James J. Burkitt

The Multiple Process Model of Goal-Directed Reaching Revisited

HIGHLIGHTSAiming movements prepared to optimize speed, accuracy and energy.Prior knowledge about feedback important for limb regulation.Two types of online regulation: impulse control and limb‐target control.Differences between multiple process model and other models. ABSTRACT Recently our group forwarded a model of speed‐accuracy relations in goal‐directed reaching. A fundamental feature of our multiple process model was the distinction between two types of online regulation: impulse control and limb‐target control. Impulse control begins during the initial stages of the movement trajectory and involves a comparison of actual limb velocity and direction to an internal representation of expectations about the limb trajectory. Limb‐target control involves discrete error‐reduction based on the relative positions of the limb and the target late in the movement. Our model also considers the role of eye movements, practice, energy optimization and strategic behavior in limb control. Here, we review recent work conducted to test specific aspects of our model. As well, we consider research not fully incorporated into our earlier contribution. We conclude that a slightly modified and expanded version of our model, that includes crosstalk between the two forms of online regulation, does an excellent job of explaining speed, accuracy, and energy optimization in goal‐directed reaching.

The Influence of Visual Feedback and Prior Knowledge About Feedback on Vertical Aiming Strategies

ABSTRACT Two experiments were conducted to examine time and energy optimization strategies for movements made with and against gravity. In Experiment 1, the authors manipulated concurrent visual feedback, and knowledge about feedback. When vision was eliminated upon movement initiation, participants exhibited greater undershooting, both with their primary submovement and their final endpoint, than when vision was available. When aiming downward, participants were more likely to terminate their aiming following the primary submovement or complete a lower amplitude corrective submovement. This strategy reduced the frequency of energy-consuming corrections against gravity. In Experiment 2, the authors eliminated vision of the hand and the target at the end of the movement. This procedure was expected to have its greatest impact under no-vision conditions where no visual feedback was available for subsequent planning. As anticipated, direction and concurrent visual feedback had a profound impact on endpoint bias. Participants exhibited pronounced undershooting when aiming downward and without vision. Differences in undershooting between vision and no vision were greater under blocked feedback conditions. When performers were uncertain about the impending feedback, they planned their movements for the worst-case scenario. Thus movement planning considers the variability in execution, and avoids outcomes that require time and energy to correct.

Effector mass and trajectory optimization in the online regulation of goal-directed movement

Goal-directed aiming movements are planned and executed so that they optimize speed, accuracy and energy expenditure. In particular, the primary submovements involved in manual aiming attempts typically undershoot targets in order to avoid costly time and energy overshoot errors. Furthermore, in aiming movements performed over a series of trials, the movement planning process considers the sensory information associated with the most recent aiming attempt. The goal of the current study was to gain further insight into how the sensory consequences associated with the recent and forthcoming aiming attempts impact performance. We first examined whether performers are more conservative in their aiming movements with a heavy, as opposed to a light, stylus by determining whether primary submovements undershot the target to a greater extent in the former due to an anticipated increase in spatial variability. Our results show that movements with the heavy stylus demonstrated greater undershoot biases in the primary submovements, as well as greater trial-to-trial spatial variability at specific trajectory kinematic landmarks. In addition, we also sought to determine whether the sensory information experienced on a previous aiming movement affected movement planning and/or online control on the subsequent aiming attempt. To vary the type sensory consequences experienced on a trial-to-trial basis, participants performed aiming movements with light and heavy styli in either blocked or random orderings of trials. In the random-order conditions, some participants were provided advance information about stylus mass for the upcoming trial, while others were not. The blocked and random trial orders had minimal impacts on end point aiming performance. Furthermore, similarities in the times to key kinematic landmarks in the trajectories of the random-order groups suggest that recent trial experience had a greater effect on the upcoming aiming movement compared with advance task knowledge.

The Impact of Strategic Trajectory Optimization on Illusory Target Biases During Goal-Directed Aiming

ABSTRACT During rapid aiming, movements are planned and executed to avoid worst-case outcomes that require time and energy to correct. As such, downward movements initially undershoot the target to avoid corrections against gravity. Illusory target context can also impact aiming bias. Here, the authors sought to determine how strategic biases mediate illusory biases. Participants aimed to Müller-Lyer figures in different directions (forward, backward, up, down). Downward biases emerged late in the movement and illusory biases emerged from peak velocity. The illusory effects were greater for downward movements at terminal endpoint. These results indicate that strategic biases interact with the limb-target control processes associated with illusory biases. Thus, multiple control processes during rapid aiming may combine and later affect endpoint accuracy (D. Elliott et al., 2010).

Extending Energy Optimization in Goal-Directed Aiming from Movement Kinematics to Joint Angles

ABSTRACT Energy optimization in goal-directed aiming has been demonstrated as an undershoot bias in primary movement endpoint locations, especially in conditions where corrections to target overshoots must be made against gravity. Two-component models of upper limb movement have not yet considered how joint angles are organized to deal with the energy constraints associated with moving the upper limb in goal-directed aiming tasks. To address this limitation, participants performed aiming movements to targets in the up and down directions with the index finger and two types of rod extensions attached to the index finger. The rod extensions were expected to invoke different energy optimizing strategies in the up and down directions by allowing the distal joints the opportunity to contribute to end effector displacement. Primary movements undershot the farthest target to a greater extent in the downward direction compared to the upward direction, showing that movement kinematics optimize energy expenditure in consideration of the effects of gravity. As rod length increased, shoulder elevation was optimized in movements to the far-up target and elbow flexion was optimally minimized in movements to the far-down target. The results suggest energy optimization in the control of joint angles independent of the force of gravity.