Multi-Frequency Functional Connectivity Networks of the Brain

Over the past twenty years, functional connectivity of the human brain has been studied using tools from complex network theory. One such tool is community detection which is fundamental for uncovering the links between structure and function in complex networks. Existing network models of the brain focus on average activity within a time window of interest and a given frequency band. Therefore, they cannot capture the changes in network connectivity across time and different frequency bands. Recently, multilayer brain networks have attracted a lot of attention as they can capture the full view of neuronal connectivity. In this talk, I will first give an overview on the construction of multilayer functional connectivity networks, where each layer corresponds to a different frequency band. I will then introduce a multilayer community detection algorithm by extending the definition of modularity to multilayer networks. The proposed approach is applied to electroencephalogram (EEG) data collected during a study of error monitoring in the human brain, where the differences between the communities formed within and across different frequency bands and response types are studied.