Abstract

It is well known that the large-scale functional MRI connectome of the human brain is composed of a manifold of so called resting-state networks (RSNs). However, the network dynamics, such as integration and segregation between and within RSNs are largely unknown. In this talk, I will describe some recent work done in our research group that addresses this question. Using a novel frequency analysis method together with graph theory we analyzed the frequency dependency of low-frequency BOLD fMRI resting-state signal (0.01–0.1 Hz) in a cohort of 80 subjects. Our results show that the existence of functional hubs, the central nodes of the networks, fluctuates as a function of frequency and that the membership of hubs to different RSNs shifts dynamically across frequency. Further, we show that the global network efficiency and network integration is peaking at 0.07 – 0.08 Hz. In my talk, I will discuss the observed frequency dependence on the spatial configuration of hubs and its implications for our understanding of the dynamics of large-scale network integration and segregation in the human brain.