Stability of brain-behavior correlation patterns across measures of social support

The social environment has a critical influence on human development, cognition, and health. By using network approaches to map and analyze the connectivity between all pairs of brain regions simultaneously, we can clarify how relationships between brain regions (e.g. connectivity) change as a function of social relationships. Here we apply multilayer modeling and modularity maximization-both established tools in network neuroscience-to jointly cluster patterns of brain-behavior associations for seven social support measures. Our analyses build on both neuroecological findings and network neuroscientific approaches. In particular we find that subcortical and control systems are especially sensitive to different constructs of perceived social support. Network nodes in these systems are highly flexible; their community affiliations, which reflect groups of nodes with similar patterns of brain behavior associations, differ across social support measures. The multilayer approach used here enables direct comparison of the roles of all regions of the brain across all social support measures included. Additionally, our application of multilayer modeling to patterns of brainbehavior correlations, as opposed to just functional connectivity, represents an innovation in how multilayer models are used in. More than that, it offers a generalizable technique for studying the stability brain-behavior correlations.