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Graham L. Baum

Researcher at University of Pennsylvania

Publications -  37
Citations -  2597

Graham L. Baum is an academic researcher from University of Pennsylvania. The author has contributed to research in topics: Network controllability & Dynamic network analysis. The author has an hindex of 16, co-authored 35 publications receiving 1654 citations. Previous affiliations of Graham L. Baum include Cornell University & Children's Hospital of Philadelphia.

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Benchmarking of participant-level confound regression strategies for the control of motion artifact in studies of functional connectivity.

TL;DR: A systematic evaluation of 14 participant‐level confound regression methods for functional connectivity highlights the heterogeneous efficacy of existing methods, and suggests that different confounding regression strategies may be appropriate in the context of specific scientific goals.
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Modular Segregation of Structural Brain Networks Supports the Development of Executive Function in Youth

TL;DR: In this article, structural network modules become more segregated with age, with weaker connections between modules and stronger connections within modules, and they are associated with enhanced executive performance and mediate the improvement of executive functioning with age.
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Developmental increases in white matter network controllability support a growing diversity of brain dynamics.

TL;DR: A network representation of diffusion imaging data from 882 youth ages 8–22 is used to show that white matter connectivity becomes increasingly optimized for a diverse range of predicted dynamics in development, revealing a possible mechanism of human brain development that preferentially optimizes dynamic network control over static network architecture.
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The modular organization of human anatomical brain networks: Accounting for the cost of wiring

TL;DR: A modification of an existing module detection algorithm that allowed it to focus on connections that are unexpected under a cost-reduction wiring rule and to identify modules from among these connections, which support the hypothesis that brain networks are composed of modules and provide additional insight into the function of those modules.