This study investigates how the brain's functional network adapts as individuals master a dual n-back task. Using fMRI scans over a 6-week training period, researchers assessed brain network modularity. Results showed a steady increase in whole-brain modularity during training. Dynamic analysis revealed training-modulated autonomy of the default mode system and integration among task-positive systems. Task automation led to nonlinear changes in integration between fronto-parietal and default mode systems, and integration with the subcortical system, suggesting that mastering a cognitively demanding task may result in a more segregated network organization.
Publisher
Nature Communications
Published On
May 15, 2020
Authors
Karolina Finc, Kamil Bonna, Xiaosong He, David M. Lydon-Staley, Simone Kühn, Włodzisław Duch, Danielle S. Bassett
Tags
brain network
dual n-back task
fMRI
modularity
cognitive load
task automation
integration
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