Re: [Freesurfer] Recons for Allen Brain Institute T1 images with v5.3 online

[Seán Froudist Walsh]

Fantastic, thank you!

On 30 October 2017 at 10:03, Bruce Fischl 
wrote:

> thanks Mel!
> Bruce
>
> On Mon, 30 Oct 2017, Melanie Ganz wrote:
>
>
>> Hi,
>>
>>
>>
>> So here’s the Wiki page for the human Allen brain data recons:
>> https://surfer.nmr.mgh.harvard.edu/fswiki/AllenBrainAtlas
>>
>> Right now there’s only the v5.3 recons, but the v6 recons are coming asap.
>>
>>
>>
>> Cheers,
>>
>> Melanie
>>
>>
>>
>>
>
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Re: [Freesurfer] Recon-all for Allen Brain Institute T1 image

[Seán Froudist Walsh]

Hi,

Was the following issue ever solved?
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Re: [Freesurfer] Recon-all for Allen Brain Institute T1 image

[Seán Froudist Walsh]

Hi,

Was the following issue ever solved? (sorry hit send too early!)
https://www.mail-archive.com/freesurfer@nmr.mgh.harvard.edu/msg50297.html

I tried and, like the previous two people it fails on mri_watershed.

https://www.mail-archive.com/freesurfer@nmr.mgh.harvard.edu/msg50297.html

Best wishes,

Sean




Hi Mike


it's hard to say without looking at the data. if you upload the subject dir
we will take a look

Bruce
On Thu, 24 Nov 2016, Michael Craig wrote:

Hi All,
I am trying to run recon-all on the Allen Brain Institute T1 images. It works
without any issue on all but one subject (H0351.1009).

I saw this post from a few years ago describing the exact problem I’m having,
but don’t see a solution. Has anyone figured out how to get this subject to run
in recon-all? Or is it simply a matter of there not being enough contrast
between grey and white matter? Thanks for the help!
https://mail.nmr.mgh.harvard.edu/pipermail/freesurfer/2013-July/031482.html

Best wishes,
Mike



On 19 October 2017 at 15:05, Seán Froudist Walsh <froud...@tcd.ie> wrote:

> Hi,
>
> Was the following issue ever solved?
>
>
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Re: [Freesurfer] LME model

[Seán Froudist Walsh]

Thanks a lot Jorge, that's a big help.




On 12 December 2013 23:54, jorge luis jbernal0...@yahoo.es wrote:

 Hi Sean

  An important issue in the LME model concerns the centering of the times
 of measurement. It changes the interpretation of both the mean response and
 the variance of the random effects. If tij represents time since baseline
 then the subject-specific intercept coefficient ß1+b1i  represents the
 subject-specific mean response at baseline and Var(b1i) is the
 between-subject variation in the mean response at baseline. On the other
 hand, if tij is an individual's age at the jth measurement occasion, then
 ß1+b1i might not have a useful interpretation since it represents the
 subject-specific mean response at age zero.  Another choice is to center
 the times of measurement for all subjects at some common fixed age within
 the age range of the study participants (i.e. tij-a, for some fixed value
 a). In this case ß1+b1i represents the subject-specific mean response at
 the common age a and Var(b1i ) is the between-subject variation in the
 mean response at that age.

 You should use real-valued time measurements so the first and second scan
 times on the same subject are always different.

 In your setting you only have two measurement occasions so you can only
 use a single random effect. If tij represents time since baseline then
 you can only use a random effect for the intercept term and add
 age-at-baseline as an additional time-independent covariate (its value
 doesn't change through measurement occasions).  Otherwise if tij doesn't 
 represent
 time since baseline you can test whether a single random effect for the
 time variable works better (i.e see if it produces higher optimal
 likelihood values). You can specify a random effect for the slope by
 indicating the column of the time variable:

 [stats, st] = lme_mass_fit_vw(X,3,Y,ni,Mask,[],12);

 BTW it is best to order your design matrix in the following  way (just for
 organizational purposes):
 X = [Intercept  Age(at scan)  Group Group*Age  Gender]  so the
 time-variying covariates appear first.

 You don't need to re-do the design matrix to test the effect of age within
 a group (group-specific slope different from zero) just use the appropriate
 contrast.

 Hope this helps

 -Jorge


   El Jueves 12 de diciembre de 2013 14:29, Seán Froudist Walsh 
 froud...@tcd.ie escribió:

 Dear Jorge and FreeSurfers,

 Would you mind having a look at my set-up and advising on whether it is
 correct or needs changing?

 I have participants with one or two scans, who are divided into two
 groups. I'm interested in the longitudinal effects of aging, and the
 difference in the effect of age on the two groups. Not all people were
 scanned at exactly the same age, and the interscan interval in not exactly
 the same for each person. Rather, the age at scan looks like a bimodal
 distribution around the mean 1st and 2nd timepoint.

 I believe I read on the list that you should have more timepoints than
 random effects. I guess I should then only name one random effect
 (intercept).

 At the moment I have my model set up as follows:

 X = Intercept  Group  Age(at scan)  Group*Age  Gender
 [stats, st] = lme_mass_fit_vw(X,1,Y,ni,Mask,[],12);

 CM.C = [0 0 0 1 0]

 I guess I should then run
 * lme_mass_F(stats,CM); *
  and

 *lme_mass_FDR2.*
 Here I am trying to look find the areas that develop differently between
 the two groups over the timespan we are studying. If you would be able to
 advise me as to whether I have set up the model wrong it would be greatly
 appreciated. Age in this case refers to the the age at scan time,
 regardless of whether it is the first or second scan, so many participants
 will have two distinct values in the age column.

 Also, is it possible within this set-up to test the effect of age within a
 group, or would that require  re-doing the design matrix?

 Finally, is it possible to include the by-subject random slopes for the
 effect of age? In R (lmer) it would be something like (1+age|subject).

 Best wishes y gracias,

 Seán



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[Freesurfer] To believe non-convergence?

[Seán Froudist Walsh]

Dear Jorge and FreeSurfers,

I have just been running lme_mass_fit_vw for 6 hours, and I have seen many
thousands of messages like the following:

Location 337813: Convergence at iteration 4. Initial and final
likelihoods: 607.8828, 611.1052.
Location 337812: Convergence at iteration 4. Initial and final likelihoods:
603.0934, 604.4513.
etc

There was the very occasional message saying the algorithm did not converge
at some location, a message I saw only 2 or three times (although I wasn't
looking at the matlab window for 6 hours straight, thankfully).
I thought, so far, so good.

I came in to work this morning however, and found that it had finished,
with the following ugly message waiting for me:

Algorithm did not converge at 99.9997 percent of the total number of
locations.
Total elapsed time is 357.4368 minutes.

I have two questions please.

1) Should I believe this message, even though it seems to contradict what
has been printed to the screen while  lme_mass_fit_vw was running?

2) If it really is a problem, what would you recommend I do to remedy it?
Set the convergence epsilon to 10^5?

Any help is much appreciated.

Best wishes,

Seán
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Re: [Freesurfer] To believe non-convergence?

[Seán Froudist Walsh]

Hi Jorge,

Thanks a lot for your reply. I will try out everything you have said. Yes,
you're right. I've finally got around to trying out your toolbox on my
voxel-based data (see
http://www.mail-archive.com/freesurfer@nmr.mgh.harvard.edu/msg31564.html ).

My data matrix Y is 357x2122945  (number of scans x number of voxels) and
the mask is 1x2122945. I may have misinterpreted how the mask should be
input though. In the help for lme_mass_fit_vw it says that the mask should
be 1-based. I thought this might have meant making a binary mask, with ones
in the voxels to be included, and zeros elsewhere. lme_mass_fit_vw didn't
like the format of the mask so I googled the error, and Google seemed to
suggest I should be inputting a logical-type file. So I ran logical_mask =
logical(Mask); before running lme_mass_fit_vw. There are 342934 non-zero
elements in the mask. This is the amount of points that  lme_mass_fit_vw
ran for.

Many thanks,

Seán


On 4 December 2013 18:22, jorge luis jbernal0...@yahoo.es wrote:

 *Hi Sean*

  *I'm not sure what is going on. Can you please run the simpler
 univariate analysis at some random locations? Eg. At location 1000 of your
 mask **(assuming you have to random effects for intercept and time)**:*

  *[**stats, **st]** = lme_fit_FS(X, [1 2], Y**(:, mask(1000))**, ni);*

  *If your mask is empty then all vertices/voxels are considered in the
 analysis. So you should instead run *

  *[stats, st] = lme_fit_FS(X, [1 2], Y(:, 1000), ni);*

  *This can help since you will be able to see the likelihood values
 through iterations until convergence. Also check the value of **st. **If
 the algorithm converge then **st **must be 1 otherwise it must be 0. **Also
 look out for any prompted error. You will be able to see whether there is
 any problem with your design matrix. *

  *Given that you have a location as large as 337812 it se**e**ms that you
 are not applying lme to a standard surface-based analysis. Is it a VBM
 analysis? What is the size of your **mask** and data matrix **Y**?*

  *Best*
 *-Jorge*


   El Miércoles 4 de diciembre de 2013 5:04, Seán Froudist Walsh 
 froud...@tcd.ie escribió:

 Dear Jorge and FreeSurfers,

 I have just been running lme_mass_fit_vw for 6 hours, and I have seen many
 thousands of messages like the following:

 Location 337813: Convergence at iteration 4. Initial and final
 likelihoods: 607.8828, 611.1052.
 Location 337812: Convergence at iteration 4. Initial and final
 likelihoods: 603.0934, 604.4513.
 etc

 There was the very occasional message saying the algorithm did not
 converge at some location, a message I saw only 2 or three times (although
 I wasn't looking at the matlab window for 6 hours straight, thankfully).
 I thought, so far, so good.

 I came in to work this morning however, and found that it had finished,
 with the following ugly message waiting for me:

 Algorithm did not converge at 99.9997 percent of the total number of
 locations.
 Total elapsed time is 357.4368 minutes.

 I have two questions please.

 1) Should I believe this message, even though it seems to contradict what
 has been printed to the screen while  lme_mass_fit_vw was running?

 2) If it really is a problem, what would you recommend I do to remedy it?
 Set the convergence epsilon to 10^5?

 Any help is much appreciated.

 Best wishes,

 Seán

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 e-mail
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 HelpLine at
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 properly
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Re: [Freesurfer] To believe non-convergence?

[Seán Froudist Walsh]

Muchas gracias tío, eres un crack!


On 4 December 2013 19:02, jorge luis jbernal0...@yahoo.es wrote:


 I see, the problem seems to be that the input *maskvtx *is not a binary
 mask. It's a typical Freesurfer's surface label, i.e a vector with the
 locations (1-based vertices) that are going to be included in the analysis.
 If you want to include all voxels in the analysis then just set it to the
 empty vector [] :

  *stats = lme_mass_fit_vw(X,[1 2],Y,ni,[]);*

 Otherwise enter a vector with the indices of the locations that you want
 to include in the analysis.
  *Best*
 *-Jorge*


   El Miércoles 4 de diciembre de 2013 13:43, Seán Froudist Walsh 
 froud...@tcd.ie escribió:

 Hi Jorge,

 Thanks a lot for your reply. I will try out everything you have said. Yes,
 you're right. I've finally got around to trying out your toolbox on my
 voxel-based data (see
 http://www.mail-archive.com/freesurfer@nmr.mgh.harvard.edu/msg31564.html).

 My data matrix Y is 357x2122945  (number of scans x number of voxels) and
 the mask is 1x2122945. I may have misinterpreted how the mask should be
 input though. In the help for lme_mass_fit_vw it says that the mask should
 be 1-based. I thought this might have meant making a binary mask, with ones
 in the voxels to be included, and zeros elsewhere. lme_mass_fit_vw didn't
 like the format of the mask so I googled the error, and Google seemed to
 suggest I should be inputting a logical-type file. So I ran logical_mask =
 logical(Mask); before running lme_mass_fit_vw. There are 342934 non-zero
 elements in the mask. This is the amount of points that  lme_mass_fit_vw
 ran for.

 Many thanks,

 Seán


 On 4 December 2013 18:22, jorge luis jbernal0...@yahoo.es wrote:

 *Hi Sean*

  *I'm not sure what is going on. Can you please run the simpler
 univariate analysis at some random locations? Eg. At location 1000 of your
 mask **(assuming you have to random effects for intercept and time)**:*

  *[**stats, **st]** = lme_fit_FS(X, [1 2], Y**(:, mask(1000))**, ni);*

  *If your mask is empty then all vertices/voxels are considered in the
 analysis. So you should instead run *

  *[stats, st] = lme_fit_FS(X, [1 2], Y(:, 1000), ni);*

  *This can help since you will be able to see the likelihood values
 through iterations until convergence. Also check the value of **st. **If
 the algorithm converge then **st **must be 1 otherwise it must be 0. **Also
 look out for any prompted error. You will be able to see whether there is
 any problem with your design matrix. *

  *Given that you have a location as large as 337812 it se**e**ms that you
 are not applying lme to a standard surface-based analysis. Is it a VBM
 analysis? What is the size of your **mask** and data matrix **Y**?*

  *Best*
 *-Jorge*


   El Miércoles 4 de diciembre de 2013 5:04, Seán Froudist Walsh 
 froud...@tcd.ie escribió:

 Dear Jorge and FreeSurfers,

 I have just been running lme_mass_fit_vw for 6 hours, and I have seen many
 thousands of messages like the following:

 Location 337813: Convergence at iteration 4. Initial and final
 likelihoods: 607.8828, 611.1052.
 Location 337812: Convergence at iteration 4. Initial and final
 likelihoods: 603.0934, 604.4513.
 etc

 There was the very occasional message saying the algorithm did not
 converge at some location, a message I saw only 2 or three times (although
 I wasn't looking at the matlab window for 6 hours straight, thankfully).
 I thought, so far, so good.

 I came in to work this morning however, and found that it had finished,
 with the following ugly message waiting for me:

 Algorithm did not converge at 99.9997 percent of the total number of
 locations.
 Total elapsed time is 357.4368 minutes.

 I have two questions please.

 1) Should I believe this message, even though it seems to contradict what
 has been printed to the screen while  lme_mass_fit_vw was running?

 2) If it really is a problem, what would you recommend I do to remedy it?
 Set the convergence epsilon to 10^5?

 Any help is much appreciated.

 Best wishes,

 Seán

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 e-mail
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 HelpLine at
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 properly
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Re: [Freesurfer] To believe non-convergence?

[Seán Froudist Walsh]

Just to confirm (and help anyone else who may come across this),

the following should work in Matlab to create the correct mask (from my
original binary mask):

NewMask = find(BinaryMask);

Now NewMask is a 1x342934 row vector, in which each column contains one
entry that indexes the location of the nonzero elements of my BinaryMask.
From a bit of Googling it seems that 1-based means that counting starts
from 1, which seems to be the case here.

Is there a mistake I'm not seeing?

Thanks,

Seán



On 4 December 2013 19:17, Seán Froudist Walsh froud...@tcd.ie wrote:

 Muchas gracias tío, eres un crack!


 On 4 December 2013 19:02, jorge luis jbernal0...@yahoo.es wrote:


 I see, the problem seems to be that the input *maskvtx *is not a binary
 mask. It's a typical Freesurfer's surface label, i.e a vector with the
 locations (1-based vertices) that are going to be included in the analysis.
 If you want to include all voxels in the analysis then just set it to the
 empty vector [] :

  *stats = lme_mass_fit_vw(X,[1 2],Y,ni,[]);*

 Otherwise enter a vector with the indices of the locations that you want
 to include in the analysis.
  *Best*
 *-Jorge*


   El Miércoles 4 de diciembre de 2013 13:43, Seán Froudist Walsh 
 froud...@tcd.ie escribió:

 Hi Jorge,

 Thanks a lot for your reply. I will try out everything you have said.
 Yes, you're right. I've finally got around to trying out your toolbox on my
 voxel-based data (see
 http://www.mail-archive.com/freesurfer@nmr.mgh.harvard.edu/msg31564.html).

 My data matrix Y is 357x2122945  (number of scans x number of voxels) and
 the mask is 1x2122945. I may have misinterpreted how the mask should be
 input though. In the help for lme_mass_fit_vw it says that the mask should
 be 1-based. I thought this might have meant making a binary mask, with ones
 in the voxels to be included, and zeros elsewhere. lme_mass_fit_vw didn't
 like the format of the mask so I googled the error, and Google seemed to
 suggest I should be inputting a logical-type file. So I ran logical_mask =
 logical(Mask); before running lme_mass_fit_vw. There are 342934 non-zero
 elements in the mask. This is the amount of points that  lme_mass_fit_vw
 ran for.

 Many thanks,

 Seán


 On 4 December 2013 18:22, jorge luis jbernal0...@yahoo.es wrote:

 *Hi Sean*

  *I'm not sure what is going on. Can you please run the simpler
 univariate analysis at some random locations? Eg. At location 1000 of your
 mask **(assuming you have to random effects for intercept and time)**:*

  *[**stats, **st]** = lme_fit_FS(X, [1 2], Y**(:, mask(1000))**, ni);*

  *If your mask is empty then all vertices/voxels are considered in the
 analysis. So you should instead run *

  *[stats, st] = lme_fit_FS(X, [1 2], Y(:, 1000), ni);*

  *This can help since you will be able to see the likelihood values
 through iterations until convergence. Also check the value of **st. **If
 the algorithm converge then **st **must be 1 otherwise it must be 0. **Also
 look out for any prompted error. You will be able to see whether there is
 any problem with your design matrix. *

  *Given that you have a location as large as 337812 it se**e**ms that
 you are not applying lme to a standard surface-based analysis. Is it a VBM
 analysis? What is the size of your **mask** and data matrix **Y**?*

  *Best*
 *-Jorge*


   El Miércoles 4 de diciembre de 2013 5:04, Seán Froudist Walsh 
 froud...@tcd.ie escribió:

 Dear Jorge and FreeSurfers,

 I have just been running lme_mass_fit_vw for 6 hours, and I have seen
 many thousands of messages like the following:

 Location 337813: Convergence at iteration 4. Initial and final
 likelihoods: 607.8828, 611.1052.
 Location 337812: Convergence at iteration 4. Initial and final
 likelihoods: 603.0934, 604.4513.
 etc

 There was the very occasional message saying the algorithm did not
 converge at some location, a message I saw only 2 or three times (although
 I wasn't looking at the matlab window for 6 hours straight, thankfully).
 I thought, so far, so good.

 I came in to work this morning however, and found that it had finished,
 with the following ugly message waiting for me:

 Algorithm did not converge at 99.9997 percent of the total number of
 locations.
 Total elapsed time is 357.4368 minutes.

 I have two questions please.

 1) Should I believe this message, even though it seems to contradict what
 has been printed to the screen while  lme_mass_fit_vw was running?

 2) If it really is a problem, what would you recommend I do to remedy
 it?  Set the convergence epsilon to 10^5?

 Any help is much appreciated.

 Best wishes,

 Seán

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Re: [Freesurfer] LME toolbox for VBM-style data?

[Seán Froudist Walsh]

Thanks, yeah, I'll give it a go!


On 24 September 2013 01:00, jorge luis jbernal0...@yahoo.es wrote:

 Hi Sean

  If you can load the 3D VBM data into Matlab as a matrix Y(nm x nv, nm
 total number of VBM maps and nv total number of voxels) then you can use 
 *lme_mass_fit_vw
 **to fit a voxel-wise lme model (the region-wise approach is not yet
 implemented for euclidean 3D data).
 *
 *
 *
 *You should ask to the list but I think there should be a way to stack
 all your VBM maps into a single .mgh file. For 2D surface data that can be
 accomplished with **mris_preproc** but I don't know if you can use it
 with volumetric data. Once you have your dat**a** in a single .mgh file
 you can read it into Matlab using the lme  toolbox's **fs_read_Y** **function
 as explained in the wiki **and perform your analyses**. *

  *Best*
 *-Jorge*


   --
  *De:* Seán Froudist Walsh froud...@tcd.ie
 *Para:* freesurfer@nmr.mgh.harvard.edu
 *Enviado:* Lunes 23 de septiembre de 2013 13:54
 *Asunto:* [Freesurfer] LME toolbox for VBM-style data?

 Dear FreeSurfers,

 I was wondering if anyone had tried to use the MATLAB LME toolbox that you
 kindly developed for volume based VBM-style data? Either way would you be
 able to impart some initial advice as to considerations that should be made
 etc?

 Best wishes and many thanks,

 Sean

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[Freesurfer] LME toolbox for VBM-style data?

[Seán Froudist Walsh]

Dear FreeSurfers,

I was wondering if anyone had tried to use the MATLAB LME toolbox that you
kindly developed for volume based VBM-style data? Either way would you be
able to impart some initial advice as to considerations that should be made
etc?

Best wishes and many thanks,

Sean
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[Freesurfer] Large differences in subcortical structure volume between native and FreeSurfer space

[Seán Froudist Walsh]

Dear experts,

I would like to ask for help in explaining an unexpected difference in
volume in subcortical structures between orig.mgz space and rawavg.mgz
space scans.

I used FreeSurfer (v5.1, Mac 10.7.5) on a group of subjects in order to
extract subcortical segmentation volumes. I then changed the wmparc.mgz
file to nifti format and used fsl tools to extract the hippocampus and
other structures. I then used tkregister2 to produce the orig-to-rawavg
matrix and applied this to each of the subcortical structure volumes
individually to get these segmentations in the original native T1 space. On
visual inspection this seemed to work fine, but when I compared the volumes
of the orig.mgz space subcortical structures to the rawavg.mgz space
structures there was a large difference (e.g. left hippocampus is in the
range of 5000mm3 in the orig.mgz space and in the range of 7000mm3 in
rawavg.mgz space). I wasn't expecting differences of this magnitude as I
thought the rawavg-to-orig transformation only involved reorienting and
reslicing?

I compared volumes using fsl's fslstats image -V command.

Can anybody please explain these differences and recommend a way to move
forward? Ideally I would like to use the rawavg.mgz space subcortical
structures for further analysis but I would like to know that I can trust
them first!

Many thanks in advance!

Sean
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[Freesurfer] Frontiers Special Topic: Networks Underpinning Language Repetition

[Seán Froudist Walsh]

Sent on behalf of Marcelo L. Berthier and Matthew A. Lambon Ralph

Dear colleagues

As host editors of an innovative open access journal, Frontiers in
Human Neuroscience, we are currently organizing a Special Topic
centered around “Dissecting the function of networks underpinning
language repetition”. We would be thrilled if you submitted an article
to this Special Topic. A Frontiers’ Special Topic features the latest
advances and challenges in hot research areas and attempts to unify
the best researchers. It is a collection of at least ten articles,
which may be comprised of any one of Frontiers’ article types.

The proposed structure of this Special Topic is provided below and we
would be happy to hear your suggestions.

Hosting Journal: Frontiers in Human Neuroscience

Topic Title: Dissecting the function of networks underpinning language
repetition

Host Editor(s): Marcelo L. Berthier, Matthew A. Lambon Ralph

Topic description

In the 19th century ground-breaking observations on aphasia by Broca
and Wernicke suggested that language function depends on the activity
of the cerebral cortex. At the same time, Wernicke and Lichtheim also
elaborated the first large-scale network model of language which
incorporated long-range and short-range (transcortical connections)
white matter pathways in language processing. The arcuate fasciculus
(dorsal stream) was traditionally viewed as the major language pathway
for repetition, but scientists also envisioned that white matter
tracts travelling through the insular cortex (ventral stream) and
transcortical connections may take part in language processing. Modern
cognitive neuroscience has provided tools, including neuroimaging,
which allow the in vivo examination of short- and long-distance white
matter pathways binding cortical areas essential for language.
However, the state of the art on the neural correlates of language
repetition reveals contradictory findings, with some researchers
defending the role of the dorsal and ventral streams, whereas others
argue that only cortical hubs (Sylvian parieto-temporal cortex [Spt])
are crucially relevant.

An integrative approach would conceive that the interaction between
these structures is essential for verbal repetition. For instance,
different sectors of the cerebral cortex (e.g., Spt, inferior frontal
gyrus/anterior insula) act as hubs dedicated to short-term storage of
verbal information or articulatory planning and these areas in turn
interact through forward and backward white matter projections.
Importantly, white matter pathways should not be considered mere
cable-like connections as changes in their microstructural properties
correlate with focal cortical activity during language processing
tasks.

Despite considerable progress, many outstanding questions await
response. Therefore, this topic welcomes contributors addressing the
following questions (1) how white matter pathways instantiate
dialogues between different cortical language areas; (2) what are the
specific roles of different white matter pathways in language
functions in normal and pathological conditions; (3) what are the
language consequences of discrete damage to branches of the dorsal and
ventral streams; 4) what are the consequences (e.g., release from
inhibition) of damage to the left white matter pathways in
contralateral ones and viceversa; (5) how these pathways are
reorganised after brain injury; (5) can the involvement/sparing of
white matter pathways be used in outcome prediction and treatment
response; and (5) can the microstructure of white matter pathways be
remodelled with intensive rehabilitation training or biological
approaches. It is anticipated that the articles in this Research Topic
will enhance the understanding of the neural organization of language
repetition providing clues on therapeutic interventions of brain
damaged individuals.

Submission of original data is desirable, but we also encourage
mini-reviews and perspective papers which offer provocative and
insightful interpretations of the recent literature in the field.

Abstract Submission Deadline: November 1, 2012

Researchers can participate by submitting a max. 1 page
abstract/outline of work related to the focus of the research topic,
through the Frontiers submission system, on or before the abstract
submission deadline. Authors will be notified by the host editors
whether their abstract has been accepted or rejected.

Article Submission Deadline: May 1, 2013

You may find submit abstracts and find more information by clicking on
this link: 
http://www.frontiersin.org/Human_Neuroscience/researchtopics/Dissecting_the_function_of_net/1078

We look forward to hearing from you

Sincerely yours,


Marcelo L. Berthier
Matthew A. Lambon Ralph

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Re: [Freesurfer] long_mris_slopes

[Seán Froudist Walsh]

Hi Martin and all,

I would like to ask you if by comparing tp1 thickness-spc with tp2 (and
comparing tp2 with tp3) using the base brain between tp1,2 and 3
(altogether) I have messed up methodologically.

I was expecting a rise in cortical thickness in certain areas between tp1
and tp2 followed by a greater rise between tp2 and tp3. I did not expect
however a host of other changes which were not seen when viewing spc of tp1,
2 and 3 together. Most of these effects seem to be basically mirror-effects
e.g. if there is a rise between tp1 and tp2, there is a drop in thickness in
the same area between tp2 and tp3 and vice versa. This happened in several
subjects and in variable brain regions. I would like to know if this is
because of some methodological flaw. For example, should I run the whole
longitudinal stream 2 more times (once to compare tp1 and tp2, and the
second time to compare tp2 to tp3)?

Also, when viewing the spc of tp1, tp2 and tp3 together are we just looking
at the change between timepoints 1 and 3?

Many thanks for the help,

All the best,

Seán










On 27 June 2011 11:50, Seán Froudist Walsh froud...@tcd.ie wrote:

 Hi Martin,

 That worked! Thanks a lot,

 Seán


 On 23 June 2011 18:22, Martin Reuter mreu...@nmr.mgh.harvard.edu wrote:

 Hi Sean,

 I think the --out... names need to be without the ending (mgh)
 so for example --out-avg=long23.thickness-avg

 Maybe that'll fix it.

 Best, Martin

 On Thu, 2011-06-23 at 09:12 -0700, Seán Froudist Walsh wrote:
  Dear  FreeSurfers,
 
  I am looking for a little help comparing longitudinal data. I have
  three timepoints on each patient and have been able to get individual
  spc-thickness maps using the long_mris_slopes command where my table
  included all three time points. I would however like to compare
  different timepoints with each other: tp3-tp2 and tp2-tp1.
 
  I was hoping it would be as simple as specifying a new qdec table
  including (for example) only tp3 and tp2, and giving new output names
  using the following command
 
  long_mris_slopes --qdec ./qdec/long.qdec.tableTP23.dat --meas
  thickness --hemi lh --do-avg --do-rate --do-pc1 --do-spc --do-stack
  --do-label --out-avg=long23.thickness-avg.mgh
  --out-rate=long23.thickness-rate.mgh
  --out-pc1=long23.thickness-pc1.mgh  --out-spc=long23.thickness-spc.mgh
  --out-stack=long23.thickness-stack.mgh --out-label=long23.cortex
  --time scan --qcache fsaverage
 
  but I get the following error:
 
  mris_calc:
  Sorry, but I seem to have encountered an error.
  While making backup of internal data arrays,
  it seems that some of the backups already exist.
 
  I'm not really sure what the internal data arrays are, and would
  greatly appreciate any help.
 
  Many thanks in advance and all the best,
 
  Seán
 
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Re: [Freesurfer] long_mris_slopes

[Seán Froudist Walsh]

Hi Martin,

That worked! Thanks a lot,

Seán

On 23 June 2011 18:22, Martin Reuter mreu...@nmr.mgh.harvard.edu wrote:

 Hi Sean,

 I think the --out... names need to be without the ending (mgh)
 so for example --out-avg=long23.thickness-avg

 Maybe that'll fix it.

 Best, Martin

 On Thu, 2011-06-23 at 09:12 -0700, Seán Froudist Walsh wrote:
  Dear  FreeSurfers,
 
  I am looking for a little help comparing longitudinal data. I have
  three timepoints on each patient and have been able to get individual
  spc-thickness maps using the long_mris_slopes command where my table
  included all three time points. I would however like to compare
  different timepoints with each other: tp3-tp2 and tp2-tp1.
 
  I was hoping it would be as simple as specifying a new qdec table
  including (for example) only tp3 and tp2, and giving new output names
  using the following command
 
  long_mris_slopes --qdec ./qdec/long.qdec.tableTP23.dat --meas
  thickness --hemi lh --do-avg --do-rate --do-pc1 --do-spc --do-stack
  --do-label --out-avg=long23.thickness-avg.mgh
  --out-rate=long23.thickness-rate.mgh
  --out-pc1=long23.thickness-pc1.mgh  --out-spc=long23.thickness-spc.mgh
  --out-stack=long23.thickness-stack.mgh --out-label=long23.cortex
  --time scan --qcache fsaverage
 
  but I get the following error:
 
  mris_calc:
  Sorry, but I seem to have encountered an error.
  While making backup of internal data arrays,
  it seems that some of the backups already exist.
 
  I'm not really sure what the internal data arrays are, and would
  greatly appreciate any help.
 
  Many thanks in advance and all the best,
 
  Seán
 
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[Freesurfer] long_mris_slopes

[Seán Froudist Walsh]

Dear  FreeSurfers,

I am looking for a little help comparing longitudinal data. I have three
timepoints on each patient and have been able to get individual
spc-thickness maps using the long_mris_slopes command where my table
included all three time points. I would however like to compare different
timepoints with each other: tp3-tp2 and tp2-tp1.

I was hoping it would be as simple as specifying a new qdec table including
(for example) only tp3 and tp2, and giving new output names using the
following command

long_mris_slopes --qdec ./qdec/long.qdec.tableTP23.dat --meas thickness
--hemi lh --do-avg --do-rate --do-pc1 --do-spc --do-stack --do-label
--out-avg=long23.thickness-avg.mgh --out-rate=long23.thickness-rate.mgh
--out-pc1=long23.thickness-pc1.mgh  --out-spc=long23.thickness-spc.mgh
--out-stack=long23.thickness-stack.mgh --out-label=long23.cortex  --time
scan --qcache fsaverage

but I get the following error:

mris_calc:
Sorry, but I seem to have encountered an error.
While making backup of internal data arrays,
it seems that some of the backups already exist.

I'm not really sure what the internal data arrays are, and would greatly
appreciate any help.

Many thanks in advance and all the best,

Seán
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[Freesurfer] Adding tracts to Tracula!

[Seán Froudist Walsh]

Hi FreeSurfing Gurus,

I would like to add some new tracts to the Tracula pipeline using my own
regions of interest. What would be the best way to do this?

All the best and many thanks in advance,

Seán
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Re: [Freesurfer] Adding tracts to Tracula!

[Seán Froudist Walsh]

Hi Anastasia,

Thanks for getting back to me and well done on making a very nice program.
The first tracts I would like to have are the optic radiations, but there
are others that would be nice to include: a three part arcuate fasiculus (a
la Catani et al., 2005) rather than a 2 part one, Fornix, anterior
commissure.

If I were to manually do the dissections for the 33 subjects, what would be
the most Tracula compatible way of doing it? I normally use TrackVis but I
figure making all of the file conversions might be a nightmare. Which
program was used in the original virtual dissections?

Any further suggestions? Perhaps some of these tracts are included but I've
missed them.

Sean



On 15 June 2011 08:37, Anastasia Yendiki ayend...@nmr.mgh.harvard.eduwrote:


 Hi Seán - Which tracts do you want to add? Our existing tracts have been
 labeled on 33 healthy subjects. It's certainly possible to include new
 tracts in the atlas but someone has to do the labeling on the same or a
 similar set of subjects.

 a.y


 On Wed, 15 Jun 2011, Seán Froudist Walsh wrote:

  Hi FreeSurfing Gurus,

 I would like to add some new tracts to the Tracula pipeline using my own
 regions of interest. What would be the best way to do this?

 All the best and many thanks in advance,

 Seán






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Re: [Freesurfer] Resampling from MNI 152 to MNI 305 - Problem with orientation

[Seán Froudist Walsh]

Hi Balaji,

fslswapdim (a command line program which comes as part of fsl) should solve
your orientation problems.
If you have fsl installed (which you should do!) then typing
fslswapdim input_volume_name -x output_volume_name
into the terminal should swap RAS to LAS and vice versa.

Or you can just type in
fslswapdim into the terminal to get help.

Best of luck!

Sean
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[Freesurfer] Frontal lobes excluded

[Seán Froudist Walsh]

Dear FreeSurfer gurus,

I have T1 scans of a patient at three different time-points (one run at each
time-point). The cortical reconstructions of the first and third time-points
seem to have worked reasonably well, but the reconstruction of the second
time-point was a disaster. A massive part of the frontal lobe (bilaterally)
is cut out from the wm and gm  surfaces. I tried fixing this with wm edits,
but that exited with errors, then I tried to add control points to the new
wm.mgz and recon-all again exited with errors. Is there any possibility of
saving this scan? Would I be able to upload some screenshots to help you see
what is going on?

Many thanks in advance,

Sean
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Re: [Freesurfer] Mac intel - OSX tiger installation

[Seán Froudist Walsh]

Hi Nick,

Thanks a lot for the reply. However the link for the

freesurfer-Darwin-tiger-i686-stable-pub-v4.5.0-full.dmg
http://www.freesurfer.net/pub/dist/freesurfer/4.5.0/freesurfer-Darwin-tiger-i686-stable-pub-v4.5.0-full.dmg

download doesn't work for me. I've tried several times since
yesterday. Also, are cortical surface results comparable between
versions 5.0.0 and 4.5.0? I imagine not.

All the best,

Seán


On 12 March 2011 06:19, Nick Schmansky ni...@nmr.mgh.harvard.edu wrote:

 the most recent tiger intel build is for v4.5, and is available here:

 http://www.freesurfer.net/pub/dist/freesurfer/4.5.0/

 n.


 On Fri, 2011-03-11 at 14:13 +0100, Seán Froudist Walsh wrote:
 
  Hi Freesurfer group,
 
  I would like to know if it is possible for me to download FreeSurfer
  on my Intel based Mac with OSX Tiger (10.4.11)? I have been unable to
  update to Leopard/Snow Leopard due to a problem with the super-drive
  so that is not currently an option for me.
 
  Many thanks in advance
 
  All the best,
 
  Seán
 
 
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[Freesurfer] Mac intel - OSX tiger installation

[Seán Froudist Walsh]

Hi Freesurfer group,

I would like to know if it is possible for me to download FreeSurfer on my
Intel based Mac with OSX Tiger (10.4.11)? I have been unable to update to
Leopard/Snow Leopard due to a problem with the super-drive so that is not
currently an option for me.

Many thanks in advance

All the best,

Seán
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