Freesurfer

freesurfer@nmr.mgh.harvard.edu

4 participants
30076 discussions

Reminder to cite FreeSurfer in your OHBM abstract
by Douglas N Greve 14 Dec '16

14 Dec '16

Hi All, as you finalize your OHBM abstract, remember to cite FreeSurfer. There is a box to check that you used FreeSurfer when you submit your abstract, but also please put some indication in the text that you used FreeSurfer if you can. If you have room to put in a citation, there are several below you can use. thanks! doug 1999. Dale, A.M., Fischl, B., Sereno, M.I., Cortical Surface-Based Analysis I: Segmentation and Surface Reconstruction. Neuroimage 9, 179-194. 1999. Fischl, B., Sereno, M.I., Dale, A.M., Cortical surface-based analysis. II: Inflation, flattening, and a surface-based coordinate system. Neuroimage 9, 195-207. -- 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/

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Brighter image at baseline vs. follow up using longitudinal processing stream
by Tamara Tavares 14 Dec '16

14 Dec '16

Hello, I am in the process of checking the alignment of my participant's baseline and followup scans to the template scan using the norm.mgz files. I notice that sometimes the image appears brighter in the first scan vs. the second follow up scan. Is this problematic? I don't see any clear distortions or translations when I compare the participant's scan to the template. Thank you in advance for your help! Tamara

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Longitudinal base creating in version 5.1 vs 5.3
by Allison Rainford 14 Dec '16

14 Dec '16

Hi FreeSurfer team, My lab is looking at longitudinal data across 5 time points for each subject. All of our time points have been edited in version 5.1 for consistency. However, I have run into an issue when trying to create the bases for these subjects in this version due to a memory allocation problem. It appears that 5.1 cannot allocate enough memory to store the temporary files for each of these time points and consequently errors out during the registration stage with this message: Iteration(f): 2terminate called after throwing an instance of 'std::bad_alloc' what(): St9bad_alloc I also tried creating the base using a memory flag (-m) to allocate more memory but had no luck in those attempts. I tried creating the base in version 5.3 and this ran successfully. However, because this is a longitudinal data set ran in version 5.1, it's problematic that the jobs crash in 5.1. Is there anyway to allocate sufficient memory in 5.1? Thank you, Allison Rainford Research Study Assistant Cognitive Neurology and Alzheimer's Disease Center Northwestern University 320 East Superior Street Searle 11-579 Chicago, Illinois 60611 Email: allison.rainford(a)northwestern.edu

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recon-all -s <subj> -localGI
by André Schmidt 14 Dec '16

14 Dec '16

Dear experts I am trying to compute the local gyrification index but I am not sure how I have to do the following: "You will also need $FREESURFER_HOME/matlab in your matlab path set up in your ~/matlab/starup.m script." Can you please quickly help me what I need to type in the terminal to do this in order to run recon-all -s <subj> -localGI? Many thanks for your help! Best wishes André

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dimensions of the segmented MRI
by Aya Kabbara 14 Dec '16

14 Dec '16

Dear freesurfer team, Do we have the option when using "recon-all" command to predefine the dimensions of the segmented MRI? (for example 145*174*145 with 1.25 mm). Thank you a lot, Aya

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question white matter analysis
by tom parker 14 Dec '16

14 Dec '16

Dear FreeSurfers, Thanks for the previous reply on what the white.K and white.H are. I would like to make an analysis in Qdec using one of these measures. However, I didn't find much information online so I would like to ask you 3 final things: 1. Which of the two measures (mean, gaussian) is more suitable for an analysis of white matter volume/curvature? 2. How can I apply some smoothing to the white.K and white.H files to be able to make an analysis in Qdec? 3. Should I include ITV as a covariate in these analyses? Thank you so much!

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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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