Inter-brain synchronization occurs without physical co-presence during cooperative online gaming

The neurosociological paradigm of the metaverse

Metaverse integrates people into the virtual world, and challenges depend on advances in human, technological, and procedural dimensions. Until now, solutions to these challenges have not involved extensive neurosociological research. The study explores the pioneering neurosociological paradigm in metaverse, emphasizing its potential to revolutionize our understanding of social interactions through advanced methodologies such as hyperscanning and interbrain synchrony. This convergence presents unprecedented opportunities for neurotypical and neurodivergent individuals due to technology personalization. Traditional face-to-face, interbrain coupling, and metaverse interactions are empirically substantiated. Biomarkers of social interaction as feedback between social brain networks and metaverse is presented. The innovative contribution of findings to the broader literature on metaverse and neurosociology is substantiated. This article also discusses the ethical aspects of integrating the neurosociological paradigm into the metaverse.

Cooperation objective evaluation in aviation: validation and comparison of two novel approaches in simulated environment

Introduction

In operational environments, human interaction and cooperation between individuals are critical to efficiency and safety. These states are influenced by individuals' cognitive and emotional states. Human factor research aims to objectively quantify these states to prevent human error and maintain constant performances, particularly in high-risk settings such as aviation, where human error and performance account for a significant portion of accidents.

Methods

Thus, this study aimed to evaluate and validate two novel methods for assessing the degree of cooperation among professional pilots engaged in real-flight simulation tasks. In addition, the study aimed to assess the ability of the proposed metrics to differentiate between the expertise levels of operating crews based on their levels of cooperation. Eight crews were involved in the experiments, consisting of four crews of Unexperienced pilots and four crews of Experienced pilots. An expert trainer, simulating air traffic management communication on one side and acting as a subject matter expert on the other, provided external evaluations of the pilots' mental states during the simulation. The two novel approaches introduced in this study were formulated based on circular correlation and mutual information techniques.

Results and discussion

The findings demonstrated the possibility of quantifying cooperation levels among pilots during realistic flight simulations. In addition, cooperation time is found to be significantly higher (p < 0.05) among Experienced pilots compared to Unexperienced ones. Furthermore, these preliminary results exhibited significant correlations (p < 0.05) with subjective and behavioral measures collected every 30 s during the task, confirming their reliability.

Hyperscanning literature after two decades of neuroscientific research: A scientometric review

Hyperscanning, a neuroimaging approach introduced in 2002 for simultaneously recording the brain activity of multiple participants, has significantly contributed to our understanding of social interactions. Nevertheless, the existing literature requires systematic organization to advance our knowledge. This study, after two decades of hyperscanning research, aims to identify the primary thematic domains and the most influential documents in the field. We conducted a scientometric analysis to examine co-citation patterns quantitatively, using a sample of 548 documents retrieved from Scopus and their 32,022 cited references. Our analysis revealed ten major thematic domains in hyperscanning research, with the most impactful document authored by Czeszumski and colleagues in 2020. Notably, while hyperscanning was initially developed for functional magnetic resonance imaging (fMRI), our findings indicate a substantial influence of research conducted using electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS). The introduction of fNIRS and advancements in EEG methods have enabled the implementation of more ecologically valid experiments for investigating social interactions. The study also highlights the need for more research that combines multi-brain neural stimulation with neuroimaging techniques to understand the causal role played by interpersonal neural synchrony in social interactions.

Bringing together multimodal and multilevel approaches to study the emergence of social bonds between children and improve social AI

This protocol paper outlines an innovative multimodal and multilevel approach to studying the emergence and evolution of how children build social bonds with their peers, and its potential application to improving social artificial intelligence (AI). We detail a unique hyperscanning experimental framework utilizing functional near-infrared spectroscopy (fNIRS) to observe inter-brain synchrony in child dyads during collaborative tasks and social interactions. Our proposed longitudinal study spans middle childhood, aiming to capture the dynamic development of social connections and cognitive engagement in naturalistic settings. To do so we bring together four kinds of data: the multimodal conversational behaviors that dyads of children engage in, evidence of their state of interpersonal rapport, collaborative performance on educational tasks, and inter-brain synchrony. Preliminary pilot data provide foundational support for our approach, indicating promising directions for identifying neural patterns associated with productive social interactions. The planned research will explore the neural correlates of social bond formation, informing the creation of a virtual peer learning partner in the field of Social Neuroergonomics. This protocol promises significant contributions to understanding the neural basis of social connectivity in children, while also offering a blueprint for designing empathetic and effective social AI tools, particularly for educational contexts.

An Analytical Approach for Naturalistic Cooperative and Competitive EEG-Hyperscanning Data: A Proof-of-Concept Study

Investigating the neural mechanisms underlying both cooperative and competitive joint actions may have a wide impact in many social contexts of human daily life. An effective pipeline of analysis for hyperscanning data recorded in a naturalistic context with a cooperative and competitive motor task has been missing. We propose an analytical pipeline for this type of joint action data, which was validated on electroencephalographic (EEG) signals recorded in a proof-of-concept study on two dyads playing cooperative and competitive table tennis. Functional connectivity maps were reconstructed using the corrected imaginary part of the phase locking value (ciPLV), an algorithm suitable in case of EEG signals recorded during turn-based competitive joint actions. Hyperbrain, within-, and between-brain functional connectivity maps were calculated in three frequency bands (i.e., theta, alpha, and beta) relevant during complex motor task execution and were characterized with graph theoretical measures and a clustering approach. The results of the proof-of-concept study are in line with recent findings on the main features of the functional networks sustaining cooperation and competition, hence demonstrating that the proposed pipeline is promising tool for the analysis of joint action EEG data recorded during cooperation and competition using a turn-based motor task.

Inter-brain desynchronization in social interaction: a consequence of subjective involvement?

Hyperscanning approaches to human neuroscience aim to uncover the neural mechanisms of social interaction. They have been largely guided by the expectation that increased levels of engagement between two persons will be supported by higher levels of inter-brain synchrony (IBS). A common approach to measuring IBS is phase synchrony in the context of EEG hyperscanning. Yet the growing number of experimental findings does not yield a straightforward interpretation, which has prompted critical reflections about the field's theoretical and methodological principles. In this perspective piece, we make a conceptual contribution to this debate by considering the role of a possibly overlooked effect of inter-brain desynchronization (IBD), as for example measured by decreased phase synchrony. A principled reason to expect this role comes from the recent proposal of irruption theory, which operationalizes the efficacy of a person's subjective involvement in behavior generation in terms of increased neural entropy. Accordingly, IBD is predicted to increase with one or more participant's socially motivated subjective involvement in interaction, because of the associated increase in their neural entropy. Additionally, the relative prominence of IBD compared to IBS is expected to vary in time, as well as across frequency bands, depending on the extent that subjective involvement is elicited by the task and/or desired by the person. If irruption theory is on the right track, it could thereby help to explain the notable variability of IBS in social interaction in terms of a countertendency from another factor: IBD due to subjective involvement.

Exploring Inter-Brain Electroencephalogram Patterns for Social Cognitive Assessment During Jigsaw Puzzle Solving

Social interaction enables the smooth progression of our daily lives. Mounting evidence from recent hyperscanning neuroimaging studies indicates that key components of social behavior can be evaluated using inter-brain oscillations and connectivity. However, mapping out inter-brain networks and developing neurocognitive theories that explain how humans co-create and share information during social interaction remains challenging. In this study, we developed a jigsaw puzzle-solving game with hyperscanning electroencephalography (EEG) signals recorded to investigate inter-brain activities during social interactions involving cooperation and competition. Participants were recruited and paired into dyads to participate in the multiplayer jigsaw puzzle game with 32-channel EEG signals recorded. The corresponding event-related potentials (ERPs), brain oscillations, and inter-brain functional connectivity were analyzed. The results showed different ERP morphologies of P3 patterns in competitive and cooperative contexts, and brain oscillations in the low-frequency band may be an indicator of social cognitive activities. Furthermore, increased inter-brain functional connectivity in the delta, theta, alpha, and beta frequency bands was observed in the competition mode compared to the cooperation mode. By presenting comparable and valid hyperscanning EEG results alongside those of previous studies using traditional paradigms, this study demonstrates the potential of utilizing hyperscanning techniques in real-life game-playing scenarios to quantitatively assess social cognitive interactions involving cooperation and competition. Our approach offers a promising platform with potential applications in the flexible assessment of psychiatric disorders related to social functioning.

The Effects of Distancing Design Collaboration Necessitated by COVID-19 on Brain Synchrony in Teams Compared to Co-Located Design Collaboration: A Preliminary Study

Due to the widespread involvement of distributed collaboration triggered by COVID-19, it has become a new trend that has continued into the post-pandemic era. This study investigated collective performance within two collaborative environments (co-located and distancing settings) by assessing inter-brain synchrony patterns (IBS) among design collaborators using functional near-infrared spectroscopy. The preliminary study was conducted with three dyads who possessed 2-3 years of professional product design experience. Each dyad completed two designated design tasks in distinct settings. In the distributed condition, participants interacted through video conferencing in which they were allowed to communicate by verbalization and sketching using a shared digital whiteboard. To prevent the influences of different sketching tools on design outputs, we employed digital sketching for both environments. The interactions between collaborators were identified in three behaviors: verbal only, sketch only, and mixed communication (verbal and sketch). The consequences revealed a higher level of IBS when mixed communication took place in distributed conditions than in co-located conditions. Comparably, the occurrence of IBS increased when participants solely utilized sketching as the interaction approach within the co-located setting. A mixed communication method combining verbalization and sketching might lead to more coordinated cognitive processes when in physical isolation. Design collaborators are inclined to adjust their interaction behaviors in order to adapt to different design environments, strengthen the exchange of ideas, and construct design consensus. Overall, the present paper discussed the performance of virtual collaborative design based on a neurocognitive perspective, contributing valuable insights for the future intervention design that promotes effective virtual teamwork.

Decoding Multi-Brain Motor Imagery From EEG Using Coupling Feature Extraction and Few-Shot Learning

Electroencephalography (EEG)-based motor imagery (MI) is one of brain computer interface (BCI) paradigms, which aims to build a direct communication pathway between human brain and external devices by decoding the brain activities. In a traditional way, MI BCI replies on a single brain, which suffers from the limitations, such as low accuracy and weak stability. To alleviate these limitations, multi-brain BCI has emerged based on the integration of multiple individuals' intelligence. Nevertheless, the existing decoding methods mainly use linear averaging or feature integration learning from multi-brain EEG data, and do not effectively utilize coupling relationship features, resulting in undesired decoding accuracy. To overcome these challenges, we proposed an EEG-based multi-brain MI decoding method, which utilizes coupling feature extraction and few-shot learning to capture coupling relationship features among multi-brains with only limited EEG data. We performed an experiment to collect EEG data from multiple persons who engaged in the same task simultaneously and compared the methods on the collected data. The comparison results showed that our proposed method improved the performance by 14.23% compared to the single-brain mode in the 10-shot three-class decoding task. It demonstrated the effectiveness of the proposed method and usability of the method in the context of only small amount of EEG data available.

Pseudo-mutual gazing enhances interbrain synchrony during remote joint attention tasking

INTRODUCTION

Mutual gaze enables people to share attention and increase engagement during social interactions through intentional and implicit messages. Although previous studies have explored gaze behaviors and neural mechanisms underlying in-person eye contact, the growing prevalence of remote communication has raised questions about how to establish mutual gaze remotely and how the brains of interacting individuals synchronize.

METHODS

To address these questions, we conducted a study using eye trackers to create a pseudo-mutual gaze channel that mirrors the gazes of each interacting dyad on their respective remote screens. To demonstrate fluctuations in coupling across brains, we incorporated electroencephalographic hyperscanning techniques to simultaneously record the brain activity of interacting dyads engaged in a joint attention task in player-observer, collaborative, and competitive modes.

RESULTS

Our results indicated that mutual gaze could improve the efficiency of joint attention activities among remote partners. Moreover, by employing the phase locking value, we could estimate interbrain synchrony (IBS) and observe low-frequency couplings in the frontal and temporal regions that varied based on the interaction mode. While dyadic gender composition significantly affected gaze patterns, it did not impact the IBS.

CONCLUSION

These results provide insight into the neurological mechanisms underlying remote interaction through the pseudo-mutual gaze channel and have significant implications for developing effective online communication environments.