Abstract
Development of the human brain follows a complex trajectory of age-specific anatomical and physiological changes. The application of network analysis provides an illuminating perspective on the dynamic interregional and global properties of this intricate and complex system. Here, we provide a critical synopsis of methods of network analysis with a focus on developing brain networks. After discussing basic concepts and approaches to network analysis, we explore the primary events of anatomical cortical development from gestation through adolescence. Upon this framework, we describe early work revealing the evolution of age-specific functional brain networks in normal neurodevelopment. Finally, we review how these relationships can be altered in disease and perhaps even rectified with treatment. While this method of description and inquiry remains in early form, there is already substantial evidence that the application of network models and analysis to understanding normal and abnormal human neural development holds tremendous promise for future discovery.
Highlights
The developing human brain is a dynamic, complex system
Network methods are especially valuable for child neurologists, given the profound changes that occur throughout neurodevelopment in both normal and pathological circumstances
We will focus on 4 related topics: basic attributes of network analysis with a particular focus on functional brain networks, a brief overview of the primary histogenetic events and sequences of anatomical cortical development, an examination of what is known for the development of functional cortical networks, and the clinical implications of these findings as well as future directions
Summary
Chu-Shore, C. J., M. A. Kramer, M. T. Bianchi, V. S. Caviness, and S. S. Cash. 2011. “Network Analysis: Applications for the Developing Brain.” Journal of Child Neurology 26 (4) (February 7): 488–500. doi:10.1177/0883073810385345. doi:10.1177/0883073810385345 http://nrs.harvard.edu/urn-3:HUL.InstRepos:29663461 This article was downloaded from Harvard University’s DASH repository, and is made available under the terms and conditions applicable to Other Posted Material, as set forth at http:// nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-ofuse#LAA
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