# Stability and variation of brain-behavior correlation patterns across measures of social support

## TL;DR

This study explores how brain-behavior patterns change with different types of social support, revealing flexible brain systems influenced by social relationships.

## Contribution

The paper introduces a novel application of multilayer modeling to analyze brain-behavior correlations across social support measures.

## Key findings

- Subcortical and control brain systems show high flexibility in brain-behavior associations based on social support types.
- Community affiliations of brain network nodes vary across different social support measures.
- The multilayer approach offers a generalizable method for studying brain-behavior correlation stability.

## Abstract

The social environment has a critical influence on human development, cognition, and health. Research in health psychology and social neuroscience indicate an urgent need to understand how social relationships are associated with brain function and organization. To address this, 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. 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. This multilayer approach enables direct comparison of brain-behavior associations across social contexts for all brain regions and builds on both ecological and developmental neuroscientific 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. Additionally, our application of multilayer modeling to patterns of brain-behavior correlations, as opposed to just functional connectivity, represents an innovation in how multilayer models are used in human neuroscience. More than that, it offers a generalizable technique for studying the stability and variation of brain-behavior associations.