The authors examined the importance of local dynamical information when anticipating tennis shot direction. In separate experiments, they occluded the arm and racket, shoulders, hips, trunk, and legs and locally neutralized dynamical differences between shot directions, respectively. The authors examined the impact of these manipulations on resulting (display) dynamics and the ability of participants with varying perceptual skills to anticipate shot direction. The occlusion manipulation affected the display dynamics to a larger extent than did the neutralization manipulation. Although the authors observed a decrement in performance when local information from the arm and racket was occluded or neutralized and when information from the trunk and legs was neutralized, the results generally suggest that participants anticipated shot direction through a more global perceptual approach, particularly in perceptually skilled participants.

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.

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