Ah k.
Yes I’d be interested to hear what you guys think is the best option out of 1) 
running all tractography from ROIs generated from the Atlas_ files to easily 
generated a group average connectivity matrix or 2) run from subject specific 
ROIs and then deal with the issue of comparisons afterwards.

Cheers,
Linden

——————————————————————

Linden Parkes

PhD Candidate
Monash Clinical & Imaging Neuroscience (MCIN)
School of Psychological Sciences
Monash Biomedical Imaging
Monash University

A: 770 Blackburn Rd, Clayton, 3168, Vic, Australia
T: +61 3 9902 9807  |  0402 516 574
E: [email protected]
W: www.med.monash.edu.au/psych/mcin/



From: Glasser, Matthew <[email protected]>
Reply: Glasser, Matthew <[email protected]>>
Date: 5 November 2014 at 2:02:49 am
To: Linden Parkes <[email protected]>>
Cc: [email protected] <[email protected]>>, Stamatios 
Sotiropoulos <[email protected]>>
Subject:  Re: [HCP-Users] MNINonLinear ROIs  

Not perfectly.  If you wanted to use the individual ones though, you would need 
to resample the results from the individual ROIs to the atlas ones before 
comparing.  Stam has thought a lot about this, so I would be interested in his 
opinion.

Thanks,

Matt.

From: Linden Parkes <[email protected]>
Date: Tuesday, November 4, 2014 at 12:30 AM
To: Matt Glasser <[email protected]>
Cc: "[email protected]" <[email protected]>
Subject: Re: [HCP-Users] MNINonLinear ROIs

As a side note. Wouldn't using the Atlas_ variant to generate ROIs for 
tractography mean that for each participant the ROIs are going to include some 
of the surrounding white matter? 
Does using the xfms transforms account for this?

On 4 November 2014 10:07, Glasser, Matthew <[email protected]> wrote:
Yes, that would allow the results to have corresponding indices across subjects 
(like standard meshes do on the surface).

Peace,

Matt.

From: Linden Parkes <[email protected]>
Date: Monday, November 3, 2014 at 4:21 PM
To: Matt Glasser <[email protected]>, "[email protected]" 
<[email protected]>
Subject: Re: [HCP-Users] MNINonLinear ROIs

Ok cool. So then if I want to generate connectivity matrixes based on seed to 
target connectivity and then average that across subjects I’d be better served 
by using the Atlas_ variants?

Cheers,
Linden

——————————————————————

Linden Parkes

PhD Candidate
Monash Clinical & Imaging Neuroscience (MCIN)
School of Psychological Sciences
Monash Biomedical Imaging
Monash University

A: 770 Blackburn Rd, Clayton, 3168, Vic, Australia
T: +61 3 9902 9807  |  0402 516 574
E: [email protected]
W: www.med.monash.edu.au/psych/mcin/

B7AE8BF0-4F0C-4F0B-9BDE-B582B9331FA1

From: Glasser, Matthew <[email protected]>
Reply: Glasser, Matthew <[email protected]>>
Date: 4 November 2014 at 1:11:15 am
To: Linden Parkes <[email protected]>>, 
[email protected]<[email protected]>>
Subject:  Re: [HCP-Users] MNINonLinear ROIs

The files with “Atlas_” are the same across all individuals, whereas the ones 
without are individual specific.

Peace,

Matt.

From: Linden Parkes <[email protected]>
Date: Monday, November 3, 2014 at 1:08 AM
To: "[email protected]" <[email protected]>
Subject: [HCP-Users] MNINonLinear ROIs

Hi all,

In the MNINonLinear directories there are 4 files:
ROIs.2
wmparc.2
Atlas_ROIs.2
Atlas_wmparc.2

What is the difference between the files with the prefix and those without? 
When generating MNI ROIs for use with probtrackx2 which files should be used?

Cheers,
Linden

——————————————————————

Linden Parkes

PhD Candidate
Monash Clinical & Imaging Neuroscience (MCIN)
School of Psychological Sciences
Monash Biomedical Imaging
Monash University

A: 770 Blackburn Rd, Clayton, 3168, Vic, Australia
T: +61 3 9902 9807  |  0402 516 574
E: [email protected]
W: www.med.monash.edu.au/psych/mcin/

B7AE8BF0-4F0C-4F0B-9BDE-B582B9331FA1
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