Is neuroimaging ready for the classroom? A systematic review of hyperscanning studies in learning

Interbrain synchrony attenuation during a peer cooperative task in young children with autistic traits -an EEG hyperscanning study

Young children with autism spectrum disorder (ASD) traits frequently encounter difficulties in peer interaction. Assessing peer interaction performance is crucial but challenging within the clinical diagnostic paradigm of ASD. Hyperscanning, which simultaneously monitors brain activity in multiple individuals, has become a popular tool for assessing social interaction's neural features. The present study aims to investigate the brain-to-brain connectivity between child-dyads engaged in a game-like collaborative peer interaction task via the hyperscanning electroencephalogram (EEG) approach. The final sample comprised 66 young children: 18 child dyads with typical development (TD), TD-TD, and 15 with ASD traits matched to TD, TD-ASD. The study indicated a depressed level of connectivity in the dyad group with ASD as the responder, with a notable decrease observed in the beta oscillation over the right parietal to left temporal coupling between subjects. A pattern that differed from that observed in the TD-TD group was identified with regard to full-band connectivity over the right-to-right temporal region. It was observed that the TD-TD group exhibited enhanced connectivity following the completion of the task, which was not the case for the TD-ASD group. Significant correlations were observed between scores on the ASD symptom rating scale and the selected significant interbrain connectivity index. The application of a hyperscanning EEG paradigm demonstrated that the participating children with autistic traits exhibited an attenuated and apparently distinct alteration pattern of interbrain connectivity in comparison to a control group. These findings highlight the value of physiologically based measures in informing etiological and interventional studies in neuropsychiatry.

Psychophysiological correlates of learner-instructor interaction: A scoping review

This article reviews recent studies of real-time learner-instructor interactions and psychophysiological indicators associated with this process. The initial systematic search of the literature yielded 2,663 articles; 26 peer-reviewed articles in English were included in the final sample. The learner-instructor interpersonal relationships were studied using neuroimaging, eye movements, and peripheral physiological devices. Retrieved articles covered several phenomena accompanying learning interaction, including attention and meditation processes, mental effort, engagement, inter-brain synchronization, relationship quality, and interpersonal behavior. Some articles emphasized the link between the aforementioned processes and learning outcomes. The following psychophysiological correlates of processes underlying learning interaction were indicated. Inter-brain synchronization in the prefrontal cortex and temporal-parietal area is associated with the social component of learning interactions and positively correlates with learning outcomes. Students' engagement is accompanied by a decrease in electroencephalography occipital alpha rhythm, indicating heightened attention. Experienced teachers tend to focus their gaze on students while balancing gaze between learners and content facilitates students' attention. Students' gaze allocation toward learning-related areas indicates attention and engagement, which varies with instructional strategies. Heart rate and electrodermal activity positively correlate with learners' engagement, increasing during active educational strategies and decreasing throughout the lesson. Finally, heart rate, reflecting physiological arousal and interpersonal behavior, relates to the emotions experienced by the teacher. However, most of the registered associations require replication and further research, as at this point, their direction and magnitude are inconclusive due to, most likely, the differences in the methods and analytical strategies. Limitations and implications for future research are discussed.

Is what I think what you think? Multilayer network-based inter-brain synchrony approach

Social interaction plays a crucial role in human societies, encompassing complex dynamics among individuals. To understand social interaction at the neural level, researchers have utilized hyperscanning in several social settings. These studies have mainly focused on inter-brain synchrony and the efficiency of paired functional brain networks, examining group interactions in dyads. However, this approach may not fully capture the complexity of multiple interactions, potentially leading to gaps in understanding inter-network differences. To overcome this limitation, the present study aims to bridge this gap by introducing methodological enhancements using the multilayer network approach, which is tailored to extract features from multiple networks. We applied this strategy to analyze the triad condition during social behavior processes to identify group interaction indices. Additionally, to validate our methodology, we compared the multilayer networks of triad conditions with group synchrony to paired conditions without group synchrony, focusing on statistical differences between alpha and beta waves. Correlation analysis between inter-brain and group networks revealed that this methodology accurately reflects the characteristics of actual behavioral synchrony. The findings of our study suggest that measures of paired brain synchrony and group interaction may exhibit distinct trends, offering valuable insights into interpreting group synchrony.

A multi-layer EEG fusion decoding method with channel selection for multi-brain motor imagery

Traditional motor imagery-based single-brain computer interfaces(BCIs) face inherent limitations, such as unstable signals and low recognition accuracy. In contrast, multi-brain BCIs offer a promising solution by leveraging group electroencephalography (EEG) data. This paper presents a novel multi-layer EEG fusion method with channel selection for motor imagery-based multi-brain BCIs. We utilize mutual information convergent cross-mapping (MCCM) to identify channels that the represent causal relationships between brains; this strategy is combined with multiple linear discriminant analysis (MLDA) for decoding intentions via both data-layer and decision-layer strategies. Our experimental results demonstrate that the proposed method improves the accuracy of multi-brain motor imagery decoding by approximately 10% over that of the traditional methods, with a further 3%-5% accuracy increase due to the effective channel selection mechanism.

Relational neuroscience: Insights from hyperscanning research

Humans are highly social, typically without this ability requiring noticeable efforts. Yet, such social fluency poses challenges both for the human brain to compute and for scientists to study. Over the last few decades, neuroscientific research of human sociality has witnessed a shift in focus from single-brain analysis to complex dynamics occurring across several brains, posing questions about what these dynamics mean and how they relate to multifaceted behavioural models. We propose the term 'Relational Neuroscience' to collate the interdisciplinary research field devoted to modelling the inter-brain dynamics subserving human connections, spanning from real-time joint experiences to long-term social bonds. Hyperscanning, i.e., simultaneously measuring brain activity from multiple individuals, has proven to be a highly promising technique to investigate inter-brain dynamics. Here, we discuss how hyperscanning can help investigate questions within the field of Relational Neuroscience, considering a variety of subfields, including cooperative interactions in dyads and groups, empathy, attachment and bonding, and developmental neuroscience. While presenting Relational Neuroscience in the light of hyperscanning, our discussion also takes into account behaviour, physiology and endocrinology to properly interpret inter-brain dynamics within social contexts. We consider the strengths but also the limitations and caveats of hyperscanning to answer questions about interacting people. The aim is to provide an integrative framework for future work to build better theories across a variety of contexts and research subfields to model human sociality.

Embodied hyperscanning for studying social interaction: A scoping review of simultaneous brain and body measurements

We systematically investigated the application of embodied hyperscanning methodologies in social neuroscience research. Hyperscanning enables the simultaneous recording of neurophysiological and physiological signals from multiple participants. We highlight the trend toward integrating Mobile Brain/Body Imaging (MoBI) within the 4E research framework, which emphasizes the interconnectedness of brain, body, and environment. Our analysis revealed a geographic concentration of studies in the Global North, calling for global collaboration and transcultural research to balance the field. The predominant use of Magneto/Electroencephalogram (M/EEG) in these studies suggests a traditional brain-centric perspective in social neuroscience. Future research directions should focus on integrating diverse techniques to capture the dynamic interplay between brain and body functions in real-world contexts. Our review also finds a preference for tasks involving natural settings. Nevertheless, the analysis in hyperscanning studies is often limited to physiological signal synchrony between participants. This suggests a need for more holistic and complex approaches that combine inter-corporeal synchrony with intra-individual measures. We believe that the future of the neuroscience of relationships lies in embracing the complexity of cognition, integrating diverse methods and theories to enrich our grasp of human social behavior in its natural contexts.

Brain to brain musical interaction: A systematic review of neural synchrony in musical activities

The use of hyperscanning technology has revealed the neural mechanisms underlying multi-person interaction in musical activities. However, there is currently a lack of integration among various research findings. This systematic review aims to provide a comprehensive understanding of the social dynamics and brain synchronization in music activities through the analysis of 32 studies. The findings illustrate a strong correlation between inter-brain synchronization (IBS) and various musical activities, with the frontal, central, parietal, and temporal lobes as the primary regions involved. The application of hyperscanning not only advances theoretical research but also holds practical significance in enhancing the effectiveness of music-based interventions in therapy and education. The review also utilizes Predictive Coding Models (PCM) to provide a new perspective for interpreting neural synchronization in music activities. To address the limitations of current research, future studies could integrate multimodal data, adopt novel technologies, use non-invasive techniques, and explore additional research directions.

Eye-tracker and fNIRS: Using neuroscientific tools to assess the learning experience during children's educational robotics activities

In technology education, there has been a paradigmatic shift towards student-centered approaches such as learning by doing, constructionism, and experiential learning. Educational robotics allows students to experiment with building and interacting with their creations while also fostering collaborative work. However, understanding the student's response to these approaches is crucial to adapting them during the teaching-learning process. In this sense, neuroscientific tools such as Functional Near-Infrared Spectroscopy and Eye-tracker could be useful, allowing the investigation of relevant states experienced by students. Although they have already been used in educational research, their practical relevance in the teaching-learning process has not been extensively investigated. In this perspective article expressing our position, we bring four examples of learning experiences in a robotics class with children, in which we illustrate the usefulness of these tools.

Teach a man to fish: Hyper-brain evidence on scaffolding strategy enhancing creativity acquisition and transfer

Creativity is an indispensable competency in today's innovation-driven society. Yet, the influences of instructional strategy, a key determinant of educational outcomes, on the creativity-fostering process remains an unresolved mystery. We proposed that instructional strategy affects creativity cultivation and further investigated the intricate neural mechanisms underlying this relationship. In a naturalistic laboratory setting, 66 instructor-learner dyads were randomized into three groups (scaffolding, explanation, and control), with divergent thinking instructions separately. Functional near-infrared spectroscopy (fNIRS) hyperscanning simultaneously collected brain signals in the prefrontal cortex and temporal-parietal junction regions. Results indicated that learners instructed with a scaffolding strategy demonstrated superior creative performance both in acquisition (direct learning) and transfer (use in a novel context) of creativity skills, compared to pretest levels. In contrast, the control and explanation groups did not exhibit such effects. Notably, we also observed remarkable interbrain neural synchronization (INS) between instructors and learners in the left superior frontal cortex in the scaffolding group, but not in the explanation or control groups. Furthermore, INS positively predicted enhancements in creativity performance (acquisition and transfer), indicating that it is a crucial neural mechanism in the creativity-fostering process. These findings reveal that scaffolding facilitates the acquisition and transfer of creativity and deepen our understanding of the neural mechanisms underlying the process of creativity-fostering. The current study provides valuable insights for implementing teaching strategies to fostering creativity.

Getting closer to social interactions using electroencephalography in developmental cognitive neuroscience

The field of developmental cognitive neuroscience is advancing rapidly, with large-scale, population-wide, longitudinal studies emerging as a key means of unraveling the complexity of the developing brain and cognitive processes in children. While numerous neuroscientific techniques like functional magnetic resonance imaging (fMRI), functional near-infrared spectroscopy (fNIRS), magnetoencephalography (MEG), and transcranial magnetic stimulation (TMS) have proved advantageous in such investigations, this perspective proposes a renewed focus on electroencephalography (EEG), leveraging underexplored possibilities of EEG. In addition to its temporal precision, low costs, and ease of application, EEG distinguishes itself with its ability to capture neural activity linked to social interactions in increasingly ecologically valid settings. Specifically, EEG can be measured during social interactions in the lab, hyperscanning can be used to study brain activity in two (or more) people simultaneously, and mobile EEG can be used to measure brain activity in real-life settings. This perspective paper summarizes research in these three areas, making a persuasive argument for the renewed inclusion of EEG into the toolkit of developmental cognitive and social neuroscientists.

The Brain Economy: Advancing Brain Science to Better Understand the Modern Economy

The coming years are likely to be turbulent due to a myriad of factors or polycrisis, including an escalation in climate extremes, emerging public health threats, weak productivity, increases in global economic instability and further weakening in the integrity of global democracy. These formidable challenges are not exogenous to the economy but are in some cases generated by the system itself. They can be overcome, but only with far-reaching changes to global economics. Our current socio-economic paradigm is insufficient for addressing these complex challenges, let alone sustaining human development, well-being and happiness. To support the flourishing of the global population in the age of polycrisis, we need a novel, person-centred and collective paradigm. The brain economy leverages insights from neuroscience to provide a novel way of centralising the human contribution to the economy, how the economy in turn shapes our lives and positive feedbacks between the two. The brain economy is primarily based on Brain Capital, an economic asset integrating brain health and brain skills, the social, emotional, and the diversity of cognitive brain resources of individuals and communities. People with healthy brains are essential to navigate increasingly complex systems. Policies and investments that improve brain health and hence citizens' cognitive functions and boost brain performance can increase productivity, stimulate greater creativity and economic dynamism, utilise often underdeveloped intellectual resources, afford social cohesion, and create a more resilient, adaptable and sustainability-engaged population.

Bridging Stories and Science: An fNIRS-based hyperscanning investigation into child learning in STEM

Early STEM education is crucial for later learning. This novel study utilised fNIRS to examine how STEM teaching methods (i.e., traditional, storytelling, storyboarding) affect neural activity synchronisation between teachers and students. Our results showed that left and right inferior frontal gyrus (IFG) for storytelling teaching versus traditional teaching, superior temporal gyrus for storyboard teaching versus traditional teaching, and left angular gyrus for storyboard and storytelling teaching were significant different in brain synchronisation. In the storytelling teaching condition, left supramarginal gyrus brain synchrony was found to improve STEM learning outcomes. In the storyboard teaching condition, IFG brain synchrony correlated positively with STEM learning improvement. The findings confirmed that story-based teaching and storyboarding can improve STEM learning efficacy at the neural level and unscored the significant role of neural synchronization as a predictor of learning outcomes.