Re: [Freesurfer] strange output from lme analysis - Max r value=inf

[Diers, Kersten /DZNE]

Hi Paola,

in the following I assume that you have exactly four groups - and not four 
patient groups plus one group of healthy controls. Please correct me if I am 
wrong.

The mass-univariate tutorial also has four groups (HC, sMCI, cMCI, AD) but you 
will always only see three regressors - three for the group effects, three for 
group-by-time effects, and three for group-by-time-squared effects: all of 
these are only stated for the sMCI, cMCI, AD). However, the HC group is not 
omitted from this model, but chosen as a reference group, and hence implicitly 
modeled.

Assuming exactly four groups in your case, you'd need to do the same, i.e. 
choose one of your groups as a reference group. This means that you should only 
have three group regressors, and three group-by-time interaction regressors.
I hope that I've understood your issues correctly - otherwise let us know.

Best regards,

Kersten

-Original Message-
From: Valsasina Paola 
mailto:valsasina%20paola%20%3cvalsasina.pa...@hsr.it%3e>>
Reply-to: Freesurfer support list 
To: Freesurfer support list 
mailto:freesurfer%20support%20list%20%3cfreesur...@nmr.mgh.harvard.edu%3e>>
Subject: [Freesurfer] strange output from lme analysis - Max r value=inf
Date: Thu, 25 Jan 2018 11:05:42 +0100

Dear all

I am using the lme toolbox to perform a longitudinal comparison of cortical 
thickness among 4 patient groups. Following the lme tutorial, I concatenated 
all files and I built a design matrix with following columns:

-one column for intercept (all ones)
-one column for time
-four columns for each group (1 for subjects belonging to the group, zero 
otherwise)
-four columns for group by time interaction

I then built appropriate contrasts to test the effects of time, group and time 
x group effect; e.g., to test time x group interaction between group 1 and 
group 2, I built the following contrast:

CM.C=[0 0 0 0 0 0 1 -1 0 0]

However, I obtain quite strange results, because I get a lot of very small, 
very significant clusters of difference (having max t value = inf or –inf).
Do you have any idea of the reason why I am getting this strange output? In 
your opinion, is there anything wrong in my design matrix or in the way I 
defined the contrasts?
This is the first time I am trying to compare four groups in the same LME 
models, I previously ran LME statistics including just one or two groups, and 
everything ran smoothly.

Please see a snapshot of my output statistic below:


# ClusterNo  Max   VtxMax   Size(mm^2)  TalX   TalY   TalZNVtxs   Annot
   1 -inf  112586  0.96-19.0  -95.28.3 1  
lateraloccipital
   2 -inf   93693  0.89-22.0   54.4   16.4 1  
rostralmiddlefrontal
   3  inf   29207  0.86-35.9   46.6   -9.9 1  parsorbitalis
   4  inf  158564  0.78-13.7  -98.82.3 1  
lateraloccipital
   5 -inf   67614  0.69 -8.3   35.1   25.4 1  
superiorfrontal
   6 -inf  123144  0.69-40.3   19.5   29.8 1  
caudalmiddlefrontal
   7 -inf2273  0.68-55.6  -30.9   24.2 1  supramarginal
   8 -inf  140663  0.67 -6.2   39.1   -4.4 1  
rostralanteriorcingulate
   9 -inf5857  0.64-35.58.6   50.8 1  
caudalmiddlefrontal
  10  inf   87756  0.61-14.1  -98.21.7 1  
lateraloccipital
  11  inf   95576  0.56-43.9   24.5   27.5 1  
rostralmiddlefrontal
  12 -inf  112122  0.56-29.0  -62.8   35.9 1  
inferiorparietal
  13  inf   54800  0.54-18.7  -59.32.6 1  lingual
  14 -inf  140378  0.53-19.0  -42.5   62.6 1  
superiorparietal
  15  inf   99044  0.49-43.7  -20.0   52.6 1  postcentral
  16  inf  119372  0.47-52.1   -2.5   25.5 1  precentral
  17 -inf  125951  0.47-44.3  -55.1   12.7 1  
inferiorparietal
  18  inf8776  0.46-57.0   -2.0   11.7 1  precentral
  19  inf   10137  0.44-27.8  -49.8   -1.9 1  lingual
  20  inf   20153  0.42 -6.6   13.8   29.5 1  
caudalanteriorcingulate
  21 -inf   19380  0.40-61.6   -8.6   13.7 1  postcentral
  22 -inf   38802  0.39-23.9  -56.1   49.0 1  
superiorparietal
  23  inf   53936  0.38-45.3  -25.9   46.7 1  postcentral
  24  inf   45406  0.35-38.8  -36.8   36.7 1  supramarginal
  25 -inf   46213  0.32 -6.4  -47.6   15.7 1  
isthmuscingulate
  26  inf   41829  0.26-61.1   -8.7   10.5 1  postcentral
  27  -13.032   76609  0.40-14.4  -15.8   64.7 1  precentral
  28   12.272   78924  0.27 -6.0   -6.5   30.3 1  
posteriorcingulate
  29  -10.960 822  0.63-51.8  -30.1  -17.2 1  
inferiortemporal
  30   10.326   96572  0.48-31.7   11.60.5

[Freesurfer] Neurohackademy: summer school in neuroimaging and data science, July 30th - August 10th, 2018

[Ariel Rokem]

We are happy to announce a call for applications to participate in
Neurohackademy 2018!

This two-week hands-on workshop (formerly "Neurohackweek"), held at the
University of Washington eScience Institute in Seattle, July 30th - August
10th, 2018, will focus on technologies used to analyze human neuroscience
data, on methods used to extract information from large datasets of
publicly available data (such as the Human Connectome Project, OpenfMRI,
etc.), and on tools for making human neuroscience research open and
reproducible.

Neurohackademy sessions in the first week will include lectures and
tutorials on data science, machine learning, data visualization and data
resources. The second week will be devoted to participant-directed
activities: guided work on team projects, hackathon sessions, and breakout
sessions on topics of interest.

Instructors include Deanna Barch, Eva Dyer, Fernando Perez, Russ Poldrack,
Jake Vanderplas, Gael Varoquaux, Tor Wager, and Kirstie Whitaker, among
others.

*For more details, see: https://neurohackademy.github.io/
*

We are now accepting applications to participate from trainees and
researchers in different stages of their career (graduate students,
postdocs, faculty, and research staff) at:

https://form.jotform.com/80126067304145

Ideally, applicants should have some prior experience with neuroscience
data analysis, but we welcome applications from participants with a variety
of relevant backgrounds.

Accepted applicants will be asked to pay a fee of $200 upon final
registration. This fee will include participation in the course,
accommodation in the UW dorms, and two meals a day (breakfast and lunch),
for the duration of the course. A limited number of fee waivers and travel
grants will be available. We encourage students with financial need and
students from groups that are underrepresented in neuroimaging and data
science to apply for these grants (see application form for details).

*Important dates:*
*March 19th: Application deadline*
*April 5th: Notification of acceptance*
*April 23rd: Final registration deadline*

On behalf of the instructors,

Ariel Rokem, University of Washington
Tal Yarkoni, University of Texas, Austin
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[Freesurfer] # voxels above thresholds across aparc+aseg regions - mri_segstats?

[Makaretz, Sara Johanna]

Hi FS group,


My goal is to calculate the % of voxels in a given region that are higher than 
a region-specific threshold. This is what I've done so far for each subject:


  *   recon T1
  *   coregister vol.nii to T1
  *   move aparc+aseg.mgz into functional space
  *   mri_segstats --i vol.nii --seg aparc+aseg.functionalspace.nii --sum 
vol.aparc+aseg.stats   to get NVoxels & mean stats


For each subject, for each cortical region (Seg1001-1035 & Seg2001-2035), I now 
want to count the number of voxels that are above region-specific thresholds as 
found in thresh.lst, ie.


  ctx-lh-banksstsSeg10011.383697722
  ctx-lh-caudalanteriorcingulateSeg10021.272858762
  ctx-lh-caudalmiddlefrontalSeg10031.167540497
  ...


Do you have any advice on the best way to do this? I think I can use 
mri_segstats, but am not sure if I'm looking at the right arguments and/or if 
there is a more straightforward way to do this. This is what I have so far:


  foreach s (`cat s.lst`)   /   foreach seg (`cat thresh.lst | awk '{print 
$2}'`)

  set thresh = `cat thresh.lst | grep $seg | awk '{print $3}'`

  mri_segstats --i vol.nii --seg aparc+aseg.functionalspace.nii --id $seg 
--maskthresh $thresh --masksign pos --sum tmp.$seg.stats

  ...and then grep NVoxels from tmp.$seg.stats, grep total NVoxels from 
vol.aparc+aseg.stats, divide/echo into summary stats file?



Thank you in advance for any advice!


Best,

Sara

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[Freesurfer] REPOST: mri_mcsim with mask - How do I map a volume mask to the surface space for mri_mcsim using my own template?

[Charlotte Grosse Wiesmann]

Dear freesurfer experts,

I would like to restrict my surface analyses (cortical thickness and surface 
area) to a mask from an fMRI meta-analysis using my own subject-specific 
template that I created with ANTS. So far, I have used Qdec and wanted to 
correct for cluster size running the Monte Carlo (MC) simulation on my own 
template. 
Now I would like to restrict the simulation to my mask to do a small volume 
correction in my regions of interest. I mapped the mask to my own template (in 
volume space) using ANTS (WarpImageMultiTransform) but how can I get this mask 
to the surface space to run the MC simulation on my own template within this 
mask?

I was planning to do:
mri_mcsim --o my_template/mult-comp-cor/my_template/lh/mymask --base mc-z 
--surface my_template ?h --nreps 1 --mask mymask.mgz

How do I get mymask.mgz in the correct space for this?

And can I continue using Qdec or do I have to use glmfit for these analyses?

In addition: is it also possible to do a small volume correction using FDR 
rather than cluster-size correction?

Thanks for your help!

Charlotte
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[Freesurfer] To Yendiki, Anastasia on TRACULA

[Renew Andrade]

Dear Anastasia:
All the output I get is the if Expression Syntax. 
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Re: [Freesurfer] To Yendiki, Anastasia on TRACULA

[Yendiki, Anastasia]

Can you attach your configuration file please?

On 1/29/18, 2:58 PM, "freesurfer-boun...@nmr.mgh.harvard.edu on behalf of
Renew Andrade"  wrote:

>Dear Anastasia:
>All the output I get is the if Expression Syntax.
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Re: [Freesurfer] aparc-aseg vs aseg label maps

[elisabetta_de...@hms.harvard.edu]

Hi FS team,
running FS 5.3 and checking the labelmaps, there are some differences
between the aseg and the aparc-aseg maps. The aparc-aseg are more inclusive.

My understanding is that volumes for global measures are calculated from
aseg. Could that cause problems in accuracy?
Thank you so much,
best,
Elisabetta




>
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Re: [Freesurfer] aparc-aseg vs aseg label maps

[Bruce Fischl]

Hi Elisabetta

I think in 5.3 we did not edit the aseg using the surfaces, which is 
probably the source of the discrepancy

cheers
Bruce

On Mon, 29 Jan 
2018, elisabetta_de...@hms.harvard.edu wrote:

> Hi FS team,
> running FS 5.3 and checking the labelmaps, there are some differences between 
> the aseg and the
> aparc-aseg maps. The aparc-aseg are more inclusive.
> 
> My understanding is that volumes for global measures are calculated from 
> aseg. Could that cause
> problems in accuracy?
> Thank you so much,
> best,
> Elisabetta
> 
> 
> 
> 
> 
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Re: [Freesurfer] aparc-aseg vs aseg label maps

[elisabetta_de...@hms.harvard.edu]

Bruce, thank you so much.

Another question: Would FS 6.0 give a very different output for cortical
labels than FS 5.3?

Thank you so much again,
best,
Elisabetta


On Mon, Jan 29, 2018 at 11:27 PM, Bruce Fischl 
wrote:

> Hi Elisabetta
>
> I think in 5.3 we did not edit the aseg using the surfaces, which is
> probably the source of the discrepancy
>
> cheers
> Bruce
>
> On Mon, 29 Jan
> 2018, elisabetta_de...@hms.harvard.edu wrote:
>
> > Hi FS team,
> > running FS 5.3 and checking the labelmaps, there are some differences
> between the aseg and the
> > aparc-aseg maps. The aparc-aseg are more inclusive.
> >
> > My understanding is that volumes for global measures are calculated from
> aseg. Could that cause
> > problems in accuracy?
> > Thank you so much,
> > best,
> > Elisabetta
> >
> >
> >
> >
> >
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-- 
*Elisabetta C. del Re, Ph.D.*

*Assistant Professor,*
*Department of Psychiatry*
*Harvard Medical School*
*phone 617 9675569*
*mail elisabetta_de...@hms.harvard.edu *
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Re: [Freesurfer] aparc-aseg vs aseg label maps

[Bruce Fischl]

I don't think very different, but certainly they will change
On Mon, 29 Jan 
2018, elisabetta_de...@hms.harvard.edu wrote:

> Bruce, thank you so much.
> 
> Another question: Would FS 6.0 give a very different output for cortical 
> labels than FS 5.3?
> 
> Thank you so much again,
> best,
> Elisabetta
> 
> 
> On Mon, Jan 29, 2018 at 11:27 PM, Bruce Fischl  
> wrote:
>   Hi Elisabetta
>
>   I think in 5.3 we did not edit the aseg using the surfaces, which is
>   probably the source of the discrepancy
>
>   cheers
>   Bruce
>
>   On Mon, 29 Jan
>   2018, elisabetta_de...@hms.harvard.edu wrote:
>
>   > Hi FS team,
>   > running FS 5.3 and checking the labelmaps, there are some differences 
> between the aseg
>   and the
>   > aparc-aseg maps. The aparc-aseg are more inclusive.
>   >
>   > My understanding is that volumes for global measures are calculated 
> from aseg. Could
>   that cause
>   > problems in accuracy?
>   > Thank you so much,
>   > best,
>   > Elisabetta
>   >
>   >
>   >
>   >
>   >
>   > ___
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>   > 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
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> and properly
>   > dispose of the e-mail.
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>   >
>   >
>   >
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> 
> 
> --
> Elisabetta C. del Re, Ph.D.
> Assistant Professor,
> Department of Psychiatry
> Harvard Medical School
> phone 617 9675569
> mail elisabetta_de...@hms.harvard.edu
> 
>
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Re: [Freesurfer] aparc-aseg vs aseg label maps

[elisabetta_de...@hms.harvard.edu]

Thank you so much,
OK,
best,
Elisabetta

On Mon, Jan 29, 2018 at 11:55 PM, Bruce Fischl 
wrote:

> I don't think very different, but certainly they will change
> On Mon, 29 Jan
> 2018, elisabetta_de...@hms.harvard.edu wrote:
>
> > Bruce, thank you so much.
> >
> > Another question: Would FS 6.0 give a very different output for cortical
> labels than FS 5.3?
> >
> > Thank you so much again,
> > best,
> > Elisabetta
> >
> >
> > On Mon, Jan 29, 2018 at 11:27 PM, Bruce Fischl <
> fis...@nmr.mgh.harvard.edu> wrote:
> >   Hi Elisabetta
> >
> >   I think in 5.3 we did not edit the aseg using the surfaces, which
> is
> >   probably the source of the discrepancy
> >
> >   cheers
> >   Bruce
> >
> >   On Mon, 29 Jan
> >   2018, elisabetta_de...@hms.harvard.edu wrote:
> >
> >   > Hi FS team,
> >   > running FS 5.3 and checking the labelmaps, there are some
> differences between the aseg
> >   and the
> >   > aparc-aseg maps. The aparc-aseg are more inclusive.
> >   >
> >   > My understanding is that volumes for global measures are
> calculated from aseg. Could
> >   that cause
> >   > problems in accuracy?
> >   > Thank you so much,
> >   > best,
> >   > Elisabetta
> >   >
> >   >
> >   >
> >   >
> >   >
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[Freesurfer] Recon-all -nonuintensitycor

[Alexis Moscoso]

Hello Freesurfer developers,

I’m trying to run a recon-all on ADNI T1 images. Since these data have
already been corrected with the N3 correction, I want to turn off N3
correction in the recon-all process so I added -nonuintensitycor after
-all. However, when I run it, I get an error during the normalization step
since it no nu.mgz file is generated and cannot be found by mri_normalize.
I’d like to know how to do the everything except the N3 correction.

1) Freesurfer version: 6.0.0
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Re: [Freesurfer] TRACULA path segmentation fault error because of bedpostx?

[Yendiki, Anastasia]

As a sanity check, you can downsample one of the data sets that fail to 2mm 
iso, and see if it runs that way. This would tell you if it's a data size issue.


From: Carissa Nicole Weis 
Sent: Monday, January 29, 2018 5:53:59 PM
To: Yendiki, Anastasia
Subject: RE: [Freesurfer] TRACULA path segmentation fault error because of 
bedpostx?


I went back and checked and it was just a mistake in our paperwork. All of the 
subjects’ data were acquired at 1x1x2 resolution, but for some reason some of 
the subjects would run through bedp on the first pass while others required 
several passes. I’ve requested additional memory on our cluster to run the 
subjects who stalled, but that didn’t make a difference. If you don’t see any 
potential issues from your end, then I’m beginning to think it could be a 
technical issue with our cluster perhaps it’s timing out or freezing after 
running for too long. I’ll look into this more to see if I can find any issues 
there.



Do you have any other recommendations for troubleshooting at this point?



Thanks,



Carissa



From: Yendiki, Anastasia [mailto:ayend...@mgh.harvard.edu]
Sent: Monday, January 29, 2018 1:54 PM
To: Carissa Nicole Weis 
Subject: Re: [Freesurfer] TRACULA path segmentation fault error because of 
bedpostx?



The subjects that run through with no problems have 2mm isotropic resolution 
and the subjects that give you the segmentation fault have higher resolution? 
Then it sounds like a problem of insufficient memory.



From: Carissa Nicole Weis mailto:cnw...@uwm.edu>>
Sent: Sunday, January 28, 2018 9:44:08 PM
To: Yendiki, Anastasia
Subject: Re: [Freesurfer] TRACULA path segmentation fault error because of 
bedpostx?



My mistake. It was acquired that way.



Also, after running my subjects through the -bedp step several times I’ve now 
only got one subject who is lingering there, but some subjects had to run 7+ 
times through bedp before finishing properly. I do have another dataset to 
analyze that was acquired with the same parameters so it’s quite possible this 
issue may arise again.



Thanks again for your help,



Carissa



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[Freesurfer] FSFAST

[Ashley Cole]

Hello,

I have several nifti files. I have preprocessed some of them before. I used
this command:
preproc-sess -s sess01 -fsd bold -stc odd -surface self lhrh -mni305 -fwhm
5 -per-session -force

The output files contained fmc.odd.sm5.self.lh.nii.gz,
fmc.odd.sm5.self.rh.nii.gz, fmc.odd.sm5.mni305.2mm.nii.gz, and
*fmc.odd.sm5.nii.gz*. Which this last one (fmc.odd.sm5.nii.gz) was the file
that I needed for my further analyses. However, when I run the same command
on another nifti file which was obtained from the same scanner and the same
session, the output doesn't have the fmc.odd.sm5.nii.gz.

I ran it several times but it never gave me that file. Also, it doesn't
give me any errors.

I appreciate any help.

Ash
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Re: [Freesurfer] FSFAST

[Ashley Cole]

I just noticed that that file "fmc.odd.sm5.nii.gz" is created after
selxavg3-sess. I was wondering how can I preprocess the functional image
and have the output with the same dimension as the f.nii.gz without
performing any contrasts. I just need to look at the signal in some ROIs
without performing any contrasts. I hope this makes sense.

Thanks,
Ash

On Mon, Jan 29, 2018 at 10:54 PM, Ashley Cole 
wrote:

> Hello,
>
> I have several nifti files. I have preprocessed some of them before. I
> used this command:
> preproc-sess -s sess01 -fsd bold -stc odd -surface self lhrh -mni305 -fwhm
> 5 -per-session -force
>
> The output files contained fmc.odd.sm5.self.lh.nii.gz,
> fmc.odd.sm5.self.rh.nii.gz, fmc.odd.sm5.mni305.2mm.nii.gz, and
> *fmc.odd.sm5.nii.gz*. Which this last one (fmc.odd.sm5.nii.gz) was the
> file that I needed for my further analyses. However, when I run the same
> command on another nifti file which was obtained from the same scanner and
> the same session, the output doesn't have the fmc.odd.sm5.nii.gz.
>
> I ran it several times but it never gave me that file. Also, it doesn't
> give me any errors.
>
> I appreciate any help.
>
> Ash
>
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Re: [Freesurfer] [freesurfer] Extracting values of cortical thickness in each vertex.

[박경일]

Hi Bruce, I am very new for FS, so did not understand you comments
completely. sorry..

For cortical thickness from each vertex in one subject, which scripts
should follow "mris_convert"?
And another question is how to recognize the location of each vertex in
brain finally.

thank you so much

Kyung


2017-11-13 10:06 GMT+09:00 Bruce Fischl :

> p.s. if you want the vertices to correspond, first run recon-all -qcache
> for each subject. That will generate a set of thickness maps in fsaverage
> space at predefined smoothing levels (so that the vertex numbers correspond
> across subjects)
>
> On Mon, 13 Nov 2017, 박경일 wrote:
>
> Hi Bruce,What I want is the values of cortical thickness in each vertex in
>> each subject. Is that
>>
>> possible?
>> Thanks so much.
>>
>> Kyung
>>
>>
>>
>> 2017-11-13 0:43 GMT+09:00 Bruce Fischl :
>>   Hi Kyung
>>
>>   you can load them into matlab or convert them to ascii if you want
>>   Bruce
>>   On Sun, 12 Nov 2017, 박경일 wrote:
>>
>> Dear FS experts,
>> I could get QDEC image comparing two groups.
>> However, is there a way to get numerical values of cortical
>> thickness in
>> each vertex?
>>
>> Thank you
>>
>> Best,
>> Kyung
>>
>>
>>
>>
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>>
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>> is
>> addressed. If you believe this e-mail was sent to you in error and the
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>>
>>
>>
>> --
>>
>> Kyung-Il Park, MD, PhD.
>>
>> Professor,
>>
>> Department of Neurology, Seoul National University Hospital; Seoul
>> National University Hospital
>> Healthcare System Gangnam Center.
>>
>> Office: 82-2-2112-5756 / Fax: 82-2-2112-5635
>>
>> Email: kip...@snuh.org / ideo...@gmail.com
>>
>>
>>
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>


-- 

Kyung-Il Park, MD, PhD.

Professor,

Department of Neurology, Seoul National University Hospital; Seoul National
University Hospital Healthcare System Gangnam Center.

Office: 82-2-2112-5756 / Fax: 82-2-2112-5635

Email: kip...@snuh.org / ideo...@gmail.com
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