Dynamic reconfiguration of functional brain networks during working memory training

Karolina Finc (), Kamil Bonna, Xiaosong He, David M. Lydon-Staley, Simone Kühn, Włodzisław Duch and Danielle S. Bassett
Additional contact information
Karolina Finc: Nicolaus Copernicus University
Kamil Bonna: Nicolaus Copernicus University
Xiaosong He: University of Pennsylvania
David M. Lydon-Staley: University of Pennsylvania
Simone Kühn: Max Planck Institute for Human Development
Włodzisław Duch: Nicolaus Copernicus University
Danielle S. Bassett: University of Pennsylvania

Nature Communications, 2020, vol. 11, issue 1, 1-15

Abstract: Abstract The functional network of the brain continually adapts to changing environmental demands. The consequence of behavioral automation for task-related functional network architecture remains far from understood. We investigated the neural reflections of behavioral automation as participants mastered a dual n-back task. In four fMRI scans equally spanning a 6-week training period, we assessed brain network modularity, a substrate for adaptation in biological systems. We found that whole-brain modularity steadily increased during training for both conditions of the dual n-back task. In a dynamic analysis,we found that the autonomy of the default mode system and integration among task-positive systems were modulated by training. The automation of the n-back task through training resulted in non-linear changes in integration between the fronto-parietal and default mode systems, and integration with the subcortical system. Our findings suggest that the automation of a cognitively demanding task may result in more segregated network organization.

Date: 2020
References: Add references at CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.nature.com/articles/s41467-020-15631-z Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-15631-z

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/s41467-020-15631-z

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().