Tracking planets and moons: mechanisms of object tracking revealed with a new paradigm

Team ball sport experience minimizes sex difference in visual attention

Simultaneous tracking of the position of the ball and player locations and activities places high demands on visual attention in team ball sport athletes. Owing to their extensive sports training, these athletes may be expected to exhibit visual attention skills superior to non-athletes; however, the results of studies examining this are inconsistent. Thus, the first aim of this study was to assess the impact of participating in a team ball sport on visual attention. There is limited empirical evidence indicating a sex difference in visual attention, and few studies have reported on visual attention in male and female athletes. Thus, the second aim of this study was to determine whether team ball sport experience affected any sex differences in visual attention. In total, 44 highly skilled basketball players—22 men (mean age: 21.86 ± 2.15 years) with a mean (SD) of 8.46 (2.92) years training experience and 22 women (mean age: 21.32 ± 1.58 years) with a mean (SD) of 8.22 (2.44) years of training experience—and 44 non-athletic undergraduate college students—22 men (mean age: 21.62 ± 1.88 years) and 22 women (mean age: 21.55 ± 1.72 years)—were recruited and completed this study. Visual attention was measured by using the multiple object tracking (MOT) task. Skilled basketball players showed superior tracking accuracy to non-athletic college students on the MOT task. A significant sex difference was found only among the non-athletic college students, with better tracking accuracy for men than for women on the MOT task. By contrast, no significant sex difference was observed among the skilled basketball players for tracking accuracy on the MOT task. These findings indicated that team ball sport training may enhance visual attention as assessed by tracking accuracy. Given that the male and female basketball players in this study had similar training experience and game performance demands, long-term team ball sport experience appeared to minimize the sex difference in visual attention found among non-athletic students.

Visual tracking assessment in a soccer-specific virtual environment: A web-based study

The ability to track teammates and opponents is an essential quality to achieve a high level of performance in soccer. The visual tracking ability is usually assessed in the laboratory with non-sport specific scenarios, leading in two major concerns. First, the methods used probably only partially reflects the actual ability to track players on the field. Second, it is unclear whether the situational features manipulated to stimulate visual tracking ability match those that make it difficult to track real players. In this study, participants had to track multiple players on a virtual soccer field. The virtual players moved according to either real or pseudo-random trajectories. The experiment was conducted online using a web application. Regarding the first concern, the visual tracking performance of players in soccer, other team sports, and non-team sports was compared to see if differences between groups varied with the use of soccer-specific or pseudo-random movements. Contrary to our assumption, the ANOVA did not reveal a greater tracking performance difference between soccer players and the two other groups when facing stimuli featuring movements from actual soccer games compared to stimuli featuring pseudo-random ones. Directing virtual players with real-world trajectories did not appear to be sufficient to allow soccer players to use soccer-specific knowledge in their visual tracking activity. Regarding the second concern, an original exploratory analysis based on Hierarchical Clustering on Principal Components was conducted to compare the situational features associated with hard-to-track virtual players in soccer-specific or pseudo-random movements. It revealed differences in the situational feature sets associated with hard-to-track players based on movement type. Essentially with soccer-specific movements, how the virtual players were distributed in space appeared to have a significant influence on visual tracking performance. These results highlight the need to consider real-world scenarios to understand what makes tracking multiple players difficult.

Multiple Players Tracking in Virtual Reality: Influence of Soccer Specific Trajectories and Relationship With Gaze Activity

The perceptual-cognitive ability to track multiple moving objects and its contribution to team sports performance has traditionally been studied in the laboratory under non-sports specific conditions. It is thus questionable whether the measured visual tracking performance and the underlying gaze activity reflected the actual ability of team sports players to track teammates and opponents on a real field. Using a Virtual Reality-based visual tracking task, the ability of participants to track multiple moving virtual players as they would do on a soccer field was observed to pursue two objectives. (i) See the influence of different scenario types (soccer-specific trajectories versus pseudo-random trajectories) on the visual tracking performance of soccer (n = 15) compared to non-soccer players (n = 16). (ii) Observe the influence of spatial features of the simulated situations on gaze activity between soccer players and non-soccer players. (i) The linear mixed model regression revealed a significant main effect of the group but no interaction effect between group and the type of trajectories, suggesting that the visual tracking ability of soccer players did not benefit from their specific knowledge when they faced scenarios with real game trajectories. (ii) Virtual players’ spatial dispersion and crowding affected the participants’ gaze activity and their visual tracking performance. Furthermore, the gaze activity of soccer players differed in some aspects from the gaze activity of non-soccer players. Assumptions are formulated as to the implication of these results in the difference in visual tracking performance between soccer players and non-soccer players. Overall, using soccer-specific trajectories might not be enough to replicate the representativeness of the field conditions in the study of visual tracking performance. Multitasking constraints should be considered along with motor-cognitive dual-tasks in future research to develop the representativeness of visual exploration conditions.

Continuous theta burst TMS of area MT+ impairs attentive motion tracking

Attentive motion tracking deficits measured using multiple object tracking (MOT) tasks have been identified in a number of neurodevelopmental disorders such as amblyopia and autism. These deficits are often attributed to the abnormal development of high-level attentional networks. However, neuroimaging evidence from amblyopia suggests that reduced MOT performance can be explained by impaired function in motion-sensitive area MT+ alone. To test the hypothesis that a subtle disruption of MT+ function could cause MOT impairment, we assessed whether continuous theta burst stimulation (cTBS) of MT+ influenced MOT task accuracy in individuals with normal vision. The MOT stimulus consisted of four target and four distractor dots and was presented at ±10° eccentricity (right/left hemifield). fMRI-guided cTBS was applied to left MT+. Participants (n = 13, age: 27 ± 3) attended separate active and sham cTBS sessions where the MOT task was completed before, 5-min post- and 30-min post-cTBS. Active cTBS significantly impaired MOT task accuracy relative to baseline for the right (stimulated) hemifield 5-min (10 ± 2% reduction) and 30-min (14 ± 3% reduction) post-stimulation. No impairment occurred within the left (control) hemifield after active cTBS or for either hemifield after sham cTBS. These results highlight the importance of lower level motion processing for MOT, suggesting that a minor disruption of MT+ function alone is sufficient to cause a deficit in MOT performance.

The role of kinematic properties in multiple object tracking

People commonly track objects moving in complex natural displays and their performance in the multiple object tracking paradigm has been used to study such visual attention for more than three decades. Given the theoretical and practical importance of object tracking, it is critical to understand how people solve the correspondence problem to track objects; however, it remains unclear what information people use to achieve this feat. In particular, although people can track multiple moving objects based on their positions, there is ambiguity about whether people can track objects via higher order kinematic information, such as velocity. We designed a paradigm in which position was rendered uninformative to directly examine whether people could use higher order kinematic information to track multiple objects. We find that people can track via velocity, but not acceleration, even though observers can reliably detect the acceleration cue that they cannot use for tracking. Furthermore, we show a capacity constraint on using higher order kinematic information—people perform worse when required to use velocity to resolve correspondence for multiple object pairs simultaneously. Together, our results suggest that, although people can use higher order kinematic information for object tracking, precise higher order kinematic information is not freely available from the early visual system.

A critical systematic review of the Neurotracker perceptual-cognitive training tool

In this systematic review, we evaluate the scientific evidence behind “Neurotracker,” one of the most popular perceptual-cognitive training tools in sports. The tool, which is also used in rehabilitation and aging research to examine cognitive abilities, uses a 3D multiple object-tracking (MOT) task. In this review, we examine Neurotracker from both a sport science and a basic science perspective. We first summarize the sport science debate regarding the value of general cognitive skill training, based on tools such as Neurotracker, versus sport-specific skill training. We then consider the several hundred MOT publications in cognitive and vision science from the last 30 years that have investigated cognitive functions and object tracking processes. This literature suggests that the abilities underlying object tracking are not those advertised by the Neurotracker manufacturers. With a systematic literature search, we scrutinize the evidence for whether general cognitive skills can be tested and trained with Neurotracker and whether these trained skills transfer to other domains. The literature has major limitations, for example a total absence of preregistered studies, which makes the evidence for improvements for working memory and sustained attention very weak. For other skills as well, the effects are mixed. Only three studies investigated far transfer to ecologically valid tasks, two of which did not find any effect. We provide recommendations for future Neurotracker research to improve the evidence base and for making better use of sport and basic science findings.

Individual differences in visual attention: A short, reliable, open-source, and multilingual test of multiple object tracking in PsychoPy

Individual differences in attentional abilities provide an interesting approach in studying visual attention as well as the relation of attention to other psychometric measures. However, recent research has demonstrated that many tasks from experimental research are not suitable for individual differences research, as they fail to capture these differences reliably. Here, we provide a test for individual differences in visual attention which relies on the multiple object tracking task (MOT). This test captures individual differences reliably in 6 to 15 min. Within the task, the participants have to maintain a set of targets (among identical distractors) across an interval of object motion. It captures the efficiency of attentional deployment. Importantly, this test was explicitly designed and tested for reliability under conditions that match those of most laboratory research (restricted sample of students, approximately n = 50). The test is free to use and runs fully under open-source software. In order to facilitate the application of the test, we have translated it into 16 common languages (Chinese, Danish, Dutch, English, Finnish, French, German, Italian, Japanese, Norwegian, Polish, Portuguese, Russian, Spanish, Swedish, and Turkish). The test can be downloaded at https://osf.io/qy6nb/ . We hope that this MOT test supports researchers whose field of study requires capturing individual differences in visual attention reliably.

How Do Humans Perform in Multiple Object Tracking With Unstable Features

In real-world scenarios, objects’ surface features sometimes change as they move, impairing the continuity of objects. However, it is still unknown how our visual system adapts to this dynamic change. Hence, the present study investigated the role of feature changes in attentive tracking through a modified multiple object tracking (MOT) task. The feature heterogeneity and feature stability were manipulated in two experiments. The results from Experiment 1 showed that the tracking performance under feature-changed condition was lower than that under the feature-fixed condition only when the objects were four colors grouped or all unique, suggesting that the performance decrease was moderated by the feature heterogeneity. In Experiment 2, we further examined this effect by manipulating the frequency of feature change. The results showed that when the target set was one color or two colors grouped (the color grouping for the distractor set corresponded with it), the tracking performance decreased significantly as the feature-change frequency increased. However, this trend was not the case when the objects were of the same color or eight unique colors. In addition, a relatively consistent effect appeared both in Experiments 1 and 2. When objects have unique features, the tracking performance decreased significantly as the increase of feature heterogeneity in each frequency of feature changes. Taken together, we concluded that unstable features could be utilized in attentive tracking, and the extent to which the observers relied on surface feature information to assist tracking depended on the level of feature heterogeneity and the frequency of feature change.

Dynamic visual attention characteristics and their relationship to match performance in skilled basketball players

Background

Dynamic visual attention is important in basketball because it may affect the performance of players and thus the match outcome. The goals of this study were to investigate the difference in dynamic visual attention characteristics between highly skilled basketball players and nonathletic college students and to explore the relationship between visual attention and game-related performance among the basketball players.

Methods

In total, 24 highly skilled basketball players and 24 nonathletic college students participated in a multiple object tracking task. The task was conducted so that either the number of targets that were visually tracked or the speed at which a given number of tracked targets moved was altered to examine the difference in dynamic visual attention characteristics between the basketball players and nonathletic college students. The relationship between visual tracking speed (VTS) and game-related statistics, including assists, steals, mistakes, fouls and points scored recorded for every match during the season, was assessed among the basketball players by using Pearson correlations.

Results

A significant main effect of target tracking load was observed (P < 0.001), with visual tracking performance significantly decreased as target number increased. In addition, the speed at which the targets moved had a significant effect on visual tracking performance (P < 0.001), with tracking performance significantly decreased as target speed increased. However, no significant difference was observed in the abilities of basketball players and nonathletic college students to simultaneously track up to six targets. By contrast, a significant interaction between group and target speed was found (P < 0.001), with the visual tracking accuracy of basketball players significantly greater than that of college students at the higher target speeds examined (P < 0.001). Among basketball players, there were positive, large, and statistically significant correlations in the accuracy in VTS trials and the number of assists (P < 0.001) and between the accuracy in VTS trials and the number of steals (P < 0.001).

Conclusion

The advantage of skilled basketball players to handle dynamic visual information in a multiple object tracking task was not attributable to the target number but to the target speed. Those athletes with greater dynamic visual attention were more likely to successfully assist or to steal the ball, enhancing performance of the athlete as well as contributing to a more successful team match. These findings may inform basketball training programs to improve player and team performances during matches.

Multiple-target tracking in human and machine vision

Humans are able to track multiple objects at any given time in their daily activities—for example, we can drive a car while monitoring obstacles, pedestrians, and other vehicles. Several past studies have examined how humans track targets simultaneously and what underlying behavioral and neural mechanisms they use. At the same time, computer-vision researchers have proposed different algorithms to track multiple targets automatically. These algorithms are useful for video surveillance, team-sport analysis, video analysis, video summarization, and human–computer interaction. Although there are several efficient biologically inspired algorithms in artificial intelligence, the human multiple-target tracking (MTT) ability is rarely imitated in computer-vision algorithms. In this paper, we review MTT studies in neuroscience and biologically inspired MTT methods in computer vision and discuss the ways in which they can be seen as complementary.

Multiple-target tracking (MTT) is a challenging task vital for both a human’s daily life and for many artificial intelligent systems, such as those used for urban traffic control. Neuroscientists are interested in discovering the underlying neural mechanisms that successfully exploit cognitive resources, e.g., spatial attention or memory, during MTT. Computer-vision specialists aim to develop powerful MTT algorithms based on advanced models or data-driven computational methods. In this paper, we review MTT studies from both communities and discuss how findings from cognitive studies can inspire developers to construct higher performing MTT algorithms. Moreover, some directions have been proposed through which MTT algorithms could raise new questions in the cognitive science domain, and answering them can shed light on neural processes underlying MTT.

The Effect of Fearful Expressions on Multiple Face Tracking

How does the visual system realize dynamic tracking? This topic has become popular within cognitive science in recent years. The classical theory argues that multiple object tracking is accomplished via pre-attention visual indexes as part of a cognitively impenetrable low-level visual system. The present research aimed to investigate whether and how tracking processes are influenced by facial expressions that convey abundant social information about one’s mental state and situated environment. The results showed that participants tracked fearful faces more effectively than neutral faces. However, this advantage was only present under the low-attentional load condition, and distractor face emotion did not impact tracking performance. These findings imply that visual tracking is not driven entirely by low-level vision and encapsulated by high-level representations; rather, that facial expressions, a kind of social information, are able to influence dynamic tracking. Furthermore, the effect of fearful expressions on multiple face tracking is mediated by the availability of attentional resources.

Distractor Locations Influence Multiple Object Tracking Beyond Interobject Spacing: Evidence From Equidistant Distractor Displacements

Human observers are able to keep track of several independently moving objects among other objects. Within theories of multiple object tracking (MOT), distractors are assumed to influence tracking performance only by their distance toward the next target. In order to test this assumption, we designed a variant of the MOT paradigm that involved spatially arranged target-distractor pairs and sudden displacements of distractors during a brief flash. Critically, these displacements maintained target-distractor spacing. Our results show that displacing distractors hurts tracking performance (Experiment 1). Importantly, target-distractor confusions occur within target-distractor pairs with displaced distractors (Experiment 2). This displacement effect increases with an increasing displacement angle (Experiment 3) but is equal at different distances between target and distractor (Experiment 4). This finding illustrates that distractors influence tracking performance beyond pure interobject spacing. We discuss how inhibitory processes as well as relations between targets and distractors might interfere with target tracking.

Why do people appear not to extrapolate trajectories during multiple object tracking? A computational investigation

Intuitively, extrapolating object trajectories should make visual tracking more accurate. This has proven to be true in many contexts that involve tracking a single item. But surprisingly, when tracking multiple identical items in what is known as "multiple object tracking," observers often appear to ignore direction of motion, relying instead on basic spatial memory. We investigated potential reasons for this behavior through probabilistic models that were endowed with perceptual limitations in the range of typical human observers, including noisy spatial perception. When we compared a model that weights its extrapolations relative to other sources of information about object position, and one that does not extrapolate at all, we found no reliable difference in performance, belying the intuition that extrapolation always benefits tracking. In follow-up experiments we found this to be true for a variety of models that weight observations and predictions in different ways; in some cases we even observed worse performance for models that use extrapolations compared to a model that does not at all. Ultimately, the best performing models either did not extrapolate, or extrapolated very conservatively, relying heavily on observations. These results illustrate the difficulty and attendant hazards of using noisy inputs to extrapolate the trajectories of multiple objects simultaneously in situations with targets and featurally confusable nontargets.

Speed has an effect on multiple-object tracking independently of the number of close encounters between targets and distractors

Multiple-object tracking (MOT) studies have shown that tracking ability declines as object speed increases. However, this might be attributed solely to the increased number of times that target and distractor objects usually pass close to each other ("close encounters") when speed is increased, resulting in more target-distractor confusions. The present study investigates whether speed itself affects MOT ability by using displays in which the number of close encounters is held constant across speeds. Observers viewed several pairs of disks, and each pair rotated about the pair's midpoint and, also, about the center of the display at varying speeds. Results showed that even with the number of close encounters held constant across speeds, increased speed impairs tracking performance, and the effect of speed is greater when the number of targets to be tracked is large. Moreover, neither the effect of number of distractors nor the effect of target-distractor distance was dependent on speed, when speed was isolated from the typical concomitant increase in close encounters. These results imply that increased speed does not impair tracking solely by increasing close encounters. Rather, they support the view that speed affects MOT capacity by requiring more attentional resources to track at higher speeds.

Changing target trajectories influences tracking performance

People have the ability to attentively select and successfully track several moving objects, a process known as multiple-object tracking (MOT; Pylyshyn & Storm Spatial Vision 3: 179-197, 1988). Various factors have been known to influence MOT performance, such as speed, number of distractors, and proximity, while recent work has suggested that object trajectories may also be a factor (Fencsik, Kleiger, & Horowitz Perception and Psychophysics 69: 567-577, 2007). Meanwhile, unexpected changes in motion information have been demonstrated to be a critical facet for attracting attention Howard & Holcombe Attention, Perception & Psychophysics 72: 2087-2095, (2010). Therefore, we suggest that unexpected changes in target trajectories are an important factor in tracking performance. The research presented here controlled for spatial proximity while manipulating the number of instances in which an object changed trajectory. We found that spatial proximity had no effect on tracking performance but, rather, as the number of trajectory changes increased, tracking performance suffered. Results imply that the ability to track multiple moving objects is limited by unexpected changes in direction.

Exhausting attentional tracking resources with a single fast-moving object

Driving on a busy road, eluding a group of predators, or playing a team sport involves keeping track of multiple moving objects. In typical laboratory tasks, the number of visual targets that humans can track is about four. Three types of theories have been advanced to explain this limit. The fixed-limit theory posits a set number of attentional pointers available to follow objects. Spatial interference theory proposes that when targets are near each other, their attentional spotlights mutually interfere. Resource theory asserts that a limited resource is divided among targets, and performance reflects the amount available per target. Utilising widely separated objects to avoid spatial interference, the present experiments validated the predictions of resource theory. The fastest target speed at which two targets could be tracked was much slower than the fastest speed at which one target could be tracked. This speed limit for tracking two targets was approximately that predicted if at high speeds, only a single target could be tracked. This result cannot be accommodated by the fixed-limit or interference theories. Evidently a fast target, if it moves fast enough, can exhaust attentional resources.