Re: [HCP-Users] A question about brain registration matrix

[Glasser, Matthew]

This is a deformed spherical surface, not a warpfield or affine matrix as you 
might be used to using, however, we do provide this:

${StudyFolder}/${Subject}/MNINonLinear/Native/${Subject}.L.sphere.MSMAll.native.surf.gii
${StudyFolder}/${Subject}/MNINonLinear/Native/${Subject}.R.sphere.MSMAll.native.surf.gii

What is it specifically that you need to do?

Peace,

Matt.

From: 
>
 on behalf of Aaron C >
Date: Sunday, November 19, 2017 at 9:38 PM
To: "hcp-users@humanconnectome.org" 
>
Subject: [HCP-Users] A question about brain registration matrix


Dear HCP experts,

I have a question about the transformation matrix aligning the raw data to the 
MSM-All registered data. Could I find the file of this matrix in the 
preprocessed data? Thank you.


___
HCP-Users mailing list
HCP-Users@humanconnectome.org
http://lists.humanconnectome.org/mailman/listinfo/hcp-users

___
HCP-Users mailing list
HCP-Users@humanconnectome.org
http://lists.humanconnectome.org/mailman/listinfo/hcp-users

Re: [HCP-Users] MEG resting state

[A Nunes]

Hi Giorgos,

Thanks, I did not know about ft_megrealign. Idially I would like to just
concatenate the data in the sensor level. I recently realized that between
recordings the sensor position varies up to 0.2 meters in
data.grad.chanpos. This is because the order of the sensors are different
between recordings, I don't know why though. In data.grad.labelorg it shows
the right order, however I have the impression that the order of the
sensors in the covariance matrix is based in chanpos because separate
recording have smaller rank than concatenating which has full rank. When
reading the data file FT gives me the warning 'Your data and configuration
allow for multiple sensor definitions.' maybe this is related.

Do you know how to approach this? Maybe I should somehow specify that the
right order is in data.grad.labelorg rather than data.grad.label?

Thanks
Adonay

On Fri, Nov 17, 2017 at 5:15 AM, Michalareas, Georgios 
wrote:

> Hi Adoney,
> The released data has been only 7.5 mm maximum movement within scan.
> So the sensor positions should be quite close in all three resting state
> scans.
> ICA was done with all three sessions concatenated together.
> So I believe it should be one to concatenate them for your analysis too
> and assume sensors are more or less on same location.
> If you want to treat each different scan separately then you have to
> follow different strategies like:
> -Perform beamforming for each session separately and project each session
> separately into source space and then concatenate data in source space and
> do further analysis there.
> -Make a virtual gradiometer array as the mean of the three gradiometer
> positions in the three scans and then interpolate the data of each session
> to this virtual MEG sensors using Fieltrip’s function ft_megrealign and
> then combine all data in this virtual sensor space. Keep in mind that this
> projects the data into source space and projects it back to the virtual
> sensor space.
>
> I hope this helps
> Best
> Giorgos
>
> From:  on behalf of A Nunes <
> adonay.s.nu...@gmail.com>
> Date: Thursday, 16. November 2017 at 21:56
> To: "hcp-users@humanconnectome.org" 
> Subject: [HCP-Users] MEG resting state
>
> Hi,
>
> The MEG resting state data is split in three sessions, is it possible to
> append the data before computing the covariance matrix?
> I have some doubts because the sensor position might change between the
> recordings and if ICA was done separately, then the rank would change
> between sessions and I don't know how would this affect beamforming.
>
> Any suggestions?
>
> Thanks
> Adonay
>
> ___
> HCP-Users mailing list
> HCP-Users@humanconnectome.org
> http://lists.humanconnectome.org/mailman/listinfo/hcp-users
>

___
HCP-Users mailing list
HCP-Users@humanconnectome.org
http://lists.humanconnectome.org/mailman/listinfo/hcp-users