Juggling Increases Interhemispheric Brain Connectivity: A Visual and Quantitative dMRI Study

Abstract

We use visualization to help analyze a diffusion magnetic resonance imaging study that has investigated the effects of learning how to juggle on nerve fiber microstructure in the human brain. Building on a standard voxel-wise statistical analysis, we perform a more elaborate visual analysis of the affected fiber bundles. Based on the visualization, we hypothesize that brain image data allows us to distinguish learners from controls with better-thanrandom accuracy; we test this hypothesis with a machine learning technique. We believe that our results exemplify the value of more tightly integrating statistical with visual analysis and machine learning in brain imaging studies, in order to complement the group-wise view of traditional analysis with insights about specific individuals.