Interpersonal physiological synchrony (IPS)-the temporal alignment of autonomic physiological signals-is emerging as a prominent feature of social interaction. IPS can predict complex social phenomena such as relationship quality or social bonding. Yet, the origins of IPS remain poorly understood. Here, we investigated whether and how IPS can emerge spontaneously through mere visual contact. Thirty-eight dyads of familiar participants were asked to face each other without speaking or making coverbal gestures. IPS was measured using four autonomic signals-heart rate, skin conductance, respiration rate, and pupil diameter-and quantified as the Pearson correlation between dyad members' signals. We found that visual contact was sufficient to synchronize all physiological signals in real dyads, compared with chance-level synchrony in surrogate dyads. Notably, heart rate and pupil diameter IPS were particularly vision-dependent, showing significant reductions when visual contact was prevented. Furthermore, examining the link between IPS and spontaneous social cues revealed that heart rate IPS co-occurred with synchronized body movements, whereas pupil diameter IPS co-occurred with synchronized smiling. These findings show that IPS can emerge spontaneously through mere visual contact and is linked to the exchange of social cues. They position IPS as a robust, self-organizing phenomenon that occurs naturally in social interactions.

Humans across cultures not only share the ability to recognise music but also respond to it through movement. While the sensory encoding of music is well-studied, when and how infants naturally start moving to music is largely unexplored. This study simultaneously investigates infants’ neural (auditory) responses and spontaneous movements to music during the first postnatal year. Neural activity (EEG) and body kinematics (markerless pose estimation) were recorded from 79 infants (aged 3, 6, and 12 months) listening to refrains of children’s music, along with shuffled, high-pitched, and low-pitched versions of the same songs. Neural data revealed that, across all ages, infants exhibit enhanced auditory responses to music compared to shuffled music, indicating that auditory encoding of music emerges early in development. Movement data revealed a different outcome. While coarse auditory-motor coupling is present at all ages, more complex structured movement patterns emerge in response to music only by 12 months. Notably, no age group demonstrated evidence of coordinated movements to music. Additionally, enhanced auditory responses to high vs low pitch were only evident at 6 months, while infants’ movements were better predicted by high-pitched compared to low-pitched music at all ages. This study provides initial insights into how the developing brain gradually transforms music into spontaneous movements of increasing complexity.

Estimating how the human body moves in space and time—body kinematics—has important applications for industry, healthcare, and several research fields. Gold-standard methodologies capturing body kinematics are expensive and impractical for naturalistic recordings as they rely on infrared-reflective wearables and bulky instrumentation. To overcome these limitations, several algorithms have been developed to extract body kinematics from plain video recordings. This comes with a drop in accuracy, which however has not been clearly quantified. To fill this knowledge gap, we analysed a dataset comprising 46 human participants exhibiting spontaneous movements of varying amplitude. Body kinematics were estimated using OpenPose (video-based) and Vicon (infrared-based) motion capture systems simultaneously. OpenPose accuracy was assessed using Vicon estimates as ground truth. We report that OpenPose accuracy is overall moderate and varies substantially across participants and body parts. This is explained by variability in movement amplitude. OpenPose estimates are weak for low-amplitude movements. Conversely, large-amplitude movements (i.e., > 10 cm) yield highly accurate estimates. The relationship between accuracy and movement amplitude is not linear (but mostly exponential or power) and relatively robust to camera–body distance. Together, these results dissect the limits of video-based motion capture and provide useful guidelines for future studies.

Emotions drive and influence social interactions. Actions and reactions driven by emotions are dynamically modulated by continuous feedback loops between all interacting subjects. In this framework, interacting brains operate as an integrated system, with neural dynamics coevolving over time. Neuronal synchronization across brains has been observed in a range of species, including humans, monkeys, bats, and mice. This inter-neural synchrony (INS) has been proposed as a potential mechanism facilitating social interaction by enabling the functional integration of multiple brains. However, the role of emotions in modulating these processes remains underexplored and warrants further investigation. Here we provide a brief overview of studies on inter-neural synchrony in humans and other species, emphasizing the critical role that emotions might play in shaping multibrain dynamics.

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

Interpersonal movement synchrony (IMS) is central to social behavior in several species. In humans, IMS is typically studied using structured tasks requiring participants to produce specific body movements. Instead, spontaneously generated (i.e., not instructed) movements have received less attention. To test whether spontaneous movements synchronize interpersonally, we recorded full-body kinematics from dyads of participants who were only asked to sit face-to-face and to look at each other. We manipulated interpersonal (i) visual contact and (ii) spatial proximity. We found that spontaneous movements synchronized across participants only when they could see each other and regardless of interpersonal spatial proximity. This synchronization emerged very rapidly and did not selectively entail homologous body parts (as in mimicry); rather, the synchrony generalized to nearly all possible combinations of body parts. Hence, spontaneous behavior alone can lead to IMS. More generally, our results highlight that IMS can be studied under natural and unconstrained conditions.

The ability to understand other people’s intentions by observing their actions is crucial to interpret and anticipate their behavior. However, the specific neural computations involved in this ability remain unclear and causally untested. One major reason is the difficulty of identifying intention readout patterns associated with ever-changing kinematic features. Movement is “repetition without repetition”. Statistical analyses averaging across trials can blur away how intention information encoded in single trial variations is readout in real-time. Here we developed a novel approach combining motion tracking with continuous theta burst stimulation (cTBS) and new computational analyses to determine how the transient disruption of a target region – the left inferior parietal lobule (IPL) – influences intention readout computations with single-trial resolution. In separate sessions, participants received neuronavigation-guided cTBS to the left IPL or the left Inferior frontal gyrus (IFG) before completing a two-alternative, forced-choice visual discrimination of intention. Single-trial analyses combined with a set of task manipulations revealed that cTBS to the left IPL, but not to left IFG, selectively impaired the ability to infer the intention of an observed action from variations in visual kinematics. Importantly, IPL cTBS did not interfere with the ability to ‘see’ changes in movement kinematics, nor did it alter the weight given to informative versus non-informative kinematic features. Rather, it selectively impaired the ability to link variations in informative features to the correct intention. These results support a model in which the selection of the most informative kinematic feature occurs outside of the left IPL and in which the left IPL is selectively responsible for the correct readout of such features.

Professional magicians regularly use pantomimed grasps (i.e., movements towards imagined objects) to deceive audiences. To do so, they learn to shape their hands similarly for real and pantomimed grasps. Here we tested whether this form of motor expertise provides them a significant benefit when processing pantomimed grasps. To this aim, in a one-interval discrimination design, we asked 17 professional magicians and 17 naïve controls to watch video clips of reach-to-grasp movements recorded from naïve participants and judge whether the observed movement was real or pantomimed. All video clips were edited to spatially occlude the grasped object (either present or imagined). Data were analysed within a drift diffusion model approach. Fitting different models showed that, whereas magicians and naïve performed similarly when observing real grasps, magicians had a specific advantage compared with naïve at discriminating pantomimed grasps. These findings suggest that motor expertise may be crucial for detecting relevant cues from hand movement during the discrimination of pantomimed grasps. Results are discussed in terms of motor recalibration.

Although it is well established that fronto-parietal regions are active during action observation, whether they play a causal role in the ability to infer others' intentions from visual kinematics remains undetermined. In the experiments reported here, we combined offline continuous theta burst stimulation (cTBS) with computational modeling to reveal and causally probe single-trial computations in the inferior parietal lobule (IPL) and inferior frontal gyrus (IFG). Participants received cTBS over the left anterior IPL and the left IFG pars orbitalis in separate sessions before completing an intention discrimination task (discriminate intention of observed reach-to-grasp acts) or a kinematic discrimination task unrelated to intention (discriminate peak wrist height of the same acts). We targeted intention-sensitive regions whose fMRI activity, recorded when observing the same reach-to-grasp acts, could accurately discriminate intention. We found that transient disruption of activity of the left IPL, but not the IFG, impaired the observer's ability to attribute intention to action. Kinematic discrimination unrelated to intention, in contrast, was largely unaffected. Computational analyses of how encoding (mapping of intention to movement kinematics) and readout (mapping of kinematics to intention choices) intersect at the single-trial level revealed that IPL cTBS did not diminish the overall sensitivity of intention readout to movement kinematics. Rather, it selectively misaligned intention readout with respect to encoding, deteriorating mapping from informative kinematic features to intention choices. These results provide causal evidence of how the left anterior IPL computes mapping from kinematics to intentions.

Although it is well established that fronto-parietal regions are active during action observation, whether they play a causal role in the ability to “mindread” others’ actions remains controversial. In experiments reported here, we combined offline continuous theta-burst stimulation (cTBS) with computational modeling to reveal single-trial computations in the inferior parietal lobule (IPL) and inferior frontal gyrus (IFG). Participants received cTBS over the left IPL and IFG, in separate sessions, before completing an intention discrimination task or a kinematic discrimination task unrelated to intention. We found that transient disruption of activity of the IPL, but not the IFG, specifically impaired the observer’s ability to judge intention from movement kinematics. Kinematic discrimination unrelated to intention, in contrast, was largely unaffected. Computational analyses revealed that IPL cTBS did not impair the ability to ‘see’ changes in movement kinematics, nor did it alter the weight given to informative versus non-informative kinematic features. Rather, it selectively impaired the ability to link variations in informative features to the correct intention. These results provide the first causal evidence that IPL maps kinematics to intentions.

Seeing a person perform an action activates the observer's motor system. The present study aimed at investigating the temporal relationship between execution and observation of goal-directed actions. One possibility is that the corticospinal excitability (CSE) follows the dynamic evolution of the pattern of muscle activity in the executed action. Alternatively, CSE may anticipate the future course of the observed action, prospectively extrapolating future states. Our study was designed to test these alternative hypotheses by directly comparing the time course of muscle recruitment during the execution and observation of reach-to-grasp movements. We found that the time course of CSE during action observation followed the time course of the EMG signal during action execution. This contingent coding was observed despite the outcome of the observed motor act being predictable from the earliest phases of the movement. These findings challenge the view that CSE serves to predict the target of an observed action.

Can social gaze behavior reveal the leader during real-world group interactions? To answer this question, we developed a novel tripartite approach combining (1) computer vision methods for remote gaze estimation, (2) a detailed taxonomy to encode the implicit semantics of multi-party gaze features, and (3) machine learning methods to establish dependencies between leadership and visual behaviors. We found that social gaze behavior distinctively identified group leaders. Crucially, the relationship between leadership and gaze behavior generalized across democratic and autocratic leadership styles under conditions of low and high time-pressure, suggesting that gaze can serve as a general marker of leadership. These findings provide the first direct evidence that group visual patterns can reveal leadership across different social behaviors and validate a new promising method for monitoring natural group interactions.

OPINION article Front. Psychol., 02 July 2018Sec. Quantitative Psychology and Measurement Volume 9 - 2018 | https://doi.org/10.3389/fpsyg.2018.01117

Interpersonal predictive coding (IPPC) describes the behavioral phenomenon whereby seeing a communicative rather than an individual action helps to discern a masked second agent. As little is known, yet, about the neural correlates of IPPC, we conducted a functional magnetic resonance imaging study in a group of 27 healthy participants using point-light displays of moving agents embedded in distractors. We discovered that seeing communicative compared to individual actions was associated with higher activation of right superior frontal gyrus, whereas the reversed contrast elicited increased neural activation in an action observation network that was activated during all trials. Our findings, therefore, potentially indicate the formation of action predictions and a reduced demand for executive control in response to communicative actions. Further, in a regression analysis, we revealed that increased perceptual sensitivity was associated with a deactivation of the left amygdala during the perceptual task. A consecutive psychophysiological interaction analysis showed increased connectivity of the amygdala with medial prefrontal cortex in the context of communicative compared to individual actions. Thus, whereas increased amygdala signaling might interfere with task-relevant processes, increased co-activation of the amygdala and the medial prefrontal cortex in a communicative context might represent the integration of mentalizing computations.

Expectations facilitate perception of expected stimuli but may hinder perception of unexpected alternatives. Here, we consider how prior expectations about others' intentions are integrated with visual kinematics over time in detecting the intention of an observed motor act (grasp-to-pour vs. grasp-to-drink). Using rigorous psychophysics methods, we find that the processes of ascribing intentions to others are well described by drift diffusion models in which evidence from observed movements is accumulated over time until a decision threshold is reached. Testing of competing models revealed that when kinematics contained no discriminative intention information, prior expectations predicted the intention choice of the observer. When kinematics contained intention information, kinematics predicted the intention choice. These findings provide evidence for a diffusion process in which the influence of expectations is modulated by movement informativeness and informative kinematics can override initial expectations.

Mirror neurons have been proposed to underlie humans’ ability to understand others’ actions and intentions. Despite 2 decades of research, however, the exact computational and neuronal mechanisms implied in this ability remain unclear. In the current study, we investigated whether, in the absence of contextual cues, regions considered to be part of the human mirror neuron system represent intention from movement kinematics. A total of 21 participants observed reach-to-grasp movements, performed with either the intention to drink or to pour while undergoing functional magnetic resonance imaging. Multivoxel pattern analysis revealed successful decoding of intentions from distributed patterns of activity in a network of structures comprising the inferior parietal lobule, the superior parietal lobule, the inferior frontal gyrus, and the middle frontal gyrus. Consistent with the proposal that parietal regions play a key role in intention understanding, classifier weights were higher in the inferior parietal region. These results provide the first demonstration that putative mirror neuron regions represent subtle differences in movement kinematics to read the intention of an observed motor act.