Fig. 3. Whole-brain model provides causal insights into the functional hierarchy of movie-watching.

The figure shows how to identify the underlying causal mechanisms resulting in the different levels of hierarchy (i.e., NR) when movie-watching. (A) Procedure starts with fitting a whole-brain model, initially using the anatomical connectivity and then iteratively adjusting a GEC according to either fitting this to the empirical FC alone (G_FC) or including the NR (G_NR) matrices. (B) Upper row shows the optimization of the whole-brain model based on optimizing only with FC, while the lower row shows the same but including the optimization with NR. As can be seen in the leftmost panels, the evolution of learning improves the level of fit to FC (correlation between empirical and simulated matrices, black curves) in both cases but only fitting the FC does not give a good fit to the empirical NR (see red curves). The second column of panels show the optimized GEC matrices (G_FC and G_NR). While difficult to discern, the former is symmetrical, while the latter is asymmetrical, as quantified below. The third column of panels shows the simulated NR matrices, and the level of fit to the empirical NR is shown in the scatterplot in the fourth column of panels. It is very clear that only the G_NR optimization is able to capture the level of empirical NR and consequently, the hierarchy. (C) Leftmost figure is quantifying the level of asymmetry of the G_NR. As can be seen in the boxplot, there is no asymmetry for G_FC, but strong asymmetry for G_NR. This is further explored in the inset, which shows that there are many asymmetric pairs of brain regions. Last, we visualize these asymmetries with the full and thresholded matrices.