Re: [Freesurfer] Compare individual to a group

[Douglas N. Greve]

Did you try specifying your xformed file as the argument to --cached-in ?
If that does not work, then transform the thickness in the native 
surface,then run mris_preproc, then smooth with mris_fwhm


On 5/12/2020 11:37 PM, Xiaojiang Yang wrote:


External Email - Use Caution

Hi Douglas,

I have tried to follow your suggestion to use the transformed 
thickness file like this:


mris_preproc --fsgd xxx.fsgd \

        --meas $meas.fwhm$smoothing.xformed.mgz \

    --target fsaverage \

    --hemi $hemi \

    --out $hemi.$meas.$smoothing.mgh

But it says $meas.fwhm$smoothing.xformed.mgz does not match surface 
(163842,166904).


My files $meas.fwhm$smoothing.xformed.mgz come from 
$meas.fwhm$smoothing.fsaverage (just by multiplying it with a weight). 
If I use “--cache-in” in the mris_preproc like below:


mris_preproc --fsgd xxx.fsgd \

        --cache-in 
$meas.fwhm$smoothing.fsaverage \


    --target fsaverage \

    --hemi $hemi \

    --out $hemi.$meas.$smoothing.mgh

The above command line runs fine.

I know the problem in the first command line might be that the files 
$meas.fwhm$smoothing.xformed.mgz are already on the fsaverage surface, 
not the subject surface. But mris_preproc is still trying to use 
mri_surf2surf to resample those mgh file from the subject surface to 
fsaverage surface, which leads to the “does not match surface” error.


*My question is*: How can I tell mris_preproc to regard those 
transformed files to be on the fsaverage surface already (instead of 
subject’s surface), just like the second command line where the 
“–cache-in” option is used?


You know, my transformed files are Just derived from cached files 
$hemi.$meas.fwhm$smoothing.fsaverage.mgh in the $subject/surf 
directories. I do not want to use mri_surf2surf to transform them to 
the subject surface first, and then let mris_preproc transform them 
back to fsaverage surface again.


Thanks!

Xiao


Douglas N. Greve 
Mon, 
11 May 2020 14:14:42 -0700 



Just call your thickness file some other name, 
eg,lh.xformed.thickness.mgz, the just specify --meas xformed.thickness.mgz


On 5/11/2020 3:52 PM, Xiaojiang Yang wrote:
External Email - Use Caution
Thank you Douglas!

If I apply my transform to both the healthy controls and the patient,I 
guess I would losethe convenience of using mri_glmfit, whicheventually 
loses the convenience of using mri-glmfit-sim (I don't carenot 
usingmri_glmfit, but I want to use mri_glmfit-sim to do 
multiplecomparisonscorrection). That is because mri_glmfit uses the 
preparedoutput from mris_preproc, which I have no control over to use 
thetransformed subject. The only way I can circumvent this is to use 
mytransformed thickness file to overwrite the FS calculated 
thicknessfile, but that is what I am hesitant to do. If you have 
goodsuggestions regardingthis, please let me know. Thanks!


Xiao

On Mon, May 11, 2020 at 12:25 PM Douglas N. 
Grevemailto:dgr...@mgh.harvard.edu>> wrote:


    I guess you could apply your transform to both the healthy
    controls and to your patient, can then create an FSGD file with
    two classes as before but no continuous variable. Then just have a
    contrast that computes the diff between the patient and the mean
    of the controls.


___
Freesurfer mailing list
Freesurfer@nmr.mgh.harvard.edu
https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer


___
Freesurfer mailing list
Freesurfer@nmr.mgh.harvard.edu
https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer

Re: [Freesurfer] Compare individual to a group

[Xiaojiang Yang]

External Email - Use Caution

Hi Douglas,

I have tried to follow your suggestion to use the transformed thickness file
like this:

mris_preproc --fsgd xxx.fsgd \

--meas $meas.fwhm$smoothing.xformed.mgz \

--target fsaverage \

--hemi $hemi \

--out $hemi.$meas.$smoothing.mgh

But it says $meas.fwhm$smoothing.xformed.mgz does not match surface
(163842,166904).

My files $meas.fwhm$smoothing.xformed.mgz come from
$meas.fwhm$smoothing.fsaverage (just by multiplying it with a weight). If I
use "--cache-in" in the mris_preproc like below:

mris_preproc --fsgd xxx.fsgd \

--cache-in $meas.fwhm$smoothing.fsaverage \

--target fsaverage \

--hemi $hemi \

--out $hemi.$meas.$smoothing.mgh

The above command line runs fine.

I know the problem in the first command line might be that the files
$meas.fwhm$smoothing.xformed.mgz are already on the fsaverage surface, not
the subject surface. But mris_preproc is still trying to use mri_surf2surf
to resample those mgh file from the subject surface to fsaverage surface,
which leads to the "does not match surface" error. 

My question is: How can I tell mris_preproc to regard those transformed
files to be on the fsaverage surface already (instead of subject's surface),
just like the second command line where the "-cache-in" option is used? 

You know, my transformed files are Just derived from cached files
$hemi.$meas.fwhm$smoothing.fsaverage.mgh in the $subject/surf directories. I
do not want to use mri_surf2surf to transform them to the subject surface
first, and then let mris_preproc transform them back to fsaverage surface
again.

 

Thanks!

Xiao

 
 
Douglas N. Greve
 Mon, 11 May 2020 14:14:42 -0700

Just call your thickness file some other name, eg, lh.xformed.thickness.mgz,
the just specify --meas xformed.thickness.mgz

 
On 5/11/2020 3:52 PM, Xiaojiang Yang wrote:
 
External Email - Use Caution
 
Thank you Douglas!

If I apply my transform to both the healthy controls and the patient, I
guess I would lose the convenience of using mri_glmfit, which eventually
loses the convenience of using mri-glmfit-sim (I don't care not using
mri_glmfit, but I want to use mri_glmfit-sim to do multiple comparisons
correction). That is because mri_glmfit uses the prepared output from
mris_preproc, which I have no control over to use the transformed subject.
The only way I can circumvent this is to use my transformed thickness file
to overwrite the FS calculated thickness file, but that is what I am
hesitant to do. If you have good suggestions regarding this, please let me
know. Thanks!

Xiao
 
 

On Mon, May 11, 2020 at 12:25 PM Douglas N. Greve mailto:dgr...@mgh.harvard.edu> mailto:dgr...@mgh.harvard.edu>> wrote:

 
I guess you could apply your transform to both the healthy
controls and to your patient, can then create an FSGD file with
two classes as before but no continuous variable. Then just have a
contrast that computes the diff between the patient and the mean
of the controls.

 

___
Freesurfer mailing list
Freesurfer@nmr.mgh.harvard.edu
https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer

Re: [Freesurfer] Compare individual to a group

[Douglas N. Greve]

Just call your thickness file some other name, eg, 
lh.xformed.thickness.mgz, the just specify --meas xformed.thickness.mgz


On 5/11/2020 3:52 PM, Xiaojiang Yang wrote:


External Email - Use Caution

Thank you Douglas!
If I apply my transform to both the healthy controls and the patient, 
I guess I would lose the convenience of using mri_glmfit, which 
eventually loses the convenience of using mri-glmfit-sim (I don't care 
not using mri_glmfit, but I want to use mri_glmfit-sim to do multiple 
comparisons correction). That is because mri_glmfit uses the prepared 
output from mris_preproc, which I have no control over to use the 
transformed subject. The only way I can circumvent this is to use my 
transformed thickness file to overwrite the FS calculated thickness 
file, but that is what I am hesitant to do. If you have good 
suggestions regarding this, please let me know. Thanks!

Xiao


On Mon, May 11, 2020 at 12:25 PM Douglas N. Greve 
mailto:dgr...@mgh.harvard.edu>> wrote:


I guess you could apply your transform to both the healthy
controls and to your patient, can then create an FSGD file with
two classes as before but no continuous variable. Then just have a
contrast that computes the diff between the patient and the mean
of the controls.

On 5/8/2020 11:49 AM, Xiaojiang Yang wrote:


External Email - Use Caution

Hi Douglas,

Could you please reply my last email (sent to
freesurfer@nmr.mgh.harvard.edu
) regarding my question
about the weighted age? I am eager to listen to your
answer/opinion to my question.  For your convenience, I also
include the whole email chain  below this email.

Thank you very much!

Sincerely,

Xiao

 Douglas N. Greve
 Thu, 07 May 2020 14:56:08 -0700
sorry, please include the previous email chain so that I know
what you are
referring to
On 5/7/2020 5:33 PM, Xiaojiang Yang wrote:
External Email - Use Caution
Douglas,
Just as I mentioned in the initial email, subjects in the healthy
group have
different ages. Because average cortical thickness is believed to be
declined as the age gets older, I want to "normalize" the group by
multiplying each subject's thickness with an age-dependent scalar
(pre-calculated constant). Suppose I take age 30 as the
"standard" age, then
subjects with ages greater than 30 will have scalars greater than
1 (depend
on age); subjects with ages smaller than 30 will have scalars
less than 1.
In this way, all subjects in the group looks like to be at the
same age
(30).
Of course, I also suspect that there is no need to do the above
mentioned
normalization if I use mri_glmfit. But my initial intention was using
non-linear scalars, and mri_glmft can only use linear fit. Please
give me
your opinion. Thank you!
Xiao
 Douglas N. Greve
 Thu, 07 May 2020 14:06:27 -0700
I don't know what weight is. Can you elaborate?
On 5/7/2020 4:54 PM, Xiaojiang Yang wrote:
External Email - Use Caution
Hi Douglas,
Thank you very much! Could you please help me with more detailed
information?
1)Should I use "Variables age" or "Variables age weight" in the
fsgd file?
If I can use either of them, which one is better?
I don't know what weight is. Can you elaborate?
2)For the contrast file, the content "1 -1  0" you mentioned, it
corresponds
to the "Variables age" fsgd file, correct?
Yes
3)If I use the "Variables age weight" fsgd file, what will be the
content of
the contrast file? Is it "1  -1  0  0"?
Yes
Thank you again!
Xiao
 Douglas N. Greve
 Thu, 07 May 2020 11:55:27 -0700
I think it will work properly if you use the raw data as input
and create an
FSGD file with two classes: (1) the individual subject and (2)
healthy
subjects. Also include age as a covariate. Use DOSS instead of
DODS. Then
set your contrast to be 1 -1 0 and run mri_glmfit. I think that
should
properly account for age.
On 5/7/2020 2:44 PM, Xiaojiang Yang wrote:
    External Email - Use Caution
Dear FS experts,
I have a group of healthy subjects. Given a new individual
subject, I want
to compare its cortical thickness to the h

Re: [Freesurfer] Compare individual to a group

[Xiaojiang Yang]

External Email - Use Caution

Thank you Douglas!
If I apply my transform to both the healthy controls and the patient, I
guess I would lose the convenience of using mri_glmfit, which eventually
loses the convenience of using mri-glmfit-sim (I don't care not
using mri_glmfit, but I want to use mri_glmfit-sim to do multiple
comparisons correction). That is because mri_glmfit uses the prepared
output from mris_preproc, which I have no control over to use the
transformed subject. The only way I can circumvent this is to use my
transformed thickness file to overwrite the FS calculated thickness file,
but that is what I am hesitant to do. If you have good suggestions
regarding this, please let me know. Thanks!
Xiao


On Mon, May 11, 2020 at 12:25 PM Douglas N. Greve 
wrote:

> I guess you could apply your transform to both the healthy controls and to
> your patient, can then create an FSGD file with two classes as before but
> no continuous variable. Then just have a contrast that computes the diff
> between the patient and the mean of the controls.
>
> On 5/8/2020 11:49 AM, Xiaojiang Yang wrote:
>
> External Email - Use Caution
>
> Hi Douglas,
>
>
>
> Could you please reply my last email (sent to
> freesurfer@nmr.mgh.harvard.edu) regarding my question about the weighted
> age? I am eager to listen to your answer/opinion to my question.  For your
> convenience, I also include the whole email chain  below this email.
>
>
>
> Thank you very much!
>
>
>
> Sincerely,
>
> Xiao
>
>
>
>
>
>  
> :%22Douglas+N.+Greve%22> Douglas N. Greve
>
> 
> :20200507> Thu, 07 May 2020 14:56:08 -0700
>
>
>
> sorry, please include the previous email chain so that I know what you are
>
> referring to
>
>
>
>
>
>
>
>
>
> On 5/7/2020 5:33 PM, Xiaojiang Yang wrote:
>
>  External Email - Use Caution
>
>  Douglas,
>
>
>
> Just as I mentioned in the initial email, subjects in the healthy group have
>
> different ages. Because average cortical thickness is believed to be
>
> declined as the age gets older, I want to "normalize" the group by
>
> multiplying each subject's thickness with an age-dependent scalar
>
> (pre-calculated constant). Suppose I take age 30 as the "standard" age, then
>
> subjects with ages greater than 30 will have scalars greater than 1 (depend
>
> on age); subjects with ages smaller than 30 will have scalars less than 1.
>
> In this way, all subjects in the group looks like to be at the same age
>
> (30).
>
>
>
>
>
> Of course, I also suspect that there is no need to do the above mentioned
>
> normalization if I use mri_glmfit. But my initial intention was using
>
> non-linear scalars, and mri_glmft can only use linear fit. Please give me
>
> your opinion. Thank you!
>
>
>
>  Xiao
>
>
>
>
>
>  
> :%22Douglas+N.+Greve%22> Douglas N. Greve
>
> 
> :20200507> Thu, 07 May 2020 14:06:27 -0700
>
>
>
> I don't know what weight is. Can you elaborate?
>
>  On 5/7/2020 4:54 PM, Xiaojiang Yang wrote:
>
>  External Email - Use Caution
>
>  Hi Douglas,
>
>
>
> Thank you very much! Could you please help me with more detailed
>
> information?
>
>
>
>
>
> 1)Should I use "Variables age" or "Variables age weight" in the fsgd file?
>
> If I can use either of them, which one is better?
>
>
>
>  I don't know what weight is. Can you elaborate?
>
>
>
> 2)For the contrast file, the content "1 -1  0" you mentioned, it corresponds
>
> to the "Variables age" fsgd file, correct?
>
>
>
>  Yes
>
>
>
> 3)If I use the "Variables age weight" fsgd file, what will be the content of
>
> the contrast file? Is it "1  -1  0  0"?
>
>
>
>  Yes
>
>  Thank you again!
>
>  Xiao
>
>
>
>
>
>
>
>  
> :%22Douglas+N.+Greve%22> Douglas N. Greve
>
> 
> :20200507> Thu, 07 May 2020 11:55:27 -0700
>
>
>
> I think it will work properly if you use the raw data as input and create an
>
> FSGD file with two classes: (1) the individual subject and (2) healthy
>
> subjects. Also include age as a covariate. Use DOSS instead of DODS. Then
>
> set your contrast to be 1 -1 0 and run mri_glmfit. I think that should
>
> properly account for age.
>
>
>
>
>
>
>
>
>
>
>
> On 5/7/2020 2:44 PM, Xiaojiang Yang wrote:
>
>
>
>
>
> External Email - Use Caution
>
>
>
>
>
> Dear FS experts,
>
>
>
>
>
> I have a group of healthy subjects. Given a new individual subject, I want
>
> to compare its cortical thickness to the healthy group so that I can find
>
> where the thickness is abnormal (thickening or thinning).
>
>
>
>
>
> I use fsaverage as the template subject to calculate mean and std 

Re: [Freesurfer] Compare individual to a group

[Douglas N. Greve]

I guess you could apply your transform to both the healthy controls and 
to your patient, can then create an FSGD file with two classes as before 
but no continuous variable. Then just have a contrast that computes the 
diff between the patient and the mean of the controls.


On 5/8/2020 11:49 AM, Xiaojiang Yang wrote:


External Email - Use Caution

Hi Douglas,

Could you please reply my last email (sent to 
freesurfer@nmr.mgh.harvard.edu 
) regarding my question about 
the weighted age? I am eager to listen to your answer/opinion to my 
question.  For your convenience, I also include the whole email chain  
below this email.


Thank you very much!

Sincerely,

Xiao

 Douglas N. Greve
 Thu, 07 May 2020 14:56:08 -0700
sorry, please include the previous email chain so that I know what you are
referring to
On 5/7/2020 5:33 PM, Xiaojiang Yang wrote:
External Email - Use Caution
Douglas,
Just as I mentioned in the initial email, subjects in the healthy 
group have

different ages. Because average cortical thickness is believed to be
declined as the age gets older, I want to "normalize" the group by
multiplying each subject's thickness with an age-dependent scalar
(pre-calculated constant). Suppose I take age 30 as the "standard" 
age, then
subjects with ages greater than 30 will have scalars greater than 1 
(depend

on age); subjects with ages smaller than 30 will have scalars less than 1.
In this way, all subjects in the group looks like to be at the same age
(30).
Of course, I also suspect that there is no need to do the above mentioned
normalization if I use mri_glmfit. But my initial intention was using
non-linear scalars, and mri_glmft can only use linear fit. Please give me
your opinion. Thank you!
Xiao
 Douglas N. Greve
 Thu, 07 May 2020 14:06:27 -0700
I don't know what weight is. Can you elaborate?
On 5/7/2020 4:54 PM, Xiaojiang Yang wrote:
External Email - Use Caution
Hi Douglas,
Thank you very much! Could you please help me with more detailed
information?
1)Should I use "Variables age" or "Variables age weight" in the fsgd file?
If I can use either of them, which one is better?
I don't know what weight is. Can you elaborate?
2)For the contrast file, the content "1 -1  0" you mentioned, it 
corresponds

to the "Variables age" fsgd file, correct?
Yes
3)If I use the "Variables age weight" fsgd file, what will be the 
content of

the contrast file? Is it "1  -1  0  0"?
Yes
Thank you again!
Xiao
 Douglas N. Greve
 Thu, 07 May 2020 11:55:27 -0700
I think it will work properly if you use the raw data as input and 
create an

FSGD file with two classes: (1) the individual subject and (2) healthy
subjects. Also include age as a covariate. Use DOSS instead of DODS. Then
set your contrast to be 1 -1 0 and run mri_glmfit. I think that should
properly account for age.
On 5/7/2020 2:44 PM, Xiaojiang Yang wrote:
    External Email - Use Caution
Dear FS experts,
I have a group of healthy subjects. Given a new individual subject, I want
to compare its cortical thickness to the healthy group so that I can find
where the thickness is abnormal (thickening or thinning).
I use fsaverage as the template subject to calculate mean and std of the
healthy group. Since subjects in the healthy group have different 
ages, I do

a "normalization" process to all the subjects in the group BEFORE
calculating the mean and std. Thus the normalized healthy group can be
regarded as all subjects having the same "standard" age. The normalization
process is just multiplying some pre-obtained scale (varied by age, 
but not

linearly ) to the file *?h.thickness.fwhm0.fsaverage.mgh* of each subject
that are already calculated by "recon-all --qcache" command. So the 
mean and

std of the group are actually weighted in the sense of Freesurfer's
recon-all results.
My questions are:
1)If I do vertex-wise t-tests by simply comparing individual subject's
thickness to the group using mris_calc but WITHOUT using mri_glmfit, can I
still use mri_glmfit-sim to do multiple comparisons correction? If 
yes, how?
2)If the answer is no for the above question, how should I use 
mris_glmft to

implement my above thoughts so that I can use use mri_glmfit-sim?
Specifically, how can I use the weighted mean for the group?
3)Take a step back, if I consider the weight is linearly correlated 
with the

age, how to design the fsdg and contrast file?

Re: [Freesurfer] Compare individual to a group

[Xiaojiang Yang]

External Email - Use Caution

Hi Douglas,

 

Sorry I didn't find an easy way to include previous email chain. Now I just
copied all of them below, so that it's easy to follow.

 

Thanks,

Xiao

 

 

 

 
 Douglas N. Greve
 Thu, 07 May 2020 14:56:08 -0700

sorry, please include the previous email chain so that I know what you are
referring to

 
 
 
 
On 5/7/2020 5:33 PM, Xiaojiang Yang wrote:
 
External Email - Use Caution
 
Douglas,
 

Just as I mentioned in the initial email, subjects in the healthy group have
different ages. Because average cortical thickness is believed to be
declined as the age gets older, I want to "normalize" the group by
multiplying each subject's thickness with an age-dependent scalar
(pre-calculated constant). Suppose I take age 30 as the "standard" age, then
subjects with ages greater than 30 will have scalars greater than 1 (depend
on age); subjects with ages smaller than 30 will have scalars less than 1.
In this way, all subjects in the group looks like to be at the same age
(30).

 

Of course, I also suspect that there is no need to do the above mentioned
normalization if I use mri_glmfit. But my initial intention was using
non-linear scalars, and mri_glmft can only use linear fit. Please give me
your opinion. Thank you!

 
Xiao
 
 

 
 Douglas N. Greve
 Thu, 07 May 2020 14:06:27 -0700

I don't know what weight is. Can you elaborate?
 
On 5/7/2020 4:54 PM, Xiaojiang Yang wrote:
 
External Email - Use Caution
 
Hi Douglas,
 

Thank you very much! Could you please help me with more detailed
information?

 

1)Should I use "Variables age" or "Variables age weight" in the fsgd file?
If I can use either of them, which one is better?

 
I don't know what weight is. Can you elaborate?
 

2)For the contrast file, the content "1 -1  0" you mentioned, it corresponds
to the "Variables age" fsgd file, correct?

 
Yes
 

3)If I use the "Variables age weight" fsgd file, what will be the content of
the contrast file? Is it "1  -1  0  0"?

 
Yes
 
Thank you again!
 
Xiao
 
 
 

 
 Douglas N. Greve
 Thu, 07 May 2020 11:55:27 -0700

I think it will work properly if you use the raw data as input and create an
FSGD file with two classes: (1) the individual subject and (2) healthy
subjects. Also include age as a covariate. Use DOSS instead of DODS. Then
set your contrast to be 1 -1 0 and run mri_glmfit. I think that should
properly account for age.

 

 

 

 

On 5/7/2020 2:44 PM, Xiaojiang Yang wrote:

 

External Email - Use Caution

 

Dear FS experts,

 

I have a group of healthy subjects. Given a new individual subject, I want
to compare its cortical thickness to the healthy group so that I can find
where the thickness is abnormal (thickening or thinning).

 

I use fsaverage as the template subject to calculate mean and std of the
healthy group. Since subjects in the healthy group have different ages, I do
a "normalization" process to all the subjects in the group BEFORE
calculating the mean and std. Thus the normalized healthy group can be
regarded as all subjects having the same "standard" age. The normalization
process is just multiplying some pre-obtained scale (varied by age, but not
linearly ) to the file *?h.thickness.fwhm0.fsaverage.mgh* of each subject
that are already calculated by "recon-all --qcache" command. So the mean and
std of the group are actually weighted in the sense of Freesurfer's
recon-all results.

 

My questions are:

 

1)If I do vertex-wise t-tests by simply comparing individual subject's
thickness to the group using mris_calc but WITHOUT using mri_glmfit, can I
still use mri_glmfit-sim to do multiple comparisons correction? If yes, how?

 

2)If the answer is no for the above question, how should I use mris_glmft to
implement my above thoughts so that I can use use mri_glmfit-sim?
Specifically, how can I use the weighted mean for the group?

 

3)Take a step back, if I consider the weight is linearly correlated with the
age, how to design the fsdg and contrast file?

 

Thank you very much!

 

Xiao

 

___
Freesurfer mailing list
Freesurfer@nmr.mgh.harvard.edu
https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer

Re: [Freesurfer] Compare individual to a group

[Douglas N. Greve]

sorry, please include the previous email chain so that I know what you 
are referring to


On 5/7/2020 5:33 PM, Xiaojiang Yang wrote:


External Email - Use Caution

Douglas,

Just as I mentioned in the initial email, subjects in the healthy 
group have different ages. Because average cortical thickness is 
believed to be declined as the age gets older, I want to “normalize” 
the group by multiplying each subject’s thickness with an 
age-dependent scalar (pre-calculated constant). Suppose I take age 30 
as the “standard” age, then subjects with ages greater than 30 will 
have scalars greater than 1 (depend on age); subjects with ages 
smaller than 30 will have scalars less than 1. In this way, all 
subjects in the group looks like to be at the same age (30).


Of course, I also suspect that there is no need to do the above 
mentioned normalization if I use mri_glmfit. But my initial intention 
was using non-linear scalars, and mri_glmft can only use linear fit. 
Please give me your opinion. Thank you!


Xiao


___
Freesurfer mailing list
Freesurfer@nmr.mgh.harvard.edu
https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer


___
Freesurfer mailing list
Freesurfer@nmr.mgh.harvard.edu
https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer

Re: [Freesurfer] Compare individual to a group

[Xiaojiang Yang]

External Email - Use Caution

Douglas,

Just as I mentioned in the initial email, subjects in the healthy group have
different ages. Because average cortical thickness is believed to be
declined as the age gets older, I want to "normalize" the group by
multiplying each subject's thickness with an age-dependent scalar
(pre-calculated constant). Suppose I take age 30 as the "standard" age, then
subjects with ages greater than 30 will have scalars greater than 1 (depend
on age); subjects with ages smaller than 30 will have scalars less than 1.
In this way, all subjects in the group looks like to be at the same age
(30).

Of course, I also suspect that there is no need to do the above mentioned
normalization if I use mri_glmfit. But my initial intention was using
non-linear scalars, and mri_glmft can only use linear fit. Please give me
your opinion. Thank you!

Xiao

 

 

___
Freesurfer mailing list
Freesurfer@nmr.mgh.harvard.edu
https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer

Re: [Freesurfer] Compare individual to a group

[Douglas N. Greve]

I don't know what weight is. Can you elaborate?

On 5/7/2020 4:54 PM, Xiaojiang Yang wrote:


External Email - Use Caution

Hi Douglas,

Thank you very much! Could you please help me with more detailed 
information?


1)Should I use “Variables age” or “Variables age weight” in the fsgd 
file?  If I can use either of them, which one is better?



I don't know what weight is. Can you elaborate?


2)For the contrast file, the content “1 -1  0” you mentioned, it 
corresponds to the “Variables age” fsgd file, correct?



Yes


3)If I use the “Variables age weight” fsgd file, what will be the 
content of the contrast file? Is it “1  -1  0  0”?



Yes


Thank you again!

Xiao


___
Freesurfer mailing list
Freesurfer@nmr.mgh.harvard.edu
https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer


___
Freesurfer mailing list
Freesurfer@nmr.mgh.harvard.edu
https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer

Re: [Freesurfer] Compare individual to a group

[Xiaojiang Yang]

External Email - Use Caution

Hi Douglas,

 

Thank you very much! Could you please help me with more detailed
information?

1)  Should I use "Variables age" or "Variables age weight" in the fsgd
file?  If I can use either of them, which one is better?

2)  For the contrast file, the content "1 -1  0" you mentioned, it
corresponds to the "Variables age" fsgd file, correct?

3)  If I use the "Variables age weight" fsgd file, what will be the
content of the contrast file? Is it "1  -1  0  0"?

 

Thank you again!

Xiao

 

___
Freesurfer mailing list
Freesurfer@nmr.mgh.harvard.edu
https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer

Re: [Freesurfer] Compare individual to a group

[Douglas N. Greve]

I think it will work properly if you use the raw data as input and 
create an FSGD file with two classes: (1) the individual subject and (2) 
healthy subjects. Also include age as a covariate. Use DOSS instead of 
DODS. Then set your contrast to be 1 -1 0 and run mri_glmfit. I think 
that should properly account for age.


On 5/7/2020 2:44 PM, Xiaojiang Yang wrote:


External Email - Use Caution

Dear FS experts,

I have a group of healthy subjects. Given a new individual subject, I 
want to compare its cortical thickness to the healthy group so that I 
can find where the thickness is abnormal (thickening or thinning).


I use fsaverage as the template subject to calculate mean and std of 
the healthy group. Since subjects in the healthy group have different 
ages, I do a “normalization” process to all the subjects in the group 
BEFORE calculating the mean and std. Thus the normalized healthy group 
can be regarded as all subjects having the same “standard” age. The 
normalization process is just multiplying some pre-obtained scale 
(varied by age, but not linearly ) to the file 
*?h.thickness.fwhm0.fsaverage.mgh* of each subject that are already 
calculated by “recon-all --qcache” command. So the mean and std of the 
group are actually weighted in the sense of Freesurfer’s recon-all 
results.


My questions are:

1)If I do vertex-wise t-tests by simply comparing individual subject’s 
thickness to the group using mris_calc but WITHOUT using mri_glmfit, 
can I still use mri_glmfit-sim to do multiple comparisons correction? 
If yes, how?


2)If the answer is no for the above question, how should I use 
mris_glmft to implement my above thoughts so that I can use use 
mri_glmfit-sim? Specifically, how can I use the weighted mean for the 
group?


3)Take a step back, if I consider the weight is linearly correlated 
with the age, how to design the fsdg and contrast file?


Thank you very much!

Xiao


___
Freesurfer mailing list
Freesurfer@nmr.mgh.harvard.edu
https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer


___
Freesurfer mailing list
Freesurfer@nmr.mgh.harvard.edu
https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer

[Freesurfer] Compare individual to a group

[Xiaojiang Yang]

External Email - Use Caution

Dear FS experts,

I have a group of healthy subjects. Given a new individual subject, I want
to compare its cortical thickness to the healthy group so that I can find
where the thickness is abnormal (thickening or thinning). 

I use fsaverage as the template subject to calculate mean and std of the
healthy group. Since subjects in the healthy group have different ages, I do
a "normalization" process to all the subjects in the group BEFORE
calculating the mean and std. Thus the normalized healthy group can be
regarded as all subjects having the same "standard" age. The normalization
process is just multiplying some pre-obtained scale (varied by age, but not
linearly ) to the file ?h.thickness.fwhm0.fsaverage.mgh of each subject that
are already calculated by "recon-all --qcache" command. So the mean and std
of the group are actually weighted in the sense of Freesurfer's recon-all
results.

My questions are: 

1)  If I do vertex-wise t-tests by simply comparing individual subject's
thickness to the group using mris_calc but WITHOUT using mri_glmfit, can I
still use mri_glmfit-sim to do multiple comparisons correction? If yes, how?

2)  If the answer is no for the above question, how should I use
mris_glmft to implement my above thoughts so that I can use use
mri_glmfit-sim? Specifically, how can I use the weighted mean for the group?

3)  Take a step back, if I consider the weight is linearly correlated
with the age, how to design the fsdg and contrast file?

Thank you very much!

Xiao

 

 

 

 

 

 

 

___
Freesurfer mailing list
Freesurfer@nmr.mgh.harvard.edu
https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer