Dear FSL experts,
I am working the between-network connectivity with FSLNets and have some questions about the nets hierarchy algorithm:
After computing the group-average netmat summaries (T-maps and then, Z transformation), I got my nice nets-hierarchy matrix. According to the description, I should be able to associate the different branches of the tree with large-scale
brain networks from the literature. I was wondering if this association could only be seen in the full correlation analyses because my partial correlation yields different results. I used a partial correlation because I thought it is better to take into account
the shared variance between components.
The second question is: In case the partial correlation is a valid way to go on, is it also more informative to try to correlate the partial correlation coefficient with certain behavioral score to see the modulation of this score in the
between-network analysis? Or should I stick to the full correlation coefficient from the beginning?
Thanks a lot for your attention
--
Yacila Deza Araujo, M.Sc. Neuropsych.
PhD Student
Technische Universität Dresden
Faculty of Medicine Carl Gustav Carus
Department of Psychiatry & Psychotherapy
Section of Systems Neuroscience
Würzburger Straße 35
01187 Dresden
Germany