Overlapping Replicator Dynamics for Functional Subnetwork Identification

Abstract. Functional magnetic resonance imaging (fMRI) has been widely used for inferring brain regions that tend to work in tandem and grouping them into subnetworks. Despite that certain brain regions are known to interact with multiple subnetworks, few existing techniques support identification of subnetworks with overlaps. To address this limitation, we propose a novel approach based on replicator dynamics that facilitates detection of sparse overlapping subnetworks. We refer to our approach as overlapping replicator dynamics (RDOL). On synthetic data, we show that RDOL achieves higher accuracy in subnetwork identification than state-of-the-art methods. On real data, we demonstrate that RDOL is able to identify major functional hubs that are known to serve as communication channels between brain regions, in addition to detecting commonly observed functional subnetworks. Moreover, we illustrate that knowing the subnetwork overlaps enables inference of functional pathways, e.g. from primary sensory areas to the integration hubs