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The seemingly straightforward task of tying one's shoes requires a sophisticated interplay of joints, muscles, and neural pathways, posing a formidable challenge for researchers studying the intricacies of coordination. A widely accepted framework for measuring coordinated behavior is the Haken-Kelso-Bunz (HKB) model. However, a significant limitation of this model is its lack of accounting for the diverse variability structures inherent in the coordinated systems it frequently models. Variability is a pervasive phenomenon across various biological and physical systems, and it changes in healthy adults, older adults, and pathological populations. Here, we show, both empirically and with simulations, that manipulating the variability in coordinated movements significantly impacts the ability to change coordination patterns-a fundamental feature of the HKB model. Our results demonstrate that synchronized bimanual coordination, mirroring a state of healthy variability, instigates earlier transitions of coordinated movements compared to other variability conditions. This suggests a heightened adaptability when movements possess a healthy variability. We anticipate our study to show the necessity of adapting the HKB model to encompass variability, particularly in predictive applications such as neuroimaging, cognition, skill development, biomechanics, and beyond.

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Over two decades have passed since the publication of van Gelder's (1998) "dynamical hypothesis." In that paper, van Gelder proposed that cognitive agents were not digital computers-per the representational computational approach-but dynamical systems. The evolution of the dynamical hypothesis was driven by parallel advances in three areas. Theoretically, a deeper understanding of genetics, biology, neuroscience, and cognitive science inspired questions about how systems within each domain dynamically interact and extend their effects across spatiotemporal scales. Methodologically, more sophisticated and domain-general tools allowed researchers to discover, model, and quantify system dynamics, structure, and patterns across multiple scales to generate a more comprehensive system-level understanding of behaviors. Empirically, we can analyze a system's behavior while preserving its natural dynamics, revealing evidence that the reductionist approach leads to an incomplete understanding of the components and the overall system. Researchers have traditionally reduced a complex system into its component processes and assumed that the parts can be recombined to explain the whole. These three advances fundamentally altered our understanding of a "cognitive agent:" How their behaviors are driven by long-range coordination across multiple processes, how the interdependent and nested structure of interacting variables produces behaviors that are greater than the sum of its parts, and how environmental constraints shape adaptive yet stable behavioral patterns.

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Free-recall tasks suggest human memory foraging may follow a heavy-tailed distribution, such as a Lévy flight, patch foraging, or area-restricted search - walk procedures that are common in other activities of cognitive agents, such as food foraging in both animals and humans. To date, research merely equates memory foraging with hunting in the physical world based on similarities in statistical structure. The current work supports that memory foraging follows a heavy-tailed distribution by using categories with quantitative distances between each item: countries, which have physical distances, and animals, from which cognitive distances can be derived using a multidimensional scaling (MDS) procedure. Likewise, inter-item lag times follow a heavy-tailed distribution. The current work also demonstrates that inter-item distances and times are positively correlated, suggesting the organization of items in memory may be akin to the organization of a physical landscape. Finally, both studies show that participants' original, heavy-tailed lists of countries and animal names produce shorter overall distances traveled than random selection. Human memory foraging follows the same pattern as foraging in the natural world - perhaps because exposure to ecological settings informs our inner cognitive experience - leading to a processing and retrieval time benefit.

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Variability is commonly observed in complex behavior, such as the maintenance of upright posture. The current study examines the value added by using nonlinear measures of variability to identify dynamic stability instead of linear measures that reflect average fluctuations about a mean state. The largest Lyapunov exponent (λ1) and SD were calculated on mediolateral movement as participants performed a sit-to-stand task on a stable and unstable platform. Both measures identified changes in movement across postures, but results diverged when participants stood on the unstable platform. Large SD indicated an increase in movement variability, but small λ1 identified those movements as stable and controlled. The results suggest that a combination of linear and nonlinear analyses is useful in identifying the proportion of observed variability that may be attributed to structured, controlled sources. Nonlinear measures of variability, like λ1, can further be used to make predictions about transitions between stable postures and to identify a system's resistance to disruption from external perturbations. Those features make nonlinear analyses highly applicable to both human movement research and clinical practice.

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The common practice of standardizing foot placement in postural research and in clinical practice may serve to increase postural sway. The focus of this study was to investigate foot placement strategies in the tandem (anteroposterior, AP) and side-to-side (mediolateral, ML) stance in healthy adults. Foot placement was either experimenter-controlled or selected by the participant. Greater sway was observed for the AP stance than the ML stance, where sway was minimal. When foot placement was self-selected, participants recruited additional degrees of freedom by rotating both feet outward to expand the base of support; they narrowed their stance width in the AP stance only. Self-selection served to decrease AP sway for the AP stance and increase ML sway for both the AP and ML stances. A dynamical measure, the largest Lyapunov exponent, supported the finding that self-selection of foot placement serves to stabilize posture. The implication is that improvements in postural control were due primarily to self-selection of foot placement and not to adjustments in stance width. Experimental and perhaps clinical procedures should be revised to allow participants to self-select foot placement during postural tasks.

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The maintenance of upright posture involves constant adjustment to external and internal perturbations. This balancing act is often assumed to be an automatic process, but studies suggest that cognitive processes, particularly attention, are necessary for the control of posture. The current study examines the role of attention in balance using a dual-task paradigm. Twenty-four healthy young adults performed a sit-to-stand (STS) task on either a stable or unstable platform while performing a secondary cognitive task of counting backwards aloud. Movement of the upper and lower body was analyzed using the largest Lyapunov exponent (λ1) and standard deviation (SD). Results replicated earlier findings (Gibbons, Amazeen, & Likens, 2018) that the transition from sit to stand was marked by increased variability and a temporary destabilization of postural control. Participants exhibited greater movement variability overall on the unstable platform (large SD), but small λ1 indicated that movement was controlled. During second task performance, SD increased for the upper body only. Further research is necessary to understand the interaction between attention and balance in young adults.

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In activities such as dancing and sports, people synchronize behaviors in many different ways. Synchronization between people has traditionally been characterized as either perfect mirroring (1:1 in-phase synchronization, spontaneous synchrony, and mimicry) or reflectional mirroring (1:1 antiphase synchronization), but most activities require partners to synchronize more complicated patterns. We asked visually coupled dyads to coordinate finger movements to perform multifrequency ratios (1:1, 2:1, 3:1, 4:1, and 5:1). Because these patterns are coordinated across and not just within individual physiological and motor systems, we based our predictions on frequency-locking dynamics, which is a general coordination principle that is not limited to physiological explanations. Twenty dyads performed five multifrequency ratios under three levels of visual coupling, with half using a subcritical visual information update rate. The dynamical principle was supported, such that multifrequency performance tends to abide by the strictures of frequency locking. However, these constraints are relaxed if the visual information rate is beyond the critical information update rate. An analysis of turning points in the oscillatory finger movements suggested that dyads did not rely on this visual information to stabilize coordination. How the laboratory findings align with naturalistic observations of multifrequency performance in actual sports teams (Double Dutch) is discussed. Frequency-locking accounts not only for the human propensity for perfect mirroring but also for variations in performance when dyads deviate from mirroring.

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Researchers generally agree that perceived heaviness is based on the actions associated with unsupported holding. Psychophysical research has supported this idea, as has psychophysiological research connecting muscle activity to the perceptions of heaviness and effort. However, the role of muscle activity in the context of the resulting motions has not been investigated. In the present study, perceptions of heaviness were recorded along with the electromyogram (EMG) of the lifting muscle and peak acceleration of the lift. Consistent with predictions derived from Newton's Second Law of motion (Force=Mass × Acceleration), normal and illusory perceptions of heaviness were a function of the ratio of muscle activity to lifting acceleration. These results identify a psychophysiological mechanism for heaviness perception based on the forces and motions associated with unsupported holding.

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OBJECTIVE: We investigated cross-level effects, which are concurrent changes across neural and cognitive-behavioral levels of analysis as teams interact, between neurophysiology and team communication variables under variations in team training. BACKGROUND: When people work together as a team, they develop neural, cognitive, and behavioral patterns that they would not develop individually. It is currently unknown whether these patterns are associated with each other in the form of cross-level effects. METHOD: Team-level neurophysiology and latent semantic analysis communication data were collected from submarine teams in a training simulation. We analyzed whether (a) both neural and communication variables change together in response to changes in training segments (briefing, scenario, or debriefing), (b) neural and communication variables mutually discriminate teams of different experience levels, and (c) peak cross-correlations between neural and communication variables identify how the levels are linked. RESULTS: Changes in training segment led to changes in both neural and communication variables, neural and communication variables mutually discriminated between teams of different experience levels, and peak cross-correlations indicated that changes in communication precede changes in neural patterns in more experienced teams. CONCLUSION: Cross-level effects suggest that teamwork is not reducible to a fundamental level of analysis and that training effects are spread out across neural and cognitive-behavioral levels of analysis. Cross-level effects are important to consider for theories of team performance and practical aspects of team training. APPLICATION: Cross-level effects suggest that measurements could be taken at one level (e.g., neural) to assess team experience (or skill) on another level (e.g., cognitive-behavioral).

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The list of psychological processes thought to exhibit fractal behavior is growing. Although some might argue that the seeming ubiquity of fractal patterns illustrates their significance, unchecked growth of that list jeopardizes their relevance. It is important to identify when a single behavior is and is not fractal in order to make meaningful conclusions about the processes underlying those patterns. The hypothesis tested in the present experiment is that fractal patterns reflect the enactment of control. Participants performed two steering tasks: steering on a straight track and steering on a circular track. Although each task could be accomplished by holding the steering wheel at a constant angle, steering around a curve may require more constant control, at least from a psychological standpoint. Results showed that evidence for fractal behavior was strongest for the circular track; straight tracks showed evidence of two scaling regions. We argue from those results that, going forward, the goal of the fractal literature should be to bring scaling behavior under experimental control.

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Rhythmic coordination with stimuli and other people's movements containing variable or unpredictable fluctuations might involve distinct processes: detecting the fluctuation structure and tuning to or matching the structure's temporal complexity. This framework predicts that global tuning and local parameter adjustments (e.g., position, velocity or phase) can operate independently during coordination (Marmelat & Delignières, 2012). Alternatively, we propose that complexity matching is a result of local phase adjustments during coordination (Delignières & Marmelat, 2014; Torre, Varlet, & Marmelat, 2013). The current study examined this relationship in a rhythmic interpersonal coordination task. Dyads coordinated swinging pendulums that differed in their uncoupled frequencies (detuning). We predicted that frequency detuning would require increased local corrections to maintain the intended phase pattern (in phase). This was expected to yield a relative phase shift accompanied by a change in period complexity and matching. Experimental data and numerical modeling of the pendulum dynamics confirmed our predictions. Increased relative phase shifts occurred simultaneously with increased dissociation between individuals' movement period complexity. This provided evidence that global complexity matching is intricately linked to local movement adjustments and is not a distinct coordination mechanism. These findings are considered with respect to dynamical and computational approaches to interpersonal coordination.

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The quality of a team depends on its ability to deliver information through a hierarchy of team members and negotiate processes spanning different time scales. That structure and the behavior that results from it pose problems for researchers because multiply-nested interactions are not easily separated. We explored the behavior of a six-person team engaged in a Submarine Piloting and Navigation (SPAN) task using the tools of dynamical systems. The data were a single entropy time series that showed the distribution of activity across six team members, as recorded by nine-channel electroencephalography (EEG). A single team's data were analyzed for the purposes of illustrating the utility of multifractal analysis and allowing for in-depth exploratory analysis of temporal characteristics. Could the meaningful events experienced by one of these teams be captured using multifractal analysis, a dynamical systems tool that is specifically designed to extract patterns across levels of analysis? Results indicate that nested patterns of team activity can be identified from neural data streams, including both routine and novel events. The novelty of this tool is the ability to identify social patterns from the brain activity of individuals in the social interaction. Implications for application and future directions of this research are discussed.

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Motor-respiratory coordination occurs naturally during exercise, but the number of coordination patterns performed between movement and breathing is limited. We investigated whether participants could acquire novel ratios (either 5:2 or 5:3). To examine complex temporal relationships between movement and breathing, we used lagged return plots that were produced by graphing relative phase against relative phase after a time delay. By the end of practice, participants performed 5:2 consistently and performed 5:3 using more stable ratios (3:2 and 2:1). Lagged return plots revealed that 5:3 learners harnessed the stable inphase and antiphase patterns to stabilize the required ratio. That strategy resulted in the performance of smaller-integer ratios in the production of 5:3 but not 5:2. Despite those differences, there was positive transfer to unpracticed ratios that was similar in both learning conditions. The time series analysis of lagged return plots revealed differences in ratio performance at transfer. Ratios whose component frequencies were farther apart, like 7:2, were performed consistently, while ratios whose component frequencies were more similar, like 5:4, elicited attraction to inphase and antiphase. The implication is that participants can combine more stable chunks of rhythmic behavior to produce more complex ratios.

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OBJECTIVE: Recurrence-based measures of communication determinism and pattern information are described and validated using previously collected team interaction data. BACKGROUND: Team coordination dynamics has revealed that"mixing" team membership can lead to flexible interaction processes, but keeping a team "intact" can lead to rigid interaction processes. We hypothesized that communication of intact teams would have greater determinism and higher pattern information compared to that of mixed teams. METHOD: Determinism and pattern information were measured from three-person Uninhabited Air Vehicle team communication sequences over a series of 40-minute missions. Because team members communicated using push-to-talk buttons, communication sequences were automatically generated during each mission. RESULTS: The Composition x Mission determinism effect was significant. Intact teams' determinism increased over missions, whereas mixed teams' determinism did not change. Intact teams had significantly higher maximum pattern information than mixed teams. CONCLUSION: Results from these new communication analysis methods converge with content-based methods and support our hypotheses. APPLICATION: Because they are not content based, and because they are automatic and fast, these new methods may be amenable to real-time communication pattern analysis.

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Dynamical systems methods characterise patterns of change over time. Typically, such methods are applied only after data collection is complete. However, brief disturbances - perturbations - can occur as a process unfolds and can result in undesirable outcomes if not acted on. The application of dynamics in real time would be useful for detecting these sudden changes. Real-time analysis was accomplished by updating dynamical estimates simultaneously across different window sizes. We calculated the largest Lyapunov exponent, a measure of dynamical stability, to detect a perturbation to team communication in a simulated uninhabited air vehicle (UAV) reconnaissance mission. The perturbation consisted of information demands from a confederate that occurred unexpectedly during performance of a UAV mission. We demonstrate the use of real-time methods in detecting that perturbation as it occurred. In application, this technique would have enabled real-time intervention. Extensions of the real-time dynamical method to other domains of psychological inquiry are discussed. PRACTITIONER SUMMARY: A real-time dynamical analysis method that was developed to detect unexpected perturbations in team communication is described. The use of the method is demonstrated on perturbed communication from a three-person uninhabited air vehicle command-and-control team. The generalisability of the method is considered with respect to physiological and motor coordination dynamics.

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Controversy surrounds questions regarding the influence of being gender consistent (i.e., having and expressing gendered characteristics that are consistent with one's biological sex) versus being gender flexible (i.e., having and expressing gendered characteristics that vary from masculine to feminine as circumstances arise) on children's adjustment outcomes, such as self-esteem, positive emotion, or behavior problems. Whereas evidence supporting the consistency hypothesis is abundant, little support exists for the flexibility hypothesis. To shed new light on the flexibility hypothesis, we explored children's gendered behavior from a dynamical perspective that highlighted variability and flexibility in addition to employing a conventional approach that emphasized stability and consistency. Conventional mean-level analyses supported the consistency hypothesis by revealing that gender atypical behavior was related to greater maladjustment, and dynamical analyses supported the flexibility hypothesis by showing that flexibility of gendered behavior over time was related to positive adjustment. Integrated analyses showed that gender typical behavior was related to the adjustment of children who were behaviorally inflexible, but not for those who were flexible. These results provided a more comprehensive understanding of the relation between gendered behavior and adjustment in young children and illustrated for the first time the feasibility of applying dynamical analyses to the study of gendered behavior.

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Variability of repeated measurements in human performances exhibits fractal 1/ƒ noise. Yet the relative strength of this fractal pattern varies widely across conditions, tasks, and individuals. Four experiments illustrate how subtle details of the conditions of measurement change the fractal patterns observed across task conditions. The results call into question whether measurement noise and measured signal can be distinguished in human performance, suggesting that human performance is inextricably entangled with measurement context. Perhaps, though, a hypothesis of soft assembly of human performance can circumvent the conundrum (e.g., Turvey, 2007).

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OBJECTIVE: We report an experiment in which three training approaches are compared with the goal of training adaptive teams. BACKGROUND: Cross-training is an established method in which team members are trained with the goal of building shared knowledge. Perturbation training is a new method in which team interactions are constrained to provide new coordination experiences during task acquisition. These two approaches, and a more traditional procedural approach, are compared. METHOD: Assigned to three training conditions were 26 teams. Teams flew nine simulated uninhabited air vehicle missions; three were critical tests of the team's ability to adapt to novel situations. Team performance, response time to novel events, and shared knowledge were measured. RESULTS: Perturbation-trained teams significantly outperformed teams in the other conditions in two out of three critical test missions. Cross-training resulted in significant increases in shared teamwork knowledge and highest mean performance in one critical test. Procedural training led to the least adaptive teams. CONCLUSION: Perturbation training allows teams to match coordination variability during training to demands for coordination variability during posttraining performance. Although cross-training has adaptive benefits, it is suggested that process-oriented approaches, such as perturbation training, can lead to more adaptive teams. APPLICATION: Perturbation training is amenable to simulation-based training, where perturbations provide interaction experiences that teams can transfer to novel, real-world situations.

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Team coordination consists of both the dynamics of team member interaction and the environmental dynamics to which a team is subjected. Focusing on dynamics, an approach is developed that contrasts with traditional aggregate-static concepts of team coordination as characterized by the shared mental model approach. A team coordination order parameter was developed to capture momentary fluctuations in coordination. Team coordination was observed in three-person uninhabited air vehicle teams across two experimental sessions. The dynamics of the order parameter were observed under changes of a team familiarity control parameter. Team members returned for the second session to either the same (Intact) or different (Mixed) team. 'Roadblock' perturbations, or novel changes in the task environment, were introduced in order to probe the stability of team coordination. Nonlinear dynamic methods revealed differences that a traditional approach did not: Intact and Mixed team coordination dynamics looked very different; Mixed teams were more stable than Intact teams and explored the space of solutions without the need for correction. Stability was positively correlated with the number of roadblock perturbations that were overcome successfully. The novel and non-intuitive contribution of a dynamical analysis was that Mixed teams, who did not have a long history working together, were more adaptive. Team coordination dynamics carries new implications for traditional problems such as training adaptive teams.

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Dynamical systems modeling was used to analyze fluctuations in the pain prediction process of people with rheumatoid arthritis. 170 people diagnosed with rheumatoid arthritis completed 29 consecutive days of diaries. Difference scores between pain predictions and next-day pain experience ratings provided a time series of pain prediction accuracy. Pain prediction accuracy oscillated over time. The oscillation amplitude was larger at the start of the diary than at the end, which indicates damping toward more accurate predictions. State-level psychological characteristics moderated the damping pattern such that the oscillations for patients with lower negative affect and higher pain control damped more quickly than the oscillations for their counterparts. Those findings suggest that low negative affect and high pain control generally contributed to a more accurate pain prediction process in the chronically ill. Positive affect did not differentiate the damping pattern but, within each oscillation cycle, patients with higher positive affect spent more time making inaccurate predictions than their counterparts. The current analyses highlight the need to account for change in data through dynamical modeling, which cannot be fully observed through traditional statistical techniques.

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