The goal of this project is to discover the dynamical principles and mechanisms at play both within and between human brains during real-time social interaction. The research plan employs a three-pronged approach that combines (1) experimental manipulations to test specific hypotheses regarding key issues in the neurophysiology of social neuroscience (2) sophisticated measurement and analysis tools from the theory of dynamical systems, including virtual partner interaction (behavioral dynamic clamp of reciprocally coupled humans and model-partners) and (3) multiscale neurocomputational modeling of both structure and function in order to advance our understanding of how individual behavior and the interaction of individuals drives basic forms of social behavior. In our previous research, we established a comprehensive framework to tackle real- time interactions between people in simple, well-defined experimental paradigms in which pairs of participants simultaneously performed and perceived each other's movements. The research program led to the discovery of the phi complex, a neuromarker of social coordination. Also clarified were the contributions of other neuromarkers, especially alpha and mu, to different phases and facets of social behavior. What is most needed now -and what we seek support for in the present Competing Renewal- is to understand the dynamical orchestration of identified neuromarkers over the course of social behavior. The experimental thread works hand-in-hand with neurocomputational modeling of social behavior, theoretical models informing experiments and vice-versa.
The aims of this research program-still very much in its infancy-- are (1) to elucidate the """"""""neuromarker choreography"""""""", that is, to determine when each neuromarker is recruited and disengaged, which neuromarkers originate from which brain areas and how neuromarkers interact with each other in transient networks during the course of social behavior. All of the proposed work is geared to the prediction of efficient or deficient outcomes as assessed by detailed single trial analysis of real-time social behavior;(2) to construct a human dynamic clamp that allows for direct manipulation of the interaction between human participants and virtual partners endowed with human appearance and coordinative capacities. This new paradigm opens up the detailed parametric exploration of social behavior;and (3) to integrate the findings in a multiscale neuro- computational model of social behavior, a platform that will enable understanding of basic mechanisms of interpersonal interactions at combined neural, behavioral and social levels. Successful achievement of this program will specify the neurobehavioral routes leading to improved social function. Given the vast number of pathologies with etiological or symptomatic ties to social behavior, such information will afford many translational opportunities for the compensation or remediation of deficits in diseases such as autism, schizophrenia, depression and dementia to name just a few.
Social interaction is a prime example of an emergent property in complex systems that requires dynamical investigations formalized at multiple scales in brains and behavior. The proposed research conducted by an interdisciplinary team uses dual high density EEG arrays, sophisticated behavioral measures and dynamical analyses and biologically realistic computational models to uncover the neural choreography of social coordination. Given the vast number of pathologies that entertains etiological or symptomatic ties with social behavior, such information should lead to many translational opportunities for the remediation of deficits in social behavior (in autism, schizophrenia, depression and dementia to name a few).
| Zhang, Mengsen; Kelso, J A Scott; Tognoli, Emmanuelle (2018) Critical diversity: Divided or united states of social coordination. PLoS One 13:e0193843 |
| Tognoli, Emmanuelle; Dumas, Guillaume; Kelso, J A Scott (2018) A roadmap to computational social neuroscience. Cogn Neurodyn 12:135-140 |
| Bressler, Steven L; Kelso, J A Scott (2016) Coordination Dynamics in Cognitive Neuroscience. Front Neurosci 10:397 |
| Correia, Vanda; Passos, Pedro; Araújo, Duarte et al. (2016) Coupling tendencies during exploratory behaviours of competing players in rugby union dyads. Eur J Sport Sci 16:11-9 |
| Kelso, J A Scott (2016) On the Self-Organizing Origins of Agency: (Trends in Cognitive Sciences 20, 490-499; June 14, 2016). Trends Cogn Sci 20:868 |
| Kelso, J A Scott (2016) On the Self-Organizing Origins of Agency. Trends Cogn Sci 20:490-499 |
| Zhang, Mengsen; Dumas, Guillaume; Kelso, J A Scott et al. (2016) Enhanced emotional responses during social coordination with a virtual partner. Int J Psychophysiol 104:33-43 |
| Tognoli, Emmanuelle; Kelso, J A Scott (2015) The coordination dynamics of social neuromarkers. Front Hum Neurosci 9:563 |
| Jing, Min; McGinnity, T Martin; Coleman, Sonya et al. (2015) Temporal changes of diffusion patterns in mild traumatic brain injury via group-based semi-blind source separation. IEEE J Biomed Health Inform 19:1459-71 |
| Kostrubiec, Viviane; Dumas, Guillaume; Zanone, Pier-Giorgio et al. (2015) The Virtual Teacher (VT) Paradigm: Learning New Patterns of Interpersonal Coordination Using the Human Dynamic Clamp. PLoS One 10:e0142029 |
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