Independent component analysis-based source-level hyperlink analysis for two-person neuroscience studies.

Two-person neuroscience, a perspective in understanding human social cognition and interaction, involves designing immersive social interaction experiments as well as simultaneously recording brain activity of two or more subjects, a process termed "hyperscanning." Using newly developed imaging techniques, the interbrain connectivity or hyperlink of various types of social interaction has been revealed. Functional near-infrared spectroscopy (fNIRS)-hyperscanning provides a more naturalistic environment for experimental paradigms of social interaction and has recently drawn much attention. However, most fNIRS-hyperscanning studies have computed hyperlinks using sensor data directly while ignoring the fact that the sensor-level signals contain confounding noises, which may lead to a loss of sensitivity and specificity in hyperlink analysis. In this study, on the basis of independent component analysis (ICA), a source-level analysis framework is proposed to investigate the hyperlinks in a fNIRS two-person neuroscience study. The performance of five widely used ICA algorithms in extracting sources of interaction was compared in simulative datasets, and increased sensitivity and specificity of hyperlink analysis by our proposed method were demonstrated in both simulative and real two-person experiments.

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

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.

Cross-brain neurofeedback: scientific concept and experimental platform.

The present study described a new type of multi-person neurofeedback with the neural synchronization between two participants as the direct regulating target, termed as "cross-brain neurofeedback." As a first step to implement this concept, an experimental platform was built on the basis of functional near-infrared spectroscopy, and was validated with a two-person neurofeedback experiment. This novel concept as well as the experimental platform established a framework for investigation of the relationship between multiple participants' cross-brain neural synchronization and their social behaviors, which could provide new insight into the neural substrate of human social interactions.