Cohesive network reconfiguration accompanies extended training

Abstract

Human behavior is supported by flexible neurophysiological processes that enable the fine‐scale manipulation of information across distributed neural circuits. Yet, approaches for understanding the dynamics of these circuit interactions have been limited. One promising avenue for quantifying and describing these dynamics lies in multilayer network models. Here, networks are composed of nodes (which represent brain regions) and time‐dependent edges (which represent statistical similarities in activity time series). We use this approach to examine functional connectivity measured by non‐invasive neuroimaging techniques. These multilayer network models facilitate the examination of changes in the pattern of statistical interactions between large‐scale brain regions that might facilitate behavior. In this study, we define and exercise two novel measures of network reconfiguration, and demonstrate their utility in neuroimaging data acquired as healthy adult human subjects learn a new motor skill. In particular, we identify putative functional modules in multilayer networks and characterize the degree to which nodes switch between modules. Next, we define cohesive switches, in which a set of nodes moves between modules together as a group, and we define disjoint switches, in which a single node moves between modules independently from other nodes. Together, these two concepts offer complementary yet distinct insights into the changes in functional connectivity that accompany motor learning. More generally, our work offers statistical tools that other researchers can use to better understand the reconfiguration patterns of functional connectivity over time. Hum Brain Mapp 38:4744–4759, 2017. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Dynamic reconfiguration, fragmentation and integration of whole-brain modular structure across depths of unconsciousness

“…To test our hypothesis that brain regions change modules in a more uncoordinated manner with increasing levels of isoflurane dose, we calculated the disjointed flexibility (disjointedness) of each brain region on each partition, defined by the number of times the region changes modules independently (i.e., without other brain regions) relative to the total number of possible changes (Telesford et al 2017) . We calculated the mean disjointedness by taking the average over all regions on each partition, before taking the mean over these partition means (this procedure was also performed for all other region-specific measures; see below).…”

“…Based on this finding, we hypothesized that the opposite arrangement would also be true, that is, that brain regions would change modules in a more coordinated manner at lower levels of dose. To test this hypothesis, we calculated the strength of cohesive flexibility (cohesion strength) of each region on each partition, an independent measure from disjointedness (Telesford et al 2017) . We calculated this measure by first determining the number of times each region changes modules together with each other region (relative to the total number of possible changes) and then summing over all other regions (Telesford et al 2017) .…”

“…To test this hypothesis, we calculated the strength of cohesive flexibility (cohesion strength) of each region on each partition, an independent measure from disjointedness (Telesford et al 2017) . We calculated this measure by first determining the number of times each region changes modules together with each other region (relative to the total number of possible changes) and then summing over all other regions (Telesford et al 2017) . The fit of a linear regression model revealed a negative linear relationship between dose and cohesion strength ( β dose =-3.276, t(56)=-5.648, R 2 =0.363, p=5.644e-7; Figure 2D).…”

“…Likewise, our finding that cohesion strength decreased with increased isoflurane dose ( Figure 2C) is consistent with the decrease in whole-brain state transitions at higher dose (Hutchison et al 2014;Barttfeld et al 2015) , assuming that such state transitions are more readily driven by groups of brain regions acting in concert than by individual brain regions. The inverse relationship between disjointedness and cohesion strength, which serve as two independent measures of regional flexibility (Telesford et al 2017) , suggests that these measures may also provide a useful marker for tracking levels of conscious processing. Prior work using dynamic connectivity methods has shown that the awake state is characterized by a rich and flexible repertoire of whole-brain states (Barttfeld et al 2015;Uhrig et al 2018) , and that these states are expressed more frequently at lighter (compared to deeper) levels of sedation (Hutchison et al 2014;Barttfeld et al 2015) .…”

“…Prior work using dynamic connectivity methods has shown that the awake state is characterized by a rich and flexible repertoire of whole-brain states (Barttfeld et al 2015;Uhrig et al 2018) , and that these states are expressed more frequently at lighter (compared to deeper) levels of sedation (Hutchison et al 2014;Barttfeld et al 2015) . From this perspective, coordinated changes in modular structure may provide a signature of an engaged mind, suggesting that cohesive flexibility should correlate with the performance of demanding cognitive tasks, from learning (Telesford et al 2017) and problem solving, to creative thinking. Our finding that promiscuity increased with decreasing isoflurane dose is also consistent with this possibility, assuming that the exploration of a larger number of diverse brain states entails a broader range of modular reconfigurations, and correspondingly, a proportionally larger repertoire of modules in which brain regions participate.…”