Hi,After wrestling with this a bit, I think I get the idea (finally!). Just to confirm:
1- set a primary threshold in the mri_glmfit command, e.g., --sim perm 5000 1.3 will run 5000 permutations with the primary cluster forming threshold set at .05.
2- Look up the cluster summary table and identify clusters with CWP < .05 (if alpha=.04). These CWP values are corrected based on the maximal cluster size statistics generated during the permutations.
3 - Visualize clusters in tksurfer - one way is to load the --cwsig file, where each cluster is assigned a corrected p-value. Seeting the overlay display to min=1.3 will then show you all clusters that are significant at the clusterwise corrected .05 level.
Am I right so far?
Couple more questions regarding smoothing:
1 - If I input data obtaioned from qdec into mri_glmfit just to run the permutations, do I need to specify the --fwhm? Does this correspond to the one used for the analysis (i.e., the one specific in qdec), or the residual fwhm obtained from the y.fsgd file? (Note, I see that you need to specify the residual fwhm for the monte-carlo sims, by I wanted to check whether a fwhm is required for the --sim perm option)
2 - does the --var-fwhm option corresond to the variance smoothing described in the Nichols and Holmes Hum Brain Mapp paper? If so, it seems this would be useful for --sim perm. Does anyone have any recommendations for what a good value would be? Should it be the same fwhm as that used to smooth the thickness values; i.e., is I specify 15mm in qdec, should I use 15mm for --var-fwhm?
Thanks again for your help,
Alex
On 11/12/2007, at 12:49 PM, Doug Greve wrote:
Alex Fornito wrote: Sorry Doug, I'm a bit thick , so pls let me clarify :)
The threshold set in mri_glmfit with --sim perm 5000 1.3 corresponds to the primary (1) vertex-wise threshold; (2) the cluster-based threshold; or (3) both?
Just #1, the vertex-wise. The simulation is done to figure out #2.
I'm a little confused, as in you previous response you stated:
Thus, if I set --sim perm 5000 1.3, vertices significant at p<.05 will first be identified, and those that are connected will be assigned to clusters.
Correct so far.
But then later said the vertex-wise values are uncorrected. In that case, and based on your response re: data contained in the .csd file, I assume that the '1.3' threshold corresponds to that determined by the permutation distribution for the group difference statistic at each vertex, rather than the maxima across all vertices, which corrects for multiple comparisons as detailed in the Nichols & Holmes (2001) paper. This is why the vertex-wise values are uncorrected?
The 1.3 is what you determined and specified on the command-line. The maxima across all vertices is stored in the CSD and can in principle be used to compute a vertex-wise threshold (instead of using a cluster-wise correction). In this case, the 1.3 you spec on the cmd line would be meaningless.
If the above is the case, than how and when is the cluster-wise threshold selected? I noted that you said any cluster-wise threshold can be selected, by mri_surfcluster does not allow me to set a --thmin different to that passed to mri_glmfit when using a .csd file.
By default, mri_surfcluster will print out all clusters along with their cluster-wise p-value. You then look at the list and only report the ones that meet the threshold that you feel comfortable with.
Thanks again.
On 11/12/2007, at 12:03 PM, Doug Greve wrote:
Alex Fornito wrote: Ok, so sounds like that is not possible - thanks for clarifying.
I have been playing with the --sim perm option and was wondering how cluster-level inferences are determined. From what I understand, a primary (voxel-level) threshold generally needs to be specified to form clusters, prior to some statistics assessing a particular property of the suprathreshold clusters (e.g., size or mass) being tested again its null distribution.
I know that the --sim perm requires specification of a threshold, but I am presuming that this if for cluster-level inference. mri_surfcluster obtains threshold information from the .csd file with no further user input, making me wonder how the 'primary', vertex-level threshold for determining supra-threshold clusters is set. I see two possible options:
1 - You are implementing the Threshold-Free Cluster Enhancement (TFCE) technique described on the Randomize website.
Never heard of it.
2 - The primary, vertex-wise threshold is determined by the permutation distribution of the maximal statistic for the difference between two groups (in a 2-group comparison). All connected suprathreshold vertices are then assigned to different clusters, and the size of these clusters is then tested against the permutation distribution for cluster size.
Thus, if I set --sim perm 5000 1.3, vertices significant at p<.05 will first be identified, and those that are connected will be assigned to clusters.
Correct so far.
Clusters will then be determined significant if p<05, as evaluated against the permutation distribution for the maximal cluster size statistic.
You can choose any cluster-wise sig threshold you want (ie, it is distinct from the vertex-wise threshold).
Is this what the MaxStat and MaxClusterSize columns in the .csd file correspond to?
I've programmed mri_glmfit to keep track of both the max cluster size and the maximum statistic. The latter can be used to do a vertex-wise correction for muliple comparisons instead of a cluster-wise. This avoids having to set an arbitrary vertex-wise threshold needed when clustering. I'm still missing a piece of code that will apply the CSD in this way.
If this is the case, is using 2 corrected thresholds (for primary, vertex-wise, and then cluster-level inferences) seems to be relatively conservative? I have noted that in many fMR experiments, it seems customary to use an uncorrected primary threshold based on signal intensity, coupled with an extent threshold to form clusters, prior to making FWE-corrected cluster-level inferences.
The vertex-wise theshold is not corrected in any way.
doug
Appreciate help on this and sorry for all the questions - much of this is new to me!!
Alex
On 07/12/2007, at 5:59 AM, Doug Greve wrote:
FDR assumes that the collection of values has both positives and negatives. It assumes that the pvalues of the negatives are uniformly distributed between 0 and 1, and this model is used to estimate the total number of positives (both true and false). When you cluster, you are setting all voxels below a certain threshold to 0, thus invalidating the assumption about the distribution of the negatives.
doug
Alexander Fornito wrote: Sorry, can I ask why the clustering step would invalidate FDR?
>From my understanding, FDR allows you set a limit on the number of false
positive in a family of contrasts reaching significance at a nominal
threshold. I would like to this nominal threshold using cluster stats
(e.g., p<.05, cluster extent 30mm), and then use FDR to correct for
comparisons at vertices exceeding this initial threshold, therefore
avoiding running FDR on each vertex of the surface. Is this not possible?
That does not sound right, I think that the first clustering step will
probably invalidate FDR. You can use FDR to set the voxel-wise threshold
when you run mri_surfcluster, but I'm not sure you can do it afterwards.
Alex Fornito wrote:
I retract the last email - it seems like I was entering the wrong
sig.mgh file as input. Sorry for the confusion!!!
On a separate issue, I would like to check that I have the following
correct:
I have extracted a cluster image using mri_surfcluster withouth
running simulations. Say, for e.g., I use thmin 2 and minarea 30. I
load the resulting output.mgh file into tksurfer.
I would then like to perform FDR correction on the resulting clusters.
I'm guessing that pressing the FDR button in the Overlay config menu
will do the trick, since (from what I understand) the output.mgh file
I have loaded assigns a zero to all vertices not in a cluster. I
figure that this will therefore result in an FDR correction that
accounts only for the vertices within my clusters.
However, I'm uncertain how the 'only marked' checkbox fits in. If I
tick it, I get an error calculating the FDR. I'm guessing this option
is relevant if you combined a stat map with a label file.
Am I on the right track?
Thanks again,
Alex
On 05/12/2007, at 9:52 AM, Alex Fornito wrote:
<Pic.png>
Thanks for all your help guys, but I am still having trouble (!).
This time I've tried a different dataset, again just a simple 2 group
comaprison with no covariates.
Running this in qdec, and visualizing with a low threshold (min=1.3),
I see a whole bunch of clusters (see attached). However, when I run
mri_surfcluster, I only get one whole brain cluster again (see
below). This time I smoothed with 15 mm in qdec, although I get the
same if I smooth with 10mm. I have kept the thresholds low on
purpose, because I expect that something should come out?? I did not
run simulations in this instance, to cut processing time.
mri_surfcluster --in qdec/MF_lh_15mm/contrasts.sig.mgh --no-adjust
--subject fsaverage/ --hemi l h --thmin 1.3 --minarea 15 --sum
TestClusters
thsign = abs, id = 0
version $Id: mri_surfcluster.c,v 1.39 2007/07/31 00:34:19 greve Exp $
hemi = lh
srcid = qdec/MF_lh_15mm/contrasts.sig.mgh paint
srcsubjid = fsaverage/
srcsurf = white
srcframe = 0
thsign = abs
thmin = 1.3
thmax = -1
fdr = -1
minarea = 15
xfmfile = talairach.xfm
nth = -1
sumfile = TestClusters
subjectsdir = /data/kang/work/struct/alex/freesurfer/subjects_cann
FixMNI = 1
------------- XFM matrix (RAS2RAS) ---------------
/data/kang/work/struct/alex/freesurfer/subjects_cann/fsaverage//mri/transforms/t
alairach.xfm
1.000 0.000 0.000 0.000;
0.000 1.000 0.000 0.000;
0.000 0.000 1.000 0.000;
0.000 0.000 0.000 1.000;
----------------------------------------------------
Reading source surface
/data/kang/work/struct/alex/freesurfer/subjects_cann/fsav
erage//surf/lh.white
reading group avg surface area 822 cm^2 from file
Reading in average area
/data/kang/work/struct/alex/freesurfer/subjects_cann/fsa
verage//surf/lh.white.avg.area.mgh
Done reading source surface
Computing metric properties
Loading source values
number of voxels in search space = 163842
Done loading source values (nvtxs = 163842)
overall max = 1e+10 at vertex 26
overall min = 1.75775 at vertex 126983
surface nvertices 163842
surface area 65416.985991
surface area 65416.985976
NOT Adjusting threshold for 1-tailed test
Searching for Clusters ...
thmin=1.300000 (1.300000), thmax=-1.000000 (-1), thsignid=0,
minarea=15.000000
Found 1 clusters
Max cluster size 103339.460938
INFO: fixing MNI talairach coordinates
On 05/12/2007, at 4:19 AM, Doug Greve wrote:
There's really no such thing as an opt kernel size. The best size
depends on the underlying signal and can be space variant.
doug
Alex Fornito wrote:
Yes, I selected 25 mm on qdec, based on the Lerch paper suggesting
this was a generally 'optimal' kernel size. The 34.309.. was the
residual output to y.fsgd.
Do you recommend a smaller kernel?
On 04/12/2007, at 5:41 PM, Pratap Kunwar wrote:
I think, one reason for getting only one big cluster is because
your fwhm
value is very high. By the way how did you get fwhm 34.309616??,
was it
produced by selecting fwhm 25 (max on Qdec)on Qdec?
Did you try fwhm 10 or 15?
Thanks for your help Pratap.
I've actually been trying to follow the tutorial and was running
simulations initially, but when I tried to re-trace my steps I
ended
omitted them because I forgot they were necessary for
mri_surfcluster.
Either way, the results are the same- I still get one whole surface
cluster as output even after running simulations. In this case, I
re-
ran it copying your commands, except I used perm because I have low
numbers and no covariates. I also ran 1000 permutations, to get a
quick initial result for testing. My commands and output are below.
I would appreciate further help on this, as I'm not sure where I'm
going wrong!
also, I noticed that after your mri_glmfit command, you added --i
divided into 5000 each. Sorry, but I'm not sure what you meant by
that.
---> i had split simulation (10,000 iterations)into multiple runs
csd1*
(5000 iterations) and csd2* (5000 iterations) since mc-z
relatively takes
long time comparing to permutation.
More on,
https://surfer.nmr.mgh.harvard.edu/fswiki/FsTutorial_2fGroupAnalysis?action=highlight&value=fsgd
<https://surfer.nmr.mgh.harvard.edu/fswiki/FsTutorial_2fGroupAnalysis?action=highlight&value=fsgd>
mri_glmfit --y qdec/MF_group_rh/y.mgh --fsgd qdec/MF_group_rh/
qdec.fsgd doss --surf fsaverage rh --fwhm 34.309616 --C qdec/
MF_group_rh/contrasts/Diff-1-2-Intercept.mat --sim perm 1000 2
stats/
newperm_rh/newperm_rh --glmdir stats/newperm_rh/
gdfReadHeader: reading qdec/MF_group_rh/qdec.fsgd
INFO: demeaning continous variables
Continuous Variable Means (all subjects)
Class Means of each Continuous Variable
1 group1
2 group2
INFO: gd2mtx_method is doss
Reading source surface /data/kang/work/struct/alex/freesurfer/
subjects_cann/fsaverage/surf/rh.white
reading group avg surface area 822 cm^2 from file
Reading in average area /data/kang/work/struct/alex/freesurfer/
subjects_cann/fsaverage/surf/rh.white.avg.area.mgh
simbase stats/newperm_rh/newperm_rh
Number of vertices 163842
Number of faces 327680
Total area 65020.765625
AvgVtxArea 0.396850
AvgVtxDist 0.717994
StdVtxDist 0.193566
reading group avg surface area 822 cm^2 from file
Reading in average area /data/kang/work/struct/alex/freesurfer/
subjects_cann/fsaverage/surf/rh.white.avg.area.mgh
INFO: fwhm2niters: Fixing group surface area
Surface smoothing by fwhm=34.309616, niters=866.000000
$Id: mri_glmfit.c,v 1.138.2.1 2007/09/12 15:38:19 nicks Exp $
cwd /data/kang/work/struct/alex/freesurfer/subjects_cann
cmdline mri_glmfit --y qdec/MF_group_rh/y.mgh --fsgd
qdec/MF_group_rh/
qdec.fsgd doss --surf fsaverage rh --fwhm 34.309616 --C qdec/
MF_group_rh/contrasts/Diff-1-2-Intercept.mat --sim perm 1000 2
stats/
newperm_rh/newperm_rh --glmdir stats/newperm_rh/
sysname Linux
hostname kang
machine i686
user alex
FixVertexAreaFlag = 1
UseMaskWithSmoothing 1
fwhm 34.309616
niters 866.000000
OneSampleGroupMean 0
y /data/kang/work/struct/alex/freesurfer/subjects_cann/qdec/
MF_group_rh/y.mgh
logyflag 0
usedti 0
FSGD qdec/MF_group_rh/qdec.fsgd
glmdir stats/newperm_rh/
DoFFx 0
Loading y from
/data/kang/work/struct/alex/freesurfer/subjects_cann/
qdec/MF_group_rh/y.mgh
Matrix condition is 1
search space = 82167.6
Smoothing input by fwhm 34.309616
Smoothing done, nsteps = 866, tsec = 1236.17
... done
DOF = 28
thresh = 2, threshadj = 2
Starting simulation sim over 1000 trials
1/1000 t=0 ------------------------------------------------
Starting fit and test
10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Diff-1-2-Intercept 0 nc=3 maxcsize=1910.81 sigmax=-3.00831
Fmax=13.551
2/1000 t=0.0572833 ------------------------------------------------
Starting fit and test
10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Diff-1-2-Intercept 1 nc=0 maxcsize=0 sigmax=1.36036 Fmax=4.46612
3/1000 t=0.0994333 ------------------------------------------------
... and so on... then
mri_surfcluster --src qdec/MF_group_lh/contrasts.sig.mgh --csd
stats/
newperm_lh/newperm_lh-Diff-1-2-Intercept.csd --sum
stats/newperm_lh/
newperm_lh --ocp stats/newperm_lh/newperm_lh.mgh
thsign = abs, id = 0
version $Id: mri_surfcluster.c,v 1.39 2007/07/31 00:34:19 greve Exp
$
hemi = rh
srcid = qdec/MF_group_lh/contrasts.sig.mgh paint
srcsubjid = fsaverage
srcsurf = white
srcframe = 0
thsign = abs
thmin = 2
thmax = -1
fdr = -1
minarea = 0
xfmfile = talairach.xfm
nth = -1
sumfile = stats/newperm_lh/newperm_lh
subjectsdir =
/data/kang/work/struct/alex/freesurfer/subjects_cann
FixMNI = 1
------------- XFM matrix (RAS2RAS) ---------------
/data/kang/work/struct/alex/freesurfer/subjects_cann/fsaverage/mri/
transforms/talairach.xfm
1.000 0.000 0.000 0.000;
0.000 1.000 0.000 0.000;
0.000 0.000 1.000 0.000;
0.000 0.000 0.000 1.000;
----------------------------------------------------
Reading source surface /data/kang/work/struct/alex/freesurfer/
subjects_cann/fsaverage/surf/rh.white
reading group avg surface area 822 cm^2 from file
Reading in average area /data/kang/work/struct/alex/freesurfer/
subjects_cann/fsaverage/surf/rh.white.avg.area.mgh
Done reading source surface
Computing metric properties
Loading source values
number of voxels in search space = 163842
Done loading source values (nvtxs = 163842)
overall max = 43.1907 at vertex 101931
overall min = 7.66111 at vertex 28089
surface nvertices 163842
surface area 65020.838384
surface area 65020.838382
NOT Adjusting threshold for 1-tailed test
Searching for Clusters ...
thmin=2.000000 (2.000000), thmax=-1.000000 (-1), thsignid=0,
minarea=0.000000
Found 1 clusters
Max cluster size 103836.125000
INFO: fixing MNI talairach coordinates
Saving cluster pval stats/newperm_lh/newperm_lh.mgh
On 04/12/2007, at 11:30 AM, Pratap Kunwar wrote:
Alex,
You have to do simulations using mri_glmfit before youdo
mri_surfcluster,
[more info in this link at
https://surfer.nmr.mgh.harvard.edu/fswiki/
FsTutorial_2fGroupAnalysis?action=highlight&value=fsgd
go down to [4.0 Using mri_glmfit to correct for multiple
comparisons: ]
USAGE: ./mri_glmfit
--glmdir dir : save outputs to dir
--y inputfile **y.mgh
--fsgd FSGDF <gd2mtx> : freesurfer descriptor file **qdec.fsgd
--C contrast1.mat <--C contrast2.mat ...>
--fwhm fwhm : smooth input by fwhm ** your smoothing value from
"
fwhm.dat"
--surf subject hemi <surfname> : needed for some flags (uses
white by
default) **lh or rh
--sim nulltype nsim thresh csdbasename : simulation perm, mc-
full, mc-z
**mc-z (i used) is faster than mc-full, minimum threshold value
( i.e.
1.3 for 0.05),
My command was more like this,
mri_glmfit --y y.mgh --fsgd qdec.fsgd doss --surf fsaverage rh --
fwhm < ??
--C contrast/contrastname.mat --sim mc-z 5000 1.3 f11/csd1 --
glmdir f11
mri_glmfit --y y.mgh --fsgd qdec.fsgd doss --surf fsaverage rh
--fwhm
14.504073 --C contrast/contrastname.mat --sim mc-z 5000 1.3
f11/csd2
--glmdir f11
--i divided into 5000 each
from above mri_glmfit, i got two files starting with csd1* .csd
and
csd2*.csd.
Next one is
mri_surfcluster,
mri_surfcluster --src contrastname/sig.mgh --csd csd1* .csd --csd
csd2*
..csd --sum <text summary file --sum <*.sum> --ocp <*.mgh>
the output file *.sum can be opened in text editor and *.mgh can
be seen
using tksurfer. Check the link above link for more details (i just
followed that link when i did last month).
let me know if you get into more problems.
pratap
On 11/28/2007 07:43 PM, Alex Fornito wrote:
Hi,
I have run qdec for a simple contrast comparing thickness
across
the
cortical surface between a patient and control group. Not much
survives vertex-wise FDR correction, and I would like to try
cluster-based thresholding. I would like to make sure I
understand the
inputs to the command. Am I correct on the following?
--in = the signifcance values (i.e., contrast_name.sig.mgh
file)
--thmin = the vertexwise threshold for determining clusters,
where 2
corresponds to p=.01
--minarea = the cluster extent threshold - Am I correct in
assuming
this should not be smaller than the smoothing kernel?
When I run the command below, I get the following output.
Only one
(whole hemi) cluster is identified. I'm not sure if its a
problem in
my command line, or with my data. Also, I seem to have the
--cwsig
flag wrong, but can't figure out the error (appending .w
or .label to
the end of the output filename does not change the error).
I greatly appreciate your help.
mri_surfcluster --in qdec/MF_group_lh/contrasts.sig.mgh
--subject
fsaverage --hemi lh --surf white --annot aparc --sign abs
--thmin 2
--minarea 25 --sum stats/qdec_run/cluster/summary.txt --o
stats/qdec_run/cluster/cluster_output --cwsig
stats/qdec_run/cluster/cwsig --olab
stats/qdec_run/cluster/MF_group_lh_thk
thsign = abs, id = 0
version $Id: mri_surfcluster.c,v 1.39 2007/07/31 00:34:19 greve
Exp $
hemi = lh
srcid = qdec/MF_group_lh/contrasts.sig.mgh paint
srcsubjid = fsaverage
srcsurf = white
srcframe = 0
thsign = abs
thmin = 2
thmax = -1
fdr = -1
minarea = 25
xfmfile = talairach.xfm
nth = -1
outid = stats/qdec_run/cluster/cluster_output paint
sumfile = stats/run2/cluster/summary.txt
subjectsdir = /data/kang/work/struct/alex/freesurfer/
subjects_cann
FixMNI = 1
------------- XFM matrix (RAS2RAS) ---------------
/data/kang/work/struct/alex/freesurfer/subjects_cann/fsaverage/
mri/transforms/talairach.xfm
1.000 0.000 0.000 0.000;
0.000 1.000 0.000 0.000;
0.000 0.000 1.000 0.000;
0.000 0.000 0.000 1.000;
----------------------------------------------------
Reading source surface
/data/kang/work/struct/alex/freesurfer/subjects_cann/fsaverage/
surf/lh.white
reading group avg surface area 822 cm^2 from file
Reading in average area
/data/kang/work/struct/alex/freesurfer/subjects_cann/fsaverage/
surf/lh.white.avg.area.mgh
Done reading source surface
Reading annotation
/data/kang/work/struct/alex/freesurfer/subjects_cann/fsaverage/
label/lh.aparc.annot
reading colortable from annotation file...
colortable with 35 entries read (originally
/space/amaebi/26/users/buckner_cortical_atlas/scripts/
colortable_final.txt)
Computing metric properties
Loading source values
number of voxels in search space = 163842
Done loading source values (nvtxs = 163842)
overall max = 43.1907 at vertex 101931
overall min = 7.66111 at vertex 28089
surface nvertices 163842
surface area 65416.985991
surface area 65416.985976
NOT Adjusting threshold for 1-tailed test
Searching for Clusters ...
thmin=2.000000 (2.000000), thmax=-1.000000 (-1), thsignid=0,
minarea=25.000000
Found 1 clusters
Max cluster size 103339.460938
INFO: fixing MNI talairach coordinates
Saving thresholded output to
stats/qdec_run/cluster/cluster_output
avg = 35.029, stdev = 4.669, min = 7.661, max = 43.191
Saving cluster pval stats/qdec_run/cluster/cwsig
unknown file type for file (stats/qdec_run/cluster/cwsig)
LabelWrite: saving to stats/qdec_run/cluster/
MF_group_lh_thk-0001.label
Alex Fornito
JN Peters Research Fellow
Melbourne Neuropsychiatry Centre
Department of Psychiatry
The University of Melbourne
Postal address:
Melbourne Neuropsychiatry Centre
National Neuroscience Facility
Levels 2 & 3, 161 Barry St
Carlton South Vic 3053 Australia
Ph: +61 3 8344 1861
Fax: +61 3 9348 0469
fornitoa@unimelb.edu.au <mailto:fornitoa@unimelb.edu.au>
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Alex Fornito
JN Peters Research Fellow
Melbourne Neuropsychiatry Centre
Department of Psychiatry
The University of Melbourne
Postal address:
Melbourne Neuropsychiatry Centre
National Neuroscience Facility
Levels 2 & 3, 161 Barry St
Carlton South Vic 3053 Australia
Ph: +61 3 8344 1861
Fax: +61 3 9348 0469
fornitoa@unimelb.edu.au <mailto:fornitoa@unimelb.edu.au>
Alex Fornito
JN Peters Research Fellow
Melbourne Neuropsychiatry Centre
Department of Psychiatry
The University of Melbourne
Postal address:
Melbourne Neuropsychiatry Centre
National Neuroscience Facility
Levels 2 & 3, 161 Barry St
Carlton South Vic 3053 Australia
Ph: +61 3 8344 1861
Fax: +61 3 9348 0469
fornitoa@unimelb.edu.au <mailto:fornitoa@unimelb.edu.au>
--
Douglas N. Greve, Ph.D.
MGH-NMR Center
greve@nmr.mgh.harvard.edu
Phone Number: 617-724-2358
Fax: 617-726-7422
In order to help us help you, please follow the steps in:
surfer.nmr.mgh.harvard.edu/fswiki/BugReporting
Alex Fornito
JN Peters Research Fellow
Melbourne Neuropsychiatry Centre
Department of Psychiatry
The University of Melbourne
Postal address:
Melbourne Neuropsychiatry Centre
National Neuroscience Facility
Levels 2 & 3, 161 Barry St
Carlton South Vic 3053 Australia
Ph: +61 3 8344 1861
Fax: +61 3 9348 0469
fornitoa@unimelb.edu.au <mailto:fornitoa@unimelb.edu.au>
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Alex Fornito
JN Peters Research Fellow
Melbourne Neuropsychiatry Centre
Department of Psychiatry
The University of Melbourne
Postal address:
Melbourne Neuropsychiatry Centre
National Neuroscience Facility
Levels 2 & 3, 161 Barry St
Carlton South Vic 3053 Australia
Ph: +61 3 8344 1861
Fax: +61 3 9348 0469
fornitoa@unimelb.edu.au <mailto:fornitoa@unimelb.edu.au>
--
Douglas N. Greve, Ph.D.
MGH-NMR Center
greve@nmr.mgh.harvard.edu
Phone Number: 617-724-2358
Fax: 617-726-7422
In order to help us help you, please follow the steps in:
surfer.nmr.mgh.harvard.edu/fswiki/BugReporting
--
Douglas N. Greve, Ph.D.
MGH-NMR Center
greve@nmr.mgh.harvard.edu
Phone Number: 617-724-2358
Fax: 617-726-7422
In order to help us help you, please follow the steps in:
surfer.nmr.mgh.harvard.edu/fswiki/BugReporting
_______________________________________________
Freesurfer mailing list
Alex Fornito
JN Peters Research Fellow
Melbourne Neuropsychiatry Centre
Department of Psychiatry
The University of Melbourne
Postal address:
Melbourne Neuropsychiatry Centre
National Neuroscience Facility
Levels 2 & 3, 161 Barry St
Carlton South Vic 3053 Australia
Ph: +61 3 8344 1861
Fax: +61 3 9348 0469
--
Douglas N. Greve, Ph.D.
MGH-NMR Center
greve@nmr.mgh.harvard.edu
Phone Number: 617-724-2358
Fax: 617-726-7422
In order to help us help you, please follow the steps in:
surfer.nmr.mgh.harvard.edu/fswiki/BugReporting
Alex Fornito
JN Peters Research Fellow
Melbourne Neuropsychiatry Centre
Department of Psychiatry
The University of Melbourne
Postal address:
Melbourne Neuropsychiatry Centre
National Neuroscience Facility
Levels 2 & 3, 161 Barry St
Carlton South Vic 3053 Australia
Ph: +61 3 8344 1861
Fax: +61 3 9348 0469
--
Douglas N. Greve, Ph.D.
MGH-NMR Center
greve@nmr.mgh.harvard.edu
Phone Number: 617-724-2358
Fax: 617-726-7422
In order to help us help you, please follow the steps in:
surfer.nmr.mgh.harvard.edu/fswiki/BugReporting
_______________________________________________
Freesurfer mailing list
Alex Fornito
JN Peters Research Fellow
Melbourne Neuropsychiatry Centre
Department of Psychiatry
The University of Melbourne
Postal address:
Melbourne Neuropsychiatry Centre
National Neuroscience Facility
Levels 2 & 3, 161 Barry St
Carlton South Vic 3053 Australia
Ph: +61 3 8344 1861
Fax: +61 3 9348 0469