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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

Age-related changes in different network metrics for the developing WM network from early childhood to adult. (A) Total network strength (S), (B) Clustering coefficient (CC), (C) Shortest path length (Lp), (D) Modularity (Q), (E) Global efficiency (Eglob), and (F) Local efficiency (Eloc). Significant changes between any adjacent age groups are indicated by their p value. An increase with age is observed in S over the full age span. Eglob increases only between the two youngest age groups and Eloc only between late childhood and adolescence; in both cases, the efficiency values then stay elevated. Reductions are observed in Lp and Q from early to late childhood that is then maintained low. There is no change in CC between any adjacent age groups. The + signs indicate outliers.
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Figure 4: Age-related changes in different network metrics for the developing WM network from early childhood to adult. (A) Total network strength (S), (B) Clustering coefficient (CC), (C) Shortest path length (Lp), (D) Modularity (Q), (E) Global efficiency (Eglob), and (F) Local efficiency (Eloc). Significant changes between any adjacent age groups are indicated by their p value. An increase with age is observed in S over the full age span. Eglob increases only between the two youngest age groups and Eloc only between late childhood and adolescence; in both cases, the efficiency values then stay elevated. Reductions are observed in Lp and Q from early to late childhood that is then maintained low. There is no change in CC between any adjacent age groups. The + signs indicate outliers.

Mentions: Over all subjects in each age group, the total network weight, CC, Lp, modularity (Q), Eglob and Eloc was calculated for the WM network and the age-related trajectories are shown in Figure 4. The total network weight displayed significant increases in three of the four developing stages, whereas the other metrics such as Lp, Q, Eglob, and Eloc demonstrated non-linear alteration patterns where most changes happened from young childhood to late childhood that then leveled off. Both Lp and Q decreased significantly from young childhood to late childhood but stabilized at older ages. Global network efficiency increased significantly from young childhood to late childhood but also stabilized later. Local network efficiency increased significantly from late childhood to adolescence and stabilized afterwards.


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

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

Age-related changes in different network metrics for the developing WM network from early childhood to adult. (A) Total network strength (S), (B) Clustering coefficient (CC), (C) Shortest path length (Lp), (D) Modularity (Q), (E) Global efficiency (Eglob), and (F) Local efficiency (Eloc). Significant changes between any adjacent age groups are indicated by their p value. An increase with age is observed in S over the full age span. Eglob increases only between the two youngest age groups and Eloc only between late childhood and adolescence; in both cases, the efficiency values then stay elevated. Reductions are observed in Lp and Q from early to late childhood that is then maintained low. There is no change in CC between any adjacent age groups. The + signs indicate outliers.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 4: Age-related changes in different network metrics for the developing WM network from early childhood to adult. (A) Total network strength (S), (B) Clustering coefficient (CC), (C) Shortest path length (Lp), (D) Modularity (Q), (E) Global efficiency (Eglob), and (F) Local efficiency (Eloc). Significant changes between any adjacent age groups are indicated by their p value. An increase with age is observed in S over the full age span. Eglob increases only between the two youngest age groups and Eloc only between late childhood and adolescence; in both cases, the efficiency values then stay elevated. Reductions are observed in Lp and Q from early to late childhood that is then maintained low. There is no change in CC between any adjacent age groups. The + signs indicate outliers.
Mentions: Over all subjects in each age group, the total network weight, CC, Lp, modularity (Q), Eglob and Eloc was calculated for the WM network and the age-related trajectories are shown in Figure 4. The total network weight displayed significant increases in three of the four developing stages, whereas the other metrics such as Lp, Q, Eglob, and Eloc demonstrated non-linear alteration patterns where most changes happened from young childhood to late childhood that then leveled off. Both Lp and Q decreased significantly from young childhood to late childhood but stabilized at older ages. Global network efficiency increased significantly from young childhood to late childhood but also stabilized later. Local network efficiency increased significantly from late childhood to adolescence and stabilized afterwards.

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