Keeping your eyes continuously on the ball while running for catchable and uncatchable fly balls

The predictive outfielder: a critical test across gravities

Intercepting moving targets is a widespread challenge across many species. In humans, heuristics that use optic variables have excelled in guiding interception, relying on a closed-loop system to couple optic variables directly with direction of locomotion. This contrasts with models that explicitly recover final positions from initial trajectory conditions. However, comparing these different approaches using empirical data is challenging, as they often predict similar locomotion trajectories. We present a model based on optic variables that continuously updates predictions on the landing position in the three-dimensional scene and remaining flight time based on the outfielder's real-time movements. A distinct feature is the model's adaptability to different gravitational accelerations, making its predictions inherently tailored to specific environments. By actively integrating gravity, our model produces trajectory predictions that can be validated against actual paths. To compare our model with previous ones, we conducted experiments within virtual reality, strategically varying simulated gravity and physical size. The variation in gravity resulted in qualitatively distinct predictions between heuristics based solely on optic variables and our model, which incorporates gravity. The empirical trajectories, kinematic patterns and timing responses aligned well with our model's predictions, emphasizing the importance of including environmental constants.

Can I catch this ball and do I know if I can? Characterizing the affordance of interceptability for oneself

In this study, we aimed to characterize the affordance of interceptability for oneself using a manual lateral interception paradigm. We asked a two-fold research question: (1) What makes a virtual ball interceptable or not? (2) How reliably can individuals perceive this affordance for oneself? We hypothesized that a spatiotemporal boundary would determine the interceptability of a ball, and that individuals would be able to perceive this boundary and make accurate perceptual judgments regarding their own interceptability. To test our hypotheses, we administered a manual lateral interception task to 15 subjects. They were first trained on the task, which was followed by two experimental sessions: action and judging. In the former, participants were instructed to intercept as many virtual balls as possible using a hand-held slider to control an on-screen paddle. In the latter session, while making interceptions, participants were instructed to call "no" as soon as they perceived a ball to be uninterceptable. Using generalized linear modeling on the data, we found a handful of factors that best characterized the affordance of interceptability. As hypothesized, distance to be covered and ball flight time shaped the boundary between interceptable and uninterceptable balls. Surprisingly, the angle of approach of the ball also co-determined interceptability. Altogether, these variables characterized the actualized interceptability. Secondly, participants accurately perceived their own ability to intercept balls on over 75% of trials, thus supporting our hypothesis on perceived interceptability. Analyses revealed that participants considered this action boundary while making their perceptual judgments. Our results imply that the perceiving and actualizing of interceptability are characterized by a combination of the same set of variables.

How the conception of control influences our understanding of actions

Wilful movement requires neural control. Commonly, neural computations are thought to generate motor commands that bring the musculoskeletal system - that is, the plant - from its current physical state into a desired physical state. The current state can be estimated from past motor commands and from sensory information. Modelling movement on the basis of this concept of plant control strives to explain behaviour by identifying the computational principles for control signals that can reproduce the observed features of movements. From an alternative perspective, movements emerge in a dynamically coupled agent-environment system from the pursuit of subjective perceptual goals. Modelling movement on the basis of this concept of perceptual control aims to identify the controlled percepts and their coupling rules that can give rise to the observed characteristics of behaviour. In this Perspective, we discuss a broad spectrum of approaches to modelling human motor control and their notions of control signals, internal models, handling of sensory feedback delays and learning. We focus on the influence that the plant control and the perceptual control perspective may have on decisions when modelling empirical data, which may in turn shape our understanding of actions.

Pulled fly balls are harder to catch: a game analysis with a machine learning approach

Two hypotheses were tested: (1) the deflecting motion of fly balls caused by aerodynamic effects varies between the pull side and opposite side of the fair territory, and (2) the probability of flyout is lower on the pull side than the opposite side in Japan’s professional baseball games. From all radar-tracking outputs of official games in 2018–2019, fly balls that resulted in outs or base hits were selected for analysis (N = 25,413), and indices representing horizontal and vertical deflecting motions of fly balls were computed and compared between the pull side and opposite side. A machine learning algorithm was used to construct a model to predict the probability of flyout from the kinematic characteristics of fly balls. Flyout zones where the probability of flyout was > 0.6 were computed for a systematically constructed set of fly balls having identical distribution between the pull side and opposite side. The results showed that: (1) most fly balls landing on the opposite side deflected in the same direction whereas the pulled fly balls deflected to either direction, (2) the pulled low fly balls had greater variability in the deflecting motions than the opposite side counterpart, (3) overall probability of flyout of the low fly balls was lower in the pull side (0.41) than the opposite side (0.49), and (4) the flyout zone of an outfielder in the pull side (mean = 698 m2) for low fly balls was smaller than that of the others (≥ 779 m2). The hypotheses were supported. The pulled low fly balls had substantial variations in the direction and magnitude of deflections, which might have reduced the flyout zone on the pull side.

Gravity and Known Size Calibrate Visual Information to Time Parabolic Trajectories

Catching a ball in a parabolic flight is a complex task in which the time and area of interception are strongly coupled, making interception possible for a short period. Although this makes the estimation of time-to-contact (TTC) from visual information in parabolic trajectories very useful, previous attempts to explain our precision in interceptive tasks circumvent the need to estimate TTC to guide our action. Obtaining TTC from optical variables alone in parabolic trajectories would imply very complex transformations from 2D retinal images to a 3D layout. We propose based on previous work and show by using simulations that exploiting prior distributions of gravity and known physical size makes these transformations much simpler, enabling predictive capacities from minimal early visual information. Optical information is inherently ambiguous, and therefore, it is necessary to explain how these prior distributions generate predictions. Here is where the role of prior information comes into play: it could help to interpret and calibrate visual information to yield meaningful predictions of the remaining TTC. The objective of this work is: (1) to describe the primary sources of information available to the observer in parabolic trajectories; (2) unveil how prior information can be used to disambiguate the sources of visual information within a Bayesian encoding-decoding framework; (3) show that such predictions might be robust against complex dynamic environments; and (4) indicate future lines of research to scrutinize the role of prior knowledge calibrating visual information and prediction for action control.

Review: Head and Eye Movements and Gaze Tracking in Baseball Batting

SIGNIFICANCE

After a 30-year gap, several studies on head and eye movements and gaze tracking in baseball batting have been performed in the last decade. These baseball studies may lead to training protocols for batting. Here we review these studies and compare the tracking behaviors with those in other sports.Baseball batters are often instructed to "keep your eye on the ball." Until recently, the evidence regarding whether batters follow this instruction and if there are benefits to following this instruction was limited. Baseball batting studies demonstrate that batters tend to move the head more than the eyes in the direction of the ball at least until a saccade occurs. Foveal gaze tracking is often maintained on the ball through the early portion of the pitch, so it can be said that baseball batters do keep the eyes on the ball. While batters place gaze at or near the point of bat-ball contact, the way this is accomplished varies. In some studies, foveal gaze tracking continues late in the pitch trajectory, whereas in other studies, anticipatory saccades occur. The relative advantages of these discrepant gaze strategies on perceptual processing and motor planning speed and accuracy are discussed, and other variables that may influence anticipatory saccades including the predictability of the pitch and the level of batter expertise are described. Further studies involving larger groups with different levels of expertise under game conditions are required to determine which gaze tracking strategies are most beneficial for baseball batting.

Affordance-based versus current-future accounts of choosing whether to pursue or abandon the chase of a moving target

Affordance-based control and current-future control offer competing theoretical accounts of the visual control of locomotion. The aim of this study was to test predictions derived from these accounts about the necessity of self-motion (Experiment 1) and target-ground contact (Experiment 2) in perceiving whether a moving target can be intercepted before it reaches an escape zone. We designed a novel interception task wherein the ability to perceive target catchability before initiating movement was advantageous. Subjects pursued a target moving through a field in a virtual environment and attempted to intercept the target before it escaped into a forest. Targets were catchable on some trials but not others. If subjects perceived that they could not reach the target, they were instructed to immediately give up by pressing a button. After each trial, subjects received a point reward that incentivized them to pursue only those targets that were catchable. On the majority of trials, subjects either pursued and successfully intercepted the target or chose not to pursue at all, demonstrating that humans are sensitive to catchability while stationary. Performance also degraded when the target was floating rather than in contact with the ground. Both findings are incompatible with the current-future account and support the affordance-based account of choosing whether to pursue moving targets.

The visual control of interceptive steering: How do people steer a car to intercept a moving target?

The visually guided interception of a moving target is a fundamental visuomotor task that humans can do with ease. But how humans carry out this task is still unclear despite numerous empirical investigations. Measurements of angular variables during human interception have suggested three possible strategies: the pursuit strategy, the constant bearing angle strategy, and the constant target-heading strategy. Here, we review previous experimental paradigms and show that some of them do not allow one to distinguish among the three strategies. Based on this analysis, we devised a virtual driving task that allows investigating which of the three strategies best describes human interception. Crucially, we measured participants' steering, head, and gaze directions over time for three different target velocities. Subjects initially aligned head and gaze in the direction of the car's heading. When the target appeared, subjects centered their gaze on the target, pointed their head slightly off the heading direction toward the target, and maintained an approximately constant target-heading angle, whose magnitude varied across participants, while the target's bearing angle continuously changed. With a second condition, in which the target was partially occluded, we investigated several alternative hypotheses about participants' visual strategies. Overall, the results suggest that interceptive steering is best described by the constant target-heading strategy and that gaze and head are coordinated to continuously acquire visual information to achieve successful interception.

Continuously updating one’s predictions underlies successful interception

This paper reviews our understanding of the interception of moving objects. Interception is a demanding task that requires both spatial and temporal precision. The required precision must be achieved on the basis of imprecise and sometimes biased sensory information. We argue that people make precise interceptive movements by continuously adjusting their movements. Initial estimates of how the movement should progress can be quite inaccurate. As the movement evolves, the estimate of how the rest of the movement should progress gradually becomes more reliable as prediction is replaced by sensory information about the progress of the movement. The improvement is particularly important when things do not progress as anticipated. Constantly adjusting one’s estimate of how the movement should progress combines the opportunity to move in a way that one anticipates will best meet the task demands with correcting for any errors in such anticipation. The fact that the ongoing movement might have to be adjusted can be considered when determining how to move, and any systematic anticipation errors can be corrected on the basis of the outcome of earlier actions.

When a Fly Ball Is Out of Reach: Catchability Judgments Are Not Based on Optical Acceleration Cancelation

The optical acceleration cancelation (OAC) strategy, based on Chapman's (1968) analysis of the outfielder problem, has been the dominant account for the control of running to intercept fly balls approaching head on. According to the OAC strategy, outfielders will arrive at the interception location just in time to catch the ball when they keep optical acceleration zero. However, the affordance aspect of this task, that is, whether or not an approaching fly ball is catchable, is not part of this account. The present contribution examines whether the scope of the OAC strategy can be extended to also include the affordance aspect of running to catch a fly ball. This is done by considering a fielder's action boundaries (i.e., maximum running velocity and -acceleration) in the context of the OAC strategy. From this, only when running velocity is maximal and optical acceleration is non-zero, a fielder would use OAC to perceive a fly ball as uncatchable. The present contribution puts this hypothesis to the test. Participants were required to try to intercept fly balls projected along their sagittal plane. Some fly balls were catchable whereas others were not. Participants were required to catch as many fly balls as possible and to call 'no' when they perceived a fly ball to be uncatchable. Participants' running velocity and -acceleration at the moment of calling 'no' were examined. Results showed that participants' running velocity was submaximal before or while calling 'no'. Also running acceleration was often submaximal. These results cannot be explained by the use of OAC in judging catchability and ultimately call for a new strategy of locomotor control in running to catch a fly ball.