Abstract

Complex human cognition arises from the integrated processing of multiple brain systems. However, little is known about how brain systems and their interactions might relate to, or perhaps even explain, human cognitive capacities. Here, we address this gap in knowledge by proposing a mechanistic framework linking frontoparietal system activity, default mode system activity, and the interactions between them, with individual differences in working memory capacity. We show that working memory performance depends on the strength of functional interactions between the frontoparietal and default mode systems. We find that this strength is modulated by the activation of two newly described brain regions, and demonstrate that the functional role of these systems is underpinned by structural white matter. Broadly, our study presents a holistic account of how regional activity, functional connections, and structural linkages together support integrative processing across brain systems in order for the brain to execute a complex cognitive process.

Working memory is a critical component of executive function that allows people to complete complex tasks in the moment. Here, the authors show that this ability is underpinned by two newly defined brain networks.

Details

Title
Multimodal network dynamics underpinning working memory
Author
Murphy, Andrew C 1 ; Bertolero Maxwell A 2 ; Papadopoulos Lia 3 ; Lydon-Staley, David M 2   VIAFID ORCID Logo  ; Bassett, Danielle S 4   VIAFID ORCID Logo 

 University of Pennsylvania, Department of Bioengineering, School of Engineering & Applied Sciences, Philadelphia, USA (GRID:grid.25879.31) (ISNI:0000 0004 1936 8972); University of Pennsylvania, Perelman School of Medicine, Philadelphia, USA (GRID:grid.25879.31) (ISNI:0000 0004 1936 8972) 
 University of Pennsylvania, Department of Bioengineering, School of Engineering & Applied Sciences, Philadelphia, USA (GRID:grid.25879.31) (ISNI:0000 0004 1936 8972) 
 University of Pennsylvania, Department of Physics and Astronomy, School of Arts & Sciences, Philadelphia, USA (GRID:grid.25879.31) (ISNI:0000 0004 1936 8972) 
 University of Pennsylvania, Department of Bioengineering, School of Engineering & Applied Sciences, Philadelphia, USA (GRID:grid.25879.31) (ISNI:0000 0004 1936 8972); University of Pennsylvania, Department of Physics and Astronomy, School of Arts & Sciences, Philadelphia, USA (GRID:grid.25879.31) (ISNI:0000 0004 1936 8972); University of Pennsylvania, Department of Neurology, Perelman School of Medicine, Philadelphia, USA (GRID:grid.25879.31) (ISNI:0000 0004 1936 8972); University of Pennsylvania, Department of Psychiatry, Perelman School of Medicine, Philadelphia, USA (GRID:grid.25879.31) (ISNI:0000 0004 1936 8972); University of Pennsylvania, Department of Electrical & Systems Engineering, School of Engineering & Applied Sciences, Philadelphia, USA (GRID:grid.25879.31) (ISNI:0000 0004 1936 8972); Santa Fe Institute, Santa Fe, USA (GRID:grid.209665.e) (ISNI:0000 0001 1941 1940) 
Publication year
2020
Publication date
2020
Publisher
Nature Publishing Group
e-ISSN
20411723
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2413232057
Copyright
© The Author(s) 2020. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.