In 1899, R. S. Woodworth published a seminal monograph, "The Accuracy of Voluntary Movement." As well as making a number of important empirical contributions, Woodworth presented a model of speed-accuracy relations in the control of upper limb movements. The model has come to be known as the two-component model because the control of speeded limb movements was hypothesized to entail both a central and a feedback-based component. Woodworth's (1899) ideas about the control of rapid aiming movements are evaluated in the context of current empirical and theoretical contributions.

This article reviews the behavioral literature on the control of goal-directed aiming and presents a multiple-process model of limb control. The model builds on recent variants of Woodworth's (1899) two-component model of speed-accuracy relations in voluntary movement and incorporates ideas about dynamic online limb control based on prior expectations about the efferent and afferent consequences of a planned movement. The model considers the relationship between movement speed and accuracy, and how performers adjust their trial-to-trial aiming behavior to find a safe, but fast, zone for movement execution. The model also outlines how the energy and safety costs associated with different movement outcomes contribute to movement planning processes and the control of aiming trajectories. Our theoretical position highlights the importance of advance knowledge about the sensory information that will be available for online control and the need to develop a robust internal representation of expected sensory consequences. We outline how early practice contributes to optimizing strategic planning to avoid worst-case outcomes associated with inherent neural-motor variability. Our model considers the role of both motor development and motor learning in refining feed-forward and online control. The model reconciles procedural and representational accounts of the specificity-of-learning phenomenon. Finally, we examine the breakdown of perceptual-motor precision in several special populations (i.e., Down syndrome, Williams syndrome, autism spectrum disorder, normal aging) within the framework of a multiple-process approach to goal-directed aiming.

We examined the planning and control of goal-directed aiming movements in young adults with autism. Participants performed rapid manual aiming movements to one of two targets. We manipulated the difficulty of the planning and control process by varying both target size and amplitude of the movements. Consistent with previous research, participants with autism took longer to prepare and execute movements, particularly when the index of difficulty was high. Although there were no group differences for accuracy, participants with autism exhibited more temporal and spatial variability over the initial phase of the movement even though mean peak accelerations and velocities were lower than for control participants. Our results suggest that although persons with autism have difficulty specifying muscular force, they compensate for this initial variability during limb deceleration. Perhaps persons with autism have learned to keep initial impulses low to minimize the spatial variability that needs to be corrected for during the online control phase of the movement.

Over the last century, investigators have developed a number of models to explain the relation between speed and accuracy in target-directed manual aiming. The models vary in the extent to which they stress the importance of feedforward processes and the online use of sensory information (see D. Elliott, W. F. Helsen, & R. Chua, 2001, for a recent review). A common feature of those models is that the role of practice in optimizing speed, accuracy, and energy expenditure in goal-directed aiming is either ignored or minimized. The authors present a theoretical framework for understanding speed-accuracy tradeoffs that takes into account the strategic, trial-to-trial behavior of the performer. The strategic behavior enables individuals to maximize movement speed while minimizing error and energy expenditure.

Consistent with action-based theories of attention, the presence of a nontarget stimulus in the environment has been shown to alter the characteristics of goal-directed movements. Specifically, it has been reported that movement trajectories veer away from (Howard & Tipper, 1997) or towards (Welsh, Elliott, & Weeks, 1999) the location of a nontarget stimulus. The purpose of the experiments reported in this paper was to test a response activation model of selective reaching conceived to account for these variable results. In agreement with the model, the trajectory changes in the movements appear to be determined by the activation levels of each competing response at the moment of response initiation. The results of the present work, as well as those of previous studies, are discussed within the framework of the model of response activation. In order to effectively reach to and grasp objects in a complex visual environment, two processes must be completed-the target object must be selected from the competing, nontarget objects, and a movement must be planned to interact with the selected object. Although the processes of selective attention and movement organization have been investigated independently, action-based models of visual selective attention have recently surfaced. For example, Rizzolatti and colleagues have proposed a premotor theory of attention (see Rizzolatti, Riggio, & Sheliga, 1994, for a review). Citing evidence such as shared spatial and motor mapping systems, and increased activity in early visual perceptual centres

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Recent studies suggest motor skills are not entirely spared in individuals with an autism spectrum disorder (ASD). Previous reports demonstrated that young adults with ASD were able to land accurately on a target despite increased temporal and spatial variability during their movement. This study explored how a group of adolescents and young adults with an ASD used vision and proprioception to land successfully on one of two targets. Participants performed eye movements and/or manual reaching movements, either with or without vision. Although eye movements were executed in a similar timeframe, participants with ASD took longer to plan and execute manual reaching movements. They also exhibited significantly greater variability during eye and hand movements, but were able to land on the target regardless of the vision condition. In general, individuals with autism used vision and proprioception. However, they took considerably more time to perform movements that required greater visual-proprioceptive integration.