Social interaction in real-life contexts necessitates dynamical interactions among two or more brains as individuals listen, speak, act, and mutually adapt to one another to reach shared understanding. Elucidating how brains forge such shared understanding requires shifting from a ?one-brain? to a ?multiple-brain? frame of reference, as well as from artificial laboratory conditions to natural, real-life settings. Here we outline a novel framework to identify inter-brain dynamical coupling that underpins knowledge about social phenomena (e.g., mental states, social norms, emotions, etc.), henceforth referred to as social knowledge. The long-term goal of our laboratories is to understand how neural networks couple, within and across brains, to create and share information that enables social understanding and connectedness. We intend to develop a novel brain-to-brain coupling framework to better understand how social concepts are represented in the brain and how they are transferred across brains to achieve group cohesiveness. The overall objective of this application is to identify mechanisms that facilitate coupling across a speaker and a listener during real?life interaction. This approach is innovative because it uses new experimental paradigms optimize for studying social interactions in naturalistic contexts, employs both fMRI and fNIRS methods (single scanning and hyperscanning), and includes development of novel analysis methods for modeling shared brain responses to complex, natural social stimuli in real-life contexts. This contribution is significant because the proposed research will provide new insights into a central function of the human brain: the ability to connect with others by dynamically and interactively creating and sharing social knowledge. The work proposed in this application will advance knowledge of how brains process and share information in ways that promote social understanding and will produce new approaches for detecting and diagnosing communication and developmental disorders.

Public Health Relevance

In this proposal, we advance a new and versatile brain-to-brain coupling framework, which in combination with innovations neuroimaging methods including hyperscanning fMRI, portable hyperscanning fNIRS, and new mathematical tools, will open new ways for quantifying dyadic interactions during communication in real-life social settings. Such tools will enable the concurrent recording of neural dynamics across brains in clinical settings, such as during caregiver-child and clinician-patient interactions. We argue that such measurements can be used in the future as a valuable biomarker for detecting and diagnosing communication and developmental disorders, as well as a tool for assessing the effectiveness of psychological and pharmacological interventions for improving the trajectory of social outcomes related to mental health.

National Institute of Health (NIH)
National Institute of Mental Health (NIMH)
Research Project (R01)
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Special Emphasis Panel (ZMH1)
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Ferrante, Michele
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Princeton University
Schools of Arts and Sciences
United States
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Zadbood, A; Chen, J; Leong, Y C et al. (2017) How We Transmit Memories to Other Brains: Constructing Shared Neural Representations Via Communication. Cereb Cortex 27:4988-5000