Perspectives on the Dynamic Nature of Coupling in Human Coordination

Calvin, Sarah; Jirsa, Viktor K.

doi:10.1007/978-3-642-16262-6_4

Cited by 9 publications

(10 citation statements)

References 32 publications

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“…The above system of two coupled second order ordinary differential equations (ODEs) ( 9 ) can be written as a four-dimensional autonomous system of first order ODEs: where and represent position and velocity of the i th agent’s end effector, respectively. The resulting dynamical system has a four-dimensional state space [ 7 ]. The parameter (commonly referred to as eigenfrequency ) defines, in conjunction with and , the intrinsic dynamics of the two coupled oscillators.…”

Section: Resultsmentioning

confidence: 99%

“…A classical example of model exhibiting bistability is the so-called HKB model proposed in the seminal work by Haken, Kelso and Bunz [ 18 , 22 ]. The model, which was originally developed for bimanual finger coordination [ 30 ], was found to be representative of a wide range of applications in human movement [ 7 , 18 ], suggesting that the dynamics that it produces are somehow fundamental and make formal construct for the study of coordination dynamics [ 32 , 33 ]. Although the model was originally developed in order to account for intra-personal phenomena, the same patterns have been shown to be representative of both sensorimotor and interpersonal behaviours [ 31 , 49 , 50 ].…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, most previous research has focused on a fixed set of model parameters that guarantees the stability of these particular dynamics. Furthermore, significant contributions to understanding these coordination patterns (albeit in a narrow parameter range and with limiting assumptions on the parameters controlling the coupling strength) have been made for different oscillator frequencies and inputs [ 1 , 3 , 7 , 17 , 19 , 25 ] as well as noise in the system [ 9 , 49 , 50 ]. All previous mathematical analyses of the HKB model have focused on the relative phase dynamics, under the assumption that the amplitude of the coupled oscillators is constant [ 1 , 3 , 9 , 17 , 19 , 22 ].…”

Section: Introductionmentioning

confidence: 99%

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Beyond in-phase and anti-phase coordination in a model of joint action

et al. 2016

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In 1985, Haken, Kelso and Bunz proposed a system of coupled nonlinear oscillators as a model of rhythmic movement patterns in human bimanual coordination. Since then, the Haken–Kelso–Bunz (HKB) model has become a modelling paradigm applied extensively in all areas of movement science, including interpersonal motor coordination. However, all previous studies have followed a line of analysis based on slowly varying amplitudes and rotating wave approximations. These approximations lead to a reduced system, consisting of a single differential equation representing the evolution of the relative phase of the two coupled oscillators: the HKB model of the relative phase. Here we take a different approach and systematically investigate the behaviour of the HKB model in the full four-dimensional state space and for general coupling strengths. We perform detailed numerical bifurcation analyses and reveal that the HKB model supports previously unreported dynamical regimes as well as bistability between a variety of coordination patterns. Furthermore, we identify the stability boundaries of distinct coordination regimes in the model and discuss the applicability of our findings to interpersonal coordination and other joint action tasks.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Beyond in-phase and anti-phase coordination in a model of joint action

et al. 2016

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“…An important one is the HKB model, which uses a simple equation to explain the possible phase relationships between two coupled oscillatory systems in many contexts, including human intra- and inter-personal synchronization [32]. Because of its focus on relative phase [58], the HKB model is flexible, parsimonious, and a powerful tool to explain and predict periodic human motor behavior [59]. By changing two parameters in a single equation, the HKB model is able to explain transitions between anti-phase (180°) and in-phase (0°) coordination when one person taps both index fingers together [59] or two people swing their feet in tandem [59] at different frequencies.…”

Section: Discussionmentioning

confidence: 99%

Delayed feedback embedded in perception-action coordination cycles results in anticipation behavior during synchronized rhythmic action: A dynamical systems approach

et al. 2019

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Dancing and playing music require people to coordinate actions with auditory rhythms. In laboratory perception-action coordination tasks, people are asked to synchronize taps with a metronome. When synchronizing with a metronome, people tend to anticipate stimulus onsets, tapping slightly before the stimulus. The anticipation tendency increases with longer stimulus periods of up to 3500ms, but is less pronounced in trained individuals like musicians compared to non-musicians. Furthermore, external factors influence the timing of tapping. These factors include the presence of auditory feedback from one’s own taps, the presence of a partner performing coordinated joint tapping, and transmission latencies (TLs) between coordinating partners. Phenomena like the anticipation tendency can be explained by delay-coupled systems, which may be inherent to the sensorimotor system during perception-action coordination. Here we tested whether a dynamical systems model based on this hypothesis reproduces observed patterns of human synchronization. We simulated behavior with a model consisting of an oscillator receiving its own delayed activity as input. Three simulation experiments were conducted using previously-published behavioral data from 1) simple tapping, 2) two-person alternating beat-tapping, and 3) two-person alternating rhythm-clapping in the presence of a range of constant auditory TLs. In Experiment 1, our model replicated the larger anticipation observed for longer stimulus intervals and adjusting the amplitude of the delayed feedback reproduced the difference between musicians and non-musicians. In Experiment 2, by connecting two models we replicated the smaller anticipation observed in human joint tapping with bi-directional auditory feedback compared to joint tapping without feedback. In Experiment 3, we varied TLs between two models alternately receiving signals from one another. Results showed reciprocal lags at points of alternation, consistent with behavioral patterns. Overall, our model explains various anticipatory behaviors, and has potential to inform theories of adaptive human synchronization.

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“…We applaud this step, though we think that the authors' rapprochement between Darwin machines and "multi-agent cooperative systems" requires some elaboration. What seems to be missing are the concepts, methods, and tools of self-organizing dynamical systems tailored specifically to the coordinated activities of living thingshow they move, adapt, learn, develop, and so on (Beek et al 1995;Calvin & Jirsa 2010;Haken et al 1985;Kelso 1995;Kelso & Haken 1995;Schöner & Kelso 1988;Turvey & Carello 2012;Warren 2006;Zanone & Kelso 1992). Among others, Coordination Dynamics (CD) has long been inspired by the works of Howard Pattee, who understood the significance of biological coordination, particularly the complementary nature of symbolic and dynamic descriptions (Kelso & Engstrøm, 2006;Pattee & Raczaszek-Leonardi 2012).…”

Section: Bjørn Grindementioning

confidence: 99%

Collaborating on evolving the future

Wilson¹,

Hayes²,

Biglan³

et al. 2014

Behav Brain Sci

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Humans possess great capacity for behavioral and cultural change, but our ability to manage change is still limited. This article has two major objectives: first, to sketch a basic science of intentional change centered on evolution; second, to provide examples of intentional behavioral and cultural change from the applied behavioral sciences, which are largely unknown to the basic sciences community.All species have evolved mechanisms of phenotypic plasticity that enable them to respond adaptively to their environments. Some mechanisms of phenotypic plasticity count as evolutionary processes in their own right. The human capacity for symbolic thought provides an inheritance system having the same kind of combinatorial diversity as does genetic recombination and antibody formation. Taking these propositions seriously allows an integration of major traditions within the basic behavioral sciences, such as behaviorism, social constructivism, social psychology, cognitive psychology, and evolutionary psychology, which are often isolated and even conceptualized as opposed to one another.The applied behavioral sciences include well-validated examples of successfully managing behavioral and cultural change at scales ranging from individuals to small groups to large populations. However, these examples are largely unknown beyond their disciplinary boundaries, for lack of a unifying theoretical framework. Viewed from an evolutionary perspective, they are examples of managing evolved mechanisms of phenotypic plasticity, including open-ended processes of variation and selection.Once the many branches of the basic and applied behavioral sciences become conceptually unified, we are closer to a science of intentional change than one might think.

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Perspectives on the Dynamic Nature of Coupling in Human Coordination

Cited by 9 publications

References 32 publications

Beyond in-phase and anti-phase coordination in a model of joint action

Beyond in-phase and anti-phase coordination in a model of joint action

Delayed feedback embedded in perception-action coordination cycles results in anticipation behavior during synchronized rhythmic action: A dynamical systems approach

Collaborating on evolving the future

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