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Multimodal network dynamics underpinning working memory

Author

Listed:
  • Andrew C. Murphy

    (University of Pennsylvania
    University of Pennsylvania)

  • Maxwell A. Bertolero

    (University of Pennsylvania)

  • Lia Papadopoulos

    (University of Pennsylvania)

  • David M. Lydon-Staley

    (University of Pennsylvania)

  • Danielle S. Bassett

    (University of Pennsylvania
    University of Pennsylvania
    University of Pennsylvania
    University of Pennsylvania)

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.

Suggested Citation

  • Andrew C. Murphy & Maxwell A. Bertolero & Lia Papadopoulos & David M. Lydon-Staley & Danielle S. Bassett, 2020. "Multimodal network dynamics underpinning working memory," Nature Communications, Nature, vol. 11(1), pages 1-13, December.
    • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-15541-0
    DOI: 10.1038/s41467-020-15541-0
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    Cited by:

    1. Elizabeth L. Johnson & Jack J. Lin & David King-Stephens & Peter B. Weber & Kenneth D. Laxer & Ignacio Saez & Fady Girgis & Mark D’Esposito & Robert T. Knight & David Badre, 2023. "A rapid theta network mechanism for flexible information encoding," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    2. Adam R. Pines & Bart Larsen & Zaixu Cui & Valerie J. Sydnor & Maxwell A. Bertolero & Azeez Adebimpe & Aaron F. Alexander-Bloch & Christos Davatzikos & Damien A. Fair & Ruben C. Gur & Raquel E. Gur & H, 2022. "Dissociable multi-scale patterns of development in personalized brain networks," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    3. D. Jones & V. Lowe & J. Graff-Radford & H. Botha & L. Barnard & D. Wiepert & M. C. Murphy & M. Murray & M. Senjem & J. Gunter & H. Wiste & B. Boeve & D. Knopman & R. Petersen & C. Jack, 2022. "A computational model of neurodegeneration in Alzheimer’s disease," Nature Communications, Nature, vol. 13(1), pages 1-13, December.

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