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help > RE: Graph-theory in conn
Jul 10, 2012 08:07 AM | Alfonso Nieto-Castanon - Boston University
RE: Graph-theory in conn
Hi Igor,
You are right that the 'results' tab is for second-level analyses (to perform inferences about the population) so it requires multiple subjects. In any particular analysis, beta values represent effect sizes, T-values are the statistics, p-unc represent the false positive level of each individual test, and p-FDR represents the false discovery rate (a correction of the false positive level to account for multiple comparisons). All of these values depend on the actual contrasts that you choose for your second-level analyses. If you want to explore manually the graph-theory measures (e.g. global efficiency) for each subject 'export data' will create a .csv and a .network file with this information (the .network file can be loaded directly from matlab; the only reason I can think that would result in this files being 'empty' would be if you are using an overly conservative adjacency matrix threshold). If you want to explore the ROI-to-ROI connectivity matrix manually question 14 in the FAQ (http://www.alfnie.com/software/conn) should point you in the right direction.
Hope this helps
Alfonso
Originally posted by Igor M:
You are right that the 'results' tab is for second-level analyses (to perform inferences about the population) so it requires multiple subjects. In any particular analysis, beta values represent effect sizes, T-values are the statistics, p-unc represent the false positive level of each individual test, and p-FDR represents the false discovery rate (a correction of the false positive level to account for multiple comparisons). All of these values depend on the actual contrasts that you choose for your second-level analyses. If you want to explore manually the graph-theory measures (e.g. global efficiency) for each subject 'export data' will create a .csv and a .network file with this information (the .network file can be loaded directly from matlab; the only reason I can think that would result in this files being 'empty' would be if you are using an overly conservative adjacency matrix threshold). If you want to explore the ROI-to-ROI connectivity matrix manually question 14 in the FAQ (http://www.alfnie.com/software/conn) should point you in the right direction.
Hope this helps
Alfonso
Originally posted by Igor M:
It looks like I solved the above problem by
running an analysis with 2 participants instead of just 1.
Results are now showing up in the "Network theory" window.
My question now is how to interpret these.
What are the "beta, T, p-unc, and p-FDR" values related to?
Are these based on the contrast that was set up in the "second-level Results" window?
What if I just want to look at the Global efficiency of a network based on all nodes and don't want a group contrast?
How do you display the actual parameters (i.e. actual "global efficiency")?
How do you display the correlation matrix between ROIs?
"Export data" creates one .csv file and a .dl file per subject, but these files are all empty for some reason.
Any help would be greatly appreciated.
Results are now showing up in the "Network theory" window.
My question now is how to interpret these.
What are the "beta, T, p-unc, and p-FDR" values related to?
Are these based on the contrast that was set up in the "second-level Results" window?
What if I just want to look at the Global efficiency of a network based on all nodes and don't want a group contrast?
How do you display the actual parameters (i.e. actual "global efficiency")?
How do you display the correlation matrix between ROIs?
"Export data" creates one .csv file and a .dl file per subject, but these files are all empty for some reason.
Any help would be greatly appreciated.
Threaded View
| Title | Author | Date |
|---|---|---|
| Igor M | Jul 9, 2012 | |
| Igor M | Jul 9, 2012 | |
| Alfonso Nieto-Castanon | Jul 10, 2012 | |
| Igor M | Jul 10, 2012 | |
| Alfonso Nieto-Castanon | Jul 11, 2012 | |
| Saman Sarraf | Jan 21, 2014 | |
| Igor M | Jul 12, 2012 | |
| Alfonso Nieto-Castanon | Jul 13, 2012 | |
| Igor M | Jul 21, 2012 | |
| Alfonso Nieto-Castanon | Jul 21, 2012 | |