Target velocity effects on manual interception kinematics

Participants generated manual interception movements toward a target cursor that moved across a computer screen. The target reached its peak velocity either during the first third, at the midpoint, or during the last third of the movement. In Experiment 1 the view of the target was available for either the first 316, 633, 950, or 1267 ms, after which it disappeared. Results showed that for all viewing conditions, the timing of the interception velocity was related to the temporal properties of the target's trajectory. In Experiment 2, when the portion of the target trajectory that was viewed was reversed (such that participants did not see the first 316, 633, 950, or 1267 ms of the trajectory, but instead saw only the later portions of the trajectory), there was no clear relationship between the target trajectory and the timing of the aiming trajectory. These results suggest that participants use visual information early in the target's trajectory to form a representation of the target motion that is used to facilitate manual interception.     

Colour correspondence effects between controlled objects and targets

It is increasingly popular to use movement trajectories as a measure of mental processes related to task performance. Often this is accomplished by moving a cursor to a target on a computer screen. However, the relation between features of the cursor and the targets is rarely, if at all, considered. In five experiments, we examined whether moving a cursor to a target was affected by the relation between their colours, even when this relation was task irrelevant. In Experiments 1–3, a mouse-controlled cursor was moved to one of two coloured targets. Results showed colour correspondence effects in latency to initiate a response, duration of movement times, and movement trajectories when the relationship between cursor and target colours was task relevant (Experiment 1) and when only the cursor colour was task relevant (Experiment 2), but not when only the target was task relevant (Experiment 3). Follow-up experiments using single targets showed that colour correspondence effects occurred as long as attention was dedicated to the colour of the cursor, even when neither the cursor nor the target colour was relevant to selecting the correct movement (Experiments 4 and 5). Furthermore, when the relation between cursor and target colours is task irrelevant, colour correspondence effects for response initiation times are uncorrelated with those for movement times and movement trajectories. We interpret the observed correspondence effect in terms of response coding, although attention cueing may also play a role, and suggest that greater consideration of cursor features is needed when examining movement trajectories in choice reaction tasks.     

Colour correspondence effects between controlled objects and targets

It is increasingly popular to use movement trajectories as a measure of mental processes related to task performance. Often this is accomplished by moving a cursor to a target on a computer screen. However, the relation between features of the cursor and the targets is rarely, if at all, considered. In five experiments, we examined whether moving a cursor to a target was affected by the relation between their colours, even when this relation was task irrelevant. In Experiments 1-3, a mouse-controlled cursor was moved to one of two coloured targets. Results showed colour correspondence effects in latency to initiate a response, duration of movement times, and movement trajectories when the relationship between cursor and target colours was task relevant (Experiment 1) and when only the cursor colour was task relevant (Experiment 2), but not when only the target was task relevant (Experiment 3). Follow-up experiments using single targets showed that colour correspondence effects occurred as long as attention was dedicated to the colour of the cursor, even when neither the cursor nor the target colour was relevant to selecting the correct movement (Experiments 4 and 5). Furthermore, when the relation between cursor and target colours is task irrelevant, colour correspondence effects for response initiation times are uncorrelated with those for movement times and movement trajectories. We interpret the observed correspondence effect in terms of response coding, although attention cueing may also play a role, and suggest that greater consideration of cursor features is needed when examining movement trajectories in choice reaction tasks.     

伸手拦截启动中的信息利用

通过两项实验考察时空信息对拦截运动启动的影响: 实验一为知觉估计实验, 通过释放匀速小球模拟拦截过程; 实验二为特定拦截路线情景下的拦截行为实验, 即固定手的拦截方向, 但容许拦截速度自由控制。结果发现, 拦截行为的启动基于综合信息, 在所拦截物体作慢速运动的情景下拦截行为启动偏早, 而在快速运动的情景下启动偏晚, 结果不支持单纯用tau理论解释启动行为。本研究对手的速度伴随效应提出了新的解释。     

Moving the Arm at Different Rates: Slow Movements are Avoided

Qualitative and quantitative changes characterize locomotion and rhythmic interlimb coordination at different speeds. Legs and hands do not move more or less quickly; they also adopt different relative coordination patterns. In the present article, the authors asked whether similar transitions occur for unimanual hand movements when speed is slowed below the preferred speed. Participants moved a handheld dowel back and forth between 2 large circular targets in time with a metronome at periods between 370 ms and 1667 ms. The authors analyzed the kinematics of participants’ movements at each period and found that proportional dwell time and number of peaks in the velocity profile increased as driving periods increased. Path lengths and peak velocities remained relatively constant for driving periods exceeding 800 ms. Participants made only gradual changes to their movement parameters, so that they went from a continuous mode to a more discrete mode of behavior for longer driving periods. Thus, unlike for rhythmic bimanual movements or locomotory patterns, there are quantitative but no clear qualitative changes for unimanual movements. The results suggest that participants tried to move close to their preferred tempo at different rates, and that they avoided moving slowly.     

自由拦截启动策略与信息利用

手的启动方向自由, 伸手拦截不同速度的运动小球。本研究通过考察手启动时的运动参数, 研究自由启动的情况下的信息利用和拦截策略, 并且考察了人的启动模式。结果发现, 自由拦截时手的拦截区域相对固定, 在物体快速运动情景下启动晚, 而在慢速下启动早, 可能综合利用了接触时间和距离信息, 存在速度伴随效应, 手的拦截启动策略为启动有相对稳定的角度和加速度, 并不随物体运动速度和物体大小的改变而改变。     

Minimal mimicry: Mere effector matching induces preference

Both mimicking and being mimicked induces preference for a target. The present experiments investigate the minimal sufficient conditions for this mimicry-preference link to occur. We argue that mere effector matching between one’s own and the other person’s movement is sufficient to induce preference, independent of which movement is actually performed. In Experiments 1 and 2, participants moved either their arms or legs, and watched avatars that moved either their arms or legs, respectively, without any instructions to mimic. The executed movements themselves and their pace were completely different between participants (fast circular movements) and targets (slow linear movements). Participants preferred avatars that moved the same body part as they did over avatars that moved a different body part. In Experiment 3, using human targets and differently paced movements, movement similarity was manipulated in addition to effector overlap (moving forward–backward or sideways with arms or legs, respectively). Only effector matching, but not movement matching, influenced preference ratings. These findings suggest that mere effector overlap is sufficient to trigger preference by mimicry.     

Minimal mimicry: Mere effector matching induces preference

Both mimicking and being mimicked induces preference for a target. The present experiments investigate the minimal sufficient conditions for this mimicry-preference link to occur. We argue that mere effector matching between one’s own and the other person’s movement is sufficient to induce preference, independent of which movement is actually performed. In Experiments 1 and 2, participants moved either their arms or legs, and watched avatars that moved either their arms or legs, respectively, without any instructions to mimic. The executed movements themselves and their pace were completely different between participants (fast circular movements) and targets (slow linear movements). Participants preferred avatars that moved the same body part as they did over avatars that moved a different body part. In Experiment 3, using human targets and differently paced movements, movement similarity was manipulated in addition to effector overlap (moving forward–backward or sideways with arms or legs, respectively). Only effector matching, but not movement matching, influenced preference ratings. These findings suggest that mere effector overlap is sufficient to trigger preference by mimicry.     

Synchronizing self and object movement: how child and adult cyclists intercept moving gaps in a virtual environment

Two experiments examined how 10- and 12-year-old children and adults intercept moving gaps while bicycling in an immersive virtual environment. Participants rode an actual bicycle along a virtual roadway. At 12 test intersections, participants attempted to pass through a gap between 2 moving, car-sized blocks without stopping. The blocks were timed such that it was sometimes necessary for participants to adjust their speed in order to pass through the gap. We manipulated available visual information by presenting the target blocks in isolation in Experiment 1 and in streams of blocks in Experiment 2. In both experiments, adults had more time to spare than did children. Both groups had more time to spare when they were required to slow down than when they were required to speed up. Participants' behavior revealed a multistage interception strategy that cannot be explained by the use of a monotonic control law such as the constant bearing angle strategy. The General Discussion section focuses on possible sources of changes in perception-action coupling over development and on task-specific constraints that could underlie the observed interception strategy.     

Metacognition of agency

The feeling that we are agents, intentionally making things happen by our own actions, is foundational to our understanding of ourselves as humans. People's metacognitions of agency were investigated in 4 experiments. Participants played a game in which they tried to touch downward scrolling Xs and avoid touching Os. Variables that affected accuracy included speed of the scroll, density of the targets, and feedback. Of central interest were variables directed not only at accuracy but also at people's control: the turbulence of the cursor and how close the cursor had to come to the target for a hit (i.e., "magic"). After each trial, people made judgments of agency or judgments of performance. People were selectively sensitive to the variables to which they should be responsive in agency monitoring--whether the cursor moved in close synchrony to their movements and whether targets disappeared by magic. People knew, separably from their objective or judged performance, when they were in control and when they were not. These results indicate that people can sensitively monitor their own agency.     

Metacognitive control of action: Preparation for aiming reflects knowledge of Fitts’s law

Metacognitive control has been studied in intellectual skills but has not yet been studied in perceptual-motor skills. To probe metacognitive control in a perceptual-motor context, we developed a task in which participants chose the position of a cursor relative to two targets. One of the two targets was randomly erased. Participants tried to move the cursor into the remaining target within a limited amount of time. The target widths were varied, making the difficulty of moving to either target dependent on the chosen cursor position. Predictions were based on the assumption that participants could use an analogue of Fitts’s law to choose optimal positions. The fit between observed and predicted positions was excellent, suggesting that participants used information about movement speed-accuracy trade-offs to guide movement preparation. The findings suggest that metacognition applies to both perceptual-motor skills and intellectual skills, and that these two domains are more similar than traditionally assumed.     

Different strategies for using motion-in-depth information in catching

Previous studies on ball catching have had the limitation that the catcher was restricted to lateral hand movements. The authors investigated catching behavior in the more natural situation in which hand movements were unconstrained. Movements of the hand were tracked as participants tried to "catch" an approaching ball simulated with changing size and/or changing disparity. Participants used 1 of 2 distinct interception strategies: (a) a "cutting-off" strategy where time to passage (TTP) information was used to guide movements of the hand in depth such that the ball was caught farther in front of the face when the ball was approaching more slowly and (b) a "waiting" strategy where the hand was moved along a frontoparallel plane that was constant across ball trajectories and speeds. Cue dissociation and selective adaptation manipulations demonstrated that the catcher's estimates of TTP and crossing distance were based on a combination of binocular and monocular information.     

When causality does not imply correlation: more spadework at the foundations of scientific psychology

Experimental research in psychology is based on an open-loop causal model which assumes that sensory input causes behavioral output. This model was tested in a tracking experiment where participants were asked to control a cursor, keeping it aligned with a target by moving a mouse to compensate for disturbances of differing difficulty. Since cursor movements (inputs) are the only observable cause of mouse movements (outputs), the open-loop model predicts that there will be a correlation between input and output that increases as tracking performance improves. In fact, the correlation between sensory input and motor output is very low regardless of the quality of tracking performance; causality, in terms of the effect of input on output, does not seem to imply correlation in this situation. This surprising result can be explained by a closed-loop model which assumes that input is causing output while output is causing input.     

Grasping a 2D virtual target: The influence of target position and movement on gaze and digit placement

While much has been learned about the visual pursuit and motor strategies used to intercept a moving object, less research has focused on the coordination of gaze and digit placement when grasping moving stimuli. Participants grasped 2D computer generated square targets that either encouraged placement of the index finger and thumb along the horizontal midline (Control targets) or had narrow “notches” in the top and bottom surfaces of the target, intended to discourage digit placement near the midline (Experimental targets). In Experiment 1, targets remained stationary at the left, middle, or right side of the screen. Gaze and digit placement were biased toward the closest side of non-central targets, and toward the midline of center targets. These locations were shifted rightward when grasping Experimental targets, suggesting participants prioritized visibility of the target. In Experiment 2, participants grasped horizontally translating targets at early, middle, or late stages of travel. Average gaze and digit placement were consistently positioned behind the moving target's horizontal midline when grasping. Gaze was directed farther behind the midline of Experimental targets, suggesting the absence of a flat central grasp location pulled participants' gaze toward the trailing edge. Participants placed their digits at positions closer to the horizontal midline of leftward moving targets, suggesting participants were compensating for the added mechanical constraints associated with grasping targets moving in a direction contralateral to the grasping hand. These results suggest participants minimize the effort associated with reaching to non-central targets by grasping the nearest side when the target is stationary, but grasp the trailing side of moving targets, even if this means placing the digits at locations on the far side of the target, potentially limiting visibility of the target.     

Exploring specificity of speeded aiming movements: Examining different measures of transfer

Participants were trained and tested to move a mouse cursor from a start position to targets on a circular display in a perceptual-motor reversal condition, with horizontal, but not vertical, reversals. During training, some participants (experimental) moved to two targets either along a single diagonal axis (D1) or along both axes (D2). For D2, return movements from the targets were in the same direction as instructed movements to unpracticed targets. Others (control) trained on all targets. Testing always involved all targets. At test, movement times (to reach the target after leaving the start position) were shorter on trained than on untrained targets, especially for the D1 condition, documenting training specificity. However, movement times in the experimental conditions to new targets during testing were shorter than those in the control condition during training, documenting transfer of learning, with more transfer for D2 than for D1. Initiation times (to leave the start position after target onset) showed no transfer. The results provide evidence that specificity and transfer are not mutually exclusive and depend on the measure used to assess performance.     

The utilization of visual information in the control of reciprocal aiming movements

Two experiments examined on-line processing during the execution of reciprocal aiming movements. In Experiment 1, participants used a stylus to make movements between two targets of equal size. Three vision conditions were used: full vision, vision during flight and vision only on contact with the target. Participants had significantly longer movement times and spent more time in contact with the targets when vision was available only on contact with the target. Additionally, the proportion of time to peak velocity revealed that movement trajectories became more symmetric when vision was not available during flight. The data indicate that participants used vision not only to 'home-in' on the current target, but also to prepare subsequent movements. In Experiment 2, liquid crystal goggles provided a single visual sample every 40 ms of a 500 ms duty cycle. Of interest was how participants timed their reciprocal aiming to take advantage of these brief visual samples. Although across participants no particular portion of the movement trajectory was favored, individual performers did time their movements consistently with the onset and offset of vision. Once again, performance and kinematic data indicated that movement segments were not independent of each other.     

Postural Sway and the Amplitude of Horizontal Eye Movements

In 2 experiments, we evaluated relations between postural activity and the amplitude of visually guided eye movements. Participants shifted their gaze to follow horizontal oscillation of a visible target. The target moved with amplitude 9° or 24°. In different experiments, the frequency of target oscillation was 0.5 Hz or 1.1 Hz. In both experiments, the variability of head and torso motion was reduced (in the anterior-posterior axis) when participants viewed moving targets, relative to sway during viewing of stationary targets. Sway variability was not influenced by the amplitude of target motion. The results are compatible with the hypothesis that postural activity was modulated relative to the demands of suprapostural visual tasks.     

When is the ball going to hit the ground? Duration estimates, eye movements, and mental imagery of object motion

Performance in 2 versions of a computer-animated task was compared. Participants either indicated the time of arrival of a target that rolled off a horizontal surface and fell--hidden from view--onto a landing point (production task) or judged flight time on a rating scale (judgment task). As predicted, performance was significantly better in the production task (Experiment 1), in which imagery of object motion probably replaced reasoning processes. Participants who exhibited eye movements suggesting mental tracking performed particularly well in the production task (Experiment 2). There was, however, no decrement in performance when participants were asked to fixate the point where the target disappeared. For motion duration estimations, eye movements seem to be only a by-product of mental tracking.     

Higher visuo-Attentional Demands of Multiple Object Tracking (MOT) Lead to A Lower Precision in Pointing Movements

Multiple object tracking (MOT) requires visually attending to dynamically moving targets and distractors. This cognitive ability is based on perceptual-attentional processes that are also involved in goal-directed movements. This study aimed to test the hypothesis that MOT affects the motor performance of aiming movements. Therefore, the participants performed pointing movements using their fingers or a computer mouse that controlled the movements of a cursor directed at the targets in the MOT task. The precision of the pointing movements was measured, and it was predicted that a higher number of targets and distractors in the MOT task would result in a lower pointing precision. The results confirmed this hypothesis, indicating that MOT might influence the performance of motor actions. The potential factors underlying this influence are discussed.     

Frames of reference in perceptual-motor learning: Evidence from a blind manual positioning task

Participants moved a joystick to bring a computer-displayed cursor to each of six on-screen target locations arrayed around the center of the screen. At the start of each trial, the stick rested vertically, with a cursor occupying the center of the screen. A target appeared at another location and as soon as the stick was moved away from its rest position the cursor disappeared until the participant pressed a trigger on the stick to indicate when s/he thought the stick-controlled cursor was at the target site. With training, participants improved on the blind positioning task, but when conditions changed their performance suffered. Changing the hand used in the task or the location of the stick caused approximately equal disruptions, but changing both hand and location was significantly more disruptive than changing just one feature. The results support the hypothesis that perceptual-motor learning entails coding of extrinsic (spatial coordinates) as well as intrinsic (postural or body movement) information. Received: 14 October 1999 / Accepted: 6 November 2000