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help > RE: Connected components in NBS
Dec 13, 2019 05:12 AM | Andrew Zalesky
RE: Connected components in NBS
Hi Anita,
Measuring component size with extent or intensity are both valid options and will in most cases yield comparable results. Component size measured using intensity can better capture large effect sizes that are circumscribed to a few connections only. In contrast, component size measured using extent can be more sensitive to spatially diffuse effects. You could try both methods. There is no right or wrong option.
I am not sure if I follow your second question. To visualize the significant network, you will need to provide the MNI coordinates of each node as a text file. Without coordinates, the software does not know where to position the nodes in the brain volume. Of course, you can still run the NBS and generate results without visualizing them, in which case it is not necessary to provide any coordinates. How the ROIs were defined should not affect the running of the NBS. NBS just sees the connectivity matrices for each sample/individual.
Andrew
Originally posted by asinha:
Measuring component size with extent or intensity are both valid options and will in most cases yield comparable results. Component size measured using intensity can better capture large effect sizes that are circumscribed to a few connections only. In contrast, component size measured using extent can be more sensitive to spatially diffuse effects. You could try both methods. There is no right or wrong option.
I am not sure if I follow your second question. To visualize the significant network, you will need to provide the MNI coordinates of each node as a text file. Without coordinates, the software does not know where to position the nodes in the brain volume. Of course, you can still run the NBS and generate results without visualizing them, in which case it is not necessary to provide any coordinates. How the ROIs were defined should not affect the running of the NBS. NBS just sees the connectivity matrices for each sample/individual.
Andrew
Originally posted by asinha:
Dr. Zalesky,
I am using the NBS toolbox to analyze differences between 2 population groups, in which I have one representative connectivity matrix (sample) for each subject. In regards to the "Advanced Settings" block in the GUI, how do we decide whether to use component size = extent vs. component size = intensity?
Also, is it related to the following statement from your 2010 paper, "The NBS is of no use if the contrast does not form a connected component. The following remarks pertain only to scenarios, where the contrast does form a component"? I don't have the MNI coordinates for the parcellation scheme I'm using, so I cannot generate brain figures of the significant connections, but I'm wondering if I can get "groups of connected components/connections" that are significant, since I'm using a large multi-network ROI atlas?
Thank you for your time. I look forward to hearing from you soon.
Regards,
Anita
I am using the NBS toolbox to analyze differences between 2 population groups, in which I have one representative connectivity matrix (sample) for each subject. In regards to the "Advanced Settings" block in the GUI, how do we decide whether to use component size = extent vs. component size = intensity?
Also, is it related to the following statement from your 2010 paper, "The NBS is of no use if the contrast does not form a connected component. The following remarks pertain only to scenarios, where the contrast does form a component"? I don't have the MNI coordinates for the parcellation scheme I'm using, so I cannot generate brain figures of the significant connections, but I'm wondering if I can get "groups of connected components/connections" that are significant, since I'm using a large multi-network ROI atlas?
Thank you for your time. I look forward to hearing from you soon.
Regards,
Anita
Threaded View
| Title | Author | Date |
|---|---|---|
| asinha | Dec 12, 2019 | |
| Andrew Zalesky | Dec 13, 2019 | |
| asinha | Dec 13, 2019 | |
| Andrew Zalesky | Dec 14, 2019 | |
