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. 2008 Oct;18(10):2374-81.
doi: 10.1093/cercor/bhn003. Epub 2008 Feb 10.

Revealing modular architecture of human brain structural networks by using cortical thickness from MRI

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Revealing modular architecture of human brain structural networks by using cortical thickness from MRI

Zhang J Chen et al. Cereb Cortex. 2008 Oct.

Abstract

Modularity, presumably shaped by evolutionary constraints, underlies the functionality of most complex networks ranged from social to biological networks. However, it remains largely unknown in human cortical networks. In a previous study, we demonstrated a network of correlations of cortical thickness among specific cortical areas and speculated that these correlations reflected an underlying structural connectivity among those brain regions. Here, we further investigated the intrinsic modular architecture of the human brain network derived from cortical thickness measurement. Modules were defined as groups of cortical regions that are connected morphologically to achieve the maximum network modularity. We show that the human cortical network is organized into 6 topological modules that closely overlap known functional domains such as auditory/language, strategic/executive, sensorimotor, visual, and mnemonic processing. The identified structure-based modular architecture may provide new insights into the functionality of cortical regions and connections between structural brain modules. This study provides the first report of modular architecture of the structural network in the human brain using cortical thickness measurements.

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Figures

Figure 1.
Figure 1.
Identification of the functional modules in the human brain structural network. (a) (Top panel) The binarized matrix represents the human brain structural network constructed using cortical thickness from MRI (He, Chen, et al. 2007). (Bottom panel) Each suprathreshold cell in the top panel represents 1 “link” in the brain network. (1,2) SFG, (3,4) MFG, (5,6) IFG, (7,8) MdFG, (9,10) PrCG, (11,12) LOFG: lateral frontoorbital gyrus, (13,14) MOFG, (15,16) SPL, (17,18) SMG, (19,20) ANG: angular gyrus, (21,22) PCU: precuneus gyrus, (23,24) PoCG, (25,26) STG, (27,28) MTG, (29,30) ITG: inferior temporal gyrus, (31,32) UNC: uncus, (33,34) MOTG: medial occipitotemporal gyrus, (35,36) LOTG, (37,38) PHG: parahippocampal gyrus, (39,40) OP: occipital pole, (41,42) SOG: superior occipital gyrus, (43,44) MOG: middle occipital gyrus, (45,46) IOG: inferior occipital gyrus, (47,48) CUN: cuneus, (49,50) LING, (51,52) CING: cingulate region, (53,54) INS: insula. (b) Progress of the network modularity, Q, as regions are merged into modules for the human cortical network (blue) and 1000 random networks (dotted). Red down arrow indicates the cortical network modularity reaches maximum when the network is segmented into 6 modules (Z score = 7.9). The network modularity decreases as the merge continues indicating a less optimized network modular organization. (c) Dendrogram representation of the modules identification progress determined by modularity (Q). The maximum Q is reached when the network is separated into 6 modules indicated by the red up arrow.
Figure 2.
Figure 2.
Modular architecture of the human cortical network. Six modules of human cortical network displayed in groups. Red: module I, orange: module II, pink: module III, blue: module IV, yellow: module V, green: module VI. The intermodular connections and intramodular connections of the network are shown in dark and gray lines, respectively. The size of each node denotes the relative betweenness centrality (Nbc) of the cortical region in the brain network (for details, see Table 1).

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