due to the chaotic nature of the dynamics (see Supplementary Materials). So, remarkably, the noise terms $\xi_i$ are needed to access the community structure.

Using steps (i)-(iii) we obtained a model for the isolated dynamics, coupling function, and distribution of degrees. To apply current methods of community detection, we obtain an adjacency matrix with entries equal to zero or one from the matrix of correlations Fig. \[RC\] (c). This is done by thresholding the entries and considering a link only when the correlations were greater than $0.5$. We tested threshold values ranging from $0.3$ to $0.6$ and obtained the same results. Indeed, the distribution of the entries of the matrix of correlations is unimodal and has a peak near 0.5. We computed rich-club coefficients for each node [@colizza2006] (see details in Methods), and nodes with the highest coefficients formed the rich-club displayed at the centre of the network. By applying the community detection method [@blondel2008] to the thresholded effective matrix, we recovered the communities according to their function as shown in Figure \[RC2\] (d).

There is no reason to expect that the links in the effective network correspond to links in the actual network. However, since every node makes most 