Brain-to-Brain Synchrony Tracks Real-World Dynamic Group Interactions in the Classroom

Analyzing teacher-student interactions through graph theory applied to hyperscanning fNIRS data

Teacher-student relationships have been found consistently important for student school effectiveness in mathematics in the last three decades. Although this observation is generally made from the teacher's perspective, neuroscience can provide new insights by establishing the neurobiological underpinning of social interactions. This paper further develops this line of research by utilizing graph theory to represent interactions between teachers and students at the neural level. Through hyperscanning with functional near-infrared spectroscopy (fNIRS), we collected data from the prefrontal cortex and the temporoparietal junction of 24 dyads composed of a teacher and a student. Each dyad used a board game to perform a programming logic class that consisted of three steps: independent activities (control), presentation of concepts, and interactive exercises. Graph theory provides results regarding the strength of teacher-student interaction and the main channels involved in these interactions. We combined graph modularity and bootstrap to measure pair coactivation, thus establishing the strength of teacher-student interaction. Also, graph centrality detects the main brain channels involved during this interaction. In general, the teacher's most relevant nodes rely on the regions related to language and number processing, spatial cognition, and attention. Also, the students' most relevant nodes rely on the regions related to task management.

Brain-to-brain communication during musical improvisation: a performance case study

Understanding and predicting others' actions in ecological settings is an important research goal in social neuroscience. Here, we deployed a mobile brain-body imaging (MoBI) methodology to analyze inter-brain communication between professional musicians during a live jazz performance. Specifically, bispectral analysis was conducted to assess the synchronization of scalp electroencephalographic (EEG) signals from three expert musicians during a three-part 45 minute jazz performance, during which a new musician joined every five minutes. The bispectrum was estimated for all musician dyads, electrode combinations, and five frequency bands. The results showed higher bispectrum in the beta and gamma frequency bands (13-50 Hz) when more musicians performed together, and when they played a musical phrase synchronously. Positive bispectrum amplitude changes were found approximately three seconds prior to the identified synchronized performance events suggesting preparatory cortical activity predictive of concerted behavioral action. Moreover, a higher amount of synchronized EEG activity, across electrode regions, was observed as more musicians performed, with inter-brain synchronization between the temporal, parietal, and occipital regions the most frequent. Increased synchrony between the musicians' brain activity reflects shared multi-sensory processing and movement intention in a musical improvisation task.

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

Whether education research can be informed by findings from neuroscience studies has been hotly debated since Bruer's (1997) famous claim that neuroscience and education are "a bridge too far". However, this claim came before recent advancements in portable electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) technologies, and second-person neuroscience techniques that brought about significant headway in understanding instructor-learner interactions in the classroom. To explore whether neuroscience and education are still two very separate fields, we systematically review 15 hyperscanning studies that were conducted in real-world classrooms or that implemented a teaching-learning task to investigate instructor-learner dynamics. Findings from this investigation illustrate that inter-brain synchrony between instructor and learner is an additional and valuable dimension to understand the complex web of instructor- and learner-related variables that influence learning. Importantly, these findings demonstrate the possibility of conducting real-world classroom studies with portable neuroimaging techniques and highlight the potential of such studies in providing translatable real-world implications. Once thought of as incompatible, a successful coupling between neuroscience and education is now within sight.

The Brain's Control Networks in Reading: Insights From Cross-Task Studies of Youth

Humans engage multiple brain systems to read successfully, including using regions important for vision, language, and control. Control refers to the set of executive processes in the brain that guide moment-to-moment behavior in service of our goals. There is a growing appreciation for the role of the brain's control system in reading comprehension, in reading skill change over time, and in those who have difficulty with the reading process. One way to understand the brain's control engagement in reading may be to study control engagement across multiple tasks in order to study consistencies, or cross-task similarities, relative to reading-specific variations. In this commentary, I briefly summarize some of our recent work studying the brain's control networks across different tasks (e.g., when reading, or doing different executive function tasks). I then review our findings of when control activation does or does not relate to measures of reading ability, and reading growth over time. The utility of cross-task comparisons in neuroimaging is noted, as well as the need to better understand multiple sources of heterogeneity in our developmental samples. I end by discussing a few of the many future directions for further study of the brain with regard to the brain's control processing and academic achievement.

MEG correlates of speech planning in simple vs. interactive picture naming in children and adults

The picture naming task is common both as a clinical task and as a method to study the neural bases of speech production in the healthy brain. However, this task is not reflective of most naturally occurring productions, which tend to happen within a context, typically in dialogue in response to someone else's production. How the brain basis of the classic "confrontation picture naming" task compares to the planning of utterances in dialogue is not known. Here we used magnetoencephalography (MEG) to measure neural activity associated with language production using the classic picture naming task as well as a minimal variant of the task, intended as more interactive or dialogue-like. We assessed how neural activity is affected by the interactive context in children, teenagers, and adults. The general pattern was that in adults, the interactive task elicited a robust sustained increase of activity in frontal and temporal cortices bilaterally, as compared to simple picture naming. This increase was present only in the left hemisphere in teenagers and was absent in children, who, in fact, showed the reverse effect. Thus our findings suggest a robustly bilateral neural basis for the coordination of interaction and a very slow developmental timeline for this network.

Quantification of inter-brain coupling: A review of current methods used in haemodynamic and electrophysiological hyperscanning studies

Hyperscanning is a form of neuroimaging experiment where the brains of two or more participants are imaged simultaneously whilst they interact. Within the domain of social neuroscience, hyperscanning is increasingly used to measure inter-brain coupling (IBC) and explore how brain responses change in tandem during social interaction. In addition to cognitive research, some have suggested that quantification of the interplay between interacting participants can be used as a biomarker for a variety of cognitive mechanisms aswell as to investigate mental health and developmental conditions including schizophrenia, social anxiety and autism. However, many different methods have been used to quantify brain coupling and this can lead to questions about comparability across studies and reduce research reproducibility. Here, we review methods for quantifying IBC, and suggest some ways moving forward. Following the PRISMA guidelines, we reviewed 215 hyperscanning studies, across four different brain imaging modalities: functional near-infrared spectroscopy (fNIRS), functional magnetic resonance (fMRI), electroencephalography (EEG) and magnetoencephalography (MEG). Overall, the review identified a total of 27 different methods used to compute IBC. The most common hyperscanning modality is fNIRS, used by 119 studies, 89 of which adopted wavelet coherence. Based on the results of this literature survey, we first report summary statistics of the hyperscanning field, followed by a brief overview of each signal that is obtained from each neuroimaging modality used in hyperscanning. We then discuss the rationale, assumptions and suitability of each method to different modalities which can be used to investigate IBC. Finally, we discuss issues surrounding the interpretation of each method.

Friend or foe: classifying collaborative interactions using fNIRS

To succeed, effective teams depend on both cooperative and competitive interactions between individual teammates. Depending on the context, cooperation and competition can amplify or neutralize a team's problem solving ability. Therefore, to assess successful collaborative problem solving, it is first crucial to distinguish competitive from cooperative interactions. We investigate the feasibility of using lightweight brain sensors to distinguish cooperative from competitive interactions in pairs of participants (N=84) playing a decision-making game involving uncertain outcomes. We measured brain activity using functional near-infrared spectroscopy (fNIRS) from social, motor, and executive areas during game play alone and in competition or cooperation with another participant. To distinguish competitive, cooperative, and alone conditions, we then trained support vector classifiers using combinations of features extracted from fNIRS data. We find that features from social areas of the brain outperform other features for discriminating competitive, cooperative, and alone conditions in cross-validation. Comparing the competitive and alone conditions, social features yield a 5% improvement over motor and executive features. Social features show promise as means of distinguishing competitive and cooperative environments in problem solving settings. Using fNIRS data provides a real-time measure of subjective experience in an ecologically valid environment. These results have the potential to inform intelligent team monitoring to provide better real-time feedback and improve team outcomes in naturalistic settings.

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.

Epigenetic modification of the oxytocin receptor gene is associated with child-parent neural synchrony during competition

Interpersonal neural synchrony (INS) occurs when neural electrical activity temporally aligns between individuals during social interactions. It has been used as a metric for interpersonal closeness, often during naturalistic child-parent interactions. This study evaluated whether other biological correlates of social processing predicted the prevalence of INS during child-parent interactions, and whether their observed cooperativity modulated this association. Child-parent dyads (n = 27) performed a visuospatial tower-building task in cooperative and competitive conditions. Neural activity was recorded using mobile electroencephalogram (EEG) headsets, and experimenters coded video-recordings post-hoc for behavioral attunement. DNA methylation of the oxytocin receptor gene (OXTRm) was measured, an epigenetic modification associated with reduced oxytocin activity and socioemotional functioning. Greater INS during competition was associated with lower child OXTRm, while greater behavioral attunement during competition and cooperation was associated with higher parent OXTRm. These differential relationships suggest that interpersonal dynamics as measured by INS may be similarly reflected by other biological markers of social functioning, irrespective of observed behavior. Children's self-perceived communication skill also showed opposite associations with parent and child OXTRm, suggesting complex relationships between children's and their parents' social functioning. Our findings have implications for ongoing developmental research, supporting the utility of biological metrics in characterizing interpersonal relationships.

The role of mindfulness on theta inter-brain synchrony during cooperation feedback processing: An EEG-based hyperscanning study

Mindfulness appears to improve empathy and understanding in relationships, which are necessary for successful cooperation. However, the impact of mindfulness on cooperation has not been fully studied. This study used hyperscanning technique to examine the effect of mindfulness on the inter-brain synchrony of interacting individuals during the cooperative tasks. Forty-one dyads were randomly assigned to a mindfulness group or a non-mindfulness group. Dyads of the mindfulness group performed a short mindfulness exercise following a 15-minute mindfulness audio guidance. Dyads of the non-mindfulness group were instructed to rest quietly with their eyes closed. Then, simultaneously and continuously EEG was recorded from all dyads when they completed a computer-based cooperative game task. Reaction times (RTs) and success rates were used to indicate the behavioral performance, and phase locking value (PLV) was used to indicate the inter-brain synchrony. The results showed that (1) Greater theta inter-brain synchrony during the cooperative computer game tasks was observed in the mindfulness group than in the non-mindfulness group; (2) Greater theta inter-brain synchrony was observed in the successful cooperation conditions as compared to those in the failure cooperation conditions; (3) Greater theta inter-brain synchrony was observed at the frontal region as compared to those at the parietal-occipital region in the successful cooperation condition. The results expand the neural basis of the effects of mindfulness on cooperation feedback processing.

A Brain-To-Brain Mechanism for Social Transmission of Threat Learning

Survival and adaptation in environments require swift and efficacious learning about what is dangerous. Across species, much of such threat learning is acquired socially, e.g., through the observation of others' ("demonstrators'") defensive behaviors. However, the specific neural mechanisms responsible for the integration of information shared between demonstrators and observers remain largely unknown. This dearth of knowledge is addressed by performing magnetoencephalography (MEG) neuroimaging in demonstrator-observer dyads. A set of stimuli are first shown to a demonstrator whose defensive responses are filmed and later presented to an observer, while neuronal activity is recorded sequentially from both individuals who never interacted directly. These results show that brain-to-brain coupling (BtBC) in the fronto-limbic circuit (including insula, ventromedial, and dorsolateral prefrontal cortex) within demonstrator-observer dyads predict subsequent expressions of learning in the observer. Importantly, the predictive power of BtBC magnifies when a threat is imminent to the demonstrator. Furthermore, BtBC depends on how observers perceive their social status relative to the demonstrator, likely driven by shared attention and emotion, as bolstered by dyadic pupillary coupling. Taken together, this study describes a brain-to-brain mechanism for social threat learning, involving BtBC, which reflects social relationships and predicts adaptive, learned behaviors.

A scalable and robust system for audience EEG recordings

The neural mechanisms that unfold when humans form a large group defined by an overarching context, such as audiences in theater or sports, are largely unknown and unexplored. This is mainly due to the lack of availability of a scalable system that can record the brain activity from a significantly large portion of such an audience simultaneously. Although the technology for such a system has been readily available for a long time, the high cost as well as the large overhead in human resources and logistic planning have prohibited the development of such a system. However, during the recent years reduction in technology costs and size have led to the emergence of low-cost, consumer-oriented EEG systems, developed primarily for recreational use. Here by combining such a low-cost EEG system with other off-the-shelve hardware and tailor-made software, we develop in the lab and test in a cinema such a scalable EEG hyper-scanning system. The system has a robust and stable performance and achieves accurate unambiguous alignment of the recorded data of the different EEG headsets. These characteristics combined with small preparation time and low-cost make it an ideal candidate for recording large portions of audiences.

Tracking gaze position from EEG: Exploring the possibility of an EEG-based virtual eye-tracker

INTRODUCTION

Ocular artifact has long been viewed as an impediment to the interpretation of electroencephalogram (EEG) signals in basic and applied research. Today, the use of blind source separation (BSS) methods, including independent component analysis (ICA) and second-order blind identification (SOBI), is considered an essential step in improving the quality of neural signals. Recently, we introduced a method consisting of SOBI and a discriminant and similarity (DANS)-based identification method, capable of identifying and extracting eye movement-related components. These recovered components can be localized within ocular structures with a high goodness of fit (>95%). This raised the possibility that such EEG-derived SOBI components may be used to build predictive models for tracking gaze position.

METHODS

As proof of this new concept, we designed an EEG-based virtual eye-tracker (EEG-VET) for tracking eye movement from EEG alone. The EEG-VET is composed of a SOBI algorithm for separating EEG signals into different components, a DANS algorithm for automatically identifying ocular components, and a linear model to transfer ocular components into gaze positions.

RESULTS

The prototype of EEG-VET achieved an accuracy of 0.920° and precision of 1.510° of a visual angle in the best participant, whereas an average accuracy of 1.008° ± 0.357° and a precision of 2.348° ± 0.580° of a visual angle across all participants (N = 18).

CONCLUSION

This work offers a novel approach that readily co-registers eye movement and neural signals from a single-EEG recording, thus increasing the ease of studying neural mechanisms underlying natural cognition in the context of free eye movement.

The Synergy Zone: Connecting the Mind, Brain, and Heart for the Ideal Classroom Learning Environment

This paper proposes a new perspective on implementing neuroeducation in the classroom. The pandemic exacerbated the mental health issues of faculty and students, creating a mental health crisis that impairs learning. It is important to get our students back in "the zone", both cognitively and emotionally, by creating an ideal learning environment for capturing our students and keeping them-the Synergy Zone. Research that examines the classroom environment often focuses on the foreground-instructors' organizational and instructional aspects and content. However, the emotional climate of the classroom affects student well-being. This emotional climate would ideally exhibit the brain states of engagement, attention, connection, and enjoyment by addressing the mind, brain, and heart. This ideal learning environment would be achieved by combining proposed practices derived from three areas of research: flow theory, brain synchronization, and positive emotion with heart engagement. Each of these enhances the desired brain states in a way that the whole is greater than the sum of the individual parts. I call this the Synergy Zone. A limitation of this proposed model is that implementation of some aspects may be challenging, and professional development resources might be needed. This essay presenting this perspective provides the relevant scientific research and the educational implications of implementation.

Improvised herding: Mapping biobehavioral mechanisms that underlie group efficacy during improvised social interaction

Improvisation is a natural occurring phenomenon that is central to social interaction. Yet, improvisation is an understudied area in group processes and intergroup relations. Here we build on theory and research about human herding to study the contributions of improvisation on group efficacy and its biobehavioral underpinnings. We employed a novel multimodal approach and integrative method when observing face-to-face interactions-51 triads (total N = 153) drummed together in spontaneous-free improvisations as a group, while their electrodermal activity was monitored simultaneously with their second-by-second rhythmic coordination on a shared electronic drum machine. Our results show that three hypothesized factors of human herding-physiological synchrony, behavioral coordination, and emotional contagion-predict a sense of group efficacy in its group members. These findings are some of the first to show herding at three levels (physiological, behavioral, and mental) in a single study and lay a basis for understanding the role of improvisation in social interaction.

Defining the Science of Learning: A scoping review

BACKGROUND

Interest in research on the Science of Learning continues to grow. However, ambiguity about what this field is can negatively impact communication and collaboration and may inadequately inform educational training programs or funding initiatives that are not sufficiently inclusive in focus.

METHODS

The present scoping review aimed to synthesize a working definition of the Science of Learning using Web of Science and ProQuest database searches.

RESULTS

In total, 43 unique definitions were identified across 50 documents including journal articles, theses, conference papers, and book chapters. Definitions of the Science of Learning differed considerably when describing the fields thought to contribute to research on this topic.

CONCLUSIONS

Based on findings, we propose a working definition of the Science of Learning for discussion and further refinement: the scientific study of the underlying bases of learning with the goal of describing, understanding, or improving learning across developmental stages and diverse contexts.

Investigating the contributions of active, playful learning to student interest and educational outcomes

A growing body of evidence from the science of learning demonstrates the educational effectiveness of active, playful learning. Connections are emerging between this pedagogy and the broad set of skills that it promotes in learners, but potential mechanisms behind these relations remain unexplored. This paper offers a commentary based on the science of learning and interest development literature, suggesting that interest may mediate the relation between active, playful learning and student outcomes. This theory is established by identifying principles of active, playful learning that predict interest development and associations between learner interest and key skills for success in the classroom and beyond. Future research should investigate the dynamic relation between active, playful learning, interest, and student achievement over time and across phases of interest while taking a broader set of student outcomes into account.

Moving beyond the lab: investigating empathy through the Empirical 5E approach

Empathy is a complex and multifaceted phenomenon that plays a crucial role in human social interactions. Recent developments in social neuroscience have provided valuable insights into the neural underpinnings and bodily mechanisms underlying empathy. This methodology often prioritizes precision, replicability, internal validity, and confound control. However, fully understanding the complexity of empathy seems unattainable by solely relying on artificial and controlled laboratory settings, while overlooking a comprehensive view of empathy through an ecological experimental approach. In this article, we propose articulating an integrative theoretical and methodological framework based on the 5E approach (the "E"s stand for embodied, embedded, enacted, emotional, and extended perspectives of empathy), highlighting the relevance of studying empathy as an active interaction between embodied agents, embedded in a shared real-world environment. In addition, we illustrate how a novel multimodal approach including mobile brain and body imaging (MoBi) combined with phenomenological methods, and the implementation of interactive paradigms in a natural context, are adequate procedures to study empathy from the 5E approach. In doing so, we present the Empirical 5E approach (E5E) as an integrative scientific framework to bridge brain/body and phenomenological attributes in an interbody interactive setting. Progressing toward an E5E approach can be crucial to understanding empathy in accordance with the complexity of how it is experienced in the real world.

Music as a window into real-world communication

Communication has been studied extensively in the context of speech and language. While speech is tremendously effective at transferring ideas between people, music is another communicative mode that has a unique power to bring people together and transmit a rich tapestry of emotions, through joint music-making and listening in a variety of everyday contexts. Research has begun to examine the behavioral and neural correlates of the joint action required for successful musical interactions, but it has yet to fully account for the rich, dynamic, multimodal nature of musical communication. We review the current literature in this area and propose that naturalistic musical paradigms will open up new ways to study communication more broadly.

Intra- and inter-brain synchrony oscillations underlying social adjustment

Humans naturally synchronize their behavior with other people. However, although it happens almost automatically, adjusting behavior and conformity to others is a complex phenomenon whose neural mechanisms are still yet to be understood entirely. The present experiment aimed to study the oscillatory synchronization mechanisms underlying automatic dyadic convergence in an EEG hyperscanning experiment. Thirty-six people performed a cooperative decision-making task where dyads had to guess the correct position of a point on a line. A reinforcement learning algorithm was used to model different aspects of the participants' behavior and their expectations of their peers. Intra- and inter-connectivity among electrode sites were assessed using inter-site phase clustering in three main frequency bands (theta, alpha, beta) using a two-level Bayesian mixed-effects modeling approach. The results showed two oscillatory synchronization dynamics related to attention and executive functions in alpha and reinforcement learning in theta. In addition, inter-brain synchrony was mainly driven by beta oscillations. This study contributes preliminary evidence on the phase-coherence mechanism underlying inter-personal behavioral adjustment.

Spontaneous dyadic behaviour predicts the emergence of interpersonal neural synchrony

Synchronization of neural activity across brains - interpersonal neural synchrony (INS) - is emerging as a powerful marker of social interaction that predicts success of multi-person coordination, communication, and cooperation. As the origins of INS are poorly understood, we tested whether and how INS might emerge from spontaneous dyadic behavior. We recorded neural activity (EEG) and human behavior (full-body kinematics, eye movements and facial expressions) while dyads of participants were instructed to look at each other without speaking or making co-verbal gestures. We made four fundamental observations. First, despite the absence of a structured social task, INS emerged spontaneously only when participants were able to see each other. Second, we show that such spontaneous INS, comprising specific spectral and topographic profiles, did not merely reflect intra-personal modulations of neural activity, but it rather reflected real-time and dyad-specific coupling of neural activities. Third, using state-of-art video-image processing and deep learning, we extracted the temporal unfolding of three notable social behavioral cues - body movement, eye contact, and smiling - and demonstrated that these behaviors also spontaneously synchronized within dyads. Fourth, we probed the correlates of INS in such synchronized social behaviors. Using cross-correlation and Granger causality analyses, we show that synchronized social behaviors anticipate and in fact Granger cause INS. These results provide proof-of-concept evidence for studying interpersonal neural and behavioral synchrony under natural and unconstrained conditions. Most importantly, the results suggest that INS could be conceptualized as an emergent property of two coupled neural systems: an entrainment phenomenon, promoted by real-time dyadic behavior.

Naturalistic Hyperscanning with Wearable Magnetoencephalography

The evolution of human cognitive function is reliant on complex social interactions which form the behavioural foundation of who we are. These social capacities are subject to dramatic change in disease and injury; yet their supporting neural substrates remain poorly understood. Hyperscanning employs functional neuroimaging to simultaneously assess brain activity in two individuals and offers the best means to understand the neural basis of social interaction. However, present technologies are limited, either by poor performance (low spatial/temporal precision) or an unnatural scanning environment (claustrophobic scanners, with interactions via video). Here, we describe hyperscanning using wearable magnetoencephalography (MEG) based on optically pumped magnetometers (OPMs). We demonstrate our approach by simultaneously measuring brain activity in two subjects undertaking two separate tasks-an interactive touching task and a ball game. Despite large and unpredictable subject motion, sensorimotor brain activity was delineated clearly, and the correlation of the envelope of neuronal oscillations between the two subjects was demonstrated. Our results show that unlike existing modalities, OPM-MEG combines high-fidelity data acquisition and a naturalistic setting and thus presents significant potential to investigate neural correlates of social interaction.

A Versatile In-Ear Biosensing System and Body-Area Network for Unobtrusive Continuous Health Monitoring

To enable continuous, mobile health monitoring, body-worn sensors need to offer comparable performance to clinical devices in a lightweight, unobtrusive package. This work presents a complete versatile wireless electrophysiology data acquisition system (weDAQ) that is demonstrated for in-ear electroencephalography (EEG) and other on-body electrophysiology with user-generic dry-contact electrodes made from standard printed circuit boards (PCBs). Each weDAQ device provides 16 recording channels, driven right leg (DRL), a 3-axis accelerometer, local data storage, and adaptable data transmission modes. The weDAQ wireless interface supports deployment of a body area network (BAN) capable of aggregating various biosignal streams over multiple worn devices simultaneously, on the 802.11n WiFi protocol. Each channel resolves biopotentials ranging over 5 orders of magnitude with a noise level of 0.52 μVrms over a 1000-Hz bandwidth, and a peak SNDR of 119 dB and CMRR of 111 dB at 2 ksps. The device leverages in-band impedance scanning and an input multiplexer to dynamically select good skin contacting electrodes for reference and sensing channels. In-ear and forehead EEG measurements taken from subjects captured modulation of alpha brain activity, electrooculogram (EOG) characteristic eye movements, and electromyogram (EMG) from jaw muscles. Simultaneous ECG and EMG measurements were demonstrated on multiple, freely-moving subjects in their natural office environment during periods of rest and exercise. The small footprint, performance, and configurability of the open-source weDAQ platform and scalable PCB electrodes presented, aim to provide the biosensing community greater experimental flexibility and lower the barrier to entry for new health monitoring research.

Mobile cognition: imaging the human brain in the 'real world'

Cognitive neuroscience studies in humans have enabled decades of impactful discoveries but have primarily been limited to recording the brain activity of immobile participants in a laboratory setting. In recent years, advances in neuroimaging technologies have enabled recordings of human brain activity to be obtained during freely moving behaviours in the real world. Here, we propose that these mobile neuroimaging methods can provide unique insights into the neural mechanisms of human cognition and contribute to the development of novel treatments for neurological and psychiatric disorders. We further discuss the challenges associated with studying naturalistic human behaviours in complex real-world settings as well as strategies for overcoming them. We conclude that mobile neuroimaging methods have the potential to bring about a new era of cognitive neuroscience in which neural mechanisms can be studied with increased ecological validity and with the ability to address questions about natural behaviour and cognitive processes in humans engaged in dynamic real-world experiences.

A garment that measures brain activity: proof of concept of an EEG sensor layer fully implemented with smart textiles

This paper presents the first garment capable of measuring brain activity with accuracy comparable to that of state-of-the art dry electroencephalogram (EEG) systems. The main innovation is an EEG sensor layer (i.e., the electrodes, the signal transmission, and the cap support) made entirely of threads, fabrics, and smart textiles, eliminating the need for metal or plastic materials. The garment is connected to a mobile EEG amplifier to complete the measurement system. As a first proof of concept, the new EEG system (Garment-EEG) was characterized with respect to a state-of-the-art Ag/AgCl dry-EEG system (Dry-EEG) over the forehead area of healthy participants in terms of: (1) skin-electrode impedance; (2) EEG activity; (3) artifacts; and (4) user ergonomics and comfort. The results show that the Garment-EEG system provides comparable recordings to Dry-EEG, but it is more susceptible to artifacts under adverse recording conditions due to poorer contact impedances. The textile-based sensor layer offers superior ergonomics and comfort compared to its metal-based counterpart. We provide the datasets recorded with Garment-EEG and Dry-EEG systems, making available the first open-access dataset of an EEG sensor layer built exclusively with textile materials. Achieving user acceptance is an obstacle in the field of neurotechnology. The introduction of EEG systems encapsulated in wearables has the potential to democratize neurotechnology and non-invasive brain-computer interfaces, as they are naturally accepted by people in their daily lives. Furthermore, supporting the EEG implementation in the textile industry may result in lower cost and less-polluting manufacturing processes compared to metal and plastic industries.

Nonlinear and machine learning analyses on high-density EEG data of math experts and novices

Current trend in neurosciences is to use naturalistic stimuli, such as cinema, class-room biology or video gaming, aiming to understand the brain functions during ecologically valid conditions. Naturalistic stimuli recruit complex and overlapping cognitive, emotional and sensory brain processes. Brain oscillations form underlying mechanisms for such processes, and further, these processes can be modified by expertise. Human cortical functions are often analyzed with linear methods despite brain as a biological system is highly nonlinear. This study applies a relatively robust nonlinear method, Higuchi fractal dimension (HFD), to classify cortical functions of math experts and novices when they solve long and complex math demonstrations in an EEG laboratory. Brain imaging data, which is collected over a long time span during naturalistic stimuli, enables the application of data-driven analyses. Therefore, we also explore the neural signature of math expertise with machine learning algorithms. There is a need for novel methodologies in analyzing naturalistic data because formulation of theories of the brain functions in the real world based on reductionist and simplified study designs is both challenging and questionable. Data-driven intelligent approaches may be helpful in developing and testing new theories on complex brain functions. Our results clarify the different neural signature, analyzed by HFD, of math experts and novices during complex math and suggest machine learning as a promising data-driven approach to understand the brain processes in expertise and mathematical cognition.

Associations of Empathy with Teacher-Student Interactions: A Potential Ternary Model

Empathy has garnered increasing recognition as a pivotal component of teacher-student interactions and a notable determinant of student achievement. Nevertheless, the exact impact of empathy on teacher-student interactions remains elusive, despite research endeavors into the neural mechanisms of teacher empathy. Our article examines the cognitive neural processes of teacher empathy during various forms of teacher-student interactions. To this end, we first present a concise review of theoretical considerations related to empathy and interactions, followed by an extensive discussion of teacher-student interactions and teacher empathy through both "single-brain" and "dual-brain" perspectives. Drawing on these discussions, we propose a potential model of empathy that integrates the affective contagion, cognitive evaluation, and behavior prediction aspects of teacher-student interactions. Finally, future research directions are discussed.

Inter-brain coupling reflects disciplinary differences in real-world classroom learning

The classroom is the primary site for learning. A vital feature of classroom learning is the division of educational content into various disciplines. While disciplinary differences could substantially influence the learning process toward success, little is known about the neural mechanism underlying successful disciplinary learning. In the present study, wearable EEG devices were used to record a group of high school students during their classes of a soft (Chinese) and a hard (Math) discipline throughout one semester. Inter-brain coupling analysis was conducted to characterize students' classroom learning process. The students with higher scores in the Math final exam were found to have stronger inter-brain couplings to the class (i.e., all the other classmates), whereas the students with higher scores in Chinese were found to have stronger inter-brain couplings to the top students in the class. These differences in inter-brain couplings were also reflected in distinct dominant frequencies for the two disciplines. Our results illustrate disciplinary differences in the classroom learning from an inter-brain perspective, suggesting that an individual's inter-brain coupling to the class and to the top students could serve as potential neural correlates for successful learning in hard and soft disciplines correspondingly.

The Temporal Dynamics of Brain-to-Brain Synchrony Between Students and Teachers Predict Learning Outcomes

Much of human learning happens through interaction with other people, but little is known about how this process is reflected in the brains of students and teachers. Here, we concurrently recorded electroencephalography (EEG) data from nine groups, each of which contained four students and a teacher. All participants were young adults from the northeast United States. Alpha-band (8-12 Hz) brain-to-brain synchrony between students predicted both immediate and delayed posttest performance. Further, brain-to-brain synchrony was higher in specific lecture segments associated with questions that students answered correctly. Brain-to-brain synchrony between students and teachers predicted learning outcomes at an approximately 300-ms lag in the students' brain activity relative to the teacher's brain activity, which is consistent with the time course of spoken-language comprehension. These findings provide key new evidence for the importance of collecting brain data simultaneously from groups of learners in ecologically valid settings.

Wireless EEG: A survey of systems and studies

The popular brain monitoring method of electroencephalography (EEG) has seen a surge in commercial attention in recent years, focusing mostly on hardware miniaturization. This has led to a varied landscape of portable EEG devices with wireless capability, allowing them to be used by relatively unconstrained users in real-life conditions outside of the laboratory. The wide availability and relative affordability of these devices provide a low entry threshold for newcomers to the field of EEG research. The large device variety and the at times opaque communication from their manufacturers, however, can make it difficult to obtain an overview of this hardware landscape. Similarly, given the breadth of existing (wireless) EEG knowledge and research, it can be challenging to get started with novel ideas. Therefore, this paper first provides a list of 48 wireless EEG devices along with a number of important-sometimes difficult-to-obtain-features and characteristics to enable their side-by-side comparison, along with a brief introduction to each of these aspects and how they may influence one's decision. Secondly, we have surveyed previous literature and focused on 110 high-impact journal publications making use of wireless EEG, which we categorized by application and analyzed for device used, number of channels, sample size, and participant mobility. Together, these provide a basis for informed decision making with respect to hardware and experimental precedents when considering new, wireless EEG devices and research. At the same time, this paper provides background material and commentary about pitfalls and caveats regarding this increasingly accessible line of research.

Hyperscanning EEG Paradigm Applied to Remote vs. Face-To-Face Learning in Managerial Contexts: Which Is Better?

We propose a hyperscanning research design, where electroencephalographic (EEG) data were collected on an instructor and teams of learners. We compared neurophysiological measures within the frequency domain (delta, theta, alpha, and beta EEG bands) in the two conditions: face-to-face and remote settings. Data collection was carried out using wearable EEG systems. Conversational analysis was previously applied to detect comparable EEG time blocks and semantic topics. The digitalization of training can be considered a challenge but also a chance for organizations. However, if not carefully addressed, it might constitute a criticality. Limited research explored how remote, as opposed to face-to-face, training affects cognitive, (such as memory and attention), affective, and social processes in workgroups. Data showed an alpha desynchronization and, conversely, a theta and beta synchronization for the face-to-face condition. Moreover, trainees showed different patterns for beta power depending on the setting condition, with significantly increased power spectral density (PSD) in the face-to-face condition. These results highlight the relevance of neurophysiological measures in testing the e-learning process, in relation to the emotional engagement, memory encoding, and attentional processing.

Learning from others is good, with others is better: the role of social interaction in human acquisition of new knowledge

Learning in humans is highly embedded in social interaction: since the very early stages of our lives, we form memories and acquire knowledge about the world from and with others. Yet, within cognitive science and neuroscience, human learning is mainly studied in isolation. The focus of past research in learning has been either exclusively on the learner or (less often) on the teacher, with the primary aim of determining developmental trajectories and/or effective teaching techniques. In fact, social interaction has rarely been explicitly taken as a variable of interest, despite being the medium through which learning occurs, especially in development, but also in adulthood. Here, we review behavioural and neuroimaging research on social human learning, specifically focusing on cognitive models of how we acquire semantic knowledge from and with others, and include both developmental as well as adult work. We then identify potential cognitive mechanisms that support social learning, and their neural correlates. The aim is to outline key new directions for experiments investigating how knowledge is acquired in its ecological niche, i.e. socially, within the framework of the two-person neuroscience approach. This article is part of the theme issue 'Concepts in interaction: social engagement and inner experiences'.

Interpersonal attunement in social interactions: from collective psychophysiology to inter-personalized psychiatry and beyond

In this article, we analyse social interactions, drawing on diverse points of views, ranging from dialectics, second-person neuroscience and enactivism to dynamical systems, active inference and machine learning. To this end, we define interpersonal attunement as a set of multi-scale processes of building up and materializing social expectations-put simply, anticipating and interacting with others and ourselves. While cultivating and negotiating common ground, via communication and culture-building activities, are indispensable for the survival of the individual, the relevant multi-scale mechanisms have been largely considered in isolation. Here, collective psychophysiology, we argue, can lend itself to the fine-tuned analysis of social interactions, without neglecting the individual. On the other hand, an interpersonal mismatch of expectations can lead to a breakdown of communication and social isolation known to negatively affect mental health. In this regard, we review psychopathology in terms of interpersonal misattunement, conceptualizing psychiatric disorders as disorders of social interaction, to describe how individual mental health is inextricably linked to social interaction. By doing so, we foresee avenues for an inter-personalized psychiatry, which moves from a static spectrum of disorders to a dynamic relational space, focusing on how the multi-faceted processes of social interaction can help to promote mental health. This article is part of the theme issue 'Concepts in interaction: social engagement and inner experiences'.

Three heads are better than one: cooperative learning brains wire together when a consensus is reached

Theories of human learning converge on the view that individuals working together learn better than do those working independently. Little is known, however, about the neural mechanisms of learning through cooperation. We addressed this research gap by leveraging functional near-infrared spectroscopy to record the brain activity of triad members in a group simultaneously. Triads were instructed to analyze an ancient Chinese poem either cooperatively or independently. Four main findings emerged. First, we observed significant within-group neural synchronization (GNS) in the left superior temporal cortex, supramarginal gyrus, and postcentral gyrus during cooperative learning compared with independent learning. Second, the enhancement of GNS in triads was amplified when a consensus was reached (vs. elaboration or argument) during cooperative learning. Third, GNS was predictive of learning outcome at an early stage (156-170 s after learning was initiated). Fourth, social factors such as social closeness (e.g. how much learners liked one other) were reflected in GNS and co-varied with learning engagement. These results provide neuroscientific support for Piaget's theory of cognitive development and favor the notion that successful learning through cooperation involves dynamic consensus-building, which is captured in neural patterns shared across learners in a group.

Multimodal Fast–Slow Neural Network for learning engagement evaluation

Purpose

Student engagement is a key factor that connects with student achievement and retention. This paper aims to identify individuals' engagement automatically in the classroom with multimodal data for supporting educational research.

Design/methodology/approach

The video and electroencephalogram data of 36 undergraduates were collected to represent observable and internal information. Since different modal data have different granularity, this study proposed the Fast–Slow Neural Network (FSNN) to detect engagement through both observable and internal information, with an asynchrony structure to preserve the sequence information of data with different granularity.

Findings

Experimental results show that the proposed algorithm can recognize engagement better than the traditional data fusion methods. The results are also analyzed to figure out the reasons for the better performance of the proposed FSNN.

Originality/value

This study combined multimodal data from observable and internal aspects to improve the accuracy of engagement detection in the classroom. The proposed FSNN used the asynchronous process to deal with the problem of remaining sequential information when facing multimodal data with different granularity.

Speaking and listening to inter-brain relationships

Studies of inter-brain relationships thrive, and yet many reservations regarding their scope and interpretation of these phenomena have been raised by the scientific community. It is thus essential to establish common ground on methodological and conceptual definitions related to this topic and to open debate about any remaining points of uncertainty. We here offer insights to improve the conceptual clarity and empirical standards offered by social neuroscience studies of inter-personal interaction using hyperscanning with a particular focus on verbal communication.

multiSyncPy: A Python package for assessing multivariate coordination dynamics

In order to support the burgeoning field of research into intra- and interpersonal synchrony, we present an open-source software package: multiSyncPy. Multivariate synchrony goes beyond the bivariate case and can be useful for quantifying how groups, teams, and families coordinate their behaviors, or estimating the degree to which multiple modalities from an individual become synchronized. Our package includes state-of-the-art multivariate methods including symbolic entropy, multidimensional recurrence quantification analysis, coherence (with an additional sum-normalized modification), the cluster-phase 'Rho' metric, and a statistical test based on the Kuramoto order parameter. We also include functions for two surrogation techniques to compare the observed coordination dynamics with chance levels and a windowing function to examine time-varying coordination for most of the measures. Taken together, our collation and presentation of these methods make the study of interpersonal synchronization and coordination dynamics applicable to larger, more complex and often more ecologically valid study designs. In this work, we summarize the relevant theoretical background and present illustrative practical examples, lessons learned, as well as guidance for the usage of our package - using synthetic as well as empirical data. Furthermore, we provide a discussion of our work and software and outline interesting further directions and perspectives. multiSyncPy is freely available under the LGPL license at: https://github.com/cslab-hub/multiSyncPy , and also available at the Python package index.

Formal perspectives on shared interbrain activity in social communication: Insights from information and control theories

The mechanisms underlying a reorientation of neuroscience from a single-brain to a multi-brain frame of reference have long been with us. These revolve around the evolutionary exaptation of the inevitable second-law 'leakage' of crosstalk between co-resident cognitive phenomena. Crosstalk characterizes such processes as immune response, wound-healing, gene expression, as so on, up through and including far more rapid neural processes. It is not a great leap-of-faith to infer that similar phenomena affect/afflict social interactions between individuals within and across populations.

The social roots of self development: from a bodily to an intellectual interpersonal dialogue

In this paper, we propose that interpersonal bodily interactions represent a fertile ground in which the bodily and psychological self is developed, gradually allowing for forms of more abstract and disembodied interactions. We start by focusing on how early infant-caregiver bodily interactions play a crucial role in shaping the boundaries of the self but also in learning to predict others' behavior. We then explore the social function of the sense of touch in the entire life span, highlighting its role in promoting physical and psychological well-being by supporting positive interpersonal exchanges. We go on by introducing the concept of implicit theory of mind, as the early ability to interpret others' intentions, possibly grounded in infant-caregiver bodily exchanges (embodied practices). In the following part, we consider so-called higher level forms of social interaction: intellectual exchanges among individuals. In this regard, we defend the view that, beside the apparent private dimension of "thinking abstractly", using abstract concepts is intrinsically a social process, as it entails the re-enactment of the internalized dialogue through which we acquired the concepts in the first place. Finally, we describe how the hypothesis of "dialectical attunement" may explain the development of abstract thinking: to effectively transform the world according to their survival needs, individuals co-construct structured concepts of it; by doing so, humans fundamentally transform not merely the world they are being in, but their being in the world.

Communication style drives emergent leadership attribution in virtual teams

Leader selection plays a key role in how human social groups are formed and maintained. Leadership is either assigned through formal processes within an organization, or emerges informally through interactions with other group members-particularly in novel contexts. COVID-19 has accelerated the adoption of virtual meetings and more flexible team structures. However our understanding of how assigned leadership influences subsequent leadership emergence in virtual settings is limited. Here we examine the relationship between assigned leadership within an existing organization and subsequent emergent leadership attributions as members engage in virtual interactions. To do so, we created and implemented a novel virtual group decision-making task designed to support quantification of a more comprehensive set of communication style elements, such as speech dynamics and facial expressions, as well as task behaviors. Sixteen members of a real world organization engaged four repeated rounds of a group decision making task with new team members each time. We found participants made novel attributions of emergent leadership rather than relying solely on existing assigned leadership. While assigned leadership did influence leadership attributions, communication style, including amount of speech but also variability in facial expressions, played a larger role. The behavior of these novel emergent leaders was also more consistent with expectations of leadership behavior: they spoke earlier, more often, and focused more on the correct decision than did assigned leaders. These findings suggest that, even within existing social networks, virtual contexts promote flexible group structures that depend more on communication style and task performance than assigned leadership.

Functional near-infrared spectroscopy is a useful tool for multi-perspective psychobiological study of neurophysiological correlates of parenting behaviour

The quality of the relationship between caregiver and child has long-term effects on the cognitive and socio-emotional development of children. A process involved in human parenting is the bio-behavioural synchrony that occurs between the partners in the relationship during interaction. Through interaction, bio-behavioural synchronicity allows the adaptation of the physiological systems of the parent to those of the child and promotes the positive development and modelling of the child's social brain. The role of bio-behavioural synchrony in building social bonds could be investigated using functional near-infrared spectroscopy (fNIRS). In this paper we have (a) highlighted the importance of the quality of the caregiver-child relationship for the child's cognitive and socio-emotional development, as well as the relevance of infantile stimuli in the activation of parenting behaviour; (b) discussed the tools used in the study of the neurophysiological substrates of the parental response; (c) proposed fNIRS as a particularly suitable tool for the study of parental responses; and (d) underlined the need for a multi-systemic psychobiological approach to understand the mechanisms that regulate caregiver-child interactions and their bio-behavioural synchrony. We propose to adopt a multi-system psychobiological approach to the study of parental behaviour and social interaction.

Neurocomputational mechanisms of young children's observational learning of delayed gratification

The ability to delay gratification is crucial for a successful and healthy life. An effective way for young children to learn this ability is to observe the action of adult models. However, the underlying neurocomputational mechanism remains unknown. Here, we tested the hypotheses that children employed either the simple imitation strategy or the goal-inference strategy when learning from adult models in a high-uncertainty context. Results of computational modeling indicated that children used the goal-inference strategy regardless of whether the adult model was their mother or a stranger. At the neural level, results showed that successful learning of delayed gratification was associated with enhanced interpersonal neural synchronization (INS) between children and the adult models in the dorsal lateral prefrontal cortex but was not associated with children's own single-brain activity. Moreover, the discounting of future reward's value obtained from computational modeling of the goal-inference strategy was positively correlated with the strength of INS. These findings from our exploratory study suggest that, even for 3-year-olds, the goal-inference strategy is used to learn delayed gratification from adult models, and the learning strategy is associated with neural interaction between the brains of children and adult models.

Practical anatomy classes: An alternative to improve the learning of middle school students

Anatomy is the branch discipline focused on studying organisms' physical structures and parts. Although technological advances are broadening the anatomy study, the practices of prosection and dissection of human cadavers and animals remain a primary teaching method. Despite the large body of research supporting its benefits, in some countries, cadaveric prosection and dissection of vertebrate animals in secondary education have been banned. In the current study, to prevent a lack of access to anatomical sciences education, the use of plastinated biological specimens was proposed for teaching practical biology in middle and high schools. The study was conducted in the 2014 academic year. Eighty-seven middle school students participated in the experiment. Groups consisted of: (i) theoretical classes only; (ii) theoretical class plus prosection with fresh specimens class; (iii) theoretical class plus expository with plastinated specimens classes. A post-test grade method was used to assess the impact of such tasks on the learning experience of each group. An ANOVA test and multiple regression model were used to analyze the effects of the variables of interest. Our study highlighted that students who underwent the plastination practical class had higher overall performance and a higher mean post-test grade than those in the pure theoretical group. A favorable effect of a positive self-knowledge assessment on the students' performance was found, supporting the self-efficacy model of human behavior. Thus, the current study provides further evidence to support the use of plastinated specimens as an effective teaching method in countries where dissection is not feasible.

Educational neurotechnology: Where do we go from here?

Recent educational trends point to an interest in educational neurotechnology. While these tools have the potential to change education, little is known about whether their use improves educational outcomes. Additionally, their adoption may be negatively impacted by teachers' lack of knowledge about the brain. In this paper we outline the potential of educational neurotechnology including what we know, what we do not yet know, and additional considerations for the ethical, successful adoption of these tools in classrooms around the world. Special consideration is given to the training needs of pre- and in-service educators whose support will be essential to the successful adoption of educational neurotechnology.

Measurement of interpersonal physiological synchrony in dyads: A review of timing parameters used in the literature

When individuals share interpersonal connections, such as the bond between a mother and child or between a therapist and their client, they often exhibit measurable coordination of some physiological response patterns during their interactions known as interpersonal physiological synchrony (IPS Butler, 2011; Palumbo et al., 2016; Tscacher & Meier, 2019). However, as there is no single definition of IPS in the literature, researchers across fields have not established a standardized method for its study. This paper outlines methodological considerations that researchers should take into account when designing studies of IPS. Due to the inherent temporal component of synchrony analyses, we direct particular focus to the issue of measurement timing. Synchrony is described across multiple physiological processes, including electrodermal skin activation, cardiac function, respiration, and neural oscillatory activity, and we make specific recommendations for each. Across physiological measures and analytic strategies, we recommend that when determining an experimental timeframe in which to isolate periods of dyadic IPS, researchers should account for the timing of both the biological systems of interest and the psychological processes theorized to underlie their activity in that particular context. In adopting this strategy, researchers can ensure that they capture all of the fluctuations associated with a psychological process of interest and can add to the growing body of literature examining physiological correlates of interpersonal bonds.

Bringing social interaction at the core of organizational neuroscience

Organizations are composed of individuals working together for achieving specific goals, and interpersonal dynamics do exert a strong influence on workplace behaviour. Nevertheless, the dual and multiple perspective of interactions has been scarcely considered by Organizational Neuroscience (ON), the emerging field of study that aims at incorporating findings from cognitive and brain sciences into the investigation of organizational behaviour. This perspective article aims to highlight the potential benefits of adopting experimental settings involving two or more participants (the so-called "second person" approach) for studying the neural bases of organizational behaviour. Specifically, we stress the idea that moving beyond the individual perspective and capturing the dynamical relationships occurring within dyads or groups (e.g., leaders and followers, salespersons and clients, teams) might bring novel insights into the rising field of ON. In addition, designing research paradigms that reliably recreate real work and life situations might increase the generalizability and ecological validity of its results. We start with a brief overview of the current state of ON research and we continue by describing the second-person approach to social neuroscience. In the last paragraph, we try and outline how this approach could be extended to ON. To this end, we focus on leadership, group processes and emotional contagion as potential targets of interpersonal ON research.

Delta-Alpha EEG pattern reflects the interoceptive focus effect on interpersonal motor synchronization

Little is known about how the modulation of the interoceptive focus impacts the neural correlates of high-level social processes, such as synchronization mechanisms. Therefore, the current study aims to explore the intraindividual electrophysiological (EEG) patterns induced by the interoceptive focus on breath when performing cognitive and motor tasks requiring interpersonal synchronization. A sample of 28 healthy caucasian adults was recruited and asked to perform two tasks requiring interpersonal synchronization during two distinct conditions: while focusing on the breath or without the focus on the breath. EEG frequency bands (delta, theta, alpha, and beta band) were recorded from the frontal, temporo-central, and parieto-occipital regions of interest. Significant results were observed for the delta and alpha bands. Notably, higher mean delta values and alpha desynchronization were observed in the temporo-central area during the focus on the breath condition when performing the motor compared to the cognitive synchronization task. Taken together these results could be interpreted considering the functional meaning of delta and alpha band in relation to motor synchronization. Indeed, motor delta oscillations shape the dynamics of motor behaviors and motor neural processes, while alpha band attenuation was previously observed during generation, observation, and imagery of movement and is considered to reflect cortical motor activity and action-perception coupling. Overall, the research shows that an EEG delta-alpha pattern emerges in the temporo-central areas at the intra-individual level, indicating the attention to visceral signals, particularly during interpersonal motor synchrony.