[Freesurfer] QDEC table loading errors

[James Porter]

  
  
Hello-
  
  I'm having a resurgence of an old problem
  (http://www.mail-archive.com/freesurfer@nmr.mgh.harvard.edu/msg12152.html)
  but the old solution is not cutting it. When I try to load a table
  in QDEC 1.4, I get the following error:
  
   Loading data table qdec.table.dat...
   ERROR: QdecDataTable::Load did not find a column named 'fsid',
  'ID', or 'Subject' in the first column of qdec.table.dat!
   Error loading the data table.
  
  However, the file definitely does have 'fsid' as the first column.
  
head qdec.table.dat | awk '{print $1, $2, $3}'
   fsid Sex AgeGrp
   14080 Female Oldr
   14081 Female Oldr
   14286 Female Oldr
   14287 Female Oldr
   14390 Female Oldr
   14391 Male Oldr
   14392 Male Oldr
   14428 Female Oldr
   14430 Male Oldr
  
  Creating the file on Windows, Mac, and Unix platforms using a
  variety of programs (kate, oocalc, text wrangler, excel, word,
  notepad, etc) with 'fsid', 'ID', or 'Subject' as the column title
  doesn't help, nor does running dos2unix on the file(s). Having tab
  delimited or space delimited files doesn't make any difference,
  either. Trying to open the tables with QDEC in Unix (RedHat) or
  Mac (10.6.4) doesn't change the outcome. 
  
  Any ideas on how to solve this riddle?
  
  Thanks,
  Jim

-- 
Jim Porter, M.A.
Graduate Student
Clinical Science and Psychopathology Research
University of Minnesota


  

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Re: [Freesurfer] QDEC table loading errors

[James Porter]

  
  
Of course, once I ask
  for help I stumble immediately upon the solution. There appears to
  be a limit to the number of columns that QDEC is willing to put up
  with when reading in tables. If I create a table that only has the
  few columns that I'm interested in (as opposed to the kitchen sink
  spreadsheet I was working with), then it reads in without
error. 

Thanks for the help by proxy! 
Jim


On 9/22/10 10:38 AM, Nick Schmansky wrote:

  can you send me the file?  

n.

On Wed, 2010-09-22 at 10:28 -0500, James Porter wrote:

  
Hello-

I'm having a resurgence of an old problem
(http://www.mail-archive.com/freesurfer@nmr.mgh.harvard.edu/msg12152.html) but the old solution is not cutting it. When I try to load a table in QDEC 1.4, I get the following error:

Loading data table qdec.table.dat...
ERROR: QdecDataTable::Load did not find a column named 'fsid',
'ID', or 'Subject' in the first column of qdec.table.dat!
Error loading the data table.

However, the file definitely does have 'fsid' as the first column.

 head qdec.table.dat | awk '{print $1, $2, $3}'
fsid Sex AgeGrp
14080 Female Oldr
14081 Female Oldr
14286 Female Oldr
14287 Female Oldr
14390 Female Oldr
14391 Male Oldr
14392 Male Oldr
14428 Female Oldr
14430 Male Oldr

Creating the file on Windows, Mac, and Unix platforms using a variety
of programs (kate, oocalc, text wrangler, excel, word, notepad, etc)
with 'fsid', 'ID', or 'Subject' as the column title doesn't help, nor
does running dos2unix on the file(s). Having tab delimited or space
delimited files doesn't make any difference, either. Trying to open
the tables with QDEC in Unix (RedHat) or Mac (10.6.4) doesn't change
the outcome. 

Any ideas on how to solve this riddle?

Thanks,
Jim
-- 
Jim Porter, M.A.
Graduate Student
Clinical Science and Psychopathology Research
University of Minnesota

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[Freesurfer] FDR Calculations

[James Porter]

Hello-

Does the built-in FDR function in tksurfer and QDEC run the calculations 
upon the actual values in the .mgh files, or does it take the exponent 
of those -log10(p) values first?

-- 
Jim Porter, M.A.
Graduate Student
Clinical Science  Psychopathology Research
University of Minnesota

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Re: [Freesurfer] question about clustering simulation

[James Porter]

Is there an updated version of mri_mcsim available? When I try to run 
it, all I get back are error messages that none of the option flags are 
valid (e.g., ERROR: Option --base unknown).

Thanks,
Jim

Jim Porter, M.A.
Graduate Student
Clinical Science  Psychopathology Research
University of Minnesota


On 7/22/64 1:59 PM, James Porter wrote:
 Hello Doug-

 When using mri_mcsim, is there an option to reduce the iterations of 
 fwhm values? I'd like to create a database of sims within an in-house 
 average subject as well as within different labels, but I have no need 
 for 30 fwhm values. If I could restrict it to just a few choice 
 values, that would be great.

 Jim Porter, M.A.
 Graduate Student
 Clinical Science  Psychopathology Research
 University of Minnesota


 On 7/22/64 1:59 PM, Douglas N Greve wrote:
 use the value in the fwhm.dat. I would always round up to be safe.

 doug

 Michael Waskom wrote:
 Hi Doug,

 This looks very helpful!  Should we use the fwhm size corresponding 
 to the argument of the --fwhm flag when recon-all runs mri_surf2surf 
 (for anatomical stats), or round the measure found in the fwhm.dat 
 of the glmfit dir?

 Thanks,
 Mike

 -- Forwarded message --
 From: Douglas N Greve gr...@nmr.mgh.harvard.edu 
 mailto:gr...@nmr.mgh.harvard.edu
 To: port...@umn.edu mailto:port...@umn.edu
 Date: Tue, 27 Apr 2010 11:17:24 -0400
 Subject: Re: [Freesurfer] question about clustering simulation
 Yea, that was a bug in the simulation program I used. I did confirm 
 that the simulations were done on the correct hemisphere. Feel free 
 to edit the files. I'll fix the master when I get a chance.

 doug

 James Porter wrote:

 Doug-

 Let me be the first to say thank you for saving me massive amounts
 of simulation time. One bug though: the right hemisphere files say
 they were created using the left hemisphere, and mri_surfcluster
 rejects them. Would it be verboten to just alter the csd files, or
 do you have versions that were created off of fsaverage's right
 hemisphere?

 matacao:mult-comp-cor porterj$ head
 fsaverage/rh/cortex/fwhm19/abs/th33/mc-z.csd
 # simtype null-z
 # anattype surface  fsaverage lh
 # FixGroupSubjectArea 1
 # merged  0
 # contrastNA
 # seed1271355821
 # thresh  3.30
 # threshsign  0.00
 # searchspace 74490.928733
 # nullfwhm19.00

 Jim Porter, M.A.
 Graduate Student
 Clinical Science  Psychopathology Research
 University of Minnesota


 On 7/22/64 1:59 PM, Douglas N Greve wrote:

 1. Correct on both counts. When I wrote the simulation, I was
 only trying to replicate the random fields analysis. But with
 a simulation, you have more freedom that I am not yet 
 exploiting.
 2. This is what we are already doing with mc-z
 3. I'm working on this as well. It turns out that the random
 fields approximation works a lot better when using the number
 of vertices.

 Also, I've run mc-z simulations under a bunch of thresholding
 and FWHM conditions for whole-hemisphere cortex labels. These
 will be integrated in new version of  FS, but I've put them
 here
 
 ftp://surfer.nmr.mgh.harvard.edu/transfer/outgoing/flat/greve/mult-comp-cor.tar.gz
  

 as well. There's a README file in there. This will make
 running your own time-consuming simulations unnecessary (when
 using the cortex mask at least).

 doug

 Anthony Dick wrote:

 Hello all,

 I am interested in using the mri_glmfit simulation to
 control for multiple comparisons in data I have run on the
 surface in AFNI. Before doing this, I have a few questions:

 1. What does the simulation with the mc-z flag do,
 exactly? It claims to be comparable to AFNI's AlphaSim,
 but it takes a maximum cluster area for each iteration,
 which is not exactly what AlphaSim does. Here is my guess:

 Given a surface, a given smoothness of the data, and a
 given per-vertex threshold, for each iteration the
 simulation populates that surface with random data taken
 from a normal distribution, thresholds the data, and
 applies the smoothness of the actual data (supplied as an
 input parameter). It then computes the maximum cluster
 size in area for that image. Doing this n iterations
 gives a distribution of maximum cluster sizes that occur
 for random data of a given smoothness, and taking cluster
 sizes above a certain percentile rank controls for the FWE
 at a level equal to that percentile rank (e.g., 95th%
 controls for FWE = .05). AlphaSim does something similar,
 although instead of taking maximum cluster sizes

[Freesurfer] ASCII to MGH

[James Porter]

Hello-

I know how to use mri_convert and mris_convert to obtain ascii files of 
thickness values that I can read into stats software, but I'm having 
trouble going the other direction. Is there a good way to convert ascii 
lists of vertex values into mgh files so I can view them as overlays or 
utilize commands like mri_surfcluster?

Thanks,
Jim

-- 
Jim Porter, M.A.
Graduate Student
Clinical Science  Psychopathology Research
University of Minnesota

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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
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but does not contain patient information, please contact the sender and properly
dispose of the e-mail.

Re: [Freesurfer] question about clustering simulation

[James Porter]

Hello Doug-

When using mri_mcsim, is there an option to reduce the iterations of 
fwhm values? I'd like to create a database of sims within an in-house 
average subject as well as within different labels, but I have no need 
for 30 fwhm values. If I could restrict it to just a few choice values, 
that would be great.

Jim Porter, M.A.
Graduate Student
Clinical Science  Psychopathology Research
University of Minnesota


On 7/22/64 1:59 PM, Douglas N Greve wrote:
 use the value in the fwhm.dat. I would always round up to be safe.

 doug

 Michael Waskom wrote:
 Hi Doug,

 This looks very helpful!  Should we use the fwhm size corresponding 
 to the argument of the --fwhm flag when recon-all runs mri_surf2surf 
 (for anatomical stats), or round the measure found in the fwhm.dat of 
 the glmfit dir?

 Thanks,
 Mike

 -- Forwarded message --
 From: Douglas N Greve gr...@nmr.mgh.harvard.edu 
 mailto:gr...@nmr.mgh.harvard.edu
 To: port...@umn.edu mailto:port...@umn.edu
 Date: Tue, 27 Apr 2010 11:17:24 -0400
 Subject: Re: [Freesurfer] question about clustering simulation
 Yea, that was a bug in the simulation program I used. I did confirm 
 that the simulations were done on the correct hemisphere. Feel free 
 to edit the files. I'll fix the master when I get a chance.

 doug

 James Porter wrote:

 Doug-

 Let me be the first to say thank you for saving me massive amounts
 of simulation time. One bug though: the right hemisphere files say
 they were created using the left hemisphere, and mri_surfcluster
 rejects them. Would it be verboten to just alter the csd files, or
 do you have versions that were created off of fsaverage's right
 hemisphere?

 matacao:mult-comp-cor porterj$ head
 fsaverage/rh/cortex/fwhm19/abs/th33/mc-z.csd
 # simtype null-z
 # anattype surface  fsaverage lh
 # FixGroupSubjectArea 1
 # merged  0
 # contrastNA
 # seed1271355821
 # thresh  3.30
 # threshsign  0.00
 # searchspace 74490.928733
 # nullfwhm19.00

 Jim Porter, M.A.
 Graduate Student
 Clinical Science  Psychopathology Research
 University of Minnesota


 On 7/22/64 1:59 PM, Douglas N Greve wrote:

 1. Correct on both counts. When I wrote the simulation, I was
 only trying to replicate the random fields analysis. But with
 a simulation, you have more freedom that I am not yet 
 exploiting.
 2. This is what we are already doing with mc-z
 3. I'm working on this as well. It turns out that the random
 fields approximation works a lot better when using the number
 of vertices.

 Also, I've run mc-z simulations under a bunch of thresholding
 and FWHM conditions for whole-hemisphere cortex labels. These
 will be integrated in new version of  FS, but I've put them
 here
 
 ftp://surfer.nmr.mgh.harvard.edu/transfer/outgoing/flat/greve/mult-comp-cor.tar.gz
  

 as well. There's a README file in there. This will make
 running your own time-consuming simulations unnecessary (when
 using the cortex mask at least).

 doug

 Anthony Dick wrote:

 Hello all,

 I am interested in using the mri_glmfit simulation to
 control for multiple comparisons in data I have run on the
 surface in AFNI. Before doing this, I have a few questions:

 1. What does the simulation with the mc-z flag do,
 exactly? It claims to be comparable to AFNI's AlphaSim,
 but it takes a maximum cluster area for each iteration,
 which is not exactly what AlphaSim does. Here is my guess:

 Given a surface, a given smoothness of the data, and a
 given per-vertex threshold, for each iteration the
 simulation populates that surface with random data taken
 from a normal distribution, thresholds the data, and
 applies the smoothness of the actual data (supplied as an
 input parameter). It then computes the maximum cluster
 size in area for that image. Doing this n iterations
 gives a distribution of maximum cluster sizes that occur
 for random data of a given smoothness, and taking cluster
 sizes above a certain percentile rank controls for the FWE
 at a level equal to that percentile rank (e.g., 95th%
 controls for FWE = .05). AlphaSim does something similar,
 although instead of taking maximum cluster sizes at each
 iteration it computes all given cluster sizes. AlphaSim
 also allows for different cluster connectivity radius, but
 it seems Freesurfer computes only for neighboring
 vertices. All in all, if this is correct, it seems like a
 good implementation.

 2. It is my understanding

Re: [Freesurfer] question about clustering simulation

[James Porter]

Doug-

Let me be the first to say thank you for saving me massive amounts of 
simulation time. One bug though: the right hemisphere files say they 
were created using the left hemisphere, and mri_surfcluster rejects 
them. Would it be verboten to just alter the csd files, or do you have 
versions that were created off of fsaverage's right hemisphere?

matacao:mult-comp-cor porterj$ head 
fsaverage/rh/cortex/fwhm19/abs/th33/mc-z.csd
# simtype null-z
# anattype surface  fsaverage lh
# FixGroupSubjectArea 1
# merged  0
# contrastNA
# seed1271355821
# thresh  3.30
# threshsign  0.00
# searchspace 74490.928733
# nullfwhm19.00

Jim Porter, M.A.
Graduate Student
Clinical Science  Psychopathology Research
University of Minnesota


On 7/22/64 1:59 PM, Douglas N Greve wrote:
 1. Correct on both counts. When I wrote the simulation, I was only 
 trying to replicate the random fields analysis. But with a simulation, 
 you have more freedom that I am not yet exploiting.
 2. This is what we are already doing with mc-z
 3. I'm working on this as well. It turns out that the random fields 
 approximation works a lot better when using the number of vertices.

 Also, I've run mc-z simulations under a bunch of thresholding and FWHM 
 conditions for whole-hemisphere cortex labels. These will be 
 integrated in new version of  FS, but I've put them here 
 ftp://surfer.nmr.mgh.harvard.edu/transfer/outgoing/flat/greve/mult-comp-cor.tar.gz
  
 as well. There's a README file in there. This will make running your 
 own time-consuming simulations unnecessary (when using the cortex mask 
 at least).

 doug

 Anthony Dick wrote:
 Hello all,

 I am interested in using the mri_glmfit simulation to control for 
 multiple comparisons in data I have run on the surface in AFNI. 
 Before doing this, I have a few questions:

 1. What does the simulation with the mc-z flag do, exactly? It claims 
 to be comparable to AFNI's AlphaSim, but it takes a maximum cluster 
 area for each iteration, which is not exactly what AlphaSim does. 
 Here is my guess:

 Given a surface, a given smoothness of the data, and a given 
 per-vertex threshold, for each iteration the simulation populates 
 that surface with random data taken from a normal distribution, 
 thresholds the data, and applies the smoothness of the actual data 
 (supplied as an input parameter). It then computes the maximum 
 cluster size in area for that image. Doing this n iterations gives 
 a distribution of maximum cluster sizes that occur for random data of 
 a given smoothness, and taking cluster sizes above a certain 
 percentile rank controls for the FWE at a level equal to that 
 percentile rank (e.g., 95th% controls for FWE = .05). AlphaSim does 
 something similar, although instead of taking maximum cluster sizes 
 at each iteration it computes all given cluster sizes. AlphaSim also 
 allows for different cluster connectivity radius, but it seems 
 Freesurfer computes only for neighboring vertices. All in all, if 
 this is correct, it seems like a good implementation.

 2. It is my understanding that one could bypass running the glm in 
 Freesurfer and only compute the simulation, as the simulation only 
 needs information about the surface, and the smoothness of the data 
 (which are supplied by the user). To do so, you have to fake out 
 Freesurfer to bypass glm, but that turns out to be pretty painless.

 3. In a future distribution, is it possible to modify this procedure 
 to also output maximum cluster sizes in terms of number of nodes, 
 rather than area?

 Can you please let me know if I am mistaken in any of these 
 assumptions? Thanks in advance.

 Anthony


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contains patient information, please contact the Partners Compliance HelpLine at
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but does not contain patient information, please contact the sender and properly
dispose of the e-mail.

Re: [Freesurfer] Intersection of labels with other labels or volumes

[James Porter]

Hi Nick-

I've shortened the run time of the script (attached) by comparing the 
size of the two labels and restricting the search to only those vertices 
that exist in the smaller label.


My logic is that there can't possibly be any more matching vertices than 
the size of the smaller label, so I may as well only act upon the 
smaller search space. If label A has 50,000 vertices and label B has 
1,000 vertices, well, then I've saved 49,000 searches. This might not be 
a big deal for any individual iteration of the script, but it adds up 
when I'm running the script on 2 hemispheres by 35 aparc labels by 168 
subjects!


Please let me know if I've missed some fundamental piece of info on the 
nature of labels and it would be better to stick with the longer version.


Thanks again for all of your help!

(David Brang- I copied you on this because I think your recent post can 
be answered by the thread that I have going here with Nick. The attached 
script could easily be altered to find the intersection of all of the 
labels you've created.)


-
Jim Porter
Graduate Student
Clinical Science  Psychopathology Research
University of Minnesota

Nick Schmansky wrote:

Jim

Ok, one more time, attached is another iteration of the
labels_intersection and labels_union scripts.  These ignore the x,y,z
and stats columns, looking only at the vertex numbers.  In the case of
identical vertices, the x,y,z,stats column data from the first file arg
are included in the output file. 


Nick


On Sun, 2009-08-30 at 19:37 -0500, James Porter wrote:

FYI, Nick-

It may be something to do with the 'comm' program on Mac OS X (assuming 
that you wrote the scripts on a UNIX machine), but the labels_intersect 
file doesn't quite work properly. However, I do get correct intersection 
results from the labels_union script by simply switching 'uniq -u' to 
'uniq -d' and leaving everything else the same. Below you can see that 
there are identical lines in the two files, 'comm' doesn't find them, 
and 'uniq -d' does find them.



$ grep 42796 TEST.zero.label
42796  -22.144  -40.241  27.868 0.00
142796  -4.945  52.116  -14.802 0.00

$ grep 42796 aparc_labels/lh.postcentral.label
42796  -22.144  -40.241  27.868 0.0

$ labels_intersect TEST.zero.label lh.postcentral.label Int.label

$ head Int.label
#!ascii label  , from subject 17682 vox2ras=TkReg
0

$ labels_intersect_jim TEST.zero.label lh.postcentral.label JimInt.label

$ head JimInt.label
#!ascii label  , from subject 17682 vox2ras=TkReg
1175
42796  -22.144  -40.241  27.868 0.00
43946  -22.166  -39.570  28.120 0.00
43953  -22.313  -39.961  27.481 0.00
45154  -21.927  -37.868  29.306 0.00
45167  -22.067  -38.462  27.645 0.00
45168  -22.290  -38.809  28.096 0.00
45173  -21.669  -38.528  26.871 0.00
45174  -22.199  -39.236  27.196 0.00

Also of note, if the 5th stats column in the label files are different, 
no union or intersection is correctly found. The labels generated by 
mri_surfcluster have the cluster pval from the monte carlo simulations 
in the 5th column, but the labels generated by mri_annotation2label just 
have zeros. It's easy enough to fix with sed, though.


Thanks for the help!

-
Jim Porter
Graduate Student
Clinical Science  Psychopathology Research
University of Minnesota

Nick Schmansky wrote:

Jim,

Attached are two scripts for getting the union or intersect of two label
files.

Nick

On Thu, 2009-08-27 at 20:32 -0500, James Porter wrote:

Hello-

Is there a simple way to obtain the intersection of two labels, output
into a third label? Or the intersection of a label and an .mgh file 
output by mri_surfcluster?


For instance, I have a cluster defined by mri_glmfit/mri_surfcluster 
that spans multiple anatomical regions, and I want to investigate the
values from subsections of the cluster. That is to say, I want to run 
mris_anatomical_stats on only the section of my cluster that covers, 
say, precentral cortex but not caudal middle frontal or pars opercularis.


I've tried several strategies without success. The most promising seemed 
to be just having mri_surfcluster output an aparc file, and then pass 
that aparc file into mris_anatomical_stats. However, that aparc just 
puts the very first region definition to every vertex. The same happens 
if I run mri_label2aparc on the labels output by mri_surfcluster. This 
happens no matter which LUT or ctab I use, i.e., with aparc.annot.ctab 
the whole volume gets labeled bankssts and with FreeSurferColorLUT.txt 
every vertex in the cluster volume gets labeled Left-Cerebral-Exterior.


I guess there are a few issues in this email, but the most important one 
to me is being able to run mris_anatomical_stats on the union of a 
cluster file and the individual regions from the standard aparc atlas.


Any suggestions?

Thanks in advance,
-
Jim Porter
Graduate Student
Clinical Science  Psychopathology Research
University of Minnesota

Re: [Freesurfer] Intersection of labels with other labels or volumes

[James Porter]

FYI, Nick-

It may be something to do with the 'comm' program on Mac OS X (assuming 
that you wrote the scripts on a UNIX machine), but the labels_intersect 
file doesn't quite work properly. However, I do get correct intersection 
results from the labels_union script by simply switching 'uniq -u' to 
'uniq -d' and leaving everything else the same. Below you can see that 
there are identical lines in the two files, 'comm' doesn't find them, 
and 'uniq -d' does find them.


$ grep 42796 TEST.zero.label
42796  -22.144  -40.241  27.868 0.00
142796  -4.945  52.116  -14.802 0.00

$ grep 42796 aparc_labels/lh.postcentral.label
42796  -22.144  -40.241  27.868 0.0

$ labels_intersect TEST.zero.label lh.postcentral.label Int.label

$ head Int.label
#!ascii label  , from subject 17682 vox2ras=TkReg
0

$ labels_intersect_jim TEST.zero.label lh.postcentral.label JimInt.label

$ head JimInt.label
#!ascii label  , from subject 17682 vox2ras=TkReg
1175
42796  -22.144  -40.241  27.868 0.00
43946  -22.166  -39.570  28.120 0.00
43953  -22.313  -39.961  27.481 0.00
45154  -21.927  -37.868  29.306 0.00
45167  -22.067  -38.462  27.645 0.00
45168  -22.290  -38.809  28.096 0.00
45173  -21.669  -38.528  26.871 0.00
45174  -22.199  -39.236  27.196 0.00

Also of note, if the 5th stats column in the label files are different, 
no union or intersection is correctly found. The labels generated by 
mri_surfcluster have the cluster pval from the monte carlo simulations 
in the 5th column, but the labels generated by mri_annotation2label just 
have zeros. It's easy enough to fix with sed, though.

Thanks for the help!

-
Jim Porter
Graduate Student
Clinical Science  Psychopathology Research
University of Minnesota

Nick Schmansky wrote:
 Jim,
 
 Attached are two scripts for getting the union or intersect of two label
 files.
 
 Nick
 
 On Thu, 2009-08-27 at 20:32 -0500, James Porter wrote:
 Hello-

 Is there a simple way to obtain the intersection of two labels, output
 into a third label? Or the intersection of a label and an .mgh file 
 output by mri_surfcluster?

 For instance, I have a cluster defined by mri_glmfit/mri_surfcluster 
 that spans multiple anatomical regions, and I want to investigate the
 values from subsections of the cluster. That is to say, I want to run 
 mris_anatomical_stats on only the section of my cluster that covers, 
 say, precentral cortex but not caudal middle frontal or pars opercularis.

 I've tried several strategies without success. The most promising seemed 
 to be just having mri_surfcluster output an aparc file, and then pass 
 that aparc file into mris_anatomical_stats. However, that aparc just 
 puts the very first region definition to every vertex. The same happens 
 if I run mri_label2aparc on the labels output by mri_surfcluster. This 
 happens no matter which LUT or ctab I use, i.e., with aparc.annot.ctab 
 the whole volume gets labeled bankssts and with FreeSurferColorLUT.txt 
 every vertex in the cluster volume gets labeled Left-Cerebral-Exterior.

 I guess there are a few issues in this email, but the most important one 
 to me is being able to run mris_anatomical_stats on the union of a 
 cluster file and the individual regions from the standard aparc atlas.

 Any suggestions?

 Thanks in advance,
 -
 Jim Porter
 Graduate Student
 Clinical Science  Psychopathology Research
 University of Minnesota

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[Freesurfer] Intersection of labels with other labels or volumes

[James Porter]

Hello-

Is there a simple way to obtain the intersection of two labels, output
into a third label? Or the intersection of a label and an .mgh file 
output by mri_surfcluster?

For instance, I have a cluster defined by mri_glmfit/mri_surfcluster 
that spans multiple anatomical regions, and I want to investigate the
values from subsections of the cluster. That is to say, I want to run 
mris_anatomical_stats on only the section of my cluster that covers, 
say, precentral cortex but not caudal middle frontal or pars opercularis.

I've tried several strategies without success. The most promising seemed 
to be just having mri_surfcluster output an aparc file, and then pass 
that aparc file into mris_anatomical_stats. However, that aparc just 
puts the very first region definition to every vertex. The same happens 
if I run mri_label2aparc on the labels output by mri_surfcluster. This 
happens no matter which LUT or ctab I use, i.e., with aparc.annot.ctab 
the whole volume gets labeled bankssts and with FreeSurferColorLUT.txt 
every vertex in the cluster volume gets labeled Left-Cerebral-Exterior.

I guess there are a few issues in this email, but the most important one 
to me is being able to run mris_anatomical_stats on the union of a 
cluster file and the individual regions from the standard aparc atlas.

Any suggestions?

Thanks in advance,
-
Jim Porter
Graduate Student
Clinical Science  Psychopathology Research
University of Minnesota

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Re: [Freesurfer] Clusterwise correction

[James Porter]

I have recently run simulations with and without the FWHM flag, and the 
results were 100% identical, in both the mgh output and cluster summary 
files. From what is below, I would think that the results should have 
changed in at least some way. The original qdec analysis was run with 
10mm smoothing, and the sims (mc-full, 10k) were run with and without 
10mm smoothing.

Is there a certain point at which one would not expect smoothing in the 
simulations to not matter?

-
Jim Porter
Graduate Student
Clinical Science  Psychopathology Research
University of Minnesota

Douglas N Greve wrote:
 div class=moz-text-flowed style=font-family: -moz-fixed1) The 
 smoother the data, the more likely a cluster will be found by chance. 
 When the data are created, they start with some smoothness level. When 
 you smooth them you add more. So you need to match the total level of 
 smoothing when you do the simulations, otherwise your clusters will be 
 way too significant. mri_glmfit creates a fwhm.dat file with an estimate 
 of the total smoothness.
 
 2) Just if they are nearest neighbors. There is no option to tinker with 
 this.
 
 3) Vertices in the maps created by the simulation are thresholded at the 
 level you pass. This is what defines the cluster.
 
 doug
 
 Dankner, Nathan (NIH/NIMH) [F] wrote:
 Hello all,

 I have a couple of questions regarding the way the cluster correction 
 simulation in freesurfer works.  I've read the wiki pages on the 
 subject, but if I've missed something and any of this is answered 
 elsewhere please let me know.  My technical knowledge of these things 
 is not great so I am just trying to get some background.  First of 
 all, how does smoothing the data prior to running the simulation 
 affect the results?  I've run corrections on the same data smoothed 
 with a 10mm FWHM, and also on completely unsmoothed data, and the 
 cluster results were different.  Secondly, what determines whether 
 vertices are neighbors or not?  Is there an option to tinker with this 
 or is it predetermined?  Lastly, how do the p values of individual 
 vertices factor into the simulation?  Are they taken into account when 
 the determination of the max cluster size under the null hypothesis is 
 performed?  Thanks in advance,

 Nate

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Re: [Freesurfer] Clusterwise correction

[James Porter]

Sorry, I mistyped. To clarify, the original qdec analyses were run on 
the 10mm smoothed data from qcache, and the sims were then run with and 
without passing the value from fwhm.dat into the FWHM flag in mri_glmfit.

-
Jim Porter
Graduate Student
Clinical Science  Psychopathology Research
University of Minnesota

James Porter wrote:
 I have recently run simulations with and without the FWHM flag, and the 
 results were 100% identical, in both the mgh output and cluster summary 
 files. From what is below, I would think that the results should have 
 changed in at least some way. The original qdec analysis was run with 
 10mm smoothing, and the sims (mc-full, 10k) were run with and without 
 10mm smoothing.
 
 Is there a certain point at which one would not expect smoothing in the 
 simulations to not matter?
 
 -
 Jim Porter
 Graduate Student
 Clinical Science  Psychopathology Research
 University of Minnesota
 
 Douglas N Greve wrote:
 div class=moz-text-flowed style=font-family: -moz-fixed1) The 
 smoother the data, the more likely a cluster will be found by chance. 
 When the data are created, they start with some smoothness level. When 
 you smooth them you add more. So you need to match the total level of 
 smoothing when you do the simulations, otherwise your clusters will be 
 way too significant. mri_glmfit creates a fwhm.dat file with an 
 estimate of the total smoothness.

 2) Just if they are nearest neighbors. There is no option to tinker 
 with this.

 3) Vertices in the maps created by the simulation are thresholded at 
 the level you pass. This is what defines the cluster.

 doug

 Dankner, Nathan (NIH/NIMH) [F] wrote:
 Hello all,

 I have a couple of questions regarding the way the cluster correction 
 simulation in freesurfer works.  I've read the wiki pages on the 
 subject, but if I've missed something and any of this is answered 
 elsewhere please let me know.  My technical knowledge of these things 
 is not great so I am just trying to get some background.  First of 
 all, how does smoothing the data prior to running the simulation 
 affect the results?  I've run corrections on the same data smoothed 
 with a 10mm FWHM, and also on completely unsmoothed data, and the 
 cluster results were different.  Secondly, what determines whether 
 vertices are neighbors or not?  Is there an option to tinker with 
 this or is it predetermined?  Lastly, how do the p values of 
 individual vertices factor into the simulation?  Are they taken into 
 account when the determination of the max cluster size under the null 
 hypothesis is performed?  Thanks in advance,

 Nate

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Re: [Freesurfer] Clusterwise correction

[James Porter]

Hi Doug-

You can see the full logs  a screenshot of the mgh files here:
https://netfiles.umn.edu/xythoswfs/webui/_xy-10431983_1-t_4xQ4HIVC

Below are the commands (full pathways removed for brevity) that I ran.

-Jim


# mri glmfit command  fwhm listing from original qdec log
mri_glmfit --y 168.All.FAS.lh.qdec/y.mgh --fsgd 
168.All.FAS.lh.qdec/qdec.fsgd dods --glmdir 168.All.FAS.lh.qdec --surf 
fsaverage lh --label $SUBJECTS_DIR/fsaverage/label/lh.cortex.label --C 
168.All.FAS.lh.qdec/contrasts/lh-Avg-Intercept-thickness.mat --C 
168.All.FAS.lh.qdec/contrasts/lh-Avg-thickness-FAS_Tot-Cor.mat

ResidualFWHM 16.296576


# an example of the glmfit simulation commands with smoothing
cd 168.All.FAS.lh.qdec/
mri_glmfit --y y.mgh --C contrasts/lh-Avg-thickness-FAS_Tot-Cor.mat 
--mask mask.mgh --sim mc-z 500 1.3 csd/mc-z.abs.p05.sim1 --sim-sign abs 
--fwhm 16.296576 --fsgd y.fsgd --surf fsaverage lh


# command for clustering of the doubly smoothed data
# note: if I try to pass fwhm into mri_surfcluster, I get an error that 
it can't be done with the 'abs' flag
mri_surfcluster --hemi lh --subject fsaverage --in 
lh-Avg-thickness-FAS_Tot-Cor/sig.mgh --sum 
lh-Avg-thickness-FAS_Tot-Cor/sig.mc-z.p001.sum --cwsig 
lh-Avg-thickness-FAS_Tot-Cor/sig.mc-z.p001.mgh --annot aparc --thmin 3 
--sign abs --csd 
csd/mc-z.abs.p001.sim10-lh-Avg-thickness-FAS_Tot-Cor.csd --csd 
csd/mc-z.abs.p001.sim1-lh-Avg-thickness-FAS_Tot-Cor.csd --csd 
csd/mc-z.abs.p001.sim2-lh-Avg-thickness-FAS_Tot-Cor.csd --csd 
csd/mc-z.abs.p001.sim3-lh-Avg-thickness-FAS_Tot-Cor.csd --csd 
csd/mc-z.abs.p001.sim4-lh-Avg-thickness-FAS_Tot-Cor.csd --csd 
csd/mc-z.abs.p001.sim5-lh-Avg-thickness-FAS_Tot-Cor.csd --csd 
csd/mc-z.abs.p001.sim6-lh-Avg-thickness-FAS_Tot-Cor.csd --csd 
csd/mc-z.abs.p001.sim7-lh-Avg-thickness-FAS_Tot-Cor.csd --csd 
csd/mc-z.abs.p001.sim8-lh-Avg-thickness-FAS_Tot-Cor.csd --csd 
csd/mc-z.abs.p001.sim9-lh-Avg-thickness-FAS_Tot-Cor.csd


# command from the no smoothing glmfit sims
cd 168.All.FAS.lh.qdec/
mri_glmfit --y y.mgh --C contrasts/lh-Avg-thickness-FAS_Tot-Cor.mat 
--mask mask.mgh --sim mc-z 500 3 csd/mc-z.nosmooth.abs.p001.sim2 
--sim-sign abs --fwhm 0 --fsgd y.fsgd --surf fsaverage lh

# no smoothing clustering command
mri_surfcluster --hemi lh --subject fsaverage --in 
lh-Avg-thickness-FAS_Tot-Cor/sig.mgh --sum 
lh-Avg-thickness-FAS_Tot-Cor/sig.mc-z.nosmooth.p001.sum --cwsig 
lh-Avg-thickness-FAS_Tot-Cor/sig.mc-z.nosmooth.p001.mgh --annot aparc 
--thmin 3 --sign abs --olab FAS_168.All.FAS.lh.mc-z.nosmooth.p001 --csd 
csd/mc-z.nosmooth.abs.p001.sim10-lh-Avg-thickness-FAS_Tot-Cor.csd --csd 
csd/mc-z.nosmooth.abs.p001.sim1-lh-Avg-thickness-FAS_Tot-Cor.csd --csd 
csd/mc-z.nosmooth.abs.p001.sim2-lh-Avg-thickness-FAS_Tot-Cor.csd --csd 
csd/mc-z.nosmooth.abs.p001.sim3-lh-Avg-thickness-FAS_Tot-Cor.csd --csd 
csd/mc-z.nosmooth.abs.p001.sim4-lh-Avg-thickness-FAS_Tot-Cor.csd --csd 
csd/mc-z.nosmooth.abs.p001.sim5-lh-Avg-thickness-FAS_Tot-Cor.csd --csd 
csd/mc-z.nosmooth.abs.p001.sim6-lh-Avg-thickness-FAS_Tot-Cor.csd --csd 
csd/mc-z.nosmooth.abs.p001.sim7-lh-Avg-thickness-FAS_Tot-Cor.csd --csd 
csd/mc-z.nosmooth.abs.p001.sim8-lh-Avg-thickness-FAS_Tot-Cor.csd --csd 
csd/mc-z.nosmooth.abs.p001.sim9-lh-Avg-thickness-FAS_Tot-Cor.csd



Douglas N Greve wrote:
 Can you send your mri_glmfit and mri_surfcluster command-lines?
 
 doug
 
 James Porter wrote:
 Sorry, I mistyped. To clarify, the original qdec analyses were run on 
 the 10mm smoothed data from qcache, and the sims were then run with 
 and without passing the value from fwhm.dat into the FWHM flag in 
 mri_glmfit.

 -
 Jim Porter
 Graduate Student
 Clinical Science  Psychopathology Research
 University of Minnesota

 James Porter wrote:
 I have recently run simulations with and without the FWHM flag, and 
 the results were 100% identical, in both the mgh output and cluster 
 summary files. From what is below, I would think that the results 
 should have changed in at least some way. The original qdec analysis 
 was run with 10mm smoothing, and the sims (mc-full, 10k) were run 
 with and without 10mm smoothing.

 Is there a certain point at which one would not expect smoothing in 
 the simulations to not matter?

 -
 Jim Porter
 Graduate Student
 Clinical Science  Psychopathology Research
 University of Minnesota

 Douglas N Greve wrote:
 div class=moz-text-flowed style=font-family: -moz-fixed1) The 
 smoother the data, the more likely a cluster will be found by 
 chance. When the data are created, they start with some smoothness 
 level. When you smooth them you add more. So you need to match the 
 total level of smoothing when you do the simulations, otherwise your 
 clusters will be way too significant. mri_glmfit creates a fwhm.dat 
 file with an estimate of the total smoothness.

 2) Just if they are nearest neighbors. There is no option to tinker 
 with this.

 3) Vertices in the maps created by the simulation are thresholded at 
 the level you pass. This is what

Re: Re: [Freesurfer] Longitudinal analysis with old version

[James Porter]

As a tangential follow-up question, will the longitudinal analysis
stream be discussed and demonstrated in the upcoming FSL/FreeSurfer
course in San Francisco?

-
Jim Porter
Graduate Student
Clinical Science  Psychopathology Research
University of Minnesota


Nick Schmansky wrote:

  Leticia,

In the interim until the new longitudinal stream is released, you can
run all your timepoints through the regular stream (recon-all -all), as
this is required in the new stream.  Doing so was not required in the
existing (old) longitudinal stream (only the first timepoint was
required, now all timepoints must be processed).

Nick

On Tue, 2009-05-12 at 14:09 -0400, Bruce Fischl wrote:
  
  
Hi Leticia,

the recon-all -long stuff is not quite ready yet. Hopefully we'll have 
something to distribute within a week or so.

cheers,
Bruce
On Tue, 12 May 2009 
l.gutier...@ion.ucl.ac.uk wrote:



  Hi,

We have installed the 4.0.1 version and we are starting the longitudinal
analysis. I have some problems with -base flag( recon-all -base baseid
-base-insubj tp1subjid -base-insubj tp2subjid ... -all).
Should 4.0.1 version be one problem in order to do that?

Many thanks

Leticia
  
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[Freesurfer] Making Binary Masks

[James Porter]

Hello-

Can somebody point me towards the best way to make a thresholded binary 
mask out of a sig.mgh file that comes out of qdec/mri_glmfit? I'd like 
to take the sig.mgh file and use all values above threshold as a mask 
for another mri_glmfit analysis. I'm used to functional data in FSL, and 
could do this lickety-split with fslmaths or fslroi. Does FreeSurfer 
have a similar set of utilities to be used in manipulating .mgh files?


I've tried to run thresholding within tksurfer, then Save Overlay As 
but that doesn't cut off the sub-threshold values. I'm sure I could draw 
on the surface to trace my supra-threshold areas and create a mask that 
way, but I'd prefer to just do it mathematically if possible. Thanks!


--
-
Jim Porter
Graduate Student
Clinical Science  Psychopathology Research
University of Minnesota

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[Freesurfer] Turn Off Verbose Output

[James Porter]

Howdy-

I didn't see any flags in the help files, but are there some 'hidden' 
commands I could use to attenuate the verbosity of reg-feat2anat and 
aseg2feat?


Thanks,

Jim Porter
TRiCAM Lab Coordinator
Elliott Hall N437
612.624.3892
www.psych.umn.edu/research/tricam http://www.psych.umn.edu/research/tricam

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[Freesurfer] White Matter Parcellation

[James Porter]

Hello-

In September of 2006 there was a post in which you mentioned that white 
matter parcellations were being fine-tuned but not yet ready. I'm really 
hoping to take advantage of the 3000 and 4000 level labels shown in 
FreeSurferColorLUT.txt, but I don't have them in my current 
parcellations that were created using FreeSurfer v3.0.3. Are there 
versions of the parcellation schemes available that I can upgrade to in 
order to obtain these finer white matter parcellations?


Thanks,

Jim Porter
TRiCAM Lab Coordinator
Elliott Hall N437
612.624.3892
www.psych.umn.edu/research/tricam
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