GAT: Graph Analysis Toolbox for Brain Networks Figure 4. Association and adjacency matrices. Association matrices for A) ALL and B) CON groups; the color-bar shows the strength of the connections. Binary adjacency matrices for C) ALL and D) CON groups; red color represents presence of connection. These matrices are the maps thresholded at Dmin (22%) in which all nodes became fully connected in the structural networks of both groups. For clarity, only the regions in the left hemisphere are labeled. Abbreviations are used as follow: L: left hemisphere; AMYG: amygdala; ANG: angular gyrus; CALC: calcarine fissure; CN: caudate nucleus; ACC: anterior cingulate; MCC: mid-cingulate; PCC: posterior cingulate; CUN: cuneus; IFOp: inferior frontal gyrus, opercular part; IFOr: inferior frontal gyrus, orbirtal part; IFTr: inferior frontal gyrus, triangular part; MedFOr: medial fronal gyrus, orbital part; MFG: middle frontal gyrus; MFOr: middle frontal gyrus, orbital part; SFG: superior frontal gyrus; MedSF: superior frontal gyrus, medial part; SFOr: superior frontal gyrus, orbital part; FG: fusiform gyrus; HSHL: heschl gyrus; HIPP: hippocampus; INS: insula; LNG: lingual gyrus; IOG: inferior occipital gyrus; MOG: middle occipital gyrus; SOG: superior occipital gyrus; OFB: olfactory cortex; PLD: lenticular nucleus, pallidum; PCL: paracentral lobule; PHIP: parahippocampal gyrus; IPL: inferior parietal lobule; SPL: superior parietal lobule; PoCG: postcentral gyrus; PrCG: precentral gyrus; PCUN: precuneus; PUT: putamen; REC: gyrus rectus; RLN: rolandic operculum; SMA: supplementary motor area; SMG: supramarginal gyrus; ITG: inferior temporal gyrus; MTG: middle temporal gyrus; MTP: middle temporal pole; STP: superior temporal pole; STG: superior temporal gyrus; THL: thalamus. doi:10.1371/journal.pone.0040709.g004 Within-group Global Network Measures The minimum network density below which the networks are fragmented was Dmin = 0.22. To investigate changes in the network topology as a function of network density, GAT thresholds the constructed association matrices at a range of network densities. Changes in global network measures as a function of network cost are shown in Fig. 5. The networks of both groups followed a small-world organization across a wide range of network densities; both the networks had a path length slightly higher than random networks while having a clustering coefficient that was much higher than that in random networks. This pattern results in a small-world index of higher than one across the range of network densities. Between-group Differences in Global Network Measures Differences across network densities. We investigated between-group differences in global network measures on networks thresholded at a range of densities (0.22:0.01:0.45). Compared with CON, the ALL network showed smaller normalized clustering and larger normalized path length across the range of densities but the difference was not significant (p,0.05) (Fig. 6). This pattern led to a significantly smaller small- PLoS ONE | www.plosone.org 8 July 2012 | Volume 7 | Issue 7 | e40709