Shared Attention Amplifies the Neural Processing of Emotional Faces.

Sharing an experience, without communicating, affects people's subjective perception of the experience, often by intensifying it. We investigated the neural mechanisms underlying shared attention by implementing an EEG study where participants attended to and rated the intensity of emotional faces, simultaneously or independently. Participants performed the task in three experimental conditions: (a) alone; (b) simultaneously next to each other in pairs, without receiving feedback of the other's responses (shared without feedback); and (c) simultaneously while receiving the feedback (shared with feedback). We focused on two face-sensitive ERP components: The amplitude of the N170 was greater in the "shared with feedback" condition compared to the alone condition, reflecting a top-down effect of shared attention on the structural encoding of faces, whereas the EPN was greater in both shared context conditions compared to the alone condition, reflecting an enhanced attention allocation in the processing of emotional content of faces, modulated by the social context. Taken together, these results suggest that shared attention amplifies the neural processing of faces, regardless of the valence of facial expressions.

A Kuramoto model of self-other integration across interpersonal synchronization strategies.

Human social behaviour is complex, and the biological and neural mechanisms underpinning it remain debated. A particularly interesting social phenomenon is our ability and tendency to fall into synchronization with other humans. Our ability to coordinate actions and goals relies on the ability to distinguish between and integrate self and other, which when impaired can lead to devastating consequences. Interpersonal synchronization has been a widely used framework for studying action coordination and self-other integration, showing that even in simple interactions, such as joint finger tapping, complex interpersonal dynamics emerge. Here we propose a computational model of self-other integration via within- and between-person action-perception links, implemented as a simple Kuramoto model with four oscillators. The model abstracts each member of a dyad as a unit consisting of two connected oscillators, representing intrinsic processes of perception and action. By fitting this model to data from two separate experiments we show that interpersonal synchronization strategies rely on the relationship between within- and between-unit coupling. Specifically, mutual adaptation exhibits a higher between-unit coupling than within-unit coupling; leading-following requires that the follower unit has a low within-unit coupling; and leading-leading occurs when two units jointly exhibit a low between-unit coupling. These findings are consistent with the theory of interpersonal synchronization emerging through self-other integration mediated by processes of action-perception coupling. Hence, our results show that chaotic human behaviour occurring on a millisecond scale may be modelled using coupled oscillators.

Syncopation affects free body-movement in musical groove.

One of the most immediate and overt ways in which people respond to music is by moving their bodies to the beat. However, the extent to which the rhythmic complexity of groove-specifically its syncopation-contributes to how people spontaneously move to music is largely unexplored. Here, we measured free movements in hand and torso while participants listened to drum-breaks with various degrees of syncopation. We found that drum-breaks with medium degrees of syncopation were associated with the same amount of acceleration and synchronisation as low degrees of syncopation. Participants who enjoyed dancing made more complex movements than those who did not enjoy dancing. While for all participants hand movements accelerated more and were more complex, torso movements were more synchronised to the beat. Overall, movements were mostly synchronised to the main beat and half-beat level, depending on the body-part. We demonstrate that while people do not move or synchronise much to rhythms with high syncopation when dancing spontaneously to music, the relationship between rhythmic complexity and synchronisation is less linear than in simple finger-tapping studies.

Synchronised and complementary coordination mechanisms in an asymmetric joint aiming task.

Many forms of social interaction require that behaviour be coordinated in the here and now. Much research has been conducted on how people coordinate their actions in real time to achieve a joint goal, showing that people use both synchronised (i.e., symmetric) and complementary (i.e., asymmetric) strategies. These two mechanisms have been mostly studied independently, the former in the context of rhythmic tasks, and the latter in non-rhythmic tasks. However, people often balance these two strategies in real-life social interactions, in order to achieve a joint goal more effectively. Here, our aim was to investigate how people may implicitly balance synchronisation and complementarity in a continuous joint aiming task. We asked dyads to synchronise the timing of their clicks between targets, while changing task constraints for one member of the dyad (i.e., different task difficulties) to asymmetrically perturb the continuous interaction. This allowed us to investigate how individuals implicitly negotiate complementary leader-follower dynamics to achieve synchronisation. We found that dyads flexibly switch from mutual to asymmetric adaptation given variations in task constraints. Specifically, our results show that both members adapt equally up to a certain level of difficulty; after this point, the partner with the difficult task becomes less adaptive, and hence more of a leader, while the adaptability of the member with the easier task remains unchanged. This proves to be an effective strategy in this asymmetric task, as people synchronise better with an irregular, but adaptive partner, than with a completely predictable, but non-responsive metronome. These results show that given asymmetric task constraints, adaptability, rather than predictability, facilitates coordination.

Frontal alpha oscillations distinguish leaders from followers: multivariate decoding of mutually interacting brains.

Successful social interactions rely upon the abilities of two or more people to mutually exchange information in real-time, while simultaneously adapting to one another. The neural basis of social cognition has mostly been investigated in isolated individuals, and more recently using two-person paradigms to quantify the neuronal dynamics underlying social interaction. While several studies have shown the relevance of understanding complementary and mutually adaptive processes, the neural mechanisms underlying such coordinative behavioral patterns during joint action remain largely unknown. Here, we employed a synchronized finger-tapping task while measuring dual-EEG from pairs of human participants who either mutually adjusted to each other in an interactive task or followed a computer metronome. Neurophysiologically, the interactive condition was characterized by a stronger suppression of alpha and low-beta oscillations over motor and frontal areas in contrast to the non-interactive computer condition. A multivariate analysis of two-brain activity to classify interactive versus non-interactive trials revealed asymmetric patterns of the frontal alpha-suppression in each pair, during both task anticipation and execution, such that only one member showed the frontal component. Analysis of the behavioral data showed that this distinction coincided with the leader-follower relationship in 8/9 pairs, with the leaders characterized by the stronger frontal alpha-suppression. This suggests that leaders invest more resources in prospective planning and control. Hence our results show that the spontaneous emergence of leader-follower relationships in dyadic interactions can be predicted from EEG recordings of brain activity prior to and during interaction. Furthermore, this emphasizes the importance of investigating complementarity in joint action.

Synchronized arousal between performers and related spectators in a fire-walking ritual.

Collective rituals are present in all known societies, but their function is a matter of long-standing debates. Field observations suggest that they may enhance social cohesion and that their effects are not limited to those actively performing but affect the audience as well. Here we show physiological effects of synchronized arousal in a Spanish fire-walking ritual, between active participants and related spectators, but not participants and other members of the audience. We assessed arousal by heart rate dynamics and applied nonlinear mathematical analysis to heart rate data obtained from 38 participants. We compared synchronized arousal between fire-walkers and spectators. For this comparison, we used recurrence quantification analysis on individual data and cross-recurrence quantification analysis on pairs of participants' data. These methods identified fine-grained commonalities of arousal during the 30-min ritual between fire-walkers and related spectators but not unrelated spectators. This indicates that the mediating mechanism may be informational, because participants and related observers had very different bodily behavior. This study demonstrates that a collective ritual may evoke synchronized arousal over time between active participants and bystanders. It links field observations to a physiological basis and offers a unique approach for the quantification of social effects on human physiology during real-world interactions.

A practical guide to EEG hyperscanning in joint action research: from motivation to implementation.

Developments in cognitive neuroscience have led to the emergence of hyperscanning, the simultaneous measurement of brain activity from multiple people. Hyperscanning is useful for investigating social cognition, including joint action, because of its ability to capture neural processes that occur within and between people as they coordinate actions toward a shared goal. Here, we provide a practical guide for researchers considering using hyperscanning to study joint action and seeking to avoid frequently raised concerns from hyperscanning skeptics. We focus specifically on Electroencephalography (EEG) hyperscanning, which is widely available and optimally suited for capturing fine-grained temporal dynamics of action coordination. Our guidelines cover questions that are likely to arise when planning a hyperscanning project, ranging from whether hyperscanning is appropriate for answering one's research questions to considerations for study design, dependent variable selection, data analysis and visualization. By following clear guidelines that facilitate careful consideration of the theoretical implications of research design choices and other methodological decisions, joint action researchers can mitigate interpretability issues and maximize the benefits of hyperscanning paradigms.

The role of reciprocity in dynamic interpersonal coordination of physiological rhythms.

A central question in social cognition research is how people coordinate their bodily rhythms, and how important reciprocity of interaction is for interpersonal coordination. Previous research has primarily focused on interpersonal action coordination, which has been shown to be facilitated by mechanisms of prediction and mutual adaption. Recent research is beginning to show that people also coordinate their physiological rhythms (i.e., respiration, heart rhythms) when they engage in natural forms of social interaction, such as conversation, choir singing, and rituals. However, the mechanisms underlying interpersonal physiological synchronization remain obscure, and could provide insight into the dynamic mechanisms that underlie continuous and regulatory, rather than instrumental, joint actions. Using real-time biofeedback, we investigated whether people synchronize their respiration rhythms by forming a joint dynamical system through reciprocity of interaction, or by producing more predictable respiration rhythms. Our results show that people are more in-phase synchronized but less phase-locked when interacting bidirectionally versus unidirectionally (online), but there is no difference in synchronization during reciprocal interaction and when adapting unidirectionally (offline) to recordings of respiration signals that emerged during the reciprocal interaction. Moreover, the strength of synchronization is driven by the predictability of the respiration rhythms that emerge in the bidirectional interaction - specifically, the slowing of breathing rhythms and stability of breathing frequencies - rather than the online mutual adaptation itself. These results suggest that coordination is facilitated by the emergence of predictable breathing patterns, rather than reciprocity itself.

Beyond Single-Mindedness: A Figure-Ground Reversal for the Cognitive Sciences.

A fundamental fact about human minds is that they are never truly alone: all minds are steeped in situated interaction. That social interaction matters is recognized by any experimentalist who seeks to exclude its influence by studying individuals in isolation. On this view, interaction complicates cognition. Here, we explore the more radical stance that interaction co-constitutes cognition: that we benefit from looking beyond single minds toward cognition as a process involving interacting minds. All around the cognitive sciences, there are approaches that put interaction center stage. Their diverse and pluralistic origins may obscure the fact that collectively, they harbor insights and methods that can respecify foundational assumptions and fuel novel interdisciplinary work. What might the cognitive sciences gain from stronger interactional foundations? This represents, we believe, one of the key questions for the future. Writing as a transdisciplinary collective assembled from across the classic cognitive science hexagon and beyond, we highlight the opportunity for a figure-ground reversal that puts interaction at the heart of cognition. The interactive stance is a way of seeing that deserves to be a key part of the conceptual toolkit of cognitive scientists.

Intra-individual behavioural and neural signatures of audience effects and interactions in a mirror-game paradigm.

We often perform actions while observed by others, yet the behavioural and neural signatures of audience effects remain understudied. Performing actions while being observed has been shown to result in more emphasized movements in musicians and dancers, as well as during communicative actions. Here, we investigate the behavioural and neural mechanisms of observed actions in relation to individual actions in isolation and interactive joint actions. Movement kinematics and EEG were recorded in 42 participants (21 pairs) during a mirror-game paradigm, while participants produced improvised movements alone, while observed by a partner, or by synchronizing movements with the partner. Participants produced largest movements when being observed, and observed actors and dyads in interaction produced slower and less variable movements in contrast with acting alone. On a neural level, we observed increased mu suppression during interaction, as well as to a lesser extent during observed actions, relative to individual actions. Moreover, we observed increased widespread functional brain connectivity during observed actions relative to both individual and interactive actions, suggesting increased intra-individual monitoring and action-perception integration as a result of audience effects. These results suggest that observed actors take observers into account in their action plans by increasing self-monitoring; on a behavioural level, observed actions are similar to emergent interactive actions, characterized by slower and more predictable movements.

Intellectually able adults with autism spectrum disorder show typical resting-state EEG activity.

There is broad interest in discovering quantifiable physiological biomarkers for psychiatric disorders to aid diagnostic assessment. However, finding biomarkers for autism spectrum disorder (ASD) has proven particularly difficult, partly due to high heterogeneity. Here, we recorded five minutes eyes-closed rest electroencephalography (EEG) from 186 adults (51% with ASD and 49% without ASD) and investigated the potential of EEG biomarkers to classify ASD using three conventional machine learning models with two-layer cross-validation. Comprehensive characterization of spectral, temporal and spatial dimensions of source-modelled EEG resulted in 3443 biomarkers per recording. We found no significant group-mean or group-variance differences for any of the EEG features. Interestingly, we obtained validation accuracies above 80%; however, the best machine learning model merely distinguished ASD from the non-autistic comparison group with a mean balanced test accuracy of 56% on the entirely unseen test set. The large drop in model performance between validation and testing, stress the importance of rigorous model evaluation, and further highlights the high heterogeneity in ASD. Overall, the lack of significant differences and weak classification indicates that, at the group level, intellectually able adults with ASD show remarkably typical resting-state EEG.

Resting-state EEG functional connectivity predicts post-traumatic stress disorder subtypes in veterans.

Objective. Post-traumatic stress disorder (PTSD) is highly heterogeneous, and identification of quantifiable biomarkers that could pave the way for targeted treatment remains a challenge. Most previous electroencephalography (EEG) studies on PTSD have been limited to specific handpicked features, and their findings have been highly variable and inconsistent. Therefore, to disentangle the role of promising EEG biomarkers, we developed a machine learning framework to investigate a wide range of commonly used EEG biomarkers in order to identify which features or combinations of features are capable of characterizing PTSD and potential subtypes.Approach. We recorded 5 min of eyes-closed and 5 min of eyes-open resting-state EEG from 202 combat-exposed veterans (53% with probable PTSD and 47% combat-exposed controls). Multiple spectral, temporal, and connectivity features were computed and logistic regression, random forest, and support vector machines with feature selection methods were employed to classify PTSD. To obtain robust results, we performed repeated two-layer cross-validation to test on an entirely unseen test set.Main results. Our classifiers obtained a balanced test accuracy of up to 62.9% for predicting PTSD patients. In addition, we identified two subtypes within PTSD: one where EEG patterns were similar to those of the combat-exposed controls, and another that were characterized by increased global functional connectivity. Our classifier obtained a balanced test accuracy of 79.4% when classifying this PTSD subtype from controls, a clear improvement compared to predicting the whole PTSD group. Interestingly, alpha connectivity in the dorsal and ventral attention network was particularly important for the prediction, and these connections were positively correlated with arousal symptom scores, a central symptom cluster of PTSD.Significance. Taken together, the novel framework presented here demonstrates how unsupervised subtyping can delineate heterogeneity and improve machine learning prediction of PTSD, and may pave the way for better identification of quantifiable biomarkers.

A metastable attractor model of self-other integration (MEAMSO) in rhythmic synchronization.

Human interaction is often accompanied by synchronized bodily rhythms. Such synchronization may emerge spontaneously as when a crowd's applause turns into a steady beat, be encouraged as in nursery rhymes, or be intentional as in the case of playing music together. The latter has been extensively studied using joint finger-tapping paradigms as a simplified version of rhythmic interpersonal synchronization. A key finding is that synchronization in such cases is multifaceted, with synchronized behaviour resting upon different synchronization strategies such as mutual adaptation, leading-following and leading-leading. However, there are multiple open questions regarding the mechanism behind these strategies and how they develop dynamically over time. Here, we propose a metastable attractor model of self-other integration (MEAMSO). This model conceptualizes dyadic rhythmic interpersonal synchronization as a process of integrating and segregating signals of self and other. Perceived sounds are continuously evaluated as either being attributed to self-produced or other-produced actions. The model entails a metastable system with two particular attractor states: one where an individual maintains two separate predictive models for self- and other-produced actions, and the other where these two predictive models integrate into one. The MEAMSO explains the three known synchronization strategies and makes testable predictions about the dynamics of interpersonal synchronization both in behaviour and the brain. This article is part of the theme issue 'Synchrony and rhythm interaction: from the brain to behavioural ecology'.

The sound of silence: an EEG study of how musicians time pauses in individual and joint music performance.

Pauses are an integral feature of social interaction. Conversation partners often pause between conversational turns, and musical co-performers often pause between musical phrases. How do humans coordinate the duration of pauses to ensure seamless interaction? A total of 40 trained pianists performed a simple melody containing fermatas (notated expressive pauses of unspecified duration) first alone (Solo) and then with a partner (Duet) while electroencephalography (EEG) was recorded. As predicted, Duet partners' tone onset synchrony was reduced for tones following pauses. Pauses were shorter in Duet relative to Solo performance, and synchrony of partners' Duet tone onsets was enhanced for tones following shorter pauses. EEG analysis revealed classic signatures of action preparation during pauses, namely decreases in the power of cortical beta oscillations (13-30 Hz, event-related desynchronization ERD). Beta ERD did not differ between pauses in Solo and Duet performance, but was enhanced for shorter relative to longer pauses, suggesting that reduced pause durations in Duet performance facilitated a neural state of enhanced action readiness. Together these findings provide novel insight into behavioural strategies by which musical partners resolve coordination challenges posed by expressive silence, and capture a clear neural signature of action planning during time-varying silences in natural music performance.

Transient brain networks underlying interpersonal strategies during synchronized action.

Interpersonal coordination is a core part of human interaction, and its underlying mechanisms have been extensively studied using social paradigms such as joint finger-tapping. Here, individual and dyadic differences have been found to yield a range of dyadic synchronization strategies, such as mutual adaptation, leading-leading, and leading-following behaviour, but the brain mechanisms that underlie these strategies remain poorly understood. To identify individual brain mechanisms underlying emergence of these minimal social interaction strategies, we contrasted EEG-recorded brain activity in two groups of musicians exhibiting the mutual adaptation and leading-leading strategies. We found that the individuals coordinating via mutual adaptation exhibited a more frequent occurrence of phase-locked activity within a transient action-perception-related brain network in the alpha range, as compared to the leading-leading group. Furthermore, we identified parietal and temporal brain regions that changed significantly in the directionality of their within-network information flow. Our results suggest that the stronger weight on extrinsic coupling observed in computational models of mutual adaptation as compared to leading-leading might be facilitated by a higher degree of action-perception network coupling in the brain.

Why do we fall into sync with others? Interpersonal synchronization and the brain's optimization principle.

Spontaneous interpersonal synchronization of rhythmic behavior such as gait or hand clapping is a ubiquitous phenomenon in human interactions, and is potentially important for social relationships and action understanding. Although several authors have suggested a role of the mirror neuron system in interpersonal coupling, the underlying brain mechanisms are not well understood. Here we argue that more general theories of neural computations, namely predictive coding and the Free Energy Principle, could explain interpersonal coordination dynamics. Each brain minimizes coding costs by reducing the mismatch between the representations of observed and own motor behavior. Continuous mutual prediction and alignment result in an overall minimization of free energy, thus forming a stable attractor state.

Musical interaction is influenced by underlying predictive models and musical expertise.

Musical interaction is a unique model for understanding humans' ability to align goals, intentions, and actions, which also allows for the manipulation of participants' internal predictive models of upcoming events. Here we used polyrhythms to construct two joint finger tapping tasks that even when rhythmically dissimilar resulted in equal inter-tap intervals (ITIs). Thus, behaviourally a dyad of two musicians tap isochronously at the same rate, yet with their own distinct rhythmical context model (RCM). We recruited 22 highly skilled musicians (in 11 dyads) and contrasted the effect of having a shared versus non-shared RCM on dyads' synchronization behaviour. As expected, tapping synchronization was significantly worse at the start of trials with non-shared models compared to trials with a shared model. However, the musicians were able to quickly recover when holding dissimilar predictive models. We characterised the directionality in the tapping behaviour of the dyads and found patterns mostly of mutual adaptation. Yet, in a subset of dyads primarily consisting of drummers, we found significantly different synchronization patterns, suggesting that instrument expertise can significantly affect synchronization strategies. Overall, this demonstrates that holding different predictive models impacts synchronization in musicians performing joint finger tapping.

The body talks: Sensorimotor communication and its brain and kinematic signatures.

Human communication is a traditional topic of research in many disciplines such as psychology, linguistics and philosophy, all of which mainly focused on language, gestures and deictics. However, these do not constitute the sole channels of communication, especially during online social interaction, where instead an additional critical role may be played by sensorimotor communication (SMC). SMC refers here to (often subtle) communicative signals embedded within pragmatic actions - for example, a soccer player carving his body movements in ways that inform a partner about his intention, or to feint an adversary; or the many ways we offer a glass of wine, rudely or politely. SMC is a natural form of communication that does not require any prior convention or any specific code. It amounts to the continuous and flexible exchange of bodily signals, with or without awareness, to enhance coordination success; and it is versatile, as sensorimotor signals can be embedded within every action. SMC is at the center of recent interest in neuroscience, cognitive psychology, human-robot interaction and experimental semiotics; yet, we still lack a coherent and comprehensive synthesis to account for its multifaceted nature. Some fundamental questions remain open, such as which interactive scenarios promote or do not promote SMC, what aspects of social interaction can be properly called communicative and which ones entail a mere transfer of information, and how many forms of SMC exist and what we know (or still don't know) about them from an empirical viewpoint. The present work brings together all these separate strands of research within a unified overarching, multidisciplinary framework for SMC, which combines evidence from kinematic studies of human-human interaction and computational modeling of social exchanges.

Stress Response and Cognitive Performance Modulation in Classroom versus Natural Environments: A Quasi-Experimental Pilot Study with Children.

Stress during childhood can have mental and somatic health influences that track throughout life. Previous research attributes stress-reducing effects to natural environments, but has mainly focused on adults and often following leisurely relaxation in natural environments. This pilot study explores the impact of natural environments on stress response during rest and mental load and cognitive performance in 47 children aged 10⁻12 years in a school context. Heart rate variability measures indexing tonic, event, and phasic vagal tone and attention scores were compared across classroom and natural environments. Tonic vagal tone was higher in the natural environment than the classrooms, but no differences were found in event or phasic vagal tone or cognitive performance measures. These findings suggest a situational aspect of the conditions under which natural environments may give rise to stress-buffering influences. Further research is warranted to understand the potential benefits in a real-life context, in particular with respect to the underpinning mechanisms and effects of accumulated exposure over time in settings where children spend large proportions of time in natural environments.