[Freesurfer] mri_volcluster not recognize --mindistance

[Yagmur Ozdemir 19]

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Hello FreeSurfer experts,

I am trying to run mri_volcluster with the following command to later create 
masks of clustered regions from functional data. I get an error saying that the 
option --mindistance is not recognized, even though this option is shown in 
mri_volcluster --help and the FS wiki page. Any idea what might be causing this?

mri_volcluster --in thresh_highres.nii.gz --sum volcluster.txt --ocn 
clustered_thresh_highres.nii.gz --thmin 1.5 --sign pos --regheader  
--mindistance 10 --minsizevox 800 --fwhm 3
ERROR: Option --mindistance unknown

Best
Idil
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[Freesurfer] Using Freesurfer for unconventional group analysis

[Alon Baram]

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 Hi!
(tl:dr - I have a few questions listed at the end of this message. most of
the message is just details about these questions).

I have a volumetric map of values for each subject, which you can think of
as a contrast (it is actually a contrast of distances from a
Representational Similarity Analysis (RSA) calculated in Matlab using the
RSA toolbox, but that’s irrelevant to my questions). I did my preprocessing
in FSL. These maps are currently in a downsampled (2x2x2) version of the
anatomical image (see next paragraph for details). I used FSL’s FLIRT to
move my functional images to that space, using the examplefunc2highres.mat
transformation matrix, highres (the anatomical image) as the reference
image, and the flag -applyisoxfm 2 to ensure the resolution stays 2x2x2.

(( **Less relevant to my Freesurfer questions so feel free to skip**:
the reason I chose to run my RSA analyses in this 2x2x2 anatomical space is
that I have 8 runs (EPI sequences), with a structural scan after 4 runs.
Since I need to align all my runs to one template image to do the RSA
analysis with conditions across runs, it seemed like a natural choice: I
first run FEAT preprocessing on each run separately, and use a the middle
image from run X as the motion correction template for run X (as is the
default). I then transform the filtered_func_data.nii.gz file of each run
to the 2x2x2 anatomical space. If this seems like a mistake to you, please
let me know! ))

I would like to project these contrast maps to a common surface, and to do
group analysis on the surface. I think I need to use the command
mris_preproc or mri_vol2surf (see next paragraph), but both need a
registration file which I’m not sure how to get. given that my contrast
images are already in the “correct” (anatomical space) orientation, I
thought the transformation matrix should just be the identity matrix.
I tried using bbregister with the brain extracted structural image as the
--mov template (the resolution in the resulting register.dat file will be
1x1x1, and not 2x2x2 like the transformed functional images, but the
resolution lines in the register.dat file are anyway being ignored. The
transformation matrix should be correct). I tried this and the
transformation matrix was not the identity matrix, but rather:
9.98211860657e-01 5.568005726672709e-04 -6.800168921472505e-05
5.548541247844696e-02
1.512142625870183e-04 -1.508450955152512e-01 9.885573387145996e-01
-3.581156954169273e-02
5.401717498898506e-04 -9.885571599006653e-01 -1.508451700210571e-01
3.751721233129501e-02
when I look at this registration with tkregisterfv it looks fine (both for
the structural image and for the examplefunc after transformed to the 2x2x2
structural space) - so this seems to be working. If anybody has an
explanation why the transformation matrix between the skull-striped
anatomical image from FSL to orig.mgz is not the identity matrix I would
appreciate it.

I’m not sure how to get the maps into a common surface and not subject
surface. The register.dat file I will obtain will be the registration from
the functional space (in my case the downsampled anatomical space) to the
subject’s anatomical space. If I give that as input to mri_vol2surf, but
use "--trgsubject fsaverage", will Freesurfer automatically know to apply
the registration from the subject’s surface to fsaverage (if I'm correct it
uses the sphere registration - is that the right thing to do?)? If I only
want to do surface group analysis and I’m not interested in viewing the
individual subject’s contrasts on the surface, do I even need to use
mri_vol2surf? or is it enough to just use mris_preproc and use the --iv
flags to specify the volumetric contrast images and the register.dat files?

I would like to run a one-sided Wilcoxon sign-rank test on these contrasts
across subjects (and not a GLM - I want to know if my contrasts are
different from 0 across subjects, but the contrast maps are not
necessarily normally distributed) . so I can’t use mri_glmfit. Is there any
way of doing that in Freesurfer? If not, is there an easy way to export the
output of mris_preproc (stacked contrasts of different subjects, already
sampled to fsaverage) into Matlab? After doing the analysis in Matlab, can
i just write the result (a vector of p-values of size nNodes x 1) into a
csv file or something like that, and then load it in Freeview as an overlay
on the fsaverage surface? Is there a particular way in which this
conversion from freesurfer to Matlab and back to freesurfer should be done?

Finally, I will need to correct for multiple comparisons. Is there any way
for me to still do that with the Freesurfer machinery for cluster
correction, even though I am not running  mri_glmfit, but rather doing a
non-parametric statistical test?

To summarise, my questions are:

1) How to create a registration.dat file with registration from my weird
2x2x2 anatomical space, where my (functional) contrasts 

[Freesurfer] Plotting QDEC results

[Avi Gharehgazlou]

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Hi experts,

I looked at association between LGI and a behavioural scale on QDEC. after
the analysis, to plot the significant clusters/ blobs, I wanted to export
LGI values for each subject from each significant blob and based on
instructions in previous archives I ran the following command line:

mri_glmfit-sim –glmdir (qdec output directory) --cache 1.3 abs
which generated a "cache.th13.abs.y.ocn.dat" file. This file contains 3
columns and 36 rows. I'm assuming the values in the three columns
correspond to LGI values for each significant blob for each subject? (I had
3 significant blobs and 36 participants)

Will you please confirm I am doing (and interpreting) this correctly?

Thanks so much,

Avi
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[Freesurfer] Mailing List Submission

[Maurisa Major]

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Hi, I would like to post the following to the mailing list:

Freesurfer experts,

We are a small medical practice in California and are looking for someone
who works with Freesurfer to help us visualize MRI's with DTI so we can
show the images to our patients.
If you or someone you know is willing to do some freelancing with us,
please contact us at maur...@tsmdinc.com with the subject line "Freesurfer
Freelancer."

Thank you.

-- 
Best,
Maurisa
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[Freesurfer] Q & A Forum in neuroimaging techniques

[James Brown]

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> Dear Colleagues,
> We would like to create Q & A forum about issues in neuroimaging techniques. 
> Experts from the Martinos Center and Oxford FMRIB will be invited to build 
> this forum and to answer questions and provide plans for critical technical 
> issues. This forum will serve as a reference for our colleagues who would 
> like to learn about neuroimaging  (analyses pipelines, methodologies, tools 
> development. etc) as well as a library and repository that can benefit 
> any one who is interested in this field. The forum will include chat rooms 
> and live discussions with an experts in the field.
>
> We are looking forward for your support and contributions. Please follow us 
> here:
> https://area51.stackexchange.com/proposals/119504/neuroimaging?referrer=JC-CieH5cIdCKHgDAqvZmw2
>
> Sincerely,
> James Brown___
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[Freesurfer] coregistering with bbregister

[Ben M]

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Hi,
I'm trying to coregister the strucural image to the mean functional image
using bbregister, so after reconall I did:

bbregister --t2 --init-fsl --reg /data/bbregister/reg.dat --mov
/data/mean_func.nii.gz --s 001

bet /data/structural.nii.gz /data/bet_structural.nii.gz

#brain.nii.gz is the brain.mgz from reconall output (in freesurfer space)
mri_vol2vol --mov /data/bet_structural.nii.gz --targ /data/brain.nii.gz --o
/data/coregistered_structural.nii.gz --reg /data/bbregister/reg.dat --inv
–-nearest

But when I load the coregistered_structural.nii.gz and the mean_func.nii.gz
they are not aligned. I'm sure I'm doing something wrong, could someone
help me figure it out please?

Thanks in advance,
Ben
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[Freesurfer] Q & A Forum in neuroimaging techniques

[James Brown]

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Dear Colleagues,
We would like to create Q & A forum about issues in neuroimaging techniques. 
Experts from the Martinos Center and Oxford FMRIB will be invited to build this 
forum and to answer questions and provide plans for critical technical issues. 
This forum will serve as a reference for our colleagues who would like to learn 
about neuroimaging  (analyses pipelines, methodologies, tools development. 
etc) as well as a library and repository that can benefit any one who is 
interested in this field. The forum will include chat rooms and live 
discussions with an experts in the field.

We are looking forward for your support and contributions. Please follow us 
here:
https://area51.stackexchange.com/proposals/119504/neuroimaging?referrer=JC-CieH5cIdCKHgDAqvZmw2

Sincerely,
James Brown___
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[Freesurfer] Surface Area in Toddlers/Children

[Derek Sayre Andrews]

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Dear Freesurfer Developers and Experts,

I have been exploring various vertex wise (mass univariate) effects using 
freesurfer measures of cortical thickness and surface area in a cohort of 
toddlers/children aged 25-70 months.

When looking at the effect of age on surface area using individuals’ measures 
mapped to fsaverage and smoothed at 15mm fwhm (area.pial. fwhm15.fsaverage.mgh) 
I observed a widespread negative effect of age (i.e. decreased surface area 
with age). Given the age group of the cohort this seems implausible. Plotting 
the sum of each individuals lh+rh.area.pialfsaverage.fwhm15.mgh against age 
shows the relationship:
[cid:image001.png@01D42FCE.C197B360]

However, plotting the lh+rh total surface area returned by 
mris_anatomical_stats reveals a much more plausible relationship between 
surface area and age:
[cid:image002.png@01D42FCE.C197B360]


My working hypothesis is that the significantly smaller brain sizes of our 
cohort compared to fsaverage, and the fact(?) that -qcache does not preserve 
global surface area, is causing an “over adjustment” in our cohorts smallest 
brains when mapped to fsaverage.

Thus, my questions are three fold


  1.  Is the mapping of our significantly smaller brains to fsaverage a 
potential explanation for the results we are seeing in our mass univariate 
analyses of surface area?


  1.  If this is the case, would this effect be limited to surface area or also 
extend to other freesurfer measures including cortical thickness, lGI, sulcal 
depth etc.


  1.  How would you recommend approaching vertex wise analyses in a cohort of 
this age? Create a study specific average subject using make_average_subject to 
map onto?

Thank you for your insight and guidance!

Best, Derek


PS: All processing was performed using freesurfer v5.1



Derek Sayre Andrews, PhD
Postdoctoral Scholar
Department of Psychiatry and Behavioral Sciences
The M.I.N.D Institute
University of California Davis

Telephone: +1 916 703 0360
Email: dandr...@ucdavis.edu


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