Brain network integration, segregation and quasi-periodic activation and deactivation during tasks and rest

Previous studies have shown that a re-organization of the brain's functional connectome expressed in terms of network integration and segregation may play a pivotal role for brain function. However, it has been proven diffi-cult to fully capture both processes independently in a single methodological framework. In this study, by starting from pair-wise assessments of instantaneous phase synchronization and community membership, we assemble spatiotemporally flexible networks that reflect changes in integration/segregation that occur at a spectrum of spatial as well as temporal scales. This is achieved by iteratively assembling smaller networks into larger units under the constraint that the smaller units should be internally integrated, i.e. belong to the same community. The assembled subnetworks can be partly overlapping and differ in size across time. Our results show that sub-network integration and segregation occur simultaneously in the brain. During task performance, global changes in synchronization between networks arise that are tied to the underlying temporal design of the experiment. We show that a hallmark property of the dynamics of the brain's functional connectome is a presence of quasi-periodic patterns of network activation and deactivation, which during task performance becomes intertwined with the underlying temporal structure of the experimental paradigm. Additionally, we show that the degree of network integration throughout a n-back working memory task is correlated to performance.

Automated summary

Previous research has suggested that the re-organization of the brain's functional connectome, specifically in terms of network integration and segregation, plays a significant role in brain function. However, it has been challenging to capture both processes effectively within a single methodological framework. In this study, we developed a flexible network assembly approach that incorporates changes in integration and segregation at various spatial and temporal scales. We found that sub-network integration and segregation occur simultaneously in the brain, and changes in synchronization between networks during task performance are associated with the experimental design. We also discovered that the degree of network integration during a working memory task is correlated with performance.