On Tue, Aug 13, 2019 at 10:39 AM Greve, Douglas N.,Ph.D. <DGREVE@mgh.harvard.edu> wrote:

I don't know that there is much you can do. The PVR is very
computationally intensive, and it does not surprise me that it is taking
a long time. I don't think you need to do 10k permutations. I would
start with 1k. In the output, you will get a confidence interval for the
corrected p-value. This will shrink with the number of permutations, but
if you're happy with it, no need to do more

On 8/13/19 10:17 AM, miracle ozzoude wrote:
>
>         External Email - Use Caution
>
> Thanks Doug. My correction for multiple comparison using 10000
> permutation and abs has been running for 3days. This is strange
> because i am using the --bg 10 and it usually takes 1hr to finish
> without the --pvr. how do i solve this?
> Below is my mri_glmfit and mri_glmfit-sim commands
>
> mri_glmfit --y ${lhpetsurfimg} --fsgd $bothgrpfsgd dods --C $pvr1
> --pvr ${wholebrain}/lh.$grp1fsgd.pvr.thickness.mgh \
> --pvr ${wholebrain}/lh.$grp2fsgd.pvr.thickness.mgh --surf fsaverage lh
> --cortex \
> --glmdir ${wholebrain}/lh.pet.thickness.glmdir --eres-save
>
> mri_glmfit-sim --glmdir ${wholebrain}/lh.pet.thickness.glmdir --perm
> 10000 2 abs --perm-force --cwp 0.05 --2spaces --bg 10 --overwrite
>
>
> On Mon, Aug 12, 2019 at 11:31 AM Greve, Douglas N.,Ph.D.
> <DGREVE@mgh.harvard.edu <mailto:DGREVE@mgh.harvard.edu>> wrote:
>
> You will have to click on the vertex you are interested in. The
> value will be -log10(pcorrected) where pcorrected is the corrected
> p-value
>
> On 8/12/2019 11:24 AM, miracle ozzoude wrote:
>>
>>          External Email - Use Caution
>>
>> these regions (please see below) came out significant for the
>> voxel-wise corrected map. I want to know their p-values.
>> mri-glmfit-sim doesn't give summary file for voxel-wise corrected
>> map only for cluster-wise map.
>> image.png
>>
>> On Mon, Aug 12, 2019 at 11:19 AM Greve, Douglas N.,Ph.D.
>> <DGREVE@mgh.harvard.edu <mailto:DGREVE@mgh.harvard.edu>> wrote:
>>
>> I'm not sure what you are looking for. The voxel-wise
>> analysis is voxel-wise, so there is no summary file for it
>>
>> On 8/12/2019 11:13 AM, miracle ozzoude wrote:
>>>
>>>          External Email - Use Caution
>>>
>>> Thanks Doug. Another question, how do i find the p-values
>>> for voxel-wise map corrected for multiple comparisons at a
>>> voxel (rather than cluster) level
>>> (perm.th40.abs.sig.voxel.mgh). There is no summary file for it.
>>> Best,
>>> Paul
>>>
>>> On Wed, Aug 7, 2019 at 11:08 AM Greve, Douglas N.,Ph.D.
>>> <DGREVE@mgh.harvard.edu <mailto:DGREVE@mgh.harvard.edu>> wrote:
>>>
>>> The 3 spaces is for left hemi, right hemi, and
>>> subcortical, so, if you
>>> are using all three then correct for all 3
>>>
>>> On 8/7/19 9:26 AM, miracle ozzoude wrote:
>>> >
>>> >         External Email - Use Caution
>>> >
>>> > Got it. Thanks a lot doug. If i have to correct for
>>> multiple
>>> > comparison in surface based pet analysis and
>>> mutlimodal analysis (pet
>>> > and thickness), should i use --3spaces?
>>> > Thank you.
>>> >
>>> > best,
>>> > Paul
>>> >
>>> > On Mon, Aug 5, 2019 at 10:19 PM Greve, Douglas N.,Ph.D.
>>> > <DGREVE@mgh.harvard.edu
>>> <mailto:DGREVE@mgh.harvard.edu>
>>> <mailto:DGREVE@mgh.harvard.edu
>>> <mailto:DGREVE@mgh.harvard.edu>>> wrote:
>>> >
>>> > I think there is still something not right. You
>>> should just have
>>> > one mri_glmfit command for each hemisphere in
>>> which the input is
>>> > ?h.thickness.15.mgh, the fsgdfile is project.fsgd,
>>> you then
>>> > specify the pvrs for both groups (--pvr
>>> ?h.pvr_grp1_pet.nii.gz
>>> > --pvr ?h.pvr_grp2_pet.niigz) and then use that
>>> first contrast. The
>>> > second is the same as the first but with a
>>> reversed sign, but it
>>> > is not necessary since we always use unsigned
>>> tests and show both
>>> > signs (but you can still do it).
>>> >
>>> > On 8/5/2019 8:14 PM, miracle ozzoude wrote:
>>> >>
>>> >>          External Email - Use Caution
>>> >>
>>> >> I think i got it now. Something like this:
>>> >>
>>> >> ## group1 comes first in my fsgd file. removing
>>> the effects of
>>> >> age and education
>>> >> ##amyloid-thickness. first pet pvr = 1 for group1
>>> and 0 for group 2.
>>> >> mri_glmfit --y lh.thickness.15.mgh --fsgd
>>> project.fsgd dods --c
>>> >> pvr1.mtx --pvr lh.pvr_grp1_pet.nii.gz \
>>> >> --pvr
>>> allgrp2.lhmgxctx.fsaverage.sm05.zero.nii.gz  -surf
>>> >> fsaverage lh --cortex --glmdir
>>> lh.pet.thickness.glmdir
>>> >> mri_glmfit --y rh.thickness.15.mgh --fsgd
>>> project.fsgd dods --c
>>> >> pvr1.mtx --pvr rh.pvr_grp1_pet.nii.gz \
>>> >> --pvr
>>> allgrp2.rhmgxctx.fsaverage.sm05.zero.nii.gz -surf fsaverage
>>> >> lh --cortex --glmdir rh.pet.thickness.glmdir
>>> >>
>>> >> contrast = 0 0 0 0 0 0 1 -1
>>> >>
>>> >> ##group 2 is second in my fsgd file. removing the
>>> effects of age
>>> >> and education
>>> >> ##amyloid-thickness. first pet pvr = 0 for group1
>>> and 1 for group2
>>> >>   mri_glmfit --y lh.thickness.15.mgh --fsgd
>>> project.fsgd dods --c
>>> >> pvr2.mtx --pvr
>>> allgrp1.lhmgxctx.fsaverage.sm05.zero.nii.gz \
>>> >> --pvr lh.pvr_grp2_pet.nii.gz -surf fsaverage lh
>>> --cortex --glmdir
>>> >> rh.pet.thickness.glmdir
>>> >> mri_glmfit --y rh.thickness.15.mgh --fsgd
>>> project.fsgd dods --c
>>> >> pvr2.mtx --pvr
>>> allgrp1.rhmgxctx.fsaverage.sm05.zero.nii.gz \
>>> >> --pvr rh.pvr_grp2_pet.nii.gz -surf fsaverage lh
>>> --cortex --glmdir
>>> >> rh.pet.thickness.glmdir
>>> >>
>>> >> contrast = 0 0 0 0 0 0 -1 1
>>> >>
>>> >> On Mon, Aug 5, 2019 at 6:47 PM Greve, Douglas
>>> N.,Ph.D.
>>> >> <DGREVE@mgh.harvard.edu
>>> <mailto:DGREVE@mgh.harvard.edu>
>>> <mailto:DGREVE@mgh.harvard.edu
>>> <mailto:DGREVE@mgh.harvard.edu>>> wrote:
>>> >>
>>> >> It still looks like you are using a group
>>> specific input
>>> >> (--y). The input should be a simple file with
>>> both groups
>>> >> (same input as you would use without pvr)
>>> >>
>>> >> On 8/5/2019 4:39 PM, miracooloz wrote:
>>> >>>
>>> >>>          External Email - Use Caution
>>> >>>
>>> >>> Thanks Doug. How about the mri_glmfit
>>> commands? Since the
>>> >>> contrasts are correct, I think the commands
>>> should be right.
>>> >>>
>>> >>> Best,
>>> >>> Paul.
>>> >>>
>>> >>>
>>> >>>
>>> >>> Sent from my Samsung Galaxy smartphone.
>>> >>>
>>> >>> -------- Original message --------
>>> >>> From: "Greve, Douglas N.,Ph.D."
>>> <DGREVE@mgh.harvard.edu <mailto:DGREVE@mgh.harvard.edu>>
>>> >>> <mailto:DGREVE@mgh.harvard.edu
>>> <mailto:DGREVE@mgh.harvard.edu>>
>>> >>> Date: 2019-08-05 15:52 (GMT-05:00)
>>> >>> To: freesurfer@nmr.mgh.harvard.edu
>>> <mailto:freesurfer@nmr.mgh.harvard.edu>
>>> >>> <mailto:freesurfer@nmr.mgh.harvard.edu
>>> <mailto:freesurfer@nmr.mgh.harvard.edu>>
>>> >>> Subject: Re: [Freesurfer] Fwd: multimodal
>>> analysis (pet and
>>> >>> cortical thickness relationship) using --pvr
>>> >>>
>>> >>> Yes, that contrast is correct.
>>> >>>
>>> >>> On 8/5/2019 3:11 PM, miracle ozzoude wrote:
>>> >>>>
>>> >>>>          External Email - Use Caution
>>> >>>>
>>> >>>> Hello Doug,
>>> >>>>
>>> >>>> Thanks very much for your help. Your
>>> assumption was right
>>> >>>> in that i want to run a group comparison
>>> (i.e. test for a
>>> >>>> difference in amyloid-thickness slopes
>>> between the two
>>> >>>> groups). However, I am having a hard time
>>> creating the
>>> >>>> correct mri_glmfit and contrasts in this
>>> case. Based on
>>> >>>> your advice and searching through the forum
>>> >>>>
>>>   (https://mail.nmr.mgh.harvard.edu/pipermail/freesurfer/2019-January/060029.html), i
>>> >>>> need 2 PVRs for each hemisphere in the
>>> mri_glmfit command.
>>> >>>> I gave it another shot below. Please let me
>>> know if i am
>>> >>>> correct.
>>> >>>>
>>> >>>> Thank you.
>>> >>>> Paul.
>>> >>>>
>>> >>>> ## group1 comes first in my fsgd file.
>>> removing the effects
>>> >>>> of age and education
>>> >>>> ##amyloid-thickness. first pet pvr = 1 for
>>> group1 and 0 for
>>> >>>> group 2.
>>> >>>> mri_glmfit --y lh_pvr_grp1_thickness.mgh --fsgd
>>> >>>> project.fsgd dods --c pvr1.mtx --pvr
>>> lh.pvr_grp1_pet.nii.gz \
>>> >>>> --pvr
>>> allgrp2.lhmgxctx.fsaverage.sm05.zero.nii.gz  -surf
>>> >>>> fsaverage lh --cortex --glmdir
>>> lh.pet.thickness.glmdir
>>> >>>> mri_glmfit --y rh_pvr_grp1_thickness.mgh --fsgd
>>> >>>> project.fsgd dods --c pvr1.mtx --pvr
>>> rh.pvr_grp1_pet.nii.gz \
>>> >>>> --pvr
>>> allgrp2.rhmgxctx.fsaverage.sm05.zero.nii.gz -surf
>>> >>>> fsaverage lh --cortex --glmdir
>>> rh.pet.thickness.glmdir
>>> >>>>
>>> >>>> contrast = 0 0 0 0 0 0 1 -1
>>> >>>>
>>> >>>> ##group 2 is second in my fsgd file.
>>> removing the effects
>>> >>>> of age and education
>>> >>>> ##amyloid-thickness. first pet pvr = 0 for
>>> group1 and 1 for
>>> >>>> group2
>>> >>>>   mri_glmfit --y
>>> lh_pvr_grp2_thickness.mgh --fsgd
>>> >>>> project.fsgd dods --c pvr2.mtx --pvr
>>> >>>> allgrp1.lhmgxctx.fsaverage.sm05.zero.nii.gz \
>>> >>>> --pvr lh.pvr_grp2_pet.nii.gz -surf
>>> fsaverage lh --cortex
>>> >>>> --glmdir rh.pet.thickness.glmdir
>>> >>>> mri_glmfit --y rh_pvr_grp2_thickness.mgh --fsgd
>>> >>>> project.fsgd dods --c pvr2.mtx --pvr
>>> >>>> allgrp1.rhmgxctx.fsaverage.sm05.zero.nii.gz \
>>> >>>> --pvr rh.pvr_grp2_pet.nii.gz -surf
>>> fsaverage lh --cortex
>>> >>>> --glmdir rh.pet.thickness.glmdir
>>> >>>>
>>> >>>> contrast = 0 0 0 0 0 0 -1 1
>>> >>>>
>>> >>>>
>>> >>>> On Mon, Aug 5, 2019 at 12:26 PM Greve,
>>> Douglas N.,Ph.D.
>>> >>>> <DGREVE@mgh.harvard.edu
>>> <mailto:DGREVE@mgh.harvard.edu>
>>> <mailto:DGREVE@mgh.harvard.edu
>>> <mailto:DGREVE@mgh.harvard.edu>>> wrote:
>>> >>>>
>>> >>>> That mostly looks good.
>>> >>>>
>>> >>>> I would suggest is to change your
>>> smoothing command to
>>> >>>> something like
>>> >>>> mris_fwhm --smooth-only --s fsaverage
>>> --hemi lh --fwhm
>>> >>>> 5 --cortex --prune --i
>>> >>>> allgrp1.rlhmgxctx.fsaverage.sm00.nii.gz
>>> >>>> allgrp1.lhmgxctx.fsaverage.sm05.nii.gz
>>> >>>> The only difference will be that any
>>> vertices that are
>>> >>>> 0 in the input will be excluded
>>> (pruned) from the
>>> >>>> smoothing mask.
>>> >>>>
>>> >>>> The mri_glmfit command is not right.
>>> That command looks
>>> >>>> like it is for analyzing each group
>>> separately and
>>> >>>> independently. If that is what you want
>>> to do, then you
>>> >>>> don't need to go through all the extra
>>> stuff of
>>> >>>> creating zero files, etc. I had assumed
>>> that you wanted
>>> >>>> to do some kind of comparison between
>>> groups. If so,
>>> >>>> then you would use a single file with
>>> all your data in
>>> >>>> it (probably what you were using
>>> before), and your fsgd
>>> >>>> file would have both groups.
>>> >>>>
>>> >>>> 1) will my fsgd file contain both groups?
>>> >>>> yes, see above
>>> >>>> 2) If the answer from question is yes,
>>> i should have 2
>>> >>>> contrasts (pvr1.mtx for group1 and
>>> pvr2.mtx for
>>> >>>> group2). yes/no?
>>> >>>> Again, if all you want to do is to test
>>> the pvr for
>>> >>>> each group separately, then you don't
>>> need to go
>>> >>>> through the processes of creating zero
>>> files, etc. In
>>> >>>> any event, if you want to test a pvr,
>>> then you need a
>>> >>>> contrast for it.
>>> >>>> 3) below is a sample of my fsgd file.
>>> are the
>>> >>>> constrasts correct?
>>> >>>> hard to say without resolving the
>>> questions above. You
>>> >>>> will need to have a value in the
>>> contrast for each pvr.
>>> >>>>
>>> >>>>
>>> >>>>
>>> >>>> On 8/2/2019 3:56 PM, miracle ozzoude wrote:
>>> >>>>>
>>> >>>>>          External Email - Use Caution
>>> >>>>>
>>> >>>>> Hello Doug,
>>> >>>>>
>>> >>>>> Thanks for answering. Based on your
>>> explanation, i
>>> >>>>> wrote out a series of command needed
>>> to execute this.
>>> >>>>> Please let me know if i made any
>>> mistakes/correct.
>>> >>>>> ##step1 concatenating the 10 amyloid
>>> pet volumes files
>>> >>>>> projected to surface using
>>> mri_vol2surf for group1
>>> >>>>> mri_concat --f grp1.lhmgxctx --o
>>> >>>>> allgrp1.lhmgxctx.fsaverage.sm00.nii.gz --prune
>>> >>>>> mri_concat --f grp2.rhmgxctx --o
>>> >>>>> allgrp1.rhmgxctx.fsaverage.sm00.nii.gz --prune
>>> >>>>>
>>> >>>>> ##step2 concatenating the 20 amyloid
>>> pet volumes files
>>> >>>>> projected to surface using
>>> mri_vol2surf for group2
>>> >>>>> mri_concat --f grp2.lhmgxctx --o
>>> >>>>> allgrp2.lhmgxctx.fsaverage.sm00.nii.gz --prune
>>> >>>>> mri_concat --f grp2.rhmgxctx --o
>>> >>>>> allgrp2.rhmgxctx.fsaverage.sm00.nii.gz --prune
>>> >>>>>
>>> >>>>> ##step3 smooth on the surface for each
>>> hemisphere for
>>> >>>>> group1
>>> >>>>> mri_surf2surf --hemi lh --s fsaverage
>>> --sval
>>> >>>>> allgrp1.lhmgxctx.fsaverage.sm00.nii.gz --fwhm 5
>>> >>>>> --cortex --tval
>>> allgrp1.lhmgxctx.fsaverage.sm05.nii.gz
>>> >>>>> mri_surf2surf --hemi rh --s fsaverage
>>> --sval
>>> >>>>> allgrp1.rlhmgxctx.fsaverage.sm00.nii.gz --fwhm 5
>>> >>>>> --cortex --tval
>>> allgrp1.rhmgxctx.fsaverage.sm05.nii.gz
>>> >>>>>
>>> >>>>> ##step4 smooth on the surface for each
>>> hemisphere for
>>> >>>>> group2
>>> >>>>> mri_surf2surf --hemi lh --s fsaverage
>>> --sval
>>> >>>>> allgrp2.lhmgxctx.fsaverage.sm00.nii.gz --fwhm 5
>>> >>>>> --cortex --tval
>>> allgrp2.lhmgxctx.fsaverage.sm05.nii.gz
>>> >>>>> mri_surf2surf --hemi rh --s fsaverage
>>> --sval
>>> >>>>> allgrp2.rlhmgxctx.fsaverage.sm00.nii.gz --fwhm 5
>>> >>>>> --cortex --tval
>>> allgrp2.rhmgxctx.fsaverage.sm05.nii.gz
>>> >>>>>
>>> >>>>> ##step5 create files of zeros for
>>> group1 for each
>>> >>>>> hemisphere
>>> >>>>> fscalc
>>> allgrp1.lhmgxctx.fsaverage.sm05.nii.gz mul 0 -o
>>> >>>>> allgrp1.lhmgxctx.fsaverage.sm05.zero.nii.gz
>>> >>>>> fscalc
>>> allgrp1.rhmgxctx.fsaverage.sm05.nii.gz mul 0 -o
>>> >>>>> allgrp1.rhmgxctx.fsaverage.sm05.zero.nii.gz
>>> >>>>>
>>> >>>>>   ##step6 create files of zeros for
>>> group2 for each
>>> >>>>> hemisphere
>>> >>>>> fscalc
>>> allgrp2.lhmgxctx.fsaverage.sm05.nii.gz mul 0 -o
>>> >>>>> allgrp2.lhmgxctx.fsaverage.sm05.zero.nii.gz
>>> >>>>> fscalc
>>> allgrp2.rhmgxctx.fsaverage.sm05.nii.gz mul 0 -o
>>> >>>>> allgrp2.rhmgxctx.fsaverage.sm05.zero.nii.gz
>>> >>>>>
>>> >>>>> ##step7 create pvr files for group1
>>> for each hemisphere
>>> >>>>> mri_concat
>>> allgrp1.lhmgxctx.fsaverage.sm05.nii.gz
>>> >>>>> allgrp2.lhmgxctx.fsaverage.sm05.zero.nii.gz --o
>>> >>>>> lh.pvr_grp1_pet.nii.gz
>>> >>>>> mri_concat
>>> allgrp1.rhmgxctx.fsaverage.sm05.nii.gz
>>> >>>>> allgrp2.rhmgxctx.fsaverage.sm05.zero.nii.gz --o
>>> >>>>> rh.pvr_grp1_pet.nii.gz
>>> >>>>>
>>> >>>>> ##step8 create pvr files for group2
>>> for each hemisphere
>>> >>>>> mri_concat
>>> allgrp1.lhmgxctx.fsaverage.sm05.zero.nii.gz
>>> >>>>> allgrp2.lhmgxctx.fsaverage.sm05.nii.gz --o
>>> >>>>> lh.pvr_grp2_pet.nii.gz
>>> >>>>> mri_concat
>>> allgrp1.rhmgxctx.fsaverage.sm05.zero.nii.gz
>>> >>>>> allgrp2.rhmgxctx.fsaverage.sm05.nii.gz --o
>>> >>>>> rh.pvr_grp2_pet.nii.gz
>>> >>>>>
>>> >>>>> ###-----repeat steps 1-8 for cortical
>>> thickness-------
>>> >>>>>
>>> >>>>> ###run glm-fit for group1
>>> >>>>> mri_glmfit --y lh.pvr_grp1_pet.nii.gz
>>> --fsgd
>>> >>>>> project.fsgd dods --c pvr1.mtx --pvr
>>> >>>>> lh_pvr_grp1_thickness.mgh --surf fsaverage lh
>>> --cortex
>>> >>>>> --glmdir lh.grp1.pet.thickness.glmdir
>>> >>>>> mri_glmfit --y rh.pvr_grp1_pet.nii.gz
>>> --fsgd
>>> >>>>> project.fsgd dods --c pvr1.mtx --pvr
>>> >>>>> rh_pvr_grp1_thickness.mgh --surf fsaverage lh
>>> --cortex
>>> >>>>> --glmdir rh.grp1.pet.thickness.glmdir
>>> >>>>>
>>> >>>>> ###run glm-fit for group2
>>> >>>>> mri_glmfit --y lh.pvr_grp2_pet.nii.gz
>>> --fsgd
>>> >>>>> project.fsgd dods --c pvr2.mtx --pvr
>>> >>>>> lh_pvr_grp2_thickness.mgh --surf fsaverage lh
>>> --cortex
>>> >>>>> --glmdir lh.grp2.pet.thickness.glmdir
>>> >>>>> mri_glmfit --y rh.pvr_grp2_pet.nii.gz
>>> --fsgd
>>> >>>>> project.fsgd dods --c pvr2.mtx --pvr
>>> >>>>> rh_pvr_grp2_thickness.mgh --surf fsaverage lh
>>> --cortex
>>> >>>>> --glmdir rh.grp2.pet.thickness.glmdir
>>> >>>>>
>>> >>>>> My questions.
>>> >>>>> 1) will my fsgd file contain both groups?
>>> >>>>> 2) If the answer from question is yes,
>>> i should have 2
>>> >>>>> contrasts (pvr1.mtx for group1 and
>>> pvr2.mtx for
>>> >>>>> group2). yes/no?
>>> >>>>> 3) below is a sample of my fsgd file.
>>> are the
>>> >>>>> constrasts correct?
>>> >>>>>
>>> >>>>> Thank you very much.
>>> >>>>> Paul.
>>> >>>>> The fsgd file lists:
>>> >>>>>
>>>   -------------------------------------------------------------
>>> >>>>> GroupDescriptorFile 1
>>> >>>>> Title Relationship Amy-thick reg out
>>> age and education
>>> >>>>> Class g1
>>> >>>>> Class g2
>>> >>>>> Variable Age Education
>>> >>>>> Input XX1 g1 60 16
>>> >>>>> Input YY1 g2 62 20
>>> >>>>>
>>>   -------------------------------------------------------------
>>> >>>>> matrix for group1:
>>> >>>>> pvr1.mtx= 1 0 0 0 0 0 0
>>> >>>>> is there a relationship between
>>> amyloid-thickness in group1 regressing out age
>>> >>>>> and education?
>>> >>>>> matrix for group2:
>>> >>>>> pvr2.mtx= 0 1 0 0 0 0 0
>>> >>>>> is there a relationship between
>>> amyloid-thickness in group2 regressing out age
>>> >>>>> and education?
>>> >>>>>
>>> >>>>> On Thu, Aug 1, 2019 at 9:44 PM Greve,
>>> Douglas N.,Ph.D.
>>> >>>>> <DGREVE@mgh.harvard.edu
>>> <mailto:DGREVE@mgh.harvard.edu>
>>> >>>>> <mailto:DGREVE@mgh.harvard.edu
>>> <mailto:DGREVE@mgh.harvard.edu>>> wrote:
>>> >>>>>
>>> >>>>> Each PVR adds a single column to
>>> the design
>>> >>>>> matrix. In a two group design,
>>> this can make it
>>> >>>>> tricky to set up. Let's say you
>>> have 10 of group1
>>> >>>>> and 20 of group2. You will need to
>>> create two PVR
>>> >>>>> files, each with 30=10+20 frames.
>>> In the first
>>> >>>>> one, the first 10 frames will be
>>> cortical
>>> >>>>> thickness (or amyloid sampled on
>>> the surface) of
>>> >>>>> group1; the next 20 frames will be
>>> all zeros. For
>>> >>>>> the 2nd PVR, the first 10 frames
>>> will be 0s and
>>> >>>>> the next 20 frames will be the
>>> cortical thickness
>>> >>>>> (or amyloid) for group2. I would
>>> start by running
>>> >>>>> mris_preproc for the two groups separate (so 2
>>> >>>>> files, one with 10 frames the
>>> other 20 frames).
>>> >>>>> Then create the file of zeros using
>>> >>>>> fscalc group2.mgz mul 0 -o
>>> group2.zeros.mgz
>>> >>>>> Then
>>> >>>>> mri_concat group1.mgz group2.zeros.mgz --o pvr1.mgz
>>> >>>>> Then create the contrast based on
>>> the FSGD, but
>>> >>>>> then add two more numbers, one for
>>> PVR1 (which
>>> >>>>> tests for the within group
>>> correlation), and one
>>> >>>>> for PVR2
>>> >>>>>
>>> >>>>>
>>> >>>>> On 8/1/2019 3:14 PM, miracle
>>> ozzoude wrote:
>>> >>>>>>
>>> >>>>>>          External Email - Use Caution
>>> >>>>>>
>>> >>>>>> Please, can anyone help me with this.
>>> >>>>>> Thank you
>>> >>>>>>
>>> >>>>>> Paul
>>> >>>>>>
>>> >>>>>> ---------- Forwarded message ---------
>>> >>>>>> From: *miracle ozzoude*
>>> <miracooloz@gmail.com <mailto:miracooloz@gmail.com>
>>> >>>>>> <mailto:miracooloz@gmail.com
>>> <mailto:miracooloz@gmail.com>>>
>>> >>>>>> Date: Wed, Jul 31, 2019 at 2:11 PM
>>> >>>>>> Subject: multimodal analysis (pet and cortical
>>> >>>>>> thickness relationship) using --pvr
>>> >>>>>> To: Douglas N Greve
>>> >>>>>> <freesurfer@nmr.mgh.harvard.edu
>>> <mailto:freesurfer@nmr.mgh.harvard.edu>
>>> >>>>>> <mailto:freesurfer@nmr.mgh.harvard.edu
>>> <mailto:freesurfer@nmr.mgh.harvard.edu>>>
>>> >>>>>>
>>> >>>>>>
>>> >>>>>> Hello Experts,
>>> >>>>>>
>>> >>>>>> I am performing an analysis
>>> looking at the
>>> >>>>>> relationship between amyloid uptake and cortical
>>> >>>>>> thickness using --pvr flag in mri_glmfit. I've 2
>>> >>>>>> groups and 2 variables (age and education). I
>>> >>>>>> want to run a within group
>>> analysis while
>>> >>>>>> regressing out age and education (i.e. Within
>>> >>>>>> group 1, is there a negative
>>> relationship between
>>> >>>>>> amyloid uptake and cortical thickness regressing
>>> >>>>>> out the effects of age and
>>> education).
>>> >>>>>>
>>> >>>>>> However, i'm not sure how my pvr contrasts will
>>> >>>>>> look like. Below are my fsgd and
>>> an attempt at
>>> >>>>>> creating contrasts. Please, can you let me know
>>> >>>>>> if my contrasts are correct based
>>> on my questions.
>>> >>>>>>
>>> >>>>>> Thank you.
>>> >>>>>>
>>> >>>>>> Best,
>>> >>>>>> Paul
>>> >>>>>>
>>> >>>>>> The fsgd file lists:
>>> >>>>>>
>>>   -------------------------------------------------------------
>>> >>>>>> GroupDescriptorFile 1
>>> >>>>>> Title Relationship Amy-thick reg
>>> out age and education
>>> >>>>>> Class g1
>>> >>>>>> Class g2
>>> >>>>>> Variable Age Education
>>> >>>>>> Input XX1 g1 60 16
>>> >>>>>> Input XX2 g1 58 14
>>> >>>>>> Input YY1 g2 62 20
>>> >>>>>> �� Input YY1 g2 62 20
>>> >>>>>>
>>>   -------------------------------------------------------------
>>> >>>>>> matrix for group1:
>>> >>>>>> pvrgroup1= 1 0 0 0 0 0 0
>>> >>>>>> is there a relationship between
>>> amyloid-thickness in group1 regressing out age
>>> >>>>>> and education?
>>> >>>>>> matrix for group2:
>>> >>>>>> pvrgroup2= 0 1 0 0 0 0 0
>>> >>>>>> is there a relationship between
>>> amyloid-thickness in group2 regressing out age
>>> >>>>>> and education?
>>> >>>>>>
>>> >>>>>>
>>> >>>>>>
>>> >>>>>>
>>> >>>>>> _______________________________________________
>>> >>>>>> Freesurfer mailing list
>>> >>>>>> Freesurfer@nmr.mgh.harvard.edu
>>> <mailto:Freesurfer@nmr.mgh.harvard.edu>
>>> <mailto:Freesurfer@nmr.mgh.harvard.edu
>>> <mailto:Freesurfer@nmr.mgh.harvard.edu>>
>>> >>>>>>
>>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
>>> >>>>>
>>> >>>>> _______________________________________________
>>> >>>>> Freesurfer mailing list
>>> >>>>> Freesurfer@nmr.mgh.harvard.edu
>>> <mailto:Freesurfer@nmr.mgh.harvard.edu>
>>> >>>>> <mailto:Freesurfer@nmr.mgh.harvard.edu
>>> <mailto:Freesurfer@nmr.mgh.harvard.edu>>
>>> >>>>>
>>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
>>> >>>>>
>>> >>>>>
>>> >>>>> _______________________________________________
>>> >>>>> Freesurfer mailing list
>>> >>>>> Freesurfer@nmr.mgh.harvard.edu
>>> <mailto:Freesurfer@nmr.mgh.harvard.edu>
>>> <mailto:Freesurfer@nmr.mgh.harvard.edu
>>> <mailto:Freesurfer@nmr.mgh.harvard.edu>>
>>> >>>>>
>>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
>>> >>>>
>>> >>>> _______________________________________________
>>> >>>> Freesurfer mailing list
>>> >>>> Freesurfer@nmr.mgh.harvard.edu
>>> <mailto:Freesurfer@nmr.mgh.harvard.edu>
>>> >>>> <mailto:Freesurfer@nmr.mgh.harvard.edu
>>> <mailto:Freesurfer@nmr.mgh.harvard.edu>>
>>> >>>>
>>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
>>> >>>>
>>> >>>>
>>> >>>> _______________________________________________
>>> >>>> Freesurfer mailing list
>>> >>>> Freesurfer@nmr.mgh.harvard.edu
>>> <mailto:Freesurfer@nmr.mgh.harvard.edu>
>>> <mailto:Freesurfer@nmr.mgh.harvard.edu
>>> <mailto:Freesurfer@nmr.mgh.harvard.edu>>
>>> >>>>
>>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
>>> >>>
>>> >>>
>>> >>> _______________________________________________
>>> >>> Freesurfer mailing list
>>> >>> Freesurfer@nmr.mgh.harvard.edu
>>> <mailto:Freesurfer@nmr.mgh.harvard.edu>
>>> <mailto:Freesurfer@nmr.mgh.harvard.edu
>>> <mailto:Freesurfer@nmr.mgh.harvard.edu>>
>>> >>>
>>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
>>> >>
>>> >> _______________________________________________
>>> >> Freesurfer mailing list
>>> >> Freesurfer@nmr.mgh.harvard.edu
>>> <mailto:Freesurfer@nmr.mgh.harvard.edu>
>>> >> <mailto:Freesurfer@nmr.mgh.harvard.edu
>>> <mailto:Freesurfer@nmr.mgh.harvard.edu>>
>>> >>
>>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
>>> >>
>>> >>
>>> >> _______________________________________________
>>> >> Freesurfer mailing list
>>> >> Freesurfer@nmr.mgh.harvard.edu
>>> <mailto:Freesurfer@nmr.mgh.harvard.edu>
>>> <mailto:Freesurfer@nmr.mgh.harvard.edu
>>> <mailto:Freesurfer@nmr.mgh.harvard.edu>>
>>> >>
>>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
>>> >
>>> > _______________________________________________
>>> > Freesurfer mailing list
>>> > Freesurfer@nmr.mgh.harvard.edu
>>> <mailto:Freesurfer@nmr.mgh.harvard.edu>
>>> <mailto:Freesurfer@nmr.mgh.harvard.edu
>>> <mailto:Freesurfer@nmr.mgh.harvard.edu>>
>>> >
>>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
>>> >
>>> >
>>> > _______________________________________________
>>> > Freesurfer mailing list
>>> > Freesurfer@nmr.mgh.harvard.edu
>>> <mailto:Freesurfer@nmr.mgh.harvard.edu>
>>> >
>>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
>>>
>>>
>>> _______________________________________________
>>> Freesurfer mailing list
>>> Freesurfer@nmr.mgh.harvard.edu
>>> <mailto:Freesurfer@nmr.mgh.harvard.edu>
>>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
>>>
>>>
>>> _______________________________________________
>>> Freesurfer mailing list
>>> Freesurfer@nmr.mgh.harvard.edu <mailto:Freesurfer@nmr.mgh.harvard.edu>
>>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
>>
>> _______________________________________________
>> Freesurfer mailing list
>> Freesurfer@nmr.mgh.harvard.edu
>> <mailto:Freesurfer@nmr.mgh.harvard.edu>
>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
>>
>>
>> _______________________________________________
>> Freesurfer mailing list
>> Freesurfer@nmr.mgh.harvard.edu <mailto:Freesurfer@nmr.mgh.harvard.edu>
>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
>
> _______________________________________________
> Freesurfer mailing list
> Freesurfer@nmr.mgh.harvard.edu <mailto: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

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