Autistic young people adaptively use gaze to facilitate joint attention during multi-gestural dyadic interactions

LAY ABSTRACT

Autistic people have been said to have 'problems' with joint attention, that is, looking where someone else is looking. Past studies of joint attention have used tasks that require autistic people to continuously look at and respond to eye-gaze cues. But joint attention can also be done using other social cues, like pointing. This study looked at whether autistic and non-autistic young people use another person's eye gaze during joint attention in a task that did not require them to look at their partner's face. In the task, each participant worked together with their partner to find a computer-generated object in virtual reality. Sometimes the participant had to help guide their partner to the object, and other times, they followed their partner's lead. Participants were told to point to guide one another but were not told to use eye gaze. Both autistic and non-autistic participants often looked at their partner's face during joint attention interactions and were faster to respond to their partner's hand-pointing when the partner also looked at the object before pointing. This shows that autistic people can and do use information from another person's eyes, even when they don't have to. It is possible that, by not forcing autistic young people to look at their partner's face and eyes, they were better able to gather information from their partner's face when needed, without being overwhelmed. This shows how important it is to design tasks that provide autistic people with opportunities to show what they can do.

Behavioral dynamics of conversation, (mis)communication and coordination in noisy environments

During conversations people coordinate simultaneous channels of verbal and nonverbal information to hear and be heard. But the presence of background noise levels such as those found in cafes and restaurants can be a barrier to conversational success. Here, we used speech and motion-tracking to reveal the reciprocal processes people use to communicate in noisy environments. Conversations between twenty-two pairs of typical-hearing adults were elicited under different conditions of background noise, while standing or sitting around a table. With the onset of background noise, pairs rapidly adjusted their interpersonal distance and speech level, with the degree of initial change dependent on noise level and talker configuration. Following this transient phase, pairs settled into a sustaining phase in which reciprocal speech and movement-based coordination processes synergistically maintained effective communication, again with the magnitude of stability of these coordination processes covarying with noise level and talker configuration. Finally, as communication breakdowns increased at high noise levels, pairs exhibited resetting behaviors to help restore communication-decreasing interpersonal distance and/or increasing speech levels in response to communication breakdowns. Approximately 78 dB SPL defined a threshold where behavioral processes were no longer sufficient for maintaining effective conversation and communication breakdowns rapidly increased.

Dynamical biomarkers in teams and other multiagent systems

Effective team behavior in high-performance environments such as in sport and the military requires individual team members to efficiently perceive the unfolding task events, predict the actions and action intents of the other team members, and plan and execute their own actions to simultaneously accomplish individual and collective goals. To enhance team performance through effective cooperation, it is crucial to measure the situation awareness and dynamics of each team member and how they collectively impact the team's functioning. Further, to be practically useful for real-life settings, such measures must be easily obtainable from existing sensors. This paper presents several methodologies that can be used on positional and movement acceleration data of team members to quantify and/or predict team performance, assess situation awareness, and to help identify task-relevant information to support individual decision-making. Given the limited reporting of these methods within military cohorts, these methodologies are described using examples from team sports and teams training in virtual environments, with discussion as to how they can be applied to real-world military teams.

Initial phase and frequency modulations of pumping a playground swing

The playground swing is a dynamic, coupled oscillator system consisting of the swing as an object and a human as the swinger. Here, we propose a model for capturing the effect of the initial phase of natural upper body motion on the continuous pumping of a swing and validate this model from the motion data of ten participants pumping swings of three different swing chain lengths. Our model predicts that the swing pumps the most if the phase of maximum lean back, which we call the initial phase, occurs when the swing is at a vertical (midpoint) position and moving forward when the amplitude is small. As the amplitude grows, the optimal initial phase gradually shifts towards an earlier phase of the cycle, the back extreme of the swing's trajectory. As predicted by our model, all participants shifted the initial phase of their upper body movements earlier as swing amplitude increased. This indicated that swingers adjust both the frequency and initial phase of their upper body movements to successfully pump a playground swing.

Predicting and understanding human action decisions during skillful joint-action using supervised machine learning and explainable-AI

This study investigated the utility of supervised machine learning (SML) and explainable artificial intelligence (AI) techniques for modeling and understanding human decision-making during multiagent task performance. Long short-term memory (LSTM) networks were trained to predict the target selection decisions of expert and novice players completing a multiagent herding task. The results revealed that the trained LSTM models could not only accurately predict the target selection decisions of expert and novice players but that these predictions could be made at timescales that preceded a player's conscious intent. Importantly, the models were also expertise specific, in that models trained to predict the target selection decisions of experts could not accurately predict the target selection decisions of novices (and vice versa). To understand what differentiated expert and novice target selection decisions, we employed the explainable-AI technique, SHapley Additive explanation (SHAP), to identify what informational features (variables) most influenced modelpredictions. The SHAP analysis revealed that experts were more reliant on information about target direction of heading and the location of coherders (i.e., other players) compared to novices. The implications and assumptions underlying the use of SML and explainable-AI techniques for investigating and understanding human decision-making are discussed.

Conversation dynamics in a multiplayer video game with knowledge asymmetry

Despite the challenges associated with virtually mediated communication, remote collaboration is a defining characteristic of online multiplayer gaming communities. Inspired by the teamwork exhibited by players in first-person shooter games, this study investigated the verbal and behavioral coordination of four-player teams playing a cooperative online video game. The game, Desert Herding, involved teams consisting of three ground players and one drone operator tasked to locate, corral, and contain evasive robot agents scattered across a large desert environment. Ground players could move throughout the environment, while the drone operator’s role was akin to that of a “spectator” with a bird’s-eye view, with access to veridical information of the locations of teammates and the to-be-corralled agents. Categorical recurrence quantification analysis (catRQA) was used to measure the communication dynamics of teams as they completed the task. Demands on coordination were manipulated by varying the ground players’ ability to observe the environment with the use of game “fog.” Results show that catRQA was sensitive to changes to task visibility, with reductions in task visibility reorganizing how participants conversed during the game to maintain team situation awareness. The results are discussed in the context of future work that can address how team coordination can be augmented with the inclusion of artificial agents, as synthetic teammates.

Validation of deep learning-based markerless 3D pose estimation

Deep learning-based approaches to markerless 3D pose estimation are being adopted by researchers in psychology and neuroscience at an unprecedented rate. Yet many of these tools remain unvalidated. Here, we report on the validation of one increasingly popular tool (DeepLabCut) against simultaneous measurements obtained from a reference measurement system (Fastrak) with well-known performance characteristics. Our results confirm close (mm range) agreement between the two, indicating that under specific circumstances deep learning-based approaches can match more traditional motion tracking methods. Although more work needs to be done to determine their specific performance characteristics and limitations, this study should help build confidence within the research community using these new tools.

Assessing Team Effectiveness by How Players Structure Their Search in a First-Person Multiplayer Video Game

People working as a team can achieve more than when working alone due to a team's ability to parallelize the completion of tasks. In collaborative search tasks, this necessitates the formation of effective division of labor strategies to minimize redundancies in search. For such strategies to be developed, team members need to perceive the task's relevant components and how they evolve over time, as well as an understanding of what others will do so that they can structure their own behavior to contribute to the team's goal. This study explored whether the capacity for team members to coordinate effectively can be related to how participants structure their search behaviors in an online multiplayer collaborative search task. Our results demonstrated that the structure of search behavior, quantified using detrended fluctuation analysis, was sensitive to contextual factors that limit a participant's ability to gather information. Further, increases in the persistence of movement fluctuations during search behavior were found as teams developed more effective coordinative strategies and were associated with better task performance.

Herding stochastic autonomous agents via local control rules and online target selection strategies

We propose a simple yet effective set of local control rules to make a small group of “herder agents” collect and contain in a desired region a large ensemble of non-cooperative, non-flocking stochastic “target agents” in the plane. We investigate the robustness of the proposed strategies to variations of the number of target agents and the strength of the repulsive force they feel when in proximity of the herders. The effectiveness of the proposed approach is confirmed in both simulations in ROS and experiments on real robots.

Task dynamics define the contextual emergence of human corralling behaviors

Social animals have the remarkable ability to organize into collectives to achieve goals unobtainable to individual members. Equally striking is the observation that despite differences in perceptual-motor capabilities, different animals often exhibit qualitatively similar collective states of organization and coordination. Such qualitative similarities can be seen in corralling behaviors involving the encirclement of prey that are observed, for example, during collaborative hunting amongst several apex predator species living in disparate environments. Similar encirclement behaviors are also displayed by human participants in a collaborative problem-solving task involving the herding and containment of evasive artificial agents. Inspired by the functional similarities in this behavior across humans and non-human systems, this paper investigated whether the containment strategies displayed by humans emerge as a function of the task's underlying dynamics, which shape patterns of goal-directed corralling more generally. This hypothesis was tested by comparing the strategies naïve human dyads adopt during the containment of a set of evasive artificial agents across two disparate task contexts. Despite the different movement types (manual manipulation or locomotion) required in the different task contexts, the behaviors that humans display can be predicted as emergent properties of the same underlying task-dynamic model.

Gaze facilitates responsivity during hand coordinated joint attention

The coordination of attention between individuals is a fundamental part of everyday human social interaction. Previous work has focused on the role of gaze information for guiding responses during joint attention episodes. However, in many contexts, hand gestures such as pointing provide another valuable source of information about the locus of attention. The current study developed a novel virtual reality paradigm to investigate the extent to which initiator gaze information is used by responders to guide joint attention responses in the presence of more visually salient and spatially precise pointing gestures. Dyads were instructed to use pointing gestures to complete a cooperative joint attention task in a virtual environment. Eye and hand tracking enabled real-time interaction and provided objective measures of gaze and pointing behaviours. Initiators displayed gaze behaviours that were spatially congruent with the subsequent pointing gestures. Responders overtly attended to the initiator’s gaze during the joint attention episode. However, both these initiator and responder behaviours were highly variable across individuals. Critically, when responders did overtly attend to their partner’s face, their saccadic reaction times were faster when the initiator’s gaze was also congruent with the pointing gesture, and thus predictive of the joint attention location. These results indicate that humans attend to and process gaze information to facilitate joint attention responsivity, even in contexts where gaze information is implicit to the task and joint attention is explicitly cued by more spatially precise and visually salient pointing gestures.

Navigational Behavior of Humans and Deep Reinforcement Learning Agents

Rapid advances in the field of Deep Reinforcement Learning (DRL) over the past several years have led to artificial agents (AAs) capable of producing behavior that meets or exceeds human-level performance in a wide variety of tasks. However, research on DRL frequently lacks adequate discussion of the low-level dynamics of the behavior itself and instead focuses on meta-level or global-level performance metrics. In doing so, the current literature lacks perspective on the qualitative nature of AA behavior, leaving questions regarding the spatiotemporal patterning of their behavior largely unanswered. The current study explored the degree to which the navigation and route selection trajectories of DRL agents (i.e., AAs trained using DRL) through simple obstacle ridden virtual environments were equivalent (and/or different) from those produced by human agents. The second and related aim was to determine whether a task-dynamical model of human route navigation could not only be used to capture both human and DRL navigational behavior, but also to help identify whether any observed differences in the navigational trajectories of humans and DRL agents were a function of differences in the dynamical environmental couplings.

Conversational distance adaptation in noise and its effect on signal-to-noise ratio in realistic listening environments

Everyday environments impose acoustical conditions on speech communication that require interlocutors to adapt their behavior to be able to hear and to be heard. Past research has focused mainly on the adaptation of speech level, while few studies investigated how interlocutors adapt their conversational distance as a function of noise level. Similarly, no study tested the interaction between distance and speech level adaptation in noise. In the present study, participant pairs held natural conversations while binaurally listening to identical noise recordings of different realistic environments (range of 53-92 dB sound pressure level), using acoustically transparent headphones. Conversations were in standing or sitting (at a table) conditions. Interlocutor distances were tracked using wireless motion-capture equipment, which allowed subjects to move closer or farther from each other. The results show that talkers adapt their voices mainly according to the noise conditions and much less according to distance. Distance adaptation was highest in the standing condition. Consequently, mainly in the loudest environments, listeners were able to improve the signal-to-noise ratio (SNR) at the receiver location in the standing condition compared to the sitting condition, which became less negative. Analytical approximations are provided for the conversational distance as well as the receiver-related speech and SNR.

Synchronous vs. non-synchronous imitation: Using dance to explore interpersonal coordination during observational learning

Observational learning can enhance the acquisition and performance quality of complex motor skills. While an extensive body of research has focused on the benefits of synchronous (i.e., concurrent physical practice) and non-synchronous (i.e., delayed physical practice) observational learning strategies, the question remains as to whether these approaches differentially influence performance outcomes. Accordingly, we investigate the differential outcomes of synchronous and non-synchronous observational training contexts using a novel dance sequence. Using multidimensional cross-recurrence quantification analysis, movement time-series were recorded for novice dancers who either synchronised with (n = 22) or observed and then imitated (n = 20) an expert dancer. Participants performed a 16-count choreographed dance sequence for 20 trials assisted by the expert, followed by one final, unassisted performance trial. Although end-state performance did not significantly differ between synchronous and non-synchronous learners, a significant decline in performance quality from imitation to independent replication was shown for synchronous learners. A non-significant positive trend in performance accuracy was shown for non-synchronous learners. For all participants, better imitative performance across training trials led to better end-state performance, but only for the accuracy (and not timing) of movement reproduction. Collectively, the results suggest that synchronous learners came to rely on a real-time mapping process between visual input from the expert and their own visual and proprioceptive intrinsic feedback, to the detriment of learning. Thus, the act of synchronising alone does not ensure an appropriate training context for advanced sequence learning.

Hopf Bifurcations in Complex Multiagent Activity: The Signature of Discrete to Rhythmic Behavioral Transitions

Most human actions are composed of two fundamental movement types, discrete and rhythmic movements. These movement types, or primitives, are analogous to the two elemental behaviors of nonlinear dynamical systems, namely, fixed-point and limit cycle behavior, respectively. Furthermore, there is now a growing body of research demonstrating how various human actions and behaviors can be effectively modeled and understood using a small set of low-dimensional, fixed-point and limit cycle dynamical systems (differential equations). Here, we provide an overview of these dynamical motorprimitives and detail recent research demonstrating how these dynamical primitives can be used to model the task dynamics of complex multiagent behavior. More specifically, we review how a task-dynamic model of multiagent shepherding behavior, composed of rudimentary fixed-point and limit cycle dynamical primitives, can not only effectively model the behavior of cooperating human co-actors, but also reveals how the discovery and intentional use of optimal behavioral coordination during task learning is marked by a spontaneous, self-organized transition between fixed-point and limit cycle dynamics (i.e., via a Hopf bifurcation).

Co-actors Exhibit Similarity in Their Structure of Behavioural Variation That Remains Stable Across Range of Naturalistic Activities

Human behaviour, along with any natural/biological behaviour, has varying degrees of intrinsic 'noise' or variability. Many studies have shown that the structure or patterning of this variability is sensitive to changes in task and constraint. Furthermore, two or more humans interacting together often begin to exhibit similar structures of behavioural variability (i.e., the patterning of their behavioural fluctuations becomes aligned or matched) independent of any moment-to-moment synchronization (termed complexity matching). However, much of the previous work has focused on a subset of simple or contrived behaviours within the context of highly controlled laboratory tasks. In the current study, individuals and pairs performed five self-paced (unsupervised), semi-structured activities around a university campus. Empatica E4 wristbands and iPhones were used to record the participants' behavioural activity via accelerometers and GPS. The results revealed that the structure of variability in naturalistic human behaviour co-varies with the task-goal constraints, and that the patterning of the behavioural fluctuations exhibited by co-acting individuals does become aligned during the performance of everyday activities. The results also revealed that the degree of complexity matching that occurred between pairs remained invariant across activity type, indicating that this measure could be employed as a robust, task-independent index of interpersonal behaviour.

Feedback delays can enhance anticipatory synchronization in human-machine interaction

Research investigating the dynamics of coupled physical systems has demonstrated that small feedback delays can allow a dynamic response system to anticipate chaotic behavior. This counterintuitive phenomenon, termed anticipatory synchronization, has been observed in coupled electrical circuits, laser semi-conductors, and artificial neurons. Recent research indicates that the same process might also support the ability of humans to anticipate the occurrence of chaotic behavior in other individuals. Motivated by this latter work, the current study examined whether the process of feedback delay induced anticipatory synchronization could be employed to develop an interactive artificial agent capable of anticipating chaotic human movement. Results revealed that incorporating such delays within the movement-control dynamics of an artificial agent not only enhances an artificial agent’s ability to anticipate chaotic human behavior, but to synchronize with such behavior in a manner similar to natural human-human anticipatory synchronization. The implication of these findings for the development of human-machine interaction systems is discussed.

From Crowdsourcing to Extreme Citizen Science: Participatory Research for Environmental Health

Environmental health issues are becoming more challenging, and addressing them requires new approaches to research design and decision-making processes. Participatory research approaches, in which researchers and communities are involved in all aspects of a research study, can improve study outcomes and foster greater data accessibility and utility as well as increase public transparency. Here we review varied concepts of participatory research, describe how it complements and overlaps with community engagement and environmental justice, examine its intersection with emerging environmental sensor technologies, and discuss the strengths and limitations of participatory research. Although participatory research includes methodological challenges, such as biases in data collection and data quality, it has been found to increase the relevance of research questions, result in better knowledge production, and impact health policies. Improved research partnerships among government agencies, academia, and communities can increase scientific rigor, build community capacity, and produce sustainable outcomes.

Perception of another person's maximum reach-with-jump height from walking kinematics

Humans can perceive affordances (possibilities for action) for themselves and others, including the maximum overhead height reachable by jumping (reach-with-jump height, RWJ). While observers can accurately perceive maximum RWJ for another person without previously seeing the person jump, estimates improve after viewing the person walk, suggesting there is structure in walking kinematics that is informative about the ability to produce vertical force for jumping. We used principal component analysis (PCA) to identify patterns in human walking kinematics that specify another person's maximum RWJ ability, and to determine whether athletes are more sensitive than non-athletes to these patterns. Kinematic data during treadmill walking were collected and submitted to PCA to obtain loading values for the kinematic time series variables on the first principal component. Kinematic data were also used to create point-light (PL) displays, in which the movement kinematics of PL walkers were manipulated using the obtained PCA loading values to determine how changes in body-segment movements impacted perception of maximum RWJ height. While manipulating individual segmental loadings in the PL displays did not substantially affect RWJ estimates, PL displays created by replacing the PCA loadings of a high-jumper with those of a low-jumper, and vice versa, resulted in corresponding reversals of participants' RWJ estimates, suggesting that the global structure of walking kinematics carries information about another's maximum RWJ height. Athletes exhibited greater sensitivity than controls to the kinematic manipulations, indicating that they are better attuned to useful kinematic information as a result of their sport experience.

Human social motor solutions for human-machine interaction in dynamical task contexts

Multiagent activity is commonplace in everyday life and can improve the behavioral efficiency of task performance and learning. Thus, augmenting social contexts with the use of interactive virtual and robotic agents is of great interest across health, sport, and industry domains. However, the effectiveness of human-machine interaction (HMI) to effectively train humans for future social encounters depends on the ability of artificial agents to respond to human coactors in a natural, human-like manner. One way to achieve effective HMI is by developing dynamical models utilizing dynamical motor primitives (DMPs) of human multiagent coordination that not only capture the behavioral dynamics of successful human performance but also, provide a tractable control architecture for computerized agents. Previous research has demonstrated how DMPs can successfully capture human-like dynamics of simple nonsocial, single-actor movements. However, it is unclear whether DMPs can be used to model more complex multiagent task scenarios. This study tested this human-centered approach to HMI using a complex dyadic shepherding task, in which pairs of coacting agents had to work together to corral and contain small herds of virtual sheep. Human-human and human-artificial agent dyads were tested across two different task contexts. The results revealed (i) that the performance of human-human dyads was equivalent to those composed of a human and the artificial agent and (ii) that, using a "Turing-like" methodology, most participants in the HMI condition were unaware that they were working alongside an artificial agent, further validating the isomorphism of human and artificial agent behavior.

Exploring complexity matching and asynchrony dynamics in synchronized and syncopated task performances

When two people synchronize their rhythmic behaviors (e.g., finger tapping; walking) they match one another not only at a local scale of beat-to-beat intervals, but also at a global scale of the complex (fractal) patterns of variation in their interval series. This "complexity matching" had been demonstrated in a variety of timing behaviors, but the current study was designed to address two important gaps in previous research. First, very little was known about complexity matching outside of synchronization tasks. This was important because different modes are associated with differences in the strength of coordination and the fractal scaling of the task performance. Second, very little was known about the dynamics of the asynchrony series. This was important because asynchrony is a variable directly quantifying the coordination between the two timing behaviors and the task goal. So, the current study explored complexity matching in both synchronized and syncopated finger tapping tasks, and included analyses of the fractal scaling of the asynchrony series. Participants completed an interpersonal finger tapping task, in both synchronization and syncopation conditions. The magnitude of variation and the exact power law scaling of the tapping intervals were manipulated by having one participant tap in time with a metronome. Complexity matching was most stable when there was sufficient variation in the task behavior and when a persistent scaling dynamic was presented. There were, however, several interesting differences between the two coordination modes, in terms of the heterogeneity of the complexity matching effect and the scaling of the asynchronies. These findings raised a number of important points concerning how to approach and understand the interaction of inherently complex systems.

Terrestrial support of aquatic food webs depends on light inputs: a geographically-replicated test using tank bromeliads

Food webs of freshwater ecosystems can be subsidized by allochthonous resources. However, it is still unknown which environmental factors regulate the relative consumption of allochthonous resources in relation to autochthonous resources. Here, we evaluated the importance of allochthonous resources (litterfall) for the aquatic food webs in Neotropical tank bromeliads, a naturally replicated aquatic microcosm. Aquatic invertebrates were sampled in more than 100 bromeliads within either open or shaded habitats and within five geographically distinct sites located in four different countries. Using stable isotope analyses, we determined that allochthonous sources comprised 74% (±17%) of the food resources of aquatic invertebrates. However, the allochthonous contribution to aquatic invertebrates strongly decreased from shaded to open habitats, as light incidence increased in the tanks. The density of detritus in the tanks had no impact on the importance of allochthonous sources to aquatic invertebrates. This overall pattern held for all invertebrates, irrespective of the taxonomic or functional group to which they belonged. We concluded that, over a broad geographic range, aquatic food webs of tank bromeliads are mostly allochthonous-based, but the relative importance of allochthonous subsidies decreases when light incidence favors autochthonous primary production. These results suggest that, for other freshwater systems, some of the between-study variation in the importance of allochthonous subsidies may similarly be driven by the relative availability of autochthonous resources.

Social Motor Synchronization: Insights for Understanding Social Behavior in Autism

Impairments in social interaction and communication are critical features of ASD but the underlying processes are poorly understood. An under-explored area is the social motor synchronization that happens when we coordinate our bodies with others. Here, we explored the relationships between dynamical measures of social motor synchronization and assessments of ASD traits. We found (a) spontaneous social motor synchronization was associated with responding to joint attention, cooperation, and theory of mind while intentional social motor synchronization was associated with initiating joint attention and theory of mind; and (b) social motor synchronization was associated with ASD severity but not fully explained by motor problems. Findings suggest that objective measures of social motor synchronization may provide insights into understanding ASD traits.

Virtual Reality As a Training Tool to Treat Physical Inactivity in Children

Lack of adequate physical activity in children is an epidemic that can result in obesity and other poor health outcomes across the lifespan. Physical activity interventions focused on motor skill competence continue to be developed, but some interventions, such as neuromuscular training (NMT), may be limited in how early they can be implemented due to dependence on the child's level of cognitive and perceptual-motor development. Early implementation of motor-rich activities that support motor skill development in children is critical for the development of healthy levels of physical activity that carry through into adulthood. Virtual reality (VR) training may be beneficial in this regard. VR training, when grounded in an information-based theory of perceptual-motor behavior that modifies the visual information in the virtual world, can promote early development of motor skills in youth akin to more natural, real-world development as opposed to strictly formalized training. This approach can be tailored to the individual child and training scenarios can increase in complexity as the child develops. Ultimately, training in VR may help serve as a precursor to "real-world" NMT, and once the child reaches the appropriate training age can also augment more complex NMT regimens performed outside of the virtual environment.

Creating Time: Social Collaboration in Music Improvisation

Musical collaboration emerges from the complex interaction of environmental and informational constraints, including those of the instruments and the performance context. Music improvisation in particular is more like everyday interaction in that dynamics emerge spontaneously without a rehearsed score or script. We examined how the structure of the musical context affords and shapes interactions between improvising musicians. Six pairs of professional piano players improvised with two different backing tracks while we recorded both the music produced and the movements of their heads, left arms, and right arms. The backing tracks varied in rhythmic and harmonic information, from a chord progression to a continuous drone. Differences in movement coordination and playing behavior were evaluated using the mathematical tools of complex dynamical systems, with the aim of uncovering the multiscale dynamics that characterize musical collaboration. Collectively, the findings indicated that each backing track afforded the emergence of different patterns of coordination with respect to how the musicians played together, how they moved together, as well as their experience collaborating with each other. Additionally, listeners' experiences of the music when rating audio recordings of the improvised performances were related to the way the musicians coordinated both their playing behavior and their bodily movements. Accordingly, the study revealed how complex dynamical systems methods (namely recurrence analysis) can capture the turn-taking dynamics that characterized both the social exchange of the music improvisation and the sounds of collaboration more generally. The study also demonstrated how musical improvisation provides a way of understanding how social interaction emerges from the structure of the behavioral task context.

Metacognitive deficits in categorization tasks in a population with impaired inner speech

This study examines the relation of language use to a person's ability to perform categorization tasks and to assess their own abilities in those categorization tasks. A silent rhyming task was used to confirm that a group of people with post-stroke aphasia (PWA) had corresponding covert language production (or "inner speech") impairments. The performance of the PWA was then compared to that of age- and education-matched healthy controls on three kinds of categorization tasks and on metacognitive self-assessments of their performance on those tasks. The PWA showed no deficits in their ability to categorize objects for any of the three trial types (visual, thematic, and categorial). However, on the categorial trials, their metacognitive assessments of whether they had categorized correctly were less reliable than those of the control group. The categorial trials were distinguished from the others by the fact that the categorization could not be based on some immediately perceptible feature or on the objects' being found together in a type of scenario or setting. This result offers preliminary evidence for a link between covert language use and a specific form of metacognition.

Evaluating the importance of social motor synchronization and motor skill for understanding autism

Impairments in social interaction and communicating with others are core features of autism spectrum disorder (ASD), but the specific processes underlying such social competence impairments are not well understood. An important key for increasing our understanding of ASD-specific social deficits may lie with the social motor synchronization that takes place when we implicitly coordinate our bodies with others. Here, we tested whether dynamical measures of synchronization differentiate children with ASD from controls and further explored the relationships between synchronization ability and motor control problems. We found (a) that children with ASD exhibited different and less stable patterns of social synchronization ability than controls; (b) children with ASD performed motor movements that were slower and more variable in both spacing and timing; and (c) some social synchronization that involved motor timing was related to motor ability but less rhythmic synchronization was not. These findings raise the possibility that objective dynamical measures of synchronization ability and motor skill could provide new insights into understanding the social deficits in ASD that could ultimately aid clinical diagnosis and prognosis. Autism Res 2017, 10: 1687-1699. © 2017 International Society for Autism Research, Wiley Periodicals, Inc.

Influence of stimulus velocity profile on unintentional visuomotor entrainment depends on eye movements

Humans spontaneously entrain their movements to visual rhythms in the environment. Previous research has shown that the strength of such unintentional visuomotor entrainment is enhanced when observing rhythms characterized by the nonlinear, Rayleigh kinematics typical of human movements; such movements are characterized by greater slowness towards the trajectory turning points compared to sinusoidal movements. However, the enhanced unintentional entrainment to rhythms exhibiting Rayleigh kinematics has only been shown to occur when participants tracked stimulus movements with their eyes, which might have facilitated access to important information for enhanced entrainment. The current study compared the strength of unintentional visuomotor entrainment with both Rayleigh and sinusoidal kinematics when participants were either tracking (eye following the oscillating stimulus) or non-tracking (eye fixed at the centre of the stimulus trajectory) stimulus movements. The results showed that enhanced unintentional entrainment with Rayleigh stimuli only occurred with eye-tracking, supporting that slowness of rhythmic movements towards turning points facilitate entrainment and that access to this information depends on eye movements.

To Pass or Not to Pass: Modeling the Movement and Affordance Dynamics of a Pick and Place Task

Humans commonly engage in tasks that require or are made more efficient by coordinating with other humans. In this paper we introduce a task dynamics approach for modeling multi-agent interaction and decision making in a pick and place task where an agent must move an object from one location to another and decide whether to act alone or with a partner. Our aims were to identify and model (1) the affordance related dynamics that define an actor's choice to move an object alone or to pass it to their co-actor and (2) the trajectory dynamics of an actor's hand movements when moving to grasp, relocate, or pass the object. Using a virtual reality pick and place task, we demonstrate that both the decision to pass or not pass an object and the movement trajectories of the participants can be characterized in terms of a behavioral dynamics model. Simulations suggest that the proposed behavioral dynamics model exhibits features observed in human participants including hysteresis in decision making, non-straight line trajectories, and non-constant velocity profiles. The proposed model highlights how the same low-dimensional behavioral dynamics can operate to constrain multiple (and often nested) levels of human activity and suggests that knowledge of what, when, where and how to move or act during pick and place behavior may be defined by these low dimensional task dynamics and, thus, can emerge spontaneously and in real-time with little a priori planning.

Herd Those Sheep: Emergent Multiagent Coordination and Behavioral-Mode Switching

Effectively coordinating one's behaviors with those of others is essential for successful multiagent activity. In recent years, increased attention has been given to understanding the dynamical principles that underlie such coordination because of a growing interest in behavioral synchrony and complex-systems phenomena. Here, we examined the behavioral dynamics of a novel, multiagent shepherding task, in which pairs of individuals had to corral small herds of virtual sheep in the center of a virtual game field. Initially, all pairs adopted a complementary, search-and-recover mode of behavioral coordination, in which both members corralled sheep predominantly on their own sides of the field. Over the course of game play, however, a significant number of pairs spontaneously discovered a more effective mode of behavior: coupled oscillatory containment, in which both members synchronously oscillated around the sheep. Analysis and modeling revealed that both modes were defined by the task's underlying dynamics and, moreover, reflected context-specific realizations of the lawful dynamics that define functional shepherding behavior more generally.

Effects of Agent-Environment Symmetry on the Coordination Dynamics of Triadic Jumping

We investigated whether the patterns of coordination that emerged during a three-participant (triadic) jumping task were defined by the symmetries of the (multi) agent-environment task space. Triads were instructed to jump around different geometrical arrangements of hoops. The symmetry of the hoop geometry was manipulated to create two symmetrical and two asymmetrical participant-hoop configurations. Video and motion tracking recordings were employed to determine the frequencies of coordination misses (collisions or failed jumps) and during 20 successful jump sequences, the jump direction chosen (clockwise vs. counterclockwise) and the patterning of between participant temporal movement lags within and across jump events. The results revealed that the (a)symmetry of the joint action workspace significantly influenced the (a)symmetry of the jump direction dynamics and, more importantly, the (a)symmetry of the between participant coordination lags. The symmetrical participant-hoop configurations resulted in smaller overall movement lags and a more spontaneous, interchangeable leader/follower relationship between participants, whereas the asymmetrical participant-hoop configurations resulted in slightly larger overall movements lags and a more explicit, persistent asymmetry in the leader/follower relationship of participants. The degree to which the patterns of behavioral coordination that emerged were consistent with the theory of symmetry groups and spontaneous and explicit symmetry-breaking are discussed.

The database of the PREDICTS (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems) project

The PREDICTS project-Projecting Responses of Ecological Diversity In Changing Terrestrial Systems (www.predicts.org.uk)-has collated from published studies a large, reasonably representative database of comparable samples of biodiversity from multiple sites that differ in the nature or intensity of human impacts relating to land use. We have used this evidence base to develop global and regional statistical models of how local biodiversity responds to these measures. We describe and make freely available this 2016 release of the database, containing more than 3.2 million records sampled at over 26,000 locations and representing over 47,000 species. We outline how the database can help in answering a range of questions in ecology and conservation biology. To our knowledge, this is the largest and most geographically and taxonomically representative database of spatial comparisons of biodiversity that has been collated to date; it will be useful to researchers and international efforts wishing to model and understand the global status of biodiversity.

Components of Population Vulnerability and Their Relationship With Climate-Sensitive Health Threats

Climate change is increasingly being framed as risks that will impact the poorest and most vulnerable communities among us. This has led to more efforts to estimate climate change risks across populations and in the context of human health and health equity. We describe the public health dimensions of climate vulnerability-exposure, population sensitivity, and adaptive capacity-and explore how these dimensions can modify population health impacts and their distribution. An overview of health disparities associated with specific climate risks is presented, and we offer potential solutions grounded in equitable urban development and improved characterization of climate vulnerabilities.

Complexity matching effects in bimanual and interpersonal syncopated finger tapping

The current study was designed to investigate complexity matching during syncopated behavioral coordination. Participants either tapped in (bimanual) syncopation using their two hands, or tapped in (interpersonal) syncopation with a partner, with each participant using one of their hands. The time series of inter-tap intervals (ITI) from each hand were submitted to fractal analysis, as well as to short-term and multi-timescale cross-correlation analyses. The results demonstrated that the fractal scaling of one hand's ITI was strongly correlated to that of the other hand, and this complexity matching effect was stronger in the bimanual condition than in the interpersonal condition. Moreover, the degree of complexity matching was predicted by the strength of short-term cross-correlation and the stability of the asynchrony between the two tapping series. These results suggest that complexity matching is not specific to the inphase synchronization tasks used in past research, but is a general result of coordination between complex systems.

Beliefs as Self-Sustaining Networks: Drawing Parallels Between Networks of Ecosystems and Adults' Predictions

In this paper, we argue that beliefs share common properties with the self-sustaining networks of complex systems. Matching experiences are said to couple with each other into a mutually reinforcing network. The goal of the current paper is to spell out and develop these ideas, using our understanding of ecosystems as a guide. In Part 1 of the paper, we provide theoretical considerations relevant to this new conceptualization of beliefs, including the theoretical overlap between energy and meaning. In Part 2, we discuss the implications of this new conceptualization on our understanding of belief emergence and belief change. Finally, in Part 3, we provide an analytical mapping between beliefs and the self-sustaining networks of ecosystems, namely by applying to behavioral data a measure developed for ecosystem networks. Specifically, average accuracies were subjected to analyses of uncertainty (H) and average mutual information. The ratio between these two values yields degree of order, a measure of how organized the self-sustained network is. Degree of order was tracked over time and compared to the amount of explained variance returned by a categorical non-linear principal components analysis. Finding high correspondence between the two measures of order, together with the theoretical groundwork discussed in Parts 1 and 2, lends preliminary validity to our theory that beliefs have important similarities to the structural characteristics of self-sustaining networks.

Can discrete joint action be synergistic? Studying the stabilization of interpersonal hand coordination

The human perceptual-motor system is tightly coupled to the physical and informational dynamics of a task environment. These dynamics operate to constrain the high-dimensional order of the human movement system into low-dimensional, task-specific synergies-functional groupings of structural elements that are temporarily constrained to act as a single coordinated unit. The aim of the current study was to determine whether synergistic processes operate when coacting individuals coordinate to perform a discrete joint-action task. Pairs of participants sat next to each other and each used 1 arm to complete a pointer-to-target task. Using the uncontrolled manifold (UCM) analysis for the first time in a discrete joint action, the structure of joint-angle variance was examined to determine whether there was synergistic organization of the degrees of freedom employed at the interpersonal or intrapersonal levels. The results revealed that the motor actions performed by coactors were synergistically organized at both the interpersonal and intrapersonal levels. More importantly, however, the interpersonal synergy was found to be significantly stronger than the intrapersonal synergies. Accordingly, the results provide clear evidence that coacting individuals can become temporarily organized to form single synergistic 2-person systems during performance of a discrete joint action.

Dominant predators mediate the impact of habitat size on trophic structure in bromeliad invertebrate communities

Local habitat size has been shown to influence colonization and extinction processes of species in patchy environments. However, species differ in body size, mobility, and trophic level, and may not respond in the same way to habitat size. Thus far, we have a limited understanding of how habitat size influences the structure of multitrophic communities and to what extent the effects may be generalizable over a broad geographic range. Here, we used water-filled bromeliads of different sizes as a natural model system to examine the effects of habitat size on the trophic structure of their inhabiting invertebrate communities. We collected composition and biomass data from 651 bromeliad communities from eight sites across Central and South America differing in environmental conditions, species pools, and the presence of large-bodied odonate predators. We found that trophic structure in the communities changed dramatically with changes in habitat (bromeliad) size. Detritivore : resource ratios showed a consistent negative relationship with habitat size across sites. In contrast, changes in predator: detritivore (prey) ratios depended on the presence of odonates as dominant predators in the regional pool. At sites without odonates, predator: detritivore biomass ratios decreased with increasing habitat size. At sites with odonates, we found odonates to be more frequently present in large than in small bromeliads, and predator: detritivore biomass ratios increased with increasing habitat size to the point where some trophic pyramids became inverted. Our results show that the distribution of biomass amongst food-web levels depends strongly on habitat size, largely irrespective of geographic differences in environmental conditions or detritivore species compositions. However, the presence of large-bodied predators in the regional species pool may fundamentally alter this relationship between habitat size and trophic structure. We conclude that taking into account the response and multitrophic effects of dominant, mobile species may be critical when predicting changes in community structure along a habitat-size gradient.