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Subject:

Interpretation question - dual regression with all networks vs. single network

From:

Jacqueline Scholl <[log in to unmask]>

Reply-To:

FSL - FMRIB's Software Library <[log in to unmask]>

Date:

Thu, 11 Oct 2018 10:59:41 +0100

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text/plain

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Dear FSL experts,

I have a question about interpretation of my results: I have analysed my state data that compares two groups in two ways: I have A) either used a set of networks [from Yeo 2011, rather than my own gICA] and used the dual-regression approach or B) only used a single network of interest.  [I've done B as I notice that quite a few papers in the literature seem to use this approach instead of dual regression?] Results differ and I am trying to make sense of this.

For A) I followed the dual-regression manual. For B) I used only one network in the 'dual-regression' (so not really a dual-regression anymore).

With A) I find no group differences, but with B), I find that the network includes areas in one group that it doesn't in the other (specifically, the salience network also includes premotor areas in one group, but not in the other).

I am wondering how I could interpret this: what does it mean that when I control for other networks, it does not look like premotor area is part of the salience network in one group? 

Could it mean that:
1) actually the correlation between salience network and another network that includes the premotor area is changed? I.e. that premotor area is actually part of another network, not salience and that the relationship between these two networks has changed and in the absence of controlling for the other network it looks like premotor area is part of salience network? If this
was the case, should I see a change in correlation (with FSLnets) between salience network and the right network that includes premotor area? 

2) Or does it mean that actually activity in another network is changed? I.e. that say a network including premotor area has the same correlation with the salience network in the two groups, but more activity in the premotor area in one group; and in the absence of controlling for this other network it looks like premotor area is part of salience network? And in this case, should I be able to find another network that has the group difference rather than the salience network?

3) Are there any other possibilities I could test?

I would be very grateful for any pointers
Jacquie

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