Varga PhD student School of Health Sciences Research University of Brighton Aldro Building, 49 Darley Road Eastbourne, BN20 7UR Tel: 01273 644189 ___________________________________________________________ This email has been scanned by MessageLabs' Email Security System on behalf of the University of Brighton. For more information see: https://staff.brighton.ac.uk/is/computing/Pages/Email/spam.aspx ___________________________________________________________ This email has been scanned by MessageLabs' Email Security System on behalf of the University of Brighton. For more information see: https://staff.brighton.ac.uk/is/computing/Pages/Email/spam.aspx ___________________________________________________________ This email has been scanned by MessageLabs' Email Security System on behalf of the University of Brighton. For more information see: https://staff.brighton.ac.uk/is/computing/Pages/Email/spam.aspx _______________________________________________ Freesurfer mailing list Freesurfer(a)nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer _______________________________________________ Freesurfer mailing list Freesurfer(a)nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer

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San Diego NIAAA T32 Postdoc Opening
by Eileen Moore 05 Mar '18

05 Mar '18

San Diego NIAAA T32 Postdoc Position Opening Announcement A postdoctoral position in alcohol research is available now through an NIAAA T32 institutional training grant between SDSU and UCSD in San Diego, CA. Postdoctoral appointees are supported for twelve-month, full-time appointments with the ability to receive up to two years of support based upon acceptable progress during their initial year. Qualified candidates must be U.S. citizens (or permanent resident or noncitizen national of the U.S.) and have completed their doctoral degree requirements in the clinical and behavioral sciences. Specific areas of alcohol research include fetal alcohol spectrum disorders, adolescent and adult alcohol/substance use disorders, risk and protective factors for alcoholism, alcohol and brain disease, neurobiological/behavioral effects of alcoholism, neuropsychological function, structural and functional neuroimaging, interventions, and psychiatric and medical comorbidity. Fellows will conduct research with their mentor, including comprehensive literature reviews and participation in data collection and analysis. Fellows are expected to become involved in manuscript and grant writing, to participate in alcohol research training program seminars, and present at national meetings (e.g., Research Society on Alcoholism). Faculty mentors include Drs. Edward Riley (Director), Susan Tapert (co-Director), Robert Anthenelli, Kara Bagot, Sandra A. Brown, Mariana Cherner, Cindy Ehlers, Jay Giedd, Igor Grant, Joanna Jacobus, Terry Jernigan, Ksenija Marinkovic, Sarah Mattson, David Moore, Mark Myers, Sonya Norman, Marc Schuckit, Andrea Spadoni, Michael Taylor, Jennifer Thomas, Ryan Trim, Tamara Wall, and Matt Worley. To apply please complete the online form (http://niaaa-t32.sdsu.edu/apply/) and submit your CV, personal statement, and the names of three references to Edward Riley's assistant, Jill Vander Velde, at vanderv(a)mail.sdsu.edu.

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Skull stripping error - too much brain lost
by Matthew Grecsek 05 Mar '18

05 Mar '18

Following your advice below, it was clearly apparent that the output from the skull stripping step was missing a lot. I tried adjusting the -wsthresh flag from 50 -> 200 and it still left major parts of the brain out. I have a good quality mri and subject with no known anatomical abnormalities. The log file indicates "surface validation has detected possible Error" Does this suggest a more meaningful defect in the base image or something that can be corrected via other parameters or manual editing? Log file attached. Thanks, -Matt Bruce Fischl Fri, 02 Mar 2018 08:00:11 -0800 Hi Matt check the output of the skull stripping. This error usually means that too much (everything?) has been erased and no plausible cc could be found cheers Bruce On Thu, 1 Mar 2018, Matthew Grecsek wrote: My recon-all ended prematurely with the following message: final transformation (x=136.0, yr=-10.054, zr=-0.114): 0.98464 0.00200 -0.17457 15.51372; -0.00197 1.00000 0.00035 17.22442; 0.17457 0.00000 0.98464 -17.83761; 0.00000 0.00000 0.00000 1.00000; mri_cc: no WM voxels found with norm > 40 -- check skull stripping No such file or directory Linux centos-7-1 3.10.0-693.17.1.el7.x86_64 #1 SMP Thu Jan 25 20:13:58 UTC 2018 x86_64 x86_64 x86_64 GNU/Linux recon-all -s matt2 exited with ERRORS at Thu Mar 1 04:35:09 UTC 2018 I am running: freesurfer-Linux-centos6_x86_64-stable-pub-v6.0.0-2beb96c My full log file is attached. Please let me know suggestions for correcting and continuing the process. Thanks, -Matt _______

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Re: [Freesurfer] Extraction of cortical thickness in native space
by Albrecht, Daniel S. 05 Mar '18

05 Mar '18

Thanks, Doug! I think we were probably going about this the wrong way. If I transform the ROI from MNI space back into native space, will the following commands give the proper cortical thickness extraction from native space? mri_vol2surf --mov roi_in_native_space.nii.gz --out rh.roi_in_native_space.mgh --hemi rh --regheader ${subj} #Check surface placement with: tksurfer ${subj} rh inflated -overlay rh.roi_in_native_space.mgh -fthresh 1 cd $FSdir/$subj/surf mri_segstats --seg /path_to rh.roi_in_native_space.mgh --in rh.thickness --sum segstats-rh.roi_ns.txt Thanks, Dan

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Fwd: mri_glmfit-sim --surf question
by Adam Mecca 05 Mar '18

05 Mar '18

Hello FreeSurfer Developers, I have run a glm on the left hemisphere to compare cortical thickness between 2 groups. After, I did a cluster-wise correction with permutation testing using this command mri_glmfit-sim --glmdir lh.sv2a_group.glmdir.10 --perm 1000 2 abs It completes without error, but I have a question about the log file and --surf argument. My concern if about this part of the log file where it shows "--surf fsaverage lh white" (see section from log file and complete log file attached). White is the default I based on the help file for mri_glmfit. Should I be running with --surf fsaverage lh pial? Does this imply that the glm is performed on the white matter surface. I am then visualizing on the inflated pial surface so does this cause a problem? ------------------------------------------------------------ -------------------------------------------------- 1/1 Fri Mar 2 03:23:25 EST 2018 mri_glmfit --C lh.sv2a_group.glmdir.10/tmp.mri_glmfit-sim-13158/sv2a_thickness_group.mtx --sim perm 1000 2 lh.sv2a_group.glmdir.10/csd/perm.th20.abs.j001 --sim-sign abs --fwhm 0 --fsgd lh.sv2a_group.glmdir.10/y.fsgd dods --y lh.sv2a.group.thickness.10.mgh --mask lh.sv2a_group.glmdir.10/mask.mgh --surf fsaverage lh white simbase lh.sv2a_group.glmdir.10/csd/perm.th20.abs.j001 FWHM = 0.000000 gdfRead(): reading lh.sv2a_group.glmdir.10/y.fsgd INFO: gd2mtx_method is dods Reading source surface /home1/am2359/fs6_data/fpeb_ app_fs/fsaverage/surf/lh.white --------------------------------------------------- Thank you, Adam

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