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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.


The pivotal edges and their wiring substrates in the human WM network. (A) The EBC distribution of the WM network was best fitted by an exponentially truncated power-law form. (B) The spatial pattern of the pivotal edges (red) of the group-level WM network (upper) is quite similar to the probability map of the pivotal edges across individuals. (C) Several pivotal WM edges were manifest in one representative subject. (D) The pivotal edges showed significantly higher levels of WM microstructural organization, as indicated by FA, MD, and AD, but not RD, than the non-pivotal ones. The error bars represent the standard deviation. (E) The pivotal edges also had greater streamline length and better cost-performance than the non-pivotal ones. (F) The curves for the proportion of edges vs. proportions of EBC and streamline length. EBC, edge betweenness centrality; exp, exponential; trunc, truncated; PCu, precuneus; PUT, putamen; ACG, anterior cingulate and paracingulate gyri; HES, Heschl's gyrus; STG, superior temporal gyrus; ORBinf, inferior frontal gyrus, orbital part; MOG, middle occipital gyrus; ORBsup, superior frontal gyrus, orbital part; ITG, inferior temporal gyrus; FA, fractional anisotropy; MD, mean diffusivity; AD, axial diffusivity; RD, radial diffusivity; LEN, streamline length; C-P, cost-performance; n.s., not significant; L, left; R, right.
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Figure 2: The pivotal edges and their wiring substrates in the human WM network. (A) The EBC distribution of the WM network was best fitted by an exponentially truncated power-law form. (B) The spatial pattern of the pivotal edges (red) of the group-level WM network (upper) is quite similar to the probability map of the pivotal edges across individuals. (C) Several pivotal WM edges were manifest in one representative subject. (D) The pivotal edges showed significantly higher levels of WM microstructural organization, as indicated by FA, MD, and AD, but not RD, than the non-pivotal ones. The error bars represent the standard deviation. (E) The pivotal edges also had greater streamline length and better cost-performance than the non-pivotal ones. (F) The curves for the proportion of edges vs. proportions of EBC and streamline length. EBC, edge betweenness centrality; exp, exponential; trunc, truncated; PCu, precuneus; PUT, putamen; ACG, anterior cingulate and paracingulate gyri; HES, Heschl's gyrus; STG, superior temporal gyrus; ORBinf, inferior frontal gyrus, orbital part; MOG, middle occipital gyrus; ORBsup, superior frontal gyrus, orbital part; ITG, inferior temporal gyrus; FA, fractional anisotropy; MD, mean diffusivity; AD, axial diffusivity; RD, radial diffusivity; LEN, streamline length; C-P, cost-performance; n.s., not significant; L, left; R, right.

Mentions: We used the EBC (Freeman, 1977; Girvan and Newman, 2002) to quantify the topological centrality or communication capacity of the WM edges in the structural brain network. The EBC of an edge measures the frequency with which the shortest path between any region pair passes through this edge. The EBC distribution of the network was best fitted by the exponentially truncated power-law form [P(x) ~ αxβexp(x/γ)] rather than the power-law [P(x) ~ αxβ] and or exponential [P(x) ~ αexp(βx)] models (Figure 2A). The estimated parameters were: α = 0.98, β = 0.20, γ = −15.42 and R2 = 0.998, respectively. Such a model indicates that i) the WM edges play heterogeneous roles in information communication across the network, and ii) the brain network includes some highly centralized edges but prevents the existence of extremely centralized WM connections with overly heavy loads.


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)

The pivotal edges and their wiring substrates in the human WM network. (A) The EBC distribution of the WM network was best fitted by an exponentially truncated power-law form. (B) The spatial pattern of the pivotal edges (red) of the group-level WM network (upper) is quite similar to the probability map of the pivotal edges across individuals. (C) Several pivotal WM edges were manifest in one representative subject. (D) The pivotal edges showed significantly higher levels of WM microstructural organization, as indicated by FA, MD, and AD, but not RD, than the non-pivotal ones. The error bars represent the standard deviation. (E) The pivotal edges also had greater streamline length and better cost-performance than the non-pivotal ones. (F) The curves for the proportion of edges vs. proportions of EBC and streamline length. EBC, edge betweenness centrality; exp, exponential; trunc, truncated; PCu, precuneus; PUT, putamen; ACG, anterior cingulate and paracingulate gyri; HES, Heschl's gyrus; STG, superior temporal gyrus; ORBinf, inferior frontal gyrus, orbital part; MOG, middle occipital gyrus; ORBsup, superior frontal gyrus, orbital part; ITG, inferior temporal gyrus; FA, fractional anisotropy; MD, mean diffusivity; AD, axial diffusivity; RD, radial diffusivity; LEN, streamline length; C-P, cost-performance; n.s., not significant; L, left; R, right.
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Figure 2: The pivotal edges and their wiring substrates in the human WM network. (A) The EBC distribution of the WM network was best fitted by an exponentially truncated power-law form. (B) The spatial pattern of the pivotal edges (red) of the group-level WM network (upper) is quite similar to the probability map of the pivotal edges across individuals. (C) Several pivotal WM edges were manifest in one representative subject. (D) The pivotal edges showed significantly higher levels of WM microstructural organization, as indicated by FA, MD, and AD, but not RD, than the non-pivotal ones. The error bars represent the standard deviation. (E) The pivotal edges also had greater streamline length and better cost-performance than the non-pivotal ones. (F) The curves for the proportion of edges vs. proportions of EBC and streamline length. EBC, edge betweenness centrality; exp, exponential; trunc, truncated; PCu, precuneus; PUT, putamen; ACG, anterior cingulate and paracingulate gyri; HES, Heschl's gyrus; STG, superior temporal gyrus; ORBinf, inferior frontal gyrus, orbital part; MOG, middle occipital gyrus; ORBsup, superior frontal gyrus, orbital part; ITG, inferior temporal gyrus; FA, fractional anisotropy; MD, mean diffusivity; AD, axial diffusivity; RD, radial diffusivity; LEN, streamline length; C-P, cost-performance; n.s., not significant; L, left; R, right.
Mentions: We used the EBC (Freeman, 1977; Girvan and Newman, 2002) to quantify the topological centrality or communication capacity of the WM edges in the structural brain network. The EBC of an edge measures the frequency with which the shortest path between any region pair passes through this edge. The EBC distribution of the network was best fitted by the exponentially truncated power-law form [P(x) ~ αxβexp(x/γ)] rather than the power-law [P(x) ~ αxβ] and or exponential [P(x) ~ αexp(βx)] models (Figure 2A). The estimated parameters were: α = 0.98, β = 0.20, γ = −15.42 and R2 = 0.998, respectively. Such a model indicates that i) the WM edges play heterogeneous roles in information communication across the network, and ii) the brain network includes some highly centralized edges but prevents the existence of extremely centralized WM connections with overly heavy loads.

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.