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A) Sample video frame highlighting the selected region of interest (face of partner). B) Violin plot for the duration of fixations to face of partner for each Condition and Phase: mean (filled circle), SE (error bars), and frequency of values (width of distribution). C) Sample frame of the OpenFace output video. D) Violin plot for the number of active facial action units (AUs) for each Condition and Phase: mean (filled circle), SE (error bars), and frequency of values (width of distribution). Asterisks signify difference at p < 0.05 ( * ), p < 0.01 ( * * ) and p < 0.001 ( * * * ).
Source publication
Pairs of participants mutually communicated (or not) biographical information to each other. By combining simultaneous eye-tracking, face-tracking and functional near-infrared spectroscopy, we examined how this mutual sharing of information modulates social signalling and brain activity. When biographical information was disclosed, participants dir...
Contexts in source publication
Context 1
... 2 = 0.072), but there was an interaction effect between Condition and Phase, F (2,40) = 6.77, p < 0.01, n p 2 = 0.253. Post-hoc pairwise comparisons showed that the mean fixation duration to the face of the partner was higher in the Shared condition compared to the Private condition in the Feedback phase, t (20) = 3.10, p < 0.01, d z = 0.676 (see Fig. 3 A-B). Specifically, participants looked more at the face of the partner in the Shared condition during the Feedback ...
Context 2
... Shared compared to the Private condition. There was also a main effect of Phase, F (2,58) = 132.3, p < 0.001, í µí¼ p 2 = 0.820, and post-hoc pairwise comparisons showed that Asterisks signify difference between Shared and Private conditions at p < 0.05 ( * ), p < 0.01 ( * * ) and p < 0.001 ( * * * ). t (29) = 12.06, p < 0.001, d z = 2.20) (see Fig. 3 C-D). Specifically, participants moved more facial muscles in the Shared condition across all phases, and during the Feedback phase compared to all other ...
Context 3
... significant FDRcorrected clusters for deOxyHb signal, Shared > Private, are reported in the main text, Table 2 and Fig. 4 . Full statistics for all activated clusters are given in Table S4 and Figure S2; results for the same analysis using OxyHb signal are given in Table S5 and Figure S3. ...
Context 4
... we investigated the modulation of social signals and brain activity during sharing of biographical information in a face-to-face interaction. Our findings show that participants gazed more at each other's face and produced more facial displays when communication was enabled ( Fig. 3 ). In an exploratory analysis we also found specific patterns of brain activity during spontaneous production (left supramarginal gyrus; SMG) and observation (right dlPFC/IFG) of facial displays ( Fig. 5 ). ...
Context 5
... eye gaze and facial motion is critical in this task to determine what kind of social behaviours change in face-to-face interactions, which in turn might cause changes in brain activity patterns. Our results showed that participants gazed more to the face of the partner and made more facial displays in the Shared compared to the Private condition, particularly during the Feedback phase ( Fig. 3 ). It is during the Feedback phase of the Shared condition that participants learn new information about their partner and might also be judged for their own responses. ...
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Citations
... In addition, neural coordination is significantly correlated with verbal [30][31][32][33] and non-verbal [29,34,35] coordination. For example, interpersonal neural coordination is associated with mutual gaze [22,29,36,37], changes in pupil dilation [10,38], postural sway [39], and synchronised breathing and heart rate patterns [10]. Despite these advances, questions remain about the directionality and dynamics of these interdependencies [40]. ...
... Most notably, the mutual prediction model proposed by Mayo and Shamay-Tsoory [41] characterises these dynamics through the computational lens of prediction error minimisation; that is, from a predictive processing framework, individuals align by minimising prediction errors across hierarchical generative models, cascading from low-level predictions of movements to high-level predictions of cognitive representations [41][42][43]. For multimodal data, Hamilton [44] recommends using a general linear model, where one's neural dynamics can be modelled as a (linear) combination of their partner's neural and behavioural data as well as their own behaviour (e.g., [37]). More recently, Gordon and colleagues [45] have introduced an extensive and compelling theory of flexible multimodal synchrony, setting the unit of analysis at the social unit and identifying synchrony as an emergent, holistic organisation of co-occurring changes between interactants across different modalities. ...
Social neuroscience sets out to uncover the neural mechanisms and dynamics of human sociality. Interpersonal coordination on various levels—neural, behavioural, physiological, affective, linguistic— are hallmarks of successful social communication and cooperation. However, describing these complex, interdependent dynamics has been limited by current methodological approaches, owing to a restrictive repertoire of tools and the absence of a unified, standardised methodological framework. Here, we identify information theory, the mathematical theory of communication, as a particularly well-suited conceptual framework to address this shortfall, given its appropriate sensitivity to complex dynamics, including potential nonlinearity and higher-order interactions, and its data-driven approach. Indeed, with its firm grounding in computational, cognitive, and systems neuroscience, the introduction of information-theoretic quantities and methods into social neuroscience is perhaps overdue. This Perspective presents the case for a unified information-theoretic framework to describe and model the complex dynamics of social systems whilst generating new, open research questions.
... Although we expected explain-to-others and explain-to-oneself to cause more brain activity reflective of cognitive processing than the control group, we were particularly interested in the degree to which explain-toothers caused additional brain activity reflecting additional social processing. For example, Schilbach et al. (2013) and Cañigueral et al. (2021) propose that social processing is embodied in brain networks, such that mutual engagement may stimulate additional brain dynamics compared to completing a task alone. Many studies have emphasized that human interaction with others is a major factor in how we learn (Marchiori & Warglien, 2008;Pan et al., 2018Pan et al., , 2020Pan et al., , 2023. ...
Background
Two generative learning activities aimed at improving students' learning are explaining learning materials to oneself or to others. Although these techniques have been shown to improve learning outcomes, there is less evidence concerning the role of brain activity during learning.
Aims
This study explored the effects of these techniques on brain activation patterns (as measured by fNIRS) and learning outcomes (as measured by retention and transfer tests).
Sample and methods
Ninety-nine college students studied a text-based multimedia lesson about the Doppler Effect and then either explained the material to a real person (explain-to-others group, n = 33), explained the material to themselves (explain-to-oneself group, n = 34), or restudied the text (restudy group, n = 32). Students' brain activity during learning was recorded using fNIRS techniques and all students completed retention and transfer posttests and mental effort, presence, and anxiety surveys.
Results
Both the explain-to-others group and the explain-to-oneself group obtained higher scores on retention, mental effort, and state anxiety than the restudy group. The explain-to-others and explain-to-oneself groups also displayed greater activation of brain networks associated with attention, working memory, and metacognitive processing (i.e., the bilateral TPJ and the right OFC). The explain-to-others group outperformed the restudy group on transfer test, social presence ratings, and explanation quality. The explain-to-others group also displayed greater activation in brain networks associated with social processing (the left dlPFC and the left TPJ) compared to the explain-to-oneself group.
Conclusions
This study extended generative learning theory and pointed out the advantage of learning-by-teaching based on neuroscience evidence.
... Our findings confirmed that brain synchronisation was an effective representation of learning processes and outcomes. Previous studies also found that the SMG was associated with receptive functions during communication (Hirsch et al., 2018), and was also involved in the spontaneous production and observation of facial displays during dynamic tasks (Cañigueral et al., 2021). In particular, the left SMG area was found to be associated with phonological changes (Phillips, 2001), and plays an important role in phonological working memory (Obleser and Eisner, 2009). ...
Early STEM education is crucial for later learning. This novel study utilised fNIRS to examine how STEM teaching methods (i.e., traditional, storytelling, storyboarding) affect neural activity synchronisation between teachers and students. Our results showed that left and right inferior frontal gyrus (IFG) for storytelling teaching versus traditional teaching, superior temporal gyrus for storyboard teaching versus traditional teaching, and left angular gyrus for storyboard and storytelling teaching were significant different in brain synchronisation. In the story-telling teaching condition, left supramarginal gyrus brain synchrony was found to improve STEM learning outcomes. In the storyboard teaching condition, IFG brain synchrony correlated positively with STEM learning improvement. The findings confirmed that story-based teaching and storyboarding can improve STEM learning efficacy at the neural level and unscored the significant role of neural synchronization as a predictor of learning outcomes.
... EEG, electroencephalogram. 99 during the mutual sharing of biographical information in a face-toface setting, the spontaneous production and observation of facial displays (eye gaze and facial motion) generates a cross-brain synchrony in different brain areas. As suggested by Krueger, 43 and Fanghella et al., 100 these cross-brain processes may generate a joint space-a ''wespace'' of action and meaning-that supports the interpersonal attunement between partners within the context of the common activity. ...
What distinguishes real-world communities from their online counterparts? Social and cognitive neuroscience research on social networks and collective intentionality will be used in the article to answer this question. Physical communities are born in places. And places engage "we-mode" neurobiological and cognitive processes as behavioral synchrony, shared attention, deliberate attunement, interbrain synchronization, and so on, which create coherent social networks of very different individuals who are supported by a "wisdom of crowd." Digital technologies remove physical boundaries, giving people more freedom to choose their activities and groups. At the same time, however, the lack of physical co-presence of community members significantly reduces their possibility of activating "we-mode" cognitive processes and social motivation. Because of this, unlike physical communities that allow interaction between people from varied origins and stories, digital communities are always made up of people who have the same interests and knowledge (communities of practice). This new situation disrupts the "wisdom of crowd," making the community more radical and less accurate (polarization effect), allowing influential users to wield disproportionate influence over the group's beliefs, and producing inequalities in the distribution of social capital. However, a new emergent technology-the Metaverse-has the potential to reverse this trend. Several studies have revealed that virtual and augmented reality-the major technologies underlying the Metaverse-can engage the same neurobiological and cognitive "we-mode" processes as real-world environments. If the many flaws in this technology are fixed, it might encourage people to engage in more meaningful and constructive interactions in online communities.
... 8 In these tasks, two participants were required to act synchronously; thus, the observed brain synchronization could be interpreted as partially related to simultaneous motor movements. More recent studies have used natural or free settings such as nonstructured verbal communication, 9,10 eye-to-eye contact, 11,12 turn-taking games, 13 and group creativity. 14 Because the target behaviors of these experiments were largely unscheduled, coding works were usually necessary to disentangle the relationship between the target behavior and particular brain synchronization. ...
... Although rarely reported as neural-coupling in the PFC in previous studies, there has been an increase in recent reports of synchronization in the FP 14,41-43 and the DLPFC. 12,14,42,43 These areas are crucial in neural processes of not only attention and executive decision but also theory of mind, 41,44,45 all of which are essential elements for successful communication. The DLPFC is a versatile brain region that contributes to various neural processes, except for its classic functions. ...
... Recent research also discovered synchrony between different channels/ regions. 10,12 Our findings on synchronization between the PFC region of one person and the temporal region of the other person provided further evidence for relatively long-range cross-brain synchrony during social interactions. Cañigueral et al. 12 also found synchronization between the DLPFC of one brain and the rTPJ of the other when participants were involved in an implicit interactive task demanding mentalizing, anticipation, and strategic decisions over each other's choices. ...
Significance:
In hyperscanning studies of natural social interactions, behavioral coding is usually necessary to extract brain synchronizations specific to a particular behavior. The more natural the task is, the heavier the coding effort is. We propose an analytical approach to resolve this dilemma, providing insights and avenues for future work in interactive social neuroscience.
Aim:
The objective is to solve the laborious coding problem for naturalistic hyperscanning by proposing a convenient analytical approach and to uncover brain synchronization mechanisms related to human cooperative behavior when the ultimate goal is highly free and creative.
Approach:
This functional near-infrared spectroscopy hyperscanning study challenged a cooperative goal-free creative game in which dyads can communicate freely without time constraints and developed an analytical approach that combines automated behavior classification (computer vision) with a generalized linear model (GLM) in an event-related manner. Thirty-nine dyads participated in this study.
Results:
Conventional wavelet-transformed coherence (WTC) analysis showed that joint play induced robust between-brain synchronization (BBS) among the hub-like superior and middle temporal regions and the frontopolar and dorsomedial/dorsolateral prefrontal cortex (PFC) in the right hemisphere, in contrast to sparse within-brain synchronization (WBS). Contrarily, similar regions within a single brain showed strong WBS with similar connection patterns during independent play. These findings indicate a two-in-one system for performing creative problem-solving tasks. Further, WTC-GLM analysis combined with computer vision successfully extracted BBS, which was specific to the events when one of the participants raised his/her face to the other. This brain-to-brain synchrony between the right dorsolateral PFC and the right temporo-parietal junction suggests joint functioning of these areas when mentalization is necessary under situations with restricted social signals.
Conclusions:
Our proposed analytical approach combining computer vision and WTC-GLM can be applied to extract inter-brain synchrony associated with social behaviors of interest.
... Interpersonal exercises that involve systematic sharing of personal information by asking and answering a series of intimate questions with another person also increase closeness (Aron et al., 1997). Moreover, sharing biographical information with another person increases activation in brain regions associated with social processing and may lead to cross-brain synchrony (Cañigueral et al., 2021). ...
Introduction
Increasingly, business leaders and other professionals are called upon to be vulnerable and authentic in the workplace, which often includes disclosing emotions to others. While sharing emotions is known to enhance closeness, several questions remain underexplored. Specifically, disclosing personal facts about oneself and disclosing emotions have often been studied together, making it difficult to determine the effects of disclosing emotions per se. Moreover, not enough is known about factors that may influence effects of disclosing emotions, including recipients’ attitudes toward emotion-sharing, the sharer’s gender, and whether one considers the disclosure to be similar to one’s own experiences. We examined the impact of disclosing positive and negative emotion on ratings of closeness, warmth, competence, and leadership ability.
Methods
119 participants (95 female) in the United States were shown headshots of individuals who were introduced in the first person in written format. For half of the pictures, an autobiographical fact about the individual’s past was disclosed. For the other half, an autobiographical fact and an associated emotion were disclosed.
Results
We found that sharing both positive and negative emotions increased feelings of closeness above and beyond the effects of autobiographical sharing alone. Sharing positive emotions also increased ratings of warmth, competence, and leadership ability. Male and female sharers benefited equally from disclosing emotions and effects were largely robust to recipients’ attitudes toward emotional expression. Having something in common with the disclosed fact or emotion further increased all ratings.
Conclusion
These findings indicate that disclosing emotions may improve interpersonal interactions, with potential management applications in business.
... 338,339 Quantification of dyadic properties includes measures of neural coupling, sometimes referred to as inter-brain synchrony or cross-brain coherence, [340][341][342] which quantifies the extent to which the temporal patterns of neural signals across brains are correlated. 321,[343][344][345] The main questions include: What are these dyadic mechanisms? How can they be isolated? ...
... Recent work has demonstrated that the estimation of CrCP using DCS measurements of pulsatile blood flow shows a good correlation with CrCP estimated with TCD measurements of blood flow velocity in the large arteries of both healthy subjects 513 and stroke patients. 345 Moreover, an association between DCS-measured CrCP and intracranial hypertension has been shown in infants with hydrocephalus. 514 In general, noninvasive ICP and CrCP estimation is challenging due to the complex interplay of parameters such as cerebral blood volume, arterial pressure, vascular tone, and compliance, which are usually unknown during the measurement. ...
This report is the second part of a comprehensive two-part series aimed at reviewing an extensive and diverse toolkit of novel methods to explore brain health and function. While the first report focused on neurophotonic tools mostly applicable to animal studies, here, we highlight optical spectroscopy and imaging methods relevant to noninvasive human brain studies. We outline current state-of-the-art technologies and software advances, explore the most recent impact of these technologies on neuroscience and clinical applications, identify the areas where innovation is needed, and provide an outlook for the future directions.
... Recently, an increasing number of studies have presented results based on both HbO and HbR or only on HbR changes (e.g. [42][43][44][45], due to the greater spatial specificity of the HbR 46 and its higher correlation with the blood oxygen level dependent (BOLD) signal acquired during fMRI 47 . These studies revealed different patterns of neural synchronization between HbO-and HbR-based signals. ...
As members of a social species, we spend most of our time interacting with others. In interactions, we tend to mutually align our behavior and brain responses to communicate more effectively. In a semi-computerized version of the Rock-Paper-Scissors game, we investigated whether people show enhanced interpersonal neural synchronization when making explicit predictions about others’ actions. Across four experimental conditions, we measured the dynamic brain activity using the functional near-infrared spectroscopy (fNIRS) hyperscanning method. Results showed that interpersonal neural synchrony was enhanced when participants played the game together as they would do in real life in comparison to when they played the game on their own. We found no evidence of increased neural synchrony when participants made explicit predictions about others’ actions. Hence, neural synchrony may depend on mutual natural interaction rather than an explicit prediction strategy. This study is important, as it examines one of the presumed functions of neural synchronization namely facilitating predictions.
... Previous studies demonstrated that the right temporoparietal junction (RTPJ) not only played an important role in the "social brain" of ASD (Pelphrey et al., 2011;Müeller and Fishman, 2018) but is also involved in higher-order social cognition such as processing the intentions and opinions of others (Wang et al., 2020b), reciprocating face-to-face social interactions (Tang et al., 2016), processing social faces (Kret et al., 2011), and reciprocating interpersonal empathy (Patel et al., 2019;Canigueral et al., 2021). However, the RTPJ cannot perform these social functions alone and needs to cooperate with other brain regions. ...
Social function impairment is the core deficit of autism spectrum disorder (ASD). Although many studies have investigated ASD through a variety of neuroimaging tools, its brain mechanism of social function remains unclear due to its complex and heterogeneous symptoms. The present study aimed to use resting-state functional magnetic imaging data to explore effective connectivity between the right temporoparietal junction (RTPJ), one of the key brain regions associated with social impairment of individuals with ASD, and the whole brain to further deepen our understanding of the neuropathological mechanism of ASD. This study involved 1,454 participants from 23 sites from the Autism Brain Imaging Data Exchange (ABIDE) public dataset, which included 618 individuals with ASD and 836 with typical development (TD). First, a voxel-wise Granger causality analysis (GCA) was conducted with the RTPJ selected as the region of interest (ROI) to investigate the differences in effective connectivity between the ASD and TD groups in every site. Next, to obtain further accurate and representative results, an image-based meta-analysis was implemented to further analyze the GCA results of each site. Our results demonstrated abnormal causal connectivity between the RTPJ and the widely distributed brain regions and that the connectivity has been associated with social impairment in individuals with ASD. The current study could help to further elucidate the pathological mechanisms of ASD and provides a new perspective for future research.
... For instance, by combining mocap and fNIRS to study imitation in a dyadic task, we have recently found that when participants are being watched as they perform an imitation task, there was a decrease in activation of the right parietal region and the right temporal-parietal junction (Krishnan-Barman, 2021). In another study (Cañigueral, Zhang, et al., 2021), we simultaneously recorded pairs of participants (who were facing each other) with eye-tracking, face-tracking, and fNIRS to test how social behaviours and brain activity are modulated when sharing biographical information. Results showed that reciprocal interactions where information was shared recruited brain regions previously linked to reputation management (Izuma, 2012), particularly to mentalizing (temporo-parietal junction; [TPJ]) and strategic decision-making (dorsolateral prefrontal cortex [dlPFC]; Saxe & Kanwisher, 2003;Saxe & Wexler, 2005;Soutschek et al., 2015;Speitel et al., 2019). ...
... Within the social signalling framework, it is necessary to link brain activity patterns to meaningful social signals to fully understand the neurocognitive systems engaged during social interactions. In an exploratory analysis, we investigated how the amount of facial displays is related to brain activity in face-to-face interactions (Cañigueral, Zhang, et al., 2021). We found that spontaneous production of facial displays (i.e., participants moving their own face) recruited the left supramarginal gyrus, whereas spontaneous observation of facial displays (i.e., participants seeing their partner move the face) recruited the right dlPFC. ...
... In combination with eye-tracking systems, it has also been shown that cross-brain synchrony between partners increases during moments of mutual eye contact (Hirsch et al., 2017;Leong et al., 2017;Piazza et al., 2020). To further test which specific aspects of social signalling are modulated by cross-brain synchrony, we combined behavioural and neural dyadic recordings with a novel analytical approach that carefully controls for task-and behaviourrelated effects (cross-brain GLM; Kingsbury et al., 2019;Cañigueral, Zhang, et al., 2021). We found that, after controlling for task structure and social behaviours, cross-brain synchrony between mentalizing (right TPJ) and strategic decision-making regions (left dlPFC) increased when participants were sharing information. ...
Despite the recent increase in second-person neuroscience research, it is still hard to understand which neurocognitive mechanisms underlie real-time social behaviours. Here, we propose that social signalling can help us understand social interactions both at the single- and two-brain level in terms of social signal exchanges between senders and receivers. First, we show how subtle manipulations of being watched provide an important tool to dissect meaningful social signals. We then focus on how social signalling can help us build testable hypotheses for second-person neuroscience with the example of imitation and gaze behaviour. Finally, we suggest that linking neural activity to specific social signals will be key to fully understand the neurocognitive systems engaged during face-to-face interactions.
