Freesurfer

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30099 discussions

CSF volume
by pfotiad＠nmr.mgh.harvard.edu 19 Jun '14

19 Jun '14

Hi FS community, I was wondering whether there is a way to calculate accurately the CSF volume with FreeSurfer (I have both T1 and T2 images). Should I just add the ventricular structures and the CSF volume reported in aseg.stats or is there another way to account for the sulcal CSF based on the T2 and add it to the other volumes? Thanks in advance, Panos

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Re: [Freesurfer] Seg fault (fwd)
by Cooke, Gillian 19 Jun '14

19 Jun '14

Hi Nick, Thank you so much for your response. Turns out that the XQuartz had updated to 2.7.6, I've reinstalled 2.7.5 and it is working! Finally I can finish this study! Best wishes, Gill _____________________ Gillian Cooke, Ph.D. Postdoctoral Research Associate Lifelong Brain & Cognition Lab Beckman Institute University of Illinois, Urbana Email: gillian.e.cooke(a)gmail.com<mailto:gillian.e.cooke@gmail.com> gcooke(a)illinois.edu<mailto:gcooke@illinois.edu>

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Re: [Freesurfer] Linear Mixed Models in FS?
by jorge luis 19 Jun '14

19 Jun '14

Yes there is numerical instability when p-values becomes extremely low and your solution is OK. You are just being conservative. Your actual p-value might have been 1e-25 but you couldn't observe it exactly (got zero instead) because of numerical limitations of the Matlab's fcdf function. I'll fix this issue on github:https://github.com/NeuroStats this weekend. Best -Jorge >________________________________ > De: Lars M. Rimol <larilin(a)gmail.com> >Para: jorge luis <jbernal0019(a)yahoo.es> >CC: Freesurfer support list <freesurfer(a)nmr.mgh.harvard.edu> >Enviado: Jueves 19 de junio de 2014 5:01 >Asunto: Re: [Freesurfer] Linear Mixed Models in FS? > > > >Hi Jorge, > >Thank you! Yes this makes sense, because this confirms that the second covariate in fact tests for an effect across all groups, just as I expected. >Now, there's another problem with these analyses: Please consider the attached figure lh_model1_01000_interaction_nopatch_lateral.tif, which shows a p-map (cortical > >area, smoothed with 30 mm fwhm) with two gray regions in the temporal lobe and the insula/IFG in the middle of highly significant regions. There is no darker blue transition > >into the non-significant regions. These gray regions appear to be artifacts based on eye balling of the maps. I checked the output of the significance testing in those regions and it > >appears that the output of this formula (in lme_mass_f.m) is extremely low: pval(i) = 1-fcdf(Fstat,szC,m); > >I assume there may be numerical instability when pval becomes extremely low? Could that explain this? > >I changed the code so that if > >1-fcdf(Fstat,szC,m) is zero or less than 1e-15, then pval(i) = max(1-fcdf(Fstat,szC,m),1e-15); > >(or, if it's negative pval(i) = min(1-fcdf(Fstat,szC,m),-1e-15) ) > >If it's not, then the old code applies: pval(i) = 1-fcdf(Fstat,szC,m); > >This seems to have fixed the problem as the figure model1_area_lh_01000_winteraction_wpatch_lateral.tif shows. Again, based on >eye-balling the maps. > >I have seen this problem in several data sets, both cortical and subcortical data. In all cases using a lower limit for 1-fcdf(Fstat,szC,m) - >either 1e-15 or 1e-20 - seems to fix the problem. > >Do you concur that the problem is numerical instability and is this a good way to fix it? > > >Thank you! > >yours, >LMR > > > > > >On Wed, Jun 18, 2014 at 3:49 PM, jorge luis <jbernal0019(a)yahoo.es> wrote: > > >> >>Hi LMR >> >> >>If the interaction term is not statistically significant then there is no evidence of the existence of two different groups in your sample (as far as the longitudinal trajectory is concerned they are all controls, the groups might be different at baseline though). This is why main effects are only tested after the interactions have been previously tested. In your model a common “base time slope” is assumed for both groups (the second coefficient) but you are also explicitly modeling the possibility of the case-group slope being exceeding the control/common base slope by an extra quantity. That quantity is the interaction term. >> >> >>Hope this makes sense >> >> >>Best >>-Jorge >> >> >> >> >> >>>________________________________ >>> De: Lars M. Rimol <larilin(a)gmail.com> >>>Para: FS maling list <freesurfer(a)nmr.mgh.harvard.edu> >>>Enviado: Miércoles 18 de junio de 2014 8:57 >>>Asunto: Re: [Freesurfer] Linear Mixed Models in FS? >>> >>> >>> >>>Hi Jorge, >>> >>>Thank you for your reply! >>> >>>Again considering the same model from before >>> >>> intercept(random effect) + centered age + group + group x centered age + sex >>> >>> >>>I think what is confusing me is that I think of the [centered age] covariate as a column vector which will contain the centered age of both the control- and the case group. This is how it would be seen in a GLM using the same design matrix. Therefore it is difficult for me to understand how the contrast [0 1 0 0 0] can inform us about the control group alone. To me it would seem obvious that this contrast tells me something about the effect of [centered age] on the whole of the sample, regardless of the group each subject belongs to. >>> >>>On the other hand, I agree with you that the interaction term could tell us something about the effect of [centered age] on the case-group by considering the contrast vector [0 0 0 1 0]. >>> >>> >>> >>>Just for the sake of argument, please consider the following model >>> >>> intercept(random effect) + (1-group) x centered age + group + group x centered age + sex >>> >>> >>> >>>and compare to the one presented above. Here (1-group) is a column vector which is 1 where the [group] vector is 0, and vice versa. This difference ensures that the second term only includes numbers from the control-group. Applying the contrast [0 1 0 0 0] to this model, would this not be more appropriate for consider the effect of [centered age] on the control-group alone? >>> >>>Given your previous answers I suspect I'm missing something here, but I would greatly appreciate if you could please take the time to explain to me how I've gone wrong. >>> >>>Thanks! >>>LMR >>> >>> >>>------------------------------------------------------------------- >>>Hi LMR >>> >>>1) Yes, you should >>>use n-1 (0/1) covariates to model n groups. Eg. (Controls, Case 1 >>>and Case 2) the model would be: >>> >>>intercept(random >>>effect) + centered age?(might be a random effect too)?+ ?Case1 + Case1 x centered age + Case2 + >>>Case2 x centered age + sex >>> >>>2)In model: >>> >>>intercept(random >>>effect) + centered age + group + group x centered age + sex >>> >>>the fourth coefficient is >>>the interaction term that represents the difference in slope between >>>the patient and control groups. This is easy to see from your >>>Question 1 equations. It's also easy to see from those equations >>>that [0 1 0 0 0] tests the effect of time in the control group since >>>the group-specific slope is only equal to the coefficient of the time covariate (the >>>second covariate) when the group covariate is zero (i.e for the >>>controls). >>> >>> >>>Hope this makes >>>sense. >>> >>>Best >>>-Jorge >>>-- >>> >>>yours, >>> >>>Lars M. Rimol, PhD >>>St. Olavs Hospital >>>Trondheim, >>>Norway >>>_______________________________________________ >>>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. >>> >>> >>> > > >-- > >yours, > >Lars M. Rimol, PhD >St. Olavs Hospital >Trondheim, >Norway > >

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Can not visualize read_surf.m output with matlab
by ye tian 19 Jun '14

19 Jun '14

Dear Freesurfers, I tried the following in matlab [coords,faces] =read_surf('\subject\surf\rh.orig') Hp = patch('vertices',coords,'faces',faces(:,[1 3 2]),... 'facecolor',[.5 .5 .5],'edgecolor','none') camlight('headlight','infinite') vertnormals = get(Hp,'vertexnormals'); Matlab returns the following error: Error using patch Faces values must be >= 1.0 Indeed, there are 0's in faces. Is this a mistake? Thank you very much! Sincerely, Ye

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GLM: what does "mris_preproc" do?
by ye tian 18 Jun '14

18 Jun '14

Hello Freesurfers, I understand that the output of "mris_preproc" can be the input of "mris_glmfit". In mris_glmfit, a GLM is performed. Does "mris_preproc" give you a smoothed average of all the subjects? If that's the case, how can you perform a GLM with just the average? Don't you need the data (smoothed or not) of all subjects? Thank you very much! Sincerely, Ye

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Mouse use for tkmedit
by Caroline Lewis 18 Jun '14

18 Jun '14

Hi, I'm using freesurfer on a mac computer, and therefore my mouse doesn't have a right click or middle button. Is there an alternative way to make edits in tkmedit (such as to correct voxels erroneously classified as white matter in recon-all) without using the mouse buttons? Thanks, Caroline

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GLM: What's the link?
by ye tian 18 Jun '14

18 Jun '14

Hello Freesurfers, I can not tell what the link is from the Mathematical Background in mri_glmfit . Also, why is GLM performed instead of a linear regression (OLS or weighted LS )? I can not see how logistic, probit, etc is better. Thank you very much! Sincerely, Ye

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FreeSurfur Installation problems
by Jonathan Thomas O'Neil 18 Jun '14

18 Jun '14

Hello, I am having issue with running Tkmedit, tksurfer, qdec, and recon-all. Based on the error messages I am receiving, it appears that the program think I have permission issues. I have checked these and that does not appear to be the case. Here are the errors I am getting. Please let me know what I can do tkmedit: mss169:Desktop jto929$ tkmedit bert orig.mgz =================================== ERROR: A segfault has occurred. This is not your fault, : but is most likely an unrecoverable error and has : made the program unstable. : : Please send the contents of the file .xdebug_tkmedit : that should be in this directory to freesurfer(a)nmr.mgh.harvard.edu<mailto:freesurfer@nmr.mgh.harvard.edu> : : Now exiting... tksurfer: for tksurfer it seems to run, but then stops. a view appears on the screen, but then immediately disappears. s169:Desktop jto929$ tksurfer bert rh pial subject is bert hemi is rh surface is pial surfer: current subjects dir: /Users/jto929/Desktop/freesurfer/subjects surfer: not in "scripts" dir ==> using cwd for session root surfer: session root data dir ($session) set to: surfer: /Users/jto929/Desktop checking for nofix files in 'pial' Reading image info (/Users/jto929/Desktop/freesurfer/subjects/bert) Reading /Users/jto929/Desktop/freesurfer/subjects/bert/mri/orig.mgz surfer: Reading header info from /Users/jto929/Desktop/freesurfer/subjects/bert/mri/orig.mgz surfer: vertices=133299, faces=266594 surfer: single buffered window surfer: tkoInitWindow(bert) mss169:Desktop jto929$ qdec: mss169:Desktop jto929$ qdec Segmentation fault recon-all mss169:Desktop jto929$ recon-all -s bert -autorecon1 INFO: FreeSurfer build stamps do not match Subject Stamp: freesurfer-Linux-centos4-stable-v5.3.0beta-20130503 Current Stamp: freesurfer-Darwin-lion-stable-pub-v5.3.0 INFO: SUBJECTS_DIR is /Users/jto929/Desktop/freesurfer/subjects Actual FREESURFER_HOME /Users/jto929/Desktop/freesurfer rm: /Users/jto929/Desktop/freesurfer/subjects/bert/scripts/recon-all.cmd: Permission denied mv: rename /Users/jto929/Desktop/freesurfer/subjects/bert/scripts/recon-all.env to /Users/jto929/Desktop/freesurfer/subjects/bert/scripts/recon-all.env.bak: Permission denied /Users/jto929/Desktop/freesurfer/subjects/bert/scripts/recon-all.env: Permission denied. /Users/jto929/Desktop/freesurfer/subjects/bert/scripts/recon-all.env: Permission denied.

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Improving translation of Choi striatal ROIs to original domain
by Paul Beach 18 Jun '14

18 Jun '14

Hi Freesurfers, My processing stream involves moving the parcellated functional networks of Yeo and Choi to original subject domain to do connectivity analyses. While my process works very well for the Yeo networks I'm rather unsatisfied by the results of the Choi translations. I'm hoping someone has some suggestions for improving things so that the Choi ROIs map onto individual subjects nearly as well as the general Freesurfer striatal segmentations. NB - I work with AD patients, so I'm sure part of the problem is atrophy-based. However, I'm sure there are ways to improve things... *My current pipeline involves two steps:* *mri_vol2vol \* *--mov Choi2012_17Networks_MNI152_FreeSurferConformed1mm_TightMask.nii.gz \* *--targ $FSLDIR/data/standard/MNI152_T1_2mm_brain.nii.gz --regheader \* *--o FSL_choi_17Net_MNI152_tight_parcellation.nii.gz --no-save-reg --interp nearest* *mri_label2vol \* *--seg FSL_choi_17Net_MNI152_tight_parcellation.nii.gz \* *--reg $SUBJECTS_DIR/{$subj}/mri/transforms/reg.mni152.2mm.dat \* *--invertmtx \* *--o Choi_17Network_tight_striatum_orig.nii.gz \* *--temp $SUBJECTS_DIR/{$subj}/mri/orig.mgz* I suspect one way to improve things would be to do a recon-all based procedure, but I have no clue what commands within the recon-all domain that would involve. Thanks for your suggestions. -- Paul Beach DO/PhD candidate - Year VI Michigan State University - College of Osteopathic Medicine - Neuroscience Program - MSU *Co*gnitive and *Ge*riatric *N*eurology *T*eam (*CoGeNT*)

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Re: [Freesurfer] Linear Mixed Models in FS?
by Lars M. Rimol 18 Jun '14

18 Jun '14

Hi Jorge, Thank you for your reply! Again considering the same model from before intercept(random effect) + centered age + group + group x centered age + sex I think what is confusing me is that I think of the [centered age] covariate as a column vector which will contain the centered age of both the control- and the case group. This is how it would be seen in a GLM using the same design matrix. Therefore it is difficult for me to understand how the contrast [0 1 0 0 0] can inform us about the control group alone. To me it would seem obvious that this contrast tells me something about the effect of [centered age] on the whole of the sample, regardless of the group each subject belongs to. On the other hand, I agree with you that the interaction term could tell us something about the effect of [centered age] on the case-group by considering the contrast vector [0 0 0 1 0]. Just for the sake of argument, please consider the following model intercept(random effect) + (1-group) x centered age + group + group x centered age + sex and compare to the one presented above. Here (1-group) is a column vector which is 1 where the [group] vector is 0, and vice versa. This difference ensures that the second term only includes numbers from the control-group. Applying the contrast [0 1 0 0 0] to this model, would this not be more appropriate for consider the effect of [centered age] on the control-group alone? Given your previous answers I suspect I'm missing something here, but I would greatly appreciate if you could please take the time to explain to me how I've gone wrong. Thanks! LMR ------------------------------------------------------------------- Hi LMR 1) Yes, you should use n-1 (0/1) covariates to model n groups. Eg. (Controls, Case 1 and Case 2) the model would be: intercept(random effect) + centered age?(might be a random effect too)?+ ?Case1 + Case1 x centered age + Case2 + Case2 x centered age + sex 2)In model: intercept(random effect) + centered age + group + group x centered age + sex the fourth coefficient is the interaction term that represents the difference in slope between the patient and control groups. This is easy to see from your Question 1 equations. It's also easy to see from those equations that [0 1 0 0 0] tests the effect of time in the control group since the group-specific slope is only equal to the coefficient of the time covariate (the second covariate) when the group covariate is zero (i.e for the controls). Hope this makes sense. Best -Jorge -- yours, Lars M. Rimol, PhD St. Olavs Hospital Trondheim, Norway

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