The Mathematical Institute, University of Oxford, Eprints Archive

Dynamic reconfiguration of human brain networks during learning

Bassett, D S and Wymbs, N F and Porter, M A and Mucha, P J and Carlson, J M and Grafton, S T (2011) Dynamic reconfiguration of human brain networks during learning. Proceedings of the National Academy of Sciences of the USA, 118 (18). pp. 7641-7646.



Human learning is a complex phenomenon requiring flexibility to adapt existing brain function and precision in selecting new neurophysiological activities to drive desired behavior. These two attributes—flexibility and selection—must operate over multiple temporal scales as performance of a skill changes from being slow and challenging to being fast and automatic. Such selective adaptability is naturally provided by modular structure, which plays a critical role in evolution, development, and optimal network function. Using functional connectivity measurements of brain activity acquired from initial training through mastery of a simple motor skill, we investigate the role of modularity in human learning by identifying dynamic changes of modular organization spanning multiple temporal scales. Our results indicate that flexibility, which we measure by the allegiance of nodes to modules, in one experimental session predicts the relative amount of learning in a future session. We also develop a general statistical framework for the identification of modular architectures in evolving systems, which is broadly applicable to disciplines where network adaptability is crucial to the understanding of system performance.

Item Type:Article
Uncontrolled Keywords:complex network time-dependent network fMRI motor learning community structure
Subjects:A - C > Biology and other natural sciences
Research Groups:Centre for Mathematical Biology
ID Code:1808
Deposited By: Sara Jolliffe
Deposited On:26 Feb 2014 08:44
Last Modified:29 May 2015 19:30

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