Using second-person neuroscience to elucidate the mechanisms of social interaction

Frontal EEG alpha asymmetry predicts foreign language anxiety while speaking a foreign language

Engaging in dialog requires interlocutors to coordinate sending and receiving linguistic signals to build a discourse based upon interpretations and perceptions interconnected with a range of emotions. Conversing in a foreign language may induce emotions such as anxiety which influence the quality communication. The neural processes underpinning these interactions are crucial to understanding foreign language anxiety (FLA). Electroencephalography (EEG) studies reveal that anxiety is often displayed via hemispheric frontal alpha asymmetry (FAA). To examine the neural mechanisms underlying FLA, we collected self-reported data on the listening and speaking sections of the Second language skill specific anxiety scale (L2AS) over behavioral, cognitive, and somatic domains and recorded EEG signals during participation in word chain turn-taking activities in first (L1, Chinese) and second (L2, English) languages. Regression analysis showed FAA for the L2 condition was a significant predictor primarily of the behavioral and somatic domains on the L2AS speaking section. The results are discussed along with implications for improving communication during L2 interactions.

Tools and methods to study and replicate experiments addressing human social cognition in interactive scenarios

In the last decade, scientists investigating human social cognition have started bringing traditional laboratory paradigms more "into the wild" to examine how socio-cognitive mechanisms of the human brain work in real-life settings. As this implies transferring 2D observational paradigms to 3D interactive environments, there is a risk of compromising experimental control. In this context, we propose a methodological approach which uses humanoid robots as proxies of social interaction partners and embeds them in experimental protocols that adapt classical paradigms of cognitive psychology to interactive scenarios. This allows for a relatively high degree of "naturalness" of interaction and excellent experimental control at the same time. Here, we present two case studies where our methods and tools were applied and replicated across two different laboratories, namely the Italian Institute of Technology in Genova (Italy) and the Agency for Science, Technology and Research in Singapore. In the first case study, we present a replication of an interactive version of a gaze-cueing paradigm reported in Kompatsiari et al. (J Exp Psychol Gen 151(1):121-136, 2022). The second case study presents a replication of a "shared experience" paradigm reported in Marchesi et al. (Technol Mind Behav 3(3):11, 2022). As both studies replicate results across labs and different cultures, we argue that our methods allow for reliable and replicable setups, even though the protocols are complex and involve social interaction. We conclude that our approach can be of benefit to the research field of social cognition and grant higher replicability, for example, in cross-cultural comparisons of social cognition mechanisms.

Lights on music cognition: A systematic and critical review of fNIRS applications and future perspectives

Research investigating the neural processes related to music perception and production constitutes a well-established field within the cognitive neurosciences. While most neuroimaging tools have limitations in studying the complexity of musical experiences, functional Near-Infrared Spectroscopy (fNIRS) represents a promising, relatively new tool for studying music processes in both laboratory and ecological settings, which is also suitable for both typical and pathological populations across development. Here we systematically review fNIRS studies on music cognition, highlighting prospects and potentialities. We also include an overview of fNIRS basic theory, together with a brief comparison to characteristics of other neuroimaging tools. Fifty-nine studies meeting inclusion criteria (i.e., using fNIRS with music as the primary stimulus) are presented across five thematic sections. Critical discussion of methodology leads us to propose guidelines of good practices aiming for robust signal analyses and reproducibility. A continuously updated world map is proposed, including basic information from studies meeting the inclusion criteria. It provides an organized, accessible, and updatable reference database, which could serve as a catalyst for future collaborations within the community. In conclusion, fNIRS shows potential for investigating cognitive processes in music, particularly in ecological contexts and with special populations, aligning with current research priorities in music cognition.

A context-dependent model of resilient functioning after childhood maltreatment-the case for flexible biobehavioral synchrony

Many children who experience childhood adversity, whether in the form of threat or deprivation, develop adaptive competencies that lead to resilient functioning. Still, research has not succeeded in accurately predicting the level of resilient functioning by any kind of biomarkers, likely because it has sidelined the flexibility inherent in a construct that is situationally and developmentally variable. Whilst recent research acknowledges the importance of redefining resilience in order to reflect its dynamic nature after adversity, evidence for specific behaviors that are developmentally adaptive and dynamic throughout the lifespan is limited. We here propose a model in which resilient functioning is crucially dependent on the individual's capability to flexibly synchronize with and segregate from another's cognitive-affective, behavioral, and physiological states, known as 'biobehavioral synchrony'. Such an adaptive interpersonal skill is rooted in (a) the early caregiving experience and its regulatory effects on an individual's physiological stress reactivity, as well as (b) the development of self-other distinction which can be affected by childhood maltreatment. Bridging the gap between accounts of flexible resilient functioning and the latest thinking in biobehavioral synchrony, we will review behavioral and neurobiological evidence that threat and deprivation in childhood interfere with the development of dynamic, context-sensitive boundaries between self and other, mediated by the (right) tempo-parietal junction (a central neural hub for interpersonal synchronization), which puts the individual at risk for affective fusion or cut-off from others' arousal states. Our proposed model charts a path for investigating the differential effects of maltreatment experiences and mechanisms for intergenerational transmission of non-sensitive caregiving. We conclude with metrics, data analysis methods, and strategies to facilitate flexible biobehavioral synchrony.

Can similarity of autistic traits promote neural synchronization?

People with similar levels of autistic traits are reported to exhibit better interactions than those with larger differences in autistic traits. However, whether this "similarity effect" exists at the neural level remains unclear. To address this gap, the present study employed functional near-infrared spectroscopy (fNIRS) hyperscanning technology to assess inter-brain synchronization (IBS) during naturalistic conversations among dyads with three types of autistic trait combinations (20 high-high, 22 high-low, and 18 low-low dyads). The results revealed that the high-high dyads exhibited significantly lower IBS in the right temporoparietal junction (rTPJ) region compared to the low-low dyads, with no significant differences observed between the high-low group and the other two groups. Moreover, though dyadic differences in conversation satisfaction were positively correlated with dyadic autistic trait differences, IBS only showed a significant negative correlation with the dyadic average autistic trait scores and no significant correlation with the dyadic difference scores of autistic traits. These findings suggest that dyads with high autistic traits may have shared feelings about conversations, but cannot produce IBS through successful mutual prediction and understanding.

A shared model-based linguistic space for transmitting our thoughts from brain to brain in natural conversations

Effective communication hinges on a mutual understanding of word meaning in different contexts. We recorded brain activity using electrocorticography during spontaneous, face-to-face conversations in five pairs of epilepsy patients. We developed a model-based coupling framework that aligns brain activity in both speaker and listener to a shared embedding space from a large language model (LLM). The context-sensitive LLM embeddings allow us to track the exchange of linguistic information, word by word, from one brain to another in natural conversations. Linguistic content emerges in the speaker's brain before word articulation and rapidly re-emerges in the listener's brain after word articulation. The contextual embeddings better capture word-by-word neural alignment between speaker and listener than syntactic and articulatory models. Our findings indicate that the contextual embeddings learned by LLMs can serve as an explicit numerical model of the shared, context-rich meaning space humans use to communicate their thoughts to one another.

How a speaker herds the audience: multibrain neural convergence over time during naturalistic storytelling

Storytelling-an ancient way for humans to share individual experiences with others-has been found to induce neural alignment among listeners. In exploring the dynamic fluctuations in listener-listener (LL) coupling throughout stories, we uncover a significant correlation between LL coupling and lagged speaker-listener (lag-SL) coupling over time. Using the analogy of neural pattern (dis)similarity as distances between participants, we term this phenomenon the "herding effect." Like a shepherd guiding a group of sheep, the more closely listeners mirror the speaker's preceding brain activity patterns (higher lag-SL similarity), the more tightly they cluster (higher LL similarity). This herding effect is particularly pronounced in brain regions where neural alignment among listeners tracks with moment-by-moment behavioral ratings of narrative content engagement. By integrating LL and SL neural coupling, this study reveals a dynamic, multibrain functional network between the speaker and the audience, with the unfolding narrative content playing a mediating role in network configuration.

Opacity, difference and not knowing: what can psychiatry learn from the work of Édouard Glissant?

Martinican poet, novelist and cultural theorist Édouard Glissant (1928-2011) rejected contemporary simplistic notions of creole hybridity popularised in the 1980s and 1990s in favour of a unique and explicitly antiessentialist construct of Caribbeanness-a form of being that embraces place while shunning any associated ideas of rootednesss. Throughout his work, there is a constant tension between the local and the global, the particular and the universal, the essentialist and the homogenising, a tension that is never resolved but used creatively to stake out an emergent third position against a backdrop of a metaphorical Caribbean seascape. The purpose of this article is to shed light on a central idea developed by Glissant: the importance of acknowledging opacity in the encounter with the Other, in contrast to idealised notions of transparency as inherently desirable. This 'right to opacity' has been embraced in poststructural theory, postcolonial activism and contemporary art. However, I argue that opacity is also a highly relevant notion in clinical contexts, as an essential resource for understanding concepts such as first-person, second-person and third-person perspectives in the phenomenology of mental health and illness. For illustration, I point to a number of clinical tools and approaches-such as the Cultural Formulation Interview, Therapeutic Assessment and the employment of a not-knowing stance in mentalisation-based treatment-that successfully incorporate a respect for opacity as a core value in the clinician-patient encounter. This article is not an attempt to offer a definitive how-to guide on how to make use of the ideas of Édouard Glissant in the clinic; instead, I hope to inspire further discussion about how various notions of opacity and transparency come into play for mental health practitioners and how acknowledging alterity and difference may contribute to more fruitful and respectful ways of engaging with the patient-as-Other.

Predictive coding for the actions and emotions of others and its deficits in autism spectrum disorders

Traditionally, the neural basis of social perception has been studied by showing participants brief examples of the actions or emotions of others presented in randomized order to prevent participants from anticipating what others do and feel. This approach is optimal to isolate the importance of information flow from lower to higher cortical areas. The degree to which feedback connections and Bayesian hierarchical predictive coding contribute to how mammals process more complex social stimuli has been less explored, and will be the focus of this review. We illustrate paradigms that start to capture how participants predict the actions and emotions of others under more ecological conditions, and discuss the brain activity measurement methods suitable to reveal the importance of feedback connections in these predictions. Together, these efforts draw a richer picture of social cognition in which predictive coding and feedback connections play significant roles. We further discuss how the notion of predicting coding is influencing how we think of autism spectrum disorder.

Hyperscanning shows friends explore and strangers converge in conversation

During conversation, people often endeavor to convey information in an understandable way (finding common ground) while also sharing novel or surprising information (exploring new ground). Here, we test how friends and strangers balance these two strategies to connect with each other. Using fMRI hyperscanning, we measure a preference for common ground as convergence over time and exploring new ground as divergence over time by tracking dyads' neural and linguistic trajectories over the course of semi-structured intimacy-building conversations. In our study, 60 dyads (30 friend dyads) engaged in a real-time conversation with discrete prompts and demarcated turns. Our analyses reveal that friends diverge neurally and linguistically: their neural patterns become more dissimilar over time and they explore more diverse topics. In contrast, strangers converge: neural patterns and language become more similar over time. The more a conversation between strangers resembles the exploratory conversations of friends, the more they enjoy it. Our results highlight exploring new ground as a strategy for a successful conversation.

A critical hit: Dungeons and Dragons as a buff for autistic people

LAY ABSTRACT

Tabletop role-playing games (TTRPGs) are popular hobbies that may offer specific social benefits for autistic people. This study investigated the ability of TTRPGs to provide a safe space where autistic adults could develop relationships with other autistic adults while engaging in character and world-building. A group of eight autistic adults were split into two groups and taken through a short-form online Dungeons and Dragons campaign over 6 weeks run by one of the researchers. The researcher then led a series of individual semi-structured interviews discussing how participants felt interacting in and out of the TTRPG. Several key themes were identified as important aspects of why autistic people could benefit from such an environment. Analysis showed that while real-life interactions could be challenging, in TTRPG play, they felt they experienced significantly fewer struggles. Results suggested that TTRPGs can provide a safe space environment where autistic adults can engage in productive social interactions with like-minded individuals. It also may allow autistic participants to experience 'bleed' or the ability to take on a new character that changes the way they feel about themselves outside of the game. Future directions for this work are discussed.

Implementing mobile eye tracking in psychological research: A practical guide

Eye tracking provides direct, temporally and spatially sensitive measures of eye gaze. It can capture visual attention patterns from infancy through adulthood. However, commonly used screen-based eye tracking (SET) paradigms are limited in their depiction of how individuals process information as they interact with the environment in "real life". Mobile eye tracking (MET) records participant-perspective gaze in the context of active behavior. Recent technological developments in MET hardware enable researchers to capture egocentric vision as early as infancy and across the lifespan. However, challenges remain in MET data collection, processing, and analysis. The present paper aims to provide an introduction and practical guide to starting researchers in the field to facilitate the use of MET in psychological research with a wide range of age groups. First, we provide a general introduction to MET. Next, we briefly review MET studies in adults and children that provide new insights into attention and its roles in cognitive and socioemotional functioning. We then discuss technical issues relating to MET data collection and provide guidelines for data quality inspection, gaze annotations, data visualization, and statistical analyses. Lastly, we conclude by discussing the future directions of MET implementation. Open-source programs for MET data quality inspection, data visualization, and analysis are shared publicly.

Observers predict actions from facial emotional expressions during real-time social interactions

In face-to-face social interactions, emotional expressions provide insights into the mental state of an interactive partner. This information can be crucial to infer action intentions and react towards another person's actions. Here we investigate how facial emotional expressions impact subjective experience and physiological and behavioral responses to social actions during real-time interactions. Thirty-two participants interacted with virtual agents while fully immersed in Virtual Reality. Agents displayed an angry or happy facial expression before they directed an appetitive (fist bump) or aversive (punch) social action towards the participant. Participants responded to these actions, either by reciprocating the fist bump or by defending the punch. For all interactions, subjective experience was measured using ratings. In addition, physiological responses (electrodermal activity, electrocardiogram) and participants' response times were recorded. Aversive actions were judged to be more arousing and less pleasant relative to appetitive actions. In addition, angry expressions increased heart rate relative to happy expressions. Crucially, interaction effects between facial emotional expression and action were observed. Angry expressions reduced pleasantness stronger for appetitive compared to aversive actions. Furthermore, skin conductance responses to aversive actions were increased for happy compared to angry expressions and reaction times were faster to aversive compared to appetitive actions when agents showed an angry expression. These results indicate that observers used facial emotional expression to generate expectations for particular actions. Consequently, the present study demonstrates that observers integrate information from facial emotional expressions with actions during social interactions.

Speaker-listener neural coupling correlates with semantic and acoustic features of naturalistic speech

Recent research has extensively reported the phenomenon of inter-brain neural coupling between speakers and listeners during speech communication. Yet, the specific speech processes underlying this neural coupling remain elusive. To bridge this gap, this study estimated the correlation between the temporal dynamics of speaker-listener neural coupling with speech features, utilizing two inter-brain datasets accounting for different noise levels and listener's language experiences (native vs. non-native). We first derived time-varying speaker-listener neural coupling, extracted acoustic feature (envelope) and semantic features (entropy and surprisal) from speech, and then explored their correlational relationship. Our findings reveal that in clear conditions, speaker-listener neural coupling correlates with semantic features. However, as noise increases, this correlation is only significant for native listeners. For non-native listeners, neural coupling correlates predominantly with acoustic feature rather than semantic features. These results revealed how speaker-listener neural coupling is associated with the acoustic and semantic features under various scenarios, enriching our understanding of the inter-brain neural mechanisms during natural speech communication. We therefore advocate for more attention on the dynamic nature of speaker-listener neural coupling and its modeling with multilevel speech features.

The neuroscience of active learning and direct instruction

Throughout the educational system, students experiencing active learning pedagogy perform better and fail less than those taught through direct instruction. Can this be ascribed to differences in learning from a neuroscientific perspective? This review examines mechanistic, neuroscientific evidence that might explain differences in cognitive engagement contributing to learning outcomes between these instructional approaches. In classrooms, direct instruction comprehensively describes academic content, while active learning provides structured opportunities for learners to explore, apply, and manipulate content. Synaptic plasticity and its modulation by arousal or novelty are central to all learning and both approaches. As a form of social learning, direct instruction relies upon working memory. The reinforcement learning circuit, associated agency, curiosity, and peer-to-peer social interactions combine to enhance motivation, improve retention, and build higher-order-thinking skills in active learning environments. When working memory becomes overwhelmed, additionally engaging the reinforcement learning circuit improves retention, providing an explanation for the benefits of active learning. This analysis provides a mechanistic examination of how emerging neuroscience principles might inform pedagogical choices at all educational levels.

Online chasing action recruits both mirror neuron and mentalizing systems: A pilot fNIRS study

Engaging in chasing, where an actor actively pursues a target, is considered a crucial activity for the development of social skills. Previous studies have focused predominantly on understanding the neural correlates of chasing from an observer's perspective, but the neural mechanisms underlying the real-time implementation of chasing action remain poorly understood. To gain deeper insights into this phenomenon, the current study employed functional near-infrared spectroscopy (fNIRS) techniques and a novel interactive game. In this interactive game, participants (N = 29) were tasked to engage in chasing behavior by controlling an on-screen character using a gamepad, with the goal of catching a virtual partner. To specifically examine the brain activations associated with the interactive nature of chasing, we included two additional interactive actions: following action of following the path of a virtual partner and free action of moving without a specific pursuit goal. The results revealed that chasing and following actions elicited activation in a broad and overlapping network of brain regions, including the temporoparietal junction (TPJ), medial prefrontal cortex (mPFC), premotor cortex (PMC), primary somatosensory cortex (SI), and primary motor cortex (M1). Crucially, these regions were found to be modulated by the type of interaction, with greater activation and functional connectivity during the chasing interaction than during the following and free interactions. These findings suggested that both the MNS, encompassing regions such as the PMC, M1 and SI, and the mentalizing system (MS), involving the TPJ and mPFC, contribute to the execution of online chasing actions. Thus, the present study represents an initial step toward future investigations into the roles of MNS and MS in real-time chasing interactions.

A systematic review of mobile brain/body imaging studies using the P300 event-related potentials to investigate cognition beyond the laboratory

The P300 ERP component, related to the onset of task-relevant or infrequent stimuli, has been widely used in the Mobile Brain/Body Imaging (MoBI) literature. This systematic review evaluates the quality and breadth of P300 MoBI studies, revealing a maturing field with well-designed research yet grappling with standardization and global representation challenges. While affirming the reliability of measuring P300 ERP components in mobile settings, the review identifies significant hurdles in standardizing data cleaning and processing techniques, impacting comparability and reproducibility. Geographical disparities emerge, with studies predominantly in the Global North and a dearth of research from the Global South, emphasizing the need for broader inclusivity to counter the WEIRD bias in psychology. Collaborative projects and mobile EEG systems showcase the feasibility of reaching diverse populations, which is essential to advance precision psychiatry and to integrate varied data streams. Methodologically, a trend toward ecological validity is noted, shifting from lab-based to real-world settings with portable EEG system advancements. Future hardware developments are expected to balance signal quality and sensor intrusiveness, enriching data collection in everyday contexts. Innovative methodologies reflect a move toward more natural experimental settings, prompting critical questions about the applicability of traditional ERP markers, such as the P300 outside structured paradigms. The review concludes by highlighting the crucial role of integrating mobile technologies, physiological sensors, and machine learning to advance cognitive neuroscience. It advocates for an operational definition of ecological validity to bridge the gap between controlled experiments and the complexity of embodied cognitive experiences, enhancing both theoretical understanding and practical application in study design.

Neural correlates of static and dynamic social decision-making in real-time sibling interactions

In traditional game theory tasks, social decision-making is centered on the prediction of the intentions (i.e., mentalizing) of strangers or manipulated responses. In contrast, real-life scenarios often involve familiar individuals in dynamic environments. Further research is needed to explore neural correlates of social decision-making with changes in the available information and environmental settings. This study collected fMRI hyperscanning data (N = 100, 46 same-sex pairs were analyzed) to investigate sibling pairs engaging in an iterated Chicken Game task within a competitive context, including two decision-making phases. In the static phase, participants chose between turning (cooperate) and continuing (defect) in a fixed time window. Participants could estimate the probability of different events based on their priors (previous outcomes and representation of other's intentions) and report their decision plan. The dynamic phase mirrored real-world interactions in which information is continuously changing (replicated within a virtual environment). Individuals had to simultaneously update their beliefs, monitor the actions of the other, and adjust their decisions. Our findings revealed substantial choice consistency between the two phases and evidence for shared neural correlates in mentalizing-related brain regions, including the prefrontal cortex, temporoparietal junction (TPJ), and precuneus. Specific neural correlates were associated with each phase; increased activation of areas associated with action planning and outcome evaluation were found in the static compared with the dynamic phase. Using the opposite contrast, dynamic decision-making showed higher activation in regions related to predicting and monitoring other's actions, including the anterior cingulate cortex and insula. Cooperation (turning), compared with defection (continuing), showed increased activation in mentalizing-related regions only in the static phase, while defection, relative to cooperation, exhibited higher activation in areas associated with conflict monitoring and risk processing in the dynamic phase. Men were less cooperative and had greater TPJ activation. Sibling competitive relationship did not predict competitive behavior but showed a tendency to predict brain activity during dynamic decision-making. Only individual brain activation results are included here, and no interbrain analyses are reported. These neural correlates emphasize the significance of considering varying levels of information available and environmental settings when delving into the intricacies of mentalizing during social decision-making among familiar individuals.

On the neural networks of self and other bias and their role in emergent social interactions

Extensive research has documented the brain networks that play an integral role in bias, or the alteration and filtration of information processing in a manner that fundamentally favors an individual. The roots of bias, whether self- or other-oriented, are a complex constellation of neural and psychological processes that start at the most fundamental levels of sensory processing. From the millisecond information is received in the brain it is filtered at various levels and through various brain networks in relation to extant intrinsic activity to provide individuals with a perception of reality that complements and satisfies the conscious perceptions they have for themselves and the cultures in which they were reared. The products of these interactions, in turn, are dynamically altered by the introduction of others, be they friends or strangers who are similar or different in socially meaningful ways. While much is known about the various ways that basic biases alter specific aspects of neural function to support various forms of bias, the breadth and scope of the phenomenon remains entirely unclear. The purpose of this review is to examine the brain networks that shape (i.e., bias) the self-concept and how interactions with similar (ingroup) compared to dissimilar (outgroup) others alter these network (and subsequent interpersonal) interactions in fundamental ways. Throughout, focus is placed on an emerging understanding of the brain as a complex system, which suggests that many of these network interactions likely occur on a non-linear scale that blurs the lines between network hierarchies.

From physical to digital: A theoretical-methodological primer on designing hyperscanning investigations to explore remote exchanges

As individuals increasingly engage in social interactions through digital mediums, understanding the neuroscientific underpinnings of such exchanges becomes a critical challenge and a valuable opportunity. In line with a second-person neuroscience approach, understanding the forms of interpersonal syntonisation that occur during digital interactions is pivotal for grasping the mechanisms underlying successful collaboration in virtual spaces. The hyperscanning paradigm, involving the simultaneous monitoring of the brains and bodies of multiple interacting individuals, seems to be a powerful tool for unravelling the neural correlates of interpersonal syntonisation in social exchanges. We posit that such approach can now open new windows on interacting brains' responses even to digitally-conveyed social cues, offering insights into how social information is processed in the absence of traditional face-to-face settings. Yet, such paradigm shift raises challenging methodological questions, which should be answered properly to conduct significant and informative hyperscanning investigations. Here, we provide an introduction to core methodological issues dedicated to novices approaching the design of hyperscanning investigations of remote exchanges in natural settings, focusing on the selection of neuroscientific devices, synchronization of data streams, and data analysis approaches. Finally, a methodological checklist for devising robust hyperscanning studies on digital interactions is presented.

Evidence of mutual non-verbal synchrony in learners with severe learning disability and autism, and their support workers: a motion energy analysis study

Introduction

Some research indicates that neurodivergent people are less likely than "neurotypical" people to adapt their movements to a partner's movements to facilitate interpersonal motor synchrony. Researchers therefore suggest synchrony deficits underlie the social differences associated with autism and other neurodivergences. Intensive Interaction (II) is a client-led approach, where Learning Support Workers (LSW) follow the lead of learners to create balanced and reciprocal interactions.

Methods

We aimed to examine the balance of synchrony in learners with autism and Severe Learning Disabilities and their LSWs in a special education college where learners had prior experience with II. Using Motion Energy Analysis, we assessed the degree to which each partner acted as a leader, and hence which partner acted as a follower, during moments of close synchrony.

Results

Overall, learners and LSWs showed higher than chance synchrony. There were no differences in the degree to which each partner led the moments of synchrony, or the amount pairs synchronized with zero-lag, where there was no delay between each partners' movements.

Discussion

The equal balance of leading and following in the learner and LSW pairs demonstrates that both partners consistently adapted their movements to their partner's movements to facilitate synchrony. The findings tentatively challenge the notion of a synchrony deficit in autism and suggest synchrony can be present in cross-neurotype pairs in comfortable and engaging conditions. We discuss the potential for client-led, movement-based approaches to support smooth interactions across neurotypes.

In the eye of the beholder: Social traits predict motor simulation during naturalistic action perception

Previous research has robustly demonstrated that eye contact between actor and observer promotes the simulation of perceived actions into the observer's own motor system, which in turn facilitates social perception and communication. The socially relevant connotation embedded in eye contact may however be different for individuals with differing social traits. Here, we examined how "normal" (i.e. non-clinical) variability in self-reported social responsiveness/autistic traits, social anxiety and interpersonal relationship style (secure, avoidant or anxious attachment) influences neural motor simulation during action observation in different gaze conditions. To do so, we analyzed an existing dataset involving 124 adult participants (age range: 18-35 years) who underwent transcranial magnetic stimulation (TMS) while observing an actor performing simple hand actions and simultaneously engaging in eye contact or gazing away from the observer. Motor evoked potential (MEP) amplitudes were adopted as an index of motor resonance. Regression-based analyses highlighted the role of social responsiveness and secure attachment in shaping motor resonance, indicating that socially responsive motor resonance during dyadic gaze (i.e., MEPdirect > MEPaverted) was only observed in participants displaying high levels of these traits. Furthermore, a clustering analysis identified two to three distinct subgroups of participants with unique social trait profiles, showing a clear differentiation in motor resonant patterns upon different gaze cues that is in accordance with a recent neurobiological framework of attachment. Together, results demonstrate that motor resonance within a given social interaction may serve as a sensitive tracker of socio-interactive engagement, which allows to capture subclinical inter-individual variation in relevant social traits.

Visual bodily signals and conversational context benefit the anticipation of turn ends

The typical pattern of alternating turns in conversation seems trivial at first sight. But a closer look quickly reveals the cognitive challenges involved, with much of it resulting from the fast-paced nature of conversation. One core ingredient to turn coordination is the anticipation of upcoming turn ends so as to be able to ready oneself for providing the next contribution. Across two experiments, we investigated two variables inherent to face-to-face conversation, the presence of visual bodily signals and preceding discourse context, in terms of their contribution to turn end anticipation. In a reaction time paradigm, participants anticipated conversational turn ends better when seeing the speaker and their visual bodily signals than when they did not, especially so for longer turns. Likewise, participants were better able to anticipate turn ends when they had access to the preceding discourse context than when they did not, and especially so for longer turns. Critically, the two variables did not interact, showing that visual bodily signals retain their influence even in the context of preceding discourse. In a pre-registered follow-up experiment, we manipulated the visibility of the speaker's head, eyes and upper body (i.e. torso + arms). Participants were better able to anticipate turn ends when the speaker's upper body was visible, suggesting a role for manual gestures in turn end anticipation. Together, these findings show that seeing the speaker during conversation may critically facilitate turn coordination in interaction.

Testing theory of mind in large language models and humans

At the core of what defines us as humans is the concept of theory of mind: the ability to track other people's mental states. The recent development of large language models (LLMs) such as ChatGPT has led to intense debate about the possibility that these models exhibit behaviour that is indistinguishable from human behaviour in theory of mind tasks. Here we compare human and LLM performance on a comprehensive battery of measurements that aim to measure different theory of mind abilities, from understanding false beliefs to interpreting indirect requests and recognizing irony and faux pas. We tested two families of LLMs (GPT and LLaMA2) repeatedly against these measures and compared their performance with those from a sample of 1,907 human participants. Across the battery of theory of mind tests, we found that GPT-4 models performed at, or even sometimes above, human levels at identifying indirect requests, false beliefs and misdirection, but struggled with detecting faux pas. Faux pas, however, was the only test where LLaMA2 outperformed humans. Follow-up manipulations of the belief likelihood revealed that the superiority of LLaMA2 was illusory, possibly reflecting a bias towards attributing ignorance. By contrast, the poor performance of GPT originated from a hyperconservative approach towards committing to conclusions rather than from a genuine failure of inference. These findings not only demonstrate that LLMs exhibit behaviour that is consistent with the outputs of mentalistic inference in humans but also highlight the importance of systematic testing to ensure a non-superficial comparison between human and artificial intelligences.

Prospects for Augmenting Team Interactions with Real-Time Coordination-Based Measures in Human-Autonomy Teams

Complex work in teams requires coordination across team members and their technology as well as the ability to change and adapt over time to achieve effective performance. To support such complex interactions, recent efforts have worked toward the design of adaptive human-autonomy teaming systems that can provide feedback in or near real time to achieve the desired individual or team results. However, while significant advancements have been made to better model and understand the dynamics of team interaction and its relationship with task performance, appropriate measures of team coordination and computational methods to detect changes in coordination have not yet been widely investigated. Having the capacity to measure coordination in real time is quite promising as it provides the opportunity to provide adaptive feedback that may influence and regulate teams' coordination patterns and, ultimately, drive effective team performance. A critical requirement to reach this potential is having the theoretical and empirical foundation from which to do so. Therefore, the first goal of the paper is to review approaches to coordination dynamics, identify current research gaps, and draw insights from other areas, such as social interaction, relationship science, and psychotherapy. The second goal is to collate extant work on feedback and advance ideas for adaptive feedback systems that have potential to influence coordination in a way that can enhance the effectiveness of team interactions. In addressing these two goals, this work lays the foundation as well as plans for the future of human-autonomy teams that augment team interactions using coordination-based measures.

Social context and drug cues modulate inhibitory control in cocaine addiction: involvement of the STN evidenced through functional MRI

Addictions often develop in a social context, although the influence of social factors did not receive much attention in the neuroscience of addiction. Recent animal studies suggest that peer presence can reduce cocaine intake, an influence potentially mediated, among others, by the subthalamic nucleus (STN). However, there is to date no neurobiological study investigating this mediation in humans. This study investigated the impact of social context and drug cues on brain correlates of inhibitory control in individuals with and without cocaine use disorder (CUD) using functional Magnetic Resonance Imaging (fMRI). Seventeen CUD participants and 17 healthy controls (HC) performed a novel fMRI "Social" Stop-Signal Task (SSST) in the presence or absence of an observer while being exposed to cocaine-related (vs. neutral) cues eliciting craving in drug users. The results showed that CUD participants, while slower at stopping with neutral cues, recovered control level stopping abilities with cocaine cues, while HC did not show any difference. During inhibition (Stop Correct vs Stop Incorrect), activity in the right STN, right inferior frontal gyrus (IFG), and bilateral orbitofrontal cortex (OFC) varied according to the type of cue. Notably, the presence of an observer reversed this effect in most areas for CUD participants. These findings highlight the impact of social context and drug cues on inhibitory control in CUD and the mediation of these effects by the right STN and bilateral OFC, emphasizing the importance of considering the social context in addiction research. They also comfort the STN as a potential addiction treatment target.

Enhancing musical pleasure through shared musical experience

Music and social interactions represent two of the most important sources of pleasure in our lives, both engaging the mesolimbic dopaminergic system. However, there is limited understanding regarding whether and how sharing a musical activity in a social context influences and modifies individuals' rewarding experiences. Here, we aimed at (1) modulating the pleasure derived from music under different social scenarios and (2) further investigating its impact on reward-related prosocial behavior and memory. Across three online experiments, we simulated a socially shared music listening and found that participants' music reward was significantly modulated by the social context, with higher reported pleasure for greater levels of social sharing. Furthermore, the increased pleasure reported by the participants positively influenced prosocial behavior and memory outcomes, highlighting the facilitating role of socially boosted reward. These findings provide evidence about the rewarding nature of socially driven music experiences, with important potential implications in educational and clinical settings.

Beyond human-likeness: Socialness is more influential when attributing mental states to robots

We sought to replicate and expand previous work showing that the more human-like a robot appears, the more willing people are to attribute mind-like capabilities and socially engage with it. Forty-two participants played games against a human, a humanoid robot, a mechanoid robot, and a computer algorithm while undergoing functional neuroimaging. We confirmed that the more human-like the agent, the more participants attributed a mind to them. However, exploratory analyses revealed that the perceived socialness of an agent appeared to be as, if not more, important for mind attribution. Our findings suggest top-down knowledge cues may be equally or possibly more influential than bottom-up stimulus cues when exploring mind attribution in non-human agents. While further work is now required to test this hypothesis directly, these preliminary findings hold important implications for robotic design and to understand and test the flexibility of human social cognition when people engage with artificial agents.

Advancements in brain-machine interfaces for application in the metaverse

In recent years, with the shift of focus in metaverse research toward content exchange and social interaction, breaking through the current bottleneck of audio-visual media interaction has become an urgent issue. The use of brain-machine interfaces for sensory simulation is one of the proposed solutions. Currently, brain-machine interfaces have demonstrated irreplaceable potential as physiological signal acquisition tools in various fields within the metaverse. This study explores three application scenarios: generative art in the metaverse, serious gaming for healthcare in metaverse medicine, and brain-machine interface applications for facial expression synthesis in the virtual society of the metaverse. It investigates existing commercial products and patents (such as MindWave Mobile, GVS, and Galea), draws analogies with the development processes of network security and neurosecurity, bioethics and neuroethics, and discusses the challenges and potential issues that may arise when brain-machine interfaces mature and are widely applied. Furthermore, it looks ahead to the diverse possibilities of deep and varied applications of brain-machine interfaces in the metaverse in the future.

The subjective value of genuine smiles guides real-world social behaviour

The mechanisms that underpin human social behaviour are poorly understood, in part because natural social behaviour is challenging to study. The task of linking the mechanisms thought to drive social behaviour to specific social behaviours in a manner that maintains ecological validity poses an even greater challenge. Here we report evidence that the subjective value people assign to genuine smiles, as measured in the laboratory, determines their responsiveness to genuine smiles encountered in a naturalistic social interaction. Specifically, participants (university undergraduates; age 17 to 36) who valued genuine smiles to a greater degree also showed stronger attention capture effects to neutral faces that were previously associated with genuine smiles and faster reciprocity of a social partner's smiles in a real social interaction. Additionally, the faster participants responded to the partner's genuine smiles the higher the partner's ratings of interaction quality were after the interaction. These data suggest that individual differences in subjective value of genuine smiles, measured in the lab, is one element that underpins responsiveness to natural genuine smiles and subsequent social outcomes.

Social context modulates multibrain broadband dynamics and functional brain-to-brain coupling in the group of mice

Although mice are social, multiple animals' neural activities are rarely explored. To characterise the neural activities during multi-brain interaction, we simultaneously recorded local field potentials (LFP) in the prefrontal cortex of four mice. The social context and locomotive states predominately modulated the entire LFP structure. The power of lower frequency bands-delta to alpha-were correlated with each other and anti-correlated with gamma power. The high-to-low-power ratio (HLR) provided a useful measure to understand LFP changes along the change of behavioural and locomotive states. The HLR during huddled conditions was lower than that during non-huddled conditions, dividing the social context into two. Multi-brain analyses of HLR indicated that the mice in the group displayed high cross-correlation. The mice in the group often showed unilateral precedence of HLR by Granger causality analysis, possibly comprising a hierarchical social structure. Overall, this study shows the importance of the social environment in brain dynamics and emphasises the simultaneous multi-brain recordings in social neuroscience.

Noninvasive brain stimulation in autism: review and outlook for personalized interventions in adult patients

Noninvasive brain stimulation (NIBS) has been increasingly investigated during the last decade as a treatment option for persons with autism spectrum disorder (ASD). Yet, previous studies did not reach a consensus on a superior treatment protocol or stimulation target. Persons with ASD often suffer from social isolation and high rates of unemployment, arising from difficulties in social interaction. ASD involves multiple neural systems involved in perception, language, and cognition, and the underlying brain networks of these functional domains have been well documented. Aiming to provide an overview of NIBS effects when targeting these neural systems in late adolescent and adult ASD, we conducted a systematic search of the literature starting at 631 non-duplicate publications, leading to six studies corresponding with inclusion and exclusion criteria. We discuss these studies regarding their treatment rationale and the accordingly chosen methodological setup. The results of these studies vary, while methodological advances may allow to explain some of the variability. Based on these insights, we discuss strategies for future clinical trials to personalize the selection of brain stimulation targets taking into account intersubject variability of brain anatomy as well as function.

Altered States and Social Bonds: Effects of MDMA and Serotonergic Psychedelics on Social Behavior as a Mechanism Underlying Substance-Assisted Therapy

There has been renewed interest in the use of 3,4-methylenedioxy-methamphetamine (MDMA) and serotonergic psychedelics in the treatment of multiple psychiatric disorders. Many of these compounds are known to produce prosocial effects, but how these effects relate to therapeutic efficacy and the extent to which prosocial effects are unique to a particular drug class is unknown. In this article, we present a narrative overview and compare evidence for the prosocial effects of MDMA and serotonergic psychedelics to elucidate shared mechanisms that may underlie the therapeutic process. We discuss 4 categories of prosocial effects: altered self-image, responses to social reward, responses to negative social input, and social neuroplasticity. While both categories of drugs alter self-perception, MDMA may do so in a way that is less related to the experience of mystical-type states than serotonergic psychedelics. In the case of social reward, evidence supports the ability of MDMA to enhance responses and suggests that serotonergic psychedelics may also do so, but more research is needed in this area. Both drug classes consistently dampen reactivity to negative social stimuli. Finally, preclinical evidence supports the ability of both drug classes to induce social neuroplasticity, promoting adaptive rewiring of neural circuits, which may be helpful in trauma processing. While both MDMA and serotonergic psychedelics produce prosocial effects, they differ in the mechanisms through which they do this. These differences affect the types of psychosocial interventions that may work best with each compound.

Threatened by others or by everything? The effects of momentary and trait loneliness on daily appraisals of social company and being alone in young adults

Theoretical accounts of loneliness suggest that it may lead to psychopathological consequences by increasing the perception of social threat. However, it is unclear whether the real-life effects of both trait and state loneliness are specific to social situations. To answer this question, two experience sampling studies were conducted with prestratified samples of young adults (18-35) with moderate (Study 1, N = 64) or low and high (Study 2, N = 103) levels of loneliness. Participants were asked to report their emotional states and appraisals of social and nonsocial situations. Multilevel modelling of momentary and time-lagged associations revealed that trait loneliness was associated with less positive (Study 1) and more negative (Study 2) company appraisals. Importantly, in Study 2, trait loneliness was also related to less positive and more negative appraisals of being alone. Momentary loneliness was related to less positive and more negative appraisals of both types and predicted negative social appraisals over time in both studies. In Study 2, time-lagged interaction effects on social appraisals were found between the two levels. The results suggest that in highly lonely individuals, both levels of loneliness may lead to a general negativity bias and have a synergistic effect.

Updating beliefs about pain following advice: Trustworthiness of social advice predicts pain expectations and experience

Prior expectations influence pain experience. These expectations, in turn, rely on prior pain experience, but they may also be socially influenced. Yet, most research has focused on self rather than social expectations about pain, and hardly any studies examined their combined effects on pain. Here, we adopted a Bayesian learning perspective to investigate how explicitly communicated social expectations ('advice about pain tolerance') affect own pain expectations, and ultimately pain tolerance, under varying conditions of social epistemic uncertainty (trustworthiness of the advice). N = 72 female participants took part in a coldpressor (cold water) task before (self-learning baseline) and after (socially-influenced learning) receiving advice about their likely pain tolerance from a confederate, the trustworthiness of whom was experimentally manipulated. We used path analysis to test the hypothesis that social advice from a highly trustworthy confederate would influence participants' expectations about pain more than advice from a less trustworthy source, and that the degree of this social influence would in turn predict pain tolerance. We further used a simplified, Bayesian learning, computational approach for explicit belief updating to examine the role of latent parameters of precision optimisation in how participants subsequently changed their future pain expectations (prospective posterior beliefs) based on the combined effect of the confederate's advice on their own pain expectations, and their own task experience. Results confirmed that participants adjusted their pain expectations towards the confederate's advice more in the high- vs. low-trustworthiness condition, and this advice taking predicted their pain tolerance. Furthermore, the confederate's trustworthiness influenced how participants weighted the confederate's advice in relation to their own expectations and task experience in forming prospective posterior beliefs. When participants received advice from a less trustworthy confederate, their own sensory experience was weighted more highly than their socially-influenced prior expectations. Thus, explicit social advice appears to impact pain by influencing one's own pain expectations, but low social trustworthiness leads to these expectations becoming more malleable to novel, sensory learning.

Neural mechanisms distinguishing two types of cooperative problem-solving approaches: An fNIRS hyperscanning study

Collaborative cooperation (CC) and division of labor cooperation (DLC) are two prevalent forms of cooperative problem-solving approaches in daily life. Despite extensive research on the neural mechanisms underlying cooperative problem-solving approaches, a notable gap exists between the neural processes that support CC and DLC. The present study utilized a functional near-infrared spectroscopy (fNIRS) hyperscanning technique along with a classic cooperative tangram puzzle task to investigate the neural mechanisms engaged by both friends and stranger dyads during CC versus DLC. The key findings of this study were as follows: (1) Dyads exhibited superior behavioral performance in the DLC task than in the CC task. The CC task bolstered intra-brain functional connectivity and inter-brain synchrony (IBS) in regions linked to the mirror neuron system (MNS), spatial perception (SP) and cognitive control. (2) Friend dyads showed stronger IBS in brain regions associated with the MNS than stranger dyads. (3) Perspective-taking predicted not only dyads' behavioral performance in the CC task but also their IBS in brain regions associated with SP during the DLC task. Taken together, these findings elucidate the divergent behavioral performance and neural connection patterns between the two cooperative problem-solving approaches. This study provides novel insights into the various neurocognitive processes underlying flexible coordination strategies in real-world cooperative contexts.

Interpersonal physiological and psychological synchrony predict the social transmission of nocebo hyperalgesia between individuals

Witnessing another's pain can heighten pain in the observer. However, research has focused on the observer's intrapersonal experience. Here, a social transmission-chain explored the spread of socially-acquired nocebo hyperalgesia. Dyads of genuine participants were randomised to 'Generations' (G1-G3). G1-Demonstrators, observed by G2-Observers, experienced high/low thermal pain contingent on supposed activity/inactivity of a sham-treatment. G2 became Demonstrators, witnessed by G3-Observers. They experienced fixed low-temperature stimuli irrespective of sham-treatment 'activity'. G3 then Demonstrated for G4-Observers (a confederate), also experiencing low-temperature stimuli only. Pain ratings, electrodermal activity, and facial action units were measured. G1's treatment-related pain propagated throughout the chain. G2 and G3 participants showed heightened subjective and physiological response to sham-treatment, despite equivalent stimulus temperatures, and G3 never witnessing the initial pain-event. Dyadic interpersonal physiological synchrony (electrodermal activity) and psychological synchrony (Observer's ability to predict the Demonstrator's pain), predicted subsequent socially-acquired pain. Implications relate to the interpersonal spread of maladaptive pain experiences.

Using interbrain synchrony to study teamwork: A systematic review and meta-analysis

It has been proposed that interbrain synchrony (IBS) may help to elucidate the neural mechanisms underpinning teamwork. As hyperscanning studies have provided abundant findings on IBS in team environments, the current review aims to synthesize the findings of hyperscanning studies in a way that is relevant to the teamwork research. A systematic review was conducted. Included studies were classified according to the IPO (i.e. input, process, output) model of teamwork. Three multi-level meta-analyses were performed to quantify the associations between IBS and the three IPO variables. The methodology followed PRISMA guidelines and the protocol was pre-registered (https://osf.io/7h8sa/). Of the 229 studies, 41 were included, representing 1326 teams. The three meta-analyses found statistically significant positive effects, indicating a positive association between IBS and the three IPO teamwork variables. This study provides evidence that IBS is a relevant measure of the teamwork process and argues for the continued use of IBS to study teamwork.

Protective factors for children with autism spectrum disorder during COVID-19-related strict lockdowns: a Shanghai autism early developmental cohort study

BACKGROUND

COVID-19 lockdowns increased the risk of mental health problems, especially for children with autism spectrum disorder (ASD). However, despite its importance, little is known about the protective factors for ASD children during the lockdowns.

METHODS

Based on the Shanghai Autism Early Developmental Cohort, 188 ASD children with two visits before and after the strict Omicron lockdown were included; 85 children were lockdown-free, while 52 and 51 children were under the longer and the shorter durations of strict lockdown, respectively. We tested the association of the lockdown group with the clinical improvement and also the modulation effects of parent/family-related factors on this association by linear regression/mixed-effect models. Within the social brain structures, we examined the voxel-wise interaction between the grey matter volume and the identified modulation effects.

RESULTS

Compared with the lockdown-free group, the ASD children experienced the longer duration of strict lockdown had less clinical improvement (β = 0.49, 95% confidence interval (CI) [0.19-0.79], p = 0.001) and this difference was greatest for social cognition (2.62 [0.94-4.30], p = 0.002). We found that this association was modulated by parental agreeableness in a protective way (-0.11 [-0.17 to -0.05], p = 0.002). This protective effect was enhanced in the ASD children with larger grey matter volumes in the brain's mentalizing network, including the temporal pole, the medial superior frontal gyrus, and the superior temporal gyrus.

CONCLUSIONS

This longitudinal neuroimaging cohort study identified that the parental agreeableness interacting with the ASD children's social brain development reduced the negative impact on clinical symptoms during the strict lockdown.

A social inference model of idealization and devaluation

People often form polarized beliefs, imbuing objects (e.g., themselves or others) with unambiguously positive or negative qualities. In clinical settings, this is referred to as dichotomous thinking or "splitting" and is a feature of several psychiatric disorders. Here, we introduce a Bayesian model of splitting that parameterizes a tendency to rigidly categorize objects as either entirely "Bad" or "Good," rather than to flexibly learn dispositions along a continuous scale. Distinct from the previous descriptive theories, the model makes quantitative predictions about how dichotomous beliefs emerge and are updated in light of new information. Specifically, the model addresses how splitting is context-dependent, yet exhibits stability across time. A key model feature is that phases of devaluation and/or idealization are consolidated by rationally attributing counter-evidence to external factors. For example, when another person is idealized, their less-than-perfect behavior is attributed to unfavorable external circumstances. However, sufficient counter-evidence can trigger switches of polarity, producing bistable dynamics. We show that the model can be fitted to empirical data, to measure individual susceptibility to relational instability. For example, we find that a latent categorical belief that others are "Good" accounts for less changeable, and more certain, character impressions of benevolent as opposed to malevolent others among healthy participants. By comparison, character impressions made by participants with borderline personality disorder reveal significantly higher and more symmetric splitting. The generative framework proposed invites applications for modeling oscillatory relational and affective dynamics in psychotherapeutic contexts. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Interbrain substrates of role switching during mother-child interaction

Mother-child interaction is highly dynamic and reciprocal. Switching roles in these back-and-forth interactions serves as a crucial feature of reciprocal behaviors while the underlying neural entrainment is still not well-studied. Here, we designed a role-controlled cooperative task with dual EEG recording to explore how differently two brains interact when mothers and children hold different roles. When children were actors and mothers were observers, mother-child interbrain synchrony emerged primarily within the theta oscillations and the frontal lobe, which highly correlated with children's attachment to their mothers (self-reported by mothers). When their roles were reversed, this synchrony was shifted to the alpha oscillations and the central area and associated with mothers' perception of their relationship with their children. The results suggested an observer-actor neural alignment within the actor's oscillations, which was related to the actor-toward-observer emotional bonding. Our findings contribute to the understanding of how interbrain synchrony is established and dynamically changed during mother-child reciprocal interaction.

How does the human brain process noisy speech in real life? Insights from the second-person neuroscience perspective

Comprehending speech with the existence of background noise is of great importance for human life. In the past decades, a large number of psychological, cognitive and neuroscientific research has explored the neurocognitive mechanisms of speech-in-noise comprehension. However, as limited by the low ecological validity of the speech stimuli and the experimental paradigm, as well as the inadequate attention on the high-order linguistic and extralinguistic processes, there remains much unknown about how the brain processes noisy speech in real-life scenarios. A recently emerging approach, i.e., the second-person neuroscience approach, provides a novel conceptual framework. It measures both of the speaker's and the listener's neural activities, and estimates the speaker-listener neural coupling with regarding of the speaker's production-related neural activity as a standardized reference. The second-person approach not only promotes the use of naturalistic speech but also allows for free communication between speaker and listener as in a close-to-life context. In this review, we first briefly review the previous discoveries about how the brain processes speech in noise; then, we introduce the principles and advantages of the second-person neuroscience approach and discuss its implications to unravel the linguistic and extralinguistic processes during speech-in-noise comprehension; finally, we conclude by proposing some critical issues and calls for more research interests in the second-person approach, which would further extend the present knowledge about how people comprehend speech in noise.

Artificial cognition vs. artificial intelligence for next-generation autonomous robotic agents

The trend in industrial/service robotics is to develop robots that can cooperate with people, interacting with them in an autonomous, safe and purposive way. These are the fundamental elements characterizing the fourth and the fifth industrial revolutions (4IR, 5IR): the crucial innovation is the adoption of intelligent technologies that can allow the development of cyber-physical systems, similar if not superior to humans. The common wisdom is that intelligence might be provided by AI (Artificial Intelligence), a claim that is supported more by media coverage and commercial interests than by solid scientific evidence. AI is currently conceived in a quite broad sense, encompassing LLMs and a lot of other things, without any unifying principle, but self-motivating for the success in various areas. The current view of AI robotics mostly follows a purely disembodied approach that is consistent with the old-fashioned, Cartesian mind-body dualism, reflected in the software-hardware distinction inherent to the von Neumann computing architecture. The working hypothesis of this position paper is that the road to the next generation of autonomous robotic agents with cognitive capabilities requires a fully brain-inspired, embodied cognitive approach that avoids the trap of mind-body dualism and aims at the full integration of Bodyware and Cogniware. We name this approach Artificial Cognition (ACo) and ground it in Cognitive Neuroscience. It is specifically focused on proactive knowledge acquisition based on bidirectional human-robot interaction: the practical advantage is to enhance generalization and explainability. Moreover, we believe that a brain-inspired network of interactions is necessary for allowing humans to cooperate with artificial cognitive agents, building a growing level of personal trust and reciprocal accountability: this is clearly missing, although actively sought, in current AI. The ACo approach is a work in progress that can take advantage of a number of research threads, some of them antecedent the early attempts to define AI concepts and methods. In the rest of the paper we will consider some of the building blocks that need to be re-visited in a unitary framework: the principles of developmental robotics, the methods of action representation with prospection capabilities, and the crucial role of social interaction.

Differences in the link between social trait judgment and socio-emotional experience in neurotypical and autistic individuals

Neurotypical (NT) individuals and individuals with autism spectrum disorder (ASD) make different judgments of social traits from others' faces; they also exhibit different social emotional responses in social interactions. A common hypothesis is that the differences in face perception in ASD compared with NT is related to distinct social behaviors. To test this hypothesis, we combined a face trait judgment task with a novel interpersonal transgression task that induces measures social emotions and behaviors. ASD and neurotypical participants viewed a large set of naturalistic facial stimuli while judging them on a comprehensive set of social traits (e.g., warm, charismatic, critical). They also completed an interpersonal transgression task where their responsibility in causing an unpleasant outcome to a social partner was manipulated. The purpose of the latter task was to measure participants' emotional (e.g., guilt) and behavioral (e.g., compensation) responses to interpersonal transgression. We found that, compared with neurotypical participants, ASD participants' self-reported guilt and compensation tendency was less sensitive to our responsibility manipulation. Importantly, ASD participants and neurotypical participants showed distinct associations between self-reported guilt and judgments of criticalness from others' faces. These findings reveal a novel link between perception of social traits and social emotional responses in ASD.

A dual-brain therapeutic approach using noninvasive brain stimulation based on two-person neuroscience: A perspective review

Our actions and decisions in everyday life are heavily influenced by social interactions, which are dynamic feedback loops involving actions, reactions, and internal cognitive processes between individual agents. Social interactions induce interpersonal synchrony, which occurs at different biobehavioral levels and comprises behavioral, physiological, and neurological activities. Hyperscanning-a neuroimaging technique that simultaneously measures the activity of multiple brain regions-has provided a powerful second-person neuroscience tool for investigating the phase alignment of neural processes during interactive social behavior. Neural synchronization, revealed by hyperscanning, is a phenomenon called inter-brain synchrony- a process that purportedly facilitates social interactions by prompting appropriate anticipation of and responses to each other's social behaviors during ongoing shared interactions. In this review, I explored the therapeutic dual-brain approach using noninvasive brain stimulation to target inter-brain synchrony based on second-person neuroscience to modulate social interaction. Artificially inducing synchrony between the brains is a potential adjunct technique to physiotherapy, psychotherapy, and pain treatment- which are strongly influenced by the social interaction between the therapist and patient. Dual-brain approaches to personalize stimulation parameters must consider temporal, spatial, and oscillatory factors. Multiple data fusion analysis, the assessment of inter-brain plasticity, a closed-loop system, and a brain-to-brain interface can support personalized stimulation.

The Emerging Science of Interacting Minds

For over a century, psychology has focused on uncovering mental processes of a single individual. However, humans rarely navigate the world in isolation. The most important determinants of successful development, mental health, and our individual traits and preferences arise from interacting with other individuals. Social interaction underpins who we are, how we think, and how we behave. Here we discuss the key methodological challenges that have limited progress in establishing a robust science of how minds interact and the new tools that are beginning to overcome these challenges. A deep understanding of the human mind requires studying the context within which it originates and exists: social interaction.

Social bonding in groups of humans selectively increases inter-status information exchange and prefrontal neural synchronization

Social groups in various social species are organized with hierarchical structures that shape group dynamics and the nature of within-group interactions. In-group social bonding, exemplified by grooming behaviors among animals and collective rituals and team-building activities in human societies, is recognized as a practical adaptive strategy to foster group harmony and stabilize hierarchical structures in both human and nonhuman animal groups. However, the neurocognitive mechanisms underlying the effects of social bonding on hierarchical groups remain largely unexplored. Here, we conducted simultaneous neural recordings on human participants engaged in-group communications within small hierarchical groups (n = 528, organized into 176 three-person groups) to investigate how social bonding influenced hierarchical interactions and neural synchronizations. We differentiated interpersonal interactions between individuals of different (inter-status) or same (intra-status) social status and observed distinct effects of social bonding on inter-status and intra-status interactions. Specifically, social bonding selectively increased frequent and rapid information exchange and prefrontal neural synchronization for inter-status dyads but not intra-status dyads. Furthermore, social bonding facilitated unidirectional neural alignment from group leader to followers, enabling group leaders to predictively align their prefrontal activity with that of followers. These findings provide insights into how social bonding influences hierarchical dynamics and neural synchronization while highlighting the role of social status in shaping the strength and nature of social bonding experiences in human groups.

Post-interaction neuroplasticity of inter-brain networks underlies the development of social relationship

Inter-brain coupling has been increasingly recognized for its role in supporting connectedness during social communication. Here we investigate whether inter-brain coupling is plastic and persists beyond the offset of social interaction, facilitating the emergence of social closeness. Dyads were concurrently scanned using functional near infrared spectroscopy (fNIRS) while engaging in a task that involved movement synchronization. To assess post-interaction neuroplasticity, participants performed a baseline condition with no interaction before and after the interaction. The results reveal heightened inter-brain coupling in neural networks comprising the inferior frontal gyrus (IFG) and dorsomedial prefrontal cortex in the post-task compared to the pre-task baseline. Critically, the right IFG emerged as a highly connected hub, with post-task inter-brain coupling in this region predicting the levels of motivation to connect socially. We suggest that post-interactions inter-brain coupling may reflect consolidation of socially related cues, underscoring the role of inter-brain plasticity in fundamental aspects of relationship development.

Neurophysiological correlates of interpersonal discrepancy and social adjustment in an interactive decision-making task in dyads

Introduction

The pursuit of convergence and the social behavioral adjustment of conformity are fundamental cooperative behaviors that help people adjust their mental frameworks to reach a common goal. However, while social psychology has extensively studied conformity by its influence context, there is still plenty to investigate about the neural cognitive mechanisms involved in this behavior.

Methods

We proposed a paradigm with two phases, a pre-activation phase to enhance cooperative tendencies and, later, a social decision-making phase in which dyads had to make a perceptual estimation in three consecutive trials and could converge in their decisions without an explicit request or reward to do so. In Study 1, 80 participants were divided in two conditions. In one condition participants did the pre-activation phase alone, while in the other condition the two participants did it with their partners and could interact freely. In Study 2, we registered the electroencephalographical (EEG) activity of 36 participants in the social decision-making phase.

Results

Study 1 showed behavioral evidence of higher spontaneous convergence in participants who interacted in the pre-activation phase. Event related Potentials (ERP) recorded in Study 2 revealed signal differences in response divergence in different time intervals. Time-frequency analysis showed theta, alpha, and beta evidence related to cognitive control, attention, and reward processing associated with social convergence.

Discussion

Current results support the spontaneous convergence of behavior in dyads, with increased behavioral adjustment in those participants who have previously cooperated. In addition, neurophysiological components were associated with discrepancy levels between participants, and supported the validity of the experimental paradigm to study spontaneous social behavioral adaptation in experimental settings.

Machine learning classification of autism spectrum disorder based on reciprocity in naturalistic social interactions

Autism spectrum disorder is characterized by impaired social communication and interaction. As a neurodevelopmental disorder typically diagnosed during childhood, diagnosis in adulthood is preceded by a resource-heavy clinical assessment period. The ongoing developments in digital phenotyping give rise to novel opportunities within the screening and diagnostic process. Our aim was to quantify multiple non-verbal social interaction characteristics in autism and build diagnostic classification models independent of clinical ratings. We analyzed videos of naturalistic social interactions in a sample including 28 autistic and 60 non-autistic adults paired in dyads and engaging in two conversational tasks. We used existing open-source computer vision algorithms for objective annotation to extract information based on the synchrony of movement and facial expression. These were subsequently used as features in a support vector machine learning model to predict whether an individual was part of an autistic or non-autistic interaction dyad. The two prediction models based on reciprocal adaptation in facial movements, as well as individual amounts of head and body motion and facial expressiveness showed the highest precision (balanced accuracies: 79.5% and 68.8%, respectively), followed by models based on reciprocal coordination of head (balanced accuracy: 62.1%) and body (balanced accuracy: 56.7%) motion, as well as intrapersonal coordination processes (balanced accuracy: 44.2%). Combinations of these models did not increase overall predictive performance. Our work highlights the distinctive nature of non-verbal behavior in autism and its utility for digital phenotyping-based classification. Future research needs to both explore the performance of different prediction algorithms to reveal underlying mechanisms and interactions, as well as investigate the prospective generalizability and robustness of these algorithms in routine clinical care.