Evidence of embodied social competence during conversation in high functioning children with autism spectrum disorder

From unimodal to multimodal dynamics of verbal and nonverbal cues during unstructured conversation

Conversations encompass continuous exchanges of verbal and nonverbal information. Previous research has demonstrated that gestures dynamically entrain each other and that speakers tend to align their vocal properties. While gesture and speech are known to synchronize at the intrapersonal level, few studies have investigated the multimodal dynamics of gesture/speech between individuals. The present study aims to extend our comprehension of unimodal dynamics of speech and gesture to multimodal speech/gesture dynamics. We used an online dataset of 14 dyads engaged in unstructured conversation. Speech and gesture synchronization was measured with cross-wavelets at different timescales. Results supported previous research on intrapersonal speech/gesture coordination, finding synchronization at all timescales of the conversation. Extending the literature, we also found interpersonal synchronization between speech and gesture. Given that the unimodal and multimodal synchronization occurred at similar timescales, we suggest that synchronization likely depends on the vocal channel, particularly on the turn-taking dynamics of the conversation.

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.

Social motor synchrony in autism spectrum conditions: A systematic review

LAY ABSTRACT

When two people interact, they often fall into sync with one another by moving their bodies at the same time. Some say autistic people are not as good as non-autistic people at moving at the same time as a partner. This has led some researchers to ask whether measuring synchrony might help diagnose autism. We reviewed the research so far to look at differences in Social Motor Synchrony (SMS) (the way we move together) between autistic people and people they interact with. The research suggests that interactions involving an autistic partner (either two autistic partners, or an autistic and non-autistic partner) show lower synchrony than a non-autistic pair. However, we recognised elements in the research so far that may have affected SMS in interactions involving an autistic person. One way SMS may have been affected in research so far might be the way interactions have been set up in the research studies. Few papers studied interactions between two autistic people or looked at synchrony in comfortable environments with autistic-preferred tasks. The studies also do not explain why synchrony might be different, or weaker, in pairs involving autistic partners. We use these limitations to suggest improvements for future research.

Smiling synchronization predicts interaction enjoyment in peer dyads of autistic and neurotypical youth

LAY ABSTRACT

For autistic and neurotypical youth, having positive social interactions with other youth is an important part of well-being. Other researchers have found that one factor that can make people feel like social interactions have gone well is synchronization. Synchronization happens when peoples' body movements and facial expressions align while they're interacting. We focus on smiling synchronization here because other studies have found that when neurotypical individuals synchronize their smiles more in a social interaction, they say they enjoy that social interaction more. However, no studies have directly tested whether smiling synchrony influences social interaction enjoyment in autistic and neurotypical youth. We measured smiling synchrony in pairs of interacting autistic and neurotypical youth who were meeting each other for the first time. Some pairs were autistic youth interacting with other autistic youth (autistic with autistic participant pairs), some pairs were autistic youth interacting with neurotypical youth (autistic with neurotypical participant pairs), and other pairs were neurotypical youth interacting with neurotypical youth (neurotypical with neurotypical participant pairs). We found that autistic with neurotypical participant pairs had lower smiling synchrony than neurotypical with neurotypical participant pairs. Youth who were in dyads that had more smiling synchrony said they enjoyed interacting with their partner more and that they wanted to interact with their partner again. Our research shows that smiling synchrony is one part of interactions between autistic and neurotypical youth that influences how well youth say the interaction went. Identifying natural opportunities for autistic and neurotypical youth to share positive feelings could be one way to promote positive social interactions between autistic and neurotypical youth.

Social interaction links active musical rhythm engagement and expressive communication in autistic toddlers

Rhythm is implicated in both social and linguistic development. Rhythm perception and production skills are also key vulnerabilities in neurodevelopmental disorders such as autism which impact social communication. However, direct links between musical rhythm engagement and expressive communication in autism is not clearly evident. This absence of a direct connection between rhythm and expressive communication indicates that the mechanism of action between rhythm and expressive communication may recruit other cognitive or developmental factors. We hypothesized that social interactions, including general interpersonal relationships and interactive music-making involving children and caregivers, were a significant such factor, particularly in autism. To test this, we collected data from parents of autistic and nonautistic children 14-36 months of age, including parent reports of their children's rhythmic musical engagement, general social skills, parent-child musical interactions, and expressive communication skills. Path analysis revealed a system of independent, indirect pathways from rhythmic musical engagement to expressive communication via social skills and parent-child musical interactions in autistic toddlers. Such a system implies both that social and musical interactions represent crucial links between rhythm and language and that different kinds of social interactions play parallel, independent roles linking rhythmic musical engagement with expressive communication skills.

Motor differences in autism during a human-robot imitative gesturing task

BACKGROUND

Difficulty with imitative gesturing is frequently observed as a clinical feature of autism. Current practices for assessment of imitative gesturing ability-behavioral observation and parent report-do not allow precise measurement of specific components of imitative gesturing performance, instead relying on subjective judgments. Advances in technology allow researchers to objectively quantify the nature of these movement differences, and to use less socially stressful interaction partners (e.g., robots). In this study, we aimed to quantify differences in imitative gesturing between autistic and neurotypical development during human-robot interaction.

METHODS

Thirty-five autistic (n = 19) and neurotypical (n = 16) participants imitated social gestures of an interactive robot (e.g., wave). The movements of the participants and the robot were recorded using an infrared motion-capture system with reflective markers on corresponding head and body locations. We used dynamic time warping to quantify the degree to which the participant's and robot's movement were aligned across the movement cycle and work contribution to determine how each joint angle was producing the movements.

FINDINGS

Results revealed differences between autistic and neurotypical participants in imitative accuracy and work contribution, primarily in the movements requiring unilateral extension of the arm. Autistic individuals imitated the robot less accurately and used less work at the shoulder compared to neurotypical individuals.

INTERPRETATION

These findings indicate differences in autistic participants' ability to imitate an interactive robot. These findings build on our understanding of the underlying motor control and sensorimotor integration mechanisms that support imitative gesturing in autism which may aid in identifying appropriate intervention targets.

Conversational adaptation in children and teens with autism: Differences in talkativeness across contexts

Successful social communication is complex; it relies on effectively deploying and continuously revising one's behavior to fit the needs of a given conversation, partner, and context. For example, a skilled conversationalist may instinctively become less talkative with a quiet partner and more talkative with a chattier one. Prior research suggests that behavioral flexibility across social contexts can be a particular challenge for individuals with autism spectrum condition (ASC), and that difficulty adapting to the changing needs of a conversation contributes to communicative breakdowns and poor social outcomes. In this study, we examine whether reduced conversational adaptation, as measured by talkativeness, differentiates 48 verbally fluent children and teens with ASC from 50 neurotypical (NT) peers matched on age, intelligence quotient, and sex ratio. Participants completed the Contextual Assessment of Social Skills with two novel conversation partners. The first acted interested in the conversation and talked more (Interested condition), while the second acted bored and talked less (Bored condition). Results revealed that NT participants emulated their conversation partner's behavior by being more talkative in the Interested condition as compared to the Bored condition (z = 9.92, p < 0.001). In contrast, the ASC group did not differentially adapt their behavior to the Bored versus Interested context, instead remaining consistently talkative in both (p = 0.88). The results of this study have implications for understanding social communication and behavioral adaptation in ASC, and may be valuable for clinicians interested in improving conversational competence in verbally fluent individuals with autism. LAY SUMMARY: Social communication-including everyday conversations-can be challenging for individuals on the autism spectrum. In successful conversations, people tend to adjust aspects of their language to be more similar to their partners'. In this study, we found that children and teens with autism did not change their own talkativeness in response to a social partner who was more or less talkative, whereas neurotypical peers did. These findings have clinical implications for improving conversational competence in verbally fluent individuals with autism.

Early Onset of Impairments of Interpersonal Motor Synchrony in Preschool-Aged Children with Autism Spectrum Disorder

Characteristics of interpersonal motor synchrony in individuals with autism spectrum disorder (ASD) have been investigated only in older children and adolescents, which calls for investigations in younger samples. The interpersonal motor synchrony was compared between preschool-aged children with (n = 23) and without ASD (n = 24) during free plays with familiar teachers. Children with ASD exhibited reduced synchrony of the upper body and trunk compared with typically developing (TD) children. Moreover, the degree of synchrony in ASD group was not above than chance. For autistic children, interpersonal motor synchrony was negatively correlated with aspects of autistic traits. The results suggest that the impairment of interpersonal motor synchrony has an onset earlier than school age and is a potential pathway for understanding autistic traits.

The Bidirectional Social-Cognitive Mechanisms of the Social-Attention Symptoms of Autism

Differences in social attention development begin to be apparent in the 6th to 12th month of development in children with Autism Spectrum Disorder (ASD) and theoretically reflect important elements of its neurodevelopmental endophenotype. This paper examines alternative conceptual views of these early social attention symptoms and hypotheses about the mechanisms involved in their development. One model emphasizes mechanism involved in the spontaneous allocation of attention to faces, or social orienting. Alternatively, another model emphasizes mechanisms involved in the coordination of attention with other people, or joint attention, and the socially bi-directional nature of its development. This model raises the possibility that atypical responses of children to the attention or the gaze of a social partner directed toward themselves may be as important in the development of social attention symptoms as differences in the development of social orienting. Another model holds that symptoms of social attention may be important to early development, but may not impact older individuals with ASD. The alterative model is that the social attention symptoms in infancy (social orienting and joint attention), and social cognitive symptoms in childhood and adulthood share common neurodevelopmental substrates. Therefore, differences in early social attention and later social cognition constitute a developmentally continuous axis of symptom presentation in ASD. However, symptoms in older individuals may be best measured with in vivo measures of efficiency of social attention and social cognition in social interactions rather than the accuracy of response on analog tests used in measures with younger children. Finally, a third model suggests that the social attention symptoms may not truly be a symptom of ASD. Rather, they may be best conceptualized as stemming from differences domain general attention and motivation mechanisms. The alternative argued for here that infant social attention symptoms meet all the criteria of a unique dimension of the phenotype of ASD and the bi-directional phenomena involved in social attention cannot be fully explained in terms of domain general aspects of attention development.

Biomarkers Based on Comprehensive Hierarchical EEG Coherence Analysis: Example Application to Social Competence in Autism (Preliminary Results)

Electroencephalography (EEG) coherence analysis, based on measurement of synchronous oscillations of neuronal clusters, has been used extensively to evaluate functional connectivity in brain networks. EEG coherence studies have used a variety of analysis variables (e.g., time and frequency resolutions corresponding to the analysis time period and frequency bandwidth), regions of the brain (e.g., connectivity within and between various cortical lobes and hemispheres) and experimental paradigms (e.g., resting state with eyes open or closed; performance of cognitive tasks). This variability in study designs has resulted in difficulties in comparing the findings from different studies and assimilating a comprehensive understanding of the underlying brain activity and regions with abnormal functional connectivity in a particular disorder. In order to address the variability in methods across studies and to facilitate the comparison of research findings between studies, this paper presents the structure and utilization of a comprehensive hierarchical electroencephalography (EEG) coherence analysis that allows for formal inclusion of analysis duration, EEG frequency band, cortical region, and experimental test condition in the computation of the EEG coherences. It further describes the method by which this EEG coherence analysis can be utilized to derive biomarkers related to brain (dys)function and abnormalities. In order to document the utility of this approach, the paper describes the results of the application of this method to EEG and behavioral data from a social synchrony paradigm in a small cohort of adolescents with and without Autism Spectral Disorder.

Excessive and less complex body movement in children with autism during face-to-face conversation: An objective approach to behavioral quantification

The majority of existing studies investigating characteristics of overt social behavior in individuals with autism spectrum disorder (ASD) relied on informants' evaluation through questionnaires and behavioral coding techniques. As a novelty, this study aimed to quantify the complex movements produced during social interactions in order to test differences in ASD movement dynamics and their convergence, or lack thereof, during social interactions. Twenty children with ASD and twenty-three children with typical development (TD) were videotaped while engaged in a face-to-face conversation with an interviewer. An image differencing technique was utilized to extract the movement time series. Spectral analyses were conducted to quantify the average power of movement, and the fractal scaling of movement. The degree of complexity matching was calculated to capture the level of behavioral coordination between the interviewer and children. Results demonstrated that the average power was significantly higher (p < 0.01), and the fractal scaling was steeper (p < 0.05) in children with ASD, suggesting excessive and less complex movement as compared to the TD peers. Complexity matching occurred between children and interviewers, but there was no reliable difference in the strength of matching between the ASD and TD children. Descriptive trends in the interviewer's behavior suggest that her movements adapted to match both ASD and TD movements equally well. The findings of our study might shed light on seeking novel behavioral markers of ASD, and on developing automatic ASD screening techniques during daily social interactions.

The Mirroring Dance: Synchrony and Interaction Quality of Five Adolescents and Adults on the Autism Spectrum in Dance/Movement Therapy

Background: Individuals on the autism spectrum are often described as having atypical social interactions. Ideally, interactional synchrony helps any interaction flow smoothly with each individual responding verbally, non-verbally, and/or emotionally within a short timeframe. Differences in interactional synchrony may impact how individuals on the autism spectrum experience social encounters. Method: This mixed methods pilot study examined interactional synchrony in five cases of adolescents and adults on the autism spectrum through secondary analysis of video of the participants in movement-based mirroring tasks during dance/movement therapy. Raters described the movement and interactions of the participants while they were leading and following mirroring and engaged in open-ended free dances with a partner. Videos were also scored on measures of affective engagement, flow of the interaction, and synchrony. Results: One of the most striking findings of this study was the difference between engagement in the instructions of the task and engagement with the partner: participants often followed the instructions for the mirroring tasks with little further social engagement with their partner. When participants did engage in moments of social initiation, attunement to the partner, and interactive behaviors, these did not develop into longer interactions. A paired t-test of the correlation coefficients for each participant showed that scores on synchrony and affective engagement were more strongly positively correlated in the less structured open-ended dance and in video clips of interactive behaviors, than in the videos of simply leading or following mirroring. Synchrony was also significantly more strongly positively correlated with the observed flow of the interaction than with observed affective engagement. With the small sample size, however, most of the correlation coefficients were not significant and should be tested on a larger sample. Discussion: Interpersonal synchrony may not be sufficient to effectively support social engagement when individuals on the autism spectrum simply follow instructions to synchronize their movements. Synchrony-based interventions may therefore need to include more complex open-ended social scenarios as interactional synchrony may then be more correlated with perceived interaction quality. Therapists may also need to partner with participants to model using non-verbal social behaviors to develop interactions within mirroring tasks.

Shifts in Behavioral Synchrony in Response to an Interaction Partner's Distress in Adolescents With and Without ASD

Individuals with Autism spectrum disorder (ASD) show altered behavioral synchrony and empathic behavior. Yet, an ecologically valid examination of these in adolescents is still required. We employed a social interaction sequence comprising a friendly conversation with a confederate, an expression of distress by her, and a return to friendly conversation. 44 male adolescents (22 with ASD) participated. Socio-emotional behaviors, coded by blind raters and through automated analyses of motion, were analyzed. Results indicated reduced synchrony in the ASD group. Moreover, whereas controls displayed a decrease in synchrony when facing another's distress, adolescents with ASD showed no such change. No group differences were found on empathic behavior. Findings imply gaps between verbal and non-verbal responses of adolescents with ASD to a distressed interaction partner.

Motor Skill Differences in Autism Spectrum Disorder: a Clinically Focused Review

PURPOSE OF REVIEW

This review synthesizes recent, clinically relevant findings on the scope, significance, and centrality of motor skill differences in autism spectrum disorder (ASD).

RECENT FINDINGS

Motor challenges in ASD are pervasive, clinically meaningful, and highly underrecognized, with up to 87% of the autistic population affected but only a small percentage receiving motor-focused clinical care. Across development, motor differences are associated with both core autism symptoms and broader functioning, though the precise nature of those associations and the specificity of motor profiles to ASD remain unestablished. Findings suggest that motor difficulties in ASD are quantifiable and treatable, and that detection and intervention efforts targeting motor function may also positively influence social communication. Recent evidence supports a need for explicit recognition of motor impairment within the diagnostic framework of ASD as a clinical specifier. Motor differences in ASD warrant greater clinical attention and routine incorporation into screening, evaluation, and treatment planning.

Resilience in Development and Psychopathology: Multisystem Perspectives

Resilience science in psychology and related fields emerged from clinical research on risk for psychopathology in the 1970s and matured over the ensuing decades with advances in theory, methods, and knowledge. Definitions and models of resilience shifted to reflect the expanding influence of developmental systems theory and the growing need to integrate knowledge about resilience across levels and disciplines to address multisystem threats. Resilience is defined for scalability and integrative purposes as the capacity of a dynamic system to adapt successfully through multisystem processes to challenges that threaten system function, survival, or development. Striking alignment of resilience factors observed in human systems, ranging from individuals to communities, suggests the possibility of networked, multisystem protective factors that work in concert. Evidence suggests that there may be resilience factors that provide transdiagnostic protection against the effects of adverse childhood experiences on risk for psychopathology. Multisystem studies of resilience offer promising directions for future research and its applications to promote mental health and positive development in children and youth at risk for psychopathology.

The quantification of gesture-speech synchrony: A tutorial and validation of multimodal data acquisition using device-based and video-based motion tracking

There is increasing evidence that hand gestures and speech synchronize their activity on multiple dimensions and timescales. For example, gesture’s kinematic peaks (e.g., maximum speed) are coupled with prosodic markers in speech. Such coupling operates on very short timescales at the level of syllables (200 ms), and therefore requires high-resolution measurement of gesture kinematics and speech acoustics. High-resolution speech analysis is common for gesture studies, given that field’s classic ties with (psycho)linguistics. However, the field has lagged behind in the objective study of gesture kinematics (e.g., as compared to research on instrumental action). Often kinematic peaks in gesture are measured by eye, where a “moment of maximum effort” is determined by several raters. In the present article, we provide a tutorial on more efficient methods to quantify the temporal properties of gesture kinematics, in which we focus on common challenges and possible solutions that come with the complexities of studying multimodal language. We further introduce and compare, using an actual gesture dataset (392 gesture events), the performance of two video-based motion-tracking methods (deep learning vs. pixel change) against a high-performance wired motion-tracking system (Polhemus Liberty). We show that the videography methods perform well in the temporal estimation of kinematic peaks, and thus provide a cheap alternative to expensive motion-tracking systems. We hope that the present article incites gesture researchers to embark on the widespread objective study of gesture kinematics and their relation to speech.

Interactional Synchrony and Its Association with Social and Communication Ability in Children With and Without Autism Spectrum Disorder

Social partners tend to coordinate their behaviors in time. This "interactional synchrony" is associated with a host of positive social outcomes, making it ripe for study in autism spectrum disorder (ASD). Twenty children with ASD and 17 typically developing (TD) children participated in conversations with familiar and unfamiliar adults. Conversations were rated for movement synchrony and verbal synchrony, and mothers completed measures regarding children's everyday social and communication skills. Children with ASD exhibited less interactional synchrony, with familiar and unfamiliar partners, than TD peers. Beyond group-level differences, interactional synchrony negatively correlated with autism symptom severity, and predicted dimensional scores on established social and communication measures. Results suggest that disrupted interactional synchrony may be associated with impaired social functioning in ASD.

Language Growth in Young Children with Autism: Interactions Between Language Production and Social Communication

Young children with autism spectrum disorder (ASD) present with a broad range of spoken language abilities, as well as delays in precursor skills such as gesture production and joint attention skills. While standardized assessments describe language strengths, the Communication and Symbolic Behavior Scales (CSBS-DP) is a particularly robust measure as it additionally characterizes precise aspects of social communication. This study provides a unique contribution by assessing the interactional effects of CSBS-DP Social Composite performance with early language samples on later language outcomes. Our results indicate that multiple social communication elements significantly interact with early spoken language to predict later language. Our findings also highlight the transactional relationship between early spoken vocabulary and social communication skills that bolster language development growth.

Entrainment and Modulation of Gesture-Speech Synchrony Under Delayed Auditory Feedback

Gesture–speech synchrony re‐stabilizes when hand movement or speech is disrupted by a delayed feedback manipulation, suggesting strong bidirectional coupling between gesture and speech. Yet it has also been argued from case studies in perceptual–motor pathology that hand gestures are a special kind of action that does not require closed‐loop re‐afferent feedback to maintain synchrony with speech. In the current pre‐registered within‐subject study, we used motion tracking to conceptually replicate McNeill's (1992) classic study on gesture–speech synchrony under normal and 150 ms delayed auditory feedback of speech conditions (NO DAF vs. DAF). Consistent with, and extending McNeill's original results, we obtain evidence that (a) gesture‐speech synchrony is more stable under DAF versus NO DAF (i.e., increased coupling effect), (b) that gesture and speech variably entrain to the external auditory delay as indicated by a consistent shift in gesture‐speech synchrony offsets (i.e., entrainment effect), and (c) that the coupling effect and the entrainment effect are co‐dependent. We suggest, therefore, that gesture–speech synchrony provides a way for the cognitive system to stabilize rhythmic activity under interfering conditions.

Interpersonal Synchrony in Autism

PURPOSE OF REVIEW

We review evidence for the presence, quality, and correlates of interpersonal synchrony in autism spectrum disorder (ASD) across four domains: motor, conversational, physiological, and neural. We also propose cognitive and neural mechanisms for the disruption of interpersonal synchrony and investigate synchrony as a mechanism of intervention in ASD.

RECENT FINDINGS

Across domains, synchrony is present but reduced or atypical in individuals with ASD during interactions with individuals with typical development (TD). Atypical synchrony may reflect the contribution of both intrapersonal mechanisms, such as atypical motor timing, and interpersonal mechanisms, such as atypical interindividual coupling. Research suggests evidence for synchrony interventions leading to improvements in some aspects of social behavior. Understanding synchrony in ASD has the potential to lead to biomarkers and interventions to support social functioning. However, further research should clarify mechanisms of atypical synchrony in ASD including taking features of the dyad into account.

Reduced nonverbal interpersonal synchrony in autism spectrum disorder independent of partner diagnosis: a motion energy study

BACKGROUND

One of the main diagnostic features of individuals with autism spectrum disorders is nonverbal behaviour difficulties during naturalistic social interactions. The 'Interactional Heterogeneity Hypothesis' of ASD proposes that the degree to which individuals share a common ground substantially influences their ability to achieve smooth social interactions.

METHODS

To test this hypothesis, we filmed 29 autistic and 29 matched typically developed adults engaged in several conversational tasks. Windowed cross-lagged correlations were computed using the time series of motion energy of both individuals in a dyad. These coefficients were then compared across the three dyad types that were homo- or heterogenous with respect to diagnosis: pairs of two autistic individuals, two typically developed individuals or pairs of one autistic and one typically developed person.

RESULTS

We found that all dyad types achieved above-chance interpersonal synchrony, but that synchrony was more expressed in typical dyads compared to both autistic and mixed dyads.

LIMITATIONS

The method presented here provides only one, albeit objective and robust, approach to explore synchrony. The methodological choices as well as the lack of consideration for other communication modalities may limit our interpretation of the findings. Moreover, the sample size is small with respect to exploring associations between synchrony and various outcome and social skill measures.

CONCLUSIONS

The present results do not provide support for the Interactional Heterogeneity Hypothesis given that autistic individuals do not coordinate better when interacting with another autistic individual, compared to when interacting with a typical individual.

Interactive Psychometrics for Autism With the Human Dynamic Clamp: Interpersonal Synchrony From Sensorimotor to Sociocognitive Domains

The human dynamic clamp (HDC) is a human-machine interface designed on the basis of coordination dynamics for studying realistic social interaction under controlled and reproducible conditions. Here, we propose to probe the validity of the HDC as a psychometric instrument for quantifying social abilities in children with autism spectrum disorder (ASD) and neurotypical development. To study interpersonal synchrony with the HDC, we derived five standardized scores following a gradient from sensorimotor and motor to higher sociocognitive skills in a sample of 155 individuals (113 participants with ASD, 42 typically developing participants; aged 5 to 25 years; IQ > 70). Regression analyses were performed using normative modeling on global scores according to four subconditions (HDC behavior "cooperative/competitive," human task "in-phase/anti-phase," diagnosis, and age at inclusion). Children with ASD had lower scores than controls for motor skills. HDC motor coordination scores were the best candidates for stratification and diagnostic biomarkers according to exploratory analyses of hierarchical clustering and multivariate classification. Independently of phenotype, sociocognitive skills increased with developmental age while being affected by the ongoing task and HDC behavior. Weaker performance in ASD for motor skills suggests the convergent validity of the HDC for evaluating social interaction. Results provided additional evidence of a relationship between sensorimotor and sociocognitive skills. HDC may also be used as a marker of maturation of sociocognitive skills during real-time social interaction. Through its standardized and objective evaluation, the HDC not only represents a valid paradigm for the study of interpersonal synchrony but also offers a promising, clinically relevant psychometric instrument for the evaluation and stratification of sociomotor dysfunctions.

Machine Learning to Study Social Interaction Difficulties in ASD

Autism Spectrum Disorder (ASD) is a spectrum of neurodevelopmental conditions characterized by difficulties in social communication and social interaction as well as repetitive behaviors and restricted interests. Prevalence rates have been rising, and existing diagnostic methods are both extremely time and labor consuming. There is an urgent need for more economic and objective automatized diagnostic tools that are independent of language and experience of the diagnostician and that can help deal with the complexity of the autistic phenotype. Technological advancements in machine learning are offering a potential solution, and several studies have employed computational approaches to classify ASD based on phenomenological, behavioral or neuroimaging data. Despite of being at the core of ASD diagnosis and having the potential to be used as a behavioral marker for machine learning algorithms, only recently have movement parameters been used as features in machine learning classification approaches. In a proof-of-principle analysis of data from a social interaction study we trained a classification algorithm on intrapersonal synchrony as an automatically and objectively measured phenotypic feature from 29 autistic and 29 typically developed individuals to differentiate those individuals with ASD from those without ASD. Parameters included nonverbal motion energy values from 116 videos of social interactions. As opposed to previous studies to date, our classification approach has been applied to non-verbal behavior objectively captured during naturalistic and complex interactions with a real human interaction partner assuring high external validity. A machine learning approach lends itself particularly for capturing heterogeneous and complex behavior in real social interactions and will be essential in developing automatized and objective classification methods in ASD.

Multiscale movement coordination dynamics in collaborative team problem solving

During collaborative problem solving (CPS), coordination occurs at different spatial and temporal scales. This multiscale coordination should play a functional role in facilitating effective collaboration. To evaluate this, we conducted a study of computer-based CPS with 42 dyadic teams. We used cross-wavelet coherence to examine movement coordination, extracted from videos, at several scales, and tested whether the observed coordination was greater than expected due to chance and due to task demands. We found that coordination at scales less than 2s was greater than chance and at most scales (except 16s, 1m, and 2m), was greater than expected due to task demands. Lastly, we observed that coherence at .25s and 1s scales was predictive of performance. However, when including relative phase, our results suggest that higher in-phase movement coordination at the 1s scale was the strongest predictor of CPS performance. Further, we used growth curve modeling to examine how movement coordination changes across the duration of the task and whether this is moderated by CPS performance. We found that coordination over the duration of the CPS task is quadratic (a U shape) and that better performing teams have higher coordination with a shallower curve. We discuss these findings and their relevance to understanding how low-level movement coordination facilitates CPS.

Social Impairments in Mental Disorders: Recent Developments in Studying the Mechanisms of Interactive Behavior

Most mental disorders are associated with impairments in social functioning. Paradigms developed to study social functioning in laboratory settings mostly put participants in a detached observer point of view. However, some phenomena are inherently interactive and studying full-blown reciprocal interactions may be indispensable to understand social deficits in psychopathology.

We conducted a narrative review on recent developments in the field of experimental clinical psychology and clinical social neuroscience that employs a second-person approach to studying social impairments in Autism Spectrum Disorder (ASD), Personality Disorder, Social Anxiety Disorder (SAD), and Schizophrenia.

Recent developments in methodological, analytical, and technical approaches, such as dual eye-tracking, mobile eye-tracking, live video-feed, hyperscanning, or motion capture allow for a more ecologically valid assessment of social functioning. In individuals with ASD, these methods revealed reduced sensitivity to the presence of a real interaction partner as well as diminished behavioral and neural synchronicity with interaction partners. Initial evidence suggests that interactive paradigms might be a powerful tool to reveal reduced interpersonal sensitivity in Personality Disorders and increased interpersonal sensitivity in individuals with SAD.

A shift towards adapting a second-person account has clearly benefitted research on social interaction in psychopathology. Several studies showed profound differences in behavioral and neural measures during actual social interactions, as compared to engaging participants as mere observers. While research using truly interactive paradigms is still in its infancy, it holds great potential for clinical research on social interaction.

We review studies adopting a second-person account of social interaction in clinical psychology.

Studies show profound differences between actual social interactions and mere observations.

The full extent of impairments in social functioning unfolds only in complex social interactions.

New methodological developments hold great potential for research on social interaction deficits.

Which Gait Parameters and Walking Patterns Show the Significant Differences Between Parkinson's Disease and Healthy Participants?

This study investigated the difference in the gait of patients with Parkinson’s disease (PD), age-matched controls and young controls during three walking patterns. Experiments were conducted with 24 PD, 24 age-matched controls and 24 young controls, and four gait intervals were measured using inertial measurement units (IMU). Group differences between the mean and variance of the gait parameters (stride interval, stance interval, swing interval and double support interval) for the three groups were calculated and statistical significance was tested. The results showed that the variance in each of the four gait parameters of PD patients was significantly higher compared with the controls, irrespective of the three walking patterns. This study showed that the variance of any of the gait interval parameters obtained using IMU during any of the walking patterns could be used to differentiate between the gait of PD and control people.

Multi-Scale Coordination of Distinctive Movement Patterns During Embodied Interaction Between Adults With High-Functioning Autism and Neurotypicals

Autism Spectrum Disorder (ASD) can be understood as a social interaction disorder. This requires researchers to take a “second-person” stance and to use experimental setups based on bidirectional interactions. The present work offers a quantitative description of movement patterns exhibited during computer-mediated real-time sensorimotor interaction in 10 dyads of adult participants, each consisting of one control individual (CTRL) and one individual with high-functioning autism (HFA). We applied time-series analyses to their movements and found two main results. First, multi-scale coordination between participants was present. Second, despite this dyadic alignment and our previous finding that individuals with HFA can be equally sensitive to the other’s presence, individuals’ movements differed in style: in contrast to CTRLs, HFA participants appeared less inclined to sustain mutual interaction and instead explored the virtual environment more generally. This finding is consistent with social motivation deficit accounts of ASD, as well as with hypersensitivity-motivated avoidance of overstimulation. Our research demonstrates the utility of time series analyses for the second-person stance and complements previous work focused on non-dynamical and performance-based variables.

Peripheral Network Connectivity Analyses for the Real-Time Tracking of Coupled Bodies in Motion

Dyadic interactions are ubiquitous in our lives, yet they are highly challenging to study. Many subtle aspects of coupled bodily dynamics continuously unfolding during such exchanges have not been empirically parameterized. As such, we have no formal statistical methods to describe the spontaneously self-emerging coordinating synergies within each actor’s body and across the dyad. Such cohesive motion patterns self-emerge and dissolve largely beneath the awareness of the actors and the observers. Consequently, hand coding methods may miss latent aspects of the phenomena. The present paper addresses this gap and provides new methods to quantify the moment-by-moment evolution of self-emerging cohesiveness during highly complex ballet routines. We use weighted directed graphs to represent the dyads as dynamically coupled networks unfolding in real-time, with activities captured by a grid of wearable sensors distributed across the dancers’ bodies. We introduce new visualization tools, signal parameterizations, and a statistical platform that integrates connectivity metrics with stochastic analyses to automatically detect coordination patterns and self-emerging cohesive coupling as they unfold in real-time. Potential applications of these new techniques are discussed in the context of personalized medicine, basic research, and the performing arts.