The effectiveness of constraint-led training on skill development in interceptive sports: a systematic review (Clark, McEwan and Christie) – a commentary

Clark, McEwan and Christie's systematic review1 offers a timely examination of current literature assessing effects of a constraints-led approach (CLA) to training on ‘technical and cognitive skill in sport’, in comparison to traditional training methods. They concluded that, currently, there is strong evidence to advocate for the effects of training interventions that espouse benefits of constraints-led training on acquiring skill in interceptive actions. Clark, McEwan and Christie reported that 18 studies satisfied their proposed inclusion criteria and, of these studies, 77% provided evidence of the effectiveness of the CLA. Consequently, Clark, McEwan and Christie argued that a ‘the implementation of the constraints-led approach within interceptive sport can be advocated’ (p. 17). This is a revealing insight, which supports their claims that this finding ‘provides the opportunity for researchers to collect more compelling evidence to answer the question: “Does constraint-led training assist with the development of technical skills within interceptive sport?”’. While we endorse their call for more empirical evidence on the effectiveness of a CLA to practice and training design, we qualify it by highlighting some limitations of Clark, McEwan and Christie's systematic review

Distinct Timing Mechanisms Produce Discrete and Continuous Movements

The differentiation of discrete and continuous movement is one of the pillars of motor behavior classification. Discrete movements have a definite beginning and end, whereas continuous movements do not have such discriminable end points. In the past decade there has been vigorous debate whether this classification implies different control processes. This debate up until the present has been empirically based. Here, we present an unambiguous non-empirical classification based on theorems in dynamical system theory that sets discrete and continuous movements apart. Through computational simulations of representative modes of each class and topological analysis of the flow in state space, we show that distinct control mechanisms underwrite discrete and fast rhythmic movements. In particular, we demonstrate that discrete movements require a time keeper while fast rhythmic movements do not. We validate our computational findings experimentally using a behavioral paradigm in which human participants performed finger flexion-extension movements at various movement paces and under different instructions. Our results demonstrate that the human motor system employs different timing control mechanisms (presumably via differential recruitment of neural subsystems) to accomplish varying behavioral functions such as speed constraints

Transfer of learning between unimanual and bimanual rhythmic movement coordination: transfer is a function of the task dynamic.

Under certain conditions, learning can transfer from a trained task to an untrained version of that same task. However, it is as yet unclear what those certain conditions are or why learning transfers when it does. Coordinated rhythmic movement is a valuable model system for investigating transfer because we have a model of the underlying task dynamic that includes perceptual coupling between the limbs being coordinated. The model predicts that (1) coordinated rhythmic movements, both bimanual and unimanual, are organised with respect to relative motion information for relative phase in the coupling function, (2) unimanual is less stable than bimanual coordination because the coupling is unidirectional rather than bidirectional, and (3) learning a new coordination is primarily about learning to perceive and use the relevant information which, with equal perceptual improvement due to training, yields equal transfer of learning from bimanual to unimanual coordination and vice versa [but, given prediction (2), the resulting performance is also conditioned by the intrinsic stability of each task]. In the present study, two groups were trained to produce 90° either unimanually or bimanually, respectively, and tested in respect to learning (namely improved performance in the trained 90° coordination task and improved visual discrimination of 90°) and transfer of learning (to the other, untrained 90° coordination task). Both groups improved in the task condition in which they were trained and in their ability to visually discriminate 90°, and this learning transferred to the untrained condition. When scaled by the relative intrinsic stability of each task, transfer levels were found to be equal. The results are discussed in the context of the perception–action approach to learning and performance

Individual-environment interactions in swimming: The smallest unit for analysing the emergence of coordination dynamics in performance?

Displacement in competitive swimming is highly dependent on fluid characteristics, since athletes use these properties to propel themselves. It is essential for sport scientists and practitioners to clearly identify the interactions that emerge between each individual swimmer and properties of an aquatic environment. Traditionally, the two protagonists in these interactions have been studied separately. Determining the impact of each swimmer’s movements on fluid flow, and vice versa, is a major challenge. Classic biomechanical research approaches have focused on swimmers’ actions, decomposing stroke characteristics for analysis, without exploring perturbations to fluid flows. Conversely, fluid mechanics research has sought to record fluid behaviours, isolated from the constraints of competitive swimming environments (e.g. analyses in two-dimensions, fluid flows passively studied on mannequins or robot effectors). With improvements in technology, however, recent investigations have focused on the emergent circular couplings between swimmers’ movements and fluid dynamics. Here, we provide insights into concepts and tools that can explain these on-going dynamical interactions in competitive swimming within the theoretical framework of ecological dynamics

Complex Processes from Dynamical Architectures with Time-Scale Hierarchy

The idea that complex motor, perceptual, and cognitive behaviors are composed of smaller units, which are somehow brought into a meaningful relation, permeates the biological and life sciences. However, no principled framework defining the constituent elementary processes has been developed to this date. Consequently, functional configurations (or architectures) relating elementary processes and external influences are mostly piecemeal formulations suitable to particular instances only. Here, we develop a general dynamical framework for distinct functional architectures characterized by the time-scale separation of their constituents and evaluate their efficiency. Thereto, we build on the (phase) flow of a system, which prescribes the temporal evolution of its state variables. The phase flow topology allows for the unambiguous classification of qualitatively distinct processes, which we consider to represent the functional units or modes within the dynamical architecture. Using the example of a composite movement we illustrate how different architectures can be characterized by their degree of time scale separation between the internal elements of the architecture (i.e. the functional modes) and external interventions. We reveal a tradeoff of the interactions between internal and external influences, which offers a theoretical justification for the efficient composition of complex processes out of non-trivial elementary processes or functional modes