Although activation/deactivation of specific brain regions have been shown to be predictive of successful memory encoding, the relationship between time-varying large-scale brain networks and fluctuations of memory encoding performance remains unclear. Here we investigated time-varying functional connectivity patterns across the human brain in periods of 30–40 s, which have recently been implicated in various cognitive functions. During functional magnetic resonance imaging, participants performed a memory encoding task, and their performance was assessed with a subsequent surprise memory test. A graph analysis of functional connectivity patterns revealed that increased integration of the subcortical, default-mode, salience, and visual subnetworks with other subnetworks is a hallmark of successful memory encoding. Moreover, multivariate analysis using the graph metrics of integration reliably classified the brain network states into the period of high (vs. low) memory encoding performance. Our findings suggest that a diverse set of brain systems dynamically interact to support successful memory encoding.
- Ryuta Aoki
- Koji Jimura
- Kiyoshi Nakahara
- Kiyoshi Nakahara
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Human subjects: All experimental procedures were approved by the Ethics Committee of Kochi University of Technology. Informed consent was obtained from all participants.
- Roberto Cabeza, Duke University, United States
© 2018, Keerativittayayut et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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