date:20180604

Re: [HCP-Users] -cifti-reduce -exclude-outliers

2018-06-04 Thread Timothy Coalson

It is not iterative, it calculates the stdev on the full data and uses that.

Tim


On Mon, Jun 4, 2018 at 4:19 PM, Harms, Michael  wrote:

>
>
> Hi Tim,
>
> I was wondering about the details of the -cifti-reduce -exclude-outliers
> operation.  In particular, is it “iterative”? i.e., does it recompute the
> std without the outliers from the previous pass(es) and iterate until no
> further new outliers are identified?
>
>
>
> Thanks,
>
> -MH
>
>
>
> --
>
> Michael Harms, Ph.D.
>
> ---
>
> Associate Professor of Psychiatry
>
> Washington University School of Medicine
>
> Department of Psychiatry, Box 8134
>
> 660 South Euclid Ave
> .
> Tel: 314-747-6173
>
> St. Louis, MO  63110  Email: mha...@wustl.edu
>
>
> --
>
> The materials in this message are private and may contain Protected
> Healthcare Information or other information of a sensitive nature. If you
> are not the intended recipient, be advised that any unauthorized use,
> disclosure, copying or the taking of any action in reliance on the contents
> of this information is strictly prohibited. If you have received this email
> in error, please immediately notify the sender via telephone or return mail.
>
> ___
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> http://lists.humanconnectome.org/mailman/listinfo/hcp-users
>

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[HCP-Users] -cifti-reduce -exclude-outliers

2018-06-04 Thread Harms, Michael


Hi Tim,
I was wondering about the details of the -cifti-reduce -exclude-outliers 
operation.  In particular, is it “iterative”? i.e., does it recompute the std 
without the outliers from the previous pass(es) and iterate until no further 
new outliers are identified?

Thanks,
-MH

--
Michael Harms, Ph.D.
---
Associate Professor of Psychiatry
Washington University School of Medicine
Department of Psychiatry, Box 8134
660 South Euclid Ave.Tel: 314-747-6173
St. Louis, MO  63110  Email: mha...@wustl.edu


The materials in this message are private and may contain Protected Healthcare 
Information or other information of a sensitive nature. If you are not the 
intended recipient, be advised that any unauthorized use, disclosure, copying 
or the taking of any action in reliance on the contents of this information is 
strictly prohibited. If you have received this email in error, please 
immediately notify the sender via telephone or return mail.

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Re: [HCP-Users] Variation in aparc ROIs between subjects in 32k_fs_LR space

2018-06-04 Thread Glasser, Matthew

What isn’t available is individual subject parcellations which you didn’t need 
anyway given your initial question> ;)

Matt.

From: Thomas Nichols 
mailto:thomas.nich...@bdi.ox.ac.uk>>
Date: Monday, June 4, 2018 at 11:45 AM
To: Matt Glasser mailto:glass...@wustl.edu>>
Cc: HCP Users 
mailto:hcp-users@humanconnectome.org>>
Subject: Re: [HCP-Users] Variation in aparc ROIs between subjects in 32k_fs_LR 
space

Hi Matt,

Ah!  Sorry, I didn't realise a 32k_fs_LR version was ready (I thought it was 
only available for the 449 subjects).

Will check it out.

-Tom

On Mon, Jun 4, 2018 at 5:41 PM, Glasser, Matthew 
mailto:glass...@wustl.edu>> wrote:
Hi Tom,

Why not use the multi-modal parcellation? https://balsa.wustl.edu/file/show/3VLx

Matt.

From: Thomas Nichols 
mailto:thomas.nich...@bdi.ox.ac.uk>>
Date: Monday, June 4, 2018 at 11:37 AM
To: Matt Glasser mailto:glass...@wustl.edu>>
Cc: HCP Users 
mailto:hcp-users@humanconnectome.org>>
Subject: Re: [HCP-Users] Variation in aparc ROIs between subjects in 32k_fs_LR 
space

Thanks Matt!

We're using it to just coarsely chop up the surface to build phenotypes.  What 
atlas would you suggest that we can easily apply with wb_command 
-cifti-parcellate?

-Tom

On Mon, Jun 4, 2018 at 4:29 PM, Glasser, Matthew 
mailto:glass...@wustl.edu>> wrote:
Hi Tom,

This is because FreeSurfer “fits” the aparc to each subject.  There is probably 
an atlas aparc somewhere inside FreeSurfer that wouldn’t have this property.  
That does raise the question of why you are using aparc instead of one of the 
more functionally relevant parcellations available in standard CIFTI space 
though.  Aparc is unlikely to follow task boundaries much at all.

Matt.

From: 
mailto:hcp-users-boun...@humanconnectome.org>>
 on behalf of Thomas Nichols 
mailto:thomas.nich...@bdi.ox.ac.uk>>
Date: Monday, June 4, 2018 at 2:38 AM
To: HCP Users 
mailto:hcp-users@humanconnectome.org>>
Subject: [HCP-Users] Variation in aparc ROIs between subjects in 32k_fs_LR space

Hi folks,

Sorry if this is a naive question, but looking for a sanity check...

We're using the aparc segmentations to extract data from the task fMRI CIFTI 
files.  We believe that we're working in atlas space (32k_fs_LR), so we were 
surprised that, when we load two different subjects into wb_view, the aparc 
segmentations are different for different subjects.

See attached images of
100206.aparc.32k_fs_LR.dlabel.nii &
100307.aparc.32k_fs_LR.dlabel.nii
The regions are similar but differ slightly, with the white dot showing a 
particular bit of the surface that changes from one ROI to another between 
subjects.  I would have expected this if we were in native space, but not 
32k_fs_LR.  What am I missing?

Thanks in advance!

-Tom

PS: A similar question was asked on May 9, titled "about the D-K atlas" from 
963619...@qq.com but it hasn't been answered; oddly, 
while it is in my inbox I can't find it in the archive.

__
Thomas Nichols, PhD
Professor of Neuroimaging Statistics
Nuffield Department of Population Health | University of Oxford
Big Data Institute | Li Ka Shing Centre for Health Information and Discovery
Old Road Campus | Headington | Oxford | OX3 7LF | United Kingdom
T: +44 1865 743590 | E: 
thomas.nich...@bdi.ox.ac.uk
W: http://nisox.org | http://www.bdi.ox.ac.uk

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--
__
Thomas Nichols, PhD
Professor of Neuroimaging Statistics
Nuffield Department of Population Health | University of Oxford
Big Data Institute | Li Ka Shing Centre for Health Information and Discovery
Old Road Campus | Headington | Oxford | OX3 7LF | United Kingdom
T: +44 1865 743590 | E: 
thomas.nich...@bdi.ox.ac.uk
W: http://nisox.org | http://www.bdi.ox.ac.uk

--
__
Thomas Nichols, PhD
Professor of Neuroimaging Statistics
Nuffield Department of Population Health | University of Oxford
Big Data Institute | Li Ka Shing Centre for Health Information and Discovery
Old Road Campus | Headington | Oxford | OX3 7LF | United Kingdom
T: +44 1865 743590 | E: 
thomas.nich...@bdi.ox.ac.uk
W: http://nisox.org | http://www.bdi.ox.ac.uk

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Re: [HCP-Users] Variation in aparc ROIs between subjects in 32k_fs_LR space

2018-06-04 Thread Thomas Nichols

Hi Matt,

Ah!  Sorry, I didn't realise a 32k_fs_LR version was ready (I thought it
was only available for the 449 subjects).

Will check it out.

-Tom

On Mon, Jun 4, 2018 at 5:41 PM, Glasser, Matthew  wrote:

> Hi Tom,
>
> Why not use the multi-modal parcellation? https://balsa.
> wustl.edu/file/show/3VLx
>
> Matt.
>
> From: Thomas Nichols 
> Date: Monday, June 4, 2018 at 11:37 AM
> To: Matt Glasser 
> Cc: HCP Users 
> Subject: Re: [HCP-Users] Variation in aparc ROIs between subjects in
> 32k_fs_LR space
>
> Thanks Matt!
>
> We're using it to just coarsely chop up the surface to build phenotypes.
> What atlas would you suggest that we can easily apply with
> wb_command -cifti-parcellate?
>
> -Tom
>
> On Mon, Jun 4, 2018 at 4:29 PM, Glasser, Matthew 
> wrote:
>
>> Hi Tom,
>>
>> This is because FreeSurfer “fits” the aparc to each subject.  There is
>> probably an atlas aparc somewhere inside FreeSurfer that wouldn’t have this
>> property.  That does raise the question of why you are using aparc instead
>> of one of the more functionally relevant parcellations available in
>> standard CIFTI space though.  Aparc is unlikely to follow task boundaries
>> much at all.
>>
>> Matt.
>>
>> From:  on behalf of Thomas
>> Nichols 
>> Date: Monday, June 4, 2018 at 2:38 AM
>> To: HCP Users 
>> Subject: [HCP-Users] Variation in aparc ROIs between subjects in
>> 32k_fs_LR space
>>
>> Hi folks,
>>
>> Sorry if this is a naive question, but looking for a sanity check...
>>
>> We're using the aparc segmentations to extract data from the task fMRI
>> CIFTI files.  We believe that we're working in atlas space (32k_fs_LR), so
>> we were surprised that, when we load two different subjects into wb_view,
>> the aparc segmentations are different for different subjects.
>>
>> See attached images of
>> 100206.aparc.32k_fs_LR.dlabel.nii &
>> 100307.aparc.32k_fs_LR.dlabel.nii
>> The regions are similar but differ slightly, with the white dot showing a
>> particular bit of the surface that changes from one ROI to another between
>> subjects.  I would have expected this if we were in native space, but not
>> 32k_fs_LR.  What am I missing?
>>
>> Thanks in advance!
>>
>> -Tom
>>
>> PS: A similar question was asked on May 9, titled "about the D-K atlas"
>> from 963619...@qq.com but it hasn't been answered; oddly, while it is in
>> my inbox I can't find it in the archive.
>>
>>
>> __
>> Thomas Nichols, PhD
>> Professor of Neuroimaging Statistics
>> Nuffield Department of Population Health | University of Oxford
>> Big Data Institute | Li Ka Shing Centre for Health Information and
>> Discovery
>> Old Road Campus | Headington | Oxford | OX3 7LF | United Kingdom
>> T: +44 1865 743590 | E: thomas.nich...@bdi.ox.ac.uk
>> W: http://nisox.org | http://www.bdi.ox.ac.uk
>>
>> ___
>> HCP-Users mailing list
>> HCP-Users@humanconnectome.org
>> http://lists.humanconnectome.org/mailman/listinfo/hcp-users
>>
>
>
>
> --
> __
> Thomas Nichols, PhD
> Professor of Neuroimaging Statistics
> Nuffield Department of Population Health | University of Oxford
> Big Data Institute | Li Ka Shing Centre for Health Information and
> Discovery
> Old Road Campus | Headington | Oxford | OX3 7LF | United Kingdom
> T: +44 1865 743590 | E: thomas.nich...@bdi.ox.ac.uk
> W: http://nisox.org | http://www.bdi.ox.ac.uk
>



-- 
__
Thomas Nichols, PhD
Professor of Neuroimaging Statistics
Nuffield Department of Population Health | University of Oxford
Big Data Institute | Li Ka Shing Centre for Health Information and Discovery
Old Road Campus | Headington | Oxford | OX3 7LF | United Kingdom
T: +44 1865 743590 | E: thomas.nich...@bdi.ox.ac.uk
W: http://nisox.org | http://www.bdi.ox.ac.uk

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Re: [HCP-Users] Variation in aparc ROIs between subjects in 32k_fs_LR space

2018-06-04 Thread Glasser, Matthew

Hi Tom,

Why not use the multi-modal parcellation? https://balsa.wustl.edu/file/show/3VLx

Matt.

From: Thomas Nichols 
mailto:thomas.nich...@bdi.ox.ac.uk>>
Date: Monday, June 4, 2018 at 11:37 AM
To: Matt Glasser mailto:glass...@wustl.edu>>
Cc: HCP Users 
mailto:hcp-users@humanconnectome.org>>
Subject: Re: [HCP-Users] Variation in aparc ROIs between subjects in 32k_fs_LR 
space

Thanks Matt!

We're using it to just coarsely chop up the surface to build phenotypes.  What 
atlas would you suggest that we can easily apply with wb_command 
-cifti-parcellate?

-Tom

On Mon, Jun 4, 2018 at 4:29 PM, Glasser, Matthew 
mailto:glass...@wustl.edu>> wrote:
Hi Tom,

This is because FreeSurfer “fits” the aparc to each subject.  There is probably 
an atlas aparc somewhere inside FreeSurfer that wouldn’t have this property.  
That does raise the question of why you are using aparc instead of one of the 
more functionally relevant parcellations available in standard CIFTI space 
though.  Aparc is unlikely to follow task boundaries much at all.

Matt.

From: 
mailto:hcp-users-boun...@humanconnectome.org>>
 on behalf of Thomas Nichols 
mailto:thomas.nich...@bdi.ox.ac.uk>>
Date: Monday, June 4, 2018 at 2:38 AM
To: HCP Users 
mailto:hcp-users@humanconnectome.org>>
Subject: [HCP-Users] Variation in aparc ROIs between subjects in 32k_fs_LR space

Hi folks,

Sorry if this is a naive question, but looking for a sanity check...

We're using the aparc segmentations to extract data from the task fMRI CIFTI 
files.  We believe that we're working in atlas space (32k_fs_LR), so we were 
surprised that, when we load two different subjects into wb_view, the aparc 
segmentations are different for different subjects.

See attached images of
100206.aparc.32k_fs_LR.dlabel.nii &
100307.aparc.32k_fs_LR.dlabel.nii
The regions are similar but differ slightly, with the white dot showing a 
particular bit of the surface that changes from one ROI to another between 
subjects.  I would have expected this if we were in native space, but not 
32k_fs_LR.  What am I missing?

Thanks in advance!

-Tom

PS: A similar question was asked on May 9, titled "about the D-K atlas" from 
963619...@qq.com but it hasn't been answered; oddly, 
while it is in my inbox I can't find it in the archive.

__
Thomas Nichols, PhD
Professor of Neuroimaging Statistics
Nuffield Department of Population Health | University of Oxford
Big Data Institute | Li Ka Shing Centre for Health Information and Discovery
Old Road Campus | Headington | Oxford | OX3 7LF | United Kingdom
T: +44 1865 743590 | E: 
thomas.nich...@bdi.ox.ac.uk
W: http://nisox.org | http://www.bdi.ox.ac.uk

___
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--
__
Thomas Nichols, PhD
Professor of Neuroimaging Statistics
Nuffield Department of Population Health | University of Oxford
Big Data Institute | Li Ka Shing Centre for Health Information and Discovery
Old Road Campus | Headington | Oxford | OX3 7LF | United Kingdom
T: +44 1865 743590 | E: 
thomas.nich...@bdi.ox.ac.uk
W: http://nisox.org | http://www.bdi.ox.ac.uk

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Re: [HCP-Users] Variation in aparc ROIs between subjects in 32k_fs_LR space

2018-06-04 Thread Thomas Nichols

Thanks Matt!

We're using it to just coarsely chop up the surface to build phenotypes.
What atlas would you suggest that we can easily apply with
wb_command -cifti-parcellate?

-Tom

On Mon, Jun 4, 2018 at 4:29 PM, Glasser, Matthew  wrote:

> Hi Tom,
>
> This is because FreeSurfer “fits” the aparc to each subject.  There is
> probably an atlas aparc somewhere inside FreeSurfer that wouldn’t have this
> property.  That does raise the question of why you are using aparc instead
> of one of the more functionally relevant parcellations available in
> standard CIFTI space though.  Aparc is unlikely to follow task boundaries
> much at all.
>
> Matt.
>
> From:  on behalf of Thomas Nichols
> 
> Date: Monday, June 4, 2018 at 2:38 AM
> To: HCP Users 
> Subject: [HCP-Users] Variation in aparc ROIs between subjects in
> 32k_fs_LR space
>
> Hi folks,
>
> Sorry if this is a naive question, but looking for a sanity check...
>
> We're using the aparc segmentations to extract data from the task fMRI
> CIFTI files.  We believe that we're working in atlas space (32k_fs_LR), so
> we were surprised that, when we load two different subjects into wb_view,
> the aparc segmentations are different for different subjects.
>
> See attached images of
> 100206.aparc.32k_fs_LR.dlabel.nii &
> 100307.aparc.32k_fs_LR.dlabel.nii
> The regions are similar but differ slightly, with the white dot showing a
> particular bit of the surface that changes from one ROI to another between
> subjects.  I would have expected this if we were in native space, but not
> 32k_fs_LR.  What am I missing?
>
> Thanks in advance!
>
> -Tom
>
> PS: A similar question was asked on May 9, titled "about the D-K atlas"
> from 963619...@qq.com but it hasn't been answered; oddly, while it is in
> my inbox I can't find it in the archive.
>
>
> __
> Thomas Nichols, PhD
> Professor of Neuroimaging Statistics
> Nuffield Department of Population Health | University of Oxford
> Big Data Institute | Li Ka Shing Centre for Health Information and
> Discovery
> Old Road Campus | Headington | Oxford | OX3 7LF | United Kingdom
> T: +44 1865 743590 | E: thomas.nich...@bdi.ox.ac.uk
> W: http://nisox.org | http://www.bdi.ox.ac.uk
>
> ___
> HCP-Users mailing list
> HCP-Users@humanconnectome.org
> http://lists.humanconnectome.org/mailman/listinfo/hcp-users
>



-- 
__
Thomas Nichols, PhD
Professor of Neuroimaging Statistics
Nuffield Department of Population Health | University of Oxford
Big Data Institute | Li Ka Shing Centre for Health Information and Discovery
Old Road Campus | Headington | Oxford | OX3 7LF | United Kingdom
T: +44 1865 743590 | E: thomas.nich...@bdi.ox.ac.uk
W: http://nisox.org | http://www.bdi.ox.ac.uk

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Re: [HCP-Users] FSL version in the HCP pipelines

2018-06-04 Thread Harms, Michael


Yes, you should be able to use the latest FSL release.
In fact, due to code consolidation in the newest release, FSL 5.0.6 is no 
longer allowed for the task-fMRI processing.

Cheers,
-MH

--
Michael Harms, Ph.D.

---

Associate Professor of Psychiatry

Washington University School of Medicine

Department of Psychiatry, Box 8134

660 South Euclid Ave.Tel: 314-747-6173

St. Louis, MO  63110  Email: mha...@wustl.edu
On 6/4/18, 11:23 AM, "hcp-users-boun...@humanconnectome.org on behalf of Cook, 
Philip"  wrote:

Hi,

The README.md on Github points to release notes for 3.0.4, which specifically 
requires FSL 5.0.6.

With pipelines v 3.27.0, is it still necessary to use 5.0.6 at all? Is it 
possible to use the latest release (5.0.11)?


Thanks
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or the taking of any action in reliance on the contents of this information is 
strictly prohibited. If you have received this email in error, please 
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[HCP-Users] FSL version in the HCP pipelines

2018-06-04 Thread Cook, Philip

Hi,

The README.md on Github points to release notes for 3.0.4, which specifically 
requires FSL 5.0.6.

With pipelines v 3.27.0, is it still necessary to use 5.0.6 at all? Is it 
possible to use the latest release (5.0.11)?


Thanks
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Re: [HCP-Users] Variation in aparc ROIs between subjects in 32k_fs_LR space

2018-06-04 Thread Glasser, Matthew

Hi Tom,

This is because FreeSurfer “fits” the aparc to each subject.  There is probably 
an atlas aparc somewhere inside FreeSurfer that wouldn’t have this property.  
That does raise the question of why you are using aparc instead of one of the 
more functionally relevant parcellations available in standard CIFTI space 
though.  Aparc is unlikely to follow task boundaries much at all.

Matt.

From: 
mailto:hcp-users-boun...@humanconnectome.org>>
 on behalf of Thomas Nichols 
mailto:thomas.nich...@bdi.ox.ac.uk>>
Date: Monday, June 4, 2018 at 2:38 AM
To: HCP Users 
mailto:hcp-users@humanconnectome.org>>
Subject: [HCP-Users] Variation in aparc ROIs between subjects in 32k_fs_LR space

Hi folks,

Sorry if this is a naive question, but looking for a sanity check...

We're using the aparc segmentations to extract data from the task fMRI CIFTI 
files.  We believe that we're working in atlas space (32k_fs_LR), so we were 
surprised that, when we load two different subjects into wb_view, the aparc 
segmentations are different for different subjects.

See attached images of
100206.aparc.32k_fs_LR.dlabel.nii &
100307.aparc.32k_fs_LR.dlabel.nii
The regions are similar but differ slightly, with the white dot showing a 
particular bit of the surface that changes from one ROI to another between 
subjects.  I would have expected this if we were in native space, but not 
32k_fs_LR.  What am I missing?

Thanks in advance!

-Tom

PS: A similar question was asked on May 9, titled "about the D-K atlas" from 
963619...@qq.com but it hasn't been answered; oddly, 
while it is in my inbox I can't find it in the archive.


__
Thomas Nichols, PhD
Professor of Neuroimaging Statistics
Nuffield Department of Population Health | University of Oxford
Big Data Institute | Li Ka Shing Centre for Health Information and Discovery
Old Road Campus | Headington | Oxford | OX3 7LF | United Kingdom
T: +44 1865 743590 | E: 
thomas.nich...@bdi.ox.ac.uk
W: http://nisox.org | http://www.bdi.ox.ac.uk

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Re: [HCP-Users] Additional smoothing of FIX extended resting state data?

2018-06-04 Thread David Hofmann

Thanks, Matthew & Timothy, that gave me some valuable insight, I appreciate
that!

All the best,

David

2018-05-31 1:37 GMT+02:00 Timothy Coalson :

> A bit more explanation: smoothing only spreads signal out, diluting it
> with non-signal or unrelated signal, it can't concentrate it "towards" some
> other relevant signal in another subject.  For any case that has
> non-negligible overlap of signals to begin with, smoothing basically just
> dilutes the overlap with other nearby things.  Thus, if you have one fixed
> group ROI to begin with, which nearly all subjects have substantial signal
> overlap with, smoothing is only going to hurt you (per-subject ROIs can do
> even better, but generating them well is harder).  Our preprint paper that
> Matt linked to explores this in terms of how much signal from other
> cortical areas or other tissues gets mixed in by smoothing (and by
> volume-based cortical analysis), but this particular idea of "increasing
> overlap" could also be tested by itself without taking crosstalk into
> account, and would likely show that until initial overlap gets rather
> small, common amounts of smoothing only make the overlap worse.
>
> By far, the biggest of the useful effects of smoothing is attenuating
> noise (and for some things, there are other ways to accomplish this goal -
> averaging data across a sizable ROI will be far more effective at reducing
> spatial noise, so if that is part of your analysis anyway, you don't get
> this benefit from adding smoothing, but you do get the detriments of the
> smoothing).  If your noise is largely independent per-voxel, then most of
> this attenuation occurs at relatively small smoothing amounts anyway.
>
> Also, be careful about regressing out WM and CSF, if your masks don't
> leave sufficient space from cortex, then it can pick up what is basically
> the mean gray matter signal, and cause you to accidentally do GSR.
>
> Tim
>
>
> On Wed, May 30, 2018 at 6:58 AM, Glasser, Matthew 
> wrote:
>
>> Indeed that is one of the major fallacies in brain imaging.  Have a look
>> at this paper in press at PNAS:
>>
>> https://www.biorxiv.org/content/early/2018/04/23/255620
>>
>> Peace,
>>
>> Matt.
>>
>> From: David Hofmann 
>> Date: Wednesday, May 30, 2018 at 5:14 AM
>> To: Timothy Coalson , Matt Glasser 
>> Cc: hcp-users 
>> Subject: Re: [HCP-Users] Additional smoothing of FIX extended resting
>> state data?
>>
>> Hi all,
>>
>> thanks for the comments! The idea to smooth the data was based on others
>> papers which did not use HCP data though. I always thought that
>> smoothing is a "good idea" for group studies in order to account for the
>> between-subject variability in the ROI based on the different brain sizes
>> and shapes.
>>
>> The analysis I want to run uses the data from ROIs to calculate
>> connectivity between ROIs (DCM). The ROI extraction in SPM uses the
>> component that explains the most variance in a PCA. The extraction runs on
>> the smoothed volumes. The ROIs are based on some probabilistic atlas (e.g.
>> anatomy toolbox). I have about 300 subjects.
>>
>> I thought the results will be relatively robust for different levels of
>> smoothing. But this is not the case. Since the CSF and WM signals have
>> been regressed out, I did not assume that this will have influence.
>>
>> The unsmoothed results look much better though.
>>
>> greetings
>>
>> David
>>
>> 2018-05-30 0:51 GMT+02:00 Timothy Coalson :
>>
>>> Volumetric smoothing in particular is not advised, as it causes signal
>>> from one bank of a sulcus to bleed into the opposite bank.  Analyses that
>>> average all signal within an ROI should have no benefits (and will have
>>> detriments) from smoothing, as the within-ROI averaging itself is a form of
>>> smoothing (but with a well-chosen ROI, it won't bring in signal from the
>>> opposite sulcal bank, etc, in theory).  Is this the kind of ROI analysis
>>> you are doing?  If so, I wouldn't trust the differences caused by adding
>>> volume-based smoothing, because they could be from nearby areas instead.
>>>
>>> Tim
>>>
>>>
>>> On Tue, May 29, 2018 at 4:24 PM, David Hofmann 
>>> wrote:
>>>
 Dear all,

 as far as I read in previous posts on the list, spatial smoothing of
 the volumetric resting state data is not recommended. But this was
 with regard to group ICA.
 Would you also recommend not to apply any further spatial smoothing for
 the (volumetric) resting state data, when running ROI-based (group)
 analysis on multiple subjects?

 Comparing the results of smoothed (4,6, FWHM) and unsmoothed data gives
 highly different results in my case, so I'm a bit confused now.

 greetings

 David

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