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Dear freesurfers,
for a morphometry study, I am comparing a single subject at a time to a group of controls. I would like to include age, gender (as a continuous variable for the sake of simplicity) and eTIV as "nuisance" regressors in the GLM. The FSGD looks like this:
GroupDescriptorFile 1
Title SUBJECT1_vs_allControls
Class Test
Class Controls
Variables Age Gender eTIV
Input SUBJECT1 Test 50 1 1497422.2500
Input SUBJECT2 Controls 30 0 1709039.536815
Input SUBJECT3 Controls 29 0 1423097.816203
Input SUBJECT4 Controls 31 1 1524690.026713
...
When I try to run mri_glmfit I get the following error even though I specify DOSS:
$ mri_glmfit --fsgd SUBJECT1_vs_allControls.fsgd doss [...]
gdfRead(): reading SUBJECT1_vs_allControls.fsgd
WARNING: variable 1 is "Gender" which is often a discrete factor
The proper way to handle discrete factors is to create classes.
See https://secure-web.cisco.com/10ThHTirv10OEqbkasMHR-FObJ8JCIIzwnlckPdClcabJk…
INFO: DeMeanFlag keyword not found, DeMeaning will NOT be done.
Continuous Variable Means (all subjects)
0 Age 28.6875 6.36611
1 Gender 0.46875 0.499022
2 eTIV 1.51444e+06 125811
Class Size and Means of each Continuous Variable
1 Test 1 50.0000 1.0000 1497422.2500
2 Controls 31 28.0000 0.4516 1514993.8589
ERROR: Class Test has 1 members. With 3 variables and using DODS, you need at least 4 members
How do I get mri_glmfit to use DOSS, or do I have to specify the design matrix by hand in this case?
Thank you!
Best wishes
Cornelius
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Dear Freesurfer team,
I am inspecting the different participants I have run recon-all -all and I
have found different errors I would like to discuss with you before
proceeding as I am new with this software.
1. I have found dura at some regions of the brain. I should use gcut or
delete voxels?
2. I have found discontinuity in GM and what I should do with this
(attached photo 2)
3. In photo 1, not sure at some regions were to consider wm as it is not
clear for me...any suggestion with this one? I think it should be done with
cp, right?
Kind regards,
Rosie
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Dear Freesurfer Experts,
I am wondering whether the extracted ROI volume data acquired when using the command aparcstats2table needs to be smoothed? I performed surface smoothing using surf2surf for cortical thickness data, but cannot find a way to smooth the volume data listed in aparcstats2table. Is it recommended that I do not perform smoothing?
Thank You,
Ryan
-----------------------------------------------------------------------------------------------
Ryan Patrick Bell, Ph.D.
Research Analyst, Department of Psychiatry & Behavioral Sciences
905 W. Main St., Suite 24-E
Durham, NC 27701
Phone: (919) 681-3495
Email: ryan.bell(a)duke.edu<mailto:ryan.bell@duke.edu>
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Thank you for the response Bruce.
I apologize for the confusion regarding surface map but what I was trying
is that I wanted to create a surface file that contains dice coefficients
for labels across the entire cortex. With your response, I think I can get
the average dice coefficient for each label and hopefully create a surface
map that visualizes dice coefficients on brain surface map.
Would there be a way to create my own surface map with brain morphometry
values that I created?
Best,
Julia Shin
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Hi freesurfer user.
I have been working with some cortical thickness values of a control group to test some changes related to cognitive training. However, I have been hesitating about whether I have to normalize the cortical thickness values (as happens with subcortical volumes and ICV) or not. I have read a little about it and I understood that I could use the ICV or/and mean cortical thickness, but I didn't find a specific criteria to do or not this normalization. Any clue, recommendation, explanation or paper about this will be very helpful.
Thanks in advance.
*or reposting discussion of this question.
Gabriel R.
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Hi,
In freeview, is it possible to view a collection of labels with different
filled in colors, as well as their outlines?
So, a combination of the filled in and outline only modes?
Best,
Prad
-------- Forwarded Message --------
Subject: Innis Lab postdoc position 2022
Date: Thu, 8 Jul 2021 19:45:24 +0000
From: Innis, Robert (NIH/NIMH) [E] <innisr(a)mail.nih.gov>
To: Innis, Robert (NIH/NIMH) [E] <innisr(a)mail.nih.gov>
A postdoctoral position will be available in my lab starting in the
first half of 2022. Please forward the attached advertisement to anyone
who may be interested.
The two major goals are translational studies of neuroinflammation
(i.e., COX-1, COX-2, and TSPO) and indirect markers of cAMP signaling
(via PDE4B and PDE4D). The studies extend from transgenic mice to
monkeys and to patients, including those with depression or dementia.
Stay safe and many thanks,
Bob Innis
************************************
Robert B. Innis, MD, PhD
Chief, Molecular Imaging Branch
National Institute of Mental Health
10 Center Drive, MSC-1026
Bldg. 10, Rm. B1D43
Bethesda, MD 20892-1026
Tel: 301-594-1368
Fax: 301-480-3610
Email: robert.innis(a)nih.gov <mailto:robert.innis@nih.gov>
Branch Administrative Manager: Elizabeth Alzona
Tel: 301-594-1089
Email: alzonae(a)irp.nimh.nih.gov <mailto:alzonae@irp.nimh.nih.gov>
Molecular Imaging Branch
website<https://secure-web.cisco.com/1ArBJjYhVhrUft9gNOaLCuNtmSeJ1qPEnHkkGF7qzP9gVj…>
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Dear Freesurfer team,
It is my first time editing wm segmentation (white matter segmentation
errors + topological errors).
I wonder if there is a good tutorial on which I could rely.
Also, I have read there is an example of segmentation that comes with
FreeSurfer that is called Bert. I think it would be great to have it so I
can look at it as a good example.
Your help on this is very much appreciated
Kind regards,
Rosie
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Hi,
I am running Freesurfer on longitudinal datasets all obtained on 3T
scanners. Unfortunately, many of the MRIs were done on different
scanners, Phillips and GE.
Would longitudinal pipeline help reduced scanner variability or should I
process crossectionally each time point separately and normalize these time
points with eTIV?
Many thanks
AJ
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Dear Freesurfer team,
Following this link:
https://secure-web.cisco.com/1JQvIqqm3-q4IvkVi2SEZWuHP3qoo3qga0SfN71vLNIZ9q…
It says how to run segmentation of hippocampal subfields before running
recon-all but not once you already have recon-all -all run.
Any suggestions on how I can get the segmentation of hippocampal subfields
under this situation would be appreciated.
Kind regards,
Rosie