83). Because short-distance relationships were excluded, nodes identified by high participation coefficients are not identified simply for being proximal to nodes belonging to other communities. Because nodes within relatively small communities tend to have higher participation coefficients (Figure S1), we also counted the number of communities contacted by each node, and this index, which is not biased by community size, identified a similar set of nodes as participation coefficients (Figure S3; r = 0.85). We have also proposed

a high-resolution modification of voxelwise networks (Power et al., 2011). Communities in this graph are in good agreement with INK1197 functional systems and with communities in the areal network (Power et al., 2011). This graph has excellent spatial resolution but also some distorted network properties (see Argument 2). HIF pathway We therefore focus on the spatial properties of this model. Our second method examines the spatial topography of this graph to identify locations

where many communities are present within a small volume. Such locations, which we call articulation points, would be well-suited for integrating (or distributing) a variety of types of information represented in different systems. Figure 7 outlines our methodology. A modified voxelwise network was formed in the 120 subject cohort, and community assignments were obtained for all voxels in the AAL atlas (cortical and subcortical) over multiple thresholds (2.5%–0.5% edge density in 0.5% steps) as in Power et al. (2011). Community density was then calculated for each voxel as the number of unique communities found within some radius of that voxel (see the Experimental Procedures). Radii of 5–10 mm in 1 mm steps were sampled. We use high thresholds because more communities are detected at high thresholds, yielding more focal community density maps (often articulations of four to seven commumities); at Ergoloid lower

thresholds, fewer communities are found, yielding less focal maps of community density. A representative analysis at threshold 1% and radius 8 mm is shown in Figures 7A and 7B. To identify peaks in community density that are reliable across thresholds and sampling distances, results were summed from analyses performed across these parameter spaces after normalizing the values within each analysis (Figure 7C). The topography of community density is very similar in 40 subject subcohorts of the main cohort and across parameter spaces (Figure S4; correlations between subcohorts = 0.85 ± 0.04). When calculating community density, each hemisphere was analyzed separately to avoid contributions from tissue across the midline, and subcortical structures were excluded from calculations to avoid inflated estimates in the insula (Figure S5). We have developed two methods aimed at identifying brain regions that support or integrate multiple functional systems.