Re: [Freesurfer] Question of longitudinal processing

[Martin Reuter]

Hi Jahanvi, 

I think red is positive (some people invert the colors, then red=hot=dangerous 
). But I think default is blue negative, red positive, so there is an average 
increase in thickness. You should also look at the effect size (gamma). 
The p -values are in log 10 space, so 2 = 0.01 and 5 = 0.1

Best, Martin

> On 17 May 2017, at 22:17, jahanvi patel  wrote:
> 
> Hi Martin,
> 
> Thanks a lot. It had worked nicely.
> I got one question about this following cmd 
> 
> tksurfer fsaverage lh pial -overlay 
> lh.testretest.thickness-pc1.fwhm15/osgm/sig.mgh
> 
> I got a red to yellow sig.mgh, does it mean I got a increased percent 
> thickness change (pc1)? and the color bar showing 2 to 5 means?
> 
> Best,
> Jahanvi
> 
> 
> 
> On Sun, May 14, 2017 at 10:11 PM, Martin Reuter  > wrote:
> Hi Jahanvi, 
> 
> 1. yes, you need to create this table to then perform the stats
> 2. no, the format is as I described it below
> fsidfsid-base
> tp1_subA  templatesubA
> tp2_subA  templatesubA
> tp1_subB  templatesubB
> tp2_subB  templatesubB
> 
> this is assuming that you called your base templatesubA and templatesubB for 
> the two subjects. It will automatically look in the
> tp1_subA.long.templatesubA etc. directories. 
> 
> Best, Martin
> 
>> On 12 May 2017, at 16:55, jahanvi patel > > wrote:
>> 
>> 
>> Hi Martin,
>> 
>> Do you mean by creating this long.testretest.qdec file, one can then perform 
>> the stats for the longitudinal2StageModel?
>> 
>> So for a 2 timepoints analysis, eg. TP1 & TP2.
>>  the long.testretest.qdec will be looking like this  ?
>> 
>> 
>> fsid fsid-base
>> 
>> tp1_subA.long.TemplatesubA tp2_subA.long.TemplatesubA
>> tp1_subB.long.TemplatesubB tp2_subB.long.TemplatesubB
>> tp1_subC.long.TemplatesubC tp2_subC.long.TemplatesubC
>> 
>> .
>> .
>> .
>> 
>> 
>> Thanks,
>> 
>> Jahanvi
>> 
>> 
>> 
>> tksurfer fsaverage lh pial -overlay 
>> lh.testretest.thickness-pc1.fwhm15/osgm/sig.mgh
>> 
>> 
>> Hi Jahanvi,
>> 
>> long.testretest.qdec is a qdec table in the longitudional format (with the 
>> fsid-base as the second column).
>> 
>> For test-retest (e.g. same session with subject removal), you usually don't 
>> need a time column, that is why --generic-time is specified. the qdec table 
>> would just look like
>> 
>> fsid fsid-base
>> 
>> me me_test
>> 
>> me me_retest
>> 
>> you you_test
>> 
>> you you_retest
>> 
>> ...
>> 
>> 
>> Best, Martin
>> 
>> 
>> On 05/08/2017 04:10 PM, jahanvi patel wrote:
>> Hello list,
>> 
>> I have a simple question about the LongitudinalTwoStageModel tutorials on 
>> freesurfer website.
>> 
>> It is from this link
>> https://surfer.nmr.mgh.harvard.edu/fswiki/LongitudinalTwoStageModel 
>> 
>> 
>> 
>> long_mris_slopes --qdec long.testretest.qdec \
>>   --meas thickness \
>>   --hemi lh \
>>   --sd $SUBJECTS_DIR \
>>   --do-pc1 --do-label \
>>   --generic-time \
>>   --fwhm 15 \
>>   --qcache fsaverage \
>>   --stack-pc1 lh.testretest.thickness-pc1.st 
>> ack.mgh \
>>   --isec-labels lh.testretest.fsaverage.cortex.label
>> 
>> My question is, what is the content of  long.testretest.qdec ?
>> I understood till 1st stage was done, we got only one file which is 
>> long.qdec.table.dat.
>> 
>> Could anyone help to clarify my question?
>> 
>> Thanks a lot
>> Jahanvi
>> 
>> 
>> 
>> 
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[Freesurfer] -usegpu vs -parallel in recon-all

[Octavian Lie]

Dear All,

With FS6, -parallel -openmp x can really speed things up. I inherited code
from prior versions using -usegpu flag for GPU/CUDA (not supported more
recently). Is the latter redundant or affecting in any way the -parallel
-openmp x performance, should we take it out, please advise.

Thank you,

Octavian
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[Freesurfer] longitudinal analysis or cross-sectional anslysis of the subfield of hippocampus

[Jinsong Tang]

Dear all,

I have 2 groups (patients and controls), and I want to analysis the
subfields of the hippocampus.
Some of the subjects have 2 scans (before treatment and post treatment) and
some subjects only have one scan(before treatment).
aim 1: I want to compare the subfied volume of the hippocampus between
patients and control using the before treatment data.
aim 2: I also want to calculate the treatment effects on the subfield
volume of the hippocampus.

Do I need to use longitudinal analysis ? or cross-sectional analysis is
fine? If use longitudinal analysis, for the aim 1, only part of the
subjects have 2 scans. I still need to use the cross-sectional data to
calculate the groups' difference in order to include all subjects.

What your suggestions?

Thank you so much!

Best

Jinsong
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Re: [Freesurfer] LME : longitudinal correlations between imaging and cognition scores

[Matthieu Vanhoutte]

Hi Martin,

I will read up on interpretation of time varying covariates.

If initially I use score as variable fixed across time, and define a
variable for 'score x time' interaction:
1) Would putting only 1 to 'score x time' column (for contrast) test for
progression of correlation patterns between atrophy and score ?
2) How to interpret this according to sign  of contrast (knowing that
decrease in score means worse performance) ?

Many thanks for your time and lights !

Best,
Matthieu

Le 17 mai 2017 1:46 PM, "Martin Reuter"  a
écrit :

Hi Matthieu,

replacing time by score is very different from adding score as a covariate.
Often scores are crude and often they are constant in controls (always full
score), and only vary slightly in diseased. In those cases it may not be
good to use score as a time variable.

I would either add avg. score as a variable (fixed across time - would
probably do this for intial testing anyway) or score as time-varying
covariate, but would read up on how to interpret results in the presence of
time-varying-covariates. I am not a statistician.
Best, Martin


On 05/16/2017 08:09 PM, Matthieu Vanhoutte wrote:

Hi Martin,

Thank you for this detailed answer.

Are replacing time by score or include score as time-varying covariate
leading to the same result because of looking at the same effect ?

My willing would be to find patterns of atrophy rate/progression correlated
with cognitive score. In context of AD which method would be the best for
you ?

Best,
Matthieu


Le 16 mai 2017 11:17 AM, "Martin Reuter"  a
écrit :

Hi Matthieu,

one option is to replace time with score in the model. That should be
straight forward.

The other option is to include score as a time-varying covariate. If your
score is not varying much across time and you are more interested if the
average score (or baseline score) affects atrophy rates, you can also
include is as a standard (fixed across time) co-variate (such as baseline
age) with a time (and a group  etc) interaction.

Sorry, but I cannot do your design. Ultimately the model is the research
question that you are asking and it is important that this is done
correctly. Maybe there is a local biostats person that you can talk to?

Best, Martin



On 05/15/2017 08:20 PM, Matthieu Vanhoutte wrote:

Hi Martin,

Thank you. How should this variable be coded ? Should it be as age
covariate where age at baseline is used along all time points of each
subject ?

Could you provide me an example of design matrix, I don't manage to see
what does it look like to.

Best regards,
Matthieu


Le 14 mai 2017 8:08 PM, "Martin Reuter"  a
écrit :

Hi Matthieu,

yes, that is possible. Instead of group, you use a variable for your score
(and interaction etc). Sometimes it may also makes sense to use score
instead of time.

Best, Martin


> On 12 May 2017, at 10:51, Matthieu Vanhoutte 
wrote:
>
> Dear Freesurfer's experts,
>
> I have searched through the mailing list but haven't found any answer to
my question.
>
> Is it possible with LME model to make correlations between for example
cortical thickness surface data and cognition scores along time ? As it is
possible to test for interaction of group X time, is this also in the same
way feasible to test for coognition score X time on cortical thickness ?
>
> Many thanks for your advice !
>
> Best regards,
> Matthieu
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Re: [Freesurfer] Question of longitudinal processing

[jahanvi patel]

Hi Martin,

Thanks a lot. It had worked nicely.
I got one question about this following cmd

tksurfer fsaverage lh pial -overlay
lh.testretest.thickness-pc1.fwhm15/osgm/sig.mgh

I got a red to yellow sig.mgh, does it mean I got a increased percent
thickness change (pc1)? and the color bar showing 2 to 5 means?

Best,
Jahanvi



On Sun, May 14, 2017 at 10:11 PM, Martin Reuter  wrote:

> Hi Jahanvi,
>
> 1. yes, you need to create this table to then perform the stats
> 2. no, the format is as I described it below
> fsidfsid-base
> tp1_subA  templatesubA
> tp2_subA  templatesubA
> tp1_subB  templatesubB
> tp2_subB  templatesubB
>
> this is assuming that you called your base templatesubA and templatesubB
> for the two subjects. It will automatically look in the
> tp1_subA.long.templatesubA etc. directories.
>
> Best, Martin
>
> On 12 May 2017, at 16:55, jahanvi patel  wrote:
>
>
> Hi Martin,
>
> Do you mean by creating this long.testretest.qdec file, one can then
> perform the stats for the longitudinal2StageModel?
>
> So for a 2 timepoints analysis, eg. TP1 & TP2.
>  the long.testretest.qdec will be looking like this  ?
>
>
> fsid fsid-base
>
> tp1_subA.long.TemplatesubA tp2_subA.long.TemplatesubA
> tp1_subB.long.TemplatesubB tp2_subB.long.TemplatesubB
> tp1_subC.long.TemplatesubC tp2_subC.long.TemplatesubC
>
> .
> .
> .
>
>
> Thanks,
>
> Jahanvi
>
>
>
> tksurfer fsaverage lh pial -overlay lh.testretest.thickness-pc1.
> fwhm15/osgm/sig.mgh
>
>
> Hi Jahanvi,
>>
>> long.testretest.qdec is a qdec table in the longitudional format (with
>> the fsid-base as the second column).
>>
>> For test-retest (e.g. same session with subject removal), you usually
>> don't need a time column, that is why --generic-time is specified. the qdec
>> table would just look like
>>
>> fsid fsid-base
>>
>> me me_test
>>
>> me me_retest
>>
>> you you_test
>>
>> you you_retest
>>
>> ...
>>
>>
>> Best, Martin
>>
>>
>> On 05/08/2017 04:10 PM, jahanvi patel wrote:
>> Hello list,
>>
>> I have a simple question about the LongitudinalTwoStageModel tutorials on
>> freesurfer website.
>>
>> It is from this link
>> https://surfer.nmr.mgh.harvard.edu/fswiki/LongitudinalTwoStageModel
>>
>>
>> long_mris_slopes --qdec long.testretest.qdec \
>>   --meas thickness \
>>   --hemi lh \
>>   --sd $SUBJECTS_DIR \
>>   --do-pc1 --do-label \
>>   --generic-time \
>>   --fwhm 15 \
>>   --qcache fsaverage \
>>   --stack-pc1 lh.testretest.thickness-pc1.stack.mgh \
>>   --isec-labels lh.testretest.fsaverage.cortex.label
>>
>> My question is, what is the content of  long.testretest.qdec ?
>> I understood till 1st stage was done, we got only one file which is
>> long.qdec.table.dat.
>>
>> Could anyone help to clarify my question?
>>
>> Thanks a lot
>> Jahanvi
>>
>>
>>
>>
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[Freesurfer] Mean gray-white contrast for each ROI

[Yaakub, Siti Nurbaya]

Hi,

I read from a previous post that the "{lh,rh}.w-g.pct.stats files in 
$SUBJECTS_DIR/subject/stats … will have the mean gray-white contrast for each 
ROI in the aparc."

I've looked at the lh.w-g.pct.stats file and am not sure which values I should 
be looking at if I am interested in the ratio of grey to white matter averaged 
over each of the ROIs? What are the area in mm2 and the SNR in this w-g context?

Thank you,
Siti
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[Freesurfer] Research Assistant Position in Clinical Neuroscience Laboratory

[Herring, Elizabeth J.]

Research Assistant Position

Clinical Neuroscience Laboratory
Department of Psychology
Ohio State University

Applications are being sought for a full-time research assistant position, 
starting June 1st, 2017, in the Clinical Neuroscience 
Laboratory of Dr. Ruchika 
Prakash at the Ohio State University. The laboratory is currently conducting 
several randomized controlled trials, designed to look at the effects of 
lifestyle interventions, such as mindfulness training and exercise intervention 
in improving cognitive and emotional control in older adults and in individuals 
with multiple sclerosis. This position is designed for individuals who are 
interested in building on the research experience that they already have and 
learn about the new field of health neuroscience. Applications are solicited 
from individuals with considerable programming experience, as well as 
experience in neuroimaging data analyses. Knowledge of matlab and an existing 
software package, such as FSL, AFNI, or SPM is desired. Responsibilities will 
include active involvement in all aspects of research, facilitating recruitment 
efforts between the laboratory and community partners, and overseeing 
day-to-day operations of the laboratory.

If you are interested in being considered for the position, please apply online 
at https://www.jobsatosu.com, job listing number 428162 and submit a current 
CV, a brief statement of interest, and names of three references.

If you have questions about the position or the lab, please contact Dr. Ruchika 
Prakash at prakash...@osu.edu

Contact Website: http://freud.psy.ohio-state.edu/lab/CNL/The_Lab.html

The Ohio State University is an equal opportunity employer. All qualified 
applicants will receive consideration for employment without regard to race, 
color, religion, sex, sexual orientation or identity, national origin, 
disability status, or protected veteran status.

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[Freesurfer] Posting to Freesurfer

[Herring, Elizabeth J.]

Hello,

I just subscribed to Freesurfer and I would like to be able to post to the 
list. My email is herring...@osu.edu


Thanks,
Elizabeth Herring
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[Freesurfer] ERROR: must specify input table of b-values

[David Yang]

Hello,


I am trying to run the trac-all -prep command in TRACULA on a participant. 
However, every time I run the command trac-prepoc exits with errors and I get 
the message: 'ERROR:must specify input table of b-values'. I checked over the 
configuration file and everything seems correct: b-value table is specified and 
in the correct 1 column format, and there are the same number of b-values, 
b-vectors and DTI volumes. Does anyone know why I am getting this message?


1) Freesurfer version: freesurfer-Darwin-OSX-stable-pub-v6.0.0-2beb96c

2) Platform:  OS X Mavericks 10.9.5
3) trac-all -prep -c $VSDEVEL_DATA/VSDevel_outputs/dmric_1089001_06M.txt
4) Attached is the configuration file, b-values, b-vectors

Thanks,
David
setenv SUBJECTS_DIR /Users/student/Desktop/VSDevel_data/VSDevel_recons

set dtroot = /Users/student/Desktop/VSDevel_data/VSDevel_outputs

set subjlist = (1089001_06M)

set dcmroot = /Users/student/Desktop/VSDevel_data/VSDevel_outputs

set dcmlist = (1089001_06M/1089001_06M_bedpostx/data.nii.gz)

set bvecfile = 
/Users/student/Desktop/VSDevel_data/VSDevel_outputs/1089001_06M/1089001_06M_bedpostx/bvecs.txt

set bvalfile = 
/Users/student/Desktop/VSDevel_data/VSDevel_outputs/1089001_06M/1089001_06M_bedpostx/bvals.txt0
0
0
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
0
0
0
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2 0 0
0 0 0
0 0 0
-1 0 0
-0.457 0.89 0
0.265 0.485 0.834
-0.937 -0.284 0.202
-0.063 -0.806 0.588
0.679 -0.094 0.728
-0.687 0.279 0.671
0.233 0.95 0.209
-0.923 0.179 0.342
0.111 -0.98 -0.164
0.132 -0.854 -0.503
-0.367 -0.769 -0.523
0.291 -0.705 0.647
0.676 0.714 0.185
0.599 0.078 -0.797
0.733 -0.679 0.039
-0.8 -0.216 -0.559
-0.558 -0.341 -0.756
0.435 -0.599 -0.672
0.785 0.596 -0.17
-0.496 0.791 0.357
0.66 0.434 -0.614
-0.842 -0.145 0.52
-0.144 0.43 0.891
0.302 0.282 -0.911
-0.229 -0.931 0.284
-0.943 0.012 -0.334
-0.011 -0.025 1
-0.403 0.848 -0.345
-0.922 0.388 -0.01
-0.04 0.487 -0.872
0.297 0.146 0.944
0.374 -0.166 -0.912
0.285 -0.22 0.933
0.856 -0.318 0.408
0.903 0.383 0.195
-0.765 0.531 0.364
0.519 -0.427 0.74
-0.669 0.607 -0.429
0.104 -0.973 0.205
0.66 0.57 0.49
0.035 0.691 0.722
-0.333 -0.606 0.722
0 0 0
0 0 0
0 0 0
-1 0 0
-0.457 0.89 0
0.265 0.485 0.834
-0.937 -0.284 0.202
-0.063 -0.806 0.588
0.679 -0.094 0.728
-0.687 0.279 0.671
0.233 0.95 0.209
-0.923 0.179 0.342
0.111 -0.98 -0.164
0.132 -0.854 -0.503
-0.367 -0.769 -0.523
0.291 -0.705 0.647
0.676 0.714 0.185
0.599 0.078 -0.797
0.733 -0.679 0.039
-0.8 -0.216 -0.559
-0.558 -0.341 -0.756
0.435 -0.599 -0.672
0.785 0.596 -0.17
0.66 0.434 -0.614
-0.842 -0.145 0.52
-0.144 0.43 0.891
0.302 0.282 -0.911
-0.229 -0.931 0.284
-0.943 0.012 -0.334
-0.011 -0.025 1
-0.403 0.848 -0.345
-0.922 0.388 -0.01
-0.04 0.487 -0.872
0.297 0.146 0.944
0.374 -0.166 -0.912
0.285 -0.22 0.933
0.856 -0.318 0.408
0.903 0.383 0.195
-0.539 -0.729 0.422
0.478 0.878 -0.04
-0.765 0.531 0.364
0.519 -0.427 0.74
-0.669 0.607 -0.429
0.104 -0.973 0.205
0.66 0.57 0.49
0.035 0.691 0.722
-0.333 -0.606 0.722___
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Re: [Freesurfer] long_stats results for group analysis

[Martin Reuter]

Hi Maria,

That command creates a stack of the percent changes , with one entry per 
subject (it reduces the longitudinal data of a subject to a single 
number, e.g. the percent change computed in different ways).


Make sure you know what the difference is between pc1, pc1fit (in your 
case this is the same , as you only have two time points, so the linear 
fit will go through the two time points), rate, and SPC. I would 
recommend to use spc as it is symmetric.


The -osgd tells GLMFIT that we have a single group and we look for 
difference from zero (of the slope/percent change  of aseg volumes).


So instead of it you can pass --fsgd ... --C ... as in a usual analysis. 
(You should be familiar with fsgd and glmfit, how it is used in a 
standard cross sectional analysis, take a look at

 https://surfer.nmr.mgh.harvard.edu/fswiki/FsTutorial/GroupAnalysis
which is mainly for surface data, but you get the idea. If you have 
questions about glmfit, change the subject title of your email to e.g.

"question about glmfit with tables"

so that the right people will read the question.

Best, Martin



On 05/17/2017 12:55 AM, Maria A Infante wrote:


Hi


I run the commands listed below and I was wondering if there is a way 
to get the average pc1 for each group. I get an average for the entire 
sample. What should I use instead of --osgm?




long_stats_slopes --qdec ./qdec/long.qdec.table.dat --stats aseg.stats 
--meas volume --sd $SUBJECTS_DIR --do-rate --do-pc1fit --do-pc1 
--do-spc --time years --stack-rate 
./qdec/long_3groups.aseg-rate.stack.txt --stack-pc1fit 
./qdec/long_3groups.aseg-pc1fit.stack.txt --stack-pc1 
./qdec/long_3groups.aseg-pc1.stack.txt --stack-spc 
./qdec/long_3groups.aseg-spc.stack.txt


mri_glmfit --osgm --glmdir long_3groups.aseg-pc1 --table 
./qdec/long_3groups.aseg-pc1.stack.txt




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Re: [Freesurfer] LME : longitudinal correlations between imaging and cognition scores

[Martin Reuter]

Hi Matthieu,

replacing time by score is very different from adding score as a 
covariate. Often scores are crude and often they are constant in 
controls (always full score), and only vary slightly in diseased. In 
those cases it may not be good to use score as a time variable.


I would either add avg. score as a variable (fixed across time - would 
probably do this for intial testing anyway) or score as time-varying 
covariate, but would read up on how to interpret results in the presence 
of time-varying-covariates. I am not a statistician.


Best, Martin

On 05/16/2017 08:09 PM, Matthieu Vanhoutte wrote:

Hi Martin,

Thank you for this detailed answer.

Are replacing time by score or include score as time-varying covariate 
leading to the same result because of looking at the same effect ?


My willing would be to find patterns of atrophy rate/progression 
correlated with cognitive score. In context of AD which method would 
be the best for you ?


Best,
Matthieu


Le 16 mai 2017 11:17 AM, "Martin Reuter" > a écrit :


Hi Matthieu,

one option is to replace time with score in the model. That should
be straight forward.

The other option is to include score as a time-varying covariate.
If your score is not varying much across time and you are more
interested if the average score (or baseline score) affects
atrophy rates, you can also include is as a standard (fixed across
time) co-variate (such as baseline age) with a time (and a group 
etc) interaction.


Sorry, but I cannot do your design. Ultimately the model is the
research question that you are asking and it is important that
this is done correctly. Maybe there is a local biostats person
that you can talk to?

Best, Martin



On 05/15/2017 08:20 PM, Matthieu Vanhoutte wrote:

Hi Martin,

Thank you. How should this variable be coded ? Should it be as
age covariate where age at baseline is used along all time points
of each subject ?

Could you provide me an example of design matrix, I don't manage
to see what does it look like to.

Best regards,
Matthieu


Le 14 mai 2017 8:08 PM, "Martin Reuter"
> a écrit :

Hi Matthieu,

yes, that is possible. Instead of group, you use a variable
for your score (and interaction etc). Sometimes it may also
makes sense to use score instead of time.

Best, Martin


> On 12 May 2017, at 10:51, Matthieu Vanhoutte
> wrote:
>
> Dear Freesurfer's experts,
>
> I have searched through the mailing list but haven't found
any answer to my question.
>
> Is it possible with LME model to make correlations between
for example cortical thickness surface data and cognition
scores along time ? As it is possible to test for interaction
of group X time, is this also in the same way feasible to
test for coognition score X time on cortical thickness ?
>
> Many thanks for your advice !
>
> Best regards,
> Matthieu
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