Developmentally Changing Attractor Dynamics of Manual Actions with Objects in Late Infancy

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.

Look before you reach: Fixation-reach latencies predict reaching kinematics in toddlers

Research on infant and toddler reaching has shown evidence for motor planning after the initiation of the reaching action. However, the reach action sequence does not begin after the initiation of a reach but rather includes the initial visual fixations onto the target object occurring before the reach. We developed a paradigm that synchronizes head-mounted eye-tracking and motion capture to determine whether the latency between the first visual fixation on a target object and the first reaching movement toward the object predicts subsequent reaching behavior in toddlers. In a corpus of over one hundred reach sequences produced by 17 toddlers, we found that longer fixation-reach latencies during the pre-reach phase predicted slower reaches. If the slowness of an executed reach indicates reach difficulty, then the duration of pre-reach planning would be correlated with reach difficulty. However, no relation was found with pre-reach planning duration when reach difficulty was measured by usual factors and independent of reach duration. The findings raise important questions about the measurement of reach difficulty, models of motor control, and possible developmental changes in the relations between pre-planning and continuously unfolding motor plans throughout an action sequence.

A Typology for the Application of Team Coordination Dynamics Across Increasing Levels of Dynamic Complexity

OBJECTIVE

This review and synthesis examines approaches for measuring and assessing team coordination dynamics (TCD). The authors advance a system typology for classifying TCD approaches and their applications for increasing levels of dynamic complexity.

BACKGROUND

There is an increasing focus on how teams adapt their coordination in response to changing and uncertain operational conditions. Understanding coordination is significant because poor coordination is associated with maladaptive responses, whereas adaptive coordination is associated with effective responses. This issue has been met with TCD approaches that handle increasing complexity in the types of TCD teams exhibit.

METHOD

A three-level system typology of TCD approaches for increasing dynamic complexity is provided, with examples of research at each level. For System I TCD, team states converge toward a stable, fixed-point attractor. For System II TCD, team states are periodic, which can appear complex, yet are regular and relatively stable. In System III TCD, teams can exhibit periodic patterns, but those patterns change continuously to maintain effectiveness.

RESULTS

System I and System II are applicable to TCD with known or discoverable behavioral attractors that are stationary across mid-to long-range timescales. System III TCD is the most generalizable to dynamic environments with high requirements for adaptive coordination across a range of timescales.

CONCLUSION

We outline current challenges for TCD and next steps in this burgeoning field of research.

APPLICATION

System III approaches are becoming widespread, as they are generalizable to time- and/or scale-varying TCD and multimodal analyses. Recommendations for deploying TCD in team settings are provided.

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.