Connectivity using AAL1

Dear Brainstorm Team,

  1. I am using the AAL1 brain atlas to identify my ROIs and get the number below in the connectivity matrix, as far as I understand from the connectivity tutorial this number doesn't reflect my data.

  1. When I use the function [GetConnectMatrix] I get a 4D matrix the first two dimensions are two sets of signals A and B what do these signals represent?

3)I am using Power spectrum density (Welch) to get the source power for my ROIs and I get 94 ROIs as below but the AAl Atlas as identified in brainstorm has 99 regions

  1. It was mentioned in a previous question: "To my knowledge, there are still no tools working correctly for connectivity analysis on unconstrained source models (3 dipoles with orthogonal directions for each 3D location). Therefore, I recommend doing your source analysis with constrained locations and constrained orientations."
    Help for connectivity pipeline - #3 by Francois
    but I am using volume source localization so I cannot use constrained

Kindly, address my inquiries.
Sincerely,
Abrar

The size is correct, MSC is symmetric connectivity metric, so only the lower triangle and the diagonal of the connectivity matrix are stored (all the other elements are redundant). Thus for 99 Scouts, 4950 elements are saved: these are the lower triangle (without diagonal) with 4851 elements ((99*99) - 99) / 2, and the 99 diagonal elements.

Those dimensions are the same as the number of Scouts, as you are computing connectivity NxN.

Check this link for more information on how the connectivity data is stored:
https://neuroimage.usc.edu/brainstorm/Tutorials/Connectivity#On_the_hard_drive

If you are using the same Atlas, you should have the same number of Scouts.
Please be sure that ALL the Scouts are selected in the GUI. In this example, one Scout is not selected, sometimes it is not as obvious, as unselected Scouts may be down in the list.

On the Scout list, you can use the shortcut Ctrl+A to ensure that all the Scouts are selected.

You are right, it is not possible to use constrained orientations with volume source spaces.

For unconstrained sources there are two main approaches:

  1. Unconstrained sources are flattened, so leading to constrained case
  2. Apply dimension reductions (3D to 1D), once connectivity metrics for all dimension combinations are computed.

Check this link to see the different ways how connectivity can be computed at the Scout level.

https://neuroimage.usc.edu/brainstorm/Tutorials/CorticomuscularCoherence#Coherence_Scouts_x_Scouts

1 Like

Thank you for your response, it is clearer now.
I will go through the suggested tutorial. But to make sure I have read all the documents, besides these:
https://neuroimage.usc.edu/brainstorm/Tutorials/Epilepsy
https://neuroimage.usc.edu/brainstorm/Tutorials/Connectivity#Coherence
https://neuroimage.usc.edu/brainstorm/Tutorials/Connectivity#Scout-level_connectivity
https://neuroimage.usc.edu/brainstorm/Tutorials/SourceEstimation
https://neuroimage.usc.edu/brainstorm/Tutorials/Scoutshttps://neuroimage.usc.edu/brainstorm/Tutorials/CorticomuscularCoherence#Method
https://neuroimage.usc.edu/brainstorm/Tutorials/ArtifactsFilter

Are there any documents I need to read to extract source power and connectivity for my ROIs using the parameters in the image to calculate the source?
And do I need to change the default parameters for source computation?

The steps to compute the spectral power and connectivity will not change if the sources are computed with different parameters. Check the links shared above, and let us know if you have any further question.

This depends on your research question, as you know there is not a "default" way to estimate sources.