How Position, Velocity, and Temporal Information Combine in the Prospective Control of Catching: Data and Model

Abstract

The cerebral cortex contains circuitry for continuously computing properties of the environment and one's body, as well as relations among those properties. The success of complex perceptuomotor performances requires integrated, simultaneous use of such relational information. Ball catching is a good example as it involves reaching and grasping of visually pursued objects that move relative to the catcher. Although integrated neural control of catching has received sparse attention in the neuroscience literature, behavioral observations have led to the identification of control principles that may be embodied in the involved neural circuits. Here, we report a catching experiment that refines those principles via a novel manipulation. Visual field motion was used to perturb velocity information about balls traveling on various trajectories relative to a seated catcher, with various initial hand positions. The experiment produced evidence for a continuous, prospective catching strategy, in which hand movements are planned based on gaze-centered ball velocity and ball position information. Such a strategy was implemented in a new neural model, which suggests how position, velocity, and temporal information streams combine to shape catching movements. The model accurately reproduces the main and interaction effects found in the behavioral experiment and provides an interpretation of recently observed target motion-related activity in the motor cortex during interceptive reaching by monkeys. It functionally interprets a broad range of neurobiological and behavioral data, and thus contributes to a unified theory of the neural control of reaching to stationary and moving targets.

Adaptations of lateral hand movements to early and late visual occlusion in catching

“…A large part of these studies focused on the predictive control of movement timing (Bootsma and van Wieringen 1990;Fitch and Turvey 1978;Lee et al 1983;McLeod 1987;Savelsbergh et al 1991;Tyldesley and Whiting 1975), while others focused more on the vision-based movement adjustments used to reach the right place at the right time (Brenner et al 1998;Dessing et al 2005;Jacobs and Michaels 2006;Montagne et al 1999;Peper et al 1994;Smeets and Brenner 1995). The present study extends the latter line of research by examining the effects of predictable and unpredictable occlusion on vision-based movement adjustments underlying catching.…”

“…Participants caught the ball with their right hand. Hand movements in this set-up are consistently biased leftward (Dessing et al 2005). This was particularly evident when the hand started at the ball's future passing position (unbeknownst to the participant): in this situation the hand was first moved leftward (i.e., away from the starting position), after which movement direction was reversed to catch the ball at the starting position.…”

“…In the early 1970s, Whiting et al showed that balls can be caught successfully when their trajectories are largely occluded (Whiting et al 1970;Sharp and Whiting 1974), but they did not examine the corresponding hand movements. Whereas Mazyn et al (2007) examined hand movements as a function of the effects of approach velocity and occlusion, they did not vary the lateral ball motion, which has been shown to affect vision-based movement adjustments in catching (Dessing et al 2005;Peper et al 1994; see also Montagne et al 1999). Combined variations of lateral ball motion and occlusion may therefore be expected to yield interesting new insights in this respect.…”

“…Visually, the ball moves largely downward initially, while its lateral motion becomes stronger later in the trajectory. The observed leftward movement bias may be understood from this pattern, because movement adjustments in interception mainly depend on visual position and velocity information (Brouwer et al 2002(Brouwer et al , 2003(Brouwer et al , 2005Dessing et al 2005;Montagne et al 1999). In essence, this implies that the ball's future rightward visual displacement is underestimated because visual acceleration is not (fully) taken into account (see also Werkhoven et al 1992).…”

Robotics of human movements

“…Therefore we decided to use 3D minimum jerk to generate point-to-point movements with our robotic system. Furthermore, the two phases of fast reaching and slower fine movements at the end of the placement (Jeannerod et al, 1995;Dessing et al, 2005) can clearly be seen. Fig.…”