Freesurfer December 2016

freesurfer@nmr.mgh.harvard.edu

95 participants
146 discussions

Postdoc positions available at University of Sydney, Australia
by Jerome Maller 13 Dec '16

13 Dec '16

Postdoctoral Scientist - Neurocardiovascular Disease and Depression *THE POSITION:* Interested postdoctoral applicants will be joining a dynamic and highly successful collaborative research program aimed at applying cutting edge neuroimaging technology. Our focus is on translating cutting edge neuroimaging techniques to better understand the brain changes occurring in: 1. neurocardiovascular diseases, 2. depression and 3. mild traumatic brain injury. The key techniques we use are diffusion MRI and resting state fMRI. We recently used multiband diffusion imaging to acquire the highest ever* in vivo* dataset of 1014 direction across 8 shells, which produces a vast improvement in tract accuracy. The successful candidate will have the opportunity to be involved in a number of related projects using the same standardised imaging approach and will be actively mentored to maximise future career opportunities including the chance to be involved in grant writing, working in partnership with industry and a major focus on first author publications. Our database contains over 1500 subjects, we are currently acquiring large cohorts in mTBI, perisurgical brain injury, depression and also explore the brain changes associated with cardiovascular and metabolic conditions such as diabetes, hypertension and heart failure. The group is headed by Professor Stuart Grieve who is the Director of Imaging at the Charles Perkins Centre and a group leader at the Heart Research Institute (HRI). The laboratory is based at Charles Perkins Centre but acquires a data across a large Hospital network across Sydney and Australia. *Essential Criteria – you will have:* - A neuroimaging, engineering, computer science or scientific medical research doctorate - A track record of producing high quality research that has been published in leading internationally recognised journals - Experience in assisting with student supervision including supervision of honours students and potentially the co-supervision of PhD students - A strong interest and commitment to producing leading international research - High levels of motivation and the capacity for independent work - A track record of being team focussed - Good interpersonal, written, and oral communication skills The position is full time; however flexible working arrangements may be negotiated. The appointment period is for a maximum term of 24 months with the possibility of renewal. You will be employed by The Heart Research Institute but will be required to work at our premises in Newtown and at the Charles Perkins Centre located nearby at the University of Sydney as required. This is an outstanding opportunity to develop skills and gain valuable experience conducting innovative research in state-of-the-art facilities. The high calibre of scientists, new technologies and cutting edge equipment are just a few features that make the partnership between The Heart Research Institute and the Charles Perkins Centre a new precinct of excellence in premier cardiovascular research. *Remuneration: *A competitive remuneration package is on offer, including salary-packaging options. *How to apply:* Please send any queries to carmen(a)grievelab.com. To apply, email: - a cover letter addressed to Professor Stuart Grieve - a detailed curriculum vitae (CV) -- *Dr Jerome J Maller BSc,GradDipPsych,MSc,PhD* University of Sydney

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Re: [Freesurfer] Demeaning variables
by Rodrigo Gonzalez Huerta 13 Dec '16

13 Dec '16

Hey Doug, First, thanks for your previous answer, it helped me to clarify some issues. Lately, I’ve been doing what you suggested. But something just caught my attention. To recap, I was testing with DODS for an interaction of a continuous variable (age) with two discrete factors, diagnosis (patient, control) and gender which was regressed out; since I didn’t find any significant statistical regions (interactions), I decided to proceed using DOSS using mri_glmfit. What caught my attention is that I realized that my results when DOSS is ran using the contrast [ 0.5 -0.5 0.5 -0.5 0 ] (the cero is to regress out age) are exactly the same results (same clusters, same size) as when I run DODS in QDEC using only gender and diagnosis, ignoring age covariate (i.e., not selecting the covariate on the GUI for the analysis), and selecting the output “'Does the average thickness accounting for gender differ between patient and control?” 1) 1) Am I using the correct contrast? I think it is possible to obtain the same results using DODS or DOSS, but if this is the case, what does it mean? 2) 2) Since I didn’t found any interactions between age and groups using DODS, when using DOSS, it is correct to infer that the clusters that I found are due a main effect (main effect understood as the effect of a single independent variable (diagnosis) on the dependent variable (thickness)) of the diagnosis factor, since gender factor was regressed out and I don't have other variables? Thank you very much. Rodrigo ________________________________ De: freesurfer-bounces(a)nmr.mgh.harvard.edu <freesurfer-bounces(a)nmr.mgh.harvard.edu> en nombre de Douglas N Greve <greve(a)nmr.mgh.harvard.edu> Enviado: jueves, 1 de diciembre de 2016 11:16:14 a. m. Para: freesurfer(a)nmr.mgh.harvard.edu Asunto: Re: [Freesurfer] Demeaning variables If you want to find the effect of group regressing out the effect of age and there is truly a difference in the age slopes, then you have a problem. Imagine a scatter plot of thickness vs age. Each group gets it's own best fit line (offset and slope). If the slopes are the same, then the two lines will always have the same distance between them. However, if the slopes are different, then the difference between the groups depends on age. When you "regress out age", what you are doing is selecting a single age to test the groups. If you don't demean, then you test at age=0. If you demean, you test at age=mean age. The problem is that you get different results depending upon what age you test at. There will be an age where the two lines intersect at which point there will be no difference. Before that age, one group will be greater than the other. After that, it will reverse. Some statisticians say that you should not test for a difference between groups if the slopes are different (ie, your analysis has come to an end). Most people just demean and plow ahead without understanding what it means. If you really think that there is a difference in the slopes despite the negative test result, then you can abandon the analysis or proceed with the understanding of the problems with interpretation. I would probably trust the negative result and proceed with the DOSS test. So, ... 1) Yes 2) Publish 3) Probably not. Adding the males gives you a net increase of 17 DOF, which is probably not trivial On 11/30/2016 09:45 PM, Rodrigo Gonzalez Huerta wrote: > > Hey Doug, > > > Sorry for keep bothering, today I was trying to do what you told me > yesterday, but some doubts arose. I ran QDEC using DODS to see if > there were any interactions (significant regions) between age (age > variable was not demeaned) and group. I didn’t found anything, no > significant regions survived monte carlo. If that came to happen, you > suggested me to use DOSS instead, but… because of the characteristics > of the disease I’m studying, the slopes shouldn’t be similar between > patients and controls. My questions are: > > > 1) Can I proceed using DOSS anyway? > > > 2) What if DOSS give me some clusters after running monte carlo? Which > is the case since I’ve already ran mri_glmfit and obtained three > clusters. What should I do now? Should I re-run DODS with age-variable > demeaned? > > > 3) Since most of my subjects are women (around 80%) and my sample is > small (18 patients, 18 controls), does it have an advantage to remove > the males to be able to get rid of the gender variable that I’m also > regressing out? In order to have just two classes (patient and > control) instead of four (malecontrol, malepatient,….) , or it is > better to continue as I’ve been doing, controlling for the effect of > gender. > > > Thanks for your help! > > > Rodrigo > > > ------------------------------------------------------------------------ > *De:* freesurfer-bounces(a)nmr.mgh.harvard.edu > <freesurfer-bounces(a)nmr.mgh.harvard.edu> en nombre de Douglas Greve > <greve(a)nmr.mgh.harvard.edu> > *Enviado:* martes, 29 de noviembre de 2016 08:31:20 p. m. > *Para:* freesurfer(a)nmr.mgh.harvard.edu > *Asunto:* Re: [Freesurfer] Demeaning variables > > > > On 11/29/16 8:52 PM, Rodrigo Gonzalez Huerta wrote: >> >> It makes sense to me, I only have two more questions, >> >> 1. When you say “see if there are any places where there is an >> interaction between age and group”, do you mean finding >> significant statistical regions, right? And this would be before >> or after using monte carlo? >> > After. Even if you have some sig areas, they won't matter if they do > not overlap with sig areas in DOSS >> >> 1. >> >> >> 2. What about using the median or other value instead of the mean >> since most of my subjects are in the range from 20 to 35 years >> old and only a few in the range from 35 to 55 years old. Would >> this make sense to you? >> > It has nothing to do with using the mean or median. The problem is > that the differences in the means of the groups is not a valid concept > when the age slopes are different >> >> 1. >> >> >> Thanks in advance >> >> Rodrigo >> >> >> ------------------------------------------------------------------------ >> *De:* freesurfer-bounces(a)nmr.mgh.harvard.edu >> <freesurfer-bounces(a)nmr.mgh.harvard.edu> en nombre de Douglas Greve >> <greve(a)nmr.mgh.harvard.edu> >> *Enviado:* martes, 29 de noviembre de 2016 07:33:47 p. m. >> *Para:* freesurfer(a)nmr.mgh.harvard.edu >> *Asunto:* Re: [Freesurfer] Demeaning variables >> >> It comes down to the contrast you care about. If you want to look at >> the difference in mean thickness between the groups regressing out >> the effect of age, then demeaning can make a big difference. If this >> is what you want, then you need to do the analysis in two stages. >> First run with DODS and see if there are any places where there is an >> interaction between age and group; demeaning is unimportant for this >> contrast. If there is not a difference, then reanalyze using DOSS (in >> which case demeaning is also unimportant). You cannot do DOSS in QDEC. >> >> >> >> On 11/29/16 6:23 PM, Rodrigo Gonzalez Huerta wrote: >>> >>> Hi Doug, >>> >>> >>> I mean that when I run QDEC selecting gender and diagnosis as fixed >>> factors, age as nuisance factor, and display the results, I obtain >>> totally different significant statistical regions (different >>> statistical maps) when ages are demeaned ((demeaned age = age of >>> each subject – the mean of all subjects (grandmean)) than the case >>> when ages aren't demeaned. Therefore, when I run the monte carlo >>> simulation, when I demean the age variable I don’t get any clusters, >>> but when age is not demeaned I obtain some clusters of considerable >>> size. The contrast I used in mri_glmfit is: >>> >>> 0.5 -0.5 0.5 -0.5 0 0 0 0 ("is there a difference between patient >>> and control regressing out the effects of gender and age?") >>> >>> In QDEC it seems to correspond to the output 'Does the average >>> thickness accounting for gender differ between patient and control? >>> (age as nuisance variable)’ because the statistical maps look the same. >>> >>> From what I understand, this difference in the results when age >>> variable is demeaned is something I should expect when doing a DODS >>> analysis. My main doubt would be if it was necessary to demean the >>> age variable and enter it as a nuisance factor based on the >>> characteristics of my population and the analysis I want to perform. >>> I tried to focus my questions in that direction. I’m very sorry if I >>> am not giving myself to understand. Thanks! >>> >>> >>> Rodrigo >>> >>> >>> ------------------------------------------------------------------------ >>> *De:* freesurfer-bounces(a)nmr.mgh.harvard.edu >>> <freesurfer-bounces(a)nmr.mgh.harvard.edu> en nombre de Douglas N >>> Greve <greve(a)nmr.mgh.harvard.edu> >>> *Enviado:* martes, 29 de noviembre de 2016 03:22:15 p. m. >>> *Para:* freesurfer(a)nmr.mgh.harvard.edu >>> *Asunto:* Re: [Freesurfer] Demeaning variables >>> When you say that the results are different, what do you mean? What is >>> your contrast? What is your command line? What is your fsgd file? >>> >>> >>> On 11/29/2016 03:34 PM, Rodrigo Gonzalez Huerta wrote: >>> > >>> > Just to clarify, where is said N=18 I wanted to meant 18 controls >>> + 18 >>> > patients. Thanks in advance. >>> > >>> > >>> > Rodrigo >>> > >>> > >>> ------------------------------------------------------------------------ >>> > *De:* freesurfer-bounces(a)nmr.mgh.harvard.edu >>> > <freesurfer-bounces(a)nmr.mgh.harvard.edu> en nombre de Rodrigo >>> Gonzalez >>> > Huerta <rghbecker2908(a)hotmail.com> >>> > *Enviado:* martes, 29 de noviembre de 2016 02:19:26 p. m. >>> > *Para:* freesurfer(a)nmr.mgh.harvard.edu >>> > *Asunto:* [Freesurfer] Demeaning variables >>> > >>> > Hi Freesurfers, >>> > >>> > >>> > For obtaining my undergraduate degree I’m performing a study using >>> > Freesurfer. I’m stuck with the centering (de-meaning) issue. I have >>> > two discrete variables, gender, and patient-control, and a continuous >>> > variable which is age. The age population range goes from 20 to 55 >>> > years and is paired between patients and controls. Patient’s disease >>> > affects cortical thickness over time and every patient has been >>> > presenting the disease for 6 years (no more, no less). I’ve runned >>> > QDEC and mri_glmfit using DODS obtaining the same results, the >>> problem >>> > is that when I demean the age (I used the grandmean) the results are >>> > very differente. If I don’t demean some clusters survive the >>> > monte-carlo multiple comparisons correction (p<0.05), but, when I >>> > demean no cluster survive. I have this questions: >>> > >>> > 1. Since most of my subjects are in the range of 20-35 years and only >>> > a few have more than 35 years, it is correct to use the mean? >>> > Wouldn’t be better to use the median or some other value? >>> > 2. This is maybe a silly question, but why should I care about the >>> > intercept? I know that demeaning doesn’t change the slope, just >>> > the intercept, but I don’t understand why I should care, I read in >>> > some publications that demeaning is not always necessary. >>> > >>> > Other questions: >>> > >>> > 1. Most of my subjects are women (around 80%, N=18), Does it have an >>> > advantage to remove the males to get rid of the gender variable?, >>> > or should I continue as I’ve been doing, controlling for the >>> > effect of gender. >>> > 2. Since I don’t know if this disease is more aggressive when is >>> > developed at some stage of life, I mean, if young patients are >>> > less affected than older patients after six years of presenting >>> > it, it is correct to control the effect of age? (Entering the >>> > variable as a nuisance factor), or should I search for an >>> > interaction between age and the condition variable? I only care >>> > about differences in cortical thickness. >>> > >>> > Any suggestion is very welcome, thanks in advance for your answer. >>> > >>> > >>> > Rodrigo >>> > >>> > >>> > >>> > >>> > >>> > >>> > >>> > >>> > >>> > >>> > >>> > >>> > _______________________________________________ >>> > Freesurfer mailing list >>> > Freesurfer(a)nmr.mgh.harvard.edu >>> > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer Freesurfer Info Page - Harvard University<https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer> mail.nmr.mgh.harvard.edu To see the collection of prior postings to the list, visit the Freesurfer Archives. A searchable archive which of messages PRIOR to March 2004 is at ... >>> >>> -- >>> 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 FileDrop v2.0 - Martinos Center for Biomedical Imaging<https://gate.nmr.mgh.harvard.edu/filedrop2> gate.nmr.mgh.harvard.edu Filedrop is for sending files work-related files up to 2GiB; For files over 2GiB, please use the Accellion File Transfer from Partners; Filedrop is not a secure ... >>> <https://gate.nmr.mgh.harvard.edu/filedrop2> FileDrop v2.0 - Martinos Center for Biomedical Imaging<https://gate.nmr.mgh.harvard.edu/filedrop2> gate.nmr.mgh.harvard.edu Filedrop is for sending files work-related files up to 2GiB; For files over 2GiB, please use the Accellion File Transfer from Partners; Filedrop is not a secure ... >>> www.nmr.mgh.harvard.edu/facility/filedrop/index.html<http://www.nmr.mgh.harvard.edu/facility/filedrop/index.html> Martinos Center File Drop<http://www.nmr.mgh.harvard.edu/facility/filedrop/index.html> www.nmr.mgh.harvard.edu 11/15/2012 -- There is a new version of Filedrop. Please help us test it https://gate.nmr.mgh.harvard.edu/filedrop2/ Welcome to the Martinos Center file drop area. >>> <http://www.nmr.mgh.harvard.edu/facility/filedrop/index.html> Martinos Center File Drop<http://www.nmr.mgh.harvard.edu/facility/filedrop/index.html> www.nmr.mgh.harvard.edu 11/15/2012 -- There is a new version of Filedrop. Please help us test it https://gate.nmr.mgh.harvard.edu/filedrop2/ Welcome to the Martinos Center file drop area. >>> 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 >>> >>> >>> 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 . 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 >>> 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 > > > > _______________________________________________ > 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<http://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

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project 3D ROI onto flatmap
by Niia Nikolova 13 Dec '16

13 Dec '16

Dear Experts, I have analysed retinotopy data, and have it on occipital patches of each subjects cortical flatmap. Now, I would like to also project ROI masks which I have drawn by hand in FSL (based on other functional areas) onto the same flatmaps. The ROI masks are in 3d nii.gz files and I am not sure how to approach this. I have followed the freesurfer tutorials and searched in the mail archives, but have not encountered a similar problem. If you could point me in the right direction, I would greatly appreciate it! Thank you in advance, Niia

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correlation in mri glmfit controlling for 2 categorical variables and 1 continuous variable
by Emmanuel Nwosu 13 Dec '16

13 Dec '16

Hi All Am not sure if I can do this in mri glmfit I want to investigate the relationship between cortical thickness and a continuous variable (A) while accounting for two categorical variables with two levels each and one continuous variable. That is I want to account for : 1. categorical variable X - (levels - O and P) 2. categorical variable Y - (levels - K and L) 3. Continuous variable Z. What will the contrast file in mri glmfit look like? Have anyone got an idea? Thanks in advance Emmanuel

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Re: [Freesurfer] Odd Extremely High/Low Banding of Functional Values in Volume
by Dowling, Kevin Francis 13 Dec '16

13 Dec '16

Hi Doug, My apologies for omitting the previous emails when replying earlier. To create the sig.mgh file we used a volume specific mri_glmfit analysis, with volume specific inputs / no --hemi/hemis flag. I don't know if this information is helpful but when we've run a nearly identical analysis (using almost all of the same participants and a slightly different covariate of interest) the volume came out completely fine. In case there was an error in one of our scans omitted from the successful mri_glmfit I re-ran the mri_glmfit/concatenation, excluding participants not also included in our successful mri_glmfit. However, the abnormal activation persisted (see attached screen grabs). I've also tried de-meaning our covariate of interest values (RBC Folate) and re-running the mri_glmfit, with no improvement. This is our mri_glmfit command: mri_glmfit --y /cluster/roffman/users/Stable5_PerRun/Analyses_GDD/GDD_Adults/137_GDD_RBC_Folate_Cond2vfix_KD/SIRP_LoadRegression_Stable5.3_012616_sm5_mni305/Cond2vFix/ces.nii.gz --fsgd /cluster/roffman/users/fsgd/GDD/137_GDD_Cond2vFix_Covary_RBC_Folate_linear_KDcorrect.fsgd --C /cluster/roffman/users/fsgd/TwoGroups1CovariateRegressOut1Covariate_KD --glmdir /cluster/roffman/users/Stable5_PerRun/Analyses_GDD/GDD_Adults/137_GDD_RBC_Folate_Cond2vfix_KD/SIRP_LoadRegression_Stable5.3_012616_sm5_mni305/Cond2vFix/2vFix_ClassUsed_Covary_RBCFOLATE_Nuis_Age_Gender --fwhm 6 --no-prune Thank you very much, I am most appreciative of your help and would be grateful for any other troubleshooting suggestions you might have! Kind regards, Kevin Message: 2 Date: Mon, 5 Dec 2016 14:41:15 -0500 From: Douglas N Greve <greve(a)nmr.mgh.harvard.edu> Subject: Re: [Freesurfer] Odd Extremely High/Low Banding of Functional Values in Volume To: freesurfer(a)nmr.mgh.harvard.edu Message-ID: <52df3c71-0cdc-61ba-2491-5bebffa114c1(a)nmr.mgh.harvard.edu> Content-Type: text/plain; charset=windows-1252; format=flowed How did you create sig.mgh? If you used a surface-based mri_glmfit analysis, then you'll need to convert sig.mgh to the volume (mri_surf2vol) On 12/05/2016 02:25 PM, Dowling, Kevin Francis wrote: > > Hello Freesurfer Experts, > > I?m attempting to look at activity in a working memory paradigm using > blood folate levels as my covariate of interest while controlling for > gender and age in 137 subjects. There were no errors (that I could > find) in the concatenation or mri_glmfit commands, and subject > registration looked ok for the functional data. When visualizing the > right and left hemisphere surface sig.mgh files using tksurfer > everything looks reasonable. However, when using tkmedit (tkmedit > fsaverage1 orig.mgz ?overlay sig.mgh ?fminmax 1.3 3.3 ?fmid 2.3) I am > getting odd continuous bands of incredibly high and incredibly low > activation spanning throughout most the volume (I?ve attached some > screen grabs ? the functional values in these bands are either > 10000000000 or -10000000000 and look continuous from slice to slice). > > I?ve taken a look at the list and was not able to find a similar > problem discussed. I would be most grateful for any guidance or > trouble shooting suggestions you might have! > > I?ve also attached a text file copy of the glm and tkmedit results in > case they would be of use. > > I'm using Freesurfer version 5.3 (nmr-stable53-env) on a Linux > (Release 6.7 (Santiago), Kernel Linux 2.6.32-573.12.1.el6.x86_64 > and GNOME 2.28.2) > > Thank you! > > Kevin > > Kevin Dowling > > Clinical Research Coordinator > > Brain Genomics Laboratory > > Division of Psychiatric Neuroimaging > > Massachusetts General Hospital > > 149 13th Street > > Charlestown, MA, 02129 > > (p) (617) 643 - 2479 > > > > _______________________________________________ > 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<http://www.nmr.mgh.harvard.edu/facility/filedrop/index.html> Outgoing: ftp://surfer.nmr.mgh.harvard.edu/transfer/outgoing/flat/greve/ Kevin F. Dowling Clinical Research Coordinator Brain Genomics Laboratory Division of Psychiatric Neuroimaging Martinos Center for Biomedical Imaging Massachusetts General Hospital 149 13th Street Charlestown, MA, 02129 (p) 617.643.2479

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question white matter
by tom parker 13 Dec '16

13 Dec '16

Dear Freesurfers, Could anyone tell me what the white.H and white.K measures in Qdec are? Thank you so much!

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hard time with mris_pmake
by salma bougacha 13 Dec '16

13 Dec '16

Hi Freesurfer experts, I am new to freesurfer. I installed the last freesurfer version (freesurfer-Linux-centos6_x86_64-stable-pub-v5.3.0) and I am trying to compute the shortest cortical path between two sets of vertices. 1- Using the command mris_pmake updated If I understand correctly according to https://mail.nmr.mgh.harvard.edu/pipermail/freesurfer/2013-January/027543.h… mris_pmake has been updated, but the command mris_pmake --subj bert --hemi lh --surface smoothwm --mpmProg autodijk --mpmArgs vertexPolar:0 --mpmOverlay euclidean throws the following error #####################" mris_pmake: option '--surface' is ambiguous; possibilities: '--surface0' '--surface1' #####################" Following the complain, I tried mris_pmake --subject bert --hemi lh --surface0 smoothwm --surface1 smoothwm --mpmProg autodijk --mpmArgs vertexPolar:11 --mpmOverlay euclidean This seems to work and produces options.txt and user_msg.log files in the current directory. However I am unable to find the output lh.autodijk.crv and that's where the path lengths are stored, right ? 2- making dsh work: I get the following error when trying to run dsh Traceback (most recent call last): File "/usr/local/freesurfer/bin/dsh", line 16, in <module> from dgmsocket import * ImportError: No module named dgmsocket So I commented this import as well the line "G_socket = C_dgmsocket(Gstr_host, string.atoi(Gstr_port))". Now dsh seems working in the begining but then I have the following ################################################# sh: 1: SSocket_client: not found 46.860310 Engine successfully started and environment parsed. Ready for user input. Type 'HELP' for help. 1 > Start->End vertices [ 11->6398 ] Total path cost [ 46.860310 ] process died. /usr/local/freesurfer/bin/dsh Sorry, but some error occurred. While attempting dijkstra_spawn(), the process died unexpectedly Exiting to system with code 10. ########################################### Any help is appreciated ! Thanks. Salma

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mris_apply_reg
by Matthew Defenderfer 13 Dec '16

13 Dec '16

Hi All, I am trying to mirror labels across hemispheres and found various threads using mris_apply_reg. Unfortunately the version of that command I have does not recognize labels and all of the links in the mailing list seem to be broken. Would it be possible to get a link to the updated command? Thank you. -Matthew Defenderfer

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(no subject)
by Abigail Noyce 13 Dec '16

13 Dec '16

Hi Doug et al, I would like to get a different cluster summary stat out of mri_glmfit-sim. Rather than size, I'd like to use the "sum of t-scores" (after Maris & Oostenwald 2007, for example). That is, set a cluster inclusion threshold, and then for each cluster of adjacent vertices that clear the threshold, sum their t-scores. For the permutation significance testing, then, the largest such clusterwise sum would be the statistic used to generate the null distribution... I'm happy to write my own scripts, but can't figure out where to try to pull this number out. Thanks! Abby Noyce

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Re: [Freesurfer] Odd Extremely High/Low Banding of Functional Values in Volume
by Dowling, Kevin Francis 13 Dec '16

13 Dec '16

Hi Doug, Thank you for your note and my apologies for a delayed response. To create the sig.mgh file we used a volume specific mri_glmfit analysis, omitting the --surf flag and using our volume specific input (ces.nii.gz in SIRP_LoadRegression_Stable5.3_012616_sm5_mni305). I don't know if this information is helpful but when we've run a nearly identical analysis using almost all of the same participants and a different blood folate marker (serum folate) the volumes came out completely fine. I've tried de-meaning the RBC folate values and re-running the mri_glmfit, but the odd activation persists. This is our mri_glmfit command: mri_glmfit --y /cluster/roffman/users/Stable5_PerRun/Analyses_GDD/GDD_Adults/137_GDD_RBC_Folate_Cond2vfix_KD/SIRP_LoadRegression_Stable5.3_012616_sm5_mni305/Cond2vFix/ces.nii.gz --fsgd /cluster/roffman/users/fsgd/GDD/137_GDD_Cond2vFix_Covary_RBC_Folate_linear_KDcorrect.fsgd --C /cluster/roffman/users/fsgd/TwoGroups1CovariateRegressOut1Covariate_KD --glmdir /cluster/roffman/users/Stable5_PerRun/Analyses_GDD/GDD_Adults/137_GDD_RBC_Folate_Cond2vfix_KD/SIRP_LoadRegression_Stable5.3_012616_sm5_mni305/Cond2vFix/2vFix_ClassUsed_Covary_RBCFOLATE_Nuis_Age_Gender --fwhm 6 --no-prune Thank you very much, I am most appreciative of your help! Kind regards, Kevin Kevin F. Dowling Clinical Research Coordinator Brain Genomics Laboratory Division of Psychiatric Neuroimaging Martinos Center for Biomedical Imaging Massachusetts General Hospital 149 13th Street Charlestown, MA, 02129 (p) 617.643.2479

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Freesurfer December 2016