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Updated: Sep 10, 2026

Brain Imaging Investigation of the Neural Correlates of Observing Virtual Social Interactions
Published on: July 6, 2011
Connection & Context: The variable neural architecture of social relationships
Haily Merritt1, Divyangana Rakesh2, Richard F Betzel3
1Network Science Institute, Northeastern University London, London, UK.
Abstract:
Our brains are contextual, connected, social, and dynamic; failing to account for these aspects of the brain together risks misleading results that could be translated into worse health outcomes, especially for populations already underrepresented in neuroscience. In this manuscript, we synthesize recent studies that investigate the network neuroecology of social interaction and characterize how brain network organization varies across interpersonal social experience. We describe how certain patterns of brain connectivity are associated with particular social environments as a result of trade-offs in how functional connections are distributed across the brain in accordance with social experience. We call these environment-specific patterns of connectivity and their trajectories of reconfiguration over development network neuroendophenotypes. We propose two intersecting mechanisms that underlie the development of network neuroendophenotypes, addressing both how and why brain network organization contextually varies: one more protracted via stress physiology and the other more acute via the processing of affective/supportive touch. The existence of distinguishable patterns of connectivity that are associated with different social environments has important consequences for studying normative neurodevelopment and brain-based biomarkers of disease: The pattern of brain network organization that is associated with better (mental) health may look different in different environments. Ignoring social context therefore risks either pathologizing healthy brains or dismissing real disease among those who would otherwise be considered healthy. Moving forward, methodological advances that can effectively treat brain network organization as a dynamic, high dimensional, contextually influenced neuroendophenotype will be crucial for future research.
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