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Connectomic Insights into Topologically Centralized Network Edges and Relevant Motifs in the Human Brain.

Xia M, Lin Q, Bi Y, He Y - Front Hum Neurosci (2016)

Bottom Line: We found that the pivotal WM connections with highly topological-edge centrality were primarily distributed in several long-range cortico-cortical connections (including the corpus callosum, cingulum and inferior fronto-occipital fasciculus) and some projection tracts linking subcortical regions.Computational simulation models indicated the sharp decrease of global network integrity when attacking these highly centralized edges.Together, our results demonstrated high building-cost consumption and substantial communication capacity contributions for pivotal WM connections, which deepens our understanding of the topological mechanisms that govern the organization of human connectomes.

View Article: PubMed Central - PubMed

Affiliation: State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University Beijing, China.

ABSTRACT
White matter (WM) tracts serve as important material substrates for information transfer across brain regions. However, the topological roles of WM tracts in global brain communications and their underlying microstructural basis remain poorly understood. Here, we employed diffusion magnetic resonance imaging and graph-theoretical approaches to identify the pivotal WM connections in human whole-brain networks and further investigated their wiring substrates (including WM microstructural organization and physical consumption) and topological contributions to the brain's network backbone. We found that the pivotal WM connections with highly topological-edge centrality were primarily distributed in several long-range cortico-cortical connections (including the corpus callosum, cingulum and inferior fronto-occipital fasciculus) and some projection tracts linking subcortical regions. These pivotal WM connections exhibited high levels of microstructural organization indicated by diffusion measures (the fractional anisotropy, the mean diffusivity and the axial diffusivity) and greater physical consumption indicated by streamline lengths, and contributed significantly to the brain's hubs and the rich-club structure. Network motif analysis further revealed their heavy participations in the organization of communication blocks, especially in routes involving inter-hemispheric heterotopic and extremely remote intra-hemispheric systems. Computational simulation models indicated the sharp decrease of global network integrity when attacking these highly centralized edges. Together, our results demonstrated high building-cost consumption and substantial communication capacity contributions for pivotal WM connections, which deepens our understanding of the topological mechanisms that govern the organization of human connectomes.

No MeSH data available.


Related in: MedlinePlus

A flowchart for the construction of the whole-brain WM network. (A) The T1-weighted image was firstly rigidly coregistered to the averaged b0 image in native diffusion space; (B) The transformed T1 image was then nonlinearly transformed to the ICBM152 T1 template in the MNI space, and the transformation matrix T was estimated; (C) the inversed transformation T-1 was used to warp the AAL atlas from the MNI space to the native diffusion space, obtaining the parcellation for each individual; (D) the whole-brain WM tracts were reconstructed by using deterministic tractography; (E) the WM fibers connecting each pair of regions were determined for each subject, thus the individual WM networks were constructed; (F) the group-level connectivity matrix was computed by selecting all connections that were present in at least 50% of the group of individuals; and (G) both the individual and group-level networks were further analyzed by using graph theoretical methods.
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Figure 1: A flowchart for the construction of the whole-brain WM network. (A) The T1-weighted image was firstly rigidly coregistered to the averaged b0 image in native diffusion space; (B) The transformed T1 image was then nonlinearly transformed to the ICBM152 T1 template in the MNI space, and the transformation matrix T was estimated; (C) the inversed transformation T-1 was used to warp the AAL atlas from the MNI space to the native diffusion space, obtaining the parcellation for each individual; (D) the whole-brain WM tracts were reconstructed by using deterministic tractography; (E) the WM fibers connecting each pair of regions were determined for each subject, thus the individual WM networks were constructed; (F) the group-level connectivity matrix was computed by selecting all connections that were present in at least 50% of the group of individuals; and (G) both the individual and group-level networks were further analyzed by using graph theoretical methods.

Mentions: Figure 1 illustrates the flowchart of the construction of whole-brain structural networks, which was outlined as follows.


Connectomic Insights into Topologically Centralized Network Edges and Relevant Motifs in the Human Brain.

Xia M, Lin Q, Bi Y, He Y - Front Hum Neurosci (2016)

A flowchart for the construction of the whole-brain WM network. (A) The T1-weighted image was firstly rigidly coregistered to the averaged b0 image in native diffusion space; (B) The transformed T1 image was then nonlinearly transformed to the ICBM152 T1 template in the MNI space, and the transformation matrix T was estimated; (C) the inversed transformation T-1 was used to warp the AAL atlas from the MNI space to the native diffusion space, obtaining the parcellation for each individual; (D) the whole-brain WM tracts were reconstructed by using deterministic tractography; (E) the WM fibers connecting each pair of regions were determined for each subject, thus the individual WM networks were constructed; (F) the group-level connectivity matrix was computed by selecting all connections that were present in at least 50% of the group of individuals; and (G) both the individual and group-level networks were further analyzed by using graph theoretical methods.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4835491&req=5

Figure 1: A flowchart for the construction of the whole-brain WM network. (A) The T1-weighted image was firstly rigidly coregistered to the averaged b0 image in native diffusion space; (B) The transformed T1 image was then nonlinearly transformed to the ICBM152 T1 template in the MNI space, and the transformation matrix T was estimated; (C) the inversed transformation T-1 was used to warp the AAL atlas from the MNI space to the native diffusion space, obtaining the parcellation for each individual; (D) the whole-brain WM tracts were reconstructed by using deterministic tractography; (E) the WM fibers connecting each pair of regions were determined for each subject, thus the individual WM networks were constructed; (F) the group-level connectivity matrix was computed by selecting all connections that were present in at least 50% of the group of individuals; and (G) both the individual and group-level networks were further analyzed by using graph theoretical methods.
Mentions: Figure 1 illustrates the flowchart of the construction of whole-brain structural networks, which was outlined as follows.

Bottom Line: We found that the pivotal WM connections with highly topological-edge centrality were primarily distributed in several long-range cortico-cortical connections (including the corpus callosum, cingulum and inferior fronto-occipital fasciculus) and some projection tracts linking subcortical regions.Computational simulation models indicated the sharp decrease of global network integrity when attacking these highly centralized edges.Together, our results demonstrated high building-cost consumption and substantial communication capacity contributions for pivotal WM connections, which deepens our understanding of the topological mechanisms that govern the organization of human connectomes.

View Article: PubMed Central - PubMed

Affiliation: State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University Beijing, China.

ABSTRACT
White matter (WM) tracts serve as important material substrates for information transfer across brain regions. However, the topological roles of WM tracts in global brain communications and their underlying microstructural basis remain poorly understood. Here, we employed diffusion magnetic resonance imaging and graph-theoretical approaches to identify the pivotal WM connections in human whole-brain networks and further investigated their wiring substrates (including WM microstructural organization and physical consumption) and topological contributions to the brain's network backbone. We found that the pivotal WM connections with highly topological-edge centrality were primarily distributed in several long-range cortico-cortical connections (including the corpus callosum, cingulum and inferior fronto-occipital fasciculus) and some projection tracts linking subcortical regions. These pivotal WM connections exhibited high levels of microstructural organization indicated by diffusion measures (the fractional anisotropy, the mean diffusivity and the axial diffusivity) and greater physical consumption indicated by streamline lengths, and contributed significantly to the brain's hubs and the rich-club structure. Network motif analysis further revealed their heavy participations in the organization of communication blocks, especially in routes involving inter-hemispheric heterotopic and extremely remote intra-hemispheric systems. Computational simulation models indicated the sharp decrease of global network integrity when attacking these highly centralized edges. Together, our results demonstrated high building-cost consumption and substantial communication capacity contributions for pivotal WM connections, which deepens our understanding of the topological mechanisms that govern the organization of human connectomes.

No MeSH data available.


Related in: MedlinePlus