Learning a bimanual coordination task (synchronization to a visually specified phasing relation) was studied as a dynamical process over 5 days of practicing a required phasing pattern. Systematic probes of the attractor layout of the 5 Ss' coordination dynamics (expressed through a collective variable, relative phase) were conducted before, during, and after practice. Depending on the relationship between the initial coordination dynamics (so-called intrinsic dynamics) and the pattern to be learned (termed behavioral information, which acts as an attractor of the coordination dynamics toward the required phasing), qualitative changes in the phase diagram occurred with learning, accompanied by quantitative evidence for loss of stability (phase transitions). Such effects persisted beyond 1 week. The nature of change due to learning (e.g., abrupt vs. gradual) is shown to arise from the cooperative or competitive interplay between behavioral information and the intrinsic dynamics.
The dynamics of learning a new coordinated behavior was examined by requiring participants to perform a visually specified phase relationship between the hands. Results showed that learning may involve qualitative or quantitative alterations in the layout of the coordination dynamics depending on whether such dynamics are bistable or multistable before exposure to the learning task. In both cases, the process stabilized the to-be-learned behavior and its symmetry partner, even though the latter had not actually been practiced. Kinematic analyses of hand motion showed that previously existing coordination tendencies were exploited during learning in order to match visual requirements. These findings and the concepts presented here provide a framework for understanding how learning occurs in the context of previous experience and allow individual differences in learning to be tackled explicitly.
Learning of coordination patterns was investigated theoretically from the point of view of a dynamic theory of biological coordination and with reference to recent experiments on the learning of relative timing patterns. The theory is based on theoretical and experimental work showing that coordinated movement is characterized not only by the actually performed pattern of coordination but by an entire dynamics of coordination. Theoretically, such dynamics are captured as equations of motion of relevant collective variables. Experimentally, signatures of these underlying dynamics can be found in the temporal stability of coordination patterns, which can be assessed through various stability measures as well as through processes of pattern change. We argue that not only intrinsic coordination tendencies, but also specific behavioral requirements, be they perceived, memorized, or intended, must be expressed in terms of such dynamics. The concept of behavioral information captures such requirements as part of the coordination dynamics. We expound two hypotheses on the nature of learning in this framework. First, we assume that at each point during the learning process the system is governed by a well-defined coordination dynamics. This equation of motion evolves with learning so as to acquire an attractor solution near the to-be-learned pattern. Second, we hypothesize that this change of the coordination dynamics, captured by the time course of memorized behavioral information, can itself be ascribed to an additional layer of dynamics, the slower learning dynamics. Testable consequences of these views are discussed in the light of recent experimental findings on the learning of a relative phase in rhythmic movement: (a) Learning affects dynamic properties of performed coordination patterns, in particular, their stability; (b) the change of the coordination dynamics due to learning leads to specific changes of behavior also under conditions other than the learned condition, namely, to systematic deviation toward the learned patterns; (c) learning may lead to instabilities in the coordination behavior if initial and learned performance differ sufficiently; and (d) the dynamic properties of the performed coordination patterns are distinct on the two time scales of learning and of performance.
This research reported here draws on self-organization theories and dynamical system models to investigate the collective behaviour of tennis players. In tennis, the unceasing to-and-fro displacements of a player about a "home" reference position, located in the middle of the baseline, are akin to those of an oscillator, and the reciprocal attending of both players establishes an informational linkage. Thus, theoretically, the displacement of the two players can be analysed as a system formed by two coupled non-linear oscillators. In such a system, relative phase has been shown to be an adept measure of the temporal synchronization between the oscillators. We hypothesized that relative phase is a relevant collective variable to characterize the relative motion of tennis players. Four players were videotaped and their displacements analysed. The results revealed just two stable patterns of synchronization, in-phase and anti-phase, as the players moved in the same or opposite directions, respectively. Moreover, relative phase showed two types of evolution within trials: either it remained stable at in-phase or anti-phase, or it exhibited transitions between these two modes. In accordance with our hypothesis, the results identified relative phase as a pertinent collective variable to represent both invariance and change in the relative displacements of tennis players. Such a finding opens new avenues for investigating dual sports.
Using an approach that combines experimental studies of bimanual movements to visual stimuli and theoretical modeling, the present paper develops a dynamical account of sensorimotor learning, that is, how new skills are acquired and old ones modified. A significant aspect of our approach is the focus on the individual learner as the basic unit of analysis, in particular the quantification of predispositions and capabilities that the individual learner brings to the learning environment. Such predispositions constitute the learner's behavioral repertoire, captured here theoretically as a dynamical landscape (“intrinsic dynamics”). The learning process is demonstrated to not only lead to a relatively permanent improvement of performance in the required task—the usual outcome—but also to alter the individual's entire repertoire. Changes in the dynamical landscape due to learning are shown to result from two basic mechanisms or “routes”: bifurcation and shift. Which mechanism is selected depends the initial individual repertoire before new learning begins. Both bifurcation and shift mechanisms are accommodated by a dynamical model, a relatively straightforward development of the well-established HKB model of movement coordination. Model simulations show that although environmental or task demands may be met equally well using either mechanism, the bifurcation route results in greater stabilization of the to-be-learned behavior. Thus, stability not (or not only) error is demonstrated to be the basis of selection, both of a new pattern of behavior and the path (smooth shift versus abrupt qualitative change) that learning takes. In line with these results, recent neurophysiological evidence indicates that stability is a relevant feature around which brain activity is organized while an individual performs a coordination task. Finally, we explore the consequences of the dynamical approach to learning for theories of biological change.
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