Flexibility of foveal attention during ocular pursuit

Micropursuit and the control of attention and eye movements in dynamic environments

It is more challenging to plan eye movements during perceptual tasks performed in dynamic displays than in static displays. Decisions about the timing of saccades become more critical, and decisions must also involve smooth eye movements, as well as saccades. The present study examined eye movements when judging which of two moving discs would arrive first, or collide, at a common meeting point. Perceptual discrimination after training was precise (Weber fractions < 6%). Strategies reflected a combined contribution of saccades and smooth eye movements. The preferred strategy was to look near the meeting point when strategies were freely chosen. When strategies were assigned, looking near the meeting point produced better performance than switching between the discs. Smooth eye movements were engaged in two ways: (a) low-velocity smooth eye movements correlated with the motion of each disc (micropursuit) were found while the line of sight remained between the discs; and (b) spontaneous smooth pursuit of the pair of discs occurred after the perceptual report, when the discs moved as a pair along a common path. The results show clear preferences and advantages for those eye movement strategies during dynamic perceptual tasks that require minimal management or effort. In addition, smooth eye movements, whose involvement during perceptual tasks within dynamic displays may have previously escaped notice, provide useful indictors of the strategies used to select information and distribute attention during the performance of dynamic perceptual tasks.

Visual selective attention and the control of tracking eye movements: a critical review

People’s eyes are directed at objects of interest with the aim of acquiring visual information. However, processing this information is constrained in capacity, requiring task-driven and salience-driven attentional mechanisms to select few among the many available objects. A wealth of behavioral and neurophysiological evidence has demonstrated that visual selection and the motor selection of saccade targets rely on shared mechanisms. This coupling supports the premotor theory of visual attention put forth more than 30 years ago, postulating visual selection as a necessary stage in motor selection. In this review, we examine to which extent the coupling of visual and motor selection observed with saccades is replicated during ocular tracking. Ocular tracking combines catch-up saccades and smooth pursuit to foveate a moving object. We find evidence that ocular tracking requires visual selection of the speed and direction of the moving target, but the position of the motion signal may not coincide with the position of the pursuit target. Further, visual and motor selection can be spatially decoupled when pursuit is initiated (open-loop pursuit). We propose that a main function of coupled visual and motor selection is to serve the coordination of catch-up saccades and pursuit eye movements. A simple race-to-threshold model is proposed to explain the variable coupling of visual selection during pursuit, catch-up and regular saccades, while generating testable predictions. We discuss pending issues, such as disentangling visual selection from preattentive visual processing and response selection, and the pinpointing of visual selection mechanisms, which have begun to be addressed in the neurophysiological literature.

In pursuit of visual attention: SSVEP frequency-tagging moving targets

Previous research has shown that visual attention does not always exactly follow gaze direction, leading to the concepts of overt and covert attention. However, it is not yet clear how such covert shifts of visual attention to peripheral regions impact the processing of the targets we directly foveate as they move in our visual field. The current study utilised the co-registration of eye-position and EEG recordings while participants tracked moving targets that were embedded with a 30 Hz frequency tag in a Steady State Visually Evoked Potentials (SSVEP) paradigm. When the task required attention to be divided between the moving target (overt attention) and a peripheral region where a second target might appear (covert attention), the SSVEPs elicited by the tracked target at the 30 Hz frequency band were significantly, but transiently, lower than when participants did not have to covertly monitor for a second target. Our findings suggest that neural responses of overt attention are only briefly reduced when attention is divided between covert and overt areas. This neural evidence is in line with theoretical accounts describing attention as a pool of finite resources, such as the perceptual load theory. Altogether, these results have practical implications for many real-world situations where covert shifts of attention may discretely reduce visual processing of objects even when they are directly being tracked with the eyes.

Eye movement control during visual pursuit in Parkinson's disease

BACKGROUND

Prior studies of oculomotor function in Parkinson's disease (PD) have either focused on saccades without considering smooth pursuit, or tested smooth pursuit while excluding saccades. The present study investigated the control of saccadic eye movements during pursuit tasksand assessed the quality of binocular coordinationas potential sensitive markers of PD.

METHODS

Observers fixated on a central cross while a target moved toward it. Once the target reached the fixation cross, observers began to pursue the moving target. To further investigate binocular coordination, the moving target was presented on both eyes (binocular condition), or on one eye only (dichoptic condition).

RESULTS

The PD group made more saccades than age-matched normal control adults (NC) both during fixation and pursuit. The difference between left and right gaze positions increased over time during the pursuit period for PD but not for NC. The findings were not related to age, as NC and young-adult control group (YC) performed similarly on most of the eye movement measures, and were not correlated with classical measures of PD severity (e.g., Unified Parkinson's Disease Rating Scale (UPDRS) score).

DISCUSSION

Our results suggest that PD may be associated with impairment not only in saccade inhibition, but also in binocular coordination during pursuit, and these aspects of dysfunction may be useful in PD diagnosis or tracking of disease course.

Interference between smooth pursuit and color working memory

Spatial working memory (WM) and spatial attention are closely related, but the relationship between non-spatial WM and spatial attention still remains unclear. The present study aimed to investigate the interaction between color WM and smooth pursuit eye movements. A modified delayed-match-to-sample paradigm (DMS) was applied with 2 or 4 items presented in each visual field. Subjects memorized the colors of items in the cued visual field and smoothly moved eyes towards or away from memorized items during retention interval despite that the colored items were no longer visible. The WM performance decreased with higher load in general. More importantly, the WM performance was better when subjects pursued towards rather than away from the cued visual field. Meanwhile, the pursuit gain decreased with higher load and demonstrated a higher result when pursuing away from the cued visual field. These results indicated that spatial attention, guiding attention to the memorized items, benefits color WM. Therefore, we propose that a competition for attention resources exists between color WM and smooth pursuit eye movements.

A foveal target increases catch-up saccade frequency during smooth pursuit

Images that move rapidly across the retina of the human eye blur because the retina has sluggish temporal dynamics. Voluntary smooth pursuit eye movements are modeled as matching object velocity to minimize retinal motion and prevent retinal blurring. However, "catch-up" saccades that are ubiquitous during pursuit interrupt it and disrupt clear vision. But catch-up saccades may not be a common feature of ocular pursuit, because their existence has been documented with a small moving spot, the classic pursuit stimulus, which is a weak motion stimulus that may poorly emulate larger pursuit objects. We found that spot pursuit does not generalize to that of larger objects. Observers pursued a spot or a larger virtual object with or without a superimposed spot target. Single-spot targets produced lower pursuit acceleration than larger objects. Critically, more saccadic intrusions occurred when stimuli had a central dot, even when position and velocity errors were equated, suggesting that catch-up saccades result from pursuing a single, small object or a feature on a large one. To determine what differentiates a large object from a small one, we progressively shrank the featureless virtual object and found that catch-up saccade frequency was highest when it fit in the fovea. The results suggest that pursuit of a small target or an object feature recruits a saccade mechanism that does not compensate for a weak motion signal; rather, the target compels foveation. Furthermore, catch-up saccades are likely generated by neural circuitry typically used to foveate small objects or features.

Covert enaction at work: Recording the continuous movements of visuospatial attention to visible or imagined targets by means of Steady-State Visual Evoked Potentials (SSVEPs)

Whereas overt visuospatial attention is customarily measured with eye tracking, covert attention is assessed by various methods. Here we exploited Steady-State Visual Evoked Potentials (SSVEPs) - the oscillatory responses of the visual cortex to incoming flickering stimuli - to record the movements of covert visuospatial attention in a way operatively similar to eye tracking (attention tracking), which allowed us to compare motion observation and motion extrapolation with and without eye movements. Observers fixated a central dot and covertly tracked a target oscillating horizontally and sinusoidally. In the background, the left and the right halves of the screen flickered at two different frequencies, generating two SSVEPs in occipital regions whose size varied reciprocally as observers attended to the moving target. The two signals were combined into a single quantity that was modulated at the target frequency in a quasi-sinusoidal way, often clearly visible in single trials. The modulation continued almost unchanged when the target was switched off and observers mentally extrapolated its motion in imagery, and also when observers pointed their finger at the moving target during covert tracking, or imagined doing so. The amplitude of modulation during covert tracking was ∼25-30% of that measured when observers followed the target with their eyes. We used 4 electrodes in parieto-occipital areas, but similar results were achieved with a single electrode in Oz. In a second experiment we tested ramp and step motion. During overt tracking, SSVEPs were remarkably accurate, showing both saccadic-like and smooth pursuit-like modulations of cortical responsiveness, although during covert tracking the modulation deteriorated. Covert tracking was better with sinusoidal motion than ramp motion, and better with moving targets than stationary ones. The clear modulation of cortical responsiveness recorded during both overt and covert tracking, identical for motion observation and motion extrapolation, suggests to include covert attention movements in enactive theories of mental imagery.

Allocation of attention during pursuit of large objects is no different than during fixation

Attention allocation during pursuit of a spot is usually characterized as asymmetric with more attention placed ahead of the target than behind it. However, attention is symmetrically allocated across larger pursuit stimuli. An unresolved issue is how tightly attention is constrained on large stimuli during pursuit. Although some work shows it is tightly locked to the fovea, other work shows it is allocated flexibly. To investigate this, we had observers perform a character identification task on large pursuit stimuli composed of arrays of five, nine, or 15 characters spaced between 0.6° and 4.0° apart. Initially, the characters were identical, but at a random time, they all changed briefly, rendering one of them unique. Observers identified the unique character. Consistent with previous literature, attention appeared narrow and symmetric around the pursuit target for tightly spaced (0.6°) characters. Increasing spacing dramatically expanded the attention scope, presumably by mitigating crowding. However, when we controlled for crowding, performance was limited by set size, suffering more for eccentric targets. Interestingly, the same limitations on attention allocation were observed with stationary and pursued stimuli-evidence that attention operates similarly during fixation and pursuit of a stimulus that extends into the periphery. The results suggest that attention is flexibly allocated during pursuit, but performance is limited by crowding and set size. In addition, performing the identification task did not hurt pursuit performance, further evidence that pursuit of large stimuli is relatively inattentive.

Pursuit tracks chase: exploring the role of eye movements in the detection of chasing

We explore the role of eye movements in a chase detection task. Unlike the previous studies, which focused on overall performance as indicated by response speed and chase detection accuracy, we decompose the search process into gaze events such as smooth eye movements and use a data-driven approach to separately describe these gaze events. We measured eye movements of four human subjects engaged in a chase detection task displayed on a computer screen. The subjects were asked to detect two chasing rings among twelve other randomly moving rings. Using principal component analysis and support vector machines, we looked at the template and classification images that describe various stages of the detection process. We showed that the subjects mostly search for pairs of rings that move one after another in the same direction with a distance of 3.5-3.8 degrees. To find such pairs, the subjects first looked for regions with a high ring density and then pursued the rings in this region. Most of these groups consisted of two rings. Three subjects preferred to pursue the pair as a single object, while the remaining subject pursued the group by alternating the gaze between the two individual rings. In the discussion, we argue that subjects do not compare the movement of the pursued pair to a singular preformed template that describes a chasing motion. Rather, subjects bring certain hypotheses about what motion may qualify as chase and then, through feedback, they learn to look for a motion pattern that maximizes their performance.

Motion integration for ocular pursuit does not hinder perceptual segregation of moving objects

When confronted with a complex moving stimulus, the brain can integrate local element velocities to obtain a single motion signal, or segregate the elements to maintain awareness of their identities. The integrated motion signal can drive smooth-pursuit eye movements (Heinen and Watamaniuk, 1998), whereas the segregated signal guides attentive tracking of individual elements in multiple-object tracking tasks (MOT; Pylyshyn and Storm, 1988). It is evident that these processes can occur simultaneously, because we can effortlessly pursue ambulating creatures while inspecting disjoint moving features, such as arms and legs, but the underlying mechanism is unknown. Here, we provide evidence that separate neural circuits perform the mathematically opposed operations of integration and segregation, by demonstrating with a dual-task paradigm that the two processes do not share attentional resources. Human observers attentively tracked a subset of target elements composing a small MOT stimulus, while pursuing it ocularly as it translated across a computer display. Integration of the multidot stimulus yielded optimal pursuit. Importantly, performing MOT while pursuing the stimulus did not degrade performance on either task compared with when each was performed alone, indicating that they did not share attention. A control experiment showed that pursuit was not driven by integration of only the nontargets, leaving the MOT targets free for segregation. Nor was a predictive strategy used to pursue the stimulus, because sudden changes in its global velocity were accurately followed. The results suggest that separate neural mechanisms can simultaneously segregate and integrate the same motion signals.

A P300-based brain-computer interface with stimuli on moving objects: four-session single-trial and triple-trial tests with a game-like task design

Brain-computer interfaces (BCIs) are tools for controlling computers and other devices without using muscular activity, employing user-controlled variations in signals recorded from the user's brain. One of the most efficient noninvasive BCIs is based on the P300 wave of the brain's response to stimuli and is therefore referred to as the P300 BCI. Many modifications of this BCI have been proposed to further improve the BCI's characteristics or to better adapt the BCI to various applications. However, in the original P300 BCI and in all of its modifications, the spatial positions of stimuli were fixed relative to each other, which can impose constraints on designing applications controlled by this BCI. We designed and tested a P300 BCI with stimuli presented on objects that were freely moving on a screen at a speed of 5.4°/s. Healthy participants practiced a game-like task with this BCI in either single-trial or triple-trial mode within four sessions. At each step, the participants were required to select one of nine moving objects. The mean online accuracy of BCI-based selection was 81% in the triple-trial mode and 65% in the single-trial mode. A relatively high P300 amplitude was observed in response to targets in most participants. Self-rated interest in the task was high and stable over the four sessions (the medians in the 1st/4th sessions were 79/84% and 76/71% in the groups practicing in the single-trial and triple-trial modes, respectively). We conclude that the movement of stimulus positions relative to each other may not prevent the efficient use of the P300 BCI by people controlling their gaze, e.g., in robotic devices and in video games.

Saccade reaction time asymmetries during task-switching in pursuit tracking

We investigate how smooth pursuit eye movements affect the latencies of task-switching saccades. Participants had to alternate their foveal vision between a continuous pursuit task in the display center and a discrete object discrimination task in the periphery. The pursuit task was either carried out by following the target with the eyes only (ocular) or by steering an on-screen cursor with a joystick (oculomanual). We measured participants' saccadic reaction times (SRTs) when foveal vision was shifted from the pursuit task to the discrimination task and back to the pursuit task. Our results show asymmetries in SRTs depending on the movement direction of the pursuit target: SRTs were generally shorter in the direction of pursuit. Specifically, SRTs from the pursuit target were shorter when the discrimination object appeared in the motion direction. SRTs to pursuit were shorter when the pursuit target moved away from the current fixation location. This result was independent of the type of smooth pursuit behavior that was performed by participants (ocular/oculomanual). The effects are discussed in regard to asymmetries in attention and processes that suppress saccades at the onset of pursuit.

Shared attention for smooth pursuit and saccades

Identification of brief luminance decrements on parafoveal stimuli presented during smooth pursuit improves when a spot pursuit target is surrounded by a larger random dot cinematogram (RDC) that moves with it (Heinen, Jin, & Watamaniuk, 2011). This was hypothesized to occur because the RDC provided an alternative, less attention-demanding pursuit drive, and therefore released attentional resources for visual perception tasks that are shared with those used to pursue the spot. Here, we used the RDC as a tool to probe whether spot pursuit also shares attentional resources with the saccadic system. To this end, we set out to determine if the RDC could release attention from pursuit of the spot to perform a saccade task. Observers made a saccade to one of four parafoveal targets that moved with the spot pursuit stimulus. The targets either moved alone or were surrounded by an RDC (100% coherence). Saccade latency decreased with the RDC, suggesting that the RDC released attention needed to pursue the spot, which was then used for the saccade task. Additional evidence that attention was released by the RDC was obtained in an experiment in which attention was anchored to the fovea by requiring observers to detect a brief color change applied 130 ms before the saccade target appeared. This manipulation eliminated the RDC advantage. The results imply that attentional resources used by the pursuit and saccadic eye movement control systems are shared.

Keep your eyes on the ball: smooth pursuit eye movements enhance prediction of visual motion

Success of motor behavior often depends on the ability to predict the path of moving objects. Here we asked whether tracking a visual object with smooth pursuit eye movements helps to predict its motion direction. We developed a paradigm, “eye soccer,” in which observers had to either track or fixate a visual target (ball) and judge whether it would have hit or missed a stationary vertical line segment (goal). Ball and goal were presented briefly for 100–500 ms and disappeared from the screen together before the perceptual judgment was prompted. In pursuit conditions, the ball moved towards the goal; in fixation conditions, the goal moved towards the stationary ball, resulting in similar retinal stimulation during pursuit and fixation. We also tested the condition in which the goal was fixated and the ball moved. Motion direction prediction was significantly better in pursuit than in fixation trials, regardless of whether ball or goal served as fixation target. In both fixation and pursuit trials, prediction performance was better when eye movements were accurate. Performance also increased with shorter ball-goal distance and longer presentation duration. A longer trajectory did not affect performance. During pursuit, an efference copy signal might provide additional motion information, leading to the advantage in motion prediction.