Not sure exactly what you mean there by removing the group average effect.
In the design matrix?

I am now doing effectively that with a random subject, just wanted to draw
/ leech on the community to see if anyone was able to make an informed
recommendation about which subject to choose for the first registration
step.














On 1 April 2017 at 15:13, Glasser, Matthew <glass...@wustl.edu> wrote:

> That does seem like a lot of computations.  Why not pick a random
> individual, register to that and then remove the group average effect of
> registration, retaining the improved alignment across subjects while
> eliminating the bias caused by the initial subject?
>
> Peace,
>
> Matt.
>
> From: <hcp-users-boun...@humanconnectome.org> on behalf of John Griffiths
> <j.davidgriffi...@gmail.com>
> Date: Saturday, April 1, 2017 at 2:09 PM
> To: "hcp-users@humanconnectome.org" <hcp-users@humanconnectome.org>
> Subject: [HCP-Users] most typical subject for FA registration?
>
>
> Hello.
>
> I was wondering if anyone has done the all-to-all TBSS registration step
> on FA images from the WU-Minn data to find the most typical subject for
> two-step FNIRT FA registration?
>
> If so would it be possible to get the most typical subjects' IDs?
>
> This would save me (and I'm sure many others) a very hefty analysis step.
>
> Ta,
>
> john
>
>
>
>
>
> --
>
> Dr. John Griffiths
>
> Post-Doctoral Research Fellow
>
> Rotman Research Institute, Baycrest
>
> Toronto, Canada
>
> and
>
> Honorary Associate
>
> School of Physics
>
> University of Sydney
>
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-- 

Dr. John Griffiths

Post-Doctoral Research Fellow

Rotman Research Institute, Baycrest

Toronto, Canada

and

Honorary Associate

School of Physics

University of Sydney

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