INDIVIDUAL-SPECIFIC CEREBELLAR NETWORKS ESTIMATED FROM RESTING-STATE FUNCTIONAL CONNECTIVITY

Abstract

Individual-specific brain networks can be estimated using resting-state functional magnetic resonance imaging (rs-fMRI) not only in the cerebral cortex but also in the cerebellum. It has been shown that group-average brain networks cannot capture individual-specific network features in both cerebral cortex and cerebellum. We first estimated individual-specific cerebellar networks in two intensively sampled participants. Multiple representations of the cerebral cortical networks are found in the cerebellum. There are common structures shared across participants as well as individual variations. We then estimated individual-specific cerebellar networks using a larger dataset. The large sample allowed us to quantify individual variation in cerebellar network lateralization, correspondence with task activation, and their relationships with behavioral traits. Association networks have higher cerebrocerebellar lateralization consistency in size than sensory-motor networks. The topography of individual-level cerebellar networks also agreed well with task activation patterns. Finally, individual variations in cerebellar network topography could be used to predict human behavior.