High-cost, high-capacity backbone for global brain communication

Abstract

Network studies of human brain structural connectivity have identified a specific set of brain regions that are both highly connected and highly central. Recent analyses have shown that these putative hub regions are mutually and densely interconnected, forming a "rich club" within the human brain. Here we show that the set of pathways linking rich club regions forms a central high-cost, high-capacity backbone for global brain communication. Diffusion tensor imaging (DTI) data of two sets of 40 healthy subjects were used to map structural brain networks. The contributions to network cost and communication capacity of global cortico-cortical connections were assessed through measures of their topology and spatial embedding. Rich club connections were found to be more costly than predicted by their density alone and accounted for 40% of the total communication cost. Furthermore, 69% of all minimally short paths between node pairs were found to travel through the rich club and a large proportion of these communication paths consisted of ordered sequences of edges ("path motifs") that first fed into, then traversed, and finally exited the rich club, while passing through nodes of increasing and then decreasing degree. The prevalence of short paths that follow such ordered degree sequences suggests that neural communication might take advantage of strategies for dynamic routing of information between brain regions, with an important role for a highly central rich club. Taken together, our results show that rich club connections make an important contribution to interregional signal traffic, forming a central high-cost, high-capacity backbone for global brain communication.

Fig. 1.

(A) Rich club curve relative to random model, showing a rich club organization of the human connectome (*P < 0.05, Bonferroni corrected). The selected rich club level of k > 10 is indicated by a red circle. (B) Network representation of local (Left), feeder (Center), and rich club connections (Right). (C) Schematic illustration of local, feeder, and rich club connections.

Fig. 2.

(A) Proportions of short- (<30 mm), medium- (30–90 mm), and long-range (>90 mm) connections belonging to different topological classes. (B) Contributions to network density and network cost of local, feeder, and rich club connections. (C) Nodes are depicted on a ring, organized according to minimization of the inverse of network cost, placing nodes of low connectivity cost in close proximity on the ring (SI Materials and Methods). “% of cost” expresses the proportion of total network cost taken on by connections in close proximity on the ring (proximal) and by connections placed on different parts of the ring (distal connections). cing, posterior and anterior cingulate cortex; insula, insular cortex; phip, parahippocampal; prec, precuneus; sf, superior frontal cortex.

Fig. 3.

(A) Contributions to communication cost of local feeder and rich club connections. (B) Communication cost of paths that pass through the rich club (69% of all paths). (C) Frequencies of a selection of path motifs in the brain network (main text), all occurring with a frequency greater than 1%, and their corresponding frequencies in a set of a 1,000 random networks, preserving degree sequence. L-F-R-F-L was the most common path motif in the brain network (*P < 0.05, Bonferroni corrected; SI Materials and Methods).

Fig. 4.

Paths and their dependence on node degree. (A) Schematic diagram illustrating the relation of node degrees and edge type along communication paths between nonrich club nodes, further grouped into short range, medium range, and long range. (B) Edge type traveled along each path (rows) as a function of rescaled distance between origin and target (x axis). The colored bar shows the modal edge type as a function of distance, taken as the modus over all paths. (C) Distance/degree frequency map for each of the three distance classes. Maps depict the number of times a node of degree k (y axis) is crossed along each path as a function of the distance traveled from source node to destination node (x axis). Maps show that short-range paths mostly use nodes with low degree (i.e., below rich club threshold of k > 10), whereas medium-range and long-range paths tend to follow a “zooming-out/zooming-in pattern.”