Unveiling Redundant and Synergistic Higher-Order Brain Interactions with Multivariate Information Theory

Brisbane Convention & Exhibition Centre 

The functional connectivity network, constructed from pairwise dependencies between brain regions, is a well-established tool for studying the brain. While powerful, functional connectivity is limited by its inability to capture interactions between more than two brain regions (higher-order interactions). In this talk, I will explore how multivariate information theory reveals higher-order dependencies in the human brain and allows us to identify two types of types of interactions: redundant and synergistic. I will present results from applying the O-information [1] to resting state fMRI data, showing that both functional connectivity and canonical functional systems capture primarily redundant interactions. However, subsystems dominated by synergistic interactions are widespread in the cortex. In contrast to redundant subsystems, highly synergistic subsystems are typically composed of brain regions from multiple functional systems. Like functional connectivity, redundant and synergistic interactions are time-varying. I will show results indicating that the same set of brain regions can become redundant and synergistic throughout the length of a scan, and that the location of the most strongly redundant and most strongly synergistic interaction changes in time but exhibits notable recurrence. As a whole, my talk will argue that higher-order interactions in the brain are an under-explored space that, made accessible with the tools of multivariate information theory, may offer novel insights.