Investigating Conversational Dynamics: Interactive Alignment, Interpersonal Synergy, and Collective Task Performance

Linguistic alignment with an artificial agent: A commentary and re-analysis

In this manuscript we provide a commentary and a complementary analysis of Cirillo et al.'s (2022) study on conceptual alignment in a joint picture naming task involving a social robot (Cognition, 227, 105,213). In their study, Cirillo and collaborators present evidence suggesting automatic alignment by examining response proportions, reflecting adaptation to the lexical choices made by the artificial agent (i.e., providing category names instead of basic names for specific semantic categories). Here, we conducted a complementary analysis using the openly available dataset, employing a multiverse approach and focusing on response times as a more nuanced measure of cognitive processing and automaticity. Our findings indicate that alignment in the Category condition (i.e., when the robot provided a superordinate label) is associated with longer response times and greater variability. When providing the basic label in the Basic condition, RTs are much shorter and variability is reduced, compatible with the Basic-level advantage phenomenon. Non-alignment to each condition completely reverses the pattern. This suggests that aligning when producing a superordinate label is a strategic and effortful rather than an automatic response mechanism. Furthermore, through comprehensive visual exploration of response proportions across potentially influential variables, we observed category naming alignment primarily emerging in specific semantic categories, and mostly for stimuli with basic labels at low lexical frequency and newly designed pictures not taken from the MultiPic database, thus suggesting a limited generalizability of the effect. These insights were confirmed using leave-one-out robustness checks. In conclusion, our contribution provides complementary evidence in support of strategic rather than automatic responses when aligning with Category labels in the analyzed dataset, with a limited generalizability despite all the balancing procedures the authors carefully implemented in the experimental material. This is likely to reflect individual task strategies rather than genuine alignment. Lastly, we suggest directions for future research on linguistic alignment, building on insights from both Cirillo et al.'s study and our commentary. We also briefly discuss the Open Science principles that shaped our approach to this work.

Least Effort and Alignment in Task-Oriented Communication

Conversational partners align the meanings of their words over the course of interaction to coordinate and communicate. One process of alignment is lexical entrainment, whereby partners mirror and abbreviate their word usage to converge on shared terms for referents relevant to the conversation. However, lexical entrainment may result in inefficient mimicry that does not add new information, suggesting that task-oriented communication may favor alignment through other means. The present study investigates the process of alignment in Danish conversations in which dyads learned to categorize unfamiliar "aliens" using trial-and-error feedback. Performance improved as dyad communication became less verbose, measured as a decrease in the entropy of word usage. Word usage also diverged between partners as measured by Jensen-Shannon Divergence, which indicates that alignment was not achieved through lexical entrainment. A computational model of dyadic communication is shown to account for the alien game results in terms of joint least effort. The model shows that alignment of partner referents can increase as a result of minimizing both the joint entropy of dyadic word usage and the conditional entropy of individual referents given the joint signal distribution. We conclude that the principle of least effort, originally proposed to shape language evolution, may also support alignment in task-oriented communication.

Investigating Linguistic Alignment in Collaborative Dialogue: A Study of Syntactic and Lexical Patterns in Middle School Students

Linguistic alignment, the tendency of speakers to share common linguistic features during conversations, has emerged as a key area of research in computer-supported collaborative learning. While previous studies have shown that linguistic alignment can have a significant impact on collaborative outcomes, there is limited research exploring its role in K-12 learning contexts. This study investigates syntactic and lexical linguistic alignments in a collaborative computer science-learning corpus from 24 pairs (48 individuals) of middle school students (aged 11-13). The results show stronger effects of self-alignment than partner alignment on both syntactic and lexical levels, with students often diverging from their partners on task-relevant words. Furthermore, student self-alignment on the syntactic level is negatively correlated with partner satisfaction ratings, while self-alignment on lexical level is positively correlated with their partner's satisfaction.

Dyadic differences in empathy scores are associated with kinematic similarity during conversational question-answer pairs

During conversation, speakers coordinate and synergize their behaviors at multiple levels, and in different ways. The extent to which individuals converge or diverge in their behaviors during interaction may relate to interpersonal differences relevant to social interaction, such as empathy as measured by the empathy quotient (EQ). An association between interpersonal difference in empathy and interpersonal entrainment could help to throw light on how interlocutor characteristics influence interpersonal entrainment. We investigated this possibility in a corpus of unconstrained conversation between dyads. We used dynamic time warping to quantify entrainment between interlocutors of head motion, hand motion, and maximum speech f0 during question-response sequences. We additionally calculated interlocutor differences in EQ scores. We found that, for both head and hand motion, greater difference in EQ was associated with higher entrainment. Thus, we consider that people who are dissimilar in EQ may need to "ground" their interaction with low-level movement entrainment. There was no significant relationship between f0 entrainment and EQ score differences.

Disruptions in lexical and speech entrainment: Multidimensional insights from English school-age late talkers

Late talkers, despite achieving normal language test scores by age five, often face enduring conversational challenges. This study examines whether school-age children identified as late talkers at 24 months show persistent disruptions in speech and lexical entrainment. We analysed spontaneous conversational samples from 36 late talkers and 37 typically developing five-year-olds, examining lexical entrainment patterns in high-frequency, hedge, and affirmative cue words and speech entrainment of 412 acoustic features (rhythmic, articulatory, and phonatory dimensions). Perceptual conversational quality scores were provided by raters, while cross-recurrence quantification analysis measured speech entrainment patterns. Sham conversations and machine learning identified key predictors distinguishing late talkers from controls. Our results revealed that late talkers perceptually exhibited lower conversational quality. Late talkers showed significantly lower lexical entrainment in high-frequency words but comparable use of hedge words and increased use of affirmative cue words. In speech entrainment, late talkers exhibited intermittent rather than consistent entrainment. They also exhibited more frequent but less complex speech entrainment, showing repetitive interaction patterns. Notably, late-talking children exhibited marked rigidity in articulation and reduced complexity, intermittent rhythmic entrainment, and weaker phonatory control. Finally, seven unique feature-measure matrices in late talkers, reflecting articulation and phonation stability and complexity, were significantly associated with poor conversational quality in this group. Within the framework of the Interactive Alignment Model, these findings underscore persistent disruptions in automatic entrainment processes among late talkers, contributing to reduced conversational quality.

The effect of gesture expressivity on emotional resonance in storytelling interaction

The key function of storytelling is a meeting of hearts: a resonance in the recipient(s) of the story narrator's emotion toward the story events. This paper focuses on the role of gestures in engendering emotional resonance in conversational storytelling. The paper asks three questions: Does story narrators' gesture expressivity increase from story onset to climax offset (RQ #1)? Does gesture expressivity predict specific EDA responses in story participants (RQ #2)? How important is the contribution of gesture expressivity to emotional resonance compared to the contribution of other predictors of resonance (RQ #3)? 53 conversational stories were annotated for a large number of variables including Protagonist, Recency, Group composition, Group size, Sentiment, and co-occurrence with quotation. The gestures in the stories were coded for gesture phases and gesture kinematics including Size, Force, Character view-point, Silence during gesture, Presence of hold phase, Co-articulation with other bodily organs, and Nucleus duration. The Gesture Expressivity Index (GEI) provides an average of these parameters. Resonating gestures were identified, i.e., gestures exhibiting concurrent specific EDA responses by two or more participants. The first statistical model, which addresses RQ #1, suggested that story narrators' gestures become more expressive from story onset to climax offset. The model constructed to adress RQ #2 suggested that increased gesture expressivity increases the probability of specific EDA responses. To address RQ #3 a Random Forest for emotional resonance as outcome variable and the seven GEI parameters as well as six more variables as predictors was constructed. All predictors were found to impact Eemotional resonance. Analysis of variable importance showed Group composition to be the most impactful predictor. Inspection of ICE plots clearly indicated combined effects of individual GEI parameters and other factors, including Group size and Group composition. This study shows that more expressive gestures are more likely to elicit physiological resonance between individuals, suggesting an important role for gestures in connecting people during conversational storytelling. Methodologically, this study opens up new avenues of multimodal corpus linguistic research by examining the interplay of emotion-related measurements and gesture at micro-analytic kinematic levels and using advanced machine-learning methods to deal with the inherent collinearity of multimodal variables.

Looking, pointing, and talking together: How dyads of differential expertise coordinate attention during conversation

When people discuss something that they can both see, their attention becomes increasingly coupled. Previous studies have found that this coupling is temporally asymmetric (e.g., one person leads and one follows) when dyads are assigned conversational roles (e.g., speaker and listener). And while such studies have focused on the coupling of gaze, there is also evidence that people use their hands to coordinate attention. The present study uses a visual task to expand on this past work in two respects. First, rather than assigning conversational roles, participants' background knowledge was manipulated (e.g., expert and novice) to elicit differential roles inherent to the conversation. Second, participants were permitted to gesture freely while interacting. Cross Recurrence Quantification Analysis with data from mobile eye trackers and manually coded pointing gestures revealed that although more knowledgeable participants dominated the dialogue by talking and pointing more, the symmetry of coupled behaviors (gaze and pointing) between participants remained fixed. Asymmetric attentional coupling emerged, although this was dependent on conversational turn taking. Specifically, regardless of background knowledge, the currently speaking participant led attention, both with the eyes and with the hands. These findings suggest stable, turn-dependent interpersonal coupling dynamics, and highlight the role of pointing gestures and conversational turn-taking in multimodal attention coordination.

Gaze-action coupling, gaze-gesture coupling, and exogenous attraction of gaze in dyadic interactions

In human interactions, gaze may be used to acquire information for goal-directed actions, to acquire information related to the interacting partner's actions, and in the context of multimodal communication. At present, there are no models of gaze behavior in the context of vision that adequately incorporate these three components. In this study, we aimed to uncover and quantify patterns of within-person gaze-action coupling, gaze-gesture and gaze-speech coupling, and coupling between one person's gaze and another person's manual actions, gestures, or speech (or exogenous attraction of gaze) during dyadic collaboration. We showed that in the context of a collaborative Lego Duplo-model copying task, within-person gaze-action coupling is strongest, followed by within-person gaze-gesture coupling, and coupling between gaze and another person's actions. When trying to infer gaze location from one's own manual actions, gestures, or speech or that of the other person, only one's own manual actions were found to lead to better inference compared to a baseline model. The improvement in inferring gaze location was limited, contrary to what might be expected based on previous research. We suggest that inferring gaze location may be most effective for constrained tasks in which different manual actions follow in a quick sequence, while gaze-gesture and gaze-speech coupling may be stronger in unconstrained conversational settings or when the collaboration requires more negotiation. Our findings may serve as an empirical foundation for future theory and model development, and may further be relevant in the context of action/intention prediction for (social) robotics and effective human-robot interaction.

Embodied hyperscanning for studying social interaction: A scoping review of simultaneous brain and body measurements

We systematically investigated the application of embodied hyperscanning methodologies in social neuroscience research. Hyperscanning enables the simultaneous recording of neurophysiological and physiological signals from multiple participants. We highlight the trend toward integrating Mobile Brain/Body Imaging (MoBI) within the 4E research framework, which emphasizes the interconnectedness of brain, body, and environment. Our analysis revealed a geographic concentration of studies in the Global North, calling for global collaboration and transcultural research to balance the field. The predominant use of Magneto/Electroencephalogram (M/EEG) in these studies suggests a traditional brain-centric perspective in social neuroscience. Future research directions should focus on integrating diverse techniques to capture the dynamic interplay between brain and body functions in real-world contexts. Our review also finds a preference for tasks involving natural settings. Nevertheless, the analysis in hyperscanning studies is often limited to physiological signal synchrony between participants. This suggests a need for more holistic and complex approaches that combine inter-corporeal synchrony with intra-individual measures. We believe that the future of the neuroscience of relationships lies in embracing the complexity of cognition, integrating diverse methods and theories to enrich our grasp of human social behavior in its natural contexts.

Using cross-recurrence quantification analysis to compute similarity measures for time series of unequal length with applications to sleep stage analysis

Comparing time series of unequal length requires data processing procedures that may introduce biases. This article describes, validates, and applies Cross-Recurrence Quantification Analysis (CRQA) to detect and quantify correlation and coupling among time series of unequal length without prior data processing. We illustrate and validate this application using continuous and discrete data from a model system (study 1). Then we use the method to re-analyze the Sleep Heart Health Study (SHHS), a rare large dataset comprising detailed physiological sleep measurements acquired by in-home polysomnography. We investigate whether recurrence patterns of ultradian NREM/REM sleep cycles (USC) predict mortality (study 2). CRQA exhibits better performance compared with traditional approaches that require trimming, stretching or compression to bring two time series to the same length. Application to the SHHS indicates that recurrence patterns linked to stability of USCs are associated with all-cause mortality even after controlling for other sleep parameters, health, and sociodemographics. We suggest that CRQA is a useful tool for analyzing categorical time series, where the underlying structure of the data is unlikely to result in matching data points-such as ultradian sleep cycles.

Places for reasoning

In this article, we explore behaviour settings that enable reasoning and the diversity of constraints that not only limit but also make these behaviour settings possible. We focus specifically on reasoning and surveying how behaviour settings allow for the generation of norms of action that are nevertheless differentiated by geographies and sociocultural systems. These geographies and sociocultural systems involve diverse trajectories for reasoning even within similar behaviour settings. We will touch on places for reasoning like Twitter, social movements, traditional knowledge and laboratories set up for experimentation on our reasoning abilities. We will show how these places and the behaviour settings that emerge in them can be studied in terms of the complexity of the interactions between their participants and in terms of enabling constraints. This article is part of the theme issue 'People, places, things, and communities: expanding behaviour settings theory in the twenty-first century'.

Group Coordination Catalyzes Individual and Cultural Intelligence

A large program of research has aimed to ground large-scale cultural phenomena in processes taking place within individual minds. For example, investigating whether individual agents equipped with the right social learning strategies can enable cumulative cultural evolution given long enough time horizons. However, this approach often omits the critical group-level processes that mediate between individual agents and multi-generational societies. Here, we argue that interacting groups are a necessary and explanatory level of analysis, linking individual and collective intelligence through two characteristic feedback loops. In the first loop, more sophisticated individual-level social learning mechanisms based on Theory of Mind facilitate group-level complementarity, allowing distributed knowledge to be compositionally recombined in groups; these group-level innovations, in turn, ease the cognitive load on individuals. In the second loop, societal-level processes of cumulative culture provide groups with new cognitive technologies, including shared language and conceptual abstractions, which set in motion new group-level processes to further coordinate, recombine, and innovate. Taken together, these cycles establish group-level interaction as a dual engine of intelligence, catalyzing both individual cognition and cumulative culture.

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

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

Phonetic Dissimilarity and L2 Category Formation in L2 Accommodation

Many studies of speech accommodation focus on native speakers with different dialects, whereas only a limited number of studies work on L2 speakers' accommodation and discuss theories for second language (L2) accommodation. This paper aimed to fill the theoretical gap by integrating the revised speech learning model (SLM) with the exemplar-based models for L2 speech accommodation. A total of 19 Cantonese-English bilingual speakers completed map tasks with English speakers of Received Pronunciation and General American English in two separate experiments. Their pronunciations of THOUGHT and PATH vowels, and fricatives [z] and [θ] were examined before, during, and after the map tasks. The role of phonetic dissimilarity in L2 accommodation and L2 category formation in the revised SLM (SLM-r) were tested. First, the results suggested that global phonetic dissimilarity cannot predict Hong Kong English (HKE) speakers' accommodation patterns. Instead, the segment-specific phonetic dissimilarity between participants and interlocutors was found to be positively correlated with the participants' degree of accommodation. In addition, HKE speakers who did not form a new L2 category of [z] were found to significantly accommodate toward their interlocutor, suggesting that L2 accommodation might not be constrained by phonological category. An integrated exemplar model for L2 accommodation is proposed to explain these findings.

The Emerging Science of Interacting Minds

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

Submovement interpersonal coupling is associated to audio-motor coordination performance

Acting in concert with others, a key aspect of our social life, requires behavioral coordination between persons on multiple timescales. When zooming in on the kinematic properties of movements, it appears that small speed fluctuations, called submovements, are embedded within otherwise smooth end-point trajectories. Submovements, by occurring at a faster timescale than that of movements, offer a novel window upon the functional relationship between distinct motor timescales. In this regard, it has previously been shown that when partners visually synchronize their movements, they also coordinate the timing of their submovement by following an alternated pattern. However, it remains unclear whether the mechanisms behind submovement coordination are domain-general or specific to the visual modality, and whether they have relevance for interpersonal coordination also at the scale of whole movements. In a series of solo and dyadic tasks, we show that submovements are also present and coordinated across partners when sensorimotor interactions are mediated by auditory feedback only. Importantly, the accuracy of task-instructed interpersonal coordination at the movement level correlates with the strength of submovement coordination. These results demonstrate that submovement coordination is a potentially fundamental mechanism that participates in interpersonal motor coordination regardless of the sensory domain mediating the interaction.

Frequency and characteristics of echoes and self-repetitions in minimally verbal and verbally fluent autistic individuals

Background and aims

Nongenerative speech is the rote repetition of words or phrases heard from others or oneself. The most common manifestations of nongenerative speech are immediate and delayed echolalia, which are a well-attested clinical feature and a salient aspect of atypical language use in autism. However, there are no current estimates of the frequency of nongenerative speech, and the individual characteristics associated with nongenerative speech use in individuals across the autistic spectrum are poorly understood. In this study, we aim to measure and characterize spontaneous and nongenerative speech use in minimally verbal and verbally fluent autistic children and adolescents.

Methods

Participants were 50 minimally verbal and 50 verbally fluent autistic individuals aged 6 to 21 years. Spontaneous and nongenerative speech samples were derived from SALT transcripts of ADOS-2 assessments. Participants' intelligible speech utterances were categorized as spontaneous or nongenerative. Spontaneous versus nongenerative utterances were compared between language subgroups on frequency of use and linguistic structure. Associations between nongenerative speech use and a series of individual characteristics (ADOS-2 subscale scores, nonverbal IQ, receptive vocabulary, and chronological age) were investigated over the whole sample and for each language subgroup independently.

Results

Almost all participants produced some nongenerative speech. Minimally verbal individuals produced significantly more nongenerative than spontaneous utterances, and more nongenerative utterances compared to verbally fluent individuals. Verbally fluent individuals produced limited rates of nongenerative utterances, in comparison to their much higher rates of spontaneous utterances. Across the sample, nongenerative utterance rates were associated with nonverbal IQ and receptive vocabulary, but not separately for the two language subgroups. In verbally fluent individuals, only age was significantly inversely associated with nongenerative speech use such that older individuals produced fewer nongenerative utterances. In minimally verbal individuals, there were no associations between any of the individual characteristics and nongenerative speech use. In terms of linguistic structure, the lexical diversity of nongenerative and spontaneous utterances of both language subgroups was comparable. Morphosyntactic complexity was higher for spontaneous compared to nongenerative utterances in verbally fluent individuals, while no differences emerged between the two utterance types in minimally verbal individuals.

Conclusions

Nongenerative speech presents differently in minimally verbal and verbally fluent autistic individuals. Although present in verbally fluent individuals, nongenerative speech appears to be a major feature of spoken language in minimally verbal children and adolescents.

Implications

Our results advocate for more research on the expressive language profiles of autistic children and adolescents who remain minimally verbal and for further investigations of nongenerative speech, which is usually excluded from language samples. Given its prevalence in the spoken language of minimally verbal individuals, nongenerative speech could be used as a way to engage in and maintain communication with this subgroup of autistic individuals.

Left-Hemisphere Cortical Language Regions Respond Equally to Observed Dialogue and Monologue

Much of the language we encounter in our everyday lives comes in the form of conversation, yet the majority of research on the neural basis of language comprehension has used input from only one speaker at a time. Twenty adults were scanned while passively observing audiovisual conversations using functional magnetic resonance imaging. In a block-design task, participants watched 20 s videos of puppets speaking either to another puppet (the dialogue condition) or directly to the viewer (the monologue condition), while the audio was either comprehensible (played forward) or incomprehensible (played backward). Individually functionally localized left-hemisphere language regions responded more to comprehensible than incomprehensible speech but did not respond differently to dialogue than monologue. In a second task, participants watched videos (1-3 min each) of two puppets conversing with each other, in which one puppet was comprehensible while the other's speech was reversed. All participants saw the same visual input but were randomly assigned which character's speech was comprehensible. In left-hemisphere cortical language regions, the time course of activity was correlated only among participants who heard the same character speaking comprehensibly, despite identical visual input across all participants. For comparison, some individually localized theory of mind regions and right-hemisphere homologues of language regions responded more to dialogue than monologue in the first task, and in the second task, activity in some regions was correlated across all participants regardless of which character was speaking comprehensibly. Together, these results suggest that canonical left-hemisphere cortical language regions are not sensitive to differences between observed dialogue and monologue.

Measuring Prosodic Entrainment in Conversation: A Review and Comparison of Different Methods

PURPOSE

This study aims to further our understanding of prosodic entrainment and its different subtypes by analyzing a single corpus of conversations with 12 different methods and comparing the subsequent results.

METHOD

Entrainment on three fundamental frequency features was analyzed in a subset of recordings from the LUCID corpus (Baker & Hazan, 2011) using the following methods: global proximity, global convergence, local proximity, local convergence, local synchrony (Levitan & Hirschberg, 2011), prediction using linear mixed-effects models (Schweitzer & Lewandowski, 2013), geometric approach (Lehnert-LeHouillier, Terrazas, & Sandoval, 2020), time-aligned moving average (Kousidis et al., 2008), HYBRID method (De Looze et al., 2014), cross-recurrence quantification analysis (e.g., Fusaroli & Tylén, 2016), and windowed, lagged cross-correlation (Boker et al., 2002). We employed entrainment measures on a local timescale (i.e., on adjacent utterances), a global timescale (i.e., over larger time frames), and a time series-based timescale that is larger than adjacent utterances but smaller than entire conversations.

RESULTS

We observed variance in results of different methods.

CONCLUSIONS

Results suggest that each method may measure a slightly different type of entrainment. The complex implications this has for existing and future research are discussed.

Repeat After Me? Both Children With and Without Autism Commonly Align Their Language With That of Their Caregivers

Linguistic repetitions in children are conceptualized as negative in children with autism - echolalia, without communicative purpose - and positive in typically developing (TD) children - linguistic alignment involved in shared engagement, common ground and language acquisition. To investigate this apparent contradiction we analyzed spontaneous speech in 67 parent-child dyads from a longitudinal corpus (30 minutes of play activities at 6 visits over 2 years). We included 32 children with autism and 35 linguistically matched TD children (mean age at recruitment 32.76 and 20.27 months). We found a small number of exact repetitions in both groups (roughly 1% of utterances across visits), which increased over time in children with autism and decreased in the TD group. Partial repetitions were much more frequent: children reused caregivers' words at high rates regardless of diagnostic group (24% of utterances at first visit), and this increased in frequency (but not level) over time, faster for TD children (at final visit: 33% for autism, 40% for TD). The same happened for partial repetition of syntax and semantic alignment. However, chance alignment (as measured by surrogate pairs) also increased and findings for developmental changes were reliable only for syntactic and semantic alignment. Children with richer linguistic abilities also displayed a higher tendency to partially re-use their caregivers' language (alignment rates and semantic alignment). This highlights that all children commonly re-used the words, syntax, and topics of their caregivers, albeit with some quantitative differences, and that most repetition was at least potentially productive, with repeated language being re-contextualized and integrated with non-repeated language. The salience of echolalia in ASD might be partially explained by slight differences in frequency, amplified by lower semantic alignment, persistence over time, and expectations of echolalia. More in-depth qualitative and quantitative analyses of how repetitions are used and received in context are needed.

Language-Specific Constraints on Conversation: Evidence from Danish and Norwegian

Establishing and maintaining mutual understanding in everyday conversations is crucial. To do so, people employ a variety of conversational devices, such as backchannels, repair, and linguistic entrainment. Here, we explore whether the use of conversational devices might be influenced by cross-linguistic differences in the speakers' native language, comparing two matched languages-Danish and Norwegian-differing primarily in their sound structure, with Danish being more opaque, that is, less acoustically distinguished. Across systematically manipulated conversational contexts, we find that processes supporting mutual understanding in conversations vary with external constraints: across different contexts and, crucially, across languages. In accord with our predictions, linguistic entrainment was overall higher in Danish than in Norwegian, while backchannels and repairs presented a more nuanced pattern. These findings are compatible with the hypothesis that native speakers of Danish may compensate for its opaque sound structure by adopting a top-down strategy of building more conversational redundancy through entrainment, which also might reduce the need for repairs. These results suggest that linguistic differences might be met by systematic changes in language processing and use. This paves the way for further cross-linguistic investigations and critical assessment of the interplay between cultural and linguistic factors on the one hand and conversational dynamics on the other.

(Mis)align: a simple dynamic framework for modeling interpersonal coordination

As people coordinate in daily interactions, they engage in different patterns of behavior to achieve successful outcomes. This includes both synchrony-the temporal coordination of the same behaviors at the same time-and complementarity-the coordination of the same or different behaviors that may occur at different relative times. Using computational methods, we develop a simple framework to describe the interpersonal dynamics of behavioral synchrony and complementarity over time, and explore their task-dependence. A key feature of this framework is the inclusion of a task context that mediates interactions, and consists of active, inactive, and inhibitory constraints on communication. Initial simulation results show that these task constraints can be a robust predictor of simulated agents' behaviors over time. We also show that the framework can reproduce some general patterns observed in human interaction data. We describe preliminary theoretical implications from these results, and relate them to broader proposals of synergistic self-organization in communication.

Embodied Processing at Six Linguistic Granularity Levels: A Consensus Paper

Language processing is influenced by sensorimotor experiences. Here, we review behavioral evidence for embodied and grounded influences in language processing across six linguistic levels of granularity. We examine (a) sub-word features, discussing grounded influences on iconicity (systematic associations between word form and meaning); (b) words, discussing boundary conditions and generalizations for the simulation of color, sensory modality, and spatial position; (c) sentences, discussing boundary conditions and applications of action direction simulation; (d) texts, discussing how the teaching of simulation can improve comprehension in beginning readers; (e) conversations, discussing how multi-modal cues improve turn taking and alignment; and (f) text corpora, discussing how distributional semantic models can reveal how grounded and embodied knowledge is encoded in texts. These approaches are converging on a convincing account of the psychology of language, but at the same time, there are important criticisms of the embodied approach and of specific experimental paradigms. The surest way forward requires the adoption of a wide array of scientific methods. By providing complimentary evidence, a combination of multiple methods on various levels of granularity can help us gain a more complete understanding of the role of embodiment and grounding in language processing.

Recurrence Quantification Analysis of Crowd Sound Dynamics

When multiple individuals interact in a conversation or as part of a large crowd, emergent structures and dynamics arise that are behavioral properties of the interacting group rather than of any individual member of that group. Recent work using traditional signal processing techniques and machine learning has demonstrated that global acoustic data recorded from a crowd at a basketball game can be used to classify emergent crowd behavior in terms of the crowd's purported emotional state. We propose that the description of crowd behavior from such global acoustic data could benefit from nonlinear analysis methods derived from dynamical systems theory. Such methods have been used in recent research applying nonlinear methods to audio data extracted from music and group musical interactions. In this work, we used nonlinear analyses to extract features that are relevant to the behavioral interactions that underlie acoustic signals produced by a crowd attending a sporting event. We propose that recurrence dynamics measured from these audio signals via recurrence quantification analysis (RQA) reflect information about the behavioral dynamics of the crowd itself. We analyze these dynamics from acoustic signals recorded from crowds attending basketball games, and that were manually labeled according to the crowds' emotional state across six categories: angry noise, applause, cheer, distraction noise, positive chant, and negative chant. We show that RQA measures are useful to differentiate the emergent acoustic behavioral dynamics between these categories, and can provide insight into the recurrence patterns that underlie crowd interactions.

The Social Route to Abstraction: Interaction and Diversity Enhance Performance and Transfer in a Rule-Based Categorization Task

Capacities for abstract thinking and problem-solving are central to human cognition. Processes of abstraction allow the transfer of experiences and knowledge between contexts helping us make informed decisions in new or changing contexts. While we are often inclined to relate such reasoning capacities to individual minds and brains, they may in fact be contingent on human-specific modes of collaboration, dialogue, and shared attention. In an experimental study, we test the hypothesis that social interaction enhances cognitive processes of rule-induction, which in turn improves problem-solving performance. Through three sessions of increasing complexity, individuals and groups were presented with a problem-solving task requiring them to categorize a set of visual stimuli. To assess the character of participants' problem representations, after each training session, they were presented with a transfer task involving stimuli that differed in appearance, but shared relations among features with the training set. Besides, we compared participants' categorization behaviors to simulated agents relying on exemplar learning. We found that groups performed superior to individuals and agents in the training sessions and were more likely to correctly generalize their observations in the transfer phase, especially in the high complexity session, suggesting that groups more effectively induced underlying categorization rules from the stimuli than individuals and agents. Crucially, variation in performance among groups was predicted by semantic diversity in members' dialogical contributions, suggesting a link between social interaction, cognitive diversity, and abstraction.

Speech Entrainment in Adolescent Conversations: A Developmental Perspective

PURPOSE

Defined as the similarity of speech behaviors between interlocutors, speech entrainment plays an important role in successful adult conversations. According to theoretical models of entrainment and research on motoric, cognitive, and social developmental milestones, the ability to entrain should develop throughout adolescence. However, little is known about the specific developmental trajectory or the role of speech entrainment in conversational outcomes of this age group. The purpose of this study is to characterize speech entrainment patterns in the conversations of neurotypical early adolescents.

METHOD

This study utilized a corpus of 96 task-based conversations between adolescents between the ages of 9 and 14 years and a comparison corpus of 32 task-based conversations between adults. For each conversational turn, two speech entrainment scores were calculated for 429 acoustic features across rhythmic, articulatory, and phonatory dimensions. Predictive modeling was used to evaluate the degree of entrainment and relationship between entrainment and two metrics of conversational success.

RESULTS

Speech entrainment increased throughout early adolescence but did not reach the level exhibited in conversations between adults. Additionally, speech entrainment was predictive of both conversational quality and conversational efficiency. Furthermore, models that included all acoustic features and both entrainment types performed better than models that only included individual acoustic feature sets or one type of entrainment.

CONCLUSIONS

Our findings show that speech entrainment skills are largely developed during early adolescence with continued development possibly occurring across later adolescence. Additionally, results highlight the role of speech entrainment in successful conversation in this population, suggesting the import of continued exploration of this phenomenon in both neurotypical and neurodivergent adolescents. We also provide evidence of the value of using holistic measures that capture the multidimensionality of speech entrainment and provide a validated methodology for investigating entrainment across multiple acoustic features and entrainment types.

Self-Repair Increases Referential Coordination

When interlocutors repeatedly describe referents to each other, they rapidly converge on referring expressions which become increasingly systematized and abstract as the interaction progresses. Previous experimental research suggests that interactive repair mechanisms in dialogue underpin convergence. However, this research has so far only focused on the role of other-initiated repair and has not examined whether self-initiated repair might also play a role. To investigate this question, we report the results from a computer-mediated maze task experiment. In this task, participants communicate with each other via an experimental chat tool, which selectively transforms participants' private turn-revisions into public self-repairs that are made visible to the other participant. For example, if a participant, A, types "On the top square," and then before sending, A revises the turn to "On the top row," the server automatically detects the revision and transforms the private turn-revisions into a public self-repair, for example, "On the top square umm I meant row." Participants who received these transformed turns used more abstract and systematized referring expressions, but performed worse at the task. We argue that this is due to the artificial self-repairs causing participants to put more effort into diagnosing and resolving the referential coordination problems they face in the task, yielding better grounded spatial semantics and consequently increased use of abstract referring expressions.

Caregiver linguistic alignment to autistic and typically developing children: A natural language processing approach illuminates the interactive components of language development

BACKGROUND

Language development is a highly interactive activity. However, most research on linguistic environment has focused on the quantity and complexity of linguistic input to children, with current models showing that complexity facilitates language in both typically developing (TD) and autistic children.

AIMS

After reviewing existing work on caregiver engagement of children's utterances, we aim to operationalize such engagement with automated measures of linguistic alignment, thereby providing scalable tools to assess caregivers' active reuse of their children's language. By assessing the presence of alignment, its sensitivity to the child's individual differences and how well it predicts language development beyond current models across the two groups, we showcase the usefulness of the approach and provide initial empirical foundations for further conceptual and empirical investigations.

METHODS

We measure lexical, syntactic and semantic types of caregiver alignment in a longitudinal corpus involving 32 adult-autistic child and 35 adult-TD child dyads, with children between 2 and 5 years of age. We assess the extent to which caregivers repeat their children's words, syntax, and semantics, and whether these repetitions predict language development beyond more standard predictors.

RESULTS

Caregivers tend to re-use their child's language in a way that is related to the child's individual, primarily linguistic, differences. Caregivers' alignment provides unique information improving our ability to predict future language development in both typical and autistic children.

CONCLUSIONS

We provide evidence that language development also relies on interactive conversational processes, previously understudied. We share carefully detailed methods, and open-source scripts so as to systematically extend our approach to new contexts and languages.

Distinguishing between struggling and skilled readers based on their prosodic speech patterns in oral reading: An exploratory study in grades 2 and 4

The purpose of this study was to examine if prosodic patterns in oral reading derived from Recurrence Quantification Analysis (RQA) could distinguish between struggling and skilled German readers in Grades 2 (n = 67) and 4 (n = 69). Furthermore, we investigated whether models estimated with RQA measures outperformed models estimated with prosodic features derived from prosodic transcription. According to the findings, struggling second graders appear to have a slower reading rate, longer intervals between pauses, and more repetitions of recurrent amplitudes and pauses, whereas struggling fourth graders appear to have less stable pause patterns over time, more pitch repetitions, more similar amplitude patterns over time, and more repetitions of pauses. Additionally, the models with prosodic patterns outperformed models with prosodic features. These findings suggest that the RQA approach provides additional information about prosody that complements an established approach.

Beyond speaking: neurocognitive perspectives on language production in social interaction

The human faculty to speak has evolved, so has been argued, for communicating with others and for engaging in social interactions. Hence the human cognitive system should be equipped to address the demands that social interaction places on the language production system. These demands include the need to coordinate speaking with listening, the need to integrate own (verbal) actions with the interlocutor's actions, and the need to adapt language flexibly to the interlocutor and the social context. In order to meet these demands, core processes of language production are supported by cognitive processes that enable interpersonal coordination and social cognition. To fully understand the cognitive architecture and its neural implementation enabling humans to speak in social interaction, our understanding of how humans produce language needs to be connected to our understanding of how humans gain insights into other people's mental states and coordinate in social interaction. This article reviews theories and neurocognitive experiments that make this connection and can contribute to advancing our understanding of speaking in social interaction. This article is part of a discussion meeting issue 'Face2face: advancing the science of social interaction'.

On the social nature of abstraction: cognitive implications of interaction and diversity

The human capacity for abstraction is remarkable. We effortlessly form abstract representations from varied experiences, generalizing and flexibly transferring experiences and knowledge between contexts, which can facilitate reasoning, problem solving and learning across many domains. The cognitive process of abstraction, however, is often portrayed and investigated as an individual process. This paper addresses how cognitive processes of abstraction-together with other aspects of human reasoning and problem solving-are fundamentally shaped and modulated by online social interaction. Starting from a general distinction between convergent thinking, divergent thinking and processes of abstraction, we address how social interaction shapes information processing differently depending on cognitive demands, social coordination and task ecologies. In particular, we suggest that processes of abstraction are facilitated by the interactive sharing and integration of varied individual experiences. To this end, we also discuss how the dynamics of group interactions vary as a function of group composition; that is, in terms of the similarity and diversity between the group members. We conclude by outlining the role of cognitive diversity in interactive processes and consider the importance of group diversity in processes of abstraction. This article is part of the theme issue 'Concepts in interaction: social engagement and inner experiences'.

Speaking and listening to inter-brain relationships

Studies of inter-brain relationships thrive, and yet many reservations regarding their scope and interpretation of these phenomena have been raised by the scientific community. It is thus essential to establish common ground on methodological and conceptual definitions related to this topic and to open debate about any remaining points of uncertainty. We here offer insights to improve the conceptual clarity and empirical standards offered by social neuroscience studies of inter-personal interaction using hyperscanning with a particular focus on verbal communication.

multiSyncPy: A Python package for assessing multivariate coordination dynamics

In order to support the burgeoning field of research into intra- and interpersonal synchrony, we present an open-source software package: multiSyncPy. Multivariate synchrony goes beyond the bivariate case and can be useful for quantifying how groups, teams, and families coordinate their behaviors, or estimating the degree to which multiple modalities from an individual become synchronized. Our package includes state-of-the-art multivariate methods including symbolic entropy, multidimensional recurrence quantification analysis, coherence (with an additional sum-normalized modification), the cluster-phase 'Rho' metric, and a statistical test based on the Kuramoto order parameter. We also include functions for two surrogation techniques to compare the observed coordination dynamics with chance levels and a windowing function to examine time-varying coordination for most of the measures. Taken together, our collation and presentation of these methods make the study of interpersonal synchronization and coordination dynamics applicable to larger, more complex and often more ecologically valid study designs. In this work, we summarize the relevant theoretical background and present illustrative practical examples, lessons learned, as well as guidance for the usage of our package - using synthetic as well as empirical data. Furthermore, we provide a discussion of our work and software and outline interesting further directions and perspectives. multiSyncPy is freely available under the LGPL license at: https://github.com/cslab-hub/multiSyncPy , and also available at the Python package index.

Lexical Alignment and Communicative Success in Autism Spectrum Disorder

PURPOSE

Typical speakers tend to adopt words used by their conversational partners. This "lexical alignment" enhances communication by reducing ambiguity and promoting a shared understanding of the topic under discussion. Lexical alignment has been little studied to date in autism spectrum disorder (ASD); furthermore, it has been studied primarily via structured laboratory tasks that may overestimate performance. This study examined lexical alignment in ASD during discourse and explored associations with communicative success and executive function.

METHOD

Thirty-one autistic and nonautistic adolescents were paired with a study-naïve research assistant (RA) to complete a social communication task that involved taking turns verbally instructing (guiding) the partner to navigate on a map. Lexical alignment was operationalized as the proportion of shared vocabulary produced by guides on successive maps. Task accuracy was operationalized as the pixels contained within the intended and drawn routes.

RESULTS

Results indicated that autistic adolescents had greater difficulty describing navigational routes to RAs, yielding paths that were less accurate. Alignment was reduced in autistic participants, and it was associated with path accuracy for nonautistic, but not autistic, adolescents. The association between lexical alignment and executive function missed significance (p = .05); if significant, the association would indicate that greater executive function difficulty was associated with reduced lexical alignment.

CONCLUSIONS

These findings provide preliminary evidence of reduced lexical alignment in ASD in an unstructured discourse context. Moreover, positive associations between lexical alignment and task performance in the neurotypical group raise the possibility that interventions to promote the use of shared vocabulary might support better communication.

SUPPLEMENTAL MATERIAL

https://doi.org/10.23641/asha.21313719.

Classifying Conversational Entrainment of Speech Behavior: An Expanded Framework and Review

Conversational entrainment, also known as alignment, accommodation, convergence, and coordination, is broadly defined as similarity of communicative behavior between interlocutors. Within current literature, specific terminology, definitions, and measurement approaches are wide-ranging and highly variable. As new ways of measuring and quantifying entrainment are developed and research in this area continues to expand, consistent terminology and a means of organizing entrainment research is critical, affording cohesion and assimilation of knowledge. While systems for categorizing entrainment do exist, these efforts are not entirely comprehensive in that specific measurement approaches often used within entrainment literature cannot be categorized under existing frameworks. The purpose of this review article is twofold: First, we propose an expanded version of an earlier framework which allows for the categorization of all measures of entrainment of speech behaviors and includes refinements, additions, and explanations aimed at improving its clarity and accessibility. Second, we present an extensive literature review, demonstrating how current literature fits into the given framework. We conclude with a discussion of how the proposed entrainment framework presented herein can be used to unify efforts in entrainment research.

Interpersonal Physiological Synchrony Predicts Group Cohesion

A key emergent property of group social dynamic is synchrony–the coordination of actions, emotions, or physiological processes between group members. Despite this fact and the inherent nested structure of groups, little research has assessed physiological synchronization between group members from a multi-level perspective, thus limiting a full understanding of the dynamics between members. To address this gap of knowledge we re-analyzed a large dataset (N = 261) comprising physiological and psychological data that were collected in two laboratory studies that involved two different social group tasks. In both studies, following the group task, members reported their experience of group cohesion via questionnaires. We utilized a non-linear analysis method-multidimensional recurrence quantification analysis that allowed us to represent physiological synchronization in cardiological interbeat intervals between group members at the individual-level and at the group-level. We found that across studies and their conditions, the change in physiological synchrony from baseline to group interaction predicted a psychological sense of group cohesion. This result was evident both at the individual and the group levels and was not modified by the context of the interaction. The individual- and group-level effects were highly correlated. These results indicate that the relationship between synchrony and cohesion is a multilayered construct. We re-affirm the role of physiological synchrony for cohesion in groups. Future studies are needed to crystallize our understanding of the differences and similarities between synchrony at the individual-level and synchrony at the group level to illuminate under which conditions one of these levels has primacy, or how they interact.

A systematic review and Bayesian meta-analysis of the development of turn taking in adult-child vocal interactions

Fluent conversation requires temporal organization between conversational exchanges. By performing a systematic review and Bayesian multi-level meta-analysis, we map the trajectory of infants' turn-taking abilities over the course of early development (0 to 70 months). We synthesize the evidence from 26 studies (78 estimates from 429 unique infants, of which at least 152 are female) reporting response latencies in infant-adult dyadic interactions. The data were collected between 1975 and 2019, exclusively in North America and Europe. Infants took on average circa 1 s to respond, and the evidence of changes in response over time was inconclusive. Infants' response latencies are related to those of their adult conversational partners: an increase of 1 s in adult response latency (e.g., 400 to 1400 ms) would be related to an increase of over 1 s in infant response latency (from 600 to 1857 ms). These results highlight the dynamic reciprocity involved in the temporal organization of turn-taking. Based on these results, we provide recommendations for future avenues of enquiry: studies should analyze how turn-by-turn exchanges develop on a longitudinal timescale, with rich assessment of infants' linguistic and social development.

Interbrain synchrony: on wavy ground

In recent years the study of dynamic, between-brain coupling mechanisms has taken social neuroscience by storm. In particular, interbrain synchrony (IBS) is a putative neural mechanism said to promote social interactions by enabling the functional integration of multiple brains. In this article, I argue that this research is beset with three pervasive and interrelated problems. First, the field lacks a widely accepted definition of IBS. Second, IBS wants for theories that can guide the design and interpretation of experiments. Third, a potpourri of tasks and empirical methods permits undue flexibility when testing the hypothesis. These factors synergistically undermine IBS as a theoretical construct. I finish by recommending measures that can address these issues.

Collective Rhythm as an Emergent Property During Human Social Coordination

The literature on social interactions has shown that participants coordinate not only at the behavioral but also at the physiological and neural levels, and that this coordination gives a temporal structure to the individual and social dynamics. However, it has not been fully explored whether such temporal patterns emerge during interpersonal coordination beyond dyads, whether this phenomenon arises from complex cognitive mechanisms or from relatively simple rules of behavior, or which are the sociocultural processes that underlie this phenomenon. We review the evidence for the existence of group-level rhythmic patterns that result from social interactions and argue that the complexity of group dynamics can lead to temporal regularities that cannot be predicted from the individual periodicities: an emergent collective rhythm. Moreover, we use this interpretation of the literature to discuss how taking into account the sociocultural niche in which individuals develop can help explain the seemingly divergent results that have been reported on the social influences and consequences of interpersonal coordination. We make recommendations on further research to test these arguments and their relationship to the feeling of belonging and assimilation experienced during group dynamics.

Effects of verbal tasks on driving simulator performance

We report results from a driving simulator paradigm we developed to test the fine temporal effects of verbal tasks on simultaneous tracking performance. A total of 74 undergraduate students participated in two experiments in which they controlled a cursor using the steering wheel to track a moving target and where the dependent measure was overall deviation from target. Experiment 1 tested tracking performance during slow and fast target speeds under conditions involving either no verbal input or output, passive listening to spoken prompts via headphones, or responding to spoken prompts. Experiment 2 was similar except that participants read written prompts overlain on the simulator screen instead of listening to spoken prompts. Performance in both experiments was worse during fast speeds and worst overall during responding conditions. Most significantly, fine scale time-course analysis revealed deteriorating tracking performance as participants prepared and began speaking and steadily improving performance while speaking. Additionally, post-block survey data revealed that conversation recall was best in responding conditions, and perceived difficulty increased with task complexity. Our study is the first to track temporal changes in interference at high resolution during the first hundreds of milliseconds of verbal production and comprehension. Our results are consistent with load-based theories of multitasking performance and show that language production, and, to a lesser extent, language comprehension tap resources also used for tracking. More generally, our paradigm provides a useful tool for measuring dynamical changes in tracking performance during verbal tasks due to the rapidly changing resource requirements of language production and comprehension.

Recurrence analysis of sensorimotor trajectories in a minimalist perceptual task using sonification

Active Perception perspectives claim that action is closely related to perception. An empirical approach that supports these theories is the minimalist, in which participants perform a task using an interface that provides minimal information. Their exploratory movements are crucial to generating a meaningful sequence of information. Previous studies analyzed sensorimotor trajectories describing qualitative strategies and linear quantification of participants' movement performance, but that approach struggles to capture the behavior of non-stationary data. In the present study, we applied the recurrence plot (RP) and recurrence quantification analysis (RQA) to study the structure of sensorimotor trajectories developed by participants trying to discriminate between two invisible geometric shapes (Triangle or Rectangle). The exploratory movements were made using a computer mouse and sonification-mediated feedback was provided, which depended exclusively on whether the pointer was inside or outside the shape. We applied RP and RQA to the sensorimotor trajectories, with the aim of studying their fine structure characteristics, focusing on their repetitive patterns. Recurrence analysis proved to be useful for quantifying differences in dynamic behavior that emerge when participants explore invisible virtual geometric shapes. The differences obtained in RQA-based measures associated with the vertical structures allowed to postulate the existence of particular exploration strategies for each figure. It was also possible to determine that the complexity of the dynamics changed according to the shape. We discuss these results in light of antecedents in haptic and visual perceptual exploration.

Theories of Conversation for Conversational IR

Conversational information retrieval is a relatively new and fast-developing research area, but conversation itself has been well studied for decades. Researchers have analysed linguistic phenomena such as structure and semantics but also paralinguistic features such as tone, body language, and even the physiological states of interlocutors. We tend to treat computers as social agents—especially if they have some humanlike features in their design—and so work from human-to-human conversation is highly relevant to how we think about the design of human-to-computer applications. In this article, we summarise some salient past work, focusing on social norms; structures; and affect, prosody, and style. We examine social communication theories briefly as a review to see what we have learned about how humans interact with each other and how that might pertain to agents and robots. We also discuss some implications for research and design of conversational IR systems.

Socializing Sensorimotor Contingencies

The aim of this review is to highlight the idea of grounding social cognition in sensorimotor interactions shared across agents. We discuss an action-oriented account that emerges from a broader interpretation of the concept of sensorimotor contingencies. We suggest that dynamic informational and sensorimotor coupling across agents can mediate the deployment of action-effect contingencies in social contexts. We propose this concept of socializing sensorimotor contingencies (socSMCs) as a shared framework of analysis for processes within and across brains and bodies, and their physical and social environments. In doing so, we integrate insights from different fields, including neuroscience, psychology, and research on human-robot interaction. We review studies on dynamic embodied interaction and highlight empirical findings that suggest an important role of sensorimotor and informational entrainment in social contexts. Furthermore, we discuss links to closely related concepts, such as enactivism, models of coordination dynamics and others, and clarify differences to approaches that focus on mentalizing and high-level cognitive representations. Moreover, we consider conceptual implications of rethinking cognition as social sensorimotor coupling. The insight that social cognitive phenomena like joint attention, mutual trust or empathy rely heavily on the informational and sensorimotor coupling between agents may provide novel remedies for people with disturbed social cognition and for situations of disturbed social interaction. Furthermore, our proposal has potential applications in the field of human-robot interaction where socSMCs principles might lead to more natural and intuitive interfaces for human users.

Network Connectivity Dynamics, Cognitive Biases, and the Evolution of Cultural Diversity in Round-Robin Interactive Micro-Societies

The distribution of cultural variants in a population is shaped by both neutral evolutionary dynamics and by selection pressures. The temporal dynamics of social network connectivity, that is, the order in which individuals in a population interact with each other, has been largely unexplored. In this paper, we investigate how, in a fully connected social network, connectivity dynamics, alone and in interaction with different cognitive biases, affect the evolution of cultural variants. Using agent-based computer simulations, we manipulate population connectivity dynamics (early, mid, and late full-population connectivity); content bias, or a preference for high-quality variants; coordination bias, or whether agents tend to use self-produced variants (egocentric bias), or to switch to variants observed in others (allocentric bias); and memory size, or the number of items that agents can store in their memory. We show that connectivity dynamics affect the time-course of variant spread, with lower connectivity slowing down convergence of the population onto a single cultural variant. We also show that, compared to a neutral evolutionary model, content bias accelerates convergence and amplifies the effects of connectivity dynamics, while larger memory size and coordination bias, especially egocentric bias, slow down convergence. Furthermore, connectivity dynamics affect the frequency of high-quality variants (adaptiveness), with late connectivity populations showing bursts of rapid change in adaptiveness followed by periods of relatively slower change, and early connectivity populations following a single-peak evolutionary dynamic. We evaluate our simulations against existing data collected from previous experiments and show how our model reproduces the empirical patterns of convergence.

Windowed multiscale synchrony: modeling time-varying and scale-localized interpersonal coordination dynamics

Social interactions are pervasive in human life with varying forms of interpersonal coordination emerging and spanning different modalities (e.g. behaviors, speech/language, and neurophysiology). However, during social interactions, as in any dynamical system, patterns of coordination form and dissipate at different scales. Historically, researchers have used aggregate measures to capture coordination over time. While those measures (e.g. mean relative phase, cross-correlation, coherence) have provided a wealth of information about coordination in social settings, some evidence suggests that multiscale coordination may change over the time course of a typical empirical observation. To address this gap, we demonstrate an underutilized method, windowed multiscale synchrony, that moves beyond quantifying aggregate measures of coordination by focusing on how the relative strength of coordination changes over time and the scales that comprise social interaction. This method involves using a wavelet transform to decompose time series into component frequencies (i.e. scales), preserving temporal information and then quantifying phase synchronization at each of these scales. We apply this method to both simulated and empirical interpersonal physiological and neuromechanical data. We anticipate that demonstrating this method will stimulate new insights on the mechanisms and functions of synchrony in interpersonal contexts using neurophysiological and behavioral measures.