Hi Bruce,
Thanks for the reply. The talairach.xfm file generated by the palarellizing
machine is empty; it looks as follows:
Talairach.xfm file:
MNI Transform File
% avi2talxfm
Transform_Type = Linear;
Linear_Transform =
However, the talaraich.xfm file generated by the non-paralellizing machine
is the following:
MNI Transform File
% avi2talxfm
Transform_Type = Linear;
Linear_Transform =
1.088816 -0.036409 -0.059575 1.880753
0.047590 1.030018 0.245325 -4.493217
0.029937 -0.211744 1.231518 94.663368;
Anna
On Thu, Oct 22, 2015 at 6:00 PM, <freesurfer-requ...@nmr.mgh.harvard.edu>
wrote:
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When replying, please edit your Subject line so it is more
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than "Re: Contents of Freesurfer digest..."
Today's Topics:
1. normalization of hippocampal volume (geschwind2013)
2. Postdoctoral Opportunity: Multimodal MRI registration
and
analysis (Frederic Andersson)
3. Re: A mixed effect model approach in within subject
dataset
{Disarmed} {Disarmed} (jorge luis)
4. Re: Sulcal depth units (Bruce Fischl)
5. Re: mris_expand - problem reading thickness file? (Bruce
Fischl)
6. Re: How to compute the measures on the average brain?
(Bruce Fischl)
7. Re: Talairach_afd error (Bruce Fischl)
8. Re: How to compute the measures on the average brain?
(Douglas N Greve)
9. Re: normalization of hippocampal volume (Douglas N Greve)
10. Re: per analysis with covariates (Douglas N Greve)
----------------------------------------------------------------------
Message: 1
Date: Thu, 22 Oct 2015 17:18:21 +0900
From: geschwind2013 <neurof...@gmail.com>
Subject: [Freesurfer] normalization of hippocampal volume
To: Freesurfer support list <freesurfer@nmr.mgh.harvard.edu>
Message-ID: <27af7eca-e1b4-4337-bb2c-4cbe4109f...@gmail.com>
Content-Type: text/plain; charset=euc-kr
Hi, FS Experts,
I?m using version 5.3 and have performed hippo-subfields
analysis.
To perform the statistics, shall I get the normalized volumes of
each hippo-subfields?
or just to do correction for ICV is enough ?
thanks..
Hyon
------------------------------
Message: 2
Date: Thu, 22 Oct 2015 15:30:14 +0200
From: Frederic Andersson <anders...@univ-tours.fr>
Subject: [Freesurfer] Postdoctoral Opportunity: Multimodal MRI
registration and analysis
To: freesurfer@nmr.mgh.harvard.edu
Message-ID: <6e3a85f5-c942-49d0-bbe0-4c51c4e8e...@univ-tours.fr>
Content-Type: text/plain; charset="utf-8"
Postdoctoral Opportunity: Multimodal MRI registration and
analysis
Context and methodology
This postdoctoral position will focus on the registration of
ex-vivo onto in-vivo MR data. Based on some recent advances
extending the combined volume and surface registration,
efficient approaches can be provided for dealing with this
issue. However, these methods need to be validated and several
open theoretical questions are related to this problem and will
be investigated during this postdoctoral work. The theoretical
results obtained will be tested and used on real human data in a
larger framework aiming at tractography validation (French
National Research Agency Grant ANR 2014, collaborative study
Inserm U930, Universit? de Tours, Neurospin and Martinos
Center).
Applicant profile
Candidates should have a strong background in image registration
and MR imaging, a good publication record, and strong experience
in c++ and matlab coding. Proficiency in English is required, as
well as scientific writing skills.
Applicants should send a CV, including list of publications and
a description of previous research experience, as well as the
names and emails of two academic referees to: Clovis Tauber
(clovis.tau...@univ-tours.fr
<mailto:clovis.tau...@univ-tours.fr>) and Christophe Destrieux
(christophe.destri...@univtours.fr
<mailto:christophe.destri...@univtours.fr> )
Conditions
Starting date: January 2016 (adjustable)
Contract: 2 years
Location: Imaging and Brain unit, INSERM U930, Tours.
Salary: related to experience
References
G.M. Postelnicu, L. Z?llei, B. Fischl: Combined Volumetric and
Surface Registration, IEEE Transactions on Medical Imaging 28
(4), April 2009, p. 508--522
Zemmoura I, Serres B, Andersson F, Barrantin L, Tauber C,
Filipiak I, Cottier JP, Venturini G and Destrieux C 2014
FIBRASCAN: a novel method for 3D white matter tract
reconstruction in MR space from cadaveric dissection Neuroimage
103 106?118
Serres B, Zemmoura I, Andersson F, Tauber C, Destrieux C and
Venturini G 2013 Brain Virtual Dissection and White Matter 3D
Visualization Stud. Health Technol. Inform. 184 392--396
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Message: 3
Date: Thu, 22 Oct 2015 13:45:28 +0000 (UTC)
From: jorge luis <jbernal0...@yahoo.es>
Subject: Re: [Freesurfer] A mixed effect model approach in
within
subject dataset {Disarmed} {Disarmed}
To: Freesurfer support list <freesurfer@nmr.mgh.harvard.edu>
Cc: "pablon...@hotmail.com" <pablon...@hotmail.com>
Message-ID:
<1841220171.2266406.1445521528699.javamail.ya...@mail.yahoo.com>
Content-Type: text/plain; charset="utf-8"
Hi Pablo
If you havethoroughly checked that everything is properly setup
so that theordering of the design matrix's rows is in proper
correspondence withthe ordering of the image data matrix's rows
and it is also in propercorrespondence with the ordering of the
entries in vector ni (eachentry of this vector has the number of
subjects belonging to the samefamily) and the design matrix has
enough covariates to describe yourdata then the analysis should
be correct.
Bear in mind thatyou are not analyzing longitudinal data for
which a proper imageregistration pipeline exists in Freesurfer
and there is a clearwithin-subject correlation between cortical
thickness values acrosstime points at the same surface vertex.
Instead you are analyzingfamily data in which you are trying to
model vertex-wise correlationsacross different subjects.
Although in principle there should bewithin-family correlation
the image registration procedure (and imageprocessing pipeline
in general) as well as individual variation couldhave introduced
a lot of noise in your data making the vertex-wisewithin-family
correlations rather weak. This makes it hard for theLME
estimation procedure to converge and give precise
parameterestimates.
Best-Jorge
De: pablo najt <pablon...@hotmail.com>
Para: Freesurfer support list <freesurfer@nmr.mgh.harvard.edu>
Enviado: Jueves 22 de octubre de 2015 1:15
Asunto: Re: [Freesurfer] A mixed effect model approach in
within subject dataset {Disarmed} {Disarmed}
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P{margin:0px;padding:0px;}#yiv0632092676
body.yiv0632092676hmmessage{font-size:12pt;font-family:Calibri;}-->Hello
again,I have now also run the model with 2 random effects and it
is definitively worst. The final line says:Algorithm did not
converge at 79.5859 percent of the total number of locations.
Any suggestion if I should trust in the model with 1 random
effect? I know you Martin had doubts, so I am wondering what
Jorge thinks of it.ThanksPablo
To: freesurfer@nmr.mgh.harvard.edu
From: mreu...@nmr.mgh.harvard.edu
Date: Wed, 21 Oct 2015 08:55:04 -0400
Subject: Re: [Freesurfer] A mixed effect model approach in
within subject dataset {Disarmed} {Disarmed}
Hi Pablo,
23% still seems a lot, but may be OK (maybe Jorge can comment
on that)?
If you want to do a model comparison (2 random vs 1) take a
look at the wiki. It describes how to do that.
Best, Martin
On 10/21/2015 01:19 AM, pablo najt wrote:
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{font-size:12pt;font-family:Calibri;}--> Martin, Doing the
changes in the matrix allowed me to run the command. The command
with just one random effect for the intercept term give me the
following output:
Aproximate percentage of fitted locations: 100% Summary:
Algorithm did not converge at 23.407 percent of the total
number of locations. Total elapsed time is 116.2184 minutes.
Is this ok? Is there anything I should check? Should I also
try two random effects as well? Thank you Pablo
To: freesurfer@nmr.mgh.harvard.edu
From: mreu...@nmr.mgh.harvard.edu
Date: Tue, 20 Oct 2015 09:06:53 -0400
Subject: Re: [Freesurfer] A mixed effect model approach in
within subject dataset {Disarmed} {Disarmed}
Hi Pablo,
the zero columns could be outside the cortex and then this
would be fine. Do
min(sum(lhY(:,lhcortex)))
if you get 0 you have at least one location where the column is
all zero (as we should not have any negative values, you can
test that with min(lhY(:))
Now even if you still have a column of 0 , then that vertex is
problematic, but who cares about a single vertex. If you do a
region approach, it will be part of a region anyway. so you
should check how often you get 0 columns (inside cortex).
About your M: I would subtract 1 from gender (to have 0 and 1)
Also you only need 2 columns for the groups: keep only column 3
and 4. A HC is someone who has 0 in both.
Best, Martin
On 10/20/2015 04:37 AM, pablo najt wrote:
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{font-size:12pt;font-family:Calibri;}--> Dear ?FS experts, I am
following up on an issue I am having when trying to run linear
mixed effects model. I keep getting 'Algorithm did not
converge'. So far I have changed the preprocessing steps
following literally from the wiki as in message below. Also I
tried to use only one random effect for the intercept. Also I
have checked that?sum of vectors of (ni) is equal to the number
of rows in (X).
As none of the above worked I started to have concerns about
the dimensions of my lh.thickness_sm10.mgh. ?When I load in
matlab in working space says 'too many variables'. Is this ok?
? ?
Also, when I open 'lhY' variable it shows a column of Zeros
every nine columns as below. Is this alright?
? ?
Perhaps this is fine but I would like to check on anything
that is creating this problem. For matrix 'M' I created a matlab
script that loads a matrix with intercept (all ones), HC (ones
to HC otherwise zero), U_PT (relatives of patients ones
otherwise zero), PT (patients one otherwise zero), gender, age
(see below). The three columns for groups do not match?the
qdec.table.dat which have only one column for groups (HC, U_PT,
PT). However the?order of the rows is identical in M and
qdec.table.dat ? ?
?Please let me know if this should be set differently. Thank
you Pablo
To: freesurfer@nmr.mgh.harvard.edu
From: mreu...@nmr.mgh.harvard.edu
Date: Mon, 19 Oct 2015 09:00:57 -0400
Subject: Re: [Freesurfer] A mixed effect model approach in
within subject dataset {Disarmed}
Hi Pablo,
since you did not run this through the longitudinal stream, you
won't have a base ( or subject-template), also you won't have
<tpid>.long.<base> directories, so the first command should
fail. For that you simply replace the --qdec-long with --qdec
and use the same table. Should work. The second command is fine
(it just smoothes the thickness stack).
Best, Martin
On 10/19/2015 06:51 AM, pablo najt wrote:
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{font-size:12pt;font-family:Calibri;}--> Hi Jorge and FS
experts, I have run again the analysis and still get the
convergence problem. I am assuming the issue has to do with the
preprocessing steps, as I had doubts on how to follow from the
instructions if I am not using qdec and have a cross sectional
design.
Instructions on lme in the wiki for preprocessing specify the
following:
mris_preproc --qdec-long qdec.table.dat --target
study_average --hemi lh --meas thickness --out lh.thickness.mgh
mri_surf2surf --hemi lh --s study_average --sval
lh.thickness.mgh --tval lh.thickness_sm10.mgh --fwhm-trg 10
--cortex --noreshape My data -as I explained below- is cross
section but I want to treat it as longitudinal as I want to
analyse subjects belonging to the same family.? Here is my 2
main questions:? 1) for preprocessing should I follow
instructions as it would be longitudinal data? 2) Although my
design does not allow using qdec (3 groups) do I still create a
qdec table and follow literally the two instructions above ?
Thank you Pablo
___________________________________________________________________________
_________________________________________________________
Date: Fri, 16 Oct 2015 16:24:36 +0000
From: jbernal0...@yahoo.es
To: freesurfer@nmr.mgh.harvard.edu
CC: pablon...@hotmail.com
Subject: Re: [Freesurfer] A mixed effect model approach in
within subject dataset {Disarmed}
Hi Pablo
Yes, too many locations at which the estimation algorithm
didn't converge is problematic. That might mean that having two
random effects is not appropriate for your data. You should try
to run the command with just a single random effect for the
intercept term:
lhstats = lme_mass_fit_vw(X, [1], lhY, ni, lhcortex, [], 4);
If the result still have too many non-convergence locations
then something might be wrong with the ordering of the design
matrix and its correspondence with the ordering of the ni vector
or the ordering of the image data etc... You will need to check
it thoroughly.
Cheers -Jorge
De: pablo najt <pablon...@hotmail.com>
Para: "freesurfer@nmr.mgh.harvard.edu"
<freesurfer@nmr.mgh.harvard.edu>
Enviado: Viernes 16 de octubre de 2015 1:43
Asunto: Re: [Freesurfer] A mixed effect model approach in
within subject dataset {Disarmed}
<!--#yiv0632092676 .yiv0632092676ExternalClass
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{font-size:12pt;font-family:Calibri;}--> Thanks you for the
replies. Jorge and FS experts, I have run the analysis and first
double checked that the sum of vectors of (ni) is equal to the
number of rows in (X). Both are 140 which is the number of my
subjects. The analysis gave the following 'error'(?) below: I
looked up a previous thread coming across this. At that case
you recommended Would you recommend this afain>
Aproximate percentage of fitted locations: 100% Warning:
matlabpool will be removed in a future release. To query the
size of an already started parallel pool, query the
'NumWorkers' property of the pool. To check if a pool is
already started use 'isempty(gcp('nocreate'))'.? Warning:
matlabpool will be removed in a future release. To shutdown a
parallel pool use 'delete(gcp('nocreate'))' instead.?
Parallel pool using the 'local' profile is shutting down.
?? Summary: Algorithm did not converge at 90.0637 percent
of the total number of locations. Total elapsed time is
550.1023 minutes.
Also almost all the time the screen showed the following
message:
144114: Algorithm did not converge. Initial and final
likelihoods: -38.3408-1.5708i,-241.4153-1.570796i. Location
144113: Algorithm did not converge. Initial and final
likelihoods: -5.5424-1.5708i, -133.8004-1.570796i. Location
144112: Algorithm did not converge. Initial and final
likelihoods: -7.7571-1.5708i, -319.1378-1.570796i. Location
144111: Algorithm did not converge. Initial and final
likelihoods: -16.8597-1.5708i, 0.74448. Aproximate
percentage of fitted locations: 100%
So my two questions are: 1. Is this problematic? 2. Are there
any fixes to this issue? Thank you, Pablo
Date: Thu, 15 Oct 2015 13:38:22 +0000
From: jbernal0...@yahoo.es
To: freesurfer@nmr.mgh.harvard.edu
CC: pablon...@hotmail.com
Subject: Re: [Freesurfer] A mixed effect model approach in
within subject dataset {Disarmed}
Hi Pablo
The error you are getting is because in your Matlab setup you
can only request a maximum of 4 matlab parallel workers and by
default lme requests 8. So you just need to modify your command
like this:
lhstats = lme_mass_fit_vw(X, [1 2], lhY, ni, lhcortex, [],
4);
Please make sure that sum(ni) and length(X) give the same
value before running the above command.
Cheers -Jorge
De: pablo najt <pablon...@hotmail.com>
Para: Freesurfer support list <freesurfer@nmr.mgh.harvard.edu>
Enviado: Jueves 15 de octubre de 2015 7:18
Asunto: Re: [Freesurfer] A mixed effect model approach in
within subject dataset {Disarmed}
<!----> Thank you Martin. I am trying to run the following
command line and get the error below. Would you have a
suggestion to overcome this issue? Just in case I am also
including a snapshot of my loaded variables at the bottom. Many
thanks, Pablo >> lhstats = lme_mass_fit_vw(X, [1 2], lhY, ni,
lhcortex);
Warning: matlabpool will be removed in a future release.
To query the size of an already started parallel pool, query
the 'NumWorkers'
property of the pool.
To check if a pool is already started use
'isempty(gcp('nocreate'))'.?
Warning: matlabpool will be removed in a future release.
To query the size of an already started parallel pool, query
the 'NumWorkers'
property of the pool.
To check if a pool is already started use
'isempty(gcp('nocreate'))'.?
Warning: matlabpool will be removed in a future release.
Use parpool instead.?
Starting matlabpool using the 'local' profile ...?
Error using matlabpool (line 148)
Failed to start a parallel pool. (For information in addition
to the causing error,
validate the profile 'local' in the Cluster Profile Manager.)
Error in lme_mass_fit (line 128)
? ? ? ? matlabpool(prs);
Error in lme_mass_fit_vw (line 73)
[stats1,st1] = lme_mass_fit(X,[],Xrows,Zcols,Y,ni,prs,e);
Caused by:
? ? Error using
parallel.internal.pool.InteractiveClient/start (line 330)
? ? Failed to start pool.
? ? ? ? Error using parallel.Job/submit (line 304)
? ? ? ? You requested a minimum of 8 workers, but the cluster
"local" has the
? ? ? ? NumWorkers property set to allow a maximum of 4
workers. To run a
? ? ? ? communicating job on more workers than this (up to a
maximum of 512 for the
? ? ? ? Local cluster), increase the value of the NumWorkers
property for the
? ? ? ? cluster. The default value of NumWorkers for a Local
cluster is the number of
? ? ? ? cores on the local machine.
? ???
To: freesurfer@nmr.mgh.harvard.edu
From: mreu...@nmr.mgh.harvard.edu
Date: Wed, 14 Oct 2015 10:54:41 -0400
Subject: Re: [Freesurfer] A mixed effect model approach in
within subject dataset {Disarmed}
Hi Pablo,
you should run something like this to get the ni:
[M,Y,ni] = sortData(M,1,Y,sID); # (sorts the data) see
https://surfer.nmr.mgh.harvard.edu/fswiki/LinearMixedEffectsModels
hope that helps, Martin
On 10/14/2015 10:43 AM, pablo najt wrote:
<!----> Dear FS experts. I have query about a relating to a
previous email (below).?I am aiming to run a LME analysis on
cross-sectional data from different families and have variable
'family' (number of families) as my NI vector.? My design has
three groups and therefore I am not able to use qdec. I am
running the matlab commands below and finding some difficulty
would really appreciate if you could help out. Thanks Pablo
Start analysis as follows:
1-Read your label eg.:
lhcortex =
fs_read_label('freesurfer/subjects/fsaverage/label/lh.cortex.label');
2-Read the data file eg.:
[lhY, lhmri] = fs_read_Y('lh.thickness.mgh');?
%---------------------I input the concatenated .mgh image from
preproc
andmris_surf2surf-------------------------------------------------------------
----------%
3-Fit a vertex-wise lme model with random effects.:
lhstats = lme_mass_fit_vw(X, [1 2], lhY, ni, lhcortex);
Here I am getting the following problems: %--------------------
If I use number of families as my ni get
thefollowing------------------------------------------------------------------
------------------------------%
lhstats = lme_mass_fit_vw(X, [1 2], lhY, 82, lhcortex);
Error using lme_mass_fit (line 108)
The total number of measurements, indicated by sum(ni), mustbe
the same as the number of rows of the design
matrix X
Error in lme_mass_fit_vw (line 73)
[stats1,st1] = lme_mass_fit(X,[],Xrows,Zcols,Y,ni,prs,e);
My matrix is organised in "family", "group", Sex" and "age"
columns".
? ?
4-Perform vertex-wise inference eg.: CM.C = [your contrast
matrix]; F_lhstats = lme_mass_F(lhstats, CM); 5-Save results
eg.:? fs_write_fstats(F_lhstats, lhmri,' sig.mgh', 'sig');??
Date: Thu, 10 Sep 2015 13:44:36 +0000 From:
jbernal0...@yahoo.es To: freesurfer@nmr.mgh.harvard.edu Subject:
Re: [Freesurfer] A mixed effect model approach in within
subject dataset Hi Pablo I think you can use LME to analyze
your data by ordering the rows of your design matrix
appropriately. You can consider all subjects belonging to the
same family as if they were a single subject in a longitudinal
analysis. You can put in your design matrix all subjects
belonging to family1 first, then all subjects belonging to
family 2 and so on. Then the 'ni' required by lme_mass_fit_vw
is a vector with the number of subjects in each family as its
entries (ordered according to your design matrix). So the
length of the 'ni' vector is equal to the number of different
families in your data. Now you can go further and
additionally order the rows of your design matrix within each
family by age. This will allow you to test the effect of age
within family. When choosing the random effects for your
statistical model remember that a random effect can only be the
intercept term or any covariate that varies within family. For
example you can compare a model with a single random effect
for the intercept term against the same model but considering
both the intercept term and age as random effects. Hope that
helps Cheers -Jorge
De: pablo najt <pablon...@hotmail.com> Para:
"freesurfer@nmr.mgh.harvard.edu"
<freesurfer@nmr.mgh.harvard.edu> Enviado: Jueves 10 de
septiembre de 2015 8:07 Asunto: [Freesurfer] A mixed effect
model approach in within subject dataset <!----> Dear
Freesurfer users, I wanted to enquire if anyone had
successfully been able to implement Bernal's Linear Mixed
Effects (LME) Models in cross-section dataset *not
longitudinal* (please see previous thread below). ?I am willing
to perform a LME (3 groups (HC, PT and Unaffected_relatives)
and 3 covariates (sex, age, and family) with "family" variable
been a within-subject factor. LME?will allow?to control for the
non-independence of data contributed by patients and relatives
from the same families. Thanks in advance! Pablo From:
michaelnot...@hotmail.com To: freesurfer@nmr.mgh.harvard.edu
Date: Wed, 19 Feb 2014 13:10:09 +0100 Subject: [Freesurfer]
Analysis of structural data acquired from multiple sites by
using a mixed effect model approach <!----> Hi everybody, I
want to compare the surface data of 3 groups (GroupA, GroupB
and Controlls) but have the problem that they were acquired
from 4 different scanner sites. As I can see it, there are
three ways how I could tackle this problem: 1. I could use
mri_glmfit and create a qdec table / fsgd-file with 12 classes:
Class GroupA_site1; Class GroupA_site2,... And then use the
contrasts [0.25 0.25 0.25 0.25 0 0 0 0 -0.25 -0.25 -0.25
-0.25] to compare GroupA to the Controlls. My Problem with this
approach is, that the sites don't contribute the same amount of
subjects to the analysis. I'm not sure if this could be handled
by simply using a weighted contrast. Meaning, if Site1 and
Site2 had twice as many subjects than Site3 and Site4, I could
modify the contrast to [0.33 0.33 0.17 0.17 0 0 0 0 -0.33 -0.33
-0.17 -0.17]. 2. I could create dummy variables to account
for the variability between sites. In this case, I only need
to specify 3 classes (Class GroupA; Class Gro!
upB; Cla
ss Controlls) in my fsgd-file. And I use a design matrix that
has 4 dummy variables at the end, which specify to which site a
subject belongs. This approach might work, but I'm not
confident that it is the right one. 3. I could use a mixed
effect model approach and specify site as a random effect. If
I understand it correctly, the mixed effect model approach
would be the best one, as it accounts for the variability
within sites. Is that correct or are there other issues/better
approaches? I tried to implement a mixed effect model by using
Bernal's Linear Mixed Effects (LME) Models
(http://surfer.nmr.mgh.harvard.edu/fswiki/LinearMixedEffectsModels)
but run into some problems. I'm not sure if LME can only be
applied on longitudinal data or if my implementation is wrong.
I have a design matrix X that specifies the characteristics of
each subject per row as follows: Intercept?? GroupA?? GroupB??
Controll?? Age?? IQ?? Site1?? Site2?? Site3?? Site4 1? 1? 0? 0?
11.1? 99?? 0 0 1 0 1? 0? 1? 0? 11.1? 101? 0 0 1 0 1? 1? 0? 0?
11.4? 95?? 1 0 0 0 1? 0? 0? 1? 12.4? 100? 1 0 0 0 ... As I have
no repeated measures, 'ni' is just a vector with length X
containing '1's. If I do now the vertex-wise linear
mixed-effects estimation, I get the following output: >> stats
= lme_mass_fit_vw(X,[7 8 9 10],Y,ni,lhcortex); Starting
matlabpool using the 'local' profile ... connected to 8
workers. ? Starting model fitting at each location ... ?
Location 24994: Index exceeds matrix dimensions. Location
24994: Algorithm did not converge. Initial and final
likelihoods: -10000000000, -10000000000. Location 62484: Index
exceeds matrix dimensions. Location 62484: Algorithm did not
converge. Initial and final likelihoods: -10000000000,
-10000000000. ... I've checked the matrix dimensions of X, Y,
ni and lhcortex and compared them to the LME mass_univariate
example stored in ADNI_Long_50sMCI_vs_50cMCI.mat but couldn't
find any divergence. Has anybody encountered similar problems?
Is my approach of s!
pecifyin
g 'ni' as a vector of'1's even legitimate? Thanks, Michael
_______________________________________________Freesurfer
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mailing list Freesurfer@nmr.mgh.harvard.edu
https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer The
information in this e-mail is intended only for the person to
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please contact the Partners Compliance HelpLine at
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to you in error but does not contain patient information,
please contact the sender and properly dispose of the e-mail.
_______________________________________________
Freesurfer mailing list
Freesurfer@nmr.mgh.harvard.edu
https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
--
Martin Reuter, PhD
Assistant Professor of Radiology, Harvard Medical School
Assistant Professor of Neurology, Harvard Medical School
A.A.Martinos Center for Biomedical Imaging
Massachusetts General Hospital
Research Affiliate, CSAIL, MIT
Phone: +1-617-724-5652
Web : http://reuter.mit.edu
_______________________________________________Freesurfer
mailing list Freesurfer@nmr.mgh.harvard.edu
https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer The
information in this e-mail is intended only for the person to
whom it is addressed. If you believe this e-mail was sent to
you in error and the e-mail contains patient information,
please contact the Partners Compliance HelpLine at
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to you in error but does not contain patient information,
please contact the sender and properly dispose of the e-mail.
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The information in this e-mail is intended only for the
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addressed. If you believe this e-mail was sent to you in
error and the e-mail
contains patient information, please contact the Partners
Compliance HelpLine at
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information in this e-mail is intended only for the person to
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addressed. If you believe this e-mail was sent to you in error
and the e-mail
contains patient information, please contact the Partners
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to you in error
but does not contain patient information, please contact the
sender and properly
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_______________________________________________ Freesurfer
mailing list Freesurfer@nmr.mgh.harvard.edu
https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer The
information in this e-mail is intended only for the person to
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in error and the e-mail contains patient information, please
contact the Partners Compliance HelpLine at
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to you in error but does not contain patient information, please
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_______________________________________________
Freesurfer mailing list
Freesurfer@nmr.mgh.harvard.edu
https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
--
Martin Reuter, PhD
Assistant Professor of Radiology, Harvard Medical School
Assistant Professor of Neurology, Harvard Medical School
A.A.Martinos Center for Biomedical Imaging
Massachusetts General Hospital
Research Affiliate, CSAIL, MIT
Phone: +1-617-724-5652
Web : http://reuter.mit.edu
_______________________________________________ Freesurfer
mailing list Freesurfer@nmr.mgh.harvard.edu
https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer The
information in this e-mail is intended only for the person to
whom it is addressed. If you believe this e-mail was sent to you
in error and the e-mail contains patient information, please
contact the Partners Compliance HelpLine at
http://www.partners.org/complianceline . If the e-mail was sent
to you in error but does not contain patient information, please
contact the sender and properly dispose of the e-mail.
_______________________________________________
Freesurfer mailing list
Freesurfer@nmr.mgh.harvard.edu
https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
--
Martin Reuter, PhD
Assistant Professor of Radiology, Harvard Medical School
Assistant Professor of Neurology, Harvard Medical School
A.A.Martinos Center for Biomedical Imaging
Massachusetts General Hospital
Research Affiliate, CSAIL, MIT
Phone: +1-617-724-5652
Web : http://reuter.mit.edu
_______________________________________________ Freesurfer
mailing list Freesurfer@nmr.mgh.harvard.edu
https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer The
information in this e-mail is intended only for the person to
whom it is addressed. If you believe this e-mail was sent to you
in error and the e-mail contains patient information, please
contact the Partners Compliance HelpLine at
http://www.partners.org/complianceline . If the e-mail was sent
to you in error but does not contain patient information, please
contact the sender and properly dispose of the e-mail.
_______________________________________________
Freesurfer mailing list
Freesurfer@nmr.mgh.harvard.edu
https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
--
Martin Reuter, PhD
Assistant Professor of Radiology, Harvard Medical School
Assistant Professor of Neurology, Harvard Medical School
A.A.Martinos Center for Biomedical Imaging
Massachusetts General Hospital
Research Affiliate, CSAIL, MIT
Phone: +1-617-724-5652
Web : http://reuter.mit.edu
_______________________________________________Freesurfer
mailinglistfreesur...@nmr.mgh.harvard.eduhttps://mail.nmr.mgh.harvard.edu/mailman/
listinfo/freesurferThe information in this e-mail is intended
only for the person to whom it isaddressed. If you believe this
e-mail was sent to you in error and the e-mailcontains patient
information, please contact the Partners Compliance HelpLine
athttp://www.partners.org/complianceline . If the e-mail was
sent to you in errorbut does not contain patient information,
please contact the sender and properlydispose of the e-mail.
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------------------------------
Message: 4
Date: Thu, 22 Oct 2015 10:58:55 -0400 (EDT)
From: Bruce Fischl <fis...@nmr.mgh.harvard.edu>
Subject: Re: [Freesurfer] Sulcal depth units
To: Freesurfer support list <freesurfer@nmr.mgh.harvard.edu>
Message-ID:
<alpine.lrh.2.20.1510221058360.3...@gate.nmr.mgh.harvard.edu>
Content-Type: text/plain; charset=US-ASCII; format=flowed
Hi Simon
they are originally mm, but I believe we z-score normalize them
so that
the sulc file is 0 mean and unit variance.
cheers
Bruce
On Wed, 21 Oct 2015, Simon
Vandekar wrote:
> Dear Freesurfer experts,
>
> I am reading the manuscript "Cortical Surface-Based Analysis
II: Inflation, Flattening, and a Surface-Based Coordinate
System" by Fischl, Sereno, and Dale (1999) where the estimation
of sulcal depth is described on page 199, however from the
description I am still unsure of the exact units of sulcal
depth.
> Are the units for sulcal depth in mm or are they in arbitrary
units?
>
> Thanks in advance,
> Simon
> _______________________________________________
> Freesurfer mailing list
> Freesurfer@nmr.mgh.harvard.edu
> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
>
>
>
------------------------------
Message: 5
Date: Thu, 22 Oct 2015 11:05:06 -0400 (EDT)
From: Bruce Fischl <fis...@nmr.mgh.harvard.edu>
Subject: Re: [Freesurfer] mris_expand - problem reading
thickness
file?
To: Freesurfer support list <freesurfer@nmr.mgh.harvard.edu>
Message-ID:
<alpine.lrh.2.20.1510221104450.3...@gate.nmr.mgh.harvard.edu>
Content-Type: text/plain; charset="utf-8"
Hi Alex
if you upload the subject that is causing this problem I'll take
a look.
What version are you running and what OS?
cheers
Bruce
On Thu, 22 Oct 2015, Alex Puckett
wrote:
>
> Hello!
>
>
> I'm having trouble with mris_expand using the -thickness
flag.??If I expand
> by a fixed distance instead of % thickness?then mris_expand
works no problem
> -??the program seems to be hanging up when?reading the
thickness file. Has
> anyone else?experienced?this?
>
>
> The command I'm running (from the surf folder)?is:
>
> mris_expand -thickness lh.white 0.5 lh.expandWhiteThick0p5
>
> The output from this is:
> "?using distance as a % of thickness
> expanding surface lh.white by 50.0% of thickness and writing
it to
> lh.expandWhiteThick0p5
> reading thickness..."
>
> And then...nothing! Watching the CPU usage it appears that
resources are
> used for about 10 -12 minutes and then drops to 0 and just
sits there for as
> long as I'll let it (>4 days)?- no error.
>
> Also, the thickness files do not appear to be corrupt. I can
overlay the
> thickness data onto a surface no problem.?
>
> Any help would be appreciated.
>
> Cheers,
>
> Alex
>
>
---------------------------------------------------------------------
>
> FREESURFER_HOME: /usr/local/freesurfer
>
> Build stamp: freesurfer-Linux-centos6_x86_64-stable-pub-v5.3.0
>
> RedHat release: CentOS Linux release 7.1.1503 (Core)?
>
> Kernel info: Linux 3.10.0-229.1.2.el7.x86_64 x86_64
>
>
---------------------------------------------------------------------
>
>
>
>
>
>
>
>
>
> ?
------------------------------
Message: 6
Date: Thu, 22 Oct 2015 11:08:04 -0400 (EDT)
From: Bruce Fischl <fis...@nmr.mgh.harvard.edu>
Subject: Re: [Freesurfer] How to compute the measures on the
average
brain?
To: Freesurfer support list <freesurfer@nmr.mgh.harvard.edu>
Message-ID:
<alpine.lrh.2.20.1510221107490.3...@gate.nmr.mgh.harvard.edu>
Content-Type: text/plain; charset="windows-1252"
Hi Mathieu
I don't see any reason we wouldn't continue to support it
Bruce
On Thu, 22 Oct
2015, Mathieu Dubois wrote:
> Hi again,
>
> Another advantage of using qcache in my case is that the file
names are
> automatically generated and therefore standard.
>
> Is there any risk (particularly for future compatibility) in
using
> qcache? Did anyone had some problem with it?
>
> Thanks in advance,
> Mathieu
>
> Le 21/10/2015 18:07, Mathieu Dubois a ?crit :
>> Hi Doug,
>>
>> Thanks for your answer.
>>
>> If I understand correctly, the tutorial describes the use of
>> mris_preproc with a group description file. If the data has
not been
>> cached, it will compute them and stack all the results in a
big file
>> (will it write individual files?) . Of course if the data has
been
>> cached, it will only stack them (this probably result in more
disk usage
>> but that's OK).
>>
>> I don't plan to use FreeSurfer's linear model for group
analysis (my
>> goal is to use those data in machine learning algorithms) but
other
>> people at the institute I work for may be interested in that.
I think
>> it's more convenient to have one file per subject (so I can
group them
>> in a more flexible way).
>>
>> So I guess I can always run recon-all for each subject with
-qcache (I
>> have read that is safe to do so) in order to generate the
data for each
>> subject (this can easily be distributed across a cluster and
compute
>> several measures). I can then load the data for each subject
and people
>> interested into running FreeSurfer group analysis can also
use them. Is
>> it correct?
>>
>> My only concern is: will -qcache be supported in future
versions of
>> FreeSurfer? Couldn't some part of it (like the resampling on
the average
>> subject but no the smoothing) be integrated into -all?
>>
>> Mathieu
>>
>> Le 21/10/2015 16:37, Douglas Greve a ?crit :
>>> Hi Mathieu, look at the group analysis tutorial on our wiki.
Basically,
>>> you will run mris_preproc, mri_surf2surf to smooth, then
mri_glmfit to
>>> do the group analysis, then mri_glmfit-sim to do the
correction for
>>> multiple comparisons.
>>> doug
>>>
>>> On 10/21/15 10:15 AM, Mathieu Dubois wrote:
>>>> Hi,
>>>>
>>>> I'm a beginner with freesurfer so I apologize if it's a
trivial question.
>>>>
>>>> I recently run recon-all with the -all on many subjects. As
far as I can
>>>> say, all the steps worked. However, the measures on the
average brain
>>>> (output of mris_preproc and friends) were not computed.
>>>>
>>>> A colleague told me that he usually re-run recon-all with
the -qcache
>>>> flag to compute those. This seems to work but I don't
understand if it
>>>> is the recommended way to run mris_preproc and why it is
not included
>>>> with -all. Is it possible to get those measures in one call
to recon-all?
>>>>
>>>> I don't think that the issue comes from the data (e.g. that
the failing
>>>> of a step stops some branch of the pipeline) because it
seems to run
>>>> correctly with -qcache.
>>>>
>>>> I haven't found any help on -qcache and the help of
recon-all doesn't
>>>> mention mris_preproc or mri_surf2surf.
>>>>
>>>> Thanks in advance,
>>>> Mathieu
>>>> _______________________________________________
>>>> 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
>>>
>>>
>>> The information in this e-mail is intended only for the
person to whom it is
>>> addressed. If you believe this e-mail was sent to you in
error and the e-mail
>>> contains patient information, please contact the Partners
Compliance HelpLine at
>>> http://www.partners.org/complianceline . If the e-mail was
sent to you in error
>>> but does not contain patient information, please contact the
sender and properly
>>> dispose of the e-mail.
>>>
>> _______________________________________________
>> 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
>
>
>
------------------------------
Message: 7
Date: Thu, 22 Oct 2015 11:39:22 -0400 (EDT)
From: Bruce Fischl <fis...@nmr.mgh.harvard.edu>
Subject: Re: [Freesurfer] Talairach_afd error
To: Freesurfer support list <freesurfer@nmr.mgh.harvard.edu>
Message-ID:
<alpine.lrh.2.20.1510221138530.19...@gate.nmr.mgh.harvard.edu>
Content-Type: text/plain; charset="utf-8"
Hi Anna
are the talairach.xfm files generated by the two machines
similar?
Bruce
On Wed,
21 Oct 2015, Anna I. Garcia Diaz wrote:
> Dear all,
> I am having problems running the recon-all process. The error
log is attached to this e-mail.?
>
> This error appears only when I run recon-all in a machine able
to parallelize preprocesses, however, if I use the same
> reconstructed oriented image in a machine sent as a normal job
directly to the terminal, the preprocess runs without
> any errors and the output looks correct. I have tried to use
the -notal-check flag as the error log suggests, but it
> fails anyway.?
>
> Since our team is working in a longitudinal study, and the
images from the other time points have been preprocessed
> with the parallelizing machine, we are concerned that using
the non-parallelizing machine could add significant
> methodological variabilities to our studies, and we would
rather be consistent with the previous procedures.?
>
> Do you have any comments or further suggestions on how we
might be able to fix this error?
>
> Thanks in advance for your time and help
> Anna Garcia
>
>
------------------------------
Message: 8
Date: Thu, 22 Oct 2015 11:42:07 -0400
From: Douglas N Greve <gr...@nmr.mgh.harvard.edu>
Subject: Re: [Freesurfer] How to compute the measures on the
average
brain?
To: freesurfer@nmr.mgh.harvard.edu
Message-ID: <562903cf.6030...@nmr.mgh.harvard.edu>
Content-Type: text/plain; charset=windows-1252; format=flowed
No, we will continue to support it
On 10/21/2015 11:13 PM, Mathieu Dubois wrote:
> Hi again,
>
> Another advantage of using qcache in my case is that the file
names are
> automatically generated and therefore standard.
>
> Is there any risk (particularly for future compatibility) in
using
> qcache? Did anyone had some problem with it?
>
> Thanks in advance,
> Mathieu
>
> Le 21/10/2015 18:07, Mathieu Dubois a ?crit :
>> Hi Doug,
>>
>> Thanks for your answer.
>>
>> If I understand correctly, the tutorial describes the use of
>> mris_preproc with a group description file. If the data has
not been
>> cached, it will compute them and stack all the results in a
big file
>> (will it write individual files?) . Of course if the data has
been
>> cached, it will only stack them (this probably result in more
disk usage
>> but that's OK).
>>
>> I don't plan to use FreeSurfer's linear model for group
analysis (my
>> goal is to use those data in machine learning algorithms) but
other
>> people at the institute I work for may be interested in that.
I think
>> it's more convenient to have one file per subject (so I can
group them
>> in a more flexible way).
>>
>> So I guess I can always run recon-all for each subject with
-qcache (I
>> have read that is safe to do so) in order to generate the
data for each
>> subject (this can easily be distributed across a cluster and
compute
>> several measures). I can then load the data for each subject
and people
>> interested into running FreeSurfer group analysis can also
use them. Is
>> it correct?
>>
>> My only concern is: will -qcache be supported in future
versions of
>> FreeSurfer? Couldn't some part of it (like the resampling on
the average
>> subject but no the smoothing) be integrated into -all?
>>
>> Mathieu
>>
>> Le 21/10/2015 16:37, Douglas Greve a ?crit :
>>> Hi Mathieu, look at the group analysis tutorial on our wiki.
Basically,
>>> you will run mris_preproc, mri_surf2surf to smooth, then
mri_glmfit to
>>> do the group analysis, then mri_glmfit-sim to do the
correction for
>>> multiple comparisons.
>>> doug
>>>
>>> On 10/21/15 10:15 AM, Mathieu Dubois wrote:
>>>> Hi,
>>>>
>>>> I'm a beginner with freesurfer so I apologize if it's a
trivial question.
>>>>
>>>> I recently run recon-all with the -all on many subjects. As
far as I can
>>>> say, all the steps worked. However, the measures on the
average brain
>>>> (output of mris_preproc and friends) were not computed.
>>>>
>>>> A colleague told me that he usually re-run recon-all with
the -qcache
>>>> flag to compute those. This seems to work but I don't
understand if it
>>>> is the recommended way to run mris_preproc and why it is
not included
>>>> with -all. Is it possible to get those measures in one call
to recon-all?
>>>>
>>>> I don't think that the issue comes from the data (e.g. that
the failing
>>>> of a step stops some branch of the pipeline) because it
seems to run
>>>> correctly with -qcache.
>>>>
>>>> I haven't found any help on -qcache and the help of
recon-all doesn't
>>>> mention mris_preproc or mri_surf2surf.
>>>>
>>>> Thanks in advance,
>>>> Mathieu
>>>> _______________________________________________
>>>> 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
>>>
>>>
>>> The information in this e-mail is intended only for the
person to whom it is
>>> addressed. If you believe this e-mail was sent to you in
error and the e-mail
>>> contains patient information, please contact the Partners
Compliance HelpLine at
>>> http://www.partners.org/complianceline . If the e-mail was
sent to you in error
>>> but does not contain patient information, please contact the
sender and properly
>>> dispose of the e-mail.
>>>
>> _______________________________________________
>> 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
>
>
--
Douglas N. Greve, Ph.D.
MGH-NMR Center
gr...@nmr.mgh.harvard.edu
Phone Number: 617-724-2358
Fax: 617-726-7422
Bugs: surfer.nmr.mgh.harvard.edu/fswiki/BugReporting
FileDrop: https://gate.nmr.mgh.harvard.edu/filedrop2
www.nmr.mgh.harvard.edu/facility/filedrop/index.html
Outgoing:
ftp://surfer.nmr.mgh.harvard.edu/transfer/outgoing/flat/greve/
------------------------------
Message: 9
Date: Thu, 22 Oct 2015 11:48:26 -0400
From: Douglas N Greve <gr...@nmr.mgh.harvard.edu>
Subject: Re: [Freesurfer] normalization of hippocampal volume
To: freesurfer@nmr.mgh.harvard.edu
Message-ID: <5629054a.8090...@nmr.mgh.harvard.edu>
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I'm not sure what you mean by either of those options. can you
explain?
On 10/22/2015 04:18 AM, geschwind2013 wrote:
> Hi, FS Experts,
>
> I?m using version 5.3 and have performed hippo-subfields
analysis.
>
> To perform the statistics, shall I get the normalized volumes
of each hippo-subfields?
> or just to do correction for ICV is enough ?
>
> thanks..
>
> Hyon
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>
--
Douglas N. Greve, Ph.D.
MGH-NMR Center
gr...@nmr.mgh.harvard.edu
Phone Number: 617-724-2358
Fax: 617-726-7422
Bugs: surfer.nmr.mgh.harvard.edu/fswiki/BugReporting
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------------------------------
Message: 10
Date: Thu, 22 Oct 2015 11:50:10 -0400
From: Douglas N Greve <gr...@nmr.mgh.harvard.edu>
Subject: Re: [Freesurfer] per analysis with covariates
To: freesurfer@nmr.mgh.harvard.edu
Message-ID: <562905b2.6070...@nmr.mgh.harvard.edu>
Content-Type: text/plain; charset=windows-1252; format=flowed
what do you mean to control age and gender on both lGI and
thickness? If
you have thickness = f(gender,age,lGI), then you control for
gender,
age, and lGI on thickness.
On 10/20/2015 06:20 AM, marica.pad...@libero.it wrote:
>
> Hi,
>
> I am running a vertex-wise correlation analysis between local
gyrification (--
> y) and thickness (--pvr) using as covariates age and gender.
> I want to control for the effect of age and gender both the
lGI and the
> thickness values. Does the command does this? Or the effect of
the covariates
> is only taken into account for the lGI?
>
> Here my command line:
>
> mri_glmfit --glmdir left --y lh.lGI.mgh --fsgd
fsgd_control.txt --pvr lh.
> thickness.mgh --C contrast_control.txt --surface fsaverage lh
>
> And my contrast:
>
> 0 0 0 1 (first 0 for the class, second and third for the 2
covariates).
>
> Thanks,
> Marica
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>
>
--
Douglas N. Greve, Ph.D.
MGH-NMR Center
gr...@nmr.mgh.harvard.edu
Phone Number: 617-724-2358
Fax: 617-726-7422
Bugs: surfer.nmr.mgh.harvard.edu/fswiki/BugReporting
FileDrop: https://gate.nmr.mgh.harvard.edu/filedrop2
www.nmr.mgh.harvard.edu/facility/filedrop/index.html
Outgoing:
ftp://surfer.nmr.mgh.harvard.edu/transfer/outgoing/flat/greve/
------------------------------
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End of Freesurfer Digest, Vol 140, Issue 37
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