Data from: Large-scale network integration in the human brain tracks temporal fluctuations in memory encoding performance

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) memo
ry encoding performance. Our findings suggest that a diverse set of brain
systems dynamically interact to support successful memory encoding.