Individual differences link sensory processing and motor control.

Research on saccadic and pursuit eye movements led to great advances in our understanding of sensorimotor processing and human behavior. However, studies often have focused on isolated saccadic and pursuit eye movements measured with respect to different sensory information (static vs. dynamic targets). Here, we leveraged interindividual differences across a carefully balanced combination of different tasks to demonstrate that critical links in the control of oculomotor behavior were previously missed. We observed correlations in eye movement behavior across tasks, but only when compared with the same sensory information (e.g., pursuit gain and accuracy of saccades to moving targets). Within the same task, the coordination of saccadic and pursuit eye movements was tailored to the strengths of the individual: observers with more accurate saccades to moving targets rely on them more to catch up with moving targets. Our results have profound implications for the theoretical understanding of sensorimotor processing for oculomotor control. They necessitate a reevaluation of previous data used to map brain circuits for saccadic and pursuit eye movements measured with different types of relevant sensory information. Additionally, they underscore the importance of moving beyond average observations to embrace individual differences as a rich source of information. These individual differences not only reveal the strengths and weaknesses of observers. When combined across different tasks, they allow insights about why observers behave differently in a given task. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Oculomotor routines for perceptual judgments.

In everyday life we frequently make simple visual judgments about object properties, for example, how big or wide is a certain object? Our goal is to test whether there are also task-specific oculomotor routines that support perceptual judgments, similar to the well-established exploratory routines for haptic perception. In a first study, observers saw different scenes with two objects presented in a photorealistic virtual reality environment. Observers were asked to judge which of two objects was taller or wider while gaze was tracked. All tasks were performed with the same set of virtual objects in the same scenes, so that we can compare spatial characteristics of exploratory gaze behavior to quantify oculomotor routines for each task. Width judgments showed fixations around the center of the objects with larger horizontal spread. In contrast, for height judgments, gaze was shifted toward the top of the objects with larger vertical spread. These results suggest specific strategies in gaze behavior that presumably are used for perceptual judgments. To test the causal link between oculomotor behavior and perception, in a second study, observers could freely gaze at the object or we introduced a gaze-contingent setup forcing observers to fixate specific positions on the object. Discrimination performance was similar between free-gaze and the gaze-contingent conditions for width and height judgments. These results suggest that although gaze is adapted for different tasks, performance seems to be based on a perceptual strategy, independent of potential cues that can be provided by the oculomotor system.

Cues for predictive eye movements in naturalistic scenes.

We previously compared following of the same trajectories with eye movements, but either as an isolated targets or embedded in a naturalistic scene-in this case, the movement of a puck in an ice hockey game. We observed that the oculomotor system was able to leverage the contextual cues available in the naturalistic scene to produce predictive eye movements. In this study, we wanted to assess which factors are critical for achieving this predictive advantage by manipulating four factors: the expertise of the viewers, the amount of available peripheral information, and positional and kinematic cues. The more peripheral information became available (by manipulating the area of the video that was visible), the better the predictions of all observers. However, expert ice hockey fans were consistently better at predicting than novices and used peripheral information more effectively for predictive saccades. Artificial cues about player positions did not lead to a predictive advantage, whereas impairing the causal structure of kinematic cues by playing the video in reverse led to a severe impairment. When videos were flipped vertically to introduce more difficult kinematic cues, predictive behavior was comparable to watching the original videos. Together, these results demonstrate that, when contextual information is available in naturalistic scenes, the oculomotor system is successfully integrating them and is not relying only on low-level information about the target trajectory. Critical factors for successful prediction seem to be the amount of available information, experience with the stimuli, and the availability of intact kinematic cues for player movements.

The effect of impaired velocity signals on goal-directed eye and hand movements.

Information about position and velocity is essential to predict where moving targets will be in the future, and to accurately move towards them. But how are the two signals combined over time to complete goal-directed movements? We show that when velocity information is impaired due to using second-order motion stimuli, saccades directed towards moving targets land at positions where targets were ~ 100 ms before saccade initiation, but hand movements are accurate. Importantly, the longer latencies of hand movements allow for additional time to process the sensory information available. When increasing the period of time one sees the moving target before making the saccade, saccades become accurate. In line with that, hand movements with short latencies show higher curvature, indicating corrections based on an update of incoming sensory information. These results suggest that movements are controlled by an independent and evolving combination of sensory information about the target's position and velocity.

Serial dependence for oculomotor control depends on early sensory signals.

To create an accurate percept of the world, the visual system relies on past experience and prior assumptions.1 For example, although the retinal projection of an object moving in depth changes drastically, we still perceive the object at a constant size and velocity.2,3 Consequently, if we see the same object with a constant retinal size at two different depth levels, the perceived size differs (illustrated by the Ponzo illusion). Past experience also directly influences perceptual judgments, an effect known as serial dependence.4,5 Such sequential effects have also been reported for oculomotor behavior, even on the trial-by-trial level.6-10 An integration of past experiences seems like a smart and sophisticated mechanism to reduce uncertainty and improve behavior in a world full of statistical regularities. By leveraging the Ponzo illusion to dissociate perceived size and speed from retinal signals, we show that serial-dependence effects for oculomotor control are mediated by retinal error signals. These sequential effects likely take place in early sensory processing because they transfer to different visual stimuli. In contrast to recently reported history effects for perceptual decisions,11 sequential effects for oculomotor control deviate from perceptual mechanisms by not integrating spatial context and by ignoring size and velocity constancy. Although this dissociation might appear suboptimal, we argue that this effect reveals the different goals of the oculomotor and perceptual systems. The oculomotor system tries to reduce retinal error signals to bring and keep the target close to the fovea, whereas the visual system interprets retinal input to achieve an accurate representation of the world.12.

A change in perspective: The interaction of saccadic and pursuit eye movements in oculomotor control and perception.

Due to the close relationship between oculomotor behavior and visual processing, eye movements have been studied in many different areas of research over the last few decades. While these studies have brought interesting insights, specialization within each research area comes at the potential cost of a narrow and isolated view of the oculomotor system. In this review, we want to expand this perspective by looking at the interactions between the two most important types of voluntary eye movements: saccades and pursuit. Recent evidence indicates multiple interactions and shared signals at the behavioral and neurophysiological level for oculomotor control and for visual perception during pursuit and saccades. Oculomotor control seems to be based on shared position- and velocity-related information, which leads to multiple behavioral interactions and synergies. The distinction between position- and velocity-related information seems to be also present at the neurophysiological level. In addition, visual perception seems to be based on shared efferent signals about upcoming eye positions and velocities, which are to some degree independent of the actual oculomotor response. This review suggests an interactive perspective on the oculomotor system, based mainly on different types of sensory input, and less so on separate subsystems for saccadic or pursuit eye movements.

Ice hockey spectators use contextual cues to guide predictive eye movements.

Eye movements are an integral part of human visual perception. They allow us to have a small foveal region with exquisite acuity and at the same time a large visual field. For a long time, eye movements were regarded as machine-like behaviors in response to visual stimulation1, but over the past few decades it has been convincingly shown that expectations, intended actions, rewards and many other cognitive factors can have profound effects on the way we move our eyes2-4. In order to be useful, our oculomotor system must minimize delay with respect to the dynamic events in the visual scene. The ability to do so has been demonstrated in situations where we are in control of these events, for example when we are making a sandwich or tea5, and when we are active participants, for example when hitting a cricket ball6. But what about scenes with complex dynamics that we do not control or directly take part in, like a hockey game we are watching as a spectator? A semantic influence on gaze fixation location during viewing of tennis videos has been suggested before7. Here we use carefully annotated hockey videos to show that the brain is indeed able to exploit the semantic context of the game to anticipate the continuous motion of the puck, leading to eye movements that are fundamentally different than when following exactly the same motion without any context.

Retinal error signals and fluctuations in eye velocity influence oculomotor behavior in subsequent trials.

The oculomotor system makes use of an integration of previous stimulus velocities (the prior) and current sensory inputs to adjust initial eye speeds. The present study extended this research by investigating the roles of different retinal or extra-retinal signals for this process. To test for this, participants viewed movement sequences that all ended with the same test trial. Earlier in the sequence, the prior was manipulated by presenting targets that either had different velocities, different starting positions, or target movements designed to elicit differential oculomotor behavior (tracked with or without additional corrective saccades). Additionally, these prior targets could vary in terms of contrast to manipulate reliability. When the velocity of prior trials differed from test trials, the reliability-weighted integration of prior information was replicated. When the prior trials differed in starting position, significant effects on subsequent oculomotor behavior were only observed for the reliable target. Although there were also differences in eye velocity across the different manipulations, they could not explain the observed reliability-weighted integration. When comparing the same physical prior trials but tracked with additional corrective saccades, the eye velocity in the test trial also differed systematically (slower for forward saccades, and faster for backward saccades). The direction of the observed effect contradicts the expectations based on perceived speed and eye velocity, but can be predicted by a combination of retinal velocity and position error signals. Together, these results suggest that general fluctuations in eye velocity as well as retinal error signals are related to oculomotor behavior in subsequent trials.

Somatosensory target information is used for reaching but not for saccadic eye movements.

For any type of goal-directed hand and eye movement, it is important to determine the position of the target. Though many of these movements are directed toward visual targets, humans also perform movements to targets derived by somatosensory information only, such as proprioceptive (sensory signals about static limb position), kinesthetic (sensory signals about limb movement), and tactile signals (sensory signals about touch on skin). In this study we investigated how each of these types of somatosensory information influences goal-directed hand and eye movements. Furthermore, we examined whether somatosensory target information has a differential influence on isolated and combined eye-hand movements. Participants performed right-hand reaching, eye, or coordinated eye-hand movements to their left index or middle fingers in the absence of any visual information. We varied somatosensory target information by allowing proprioceptive, proprioceptive-kinesthetic, proprioceptive-tactile, or proprioceptive-kinesthetic-tactile information. Reach endpoint precision was poorest when the target was derived by proprioceptive information only but improved when two different types of input were available. In addition, reach endpoints in conditions with kinesthetic target information were systematically shifted toward the direction of movement, while static somatosensory information decayed over time and led to systematic undershoots of the reach target location. In contrast to the effect on reaches, somatosensory information did not influence gaze endpoint accuracy or precision. When performing coordinated eye-hand movements reach accuracy and gaze endpoint precision improved, suggesting a bidirectional use of efferent information. We conclude that somatosensory target information influence endpoint control differently for goal-directed hand and eye movements to unseen targets.NEW & NOTEWORTHY A systematic investigation of contributions of different somatosensory modalities (proprioception, kinesthesia, tactile) for goal-directed movements is missing. Here we demonstrate that while eye movements are not affected by different types of somatosensory information, reach precision improves when two different types of information are available. Moreover, reach accuracy and gaze precision to unseen somatosensory targets improve when performing coordinated eye-hand movements, suggesting bidirectional contributions of efferent information in reach and eye movement control.

From Gaussian blobs to naturalistic videos: Comparison of oculomotor behavior across different stimulus complexities.

Research on eye movements has primarily been performed in two distinct ways: (1) under highly controlled conditions using simple stimuli such as dots on a uniform background, or (2) under free-viewing conditions with complex images, real-world movies, or even with observers moving around in the world. Although both approaches offer important insights, the generalizability among eye movement behaviors observed under these different conditions is unclear. Here, we compared eye movement responses to video clips showing moving objects within their natural context with responses to simple Gaussian blobs on a blank screen. Importantly, for both conditions, the targets moved along the same trajectories at the same speed. We measured standard oculometric measures for both stimulus complexities, as well as the effect of the relative angle between saccades and pursuit, and compared them across conditions. In general, eye movement responses were qualitatively similar, especially with respect to pursuit gain. For both types of stimuli, the accuracy of saccades and subsequent pursuit was highest when both eye movements were collinear. We also found interesting differences; for example, latencies of initial saccades to moving Gaussian blob targets were significantly faster compared to saccades to moving objects in video scenes, whereas pursuit accuracy was significantly higher in video scenes. These findings suggest a lower processing demand for simple target conditions during saccade preparation and an advantage for tracking behavior in natural scenes due to higher predictability provided by the context information.

Dynamic combination of position and motion information when tracking moving targets.

To accurately foveate a moving target, the oculomotor system needs to estimate the position of the target at the saccade end, based on information about its position and ongoing movement, while accounting for neuronal delays and execution time of the saccade. We investigated human interceptive saccades and pursuit responses to moving targets defined by high and low luminance contrast or by chromatic contrast only (isoluminance). We used step-ramps with perpendicular directions between vertical target steps of 10 deg/s and horizontal ramps of 2.5 to 20 deg/s to separate errors with respect to the position step of the target in the vertical dimension, and errors related to target motion in the horizontal dimension. Interceptive saccades to targets of high and low luminance contrast landed close to the actual target positions, suggesting relatively accurate estimates of the amount of target displacement. Interceptive saccades to isoluminant targets were less accurate. They landed at positions the target had on average 100 ms before saccade onset. One account of this finding is that the integration of target motion is compromised for isoluminant targets moving in the periphery. In this case, the oculomotor system can use an accurate, but delayed position component, but cannot account for target movement. This deficit was also present for the postsaccadic pursuit speed. For the two luminance conditions, pursuit direction and speed were adjusted depending on the saccadic landing position. The rapid postsaccadic pursuit adjustments suggest shared position- and motion-related signals of target and eye for saccade and pursuit control.

Corrective saccades influence velocity judgments and interception.

In daily life we often interact with moving objects in tasks that involve analyzing visual motion, like catching a ball. To do so successfully we track objects with our gaze, using a combination of smooth pursuit and saccades. Previous work has shown that the occurrence and direction of corrective saccades leads to changes in the perceived velocity of moving objects. Here we investigate whether such changes lead to equivalent biases in interception. Participants had to track moving targets with their gaze, and in separate sessions either judge the targets' velocities or intercept them by tapping on them. We separated trials in which target movements were tracked with pure pursuit from trials in which identical target movements were tracked with a combination of pursuit and corrective saccades. Our results show that interception errors are shifted in accordance with the observed influence of corrective saccades on velocity judgments. Furthermore, while the time at which corrective saccades occurred did not affect velocity judgments, it did influence their effect in the interception task. Corrective saccades around 100 ms before the tap had a stronger effect on the endpoint error than earlier saccades. This might explain why participants made earlier corrective saccades in the interception task.

Execution of saccadic eye movements affects speed perception.

Due to the foveal organization of our visual system we have to constantly move our eyes to gain precise information about our environment. Doing so massively alters the retinal input. This is problematic for the perception of moving objects, because physical motion and retinal motion become decoupled and the brain has to discount the eye movements to recover the speed of moving objects. Two different types of eye movements, pursuit and saccades, are combined for tracking. We investigated how the way we track moving targets can affect the perceived target speed. We found that the execution of corrective saccades during pursuit initiation modifies how fast the target is perceived compared with pure pursuit. When participants executed a forward (catch-up) saccade they perceived the target to be moving faster. When they executed a backward saccade they perceived the target to be moving more slowly. Variations in pursuit velocity without corrective saccades did not affect perceptual judgments. We present a model for these effects, assuming that the eye velocity signal for small corrective saccades gets integrated with the retinal velocity signal during pursuit. In our model, the execution of corrective saccades modulates the integration of these two signals by giving less weight to the retinal information around the time of corrective saccades.

Discrimination of curvature from motion during smooth pursuit eye movements and fixation.

Smooth pursuit and motion perception have mainly been investigated with stimuli moving along linear trajectories. Here we studied the quality of pursuit movements to curved motion trajectories in human observers and examined whether the pursuit responses would be sensitive enough to discriminate various degrees of curvature. In a two-interval forced-choice task subjects pursued a Gaussian blob moving along a curved trajectory and then indicated in which interval the curve was flatter. We also measured discrimination thresholds for the same curvatures during fixation. Motion curvature had some specific effects on smooth pursuit properties: trajectories with larger amounts of curvature elicited lower open-loop acceleration, lower pursuit gain, and larger catch-up saccades compared with less curved trajectories. Initially, target motion curvatures were underestimated; however, ∼300 ms after pursuit onset pursuit responses closely matched the actual curved trajectory. We calculated perceptual thresholds for curvature discrimination, which were on the order of 1.5 degrees of visual angle (°) for a 7.9° curvature standard. Oculometric sensitivity to curvature discrimination based on the whole pursuit trajectory was quite similar to perceptual performance. Oculometric thresholds based on smaller time windows were higher. Thus smooth pursuit can quite accurately follow moving targets with curved trajectories, but temporal integration over longer periods is necessary to reach perceptual thresholds for curvature discrimination.NEW & NOTEWORTHY Even though motion trajectories in the real world are frequently curved, most studies of smooth pursuit and motion perception have investigated linear motion. We show that pursuit initially underestimates the curvature of target motion and is able to reproduce the target curvature ∼300 ms after pursuit onset. Temporal integration of target motion over longer periods is necessary for pursuit to reach the level of precision found in perceptual discrimination of curvature.

Kinesthetic information facilitates saccades towards proprioceptive-tactile targets.

Saccades to somatosensory targets have longer latencies and are less accurate and precise than saccades to visual targets. Here we examined how different somatosensory information influences the planning and control of saccadic eye movements. Participants fixated a central cross and initiated a saccade as fast as possible in response to a tactile stimulus that was presented to either the index or the middle fingertip of their unseen left hand. In a static condition, the hand remained at a target location for the entire block of trials and the stimulus was presented at a fixed time after an auditory tone. Therefore, the target location was derived only from proprioceptive and tactile information. In a moving condition, the hand was first actively moved to the same target location and the stimulus was then presented immediately. Thus, in the moving condition additional kinesthetic information about the target location was available. We found shorter saccade latencies in the moving compared to the static condition, but no differences in accuracy or precision of saccadic endpoints. In a second experiment, we introduced variable delays after the auditory tone (static condition) or after the end of the hand movement (moving condition) in order to reduce the predictability of the moment of the stimulation and to allow more time to process the kinesthetic information. Again, we found shorter latencies in the moving compared to the static condition but no improvement in saccade accuracy or precision. In a third experiment, we showed that the shorter saccade latencies in the moving condition cannot be explained by the temporal proximity between the relevant event (auditory tone or end of hand movement) and the moment of the stimulation. Our findings suggest that kinesthetic information facilitates planning, but not control, of saccadic eye movements to proprioceptive-tactile targets.