Registered to the subject's anatomical volume (which registers to the surface for free anyways, if I understand correctly).
On Wed, Sep 6, 2017 at 1:38 AM, freesurfer-request@nmr.mgh.harvard.edu wrote:
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Today's Topics:
- Re: controlling for Sex in a model using two continuous variables onto CTh (Douglas N Greve)
- Re: Multi-Subject Comparison in FreeSurfer (Douglas N Greve)
- Re: group interaction with one continuous covariate and three nuisance variables (two continuous, one dichotomous) (Douglas N
Greve) 4. Re: Interpretting Brain Segmentation Volume to eTIV ratio (Douglas N Greve) 5. Problem with ambiguous voxels? (Del Re, Elisabetta) 6. Re: patch for ribbon mgz failure (Douglas N Greve) 7. Re: upsampling ?h.curv (Douglas N Greve) 8. Re: Map of covariance (Douglas N Greve) 9. Fixed Effects Analysis on Single Subject's Brain (Taylor, Johnmark) 10. Re: Freesurfer Preliminary Questions (Douglas N Greve) 11. Re: Occipital Cortex Segmentation (Douglas N Greve) 12. Re: How to estimate the Intracranial area? (Douglas N Greve) 13. Re: Combining Echo Frames Error (Douglas N Greve) 14. Re: individual mri_segstats waveforms for vertices or face in label (Douglas N Greve) 15. Re: Fixed Effects Analysis on Single Subject's Brain (Douglas N Greve) 16. Re: Reliability of labeling procedure in the same scan (Mike Schmidt) 17. Re: Problem with ambiguous voxels? (Bruce Fischl) 18. Re: controlling for Sex in a model using two continuous variables onto CTh (Uquillas, Federico D'Oleire) 19. MNI average brain in Freesurfer space (Anna Kasdan) 20. R: Re: Map of covariance (stdp82@virgilio.it) 21. Re: MNI average brain in Freesurfer space (Douglas N Greve) 22. Re: controlling for Sex in a model using two continuous variables onto CTh (Douglas N Greve) 23. Re: R: Re: Map of covariance (Douglas N Greve) 24. Re: Cortical thickness (Douglas N Greve) 25. Re: sub-cortical analysis (Douglas N Greve) 26. Error with TRACULA using dcm and nii (Ferrier, Christopher Q.) 27. Re: controlling for Sex in a model using two continuous variables onto CTh (Uquillas, Federico D'Oleire) 28. Re: controlling for Sex in a model using two continuous variables onto CTh (Douglas N Greve) 29. Re: controlling for Sex in a model using two continuous variables onto CTh (Uquillas, Federico D'Oleire) 30. Talairach registration error (Ariana Vajdi) 31. Ventricle Volumes Decreasing over time? (Tamara Tavares) 32. Re: Ventricle Volumes Decreasing over time? (Bruce Fischl) 33. Re: Talairach registration error (Douglas Greve) 34. ??: ROI (Jin Bo) 35. Re: wm topological defects (Ruotsalainen, Ilona)
Message: 1 Date: Tue, 5 Sep 2017 12:01:32 -0400 From: Douglas N Greve greve@nmr.mgh.harvard.edu Subject: Re: [Freesurfer] controlling for Sex in a model using two continuous variables onto CTh To: freesurfer@nmr.mgh.harvard.edu Message-ID: c94e8853-6171-8520-1786-e46c2746e870@nmr.mgh.harvard.edu Content-Type: text/plain; charset=utf-8; format=flowed
can you send the fsgd file for the analysis that is failing?
On 08/29/2017 02:29 PM, Uquillas, Federico D'Oleire wrote:
Dear FreeSurfer experts,
We have run a vertex-wise analysis regressing a continuous variable onto cortical thickness on the surface, and would like to verify that our contrast that uses Age and Sex as covariates was defined correctly, especially since there is probably more than one way to control for a binary variable like Sex.
On the website (https://surfer.nmr.mgh.harvard.edu/fswiki/DodsDoss) it suggests to make two regressors, one for Males, and one for Females, where for the former a 1 is indicative of the Male category, and a 1 on the latter is indicative of the Female category. However, using that FSGD file and running a DOSS contrast as [0 1 0 0 0], we get the error: matrix is ill-condition or badly scaled, condno=2.01889e+07. We believe this may be due to the fact that Male and Female categories are autocorrelated and Freesurfer likes variables to be de-meaned. Running a FSGD file with only Age and our variable of interest via a DOSS contrast of [0 1 0] works without any errors.
We thus created an FSGD file where we have Sex as our third variable (in addition to our continuous variable of interest and one demeaned continuous covariate), coding 1s for Males and 0s for Females, and we used a DOSS contrast of [0 1 0 0]. This provided us with a map that makes sense with our expectations.
We would like to verify if this is doing what we believe it is doing; that is, looking at the relationship of our continuous variable or interest after accounting for age and sex. Any thoughts would be greatly appreciated.
Thank you so much.
Best,
Fred
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
-- Douglas N. Greve, Ph.D. MGH-NMR Center greve@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/
Message: 2 Date: Tue, 5 Sep 2017 12:03:27 -0400 From: Douglas N Greve greve@nmr.mgh.harvard.edu Subject: Re: [Freesurfer] Multi-Subject Comparison in FreeSurfer To: freesurfer@nmr.mgh.harvard.edu Message-ID: 36414cb1-e5cb-b192-d1a6-80259da31da4@nmr.mgh.harvard.edu Content-Type: text/plain; charset=windows-1252; format=flowed
You will need to run 500 different recon-all jobs. Obviously, if you run them on a single computer, it will take a long time, so you will need access to a cluster. Or you can buy time on a cloud service.
On 08/29/2017 02:54 PM, Sherrill, John T wrote:
I am a new grad student and have been assigned a project in our Brain Imaging Research Center. I would be taking the time to push through and find these answers on my own but our program gives us 5 weeks of half days in a lab for a trial. So I am in a bit of a time crunch.
I have been given a database of about 500 .nii files and been asked to find duplicates or likely duplicates. (Some subjects were duel-consented so they may have multiple scans.) What is the best way to recon-all all of the files? Individually, in small groups, or in one larger group? If I do it in groups do I need to list each file or can I just recon-all the entire directory? And if a recon-all on 1 file takes 6-20hr, will doing a recon-all on the entire data set take 500*(6-20hr)=3000-10,000hr? Any help is greatly appreciated.
John Sherrill jtsherrill@uams.edu john_sherrill@me.com (870) 761-0580
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-- Douglas N. Greve, Ph.D. MGH-NMR Center greve@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/
Message: 3 Date: Tue, 5 Sep 2017 12:05:42 -0400 From: Douglas N Greve greve@nmr.mgh.harvard.edu Subject: Re: [Freesurfer] group interaction with one continuous covariate and three nuisance variables (two continuous, one dichotomous) To: freesurfer@nmr.mgh.harvard.edu Message-ID: db68777a-81ed-d750-5075-cd6b35992588@nmr.mgh.harvard.edu Content-Type: text/plain; charset=utf-8; format=flowed
try looking at the FSGD examples for a case that you can generalize
https://surfer.nmr.mgh.harvard.edu/fswiki/FsgdExamples
On 08/29/2017 08:59 PM, Ines M?rner-Lavanchy wrote:
Dear FS experts,
I would like to test if the correlations between thickness/area and cognition differ between two groups, while age, socioeconomic status (continuous) and gender (dichotomous) should be nuisance variables.
To look at the effect of cognition in one group only, I made a model with 8 regressors:
- sex male
- sex female
- age male
- age female
- cognition male
- cognition female
- ses male
- ses female
With the contrast 0 0 0 0 0.5 0.5 0 0: how does cognition correlate with Cth/CSA, controlled for age, sex, and ses.
Now how do I model this, if I have *two* groups and want to look at the interaction of group*cognition? I have trouble setting up the fsgd and design matrix.
Any help is appreciated,
Thanks in advance,
Ines
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
-- Douglas N. Greve, Ph.D. MGH-NMR Center greve@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/
Message: 4 Date: Tue, 5 Sep 2017 12:07:41 -0400 From: Douglas N Greve greve@nmr.mgh.harvard.edu Subject: Re: [Freesurfer] Interpretting Brain Segmentation Volume to eTIV ratio To: freesurfer@nmr.mgh.harvard.edu Message-ID: 3b478464-8cc5-e338-170a-0786a153e40a@nmr.mgh.harvard.edu Content-Type: text/plain; charset=windows-1252; format=flowed
I put that in there mainly as a quality check to automatically flag something that has gone wrong. I think something went wrong if the value is 0.65 (unless you have very atrophied subjects). You will have to take a look to see what might have gone wrong.
On 08/29/2017 09:03 PM, Mehta, Chintan wrote:
Dear FreeSurfer community,
I wanted to interpret the BrainSegVol.to.eTIV ratio that is outputted from FreeSurfer version 5.2.0. In my sample of normally developing adolescents of ages 8 to 21, this ratio is between 0.65 and 0.85 for 98% of subjects. However, the value is less than 0.65 for 2% of subjects.
Could this reflect actual feature of brain volume to eTIV?
Or is this a reflection of poor scans, poor overall FreeSurfer processing, or inaccurate eTIV estimates for these subjects? Subjects with BrainSegVol.to.eTIV ratios less than 0.65 tended to all be females. They had Brain Segmentation volumes falling in normal ranges of females in the full sample. However, their eTIV was on the upper-end among eTIVs of females in the sample. If the eTIVs for these subjects were over-inflated, then it makes sense the ratios are especially low.
Thank you.
Best, Chintan
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
-- Douglas N. Greve, Ph.D. MGH-NMR Center greve@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/
Message: 5 Date: Tue, 5 Sep 2017 16:07:37 +0000 From: "Del Re, Elisabetta" Elisabetta_DelRe@hms.harvard.edu Subject: [Freesurfer] Problem with ambiguous voxels? To: "freesurfer@nmr.mgh.harvard.edu" freesurfer@nmr.mgh.harvard.edu Cc: "Somes, Nathaniel G." NSOMES@BWH.HARVARD.EDU Message-ID: <CY4PR07MB2837476706EFA64ABABA2CAEB3960@CY4PR07MB2837. namprd07.prod.outlook.com>
Content-Type: text/plain; charset="iso-8859-1"
Dear FS Team,
We are running recon-all for a large dataset and 5 of the cases keep getting stuck at the exact same spot. It is the point at which the following has just been displayed on the screen:
#@# WM Segmentation Wed Aug 30 17:34:40 EDT 2017
mri_segment brain.mgz wm.seg.mgz
doing initial intensity segmentation... using local statistics to label ambiguous voxels... computing class statistics for intensity windows... WM (107.0): 105.5 +- 6.4 [91.0 --> 125.0] GM (78.0) : 81.0 +- 6.1 [56.0 --> 94.0] setting bottom of white matter range to 87.1 setting top of gray matter range to 93.2 doing initial intensity segmentation... using local statistics to label ambiguous voxels...
For these 5 cases it will sit at this step apparently still running for over a week without any change before I cancel the job. There does not seem to be anything special about these 5 cases either in terms of their header information or visually. We have not found any artifacts in the images except for some minor ringing which is present in many images in the dataset, not just these. The rest of the cases of the dataset all ran to completion and produced all of the files we were expecting, but a subset of them seem to have a related issue where most of the wmparc.mgz labelmap is unsegmented white matter. Only the very edges and the very center are getting designated as something other than this label. The rest of the files in the "mri" directory such as aparc+aseg.mgz and so on are equally as affected by this. Do you know what could be going on here? I would be happy to give you any more information that could be helpful.
Best, Elisabetta and Nate
Elisabetta C. del Re, Ph.D. Assistant Professor of Psychiatry, Department of Psychiatry Harvard Medical School phone 617 9675569 mail elisabetta_delre@hms.harvard.edu
what is this in reference to?
On 9/6/17 2:40 PM, Taylor, Johnmark wrote:
Registered to the subject's anatomical volume (which registers to the surface for free anyways, if I understand correctly).
On Wed, Sep 6, 2017 at 1:38 AM, <freesurfer-request@nmr.mgh.harvard.edu mailto:freesurfer-request@nmr.mgh.harvard.edu> wrote:
Send Freesurfer mailing list submissions to freesurfer@nmr.mgh.harvard.edu <mailto:freesurfer@nmr.mgh.harvard.edu> To subscribe or unsubscribe via the World Wide Web, visit https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer <https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer> or, via email, send a message with subject or body 'help' to freesurfer-request@nmr.mgh.harvard.edu <mailto:freesurfer-request@nmr.mgh.harvard.edu> You can reach the person managing the list at freesurfer-owner@nmr.mgh.harvard.edu <mailto:freesurfer-owner@nmr.mgh.harvard.edu> When replying, please edit your Subject line so it is more specific than "Re: Contents of Freesurfer digest..." Today's Topics: 1. Re: controlling for Sex in a model using two continuous variables onto CTh (Douglas N Greve) 2. Re: Multi-Subject Comparison in FreeSurfer (Douglas N Greve) 3. Re: group interaction with one continuous covariate and three nuisance variables (two continuous, one dichotomous) (Douglas N Greve) 4. Re: Interpretting Brain Segmentation Volume to eTIV ratio (Douglas N Greve) 5. Problem with ambiguous voxels? (Del Re, Elisabetta) 6. Re: patch for ribbon mgz failure (Douglas N Greve) 7. Re: upsampling ?h.curv (Douglas N Greve) 8. Re: Map of covariance (Douglas N Greve) 9. Fixed Effects Analysis on Single Subject's Brain (Taylor, Johnmark) 10. Re: Freesurfer Preliminary Questions (Douglas N Greve) 11. Re: Occipital Cortex Segmentation (Douglas N Greve) 12. Re: How to estimate the Intracranial area? (Douglas N Greve) 13. Re: Combining Echo Frames Error (Douglas N Greve) 14. Re: individual mri_segstats waveforms for vertices or face in label (Douglas N Greve) 15. Re: Fixed Effects Analysis on Single Subject's Brain (Douglas N Greve) 16. Re: Reliability of labeling procedure in the same scan (Mike Schmidt) 17. Re: Problem with ambiguous voxels? (Bruce Fischl) 18. Re: controlling for Sex in a model using two continuous variables onto CTh (Uquillas, Federico D'Oleire) 19. MNI average brain in Freesurfer space (Anna Kasdan) 20. R: Re: Map of covariance (stdp82@virgilio.it <mailto:stdp82@virgilio.it>) 21. Re: MNI average brain in Freesurfer space (Douglas N Greve) 22. Re: controlling for Sex in a model using two continuous variables onto CTh (Douglas N Greve) 23. Re: R: Re: Map of covariance (Douglas N Greve) 24. Re: Cortical thickness (Douglas N Greve) 25. Re: sub-cortical analysis (Douglas N Greve) 26. Error with TRACULA using dcm and nii (Ferrier, Christopher Q.) 27. Re: controlling for Sex in a model using two continuous variables onto CTh (Uquillas, Federico D'Oleire) 28. Re: controlling for Sex in a model using two continuous variables onto CTh (Douglas N Greve) 29. Re: controlling for Sex in a model using two continuous variables onto CTh (Uquillas, Federico D'Oleire) 30. Talairach registration error (Ariana Vajdi) 31. Ventricle Volumes Decreasing over time? (Tamara Tavares) 32. Re: Ventricle Volumes Decreasing over time? (Bruce Fischl) 33. Re: Talairach registration error (Douglas Greve) 34. ??: ROI (Jin Bo) 35. Re: wm topological defects (Ruotsalainen, Ilona) ---------------------------------------------------------------------- Message: 1 Date: Tue, 5 Sep 2017 12:01:32 -0400 From: Douglas N Greve <greve@nmr.mgh.harvard.edu <mailto:greve@nmr.mgh.harvard.edu>> Subject: Re: [Freesurfer] controlling for Sex in a model using two continuous variables onto CTh To: freesurfer@nmr.mgh.harvard.edu <mailto:freesurfer@nmr.mgh.harvard.edu> Message-ID: <c94e8853-6171-8520-1786-e46c2746e870@nmr.mgh.harvard.edu <mailto:c94e8853-6171-8520-1786-e46c2746e870@nmr.mgh.harvard.edu>> Content-Type: text/plain; charset=utf-8; format=flowed can you send the fsgd file for the analysis that is failing? On 08/29/2017 02:29 PM, Uquillas, Federico D'Oleire wrote: > Dear FreeSurfer experts, > > We have run a vertex-wise analysis regressing a continuous variable > onto cortical thickness on the surface, and would like to verify that > our contrast that uses Age and Sex as covariates was defined > correctly, especially since there is probably more than one way to > control for a binary variable like Sex. > > On the website (https://surfer.nmr.mgh.harvard.edu/fswiki/DodsDoss <https://surfer.nmr.mgh.harvard.edu/fswiki/DodsDoss>) it > suggests to make two regressors, one for Males, and one for Females, > where for the former a 1 is indicative of the Male category, and a 1 > on the latter is indicative of the Female category. However, using > that FSGD file and running a DOSS contrast as [0 1 0 0 0], we get the > error: matrix is ill-condition or badly scaled, condno=2.01889e+07. > We believe this may be due to the fact that Male and Female categories > are autocorrelated and Freesurfer likes variables to be de-meaned. > Running a FSGD file with only Age and our variable of interest via a > DOSS contrast of [0 1 0] works without any errors. > > We thus created an FSGD file where we have Sex as our third variable > (in addition to our continuous variable of interest and one demeaned > continuous covariate), coding 1s for Males and 0s for Females, and we > used a DOSS contrast of [0 1 0 0]. This provided us with a map that > makes sense with our expectations. > > We would like to verify if this is doing what we believe it is doing; > that is, looking at the relationship of our continuous variable or > interest after accounting for age and sex. > Any thoughts would be greatly appreciated. > > Thank you so much. > > Best, > > Fred > > > > > > _______________________________________________ > Freesurfer mailing list > 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> -- Douglas N. Greve, Ph.D. MGH-NMR Center greve@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/> ------------------------------ Message: 2 Date: Tue, 5 Sep 2017 12:03:27 -0400 From: Douglas N Greve <greve@nmr.mgh.harvard.edu <mailto:greve@nmr.mgh.harvard.edu>> Subject: Re: [Freesurfer] Multi-Subject Comparison in FreeSurfer To: freesurfer@nmr.mgh.harvard.edu <mailto:freesurfer@nmr.mgh.harvard.edu> Message-ID: <36414cb1-e5cb-b192-d1a6-80259da31da4@nmr.mgh.harvard.edu <mailto:36414cb1-e5cb-b192-d1a6-80259da31da4@nmr.mgh.harvard.edu>> Content-Type: text/plain; charset=windows-1252; format=flowed You will need to run 500 different recon-all jobs. Obviously, if you run them on a single computer, it will take a long time, so you will need access to a cluster. Or you can buy time on a cloud service. On 08/29/2017 02:54 PM, Sherrill, John T wrote: > > I am a new grad student and have been assigned a project in our Brain > Imaging Research Center. I would be taking the time to push through > and find these answers on my own but our program gives us 5 weeks of > half days in a lab for a trial. So I am in a bit of a time crunch. > > I have been given a database of about 500 .nii files and been asked to > find duplicates or likely duplicates. (Some subjects were > duel-consented so they may have multiple scans.) What is the best way > to recon-all all of the files? Individually, in small groups, or in > one larger group? If I do it in groups do I need to list each file or > can I just recon-all the entire directory? And if a recon-all on 1 > file takes 6-20hr, will doing a recon-all on the entire data set take > 500*(6-20hr)=3000-10,000hr? Any help is greatly appreciated. > > John Sherrill > jtsherrill@uams.edu <mailto:jtsherrill@uams.edu> > john_sherrill@me.com <mailto:john_sherrill@me.com> > (870) 761-0580 <tel:%28870%29%20761-0580> > ------------------------------------------------------------------------ > 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. > > > _______________________________________________ > Freesurfer mailing list > 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> -- Douglas N. Greve, Ph.D. MGH-NMR Center greve@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/> ------------------------------ Message: 3 Date: Tue, 5 Sep 2017 12:05:42 -0400 From: Douglas N Greve <greve@nmr.mgh.harvard.edu <mailto:greve@nmr.mgh.harvard.edu>> Subject: Re: [Freesurfer] group interaction with one continuous covariate and three nuisance variables (two continuous, one dichotomous) To: freesurfer@nmr.mgh.harvard.edu <mailto:freesurfer@nmr.mgh.harvard.edu> Message-ID: <db68777a-81ed-d750-5075-cd6b35992588@nmr.mgh.harvard.edu <mailto:db68777a-81ed-d750-5075-cd6b35992588@nmr.mgh.harvard.edu>> Content-Type: text/plain; charset=utf-8; format=flowed try looking at the FSGD examples for a case that you can generalize https://surfer.nmr.mgh.harvard.edu/fswiki/FsgdExamples <https://surfer.nmr.mgh.harvard.edu/fswiki/FsgdExamples> On 08/29/2017 08:59 PM, Ines M?rner-Lavanchy wrote: > > Dear FS experts, > > I would like to test if the correlations between thickness/area and > cognition differ between two groups, while age, socioeconomic status > (continuous) and gender (dichotomous) should be nuisance variables. > > To look at the effect of cognition in one group only, I made a model > with 8 regressors: > > - sex male > - sex female > - age male > - age female > - cognition male > - cognition female > - ses male > - ses female > > With the contrast 0 0 0 0 0.5 0.5 0 0: how does cognition correlate > with Cth/CSA, controlled for age, sex, and ses. > > Now how do I model this, if I have *two* groups and want to look at > the interaction of group*cognition? I have trouble setting up the fsgd > and design matrix. > > Any help is appreciated, > > Thanks in advance, > > Ines > > > > _______________________________________________ > Freesurfer mailing list > 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> -- Douglas N. Greve, Ph.D. MGH-NMR Center greve@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/> ------------------------------ Message: 4 Date: Tue, 5 Sep 2017 12:07:41 -0400 From: Douglas N Greve <greve@nmr.mgh.harvard.edu <mailto:greve@nmr.mgh.harvard.edu>> Subject: Re: [Freesurfer] Interpretting Brain Segmentation Volume to eTIV ratio To: freesurfer@nmr.mgh.harvard.edu <mailto:freesurfer@nmr.mgh.harvard.edu> Message-ID: <3b478464-8cc5-e338-170a-0786a153e40a@nmr.mgh.harvard.edu <mailto:3b478464-8cc5-e338-170a-0786a153e40a@nmr.mgh.harvard.edu>> Content-Type: text/plain; charset=windows-1252; format=flowed I put that in there mainly as a quality check to automatically flag something that has gone wrong. I think something went wrong if the value is 0.65 (unless you have very atrophied subjects). You will have to take a look to see what might have gone wrong. On 08/29/2017 09:03 PM, Mehta, Chintan wrote: > > Dear FreeSurfer community, > > > I wanted to interpret the BrainSegVol.to.eTIV ratio that is outputted > from FreeSurfer version 5.2.0. In my sample of normally developing > adolescents of ages 8 to 21, this ratio is between 0.65 and 0.85 for > 98% of subjects. However, the value is less than 0.65 for 2% of subjects. > > > Could this reflect actual feature of brain volume to eTIV? > > > Or is this a reflection of poor scans, poor overall FreeSurfer > processing, or inaccurate eTIV estimates for these subjects? Subjects > with BrainSegVol.to.eTIV ratios less than 0.65 tended to all be > females. They had Brain Segmentation volumes falling in normal ranges > of females in the full sample. However, their eTIV was on the > upper-end among eTIVs of females in the sample. If the eTIVs for these > subjects were over-inflated, then it makes sense the ratios are > especially low. > > Thank you. > > Best, > Chintan > > > > > _______________________________________________ > Freesurfer mailing list > 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> -- Douglas N. Greve, Ph.D. MGH-NMR Center greve@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/> ------------------------------ Message: 5 Date: Tue, 5 Sep 2017 16:07:37 +0000 From: "Del Re, Elisabetta" <Elisabetta_DelRe@hms.harvard.edu <mailto:Elisabetta_DelRe@hms.harvard.edu>> Subject: [Freesurfer] Problem with ambiguous voxels? To: "freesurfer@nmr.mgh.harvard.edu <mailto:freesurfer@nmr.mgh.harvard.edu>" <freesurfer@nmr.mgh.harvard.edu <mailto:freesurfer@nmr.mgh.harvard.edu>> Cc: "Somes, Nathaniel G." <NSOMES@BWH.HARVARD.EDU <mailto:NSOMES@BWH.HARVARD.EDU>> Message-ID: <CY4PR07MB2837476706EFA64ABABA2CAEB3960@CY4PR07MB2837.namprd07.prod.outlook.com <mailto:CY4PR07MB2837476706EFA64ABABA2CAEB3960@CY4PR07MB2837.namprd07.prod.outlook.com>> Content-Type: text/plain; charset="iso-8859-1" Dear FS Team, We are running recon-all for a large dataset and 5 of the cases keep getting stuck at the exact same spot. It is the point at which the following has just been displayed on the screen: #@# WM Segmentation Wed Aug 30 17:34:40 EDT 2017 mri_segment brain.mgz wm.seg.mgz doing initial intensity segmentation... using local statistics to label ambiguous voxels... computing class statistics for intensity windows... WM (107.0): 105.5 +- 6.4 [91.0 --> 125.0] GM (78.0) : 81.0 +- 6.1 [56.0 --> 94.0] setting bottom of white matter range to 87.1 setting top of gray matter range to 93.2 doing initial intensity segmentation... using local statistics to label ambiguous voxels... For these 5 cases it will sit at this step apparently still running for over a week without any change before I cancel the job. There does not seem to be anything special about these 5 cases either in terms of their header information or visually. We have not found any artifacts in the images except for some minor ringing which is present in many images in the dataset, not just these. The rest of the cases of the dataset all ran to completion and produced all of the files we were expecting, but a subset of them seem to have a related issue where most of the wmparc.mgz labelmap is unsegmented white matter. Only the very edges and the very center are getting designated as something other than this label. The rest of the files in the "mri" directory such as aparc+aseg.mgz and so on are equally as affected by this. Do you know what could be going on here? I would be happy to give you any more information that could be helpful. Best, Elisabetta and Nate Elisabetta C. del Re, Ph.D. Assistant Professor of Psychiatry, Department of Psychiatry Harvard Medical School phone 617 9675569 mail elisabetta_delre@hms.harvard.edu <mailto:elisabetta_delre@hms.harvard.edu>
freesurfer@nmr.mgh.harvard.edu
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Douglas Greve -
Taylor, Johnmark