Aaron D. Likens

Neural signatures of team coordination are revealed by multifractal analysis

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.

Cross-Level Effects Between Neurophysiology and Communication During Team Training

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).

Emergent complexity matching in interpersonal coordination: Local dynamics and global variability

Rhythmic coordination with stimuli and other peoples movements containing variable or unpredictable fluctuations might involve distinct processes: detecting the fluctuation structure and tuning to or matching the structures 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.

Experimental control of scaling behavior: what is not fractal?

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.

Perceived heaviness in the context of Newton's second law: Combined effects of muscle activity and lifting kinematics

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 Newtons 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.

Promoting Metacognitive Awareness within a Game-Based Intelligent Tutoring System

Metacognitive awareness has been shown to be a critical skill for academic success. However, students often struggle to regulate this ability during learning tasks. The current study investigates how features designed to promote metacognitive awareness can be built into the game-based intelligent tutoring system (ITS) iSTART-2. College students (n=28) interacted with iSTART-2 for one hour, completing lesson videos and practice activities. If students’ performance fell below a minimum threshold during game-based practice, they received a pop-up that alerted them of their poor performance and were subsequently transitioned to a remedial activity. Results revealed that students’ scores in the system improved after they were transitioned (even when they did not complete the remedial activity). This suggests that the pop-up feature in iSTART-2 may indirectly promote metacognitive awareness, thus leading to increased performance. These results provide insight into the potential benefits of real-time feedback designed to promote metacognitive awareness within a game-based learning environment.

Modeling the complex dynamics of teamwork from team cognition to neurophysiology

Teamwork is a complex dynamic process that emerges from team member interaction. The dynamics provide a characterization of the team over time. The stability, flexibility, and resilience of team dynamics over various windows of time can change with experience, training, environmental perturbations, and technological intervention. Once patterns of team dynamics have been established for a particular team, anomalous dynamics can signify impending teamwork problems. Dynamical systems modeling has been applied to many physical and natural systems and has only recently been applied to teamwork. The panel that we have assembled has applied dynamical modeling to this problem from different perspectives and at different scales. Each panelist will overview his or her approach to this problem. We will then discuss pros and cons of each approach and possibilities for using them in a complementary fashion.

What'd you say again?: recurrence quantification analysis as a method for analyzing the dynamics of discourse in a reading strategy tutor

In this study, we investigated the degree to which the cognitive processes in which students engage during reading comprehension could be examined through dynamical analyses of their natural language responses to texts. High school students (n = 142) generated typed self-explanations while reading a science text. They then completed a comprehension test that measured their comprehension at both surface and deep levels. The recurrent patterns of the words in students self-explanations were first visualized in recurrence plots. These visualizations allowed us to qualitatively analyze the different self-explanation processes of skilled and less skilled readers. These recurrence plots then allowed us to calculate recurrence indices, which represented the properties of these temporal word patterns. Results of correlation and regression analyses revealed that these recurrence indices were significantly related to the students comprehension scores at both surface- and deep levels. Additionally, when combined with summative metrics of word use, these indices were able to account for 32% of the variance in students overall text comprehension scores. Overall, our results suggest that recurrence quantification analysis can be utilized to guide both qualitative and quantitative assessments of students comprehension.

A multi-dimensional analysis of writing flexibility in an automated writing evaluation system

The assessment of writing proficiency generally includes analyses of the specific linguistic and rhetorical features contained in the singular essays produced by students. However, researchers have recently proposed that an individuals ability to flexibly adapt the linguistic properties of their writing might more closely capture writing skill. However, the features of the task, learner, and educational context that influence this flexibility remain largely unknown. The current study extends this research by examining relations between linguistic flexibility, reading comprehension ability, and feedback in the context of an automated writing evaluation system. Students (n = 131) wrote and revised six essays in an automated writing evaluation system and were provided both summative and formative feedback on their writing. Additionally, half of the students had access to a spelling and grammar checker that provided lower-level feedback during the writing period. The results provide evidence for the fact that developing writers demonstrate linguistic flexibility across the essays that they produce. However, analyses also indicate that lower-level feedback (i.e., spelling and grammar feedback) have little to no impact on the properties of students essays nor on their variability across prompts or drafts. Overall, the current study provides important insights into the role of flexibility in writing skill and develops a strong foundation on which to conduct future research and educational interventions.

Recurrence quantification analysis as a method for studying text comprehension dynamics

Self-explanations are commonly used to assess on-line reading comprehension processes. However, traditional methods of analysis ignore important temporal variations in these explanations. This study investigated how dynamical systems theory could be used to reveal linguistic patterns that are predictive of self-explanation quality. High school students (n = 232) generated self-explanations while they read a science text. Recurrence Plots were generated to show qualitative differences in students linguistic sequences that were later quantified by indices derived by Recurrence Quantification Analysis (RQA). To predict self-explanation quality, RQA indices, along with summative measures (i.e., number of words, mean word length, and type-token ration) and general reading ability, served as predictors in a series of regression models. Regression analyses indicated that recurrence in students self-explanations significantly predicted human rated self-explanation quality, even after controlling for summative measures of self-explanations, individual differences, and the text that was read (R2 = 0.68). These results demonstrate the utility of RQA in exposing and quantifying temporal structure in students self-explanations. Further, they imply that dynamical systems methodology can be used to uncover important processes that occur during comprehension.