Cluster imaging of multi-brain networks (CIMBN): a general framework for hyperscanning and modeling a group of interacting brains

Abstract

Studying the neural basis of human social interactions is a key topic in the field of social neuroscience. Brain imaging studies in this field usually focus on the neural correlates of the social interactions between two participants. However, as the participant number further increases, even by a small amount, great difficulties raise. One challenge is how to concurrently scan all the interacting brains with high ecological validity, especially for a large number of participants. The other challenge is how to effectively model the complex group interaction behaviors emerging from the intricate neural information exchange among a group of socially organized people. Confronting these challenges, we propose a new approach called “Cluster Imaging of Multi-brain Networks” (CIMBN). CIMBN consists of two parts. The first part is a cluster imaging technique with high ecological validity based on multiple functional near-infrared spectroscopy (fNIRS) systems. Using this technique, we can easily extend the simultaneous imaging capacity of social neuroscience studies up to dozens of participants. The second part of CIMBN is a multi-brain network (MBN) modeling method based on graph theory. By taking each brain as a network node and the relationship between any two brains as a network edge, one can construct a network model for a group of interacting brains. The emergent group social behaviors can then be studied using the network's properties, such as its topological structure and information exchange efficiency. Although there is still much work to do, as a general framework for hyperscanning and modeling a group of interacting brains, CIMBN can provide new insights into the neural correlates of group social interactions, and advance social neuroscience and social psychology.

Steady Beat Sound Facilitates both Coordinated Group Walking and Inter-Subject Neural Synchrony

“…Most previous studies on social interactions have focused on interactive tasks wherein the subjects had some constraints on their motions (NIRS: Cui et al, 2012; Jiang et al, 2012; Cheng et al, 2015; Duan et al, 2015; EEG: Lindenberger et al, 2009; Astolfi et al, 2010; Dumas et al, 2010; Yun et al, 2012) because the signal transfer was restricted by NIRS fibers or electric cords of the EEG. In an attempt to relieve such constraints, using a portable EEG, a previous study showed the possibility of measuring brain activities of multiple persons during interaction wherein the subjects had none of the above-mentioned limits (Gevins et al, 2012).…”

Interpersonal frontopolar neural synchronization in group communication: An exploration toward fNIRS hyperscanning of natural interactions

“…In exploiting the strength of fNIRS and applying the hyperscanning method to various forms of unconstrained, real-life communications/interactions, however, both Regarding the first objective, although some recent studies have begun extending it into natural triadic communication (Jiang et al, 2015) and interactions involving additional individuals (Duan et al, 2015), most previous studies have focused on dyadic and controlled forms of communication. Unstructured interactions involving more than two individuals entail aspects that do not exist in such controlled dyadic communication.…”

Algebraic Topology of Multi-Brain Connectivity Networks Reveals Dissimilarity in Functional Patterns during Spoken Communications

“…In this respect, the research of the social impact on the processes in the brain [27–29] as well as the brain processes that underly an effective social behaviour [30–38] is becoming a subject of increasing interest. New approaches using simultaneous scanning of groups of participants are being developed to study social cognition [39, 40]. The studies of face-to-face communications in dyads reveal a significant degree of synchronisation in particular brain areas, depending on the performed task [34–36, 38].…”

“…Furthermore, a higher brain activation level characterises the leader compared to its follower, the game builder compared to its partner, as well as the same individual performing the cooperation compared to the competition role [37]. In contrast to the extensive study of functional brain connections, as stated above, little attention has been devoted [38, 40] to analyse multi-brain graphs and to identify the social impact onto the functional brain networks.…”