Re: [HCP-Users] Palm with TFCE on Cifti data

[Anderson M. Winkler]

Hi Michael,

That's right, no _tfce_ in the file names in the Example 9. Fixed, thanks.

All the best,

Anderson

On 21 September 2016 at 00:54, Timothy Coalson  wrote:

> The switch in command was my suggestion, as -from-template means it will
> always match the brainordinates of the template file, while the previous
> command did not specify the ROI files that are required in order to make
> -cifti-create-dense-scalar match the input brainordinate space (and in rare
> cases, -cifti-create-dense-scalar can't reproduce the input brainordinate
> space, because it puts the structures in a predetermined order every time).
>
> Tim
>
>
> On Tue, Sep 20, 2016 at 6:47 PM, Michael F.W. Dreyfuss <
> mid2...@med.cornell.edu> wrote:
>
>> Hi, I noticed the examples page has been updated. I wanted to ask why you
>> switched from using  wb_command
>>
>> -cifti-create-dense-scalar to wb_command -cifti-create-dense-from-templ
>> ate?
>>
>>
>> Also, I think example 9 the naming of the files is off, probably copy and
>> pasted from example 10. Given the palm command above it, it should probably
>> be: results_dpv_tstat_m1_c1.gii instead of results_tfce_tstat_mfwep_m1_c1.gii
>> ,and the same for the other inputs. Maybe I am wrong, but I think that
>> naming would have resulted from a call of palm with TFCE.
>>
>>
>> Thanks,
>>
>> Michael
>>
>> --
>> *From:* andersonwink...@gmail.com  on behalf
>> of Anderson M. Winkler 
>> *Sent:* Friday, September 16, 2016 11:35:44 AM
>> *To:* Michael F.W. Dreyfuss
>> *Cc:* hcp-users@humanconnectome.org
>>
>> *Subject:* Re: [HCP-Users] Palm with TFCE on Cifti data
>>
>> Hi Michael,
>>
>> No, I have no idea of what is going on. What was the command line used?
>>
>> All the best,
>>
>> Anderson
>>
>> On 16 September 2016 at 16:32, Michael F.W. Dreyfuss <
>> mid2...@med.cornell.edu> wrote:
>>
>>> Hello,
>>>
>>>
>>> When I follow the steps of example 10, I end up with essentially a blank
>>> cifti file. When I load it it is totally transparent, and the wb_command
>>> -file-information gives the below information. The individual .gii files
>>> will not load on wb_view as well. This occurs whether I use local
>>> midthickness files for the -s option or the HCP 900 subject average as
>>> recommended. Would you perhaps have any idea what may be going on?
>>>
>>>
>>> Thanks as usual,
>>>
>>> Michael
>>>
>>>
>>> Name:   FoodGo_results_merged_tfce_tst
>>> at_fwep.dscalar.nii
>>>
>>> Type:   Connectivity - Dense Scalar
>>>
>>> Structure:  CortexLeft CortexRight
>>>
>>> Data Size:  387.42 Kilobytes
>>>
>>> Maps to Surface:true
>>>
>>> Maps to Volume: true
>>>
>>> Maps with LabelTable:   false
>>>
>>> Maps with Palette:  true
>>>
>>> All Map Palettes Equal: true
>>>
>>> Map Interval Units: NIFTI_UNITS_UNKNOWN
>>>
>>> Number of Maps: 1
>>>
>>> Number of Rows: 96854
>>>
>>> Number of Columns:  1
>>>
>>> Volume Dim[0]:  91
>>>
>>> Volume Dim[1]:  109
>>>
>>> Volume Dim[2]:  91
>>>
>>> Palette Type:   Map (Unique for each map)
>>>
>>> CIFTI Dim[0]:   1
>>>
>>> CIFTI Dim[1]:   96854
>>>
>>> ALONG_ROW map type: SCALARS
>>>
>>> ALONG_COLUMN map type:  BRAIN_MODELS
>>>
>>> Has Volume Data:true
>>>
>>> Volume Dims:91,109,91
>>>
>>> Volume Space:   -2,0,0,90;0,2,0,-126;0,0,2,-72
>>>
>>> CortexLeft: 32492 out of 32492 vertices
>>>
>>> CortexRight:32492 out of 32492 vertices
>>>
>>> AccumbensLeft:  135 voxels
>>>
>>> AccumbensRight: 140 voxels
>>>
>>> AmygdalaLeft:   315 voxels
>>>
>>> AmygdalaRight:  332 voxels
>>>
>>> BrainStem:  3472 voxels
>>>
>>> CaudateLeft:728 voxels
>>>
>>> CaudateRight:   755 voxels
>>>
>>> CerebellumLeft: 8709 voxels
>>>
>>> CerebellumRight:9144 voxels
>>>
>>> DiencephalonVentralLeft:706 voxels
>>>
>>> DiencephalonVentralRight:   712 voxels
>>>
>>> HippocampusLeft:764 voxels
>>>
>>> HippocampusRight:   795 voxels
>>>
>>> PallidumLeft:   297 voxels
>>>
>>> PallidumRight:  260 voxels
>>>
>>> PutamenLeft:1060 voxels
>>>
>>> PutamenRight:   1010 voxels
>>>
>>> ThalamusLeft:   1288 voxels
>>>
>>> ThalamusRight:  1248 voxels
>>>
>>>
>>> Map   Minimum   MaximumMean   Sample Dev   % Positive   % Negative
>>> Inf/NaN   Map Name
>>>
>>>   1 0.000 0.000   0.0000.0000.0000.000
>>>   0   #1
>>>
>>>
>>>
>>> --
>>> *Fro

Re: [HCP-Users] Palm and Variance

[Anderson M. Winkler]

Hi Michael,

I'm afraid that this isn't possible yet, sorry. However, this has been for
a while in the to-do list, and will eventually become available.

All the best,

Anderson


On 20 September 2016 at 17:10, Michael F.W. Dreyfuss <
mid2...@med.cornell.edu> wrote:

> Hello,
>
>
> Is there anyway to include subject-level variance estimates when running
> palm on a group level? Different subjects in my tfMRI study have different
> numbers of correct trials modeled in their GLMs, so confidence around each
> subject's estimate is variable. Seems it would be optimal to account for
> that in some way if possible, although probably would be computationally
> extremely burdensome.
>
>
> Thank you,
>
> Michael
>
> ___
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>

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Re: [HCP-Users] Palm with TFCE on Cifti data

[Timothy Coalson]

The switch in command was my suggestion, as -from-template means it will
always match the brainordinates of the template file, while the previous
command did not specify the ROI files that are required in order to make
-cifti-create-dense-scalar match the input brainordinate space (and in rare
cases, -cifti-create-dense-scalar can't reproduce the input brainordinate
space, because it puts the structures in a predetermined order every time).

Tim


On Tue, Sep 20, 2016 at 6:47 PM, Michael F.W. Dreyfuss <
mid2...@med.cornell.edu> wrote:

> Hi, I noticed the examples page has been updated. I wanted to ask why you
> switched from using  wb_command
>
> -cifti-create-dense-scalar to wb_command -cifti-create-dense-from-
> template?
>
>
> Also, I think example 9 the naming of the files is off, probably copy and
> pasted from example 10. Given the palm command above it, it should probably
> be: results_dpv_tstat_m1_c1.gii instead of results_tfce_tstat_mfwep_m1_c1.gii
> ,and the same for the other inputs. Maybe I am wrong, but I think that
> naming would have resulted from a call of palm with TFCE.
>
>
> Thanks,
>
> Michael
>
> --
> *From:* andersonwink...@gmail.com  on behalf
> of Anderson M. Winkler 
> *Sent:* Friday, September 16, 2016 11:35:44 AM
> *To:* Michael F.W. Dreyfuss
> *Cc:* hcp-users@humanconnectome.org
>
> *Subject:* Re: [HCP-Users] Palm with TFCE on Cifti data
>
> Hi Michael,
>
> No, I have no idea of what is going on. What was the command line used?
>
> All the best,
>
> Anderson
>
> On 16 September 2016 at 16:32, Michael F.W. Dreyfuss <
> mid2...@med.cornell.edu> wrote:
>
>> Hello,
>>
>>
>> When I follow the steps of example 10, I end up with essentially a blank
>> cifti file. When I load it it is totally transparent, and the wb_command
>> -file-information gives the below information. The individual .gii files
>> will not load on wb_view as well. This occurs whether I use local
>> midthickness files for the -s option or the HCP 900 subject average as
>> recommended. Would you perhaps have any idea what may be going on?
>>
>>
>> Thanks as usual,
>>
>> Michael
>>
>>
>> Name:   FoodGo_results_merged_tfce_tst
>> at_fwep.dscalar.nii
>>
>> Type:   Connectivity - Dense Scalar
>>
>> Structure:  CortexLeft CortexRight
>>
>> Data Size:  387.42 Kilobytes
>>
>> Maps to Surface:true
>>
>> Maps to Volume: true
>>
>> Maps with LabelTable:   false
>>
>> Maps with Palette:  true
>>
>> All Map Palettes Equal: true
>>
>> Map Interval Units: NIFTI_UNITS_UNKNOWN
>>
>> Number of Maps: 1
>>
>> Number of Rows: 96854
>>
>> Number of Columns:  1
>>
>> Volume Dim[0]:  91
>>
>> Volume Dim[1]:  109
>>
>> Volume Dim[2]:  91
>>
>> Palette Type:   Map (Unique for each map)
>>
>> CIFTI Dim[0]:   1
>>
>> CIFTI Dim[1]:   96854
>>
>> ALONG_ROW map type: SCALARS
>>
>> ALONG_COLUMN map type:  BRAIN_MODELS
>>
>> Has Volume Data:true
>>
>> Volume Dims:91,109,91
>>
>> Volume Space:   -2,0,0,90;0,2,0,-126;0,0,2,-72
>>
>> CortexLeft: 32492 out of 32492 vertices
>>
>> CortexRight:32492 out of 32492 vertices
>>
>> AccumbensLeft:  135 voxels
>>
>> AccumbensRight: 140 voxels
>>
>> AmygdalaLeft:   315 voxels
>>
>> AmygdalaRight:  332 voxels
>>
>> BrainStem:  3472 voxels
>>
>> CaudateLeft:728 voxels
>>
>> CaudateRight:   755 voxels
>>
>> CerebellumLeft: 8709 voxels
>>
>> CerebellumRight:9144 voxels
>>
>> DiencephalonVentralLeft:706 voxels
>>
>> DiencephalonVentralRight:   712 voxels
>>
>> HippocampusLeft:764 voxels
>>
>> HippocampusRight:   795 voxels
>>
>> PallidumLeft:   297 voxels
>>
>> PallidumRight:  260 voxels
>>
>> PutamenLeft:1060 voxels
>>
>> PutamenRight:   1010 voxels
>>
>> ThalamusLeft:   1288 voxels
>>
>> ThalamusRight:  1248 voxels
>>
>>
>> Map   Minimum   MaximumMean   Sample Dev   % Positive   % Negative
>> Inf/NaN   Map Name
>>
>>   1 0.000 0.000   0.0000.0000.0000.000
>>   0   #1
>>
>>
>>
>> --
>> *From:* andersonwink...@gmail.com  on behalf
>> of Anderson M. Winkler 
>> *Sent:* Friday, September 16, 2016 4:19:06 AM
>> *To:* Michael F.W. Dreyfuss
>>
>> *Subject:* Re: [HCP-Users] Palm with TFCE on Cifti data
>>
>> Hi Michael,
>>
>> The "-s" option can take 1 or 2 arguments. The first is mandatory and it
>> is a surface file (.surf.gii for insta

Re: [HCP-Users] Palm with TFCE on Cifti data

[Michael F.W. Dreyfuss]

Hi, I noticed the examples page has been updated. I wanted to ask why you 
switched from using  wb_command

-cifti-create-dense-scalar to wb_command -cifti-create-dense-from-template?


Also, I think example 9 the naming of the files is off, probably copy and 
pasted from example 10. Given the palm command above it, it should probably be: 
results_dpv_tstat_m1_c1.gii instead of results_tfce_tstat_mfwep_m1_c1.gii ,and 
the same for the other inputs. Maybe I am wrong, but I think that naming would 
have resulted from a call of palm with TFCE.


Thanks,

Michael


From: andersonwink...@gmail.com  on behalf of 
Anderson M. Winkler 
Sent: Friday, September 16, 2016 11:35:44 AM
To: Michael F.W. Dreyfuss
Cc: hcp-users@humanconnectome.org
Subject: Re: [HCP-Users] Palm with TFCE on Cifti data

Hi Michael,

No, I have no idea of what is going on. What was the command line used?

All the best,

Anderson

On 16 September 2016 at 16:32, Michael F.W. Dreyfuss 
mailto:mid2...@med.cornell.edu>> wrote:

Hello,


When I follow the steps of example 10, I end up with essentially a blank cifti 
file. When I load it it is totally transparent, and the wb_command 
-file-information gives the below information. The individual .gii files will 
not load on wb_view as well. This occurs whether I use local midthickness files 
for the -s option or the HCP 900 subject average as recommended. Would you 
perhaps have any idea what may be going on?


Thanks as usual,

Michael


Name:   
FoodGo_results_merged_tfce_tstat_fwep.dscalar.nii

Type:   Connectivity - Dense Scalar

Structure:  CortexLeft CortexRight

Data Size:  387.42 Kilobytes

Maps to Surface:true

Maps to Volume: true

Maps with LabelTable:   false

Maps with Palette:  true

All Map Palettes Equal: true

Map Interval Units: NIFTI_UNITS_UNKNOWN

Number of Maps: 1

Number of Rows: 96854

Number of Columns:  1

Volume Dim[0]:  91

Volume Dim[1]:  109

Volume Dim[2]:  91

Palette Type:   Map (Unique for each map)

CIFTI Dim[0]:   1

CIFTI Dim[1]:   96854

ALONG_ROW map type: SCALARS

ALONG_COLUMN map type:  BRAIN_MODELS

Has Volume Data:true

Volume Dims:91,109,91

Volume Space:   -2,0,0,90;0,2,0,-126;0,0,2,-72

CortexLeft: 32492 out of 32492 vertices

CortexRight:32492 out of 32492 vertices

AccumbensLeft:  135 voxels

AccumbensRight: 140 voxels

AmygdalaLeft:   315 voxels

AmygdalaRight:  332 voxels

BrainStem:  3472 voxels

CaudateLeft:728 voxels

CaudateRight:   755 voxels

CerebellumLeft: 8709 voxels

CerebellumRight:9144 voxels

DiencephalonVentralLeft:706 voxels

DiencephalonVentralRight:   712 voxels

HippocampusLeft:764 voxels

HippocampusRight:   795 voxels

PallidumLeft:   297 voxels

PallidumRight:  260 voxels

PutamenLeft:1060 voxels

PutamenRight:   1010 voxels

ThalamusLeft:   1288 voxels

ThalamusRight:  1248 voxels


Map   Minimum   MaximumMean   Sample Dev   % Positive   % Negative   
Inf/NaN   Map Name

  1 0.000 0.000   0.0000.0000.0000.000 
0   #1




From: andersonwink...@gmail.com 
mailto:andersonwink...@gmail.com>> on behalf of 
Anderson M. Winkler mailto:wink...@fmrib.ox.ac.uk>>
Sent: Friday, September 16, 2016 4:19:06 AM
To: Michael F.W. Dreyfuss

Subject: Re: [HCP-Users] Palm with TFCE on Cifti data

Hi Michael,

The "-s" option can take 1 or 2 arguments. The first is mandatory and it is a 
surface file (.surf.gii for instance). If only this argument is given, PALM 
will use this file and do two things with it: it will use it for the adjacency 
information and it will also use this file to calculate the area-per-vertex, 
which is necessary to compute the cluster extent statistic, and also to 
calculate the area of the support region of TFCE. This means that if only one 
argument is given, in order to have a reasonable approximation, this file 
should look like a brain (e.g., midthickness or white, but not sphere).

If a second argument is given, this second argument should be a scalar file 
with the area per vertex for the same vertices of the surface file. Ideally 
this file should be an average of the areas of the same subjects in your 
sample, but if in your lab you are having difficulties in calculating it, use 
the midth

Re: [HCP-Users] ROIs and Betas from Cifti Data

[Timothy Coalson]

I should read the help info a little closer myself - I meant ""
where I said "" - perhaps "" would be clearer in the help,
though...

Tim


On Tue, Sep 20, 2016 at 3:14 PM, Timothy Coalson  wrote:

> I should probably rephrase some of -cifti-label-import help.  When it says:
>
> "The label list file must have lines of the following format:
>
>   
>   "
>
> It means 2 lines per label: the first line is the label name, the second
> line is the numeric stuff, where  is an integer that you will find in
> the data file you are importing to label.
>
> If you don't need to assign names to your labels, just specify '' as the
> filename - a pair of quotes with nothing inside them (double quotes will
> also work) - quoting from the help:
>
> "You may specify the empty string ('' will work on linux/mac) for
> , which will be treated as if it is an empty file."
>
> Then it will just assign names based on what value it found in the file
> being imported:
>
> "By default, it will set new label names with names of LABEL_# for any
> values encountered that are not mentioned in the list file, specify
> -discard-others to instead set these to the "unlabeled" key."
>
> You do want these imported, rather than zeroed out, so you don't want to
> use -discard-others.
>
> Tim
>
>
>
> On Tue, Sep 20, 2016 at 3:00 PM, Michael F.W. Dreyfuss <
> mid2...@med.cornell.edu> wrote:
>
>> Thank you, I was using a bad input file. The command works now.
>>
>> for -cifti-label-import however, I am no sure how the label file is
>> supposed to look. I get a malformed error:
>>
>> ERROR: label list file is malformed for entry #1: test 255 255 255 255
>>
>> I have 4 cortical and 1 subcortical ROIs which are colored differently on
>> viewing, but the cifti file contains only 1 map.
>>
>> Ultimately I’d like to be able to identify and extract beta weights from
>> each.
>>
>> Thank you,
>> Michael
>>
>> On Sep 20, 2016, at 2:26 PM, Glasser, Matthew  wrote:
>>
>> What does the input data look like?
>>
>> Peace,
>>
>> Matt.
>>
>> From: "Michael F.W. Dreyfuss" 
>> Date: Tuesday, September 20, 2016 at 1:22 PM
>> To: Matt Glasser 
>> Cc: "Michael F.W. Dreyfuss" , Timothy Coalson <
>> tsc...@mst.edu>, "hcp-users@humanconnectome.org" <
>> hcp-users@humanconnectome.org>
>> Subject: Re: [HCP-Users] ROIs and Betas from Cifti Data
>>
>> OK, I tried this:
>>
>> wb_command -cifti-find-clusters FoodGo_HCP_mesh_TFCE_palm/Food
>> Go_results_merged_tfce_tstat_fwep.dscalar.nii 0 0 0 0 COLUMN
>> FoodGo_results_merged_tfce_tstat_fwep_ROIs.dscalar.nii -left-surface
>> HCP_S900_GroupAvg_v1/S900.L.midthickness_MSMAll.32k_fs_LR.surf.gii
>> -right-surface HCP_S900_GroupAvg_v1/S900.R.mi
>> dthickness_MSMAll.32k_fs_LR.surf.gii
>>
>> Where now I am using these 900 subject average files as templates. I
>> though the -left-surface it was looking for was with the statistics run
>>
>> The output of this is null, however. Nothing shows up on wb_view and
>> -file-information gives:
>>
>> Map   Minimum   MaximumMean   Sample Dev   % Positive   % Negative
>> Inf/NaN   Map Name
>>   1 0.000 0.000   0.0000.0000.0000.000
>>   0   #1
>>
>> Am I doing something wrong still?
>>
>> Thanks,
>> Michael
>>
>>
>> On Sep 20, 2016, at 1:59 PM, Glasser, Matthew  wrote:
>>
>> Presumably you have some of these if you have gotten this far?
>>
>>
>>
>>
>> --
>> 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] ROIs and Betas from Cifti Data

[Timothy Coalson]

I should probably rephrase some of -cifti-label-import help.  When it says:

"The label list file must have lines of the following format:

  
  "

It means 2 lines per label: the first line is the label name, the second
line is the numeric stuff, where  is an integer that you will find in
the data file you are importing to label.

If you don't need to assign names to your labels, just specify '' as the
filename - a pair of quotes with nothing inside them (double quotes will
also work) - quoting from the help:

"You may specify the empty string ('' will work on linux/mac) for
, which will be treated as if it is an empty file."

Then it will just assign names based on what value it found in the file
being imported:

"By default, it will set new label names with names of LABEL_# for any
values encountered that are not mentioned in the list file, specify
-discard-others to instead set these to the "unlabeled" key."

You do want these imported, rather than zeroed out, so you don't want to
use -discard-others.

Tim



On Tue, Sep 20, 2016 at 3:00 PM, Michael F.W. Dreyfuss <
mid2...@med.cornell.edu> wrote:

> Thank you, I was using a bad input file. The command works now.
>
> for -cifti-label-import however, I am no sure how the label file is
> supposed to look. I get a malformed error:
>
> ERROR: label list file is malformed for entry #1: test 255 255 255 255
>
> I have 4 cortical and 1 subcortical ROIs which are colored differently on
> viewing, but the cifti file contains only 1 map.
>
> Ultimately I’d like to be able to identify and extract beta weights from
> each.
>
> Thank you,
> Michael
>
> On Sep 20, 2016, at 2:26 PM, Glasser, Matthew  wrote:
>
> What does the input data look like?
>
> Peace,
>
> Matt.
>
> From: "Michael F.W. Dreyfuss" 
> Date: Tuesday, September 20, 2016 at 1:22 PM
> To: Matt Glasser 
> Cc: "Michael F.W. Dreyfuss" , Timothy Coalson <
> tsc...@mst.edu>, "hcp-users@humanconnectome.org" <
> hcp-users@humanconnectome.org>
> Subject: Re: [HCP-Users] ROIs and Betas from Cifti Data
>
> OK, I tried this:
>
> wb_command -cifti-find-clusters FoodGo_HCP_mesh_TFCE_palm/
> FoodGo_results_merged_tfce_tstat_fwep.dscalar.nii 0 0 0 0 COLUMN
> FoodGo_results_merged_tfce_tstat_fwep_ROIs.dscalar.nii -left-surface
> HCP_S900_GroupAvg_v1/S900.L.midthickness_MSMAll.32k_fs_LR.surf.gii
> -right-surface HCP_S900_GroupAvg_v1/S900.R.midthickness_MSMAll.32k_fs_LR.
> surf.gii
>
> Where now I am using these 900 subject average files as templates. I
> though the -left-surface it was looking for was with the statistics run
>
> The output of this is null, however. Nothing shows up on wb_view and
> -file-information gives:
>
> Map   Minimum   MaximumMean   Sample Dev   % Positive   % Negative
> Inf/NaN   Map Name
>   1 0.000 0.000   0.0000.0000.0000.000
> 0   #1
>
> Am I doing something wrong still?
>
> Thanks,
> Michael
>
>
> On Sep 20, 2016, at 1:59 PM, Glasser, Matthew  wrote:
>
> Presumably you have some of these if you have gotten this far?
>
>
>
>
> --
> 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] ROIs and Betas from Cifti Data

[Michael F.W. Dreyfuss]

Thank you, I was using a bad input file. The command works now.

for -cifti-label-import however, I am no sure how the label file is supposed to 
look. I get a malformed error:

ERROR: label list file is malformed for entry #1: test 255 255 255 255

I have 4 cortical and 1 subcortical ROIs which are colored differently on 
viewing, but the cifti file contains only 1 map.

Ultimately I’d like to be able to identify and extract beta weights from each.

Thank you,
Michael

On Sep 20, 2016, at 2:26 PM, Glasser, Matthew 
mailto:glass...@wustl.edu>> wrote:

What does the input data look like?

Peace,

Matt.

From: "Michael F.W. Dreyfuss" 
mailto:mid2...@med.cornell.edu>>
Date: Tuesday, September 20, 2016 at 1:22 PM
To: Matt Glasser mailto:glass...@wustl.edu>>
Cc: "Michael F.W. Dreyfuss" 
mailto:mid2...@med.cornell.edu>>, Timothy Coalson 
mailto:tsc...@mst.edu>>, 
"hcp-users@humanconnectome.org" 
mailto:hcp-users@humanconnectome.org>>
Subject: Re: [HCP-Users] ROIs and Betas from Cifti Data

OK, I tried this:

wb_command -cifti-find-clusters 
FoodGo_HCP_mesh_TFCE_palm/FoodGo_results_merged_tfce_tstat_fwep.dscalar.nii 0 0 
0 0 COLUMN FoodGo_results_merged_tfce_tstat_fwep_ROIs.dscalar.nii -left-surface 
HCP_S900_GroupAvg_v1/S900.L.midthickness_MSMAll.32k_fs_LR.surf.gii 
-right-surface 
HCP_S900_GroupAvg_v1/S900.R.midthickness_MSMAll.32k_fs_LR.surf.gii

Where now I am using these 900 subject average files as templates. I though the 
-left-surface it was looking for was with the statistics run

The output of this is null, however. Nothing shows up on wb_view and 
-file-information gives:

Map   Minimum   MaximumMean   Sample Dev   % Positive   % Negative   
Inf/NaN   Map Name
  1 0.000 0.000   0.0000.0000.0000.000 
0   #1

Am I doing something wrong still?

Thanks,
Michael


On Sep 20, 2016, at 1:59 PM, Glasser, Matthew 
mailto:glass...@wustl.edu>> wrote:

Presumably you have some of these if you have gotten this far?




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 
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Re: [HCP-Users] ROIs and Betas from Cifti Data

[Glasser, Matthew]

What does the input data look like?

Peace,

Matt.

From: "Michael F.W. Dreyfuss" 
mailto:mid2...@med.cornell.edu>>
Date: Tuesday, September 20, 2016 at 1:22 PM
To: Matt Glasser mailto:glass...@wustl.edu>>
Cc: "Michael F.W. Dreyfuss" 
mailto:mid2...@med.cornell.edu>>, Timothy Coalson 
mailto:tsc...@mst.edu>>, 
"hcp-users@humanconnectome.org" 
mailto:hcp-users@humanconnectome.org>>
Subject: Re: [HCP-Users] ROIs and Betas from Cifti Data

OK, I tried this:

wb_command -cifti-find-clusters 
FoodGo_HCP_mesh_TFCE_palm/FoodGo_results_merged_tfce_tstat_fwep.dscalar.nii 0 0 
0 0 COLUMN FoodGo_results_merged_tfce_tstat_fwep_ROIs.dscalar.nii -left-surface 
HCP_S900_GroupAvg_v1/S900.L.midthickness_MSMAll.32k_fs_LR.surf.gii 
-right-surface 
HCP_S900_GroupAvg_v1/S900.R.midthickness_MSMAll.32k_fs_LR.surf.gii

Where now I am using these 900 subject average files as templates. I though the 
-left-surface it was looking for was with the statistics run

The output of this is null, however. Nothing shows up on wb_view and 
-file-information gives:

Map   Minimum   MaximumMean   Sample Dev   % Positive   % Negative   
Inf/NaN   Map Name
  1 0.000 0.000   0.0000.0000.0000.000 
0   #1

Am I doing something wrong still?

Thanks,
Michael


On Sep 20, 2016, at 1:59 PM, Glasser, Matthew 
mailto:glass...@wustl.edu>> wrote:

Presumably you have some of these if you have gotten this far?



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 
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immediately notify the sender via telephone or return mail.

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Re: [HCP-Users] ROIs and Betas from Cifti Data

[Michael F.W. Dreyfuss]

OK, I tried this:

wb_command -cifti-find-clusters 
FoodGo_HCP_mesh_TFCE_palm/FoodGo_results_merged_tfce_tstat_fwep.dscalar.nii 0 0 
0 0 COLUMN FoodGo_results_merged_tfce_tstat_fwep_ROIs.dscalar.nii -left-surface 
HCP_S900_GroupAvg_v1/S900.L.midthickness_MSMAll.32k_fs_LR.surf.gii 
-right-surface 
HCP_S900_GroupAvg_v1/S900.R.midthickness_MSMAll.32k_fs_LR.surf.gii

Where now I am using these 900 subject average files as templates. I though the 
-left-surface it was looking for was with the statistics run

The output of this is null, however. Nothing shows up on wb_view and 
-file-information gives:

Map   Minimum   MaximumMean   Sample Dev   % Positive   % Negative   
Inf/NaN   Map Name
  1 0.000 0.000   0.0000.0000.0000.000 
0   #1

Am I doing something wrong still?

Thanks,
Michael


On Sep 20, 2016, at 1:59 PM, Glasser, Matthew 
mailto:glass...@wustl.edu>> wrote:

Presumably you have some of these if you have gotten this far?


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Re: [HCP-Users] ROIs and Betas from Cifti Data

[Glasser, Matthew]

You do need an actual surface file (e.g. that contains a mesh topology and 
vertex coordinate locations).  Presumably you have some of these if you have 
gotten this far?

Peace,

Matt.

From: "Michael F.W. Dreyfuss" 
mailto:mid2...@med.cornell.edu>>
Date: Tuesday, September 20, 2016 at 12:55 PM
To: Matt Glasser mailto:glass...@wustl.edu>>, Timothy 
Coalson mailto:tsc...@mst.edu>>
Cc: "hcp-users@humanconnectome.org" 
mailto:hcp-users@humanconnectome.org>>
Subject: Re: [HCP-Users] ROIs and Betas from Cifti Data


When I run


wb_command -cifti-find-clusters 
FoodNogo_results_merged_tfce_tstat_fwep.dscalar.nii 1 1 1 1 COLUMN 
FoodNogo_results_merged_tfce_tstat_fwep_ROIs.dscalar.nii


I get the error:

ERROR: left surface required but not provided


Then if I add the option:

-left-surface FoodNogo_results_L_cort_tfce_tstat_fwep.gii


I get

ERROR: Number of data arrays MUST be two in a SurfaceFile.


I understand that this is a metric file and not a surface file, but 1) I do not 
know how to convert it, and 2) all the information is contained within the 
cifti file anyway, so I am unsure what additional information this command is 
looking for


As for the thresholding, I arbitrarily chose 1 just to get this running.


Thanks,

Michael


From: Glasser, Matthew mailto:glass...@wustl.edu>>
Sent: Tuesday, September 20, 2016 12:57:49 PM
To: Michael F.W. Dreyfuss; NEUROSCIENCE tim
Cc: hcp-users@humanconnectome.org
Subject: Re: [HCP-Users] ROIs and Betas from Cifti Data

If you are getting error messages, I recommend posting them.

Peace,

Matt.

From: "Michael F.W. Dreyfuss" 
mailto:mid2...@med.cornell.edu>>
Date: Tuesday, September 20, 2016 at 10:40 AM
To: Matt Glasser mailto:glass...@wustl.edu>>, Timothy 
Coalson mailto:tsc...@mst.edu>>
Cc: "hcp-users@humanconnectome.org" 
mailto:hcp-users@humanconnectome.org>>
Subject: Re: [HCP-Users] ROIs and Betas from Cifti Data


Thank you for this. We had explored this option in the past and two issues were 
1) there was not a parcellation readily available with subcortical structures 
and 2) I do not feel a need to constrain activation to parcels rather than 
swaths of signal as they appear to cluster themselves.


I'm sure parcellation is a valid approach, but I would really like to be able 
to simply report activation as it appears to cluster such as with TFCE, fdr or 
cluster thresholding (although that is less favored now) as has been typical in 
fMRI reporting. Are there examples available for these kinds of analysis to 
eventually relate activation to behavior or other measures?


I am grateful for all the help you have all provided. Things are quite close, 
and I hope to be able to be able to get through these last steps as quickly as 
possible.





From: Glasser, Matthew mailto:glass...@wustl.edu>>
Sent: Tuesday, September 20, 2016 11:06:10 AM
To: Michael F.W. Dreyfuss; NEUROSCIENCE tim
Cc: hcp-users@humanconnectome.org
Subject: Re: [HCP-Users] ROIs and Betas from Cifti Data

As Tim mentions, it sounds like you might want to use a parcellated analysis, 
as this will be more sensitive/powerful and you’ll know exactly what areas you 
are finding.  The HCP’s multi-modal parcellation is available here:

https://balsa.wustl.edu/study/show/RVVG

Also, the HCP’s task analysis pipeline will allow you to parcellate before 
fitting the GLM, rather than afterwards to get the addition SNR benefits from 
averaging across a parcel.

Peace,

Matt.

From: 
mailto:hcp-users-boun...@humanconnectome.org>>
 on behalf of "Michael F.W. Dreyfuss" 
mailto:mid2...@med.cornell.edu>>
Date: Monday, September 19, 2016 at 9:40 PM
To: Timothy Coalson mailto:tsc...@mst.edu>>
Cc: "Michael F.W. Dreyfuss" 
mailto:mid2...@med.cornell.edu>>, 
"hcp-users@humanconnectome.org" 
mailto:hcp-users@humanconnectome.org>>
Subject: Re: [HCP-Users] ROIs and Betas from Cifti Data

Thank you,

Are there any examples available for how to use this, possibly? I have been 
trying to figure these out, but there are a lot of options and  I am just not 
able to decipher how to use these from the help page alone. The errors I am 
getting also do not clarify what I need to do to get the output I am looking 
for.

Before using this kind of multi-band data I had been using afni. To give an 
example of what I would want to do in terms of afni commands (if that’s any 
help), I would have saved all ROIs and then used 3dmaskave to extract mean beta 
weights for a given GLM beta for each subject and t

Re: [HCP-Users] ROIs and Betas from Cifti Data

[Michael F.W. Dreyfuss]

When I run


wb_command -cifti-find-clusters 
FoodNogo_results_merged_tfce_tstat_fwep.dscalar.nii 1 1 1 1 COLUMN 
FoodNogo_results_merged_tfce_tstat_fwep_ROIs.dscalar.nii


I get the error:

ERROR: left surface required but not provided


Then if I add the option:

-left-surface FoodNogo_results_L_cort_tfce_tstat_fwep.gii


I get

ERROR: Number of data arrays MUST be two in a SurfaceFile.


I understand that this is a metric file and not a surface file, but 1) I do not 
know how to convert it, and 2) all the information is contained within the 
cifti file anyway, so I am unsure what additional information this command is 
looking for


As for the thresholding, I arbitrarily chose 1 just to get this running.


Thanks,

Michael


From: Glasser, Matthew 
Sent: Tuesday, September 20, 2016 12:57:49 PM
To: Michael F.W. Dreyfuss; NEUROSCIENCE tim
Cc: hcp-users@humanconnectome.org
Subject: Re: [HCP-Users] ROIs and Betas from Cifti Data

If you are getting error messages, I recommend posting them.

Peace,

Matt.

From: "Michael F.W. Dreyfuss" 
mailto:mid2...@med.cornell.edu>>
Date: Tuesday, September 20, 2016 at 10:40 AM
To: Matt Glasser mailto:glass...@wustl.edu>>, Timothy 
Coalson mailto:tsc...@mst.edu>>
Cc: "hcp-users@humanconnectome.org" 
mailto:hcp-users@humanconnectome.org>>
Subject: Re: [HCP-Users] ROIs and Betas from Cifti Data


Thank you for this. We had explored this option in the past and two issues were 
1) there was not a parcellation readily available with subcortical structures 
and 2) I do not feel a need to constrain activation to parcels rather than 
swaths of signal as they appear to cluster themselves.


I'm sure parcellation is a valid approach, but I would really like to be able 
to simply report activation as it appears to cluster such as with TFCE, fdr or 
cluster thresholding (although that is less favored now) as has been typical in 
fMRI reporting. Are there examples available for these kinds of analysis to 
eventually relate activation to behavior or other measures?


I am grateful for all the help you have all provided. Things are quite close, 
and I hope to be able to be able to get through these last steps as quickly as 
possible.





From: Glasser, Matthew mailto:glass...@wustl.edu>>
Sent: Tuesday, September 20, 2016 11:06:10 AM
To: Michael F.W. Dreyfuss; NEUROSCIENCE tim
Cc: hcp-users@humanconnectome.org
Subject: Re: [HCP-Users] ROIs and Betas from Cifti Data

As Tim mentions, it sounds like you might want to use a parcellated analysis, 
as this will be more sensitive/powerful and you’ll know exactly what areas you 
are finding.  The HCP’s multi-modal parcellation is available here:

https://balsa.wustl.edu/study/show/RVVG

Also, the HCP’s task analysis pipeline will allow you to parcellate before 
fitting the GLM, rather than afterwards to get the addition SNR benefits from 
averaging across a parcel.

Peace,

Matt.

From: 
mailto:hcp-users-boun...@humanconnectome.org>>
 on behalf of "Michael F.W. Dreyfuss" 
mailto:mid2...@med.cornell.edu>>
Date: Monday, September 19, 2016 at 9:40 PM
To: Timothy Coalson mailto:tsc...@mst.edu>>
Cc: "Michael F.W. Dreyfuss" 
mailto:mid2...@med.cornell.edu>>, 
"hcp-users@humanconnectome.org" 
mailto:hcp-users@humanconnectome.org>>
Subject: Re: [HCP-Users] ROIs and Betas from Cifti Data

Thank you,

Are there any examples available for how to use this, possibly? I have been 
trying to figure these out, but there are a lot of options and  I am just not 
able to decipher how to use these from the help page alone. The errors I am 
getting also do not clarify what I need to do to get the output I am looking 
for.

Before using this kind of multi-band data I had been using afni. To give an 
example of what I would want to do in terms of afni commands (if that’s any 
help), I would have saved all ROIs and then used 3dmaskave to extract mean beta 
weights for a given GLM beta for each subject and then I would relate those 
beta weights so subject’s behavior in R or another stats package.

Definitely agree that there’s not much meaning to a peak coordinate per se. I’m 
just trying to figure out how to report the clusters I am finding. In previous 
reports we would typically focus on broadmann areas or more general regional 
nomenclature (i.e. vmPFC, mid temporal lobe, etc.). Some of the clusters I’m 
finding also cover large areas from motor to visual cortex, so I am trying to 
consider good ways to report that.

At this point I would prefer to use TFCE or some other thresholding method to 
identify contiguo

Re: [HCP-Users] Lifespan Pilot Subject Scans

[Elam, Jennifer]

Hi David,

You are right that there we did collect more data for the Lifespan Pilot 
Project that has not yet been released. The data were processed for use in the 
preliminary report, but we have since made some improvements to our processing 
pipelines and we have it on our to do list to reprocess these data before we 
make a release of the larger dataset.


This work is competing with the first priority processing and release of the 
main HCP data, so I'm afraid here at the end of the HCP efforts, release of the 
Lifespan Pilot 1a and 1b unprocessed and processed data is lower priority. 
Therefore, it will still be some months before we make this data available, 
hopefully in early 2017. We are sorry for the delay.


Best,

Jenn

Jennifer Elam, Ph.D.
Scientific Outreach, Human Connectome Project
Washington University School of Medicine
Department of Neuroscience, Box 8108
660 South Euclid Avenue
St. Louis, MO 63110
314-362-9387
e...@wustl.edu
www.humanconnectome.org



From: hcp-users-boun...@humanconnectome.org 
 on behalf of David Baric Parker 

Sent: Tuesday, September 20, 2016 11:26:13 AM
To: hcp-users@humanconnectome.org
Subject: [HCP-Users] Lifespan Pilot Subject Scans

Hello, All.

  We're interested in examining scans of older (65-75) brains, and as such have 
great interest in your lifespan study.  We understand that it's in the pilot 
stages, however after examining "The WU-Minn HCP Lifespan Pilot Project" 
Preliminary report, submitted in Feb. 2015, we see from table 1 that there 
should be 20 complete or in progress scans from WUSTL and 23 complete or in 
progress scans from MINN.  Currently, there are only 5 subjects in the 65-75 
age range released on the connectomeDB.  We were wondering if there's any way 
to get access to the other pilot subjects in this age range.  Thanks!

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Re: [HCP-Users] ROIs and Betas from Cifti Data

[Glasser, Matthew]

If you are getting error messages, I recommend posting them.

Peace,

Matt.

From: "Michael F.W. Dreyfuss" 
mailto:mid2...@med.cornell.edu>>
Date: Tuesday, September 20, 2016 at 10:40 AM
To: Matt Glasser mailto:glass...@wustl.edu>>, Timothy 
Coalson mailto:tsc...@mst.edu>>
Cc: "hcp-users@humanconnectome.org" 
mailto:hcp-users@humanconnectome.org>>
Subject: Re: [HCP-Users] ROIs and Betas from Cifti Data


Thank you for this. We had explored this option in the past and two issues were 
1) there was not a parcellation readily available with subcortical structures 
and 2) I do not feel a need to constrain activation to parcels rather than 
swaths of signal as they appear to cluster themselves.


I'm sure parcellation is a valid approach, but I would really like to be able 
to simply report activation as it appears to cluster such as with TFCE, fdr or 
cluster thresholding (although that is less favored now) as has been typical in 
fMRI reporting. Are there examples available for these kinds of analysis to 
eventually relate activation to behavior or other measures?


I am grateful for all the help you have all provided. Things are quite close, 
and I hope to be able to be able to get through these last steps as quickly as 
possible.





From: Glasser, Matthew mailto:glass...@wustl.edu>>
Sent: Tuesday, September 20, 2016 11:06:10 AM
To: Michael F.W. Dreyfuss; NEUROSCIENCE tim
Cc: hcp-users@humanconnectome.org
Subject: Re: [HCP-Users] ROIs and Betas from Cifti Data

As Tim mentions, it sounds like you might want to use a parcellated analysis, 
as this will be more sensitive/powerful and you’ll know exactly what areas you 
are finding.  The HCP’s multi-modal parcellation is available here:

https://balsa.wustl.edu/study/show/RVVG

Also, the HCP’s task analysis pipeline will allow you to parcellate before 
fitting the GLM, rather than afterwards to get the addition SNR benefits from 
averaging across a parcel.

Peace,

Matt.

From: 
mailto:hcp-users-boun...@humanconnectome.org>>
 on behalf of "Michael F.W. Dreyfuss" 
mailto:mid2...@med.cornell.edu>>
Date: Monday, September 19, 2016 at 9:40 PM
To: Timothy Coalson mailto:tsc...@mst.edu>>
Cc: "Michael F.W. Dreyfuss" 
mailto:mid2...@med.cornell.edu>>, 
"hcp-users@humanconnectome.org" 
mailto:hcp-users@humanconnectome.org>>
Subject: Re: [HCP-Users] ROIs and Betas from Cifti Data

Thank you,

Are there any examples available for how to use this, possibly? I have been 
trying to figure these out, but there are a lot of options and  I am just not 
able to decipher how to use these from the help page alone. The errors I am 
getting also do not clarify what I need to do to get the output I am looking 
for.

Before using this kind of multi-band data I had been using afni. To give an 
example of what I would want to do in terms of afni commands (if that’s any 
help), I would have saved all ROIs and then used 3dmaskave to extract mean beta 
weights for a given GLM beta for each subject and then I would relate those 
beta weights so subject’s behavior in R or another stats package.

Definitely agree that there’s not much meaning to a peak coordinate per se. I’m 
just trying to figure out how to report the clusters I am finding. In previous 
reports we would typically focus on broadmann areas or more general regional 
nomenclature (i.e. vmPFC, mid temporal lobe, etc.). Some of the clusters I’m 
finding also cover large areas from motor to visual cortex, so I am trying to 
consider good ways to report that.

At this point I would prefer to use TFCE or some other thresholding method to 
identify contiguous swaths of volumetric and surface activation.

Thank you very much again,
Michael

On Sep 19, 2016, at 6:41 PM, Timothy Coalson 
mailto:tsc...@mst.edu>> wrote:


On Mon, Sep 19, 2016 at 4:51 PM, Michael F.W. Dreyfuss 
mailto:mid2...@med.cornell.edu>> wrote:

Thank you,


How can I turn the ROIs into a label file?

You can use -cifti-find-clusters if you just want spatial contiguity to define 
where ROIs should be considered separate, then use -cifti-label-import to make 
them into a dlabel file.

Also, how can I simply get a list of the ROIs with some information like 
cluster extent and peak voxel to be able to identify what part(s) of the brain 
each ROI is covering?

A single coordinate isn't a faithful representation of the cluster.  You can 
make a figure showing the clusters displayed on the brain (for instance, choose 
two of: beta maps, significance outlines, area outlines), and hopefully also 
provide the unthresholded beta and z maps for others to u

Re: [HCP-Users] Possible Typo in task fmri script

[Glasser, Matthew]

I agree that looks like a bug.  The reason this is here is incase one has an 
${fMRIName} that can be analyzed two different ways using different designs 
${fsfName}.

Peace,

Matt.

From: 
mailto:hcp-users-boun...@humanconnectome.org>>
 on behalf of Andrew Poppe mailto:poppe...@gmail.com>>
Date: Tuesday, September 20, 2016 at 11:06 AM
To: "hcp-users@humanconnectome.org" 
mailto:hcp-users@humanconnectome.org>>
Subject: [HCP-Users] Possible Typo in task fmri script

Hello,

I was recently adapting some of your great tfMRI analysis pipeline scripts for 
use with newly collected HCP-compliant data, and I noticed a line that I can't 
understand. In TaskfMRIAnalysis.v2.0.sh 
(called by TaskfMRIAnalysis.sh when "new" FSL versions are detected) on line 
126 it says:

LevelOnefsfNames=`echo $LevelOnefMRINames | sed 's/ /@/g'`

I may be misunderstanding something, so I thought I'd ask, but it seems to me 
that second variable should be $LevelOnefsfNames. Most likely, it won't cause a 
problem because by default the two variables are set to be identical in the 
TaskfMRIAnalysisBatch.sh script.

Thanks for any input about this line.

Thanks,

Andrew Poppe, Ph.D.
Postdoctoral Researcher
Olin Neuropsychiatry Research Center
Institute of Living
Hartford Hospital

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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] ROIs and Betas from Cifti Data

[Glasser, Matthew]

That makes sense if Z stats are not involved.

Matt.

From: "Harms, Michael" mailto:mha...@wustl.edu>>
Date: Tuesday, September 20, 2016 at 11:00 AM
To: Matt Glasser mailto:glass...@wustl.edu>>, "Michael F.W. 
Dreyfuss" mailto:mid2...@med.cornell.edu>>, Timothy 
Coalson mailto:tsc...@mst.edu>>
Cc: "hcp-users@humanconnectome.org" 
mailto:hcp-users@humanconnectome.org>>
Subject: Re: [HCP-Users] ROIs and Betas from Cifti Data


As an aside, if the end-game of the analysis is a permutation approach (e.g,. 
PALM) applied to GLM betas, then I wouldn’t expect it to make much difference 
in terms of power to detect an effect if you parcellate before fitting the 
Level 1 GLM, or if you simply average the betas from the dense maps within each 
parcel (and then use those average betas as input to the permutation testing).  
The latter approach would allow one to simply run -cifti-parcellate on the 
dense task maps that HCP has already pre-computed.

cheers,
-MH

--
Michael Harms, Ph.D.
---
Conte Center for the Neuroscience of Mental Disorders
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

From: 
mailto:hcp-users-boun...@humanconnectome.org>>
 on behalf of "Glasser, Matthew" mailto:glass...@wustl.edu>>
Date: Tuesday, September 20, 2016 at 10:06 AM
To: "Michael F.W. Dreyfuss" 
mailto:mid2...@med.cornell.edu>>, NEUROSCIENCE tim 
mailto:tsc...@mst.edu>>
Cc: "hcp-users@humanconnectome.org" 
mailto:hcp-users@humanconnectome.org>>
Subject: Re: [HCP-Users] ROIs and Betas from Cifti Data

As Tim mentions, it sounds like you might want to use a parcellated analysis, 
as this will be more sensitive/powerful and you’ll know exactly what areas you 
are finding.  The HCP’s multi-modal parcellation is available here:

https://balsa.wustl.edu/study/show/RVVG

Also, the HCP’s task analysis pipeline will allow you to parcellate before 
fitting the GLM, rather than afterwards to get the addition SNR benefits from 
averaging across a parcel.

Peace,

Matt.

From: 
mailto:hcp-users-boun...@humanconnectome.org>>
 on behalf of "Michael F.W. Dreyfuss" 
mailto:mid2...@med.cornell.edu>>
Date: Monday, September 19, 2016 at 9:40 PM
To: Timothy Coalson mailto:tsc...@mst.edu>>
Cc: "Michael F.W. Dreyfuss" 
mailto:mid2...@med.cornell.edu>>, 
"hcp-users@humanconnectome.org" 
mailto:hcp-users@humanconnectome.org>>
Subject: Re: [HCP-Users] ROIs and Betas from Cifti Data

Thank you,

Are there any examples available for how to use this, possibly? I have been 
trying to figure these out, but there are a lot of options and  I am just not 
able to decipher how to use these from the help page alone. The errors I am 
getting also do not clarify what I need to do to get the output I am looking 
for.

Before using this kind of multi-band data I had been using afni. To give an 
example of what I would want to do in terms of afni commands (if that’s any 
help), I would have saved all ROIs and then used 3dmaskave to extract mean beta 
weights for a given GLM beta for each subject and then I would relate those 
beta weights so subject’s behavior in R or another stats package.

Definitely agree that there’s not much meaning to a peak coordinate per se. I’m 
just trying to figure out how to report the clusters I am finding. In previous 
reports we would typically focus on broadmann areas or more general regional 
nomenclature (i.e. vmPFC, mid temporal lobe, etc.). Some of the clusters I’m 
finding also cover large areas from motor to visual cortex, so I am trying to 
consider good ways to report that.

At this point I would prefer to use TFCE or some other thresholding method to 
identify contiguous swaths of volumetric and surface activation.

Thank you very much again,
Michael

On Sep 19, 2016, at 6:41 PM, Timothy Coalson 
mailto:tsc...@mst.edu>> wrote:


On Mon, Sep 19, 2016 at 4:51 PM, Michael F.W. Dreyfuss 
mailto:mid2...@med.cornell.edu>> wrote:

Thank you,


How can I turn the ROIs into a label file?

You can use -cifti-find-clusters if you just want spatial contiguity to define 
where ROIs should be considered separate, then use -cifti-label-import to make 
them into a dlabel file.

Also, how can I simply get a list of the ROIs with some information like 
cluster extent and peak voxel to be able to identify what part(s) of the brain 
each ROI is covering?

A single coordinate isn't a faithful representation of the cluster.  You can 
make a figure showing the clusters displayed on the brain (for instance, choose 
two of: beta maps, significance outlines, area outlines), and hopefully also 
provide the unthresholded beta and z maps for others to use.

You can get cluster extent info with -cifti-weighted-stats.

If the question you want to ask is "which ar

Re: [HCP-Users] Brain Atlas

[Glasser, Matthew]

The data are available here: https://balsa.wustl.edu/study/show/RVVG

Peace,

Matt.

From: 
mailto:hcp-users-boun...@humanconnectome.org>>
 on behalf of Leslie Huszar 
mailto:lesliehuszarmd...@gmail.com>>
Date: Tuesday, September 20, 2016 at 11:46 AM
To: "hcp-users@humanconnectome.org" 
mailto:hcp-users@humanconnectome.org>>
Subject: [HCP-Users] Brain Atlas

To Whom it May Concern:

Dr. Huszar is wanting to find out how to view the Brain Atlas developed by Dr. 
Matthew Glasser and Dr. David Van Essen. He read the article in theNeurology 
Today Magazine: A New Brain Atlas Identifies 100 Brain Regions Never Before 
Mapped - Issue date September 8th, 2016 Volume 16 Issue 17. However, there was 
no reference on how to obtain the actual atlas. Your help in this matter is 
greatly appreciated.

Thank you!

Jocelyn
Dr. Leslie Huszar MD PSC

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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 
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[HCP-Users] Brain Atlas

[Leslie Huszar]

To Whom it May Concern:

Dr. Huszar is wanting to find out how to view the Brain Atlas developed by
Dr. Matthew Glasser and Dr. David Van Essen. He read the article in the*
Neurology Today Magazine:* *A New Brain Atlas Identifies 100 Brain Regions
Never Before Mapped* - Issue date September 8th, 2016 Volume 16 Issue 17.
However, there was no reference on how to obtain the actual atlas. Your
help in this matter is greatly appreciated.

Thank you!

Jocelyn
Dr. Leslie Huszar MD PSC

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[HCP-Users] Lifespan Pilot Subject Scans

[David Baric Parker]

Hello, All.

  We're interested in examining scans of older (65-75) brains, and as such
have great interest in your lifespan study.  We understand that it's in the
pilot stages, however after examining "The WU-Minn HCP Lifespan Pilot
Project" Preliminary report, submitted in Feb. 2015, we see from table 1
that there should be 20 complete or in progress scans from WUSTL and 23
complete or in progress scans from MINN.  Currently, there are only 5
subjects in the 65-75 age range released on the connectomeDB.  We were
wondering if there's any way to get access to the other pilot subjects in
this age range.  Thanks!

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[HCP-Users] Palm and Variance

[Michael F.W. Dreyfuss]

Hello,


Is there anyway to include subject-level variance estimates when running palm 
on a group level? Different subjects in my tfMRI study have different numbers 
of correct trials modeled in their GLMs, so confidence around each subject's 
estimate is variable. Seems it would be optimal to account for that in some way 
if possible, although probably would be computationally extremely burdensome.


Thank you,

Michael

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[HCP-Users] Possible Typo in task fmri script

[Andrew Poppe]

Hello,

I was recently adapting some of your great tfMRI analysis pipeline scripts
for use with newly collected HCP-compliant data, and I noticed a line that
I can't understand. In TaskfMRIAnalysis.v2.0.sh (called by
TaskfMRIAnalysis.sh when "new" FSL versions are detected) on line 126 it
says:

LevelOnefsfNames=`echo $LevelOnefMRINames | sed 's/ /@/g'`

I may be misunderstanding something, so I thought I'd ask, but it seems to
me that second variable should be $LevelOnefsfNames. Most likely, it won't
cause a problem because by default the two variables are set to be
identical in the TaskfMRIAnalysisBatch.sh script.

Thanks for any input about this line.

Thanks,

Andrew Poppe, Ph.D.
Postdoctoral Researcher
Olin Neuropsychiatry Research Center
Institute of Living
Hartford Hospital

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Re: [HCP-Users] ROIs and Betas from Cifti Data

[Harms, Michael]

As an aside, if the end-game of the analysis is a permutation approach (e.g,. PALM) applied to GLM betas, then I wouldn’t expect it to make much difference in terms of power to detect an effect if you parcellate before fitting the Level 1 GLM, or if you
 simply average the betas from the dense maps within each parcel (and then use those average betas as input to the permutation testing).  The latter approach would allow one to simply run -cifti-parcellate on the dense task maps that HCP has already pre-computed.


cheers,
-MH




-- 
Michael Harms, Ph.D.

---
Conte Center for the Neuroscience of Mental Disorders
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






From:  on behalf of "Glasser, Matthew" 
Date: Tuesday, September 20, 2016 at 10:06 AM
To: "Michael F.W. Dreyfuss" , NEUROSCIENCE tim 
Cc: "hcp-users@humanconnectome.org" 
Subject: Re: [HCP-Users] ROIs and Betas from Cifti Data





As Tim mentions, it sounds like you might want to use a parcellated analysis, as this will be more sensitive/powerful and you’ll know exactly what areas you are finding.  The HCP’s multi-modal parcellation is available here:


https://balsa.wustl.edu/study/show/RVVG  


Also, the HCP’s task analysis pipeline will allow you to parcellate before fitting the GLM, rather than afterwards to get the addition SNR benefits from averaging across a parcel.  


Peace,


Matt.




From:  on behalf of "Michael F.W. Dreyfuss" 
Date: Monday, September 19, 2016 at 9:40 PM
To: Timothy Coalson 
Cc: "Michael F.W. Dreyfuss" , "hcp-users@humanconnectome.org" 
Subject: Re: [HCP-Users] ROIs and Betas from Cifti Data





Thank you,


Are there any examples available for how to use this, possibly? I have been trying to figure these out, but there are a lot of options and  I am just not able to decipher how to use these from the help page alone. The errors I am getting also
 do not clarify what I need to do to get the output I am looking for.


Before using this kind of multi-band data I had been using afni. To give an example of what I would want to do in terms of afni commands (if that’s any help), I would have saved all ROIs and then used 3dmaskave to extract mean beta weights for
 a given GLM beta for each subject and then I would relate those beta weights so subject’s behavior in R or another stats package. 


Definitely agree that there’s not much meaning to a peak coordinate per se. I’m just trying to figure out how to report the clusters I am finding. In previous reports we would typically focus on broadmann areas or more general regional nomenclature
 (i.e. vmPFC, mid temporal lobe, etc.). Some of the clusters I’m finding also cover large areas from motor to visual cortex, so I am trying to consider good ways to report that.


At this point I would prefer to use TFCE or some other thresholding method to identify contiguous swaths of volumetric and surface activation.


Thank you very much again,
Michael





On Sep 19, 2016, at 6:41 PM, Timothy Coalson  wrote:




On Mon, Sep 19, 2016 at 4:51 PM, Michael F.W. Dreyfuss 
 wrote:



Thank you,


How can I turn the ROIs into a label file?



You can use -cifti-find-clusters if you just want spatial contiguity to define where ROIs should be considered separate, then use -cifti-label-import to make them into a dlabel file.



Also, how can I simply get a list of the ROIs with some information like cluster extent and peak voxel to be able to identify what part(s) of the brain each ROI is covering?



A single coordinate isn't a faithful representation of the cluster.  You can make a figure showing the clusters displayed on the brain (for instance, choose two of: beta maps, significance outlines, area outlines), and hopefully also provide the
 unthresholded beta and z maps for others to use.


You can get cluster extent info with -cifti-weighted-stats.


If the question you want to ask is "which areas are involved", you could do a parcellated analysis instead of a cluster analysis.



Thank you,
Michael


From: Timothy Coalson 
Sent: Monday, September 19, 2016 4:48:28 PM
To: Michael F.W. Dreyfuss
Cc: 
hcp-users@humanconnectome.org
Subject: Re: [HCP-Users] ROIs and Betas from Cifti Data
 




The wb_command -cifti-weighted-stats command with -mean is probably what you want (outputs a number to the command line), though you'll need to have each ROI as a separ

Re: [HCP-Users] ROIs and Betas from Cifti Data

[Michael F.W. Dreyfuss]

Thank you for this. We had explored this option in the past and two issues were 
1) there was not a parcellation readily available with subcortical structures 
and 2) I do not feel a need to constrain activation to parcels rather than 
swaths of signal as they appear to cluster themselves.


I'm sure parcellation is a valid approach, but I would really like to be able 
to simply report activation as it appears to cluster such as with TFCE, fdr or 
cluster thresholding (although that is less favored now) as has been typical in 
fMRI reporting. Are there examples available for these kinds of analysis to 
eventually relate activation to behavior or other measures?


I am grateful for all the help you have all provided. Things are quite close, 
and I hope to be able to be able to get through these last steps as quickly as 
possible.





From: Glasser, Matthew mailto:glass...@wustl.edu>>
Sent: Tuesday, September 20, 2016 11:06:10 AM
To: Michael F.W. Dreyfuss; NEUROSCIENCE tim
Cc: hcp-users@humanconnectome.org
Subject: Re: [HCP-Users] ROIs and Betas from Cifti Data

As Tim mentions, it sounds like you might want to use a parcellated analysis, 
as this will be more sensitive/powerful and you’ll know exactly what areas you 
are finding.  The HCP’s multi-modal parcellation is available here:

https://balsa.wustl.edu/study/show/RVVG

Also, the HCP’s task analysis pipeline will allow you to parcellate before 
fitting the GLM, rather than afterwards to get the addition SNR benefits from 
averaging across a parcel.

Peace,

Matt.

From: 
mailto:hcp-users-boun...@humanconnectome.org>>
 on behalf of "Michael F.W. Dreyfuss" 
mailto:mid2...@med.cornell.edu>>
Date: Monday, September 19, 2016 at 9:40 PM
To: Timothy Coalson mailto:tsc...@mst.edu>>
Cc: "Michael F.W. Dreyfuss" 
mailto:mid2...@med.cornell.edu>>, 
"hcp-users@humanconnectome.org" 
mailto:hcp-users@humanconnectome.org>>
Subject: Re: [HCP-Users] ROIs and Betas from Cifti Data

Thank you,

Are there any examples available for how to use this, possibly? I have been 
trying to figure these out, but there are a lot of options and  I am just not 
able to decipher how to use these from the help page alone. The errors I am 
getting also do not clarify what I need to do to get the output I am looking 
for.

Before using this kind of multi-band data I had been using afni. To give an 
example of what I would want to do in terms of afni commands (if that’s any 
help), I would have saved all ROIs and then used 3dmaskave to extract mean beta 
weights for a given GLM beta for each subject and then I would relate those 
beta weights so subject’s behavior in R or another stats package.

Definitely agree that there’s not much meaning to a peak coordinate per se. I’m 
just trying to figure out how to report the clusters I am finding. In previous 
reports we would typically focus on broadmann areas or more general regional 
nomenclature (i.e. vmPFC, mid temporal lobe, etc.). Some of the clusters I’m 
finding also cover large areas from motor to visual cortex, so I am trying to 
consider good ways to report that.

At this point I would prefer to use TFCE or some other thresholding method to 
identify contiguous swaths of volumetric and surface activation.

Thank you very much again,
Michael

On Sep 19, 2016, at 6:41 PM, Timothy Coalson 
mailto:tsc...@mst.edu>> wrote:


On Mon, Sep 19, 2016 at 4:51 PM, Michael F.W. Dreyfuss 
mailto:mid2...@med.cornell.edu>> wrote:

Thank you,


How can I turn the ROIs into a label file?

You can use -cifti-find-clusters if you just want spatial contiguity to define 
where ROIs should be considered separate, then use -cifti-label-import to make 
them into a dlabel file.

Also, how can I simply get a list of the ROIs with some information like 
cluster extent and peak voxel to be able to identify what part(s) of the brain 
each ROI is covering?

A single coordinate isn't a faithful representation of the cluster.  You can 
make a figure showing the clusters displayed on the brain (for instance, choose 
two of: beta maps, significance outlines, area outlines), and hopefully also 
provide the unthresholded beta and z maps for others to use.

You can get cluster extent info with -cifti-weighted-stats.

If the question you want to ask is "which areas are involved", you could do a 
parcellated analysis instead of a cluster analysis.

Thank you,

Michael


From: Timothy Coalson mailto:tsc...@mst.edu>>
Sent: Monday, September 19, 2016 4:48:28 PM
To: Michael F.W. Dreyfuss
Cc: hcp-users@humanconnectome.org
Subjec

Re: [HCP-Users] hcp pipeline problem

[Glasser, Matthew]

It's probably best to post these kinds of questions to the HCP Users list for 
faster support.  Is this happening on clean runs of the latest version of the 
HCP Pipelines?  If so, perhaps posting the output of fslhd on the various input 
images would reveal the problem.

Peace,

Matt.

From: Sung Yu mailto:s...@mprc.umaryland.edu>>
Date: Monday, September 19, 2016 at 2:39 PM
To: Peter Kochunov mailto:pkochu...@gmail.com>>, Matt 
Glasser mailto:glass...@wustl.edu>>
Subject: Re: hcp pipeline problem

hi Matt,
we recently had MRI upgrade and HCP script is not working anymore. here is the 
error message from PreFreeSurferPipeline.sh.


WARNING:: Inconsistent orientations for individual images when attempting to 
merge.

Merge will use voxel-based orientation which is probably incorrect - *PLEASE 
CHECK*!

Error in size-match along non-concatenated dimension for input file: 
/home/tomcat/Library/Data/HCP//ACP1086/T2w/T2wToT1wDistortionCorrectAndReg/FieldMap/PhaseTwo_gdc
*

and i get this message when i try to run FreeSurferPipeline.sh

Image Exception : #22 :: ERROR: Could not open image 
/home/tomcat/Library/Data/HCP//ACP1086/T1w/T1w_acpc_dc_restore_brain

do you know how we can fix this problem?

thanks,
Sung

>>> Peter Kochunov mailto:pkochu...@gmail.com>> 9/19/2016 
>>> 3:26 PM >>>
Can you send an email to Matt Glassier?

On Mon, Sep 19, 2016 at 3:06 PM, Sung Yu 
mailto:s...@mprc.umaryland.edu>> wrote:
hi Peter,
the hcp scripts i ran actually created Diffusion/eddy directory so i didn't 
notice until today but it looks like there is error in pre-freesurfer and skip 
to diffusion script without running freesurfer and post-freesurfer. this is the 
error message.

WARNING:: Inconsistent orientations for individual images when attempting to 
merge.
Merge will use voxel-based orientation which is probably incorrect - *PLEASE 
CHECK*!
Error in size-match along non-concatenated dimension for input file: 
/home/tomcat/Library/Data/HCP//ACP1086/T2w/T2wToT1wDistortionCorrectAndReg/FieldMap/PhaseTwo_gdc
Image Exception : #22 :: ERROR: Could not open image 
/home/tomcat/Library/Data/HCP//ACP1086/T1w/T1w_acpc_dc_restore_brain

it supposes to create a file "T1w_acpc_dc_restore_brain".
looks like all the subject has same problem since the MRI upgrade and i am not 
sure how to fix this.
thanks,
Sung



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Re: [HCP-Users] Same data / Multiple comparisons ?

[Krieger, Donald N.]

Dear list,

Thanks to all and to you who engaged this puzzling and worrisome topic.
I appreciate the pointers to the MegaTrawl and OHBM COBIDAS reports linked in 
the correspondence below.
I agree that it’s not the role of the Human Connectome Project to police the 
results obtained with the data you provide.

I do think that there is a substantive contribution to be made with an analysis 
of this issue, a list of cautions, and at least a partial list of scenarios 
which either do or do not pose problems with suggested approaches to dealing 
with the problems.
For the universe of researchers, I don’t think we’re doing as well as we could 
by simple honest reporting of the comparisons we’ve made.
After all, that’s really been incumbent on all of us prior to this.
And it doesn’t really address how we even satisfy ourselves as individual 
researchers that we’re not being fooled by our own results from HCP data.

This problem is not confined to HCP data nor is its domain confined to human 
brain imaging, e.g. there are numerous tumor registries which, to my 
understanding, face the same issue.
A letter to a journal with wide scope would, I hope, be welcomed by editors and 
be of real value to the scientific community.
Had I the requisite knowledge and understanding, I would do the thinking and 
write it.
I hope that one or more of you will consider this .

Best - Don

From: Stephen Smith [mailto:st...@fmrib.ox.ac.uk]
Sent: Wednesday, September 14, 2016 9:02 AM
To: Thomas Nichols
Cc: Krieger, Donald N.; hcp-users@humanconnectome.org
Subject: Re: [HCP-Users] Same data / Multiple comparisons ?

Hi Tom

actually the MegaTrawl latest version is here:
https://db.humanconnectome.org/megatrawl/index.html

But yes indeed - early on within the HCP we discussed options for trying to 
deal with this large-scale-multiple-comparisons-problem, but quickly agreed 
that it really wasn't our role (and wasn't practical) for us to try to "police" 
on this issue.Another possible form of "policing" would be to keep-back a 
truly-left-out sample of subjects, but there were too many ethical, practical 
and statistical problems with that.   We also (light-heartedly!) discussed 
having some kind of "multiple-comparison sin counter" that ticks up every time 
someone does a new analysis  ;-)   but as you say there was no 
straightforward solution presenting itself...

Cheers.





On 14 Sep 2016, at 13:52, Thomas Nichols 
mailto:t.e.nich...@warwick.ac.uk>> wrote:

Dear Don, (Simon?)

I see two classes of use for the HCP data sets.
(1)The HCP participant results may be used as norms for comparison with 
matched participants from whom we capture measures which may be compared.
(2)The HCP participant results may be used exclusively.

I think it is only the latter, (2), for which there is a problem although I 
certainly could be wrong.

I agree, the first doesn't have multiplicity problems (though accuracy with 
which you can match subjects & scanner data is another concern).

 Tom, you used the scenario of a bunch of labs using the data to do one test 
each and stated: “…I would say that requires a 'science-wide' correction 
applied by the reader of the 250 papers. …”
That gets at what I’m asking.
If I’m the author of one of those papers, I don’t want to be fooled or to fool 
any of my readers with the results from my laboratory by failing to correct for 
all the other comparisons which have been run on the same data.

Yes, but the basic problem you, the individual author, face is what sort of 
correction should you apply.  You only studied variable #132; should you do a 
correction just for the 20 others in that domain, or all 250?  That's why I 
think all you can do is be open, and honestly report the scope of variables you 
considered (and if you did, e.g., search over 20 variables in a domain, correct 
over those), and report your result.  If the reader collects your result with 
50 other papers they can use the appropriate level of criticism for that 
collection, which will be different from a reader that collects 250 papers 
measures for consideration.

 If I do that now, perhaps it’s workable to take account of all the work which 
has appeared to date to do the correction for multiple comparisons.
But what about a laboratory which runs some other test 5 years from now?
They must use a more stringent criterion given all the additional results which 
have since been published.
At some point, it will become impossible to find a reliable result.

Exactly.

Of course, these notions apply to reviewers and other readers too which places 
a new level of responsibility on them compared with reading papers today.
For editors and reviewers, the problem is particularly acute.
If the authors of a paper used the correction criterion suggested by their 
isolated analysis but a ‘science-wide’ reading calls for a more stringent 
criterion, do they bounce the paper back or accept it?

As you point out, Tom, there’s no simple answers to

Re: [HCP-Users] ROIs and Betas from Cifti Data

[Glasser, Matthew]

As Tim mentions, it sounds like you might want to use a parcellated analysis, 
as this will be more sensitive/powerful and you’ll know exactly what areas you 
are finding.  The HCP’s multi-modal parcellation is available here:

https://balsa.wustl.edu/study/show/RVVG

Also, the HCP’s task analysis pipeline will allow you to parcellate before 
fitting the GLM, rather than afterwards to get the addition SNR benefits from 
averaging across a parcel.

Peace,

Matt.

From: 
mailto:hcp-users-boun...@humanconnectome.org>>
 on behalf of "Michael F.W. Dreyfuss" 
mailto:mid2...@med.cornell.edu>>
Date: Monday, September 19, 2016 at 9:40 PM
To: Timothy Coalson mailto:tsc...@mst.edu>>
Cc: "Michael F.W. Dreyfuss" 
mailto:mid2...@med.cornell.edu>>, 
"hcp-users@humanconnectome.org" 
mailto:hcp-users@humanconnectome.org>>
Subject: Re: [HCP-Users] ROIs and Betas from Cifti Data

Thank you,

Are there any examples available for how to use this, possibly? I have been 
trying to figure these out, but there are a lot of options and  I am just not 
able to decipher how to use these from the help page alone. The errors I am 
getting also do not clarify what I need to do to get the output I am looking 
for.

Before using this kind of multi-band data I had been using afni. To give an 
example of what I would want to do in terms of afni commands (if that’s any 
help), I would have saved all ROIs and then used 3dmaskave to extract mean beta 
weights for a given GLM beta for each subject and then I would relate those 
beta weights so subject’s behavior in R or another stats package.

Definitely agree that there’s not much meaning to a peak coordinate per se. I’m 
just trying to figure out how to report the clusters I am finding. In previous 
reports we would typically focus on broadmann areas or more general regional 
nomenclature (i.e. vmPFC, mid temporal lobe, etc.). Some of the clusters I’m 
finding also cover large areas from motor to visual cortex, so I am trying to 
consider good ways to report that.

At this point I would prefer to use TFCE or some other thresholding method to 
identify contiguous swaths of volumetric and surface activation.

Thank you very much again,
Michael

On Sep 19, 2016, at 6:41 PM, Timothy Coalson 
mailto:tsc...@mst.edu>> wrote:


On Mon, Sep 19, 2016 at 4:51 PM, Michael F.W. Dreyfuss 
mailto:mid2...@med.cornell.edu>> wrote:

Thank you,


How can I turn the ROIs into a label file?

You can use -cifti-find-clusters if you just want spatial contiguity to define 
where ROIs should be considered separate, then use -cifti-label-import to make 
them into a dlabel file.

Also, how can I simply get a list of the ROIs with some information like 
cluster extent and peak voxel to be able to identify what part(s) of the brain 
each ROI is covering?

A single coordinate isn't a faithful representation of the cluster.  You can 
make a figure showing the clusters displayed on the brain (for instance, choose 
two of: beta maps, significance outlines, area outlines), and hopefully also 
provide the unthresholded beta and z maps for others to use.

You can get cluster extent info with -cifti-weighted-stats.

If the question you want to ask is "which areas are involved", you could do a 
parcellated analysis instead of a cluster analysis.

Thank you,

Michael


From: Timothy Coalson mailto:tsc...@mst.edu>>
Sent: Monday, September 19, 2016 4:48:28 PM
To: Michael F.W. Dreyfuss
Cc: hcp-users@humanconnectome.org
Subject: Re: [HCP-Users] ROIs and Betas from Cifti Data

The wb_command -cifti-weighted-stats command with -mean is probably what you 
want (outputs a number to the command line), though you'll need to have each 
ROI as a separate file and run it separately for each of them.  Alternatively, 
if you turned the ROIs into a label file, you could get -cifti-parcellate to 
make a file where each parcel contains the answer for an ROI.

Tim


On Mon, Sep 19, 2016 at 3:26 PM, Michael F.W. Dreyfuss 
mailto:mid2...@med.cornell.edu>> wrote:

Hello, I have run palm with TFCE on my group level data successfully for a task 
based fMRI study (yay!), and I would like to be able to identify ROIs from my 
cifti data (both surface and volume). I then want to extract subject level beta 
weights for a given condition from those ROIs to relate those betas to behavior 
(offline). Are there simple ways to: 1) identify regions implicated on the 
group level and 2) extract subject-level beta weights from them, such as with 
wb_command?


Thank you,

Michael

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