Article Figures & Data
Figures
- Figure 1.
Cross-modal structural–functional analysis. To assess the structural properties (i.e., rich club organization) as well as functional dynamics (i.e., RSNs) of the brain's connectome, a T1 anatomical scan (A), structural DWI (B), and resting-state fMRI were acquired (C). A, Cortical nodes. The cortical mantle was automatically segmented (i) into small parcels (1170) of approximately equal size (Fischl et al., 2004), overlapping with macroscopic cortical regions (ii,iii). These cortical parcels formed the nodes of the structural network (iv). B, Structural connectivity. Structural connectivity between brain regions was assessed using diffusion imaging (i), including the reconstruction of white matter tracts (ii), forming the connections of the network (iii,iv). C, Functional connectivity. Resting-state time-series were preprocessed (i), and 11 RSNs were selected based on ICA decomposition (ii,iii), forming a functional partitioning of the nodes of the network (iv). D, Cross-modal structural–functional integration. Functional RSNs defined a modular partition of the brain. Structural relations between these functional communities were analyzed by overlaying the structural network of reconstructed white matter pathways onto the functional partition. E, Network analysis. Network analysis was used to examine the structure–function interaction, including the examination of several cross-modal metrics of this interaction.
- Figure 2.
Structural rich club formation. a, Schematic illustration of the rich club and nonrich club nodes of the network and the three classes of connections (i.e., rich club, feeder, and local connections). b, Network representation of the group-averaged structural brain network, with the “nodes” of the network expressing center-of-mass of the cortical regions and the “connections” representing the reconstructed corticocortical white matter projections between these regions. Nodes are colored according to whether they participate in the rich club (blue nodes) or not (gray nodes), similar to the color scheme used in a. Connections between the nodes are color coded according to their connection class, with rich club (red), feeder connections (orange), and local connections (yellow). c, Projection of the structural rich club nodes on the cortical surface (map spatially smoothed for visualization).
- Figure 3.
RSNs. ICA decomposition of the voxelwise resting-state fMRI time series resulted in the extraction of 11 RSNs. Consistent with other reports, the functional networks comprised the primary visual network (top row, from left to right), extrastriate visual, bilateral parietal, dorsal attention network, primary sensory, primary motor network, the right frontal parietal network, the default mode network (bottom row, from left to right), the salience processing network, the left frontal parietal network, auditory network, and a frontal network.
- Figure 4.
Spatial overlap of rich club and RSNs. Spatial overlap between members of the rich club and all RSNs, projected on the cortical surface. Parts of the surface assigned to a RSN are colored in red and blue, with blue regions indicating overlap between the RSN and the rich club.
- Figure 5.
Rich club involvement in RSNs. a, Proportional involvement of RSNs in the rich club. b, Absolute number of rich club (blue) and nonrich club nodes (color coded according to RSN) involved in each of the 11 RSNs. Sixteen structural nodes were found not to overlap with any of the RSNs (i.e., RSNs overlapped 98% of the nodes of the cortex). c, Involvement of rich club nodes within each RSN, relative to RSN size.
- Figure 6.
Participation index and within-module z-score of nodes. a, Structural–functional participation index Pi (top row) and the within-module degree degree z-score zi (bottom row) of each node of the network (maps are spatially smoothed for visualization). b, Categorizing the nodes of the network based on their Pi and zi score and the involvement of rich club and nonrich club nodes in each of these categories. Figure shows a strong involvement of rich club nodes in the “connector hubs” of the network (high Pi, high zi) expressing a high level of within-module connectivity and a diverse connectivity profile across RSNs.
- Figure 7.
Rich club level and RSN overlap. Left, Rich club level projected on a reconstruction of the cortical surface. Right, Level of “RSN overlap” for each structural node of the network, expressing the number of RSNs in which a node is (proportionally) involved. Comparison shows that, in many cases, areas of RSN overlap coincide with regions that have a high rich club level (see Results). (Maps are spatially smoothed for visualization.)
- Figure 8.
Structural and functional connectivity matrices. Side-by-side plot of the group-averaged structural and functional connectivity matrix. Network nodes in both the structural (left) and functional (right) matrix are arranged according to their “winner-take-all” assignment to each of the 11 functional RSNs. Existing entries within the matrix are marked by colored dots to allow the comparison of structural and functional connections across matrices. Colored bars to the left and top of the matrices indicate RSN assignment (compare with Fig. 4). RSNs are ordered according to their level of inter-RSN connectivity, with RSNs showing high levels of interconnectivity appearing closer to the center of the matrix. Left, Structural connections, color coded according to their connection class. Right, Connection strengths of strong positive functional couplings between nodes of the network depicted in grayscale.
- Figure 9.
Rich club, feeder, and local intra-RSN and inter-RSN connectivity. a, Side-by-side plot of the long-distance (>30 mm, corresponding to the statistics presented in d) structural and functional connections arranged in the same node ordering. Left, Long-distance inter-RSN and intra-RSN connections, color-coded according to their connection class. Right, Connection strengths of strong positive functional couplings between all network nodes depicted in grayscale. b, Panels show the connections of a divided up according to their connection class. c, Distribution of rich club, feeder, and local connections over the two classes of intra-RSN and inter-RSN connections. d, Distribution of intra-RSN and inter-RSN connections, excluding connections crossing between spatially adjacent RSNs (examining only connections with a length >30 mm). e, Distribution of intra-RSN and inter-RSN connections split out according to connection class.
- Figure 10.
Structural–functional modularity score. Reducing the weights of rich club and feeder connections (red bars, 10%–100% reduction) resulted in a gradual increase of the Qsc_fc metric, suggesting an increasingly modular partitioning of the brain. In contrast, reducing the weights of the local connections in equal proportions resulted in a decrease in Qsc_fc, indicating a progressively less modular organization of the brain's network. Gray bars represent the effects when the weights of 1000 random sets of connections are reduced (in equal proportions to the other conditions), showing no impact of random weight changes on Qsc_fc. Blue line indicates normal (i.e., 0%) level of Qsc_fc.
- Figure 11.
Structural hierarchy of functional RSNs. Examination of structural inter-RSN connectivity revealed a disproportionately dense level of interconnectivity between the DMN, salience, and left and right parietal networks (see also Fig. 9a,b). This suggests a central role of more cognitive networks in a structural hierarchy of interconnectivity between RSNs, with more primary, unimodal RSNs connected as “spokes” or “satellite networks” to this functionally central core. The figure schematically illustrates such a hypothesized structural hierarchy of functional networks in the human brain.
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