The DMN did not exhibit strong correlations with other networks when they were in their MCWs (columns of Figures 2 and 3A). Similarly, the DMN did not exhibit strong correlations with other networks outside its MCWs (Figure 3B). Importantly, the principle that a network interact with others when it is in a state of strong internal coherence generalized to both DAN and somatomotor networks, the other two networks with significant

cross-network interactions. This impression was confirmed quantitatively by an ANOVA testing across networks the difference of cross-network interaction in the β band when inside versus outside each network MCWs (Figure S5A). DMN and VAN showed respectively the largest and smallest difference as compared

to other networks (p < 0.0001 and p < 0.005, respectively). Motor and DAN also showed stronger interactions Selleck BMS 777607 within than outside their MCWs as compared to other networks except DMN (Motor, all p < 0.05; DAN, all p < 0.05 except motor). In contrast, visual and language networks did not show any significant difference between them. These analyses confirm that cross-network interactions are nonstationary, and that networks differ in their tendency to interact with others. Additional control analyses indicate that, although the results displayed in Figure 3A were obtained in the β band, they do not underlie an overall greater β-BLP in the DMN as compared to other networks; moreover, β-BLP was not specifically enhanced (within the DMN or other networks) during DMN MCWs (see Figures S5B and S5C). The results presented thus far indicate that: (a) RSNs can this website be recovered those with MEG BLP correlation, especially in the α and β bands, and exhibit large-scale, spatially segregated topographies similar to those obtained with resting state fMRI; (b) RSNs, when fully engaged (during their MCWs), differ in the degree with which they interact with other networks;

(c) the DMN exhibits the strongest cross-network interactions in the β and α bands; and (d) however, cross-network interactions are transient. The DMN, and other significantly cross-interacting networks (DAN, somatomotor), do not interact with other networks outside their MCWs, nor when correlation in other networks is strong. Given the transient nature of the BLP cross-network interactions, it is important to characterize how two networks interact in relation to the degree of internal correlation. Two possibilities were considered. First, cross-network interactions may occur predominantly when both networks are strongly engaged (i.e., when both are in a state of high internal correlation). Alternatively, interactions may occur when one network is strongly engaged and the other is not. To address this question, we developed a measure of MCW temporal overlap (see Supplemental Information). This measure quantifies the degree to which two networks share MCWs specifically in the β band.