Figure - PMC

Skip to main content

View full-text article in PMC

. Author manuscript; available in PMC: 2015 Jan 1.

Published in final edited form as: Pain. 2013 Sep 26;155(1):137–149. doi: 10.1016/j.pain.2013.09.020

HC and IBS betweenness-based structural network energized using a Kamada-Kawai algorithm.

Betweenness is a proportional measure of how often a node (brain region) is located on the shortest path between two brain regions, where shortest path refers smallest distance between two vertices and corresponds to the length (number of edges) between them. Here, the greater betweenness of a region is depicted by larger circle magnitudes. Edges of the graph represent connected regions. Abbreviations for brain regions are defined in Table 3

HC and IBS betweenness-based structural network energized using a Kamada-Kawai algorithm.

Betweenness is a proportional measure of how often a node (brain region) is located on the shortest path between two brain regions, where shortest path refers smallest distance between two vertices and corresponds to the length (number of edges) between them. Here, the greater betweenness of a region is depicted by larger circle magnitudes. Edges of the graph represent connected regions. Abbreviations for brain regions are defined in Table 3