Freesurfer November 2016

freesurfer@nmr.mgh.harvard.edu

120 participants
214 discussions

tracula: thresholding in pathstats.byvoxel
by Knut J Bjuland 21 Nov '16

21 Nov '16

Hi, We have two subjects, one with a lhcab that looks ~OK (somewhat noisy) and one with a lhcab that is almost completely missing (please see attached figures). And yet, looking at their respective pathstats.byvoxel.txt (under dpath/lh.cab_PP_avg33_mni_bbr) we find that both have data for this tract and that the subject with a seemingly missing tract (70) has more observations. Is this a thresholding issue? The default threshold in Freeview when viewing these files is 20% of the 99th percentile of the posterior probability distribution for the path, so how does that affect the data in pathstats.byvoxel and pathstats.overall; are they also thresholded? # subjectname 17 # pathwayname lh.cab # # pathway start x y z AD RD MD FA AD_Avg RD_Avg MD_Avg FA_Avg 56 35 27 0.000890712 0.000603441 0.000699198 0.315126 0.00105762 0.000596839 0.000750432 0.362276 56 36 26 0.00107635 0.000545558 0.000722489 0.41169 0.00104539 0.000615595 0.000758858 0.335287 56 37 26 0.00106187 0.000590571 0.000747672 0.372333 0.00105743 0.000602726 0.000754296 0.354483 56 38 25 0.00102202 0.000600078 0.000740726 0.368605 0.00100576 0.000632157 0.000756689 0.313797 56 39 25 0.00119029 0.000522558 0.000745135 0.485075 0.00107733 0.000611676 0.00076689 0.358958 56 39 24 0.000901928 0.000700433 0.000767598 0.204508 0.0010547 0.000622021 0.000766243 0.338646 56 40 24 0.000983715 0.000610012 0.00073458 0.333454 0.00105292 0.000634273 0.00077382 0.330426 56 41 23 0.00109975 0.000657692 0.000805043 0.318553 0.00115473 0.000602686 0.000786698 0.395328 57 42 23 0.00119796 0.000512441 0.000740946 0.50737 0.00119982 0.00058122 0.000787428 0.43539 57 43 22 0.00108816 0.000588772 0.000755234 0.368538 0.00120245 0.000589771 0.000793995 0.417918 57 44 22 0.00145913 0.000457154 0.000791146 0.628211 0.00131065 0.000556036 0.00080757 0.48867 57 45 21 0.00142093 0.000463346 0.000782542 0.617307 0.0013404 0.000544065 0.000809509 0.514237 57 46 21 0.00142182 0.000445771 0.000771122 0.632204 0.00139366 0.000547482 0.000829538 0.525517 57 47 20 0.000968663 0.000475497 0.000639886 0.434747 0.001285 0.000583274 0.000817181 0.448241 58 48 19 0.00121939 0.000531887 0.000761053 0.482488 0.00133092 0.000590401 0.000837236 0.462653 58 49 19 0.00159589 0.000576742 0.000916457 0.569308 0.00136598 0.000635182 0.000878787 0.437028 58 50 19 0.00164139 0.000624262 0.000963304 0.549971 0.00138664 0.000658869 0.000901467 0.426815 58 50 18 0.00157653 0.000942457 0.00115382 0.332295 0.00137177 0.000715268 0.000934107 0.385317 58 51 18 0.00118225 0.000642473 0.0008224 0.36823 0.00118518 0.000684428 0.000851342 0.330996 58 52 18 0.00109238 0.000519084 0.000710181 0.435882 0.00107605 0.000632073 0.000780059 0.324378 58 53 18 0.00129725 0.000623659 0.000848189 0.430382 0.00108778 0.000647922 0.000794535 0.315793 # pathway end # subjectname 70 # pathwayname lh.cab # # pathway start x y z AD RD MD FA AD_Avg RD_Avg MD_Avg FA_Avg 53 32 26 0.00117731 0.000928949 0.00101174 0.143923 0.00116391 0.00090839 0.000993563 0.153213 53 33 26 0.0010364 0.000859843 0.000918695 0.128905 0.00103869 0.000848443 0.000911856 0.138848 53 33 25 0.00105938 0.000877392 0.000938055 0.127225 0.00105752 0.000865256 0.000929355 0.135088 54 34 25 0.000944648 0.000719044 0.000794246 0.162868 0.000957389 0.000725472 0.000802768 0.16744 54 35 25 0.000972687 0.000738523 0.000816578 0.208351 0.000986717 0.000739063 0.000821629 0.213113 54 36 24 0.00101603 0.000621378 0.000752929 0.305637 0.0010253 0.000631396 0.000762693 0.302995 54 37 24 0.00113992 0.000642822 0.000808521 0.369124 0.0011217 0.000646204 0.000804698 0.353409 55 38 23 0.000890718 0.000584601 0.00068664 0.265622 0.000916719 0.000590972 0.000699556 0.273432 55 39 23 0.0013084 0.000657441 0.000874427 0.41632 0.00129438 0.000656492 0.000869102 0.409684 55 40 22 0.000897226 0.000549981 0.000665729 0.294657 0.000926128 0.000565056 0.000685412 0.294239 56 41 22 0.00129446 0.000643583 0.000860544 0.416518 0.00128053 0.000641873 0.000854761 0.410811 56 42 21 0.00095897 0.000527739 0.000671483 0.356436 0.000986408 0.00054246 0.000690451 0.355442 56 43 21 0.00126047 0.000576778 0.000804674 0.460586 0.00120436 0.000578402 0.000787051 0.4315 57 44 21 0.00141709 0.000815438 0.00101599 0.333322 0.00136115 0.000786714 0.000978188 0.330026 57 45 20 0.00107155 0.000547688 0.000722309 0.398732 0.0010439 0.000565023 0.000724638 0.366345 57 46 19 0.00106184 0.000688623 0.000813027 0.276355 0.00106565 0.000721324 0.000836098 0.250311 58 46 18 0.00138626 0.00111282 0.00120397 0.13344 0.00133896 0.00105932 0.00115254 0.147013 58 46 17 0.00190569 0.00154603 0.00166592 0.127639 0.0017048 0.00136742 0.0014799 0.141036 58 47 17 0.00182424 0.00136918 0.00152086 0.176476 0.00170912 0.00128364 0.00142549 0.178103 58 48 17 0.00179186 0.00155183 0.00163184 0.121897 0.0016827 0.00141198 0.00150224 0.137642 58 49 17 0.00173965 0.00152012 0.00159329 0.0828833 0.00156972 0.00134741 0.00142152 0.101404 58 50 17 0.00146827 0.00123617 0.00131354 0.105179 0.0013648 0.00113875 0.00121408 0.115824 59 51 17 0.000939683 0.000730799 0.000800427 0.151144 0.000913724 0.000729779 0.000791094 0.140851 59 52 17 0.000973182 0.000776841 0.000842288 0.136551 0.000937145 0.000762049 0.00082041 0.130533 59 53 17 0.000974158 0.000799803 0.000857921 0.120722 0.000938325 0.000778099 0.000831516 0.119775 59 54 17 0.00100004 0.000821513 0.000881023 0.135361 0.000956475 0.000793336 0.000847705 0.130042 # pathway end Thank you! sincerely yours, Knut Jørgen Bjuland, PhD Sørlandet sykehus [cid:BD078F74-6DFE-4119-A9F0-74B08B4DE0AF][cid:C07C98A4-AE40-4782-BD2A-9432409D7FCB]

1 0

Fwd:
by Emmanuel Nwosu 21 Nov '16

21 Nov '16

Hi Am having a bit of a problem that may be easy to resolve. I want to view an LGI two-group comparison I did in mri glm-fit with freeview. Each time I load the overlay (cache.th13.abs.sig.cluster.mgh). The grayscale inflated surface turns red like what is in picture-1 Please have anyone an idea why this is happening and what I can do to change it back to grayscale like picture 2 Thanks for your help Emmanuel

1 0

Hippocampal segmentation
by Rowa Aljondi 20 Nov '16

20 Nov '16

Hello Freesurfer Developers, I'm willing to use the new released version from Freesurfer (6.7.0) to measure the hippocampal volumes. Is that able to provide me the volumes of the anterior (hippocampal head) and posterior (hippocampal tail) parts of the Hippocampus and segmented these parts separately? Thanks, Rowa -- Rowa Aljondi PhD Candidate Faculty of Medicine, Dentistry and Health Sciences The University of Melbourne M: +61 416565756

1 0

fsaverage_sym LR-flipchecks
by James Roe 20 Nov '16

20 Nov '16

? Hi Freesurfer experts I have an ultimate goal of performing direct LH v RH comparisons using the fsaverage_sym template, so these pre-analysis steps are aiming to assess the symmetry of the template. I have performed a first-level fMRI analysis on a subject and am using this to compare the output with the exact same analysis performed on the same subject with LR-flipped data (anatomical, BOLD runs and B0 maps). I then ran recon-all on this flipped subject (treating flipped subject as new subject). Attached is a screenshot showing the different analysis outputs. In the top left image, analyses have been performed and smoothed on fsaverage_sym (RH shows LH flipped anat and BOLD data). As you can see, agreement is generally high, but there are also marked differences, most notably in postcentral/precentral regions. The bottom left shows this output resampled onto the individual surface (for comparison purposes for the next analysis). The top right image shows the output when analyses were performed on the individual surfaces of the original and flipped subject. Here, agreement seems much higher, also in postcentral/precentral regions (although still not symmetrical). The bottom right image shows this output resampled onto fsaverage_sym, and agreement remains very high. So it seems that performing the analysis on fsaverage_sym itself may be affecting the expected symmetry of the output. Originally I aimed to perform a comparison of the vectors of B-values in order to prove symmetry, although I am not sure whether this is a viable option anymore. Do you have any advice as to how I could proceed with this? Finally, it appears that also in the fsaverage_sym template the L/R vertices do not correspond to one another. So will it be possible to flip the analysis values and template in order to perform LH v RH comparisons at the group level? System: Linux CentOS 6 x86_64 (64b) stable v5.3.0 Thank you for your time James

3 7

Freesurfer 6 beta testing: mri_glmfit-sim error
by Elijah Mak 19 Nov '16

19 Nov '16

Hi Freesurfer Team, I came across the following error while running mri_glmfit-sim. What is vwsigmax? Thanks for your help again. The full log is as follows: $Id: FreeSurferEnv.csh,v 1.89 2016/06/09 14:54:31 zkaufman Exp $ Sat Nov 19 02:00:45 GMT 2016 Darwin dhcp-10-240-201-24.cp.wireless.private.cam.ac.uk 14.5.0 Darwin Kernel Version 14.5.0: Thu Jun 16 19:58:21 PDT 2016; root:xnu-2782.50.4~1/RELEASE_X86_64 x86_64 MacPro setenv SUBJECTS_DIR /Volumes/TITAN/cth_wmh_study FREESURFER_HOME //Users/MacPro/Documents/freesurfer_b6 Original mri_glmfit command line: cmdline mri_glmfit.bin --y y.mgh --fsgd FSGDs/FSGD_Z_cthVsCTH_AD_age dods --C Contrasts/C --surf fsaverage lh --cortex --glmdir Glmdirs/ProjectAD DoSim = 0 UseCache = 1 DoPoll = 0 DoPBSubmit = 0 DoBackground = 0 DiagCluster = 0 gd2mtx = dods fwhm = 20.927757 CSD //Users/MacPro/Documents/freesurfer_b6/average/mult-comp-cor/fsaverage/lh/cortex/fwhm21/abs/th30/mc-z.csd mri_surfcluster --in Glmdirs/ProjectAD/C/sig.mgh --mask Glmdirs/ProjectAD/mask.mgh --cwsig Glmdirs/ProjectAD/C/cache.th30.abs.sig.cluster.mgh --sum Glmdirs/ProjectAD/C/cache.th30.abs.sig.cluster.summary --ocn Glmdirs/ProjectAD/C/cache.th30.abs.sig.ocn.mgh --annot aparc --cwpvalthresh 0.05 --o Glmdirs/ProjectAD/C/cache.th30.abs.sig.masked.mgh --no-fixmni --csd //Users/MacPro/Documents/freesurfer_b6/average/mult-comp-cor/fsaverage/lh/cortex/fwhm21/abs/th30/mc-z.csd --csdpdf Glmdirs/ProjectAD/C/cache.th30.abs.pdf.dat --vwsig Glmdirs/ProjectAD/C/cache.th30.abs.sig.voxel.mgh --vwsigmax Glmdirs/ProjectAD/C/cache.th30.abs.sig.voxel.max.dat --oannot Glmdirs/ProjectAD/C/cache.th30.abs.sig.ocn.annot --bonferroni 2 --surf white ERROR: Option --vwsigmax unknown Best Wishes, Elijah

2 1

Re: [Freesurfer] Longitudinal surface analysis of PET data
by Matthieu Vanhoutte 19 Nov '16

19 Nov '16

Dear Freesurfer's experts, I come back to you concerning questions of registrations. Since during the longitudinal process each --long subject directory has been registered onto the common --base template, shouldn't I: 1) Register PET data onto the subject cross-sectional directory (native data) with rigid-body transformation 2) Then take into account the registration between --cross and --long directory subject and apply the registration to the PET first registered onto native space ? In this case, how and where is this transformation has been saved ? Best regards, Matthieu 2016-09-30 23:05 GMT+02:00 Douglas N Greve <greve(a)nmr.mgh.harvard.edu>: > Yes > > > On 09/30/2016 05:05 PM, Matthieu Vanhoutte wrote: > > > > Hi Douglas, > > > > Does the surface of the closest MRI time point mean the surface of the > > -long subject time point directory rather than cross-sectional subject > > time point directory ? > > > > Best regards, > > Matthieu > > > > > > Le 30 sept. 2016 9:14 PM, "Douglas N Greve" <greve(a)nmr.mgh.harvard.edu > > <mailto:greve@nmr.mgh.harvard.edu>> a écrit : > > > > There is no such long process for PET. The idea is that you > > process the > > MRI in a longitudinal way, then sample the PET data onto the > > surface of > > the closest MRI time point. Then proceed in a way similar to the > > thickness analysis > > > > > > On 09/29/2016 11:08 AM, Matthieu Vanhoutte wrote: > > > Dear Freesurfer's experts, > > > > > > Could you answer me about my last question with no response in the > > > mail below ? > > > > > > When using cortical thickness in longitudinal analysis with LME, we > > > used lh.thickness or rh.thickness from -long subject directories. > > > These data followed particular processing steps including > > > registrations in order to use them with more precision in > > longitudinal > > > studies, didn't they ? > > > > > > My problem is that I would like to perform longitudinal study on > PET > > > data images with LME. So I wonder if I just have to resample onto > > > -long cortical subject surface ? Do I need to follow the same steps > > > than cortical thickness from cross-sectional to -long subject > > > directories ? If this is the case, which commands should I use to > > > mimic cortical thickness longitudinal data ? > > > > > > Many thanks in advance for helping ! > > > > > > Best regards, > > > Matthieu > > > > > > 2016-09-18 23:02 GMT+02:00 Matthieu Vanhoutte > > > <matthieuvanhoutte(a)gmail.com > > <mailto:matthieuvanhoutte@gmail.com> > > <mailto:matthieuvanhoutte@gmail.com > > <mailto:matthieuvanhoutte@gmail.com>>>: > > > > > > Hi Martin, > > > > > > Thanks for your answer. However, it seems to me that cortical > > > thickness follow a particular process with the recon-all -long > > > process, isn’t it ? Is there any resample onto average time > > > subject then other operation following ? > > > > > > Best regards, > > > Matthieu > > > > > > > Le 18 sept. 2016 à 16:26, Martin Reuter > > > <mreuter(a)nmr.mgh.harvard.edu > > <mailto:mreuter@nmr.mgh.harvard.edu> > > <mailto:mreuter@nmr.mgh.harvard.edu > > <mailto:mreuter@nmr.mgh.harvard.edu>>> > > > a écrit : > > > > > > > > Hi Matthieu, > > > > > > > > I never used PET data, but once you manage to resample you > pet > > > data onto the surface, you will have a file similar to the > > > thickness file for each subjects. Instead of thickness it holds > > > you PET information. From that point on everything should be > > > identical to the thickness analysis. > > > > > > > > So this is really more a question how to get your PET data > > > sampled onto the surface. If no one else replies, write that > > into > > > the subject line and repost. > > > > > > > > Best, Martin > > > > > > > > > > > >> On Sep 17, 2016, at 7:37 AM, Matthieu Vanhoutte > > > <matthieuvanhoutte(a)gmail.com > > <mailto:matthieuvanhoutte@gmail.com> > > <mailto:matthieuvanhoutte@gmail.com > > <mailto:matthieuvanhoutte@gmail.com>>> > > > wrote: > > > >> > > > >> Dear Freesurfer’s experts, > > > >> > > > >> I would like to use the longitudinal mixed-effects model for > > > surface PET analysis. Although I could find all the process to > > > follow the longitudinal analysis of cortical thickness, I > > couldn’t > > > resolve the steps/commands to apply successively to > coregistered > > > PET data on T1 MRI. > > > >> > > > >> Could you precise me the process and commands to use for PET > > > longitudinal analysis ? > > > >> > > > >> Many thanks in advance ! > > > >> > > > >> Best regards, > > > >> Matthieu > > > >> _______________________________________________ > > > >> Freesurfer mailing list > > > >> Freesurfer(a)nmr.mgh.harvard.edu > > <mailto:Freesurfer@nmr.mgh.harvard.edu> > > > <mailto:Freesurfer@nmr.mgh.harvard.edu > > <mailto:Freesurfer@nmr.mgh.harvard.edu>> > > > >> > > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer > > <https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer> > > > > > <https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer > > <https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer>> > > > >> > > > >> > > > > > > > > > > > > _______________________________________________ > > > > Freesurfer mailing list > > > > Freesurfer(a)nmr.mgh.harvard.edu > > <mailto:Freesurfer@nmr.mgh.harvard.edu> > > > <mailto:Freesurfer@nmr.mgh.harvard.edu > > <mailto:Freesurfer@nmr.mgh.harvard.edu>> > > > > > > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer > > <https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer> > > > > > <https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer > > <https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer>> > > > > > > > > > > > > The information in this e-mail is intended only for the > person > > > to whom it is > > > > addressed. If you believe this e-mail was sent to you in > error > > > and the e-mail > > > > contains patient information, please contact the Partners > > > Compliance HelpLine at > > > > http://www.partners.org/complianceline > > <http://www.partners.org/complianceline> > > > <http://www.partners.org/complianceline > > <http://www.partners.org/complianceline>> . If the e-mail was sent > > > to you in error > > > > but does not contain patient information, please contact the > > > sender and properly > > > > dispose of the e-mail. > > > > > > > > > > > > > > > _______________________________________________ > > > Freesurfer mailing list > > > Freesurfer(a)nmr.mgh.harvard.edu > > <mailto:Freesurfer@nmr.mgh.harvard.edu> > > > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer > > <https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer> > > > > -- > > Douglas N. Greve, Ph.D. > > MGH-NMR Center > > greve(a)nmr.mgh.harvard.edu <mailto:greve@nmr.mgh.harvard.edu> > > Phone Number: 617-724-2358 <tel:617-724-2358> > > Fax: 617-726-7422 <tel:617-726-7422> > > > > Bugs: surfer.nmr.mgh.harvard.edu/fswiki/BugReporting > > <http://surfer.nmr.mgh.harvard.edu/fswiki/BugReporting> > > FileDrop: https://gate.nmr.mgh.harvard.edu/filedrop2 > > <https://gate.nmr.mgh.harvard.edu/filedrop2> > > www.nmr.mgh.harvard.edu/facility/filedrop/index.html > > <http://www.nmr.mgh.harvard.edu/facility/filedrop/index.html> > > Outgoing: > > ftp://surfer.nmr.mgh.harvard.edu/transfer/outgoing/flat/greve/ > > <ftp://surfer.nmr.mgh.harvard.edu/transfer/outgoing/flat/greve/> > > > > _______________________________________________ > > Freesurfer mailing list > > Freesurfer(a)nmr.mgh.harvard.edu <mailto:Freesurfer@nmr.mgh. > harvard.edu> > > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer > > <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 > > -- > Douglas N. Greve, Ph.D. > MGH-NMR Center > greve(a)nmr.mgh.harvard.edu > Phone Number: 617-724-2358 > Fax: 617-726-7422 > > Bugs: surfer.nmr.mgh.harvard.edu/fswiki/BugReporting > FileDrop: https://gate.nmr.mgh.harvard.edu/filedrop2 > www.nmr.mgh.harvard.edu/facility/filedrop/index.html > Outgoing: ftp://surfer.nmr.mgh.harvard.edu/transfer/outgoing/flat/greve/ > > _______________________________________________ > Freesurfer mailing list > Freesurfer(a)nmr.mgh.harvard.edu > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer >

3 8

tracula: thresholding in pathstats.byvoxel
by Lars M. Rimol 19 Nov '16

19 Nov '16

Hi, I have two subjects, one with a lhcab that looks ok (more or less noisy but it's there) and one with a lhcab that is almost completely missing (please see attached figures). And yet, when I look at their respective pathstats.byvoxel.txt (under dpath/lh.cab_PP_avg33_mni_bbr) I find that both have data for this tract and that the subject with a seemingly missing tract (70) has more observations. Is this a thresholding issue? Which brings me to: The default threshold in Freeview when viewing these files is 20% of the 99th percentile of the posterior probability distribution for the path, so I was wondering how that affects the data in pathstats.byvoxel and pathstats.overall; are they also thresholded? # subjectname 17 # pathwayname lh.cab # # pathway start x y z AD RD MD FA AD_Avg RD_Avg MD_Avg FA_Avg 56 35 27 0.000890712 0.000603441 0.000699198 0.315126 0.00105762 0.000596839 0.000750432 0.362276 56 36 26 0.00107635 0.000545558 0.000722489 0.41169 0.00104539 0.000615595 0.000758858 0.335287 56 37 26 0.00106187 0.000590571 0.000747672 0.372333 0.00105743 0.000602726 0.000754296 0.354483 56 38 25 0.00102202 0.000600078 0.000740726 0.368605 0.00100576 0.000632157 0.000756689 0.313797 56 39 25 0.00119029 0.000522558 0.000745135 0.485075 0.00107733 0.000611676 0.00076689 0.358958 56 39 24 0.000901928 0.000700433 0.000767598 0.204508 0.0010547 0.000622021 0.000766243 0.338646 56 40 24 0.000983715 0.000610012 0.00073458 0.333454 0.00105292 0.000634273 0.00077382 0.330426 56 41 23 0.00109975 0.000657692 0.000805043 0.318553 0.00115473 0.000602686 0.000786698 0.395328 57 42 23 0.00119796 0.000512441 0.000740946 0.50737 0.00119982 0.00058122 0.000787428 0.43539 57 43 22 0.00108816 0.000588772 0.000755234 0.368538 0.00120245 0.000589771 0.000793995 0.417918 57 44 22 0.00145913 0.000457154 0.000791146 0.628211 0.00131065 0.000556036 0.00080757 0.48867 57 45 21 0.00142093 0.000463346 0.000782542 0.617307 0.0013404 0.000544065 0.000809509 0.514237 57 46 21 0.00142182 0.000445771 0.000771122 0.632204 0.00139366 0.000547482 0.000829538 0.525517 57 47 20 0.000968663 0.000475497 0.000639886 0.434747 0.001285 0.000583274 0.000817181 0.448241 58 48 19 0.00121939 0.000531887 0.000761053 0.482488 0.00133092 0.000590401 0.000837236 0.462653 58 49 19 0.00159589 0.000576742 0.000916457 0.569308 0.00136598 0.000635182 0.000878787 0.437028 58 50 19 0.00164139 0.000624262 0.000963304 0.549971 0.00138664 0.000658869 0.000901467 0.426815 58 50 18 0.00157653 0.000942457 0.00115382 0.332295 0.00137177 0.000715268 0.000934107 0.385317 58 51 18 0.00118225 0.000642473 0.0008224 0.36823 0.00118518 0.000684428 0.000851342 0.330996 58 52 18 0.00109238 0.000519084 0.000710181 0.435882 0.00107605 0.000632073 0.000780059 0.324378 58 53 18 0.00129725 0.000623659 0.000848189 0.430382 0.00108778 0.000647922 0.000794535 0.315793 # pathway end # subjectname 70 # pathwayname lh.cab # # pathway start x y z AD RD MD FA AD_Avg RD_Avg MD_Avg FA_Avg 53 32 26 0.00117731 0.000928949 0.00101174 0.143923 0.00116391 0.00090839 0.000993563 0.153213 53 33 26 0.0010364 0.000859843 0.000918695 0.128905 0.00103869 0.000848443 0.000911856 0.138848 53 33 25 0.00105938 0.000877392 0.000938055 0.127225 0.00105752 0.000865256 0.000929355 0.135088 54 34 25 0.000944648 0.000719044 0.000794246 0.162868 0.000957389 0.000725472 0.000802768 0.16744 54 35 25 0.000972687 0.000738523 0.000816578 0.208351 0.000986717 0.000739063 0.000821629 0.213113 54 36 24 0.00101603 0.000621378 0.000752929 0.305637 0.0010253 0.000631396 0.000762693 0.302995 54 37 24 0.00113992 0.000642822 0.000808521 0.369124 0.0011217 0.000646204 0.000804698 0.353409 55 38 23 0.000890718 0.000584601 0.00068664 0.265622 0.000916719 0.000590972 0.000699556 0.273432 55 39 23 0.0013084 0.000657441 0.000874427 0.41632 0.00129438 0.000656492 0.000869102 0.409684 55 40 22 0.000897226 0.000549981 0.000665729 0.294657 0.000926128 0.000565056 0.000685412 0.294239 56 41 22 0.00129446 0.000643583 0.000860544 0.416518 0.00128053 0.000641873 0.000854761 0.410811 56 42 21 0.00095897 0.000527739 0.000671483 0.356436 0.000986408 0.00054246 0.000690451 0.355442 56 43 21 0.00126047 0.000576778 0.000804674 0.460586 0.00120436 0.000578402 0.000787051 0.4315 57 44 21 0.00141709 0.000815438 0.00101599 0.333322 0.00136115 0.000786714 0.000978188 0.330026 57 45 20 0.00107155 0.000547688 0.000722309 0.398732 0.0010439 0.000565023 0.000724638 0.366345 57 46 19 0.00106184 0.000688623 0.000813027 0.276355 0.00106565 0.000721324 0.000836098 0.250311 58 46 18 0.00138626 0.00111282 0.00120397 0.13344 0.00133896 0.00105932 0.00115254 0.147013 58 46 17 0.00190569 0.00154603 0.00166592 0.127639 0.0017048 0.00136742 0.0014799 0.141036 58 47 17 0.00182424 0.00136918 0.00152086 0.176476 0.00170912 0.00128364 0.00142549 0.178103 58 48 17 0.00179186 0.00155183 0.00163184 0.121897 0.0016827 0.00141198 0.00150224 0.137642 58 49 17 0.00173965 0.00152012 0.00159329 0.0828833 0.00156972 0.00134741 0.00142152 0.101404 58 50 17 0.00146827 0.00123617 0.00131354 0.105179 0.0013648 0.00113875 0.00121408 0.115824 59 51 17 0.000939683 0.000730799 0.000800427 0.151144 0.000913724 0.000729779 0.000791094 0.140851 59 52 17 0.000973182 0.000776841 0.000842288 0.136551 0.000937145 0.000762049 0.00082041 0.130533 59 53 17 0.000974158 0.000799803 0.000857921 0.120722 0.000938325 0.000778099 0.000831516 0.119775 59 54 17 0.00100004 0.000821513 0.000881023 0.135361 0.000956475 0.000793336 0.000847705 0.130042 # pathway end Thank you! sincerely yours, Lars M. Rimol, PhD Senior researcher, Norwegian Advisory Unit for functional MRI Department of Radiology, St. Olav's University hospital, 7006 Trondheim, Norway

1 0

Individual / fsaverage RAS152 discrepancies
by Garikoitz Lerma-Usabiaga 18 Nov '16

18 Nov '16

Hi all, I have fMRI data in individual space, converted to individual surface using vol2surf and to fsaverage surface using surf2surf (commands [1] and [2] below). With Matlab, I obtain the vertex with the maximum value: max_Vtx and max_Vtx305. If I would like to obtain the MNI152 coordinate of this vertex (for comparison with the literature), I think I have two options: 1.- Work in the individual space: >> max_SurfaceRAS = lhwhite(max_Vtx, :); >> max_RAS = T1.vox2ras*inv(T1.tkrvox2ras)*[max_SurfaceRAS';1]; I can check in freeview that the result is correct. >> max_RAS305 = TalXFM * max_RAS; I can check in tkmedit that this is right too. At last, using the MNI305to152 matrix provided by Doug in the wiki: >> max_RAS152 = MNI305to152 * max_RAS305; 2.- Work in the fsaverage (305) space >> max_SurfaceRAS305 = lhwhite305(max_Vtx305, :); as Surface RAS is the same as RAS, we only have to convert it to 152 >> max_RAS152_305 = MNI305to152 * max_SurfaceRAS305 ; The results are: For 1: [-15.57, -93.62, -2.84] For 2: [-23.06, -97.06, 1.35] Is this method ok? is this the way it should work? As the results are not the same, is one of the methods inherently better than the other? Many thanks! Gari [1] mri_vol2surf --srcsubject S001 --projfrac 0.5 --interp trilinear --hemi lh --regheader S001 --mov fMRI.img --o fMRI.mgh [2] mri_surf2surf --srcsubject S001 --srchemi lh --srcsurfreg sphere.reg --trgsubject fsaverage --trghemi lh --trgsurfreg sphere.reg --sval fMRI.mgh --tval fMRI305.mgh --sfmt curv --noreshape --no-cortex

2 2

3dClustSim and surfaces
by Hubbard, Catherine S. 18 Nov '16

18 Nov '16

Hi, I’ve read previously on the archive that it is not possible to use AFNIs alphasim with freesurfer surfaces, however, I’m wondering if it might be possible to use 3dClustSim (recent version with fixed bug)? Thanks for your help.

2 2

Re: [Freesurfer] Comparing z score maps between 2 modalities in a group?
by Elijah Mak 18 Nov '16

18 Nov '16

Hi Doug, Thanks for taking a look at the commands! I appreciate it. I would like to ask a further question about your concern/s regarding this approach? My aim was to have an analytical pipeline in Freesurfer that is analogous to several studies (using VBM-type of analyses in SPM) where they compared the relative severity of various pathological processes measured from different modalities. For reference, see: https://www.ncbi.nlm.nih .gov/pubmed/24951642 In that study, the authors in that study were trying to examine whether hypometabolism was relatively more severe compared to atrophy, and both modalities (PET and T1) were Z-scored relative to controls, and then compared against each other. Best Wishes, Elijah On Fri, Nov 18, 2016 at 5:24 PM, Elijah Mak <fkm24(a)medschl.cam.ac.uk> wrote: > Hi Doug, > > Thanks for taking a look at the commands! > > I would like to ask a further question about your concern/s regarding this approach? My aim was to have an analytical pipeline in Freesurfer that is analogous to several studies (using VBM-type of analyses in SPM) where they compared the relative severity of various pathological processes measured from different modalities. > > I have attached a little screenshot for your reference. > > For example, the authors in that study were trying to see whether hypometabolism was relatively more severe compared to atrophy, and both modalites (PET and T1) were Z-scored relative to controls, and then compared against each other. Another study that has used a similar technique is here: https://www.ncbi.nlm.nih.gov/pubmed/24951642 > > Best Wishes, > Elijah > > > > > > > Re: [Freesurfer] Comparing z score maps between 2 modalities in a group? <http://www.mail-archive.com/search?l=freesurfer@nmr.mgh.harvard.edu&q=subje…> > > Douglas N Greve <http://www.mail-archive.com/search?l=freesurfer@nmr.mgh.harvard.edu&q=from:…> Fri, 18 Nov 2016 08:19:47 -0800 <http://www.mail-archive.com/search?l=freesurfer@nmr.mgh.harvard.edu&q=date:…> > > Those commands look right, though I would do the smoothing before > computing the standard dev. Also, I don't know whether your overall > method is valid. > > On 11/15/2016 05:48 PM, Elijah Mak wrote: > > Hi Freesurfer Team, > > > > We would like to compare Z-scored surface maps between different > > modalities (MRI and PET) within a single group. 1 subject = 2 measures. > > > > These are my steps so far, using mri_concat and fscalc for the > > generation of the Z score maps. Differences between Z-score maps are > > tested using the paired t-test approach as outlined here: > > https://surfer.nmr.mgh.harvard.edu/fswiki/PairedAnalysis > > > > I am not sure if my following steps are correct, so confirmation will > > be much appreciated, many thanks for your time and help! > > > > // Generate mean/sd of healthy controls > > > > X > > mri_concat --f stacks_X_lh_HC_fsaverage --o group_mean_X_hc_lh.mgh --mean > > mri_concat --f stacks_X_lh_HC_fsaverage --o group_std_X_hc_lh.mgh --std > > > > Y > > mri_concat --f stacks__Y_HC_fsaverage --o group_mean_Y_HC_lh.mgh --mean > > mri_concat --f stacks_Y_lh_HC_fsaverage --o group_std_Y_HC_lh.mgh --std > > > > QN: Should smoothing be applied here or before? > > > > // Derive individual Z-score map for X and Y > > > > X > > for i in `cat list`; do fscalc $i/surf/lh.X.fsaverage.mgh sub > > group_mean_X_hc_lh.mgh div group_std_X_hc_lh.mgh --o > > $i/surf/lh.Z.thickness.fsaverage.mgh; done > > for i in `cat list; do fscalc $i/surf/rh.X.fsaverage.mgh sub > > group_mean_cth_hc_rh.mgh div group_std_X_hc_rh.mgh --o > > $i/surf/rh.Z.thickness. > fsaverage.mgh; done > > > > Y > > for i in `cat list`; do fscalc $i/surf/lh.Y.fsaverage.mgh sub > > group_mean_X_hc_lh.mgh div group_std_cth_hc_lh.mgh --o > > $i/surf/lh.Z.fsaverage.mgh; done > > for i in `cat list; do fscalc $i/surf/rh.Y.fsaverage.mgh sub > > group_mean_Y_hc_rh.mgh div group_std_Y_hc_rh.mgh --o > > $i/surf/rh.Z.fsaverage.mgh; done > > > > > > // Derive paired-difference of Z scores between X and Y > > > > mri_concat --f stacks_XminusY_lh --paired-diff --o concat_XminusY_lh.mgh > > mri_concat --f stacks_XminusY_rh --paired-diff --o concat_XminusY_rh.mgh > > > > // Smooth concatenated maps of paired differences > > > > mri_surf2surf --s fsaverage --hemi lh --fwhm 4 --sval > > concat_XminusY_lh.mgh --tval concat_XminusY_lh_sm4.mgh > > > > // Test significance of paired differences within the group > > > > mri_glmfit --y concat_XminusY_lh_sm4.mgh --fsgd fsgd_pairediff dods > > --osgm --surf fsaverage lh --cortex --glmdir > > > > I used the --osgm flag as there are no covariates here. > > > > > > > > > > > > > > > > _______________________________________________ > > Freesurfer mailing list > > Freesurfer(a)nmr.mgh.harvard.edu > > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer > > -- > Douglas N. Greve, Ph.D. > MGH-NMR Centergr...(a)nmr.mgh.harvard.edu > Phone Number: 617-724-2358 > Fax: 617-726-7422 > > Bugs: surfer.nmr.mgh.harvard.edu/fswiki/BugReporting > FileDrop: https://gate.nmr.mgh.harvard.edu/filedrop2www.nmr.mgh.harvard.edu/facility/… > Outgoing: ftp://surfer.nmr.mgh.harvard.edu/transfer/outgoing/flat/greve/ > > _______________________________________________ > Freesurfer mailing listFreesurfer@nmr.mgh.harvard.eduhttps://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer > > > The information in this e-mail is intended only for the person to whom it is > addressed. If you believe this e-mail was sent to you in error and the e-mail > contains patient information, please contact the Partners Compliance HelpLine athttp://www.partners.org/complianceline . If the e-mail was sent to you in error > but does not contain patient information, please contact the sender and properly > dispose of the e-mail. > > > >

2 1

← Newer
1
...
7
8
9
10
11
12
13
...
22
Older →

Jump to page:

2026

2025

2024

2023

2022

2021

2020

2019

2018

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

Freesurfer November 2016