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Graph theoretical analysis of developmental patterns of the white matter network.

Chen Z, Liu M, Gross DW, Beaulieu C - Front Hum Neurosci (2013)

Bottom Line: During late childhood period, the structural brain network showed significant increase in the global efficiency but decrease in modularity, suggesting a shift of topological organization toward a more randomized configuration.However, while preserving most topological features, there was a significant increase in the local efficiency at adolescence, suggesting the dynamic process of rewiring and rebalancing brain connections at different growth stages.Finally, a stable and functionally/anatomically related modular organization was identified throughout the development of the WM network.

View Article: PubMed Central - PubMed

Affiliation: Department of Biomedical Engineering, Faculty of Medicine and Dentistry, University of Alberta Edmonton, AB, Canada.

ABSTRACT
Understanding the development of human brain organization is critical for gaining insight into how the enhancement of cognitive processes is related to the fine-tuning of the brain network. However, the developmental trajectory of the large-scale white matter (WM) network is not fully understood. Here, using graph theory, we examine developmental changes in the organization of WM networks in 180 typically-developing participants. WM networks were constructed using whole brain tractography and 78 cortical regions of interest were extracted from each participant. The subjects were first divided into 5 equal sample size (n = 36) groups (early childhood: 6.0-9.7 years; late childhood: 9.8-12.7 years; adolescence: 12.9-17.5 years; young adult: 17.6-21.8 years; adult: 21.9-29.6 years). Most prominent changes in the topological properties of developing brain networks occur at late childhood and adolescence. During late childhood period, the structural brain network showed significant increase in the global efficiency but decrease in modularity, suggesting a shift of topological organization toward a more randomized configuration. However, while preserving most topological features, there was a significant increase in the local efficiency at adolescence, suggesting the dynamic process of rewiring and rebalancing brain connections at different growth stages. In addition, several pivotal hubs were identified that are vital for the global coordination of information flow over the whole brain network across all age groups. Significant increases of nodal efficiency were present in several regions such as precuneus at late childhood. Finally, a stable and functionally/anatomically related modular organization was identified throughout the development of the WM network. This study used network analysis to elucidate the topological changes in brain maturation, paving the way for developing novel methods for analyzing disrupted brain connectivity in neurodevelopmental disorders.

No MeSH data available.


Related in: MedlinePlus

The small-worldness of the WM networks for the five age groups. Each group was represented by one weighted backbone network to capture the underlying anatomical connectivity patterns. Compared with their corresponding random networks, all age groups showed strong small-worldness (i.e., σ > > 1). The numbers reflect the structural indices indicated in Table 2.
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Figure 3: The small-worldness of the WM networks for the five age groups. Each group was represented by one weighted backbone network to capture the underlying anatomical connectivity patterns. Compared with their corresponding random networks, all age groups showed strong small-worldness (i.e., σ > > 1). The numbers reflect the structural indices indicated in Table 2.

Mentions: To examine the small-worldness of the WM networks for all different age groups, using a previously published method by our group (Gong et al., 2009), one weighted backbone network for each age group was generated to capture the underlying anatomical connectivity patterns as shown in Figure 3. Compared with their corresponding 1000 random networks, all five age groups showed strong small-worldness (σearly childhood = 3.54, σlate childhood = 3.19, σadolescence = 3.25, σyoung adult = 3.12, σadult = 3.19).


Graph theoretical analysis of developmental patterns of the white matter network.

Chen Z, Liu M, Gross DW, Beaulieu C - Front Hum Neurosci (2013)

The small-worldness of the WM networks for the five age groups. Each group was represented by one weighted backbone network to capture the underlying anatomical connectivity patterns. Compared with their corresponding random networks, all age groups showed strong small-worldness (i.e., σ > > 1). The numbers reflect the structural indices indicated in Table 2.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3814848&req=5

Figure 3: The small-worldness of the WM networks for the five age groups. Each group was represented by one weighted backbone network to capture the underlying anatomical connectivity patterns. Compared with their corresponding random networks, all age groups showed strong small-worldness (i.e., σ > > 1). The numbers reflect the structural indices indicated in Table 2.
Mentions: To examine the small-worldness of the WM networks for all different age groups, using a previously published method by our group (Gong et al., 2009), one weighted backbone network for each age group was generated to capture the underlying anatomical connectivity patterns as shown in Figure 3. Compared with their corresponding 1000 random networks, all five age groups showed strong small-worldness (σearly childhood = 3.54, σlate childhood = 3.19, σadolescence = 3.25, σyoung adult = 3.12, σadult = 3.19).

Bottom Line: During late childhood period, the structural brain network showed significant increase in the global efficiency but decrease in modularity, suggesting a shift of topological organization toward a more randomized configuration.However, while preserving most topological features, there was a significant increase in the local efficiency at adolescence, suggesting the dynamic process of rewiring and rebalancing brain connections at different growth stages.Finally, a stable and functionally/anatomically related modular organization was identified throughout the development of the WM network.

View Article: PubMed Central - PubMed

Affiliation: Department of Biomedical Engineering, Faculty of Medicine and Dentistry, University of Alberta Edmonton, AB, Canada.

ABSTRACT
Understanding the development of human brain organization is critical for gaining insight into how the enhancement of cognitive processes is related to the fine-tuning of the brain network. However, the developmental trajectory of the large-scale white matter (WM) network is not fully understood. Here, using graph theory, we examine developmental changes in the organization of WM networks in 180 typically-developing participants. WM networks were constructed using whole brain tractography and 78 cortical regions of interest were extracted from each participant. The subjects were first divided into 5 equal sample size (n = 36) groups (early childhood: 6.0-9.7 years; late childhood: 9.8-12.7 years; adolescence: 12.9-17.5 years; young adult: 17.6-21.8 years; adult: 21.9-29.6 years). Most prominent changes in the topological properties of developing brain networks occur at late childhood and adolescence. During late childhood period, the structural brain network showed significant increase in the global efficiency but decrease in modularity, suggesting a shift of topological organization toward a more randomized configuration. However, while preserving most topological features, there was a significant increase in the local efficiency at adolescence, suggesting the dynamic process of rewiring and rebalancing brain connections at different growth stages. In addition, several pivotal hubs were identified that are vital for the global coordination of information flow over the whole brain network across all age groups. Significant increases of nodal efficiency were present in several regions such as precuneus at late childhood. Finally, a stable and functionally/anatomically related modular organization was identified throughout the development of the WM network. This study used network analysis to elucidate the topological changes in brain maturation, paving the way for developing novel methods for analyzing disrupted brain connectivity in neurodevelopmental disorders.

No MeSH data available.


Related in: MedlinePlus