Developmental increases in white matter network controllability support a growing diversity of brain dynamics

Evelyn Tang, Chad Giusti, Graham L. Baum, Shi Gu, Eli Pollock, Ari E. Kahn, David R. Roalf, Tyler M. Moore, Kosha Ruparel, Ruben C. Gur, Raquel E. Gur, Theodore D. Satterthwaite and Danielle S. Bassett ()
Additional contact information
Evelyn Tang: University of Pennsylvania
Chad Giusti: University of Pennsylvania
Graham L. Baum: University of Pennsylvania
Shi Gu: University of Pennsylvania
Eli Pollock: University of Pennsylvania
Ari E. Kahn: University of Pennsylvania
David R. Roalf: University of Pennsylvania
Tyler M. Moore: University of Pennsylvania
Kosha Ruparel: University of Pennsylvania
Ruben C. Gur: University of Pennsylvania
Raquel E. Gur: University of Pennsylvania
Theodore D. Satterthwaite: University of Pennsylvania
Danielle S. Bassett: University of Pennsylvania

Nature Communications, 2017, vol. 8, issue 1, 1-16

Abstract: Abstract As the human brain develops, it increasingly supports coordinated control of neural activity. The mechanism by which white matter evolves to support this coordination is not well understood. Here we use a network representation of diffusion imaging data from 882 youth ages 8–22 to show that white matter connectivity becomes increasingly optimized for a diverse range of predicted dynamics in development. Notably, stable controllers in subcortical areas are negatively related to cognitive performance. Investigating structural mechanisms supporting these changes, we simulate network evolution with a set of growth rules. We find that all brain networks are structured in a manner highly optimized for network control, with distinct control mechanisms predicted in child vs. older youth. We demonstrate that our results cannot be explained by changes in network modularity. This work reveals a possible mechanism of human brain development that preferentially optimizes dynamic network control over static network architecture.

Date: 2017
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DOI: 10.1038/s41467-017-01254-4

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