Adaptation to unstable coordination patterns in individual and joint actions

Abstract

Previous research on interlimb coordination has shown that some coordination patterns are more stable than others, and function as attractors in the space of possible phase relations between different rhythmic movements. The canonical coordination patterns, i.e. the two most stable phase relations, are in-phase (0 degree) and anti-phase (180 degrees). Yet, musicians are able to perform other coordination patterns in intrapersonal as well as in interpersonal coordination with remarkable precision. This raises the question of how music experts manage to produce these unstable patterns of movement coordination. In the current study, we invited participants with at least five years of training on a musical instrument. We used an adaptation paradigm to address two factors that may facilitate producing unstable coordination patterns. First, we investigated adaptation in different coordination settings, to test the hypothesis that the lower coupling strength between individuals during joint performance makes it easier to achieve stability outside of the canonical patterns than the stronger coupling during individual bimanual performance. Second, we investigated whether adding to the structure of action effects may support achieving unstable coordination patterns, both intra-and inter-individually. The structure of action effects was strengthened by adding a melodic contour to the action effects, a measure that has been shown to improve the acquisition of bimanual coordination skills. Adaptation performance was measured both in terms of asynchrony and variability thereof. As predicted, we found that producing unstable patterns benefitted from the weaker coupling during joint performance. Surprisingly, the structure of action effects did not help with achieving unstable coordination patterns.

Collaborative Creativity: Information-driven coordination dynamics and prediction in movement and musical improvisation

“…Not only this, but if individuals are actively predicting the behavior of another and adapting, then the signals produced by them should not only influence each other, but they should also vary in their degree of predictability (as a function of their experience level). We therefore apply computational methods to examine improvisation-based coordination in which predictive processes may play an increasingly larger role with concomitant increases in scale (number of people coordinating), task complexity increases, and expertise (cf., Wolf et al, 2020)…”

Dynamic Coordination Phase and Joint Profiles: Cluster and Fixed-point Shift Techniques

“…After determining a more stable internal source (Experiment 1; homogeneous characteristic from heterogeneous pool) applied to the cluster phase methods, we determined which can be the most prototypical dependent variable (Experiment 2; prototype modeling for the contexttual constraints invetigation). Then, we focused on the detected in-phase bimanual coordination that may need to be analyzed in different joint conditions (Koeneke et al, 2004;Wolf et al, 2020) investigating the synchronization that can occur between topologies in the limbs. Although there are important theoretical reasons why measuring synchrony at a different topological level may be essential (topological level of synchrony may be an important behavioral indicator for existence as an entity; Campbell, 1958), most of the observations have been made with neuromuscular constraints (Fink et al, 2000) and cognitive influence (i.e., visual and auditory event; Spencer & Ivry, 2007).…”