Dear Dr. Nieto-Castanon

I am currently working with multivariate ROI-to-ROI connectivity (mRRC) analysis and would like to clarify the interpretation of mRRC values, particularly in the context of effective connectivity.

My question concerns the asymmetry observed in mRRC values depending on whether a specific ROI is set as a seed or as a target. I have noticed that when a particular ROI is used as the seed, it shows strong mRRC values with other ROIs. However, when the same ROI is instead used as a target, its mRRC values appear relatively weaker.

Given this pattern, would it be valid to interpret this specific ROI as a key regulatory region that directly modulates the activity of other ROIs? In other words, does a strong mRRC value when an ROI is a seed indicate that it has a stronger direct influence over its target ROIs, while a weaker mRRC as a target suggests that it is less influenced by other regions?

Additionally, I would like to understand whether the computation of mRRC inherently reflects effective connectivity in the sense that it captures directed regulatory relationships rather than just statistical associations. Dynamic Causal Modeling (DCM) and Granger Causality Analysis (GCA) typically incorporate temporal information to infer causal relationships. However, my primary interest is not in the temporal precedence of activity but rather in determining whether a specific region exerts a directional regulatory influence over another region. Given this objective, can mRRC be used to infer such directed regulatory relationships?

I would greatly appreciate any clarification you can provide on this matter. Thank you in advance for your time and insights.

Best wishes,
Junhyeok Jang