3 research outputs found
Structural subnetwork evolution across the life-span: rich-club, feeder, seeder
The impact of developmental and aging processes on brain connectivity and the
connectome has been widely studied. Network theoretical measures and certain
topological principles are computed from the entire brain, however there is a
need to separate and understand the underlying subnetworks which contribute
towards these observed holistic connectomic alterations. One organizational
principle is the rich-club - a core subnetwork of brain regions that are
strongly connected, forming a high-cost, high-capacity backbone that is
critical for effective communication in the network. Investigations primarily
focus on its alterations with disease and age. Here, we present a systematic
analysis of not only the rich-club, but also other subnetworks derived from
this backbone - namely feeder and seeder subnetworks. Our analysis is applied
to structural connectomes in a normal cohort from a large, publicly available
lifespan study. We demonstrate changes in rich-club membership with age
alongside a shift in importance from 'peripheral' seeder to feeder subnetworks.
Our results show a refinement within the rich-club structure (increase in
transitivity and betweenness centrality), as well as increased efficiency in
the feeder subnetwork and decreased measures of network integration and
segregation in the seeder subnetwork. These results demonstrate the different
developmental patterns when analyzing the connectome stratified according to
its rich-club and the potential of utilizing this subnetwork analysis to reveal
the evolution of brain architectural alterations across the life-span
Age-associated changes in rich-club organisation in autistic and neurotypical human brains
Macroscopic structural networks in the human brain have a rich-club architecture comprising both highly inter-connected central regions and sparsely connected peripheral regions. Recent studies show that disruption of this functionally efficient organisation is associated with several psychiatric disorders. However, despite increasing attention to this network property, whether age-associated changes in rich-club organisation occur during human adolescence remains unclear. Here, analysing a publicly shared diffusion tensor imaging dataset, we found that, during adolescence, brains of typically developing (TD) individuals showed increases in rich-club organisation and inferred network functionality, whereas individuals with autism spectrum disorders (ASD) did not. These differences between TD and ASD groups were statistically significant for both structural and functional properties. Moreover, this typical age-related changes in rich-club organisation were characterised by progressive involvement of the right anterior insula. In contrast, in ASD individuals, did not show typical increases in grey matter volume, and this relative anatomical immaturity was correlated with the severity of ASD social symptoms. These results provide evidence that rich-club architecture is one of the bases of functionally efficient brain networks underpinning complex cognitive functions in adult human brains. Furthermore, our findings suggest that immature rich-club organisation might be associated with some neurodevelopmental disorders
Development of the 'rich club' in brain connectivity networks from 438 adolescents & adults aged 12 to 30
The 'rich club' coefficient describes a phenomenon where a network's hubs (high-degree nodes) are on average more intensely interconnected than lower-degree nodes. Networks with rich clubs often have an efficient, higher-order organization, but we do not yet know how the rich club emerges in the living brain, or how it changes as our brain networks develop. Here we chart the developmental trajectory of the rich club in anatomical brain networks from 438 subjects aged 12-30. Cortical networks were constructed from 68×68 connectivity matrices of fiber density, using whole-brain tractography in 4-Tesla 105-gradient high angular resolution diffusion images (HARDI). The adult and younger cohorts had rich clubs that included different nodes; the rich club effect intensified with age. Rich-club organization is a sign of a network's efficiency and robustness. These concepts and findings may be advantageous for studying brain maturation and abnormal brain development