Cognitive processes involved in smooth pursuit eye movements

Ocular pursuit movements allow moving objects to be tracked with a combination of smooth movements and saccades. The principal objective is to maintain smooth eye velocity close to object velocity, thus minimising retinal image motion and maintaining acuity. Saccadic movements serve to realign the image if it falls outside the fovea, the area of highest acuity. Pursuit movements are often portrayed as voluntary but their basis lies in processes that sense retinal motion and can induce eye movements without active participation. The factor distinguishing pursuit from such reflexive movements is the ability to select and track a single object when presented with multiple stimuli. The selective process requires attention, which appears to raise the gain for the selected object and/or suppress that associated with other stimuli, the resulting competition often reducing pursuit velocity. Although pursuit is essentially a feedback process, delays in motion processing create problems of stability and speed of response. This is countered by predictive processes, probably operating through internal efference copy (extra-retinal) mechanisms using short-term memory to store velocity and timing information from prior stimulation. In response to constant velocity motion, the initial response is visually driven, but extra-retinal mechanisms rapidly take over and sustain pursuit. The same extra-retinal mechanisms may also be responsible for generating anticipatory smooth pursuit movements when past experience creates expectancy of impending object motion. Similar, but more complex, processes appear to operate during periodic pursuit, where partial trajectory information is stored and released in anticipation of expected future motion, thus minimising phase errors associated with motion processing delays.     

Cognitive processes involved in smooth pursuit eye movements

Ocular pursuit movements allow moving objects to be tracked with a combination of smooth movements and saccades. The principal objective is to maintain smooth eye velocity close to object velocity, thus minimising retinal image motion and maintaining acuity. Saccadic movements serve to realign the image if it falls outside the fovea, the area of highest acuity. Pursuit movements are often portrayed as voluntary but their basis lies in processes that sense retinal motion and can induce eye movements without active participation. The factor distinguishing pursuit from such reflexive movements is the ability to select and track a single object when presented with multiple stimuli. The selective process requires attention, which appears to raise the gain for the selected object and/or suppress that associated with other stimuli, the resulting competition often reducing pursuit velocity. Although pursuit is essentially a feedback process, delays in motion processing create problems of stability and speed of response. This is countered by predictive processes, probably operating through internal efference copy (extra-retinal) mechanisms using short-term memory to store velocity and timing information from prior stimulation. In response to constant velocity motion, the initial response is visually driven, but extra-retinal mechanisms rapidly take over and sustain pursuit. The same extra-retinal mechanisms may also be responsible for generating anticipatory smooth pursuit movements when past experience creates expectancy of impending object motion. Similar, but more complex, processes appear to operate during periodic pursuit, where partial trajectory information is stored and released in anticipation of expected future motion, thus minimising phase errors associated with motion processing delays.     

The neural basis of smooth pursuit eye movements in the rhesus monkey brain

Smooth pursuit eye movements are performed in order to prevent retinal image blur of a moving object. Rhesus monkeys are able to perform smooth pursuit eye movements quite similar as humans, even if the pursuit target does not consist in a simple moving dot. Therefore, the study of the neuronal responses as well as the consequences of micro-stimulation and lesions in trained monkeys performing smooth pursuit is a powerful approach to understand the human pursuit system. The processing of visual motion is achieved in the primary visual cortex and the middle temporal area. Further processing including the combination of retinal image motion signals with extra-retinal signals such as the ongoing eye and head movement occurs in subsequent cortical areas as the medial superior temporal area, the ventral intraparietal area and the frontal and supplementary eye field. The frontal eye field especially contributes anticipatory signals which have a substantial influence on the execution of smooth pursuit. All these cortical areas send information to the pontine nuclei, which in turn provide the input to the cerebellum. The cerebellum contains two pursuit representations: in the paraflocculus/flocculus region and in the posterior vermis. While the first representation is most likely involved in the coordination of pursuit and the vestibular-ocular reflex, the latter is involved in the precise adjustments of the eye movements such as adaptation of pursuit initiation. The output of the cerebellum is directed to the moto-neurons of the extra-ocular muscles in the brainstem.     

Keeping balance during head-free smooth pursuit: The role of aging

Standing balance is often more unstable when visually pursuing a moving target than when fixating on a stationary one. These effects are common in both young and older adults when the head is restrained during visual task performance. The present study focused on the role of head motion on standing balance during smooth pursuit as a function of age. Three predictions were tested: a) standing balance is compromised to a greater extent in older than young adults by gaze target pursuit compared to fixation, b) older adults pursue a moving target with greater and more variable head rotation than young adults, and c) greater and more variable head rotation during the smooth pursuit task is associated with greater Center of Pressure (CoP) sway. Twenty-two (22) older (age: 71.7 ± 8.1, 12 M / 10 F) and twenty-three (23) young adults (age: 23.6 ± 2.5, 12 M / 11 F) stood on a force plate while either fixating a stationary or smoothly pursuing a horizontally moving target (31.9° peak-to-peak visual angle). CoP (Bertec Balance Plate), head kinematics (Vicon Motion Analysis) and head-unconstrained gaze (Pupil Labs Invisible) were synchronously recorded. The root means square (RMS) of CoP velocity increased during smooth pursuit compared to fixation regardless of age (p < .05), while the interquartile CoP range increased only in older and not in young participants (p < .05). We also calculated the head rotation range (peak to peak cycle amplitude) of motion and variability (SD of range of motion) across the cycles of the smooth pursuit task. Older adults pursued the moving target employing more variable (p = .022) head yaw rotation than young participants although the mean range of head rotation was similar between groups (p =. 077). The amplitude and variability of head yaw rotation did not correlate with CoP sway measures. Results suggest that head-free pursuing of a moving target decreased balance to a greater extent in old than young individuals when compared to fixation. Nevertheless, postural sway during head-free smooth pursuit was not associated with the extent or variability of head rotation.     

A revised analysis of the role of efference in motion perception

The analysis of motion perception historically has included efferent as well as afferent mechanisms to account for the perception of motion during eye movement. The application of efferent mechanisms to motion perception has been limited, however, by several illusions which are apparently inconsistent with the notion that oculomotor mechanisms contribute to motion perception. An alternative account is presented of the manner in which efference may contribute to the perception of motion. It is proposed that distinct smooth eye-movement systems contribute differentially to object motion perception. Specifically, activity in the smooth pursuit system gives rise to the perception of object motion, whereas activity in the smooth component of reflexive eye movements does not. Tracking of a moving object results in object motion perception as a result of efference in the pursuit system. However, the pursuit system may be activated to oppose the smooth component of reflexive eye movements in order to preserve fixation on a stationary object. In such cases neither the fixated object nor the eye is moving but illusory movement results from the efference in the pursuit system. A number of illusory movement phenomena are interpreted in terms of this model.     

Kinematic property of target motion conditions gaze behavior and eye-hand synergy during manual tracking

This study investigated how frequency demand and motion feedback influenced composite ocular movements and eye-hand synergy during manual tracking. Fourteen volunteers conducted slow and fast force-tracking in which targets were displayed in either line-mode or wave-mode to guide manual tracking with target movement of direct position or velocity nature. The results showed that eye-hand synergy was a selective response of spatiotemporal coupling conditional on target rate and feedback mode. Slow and line-mode tracking exhibited stronger eye-hand coupling than fast and wave-mode tracking. Both eye movement and manual action led the target signal during fast-tracking, while the latency of ocular navigation during slow-tracking depended on the feedback mode. Slow-tracking resulted in more saccadic responses and larger pursuit gains than fast-tracking. Line-mode tracking led to larger pursuit gains but fewer and shorter gaze fixations than wave-mode tracking. During slow-tracking, incidences of saccade and gaze fixation fluctuated across a target cycle, peaking at velocity maximum and the maximal curvature of target displacement, respectively. For line-mode tracking, the incidence of smooth pursuit was phase-dependent, peaking at velocity maximum as well. Manual behavior of slow or line-mode tracking was better predicted by composite eye movements than that of fast or wave-mode tracking. In conclusion, manual tracking relied on versatile visual strategies to perceive target movements of different kinematic properties, which suggested a flexible coordinative control for the ocular and manual sensorimotor systems.     

Neurophysiology and neuroanatomy of smooth pursuit in humans

Smooth pursuit eye movements enable us to focus our eyes on moving objects by utilizing well-established mechanisms of visual motion processing, sensorimotor transformation and cognition. Novel smooth pursuit tasks and quantitative measurement techniques can help unravel the different smooth pursuit components and complex neural systems involved in its control. The maintenance of smooth pursuit is driven by a combination of the prediction of target velocity and visual feedback about performance quality, thus a combination of retinal and extraretinal information that has to be integrated in various networks. Different models of smooth pursuit with specific in- and output parameters have been developed for a better understanding of the underlying neurophysiological mechanisms and to make quantitative predictions that can be tested in experiments. Functional brain imaging and neurophysiological studies have defined motion sensitive visual area V5, frontal (FEF) and supplementary (SEF) eye fields as core cortical smooth pursuit regions. In addition, a dense neural network is involved in the adjustment of an optimal smooth pursuit response by integrating also extraretinal information. These networks facilitate interaction of the smooth pursuit system with multiple other visual and non-visual sensorimotor systems on the cortical and subcortical level. Future studies with fMRI advanced techniques (e.g., event-related fMRI) promise to provide an insight into how smooth pursuit eye movements are linked to specific brain activation. Applying this approach to neurological and also mental illness can reveal distinct disturbances within neural networks being present in these disorders and also the impact of medication on this circuitry.     

Neurophysiology and neuroanatomy of smooth pursuit in humans

Smooth pursuit eye movements enable us to focus our eyes on moving objects by utilizing well-established mechanisms of visual motion processing, sensorimotor transformation and cognition. Novel smooth pursuit tasks and quantitative measurement techniques can help unravel the different smooth pursuit components and complex neural systems involved in its control. The maintenance of smooth pursuit is driven by a combination of the prediction of target velocity and visual feedback about performance quality, thus a combination of retinal and extraretinal information that has to be integrated in various networks. Different models of smooth pursuit with specific in- and output parameters have been developed for a better understanding of the underlying neurophysiological mechanisms and to make quantitative predictions that can be tested in experiments. Functional brain imaging and neurophysiological studies have defined motion sensitive visual area V5, frontal (FEF) and supplementary (SEF) eye fields as core cortical smooth pursuit regions. In addition, a dense neural network is involved in the adjustment of an optimal smooth pursuit response by integrating also extraretinal information. These networks facilitate interaction of the smooth pursuit system with multiple other visual and non-visual sensorimotor systems on the cortical and subcortical level. Future studies with fMRI advanced techniques (e.g., event-related fMRI) promise to provide an insight into how smooth pursuit eye movements are linked to specific brain activation. Applying this approach to neurological and also mental illness can reveal distinct disturbances within neural networks being present in these disorders and also the impact of medication on this circuitry.     

Human gaze behaviour during action execution and observation

Gaze shifts and fixations appear to be proactive in both action execution and observation. We investigated a dependency of anticipatory gaze behaviour by using a block stacking task. Blocks were rectangles depicted on a computer screen and the stacking movements were controlled via computer mouse. Subjects either had to execute the task or had to observe it made by the experimenter, or by the computer. The dependency of gaze behaviour on the visibility of a virtual effector, the visibility of the actor, and the nature of the actor was tested by measuring eye movements. Anticipatory eye movements were predominant when the subjects themselves executed the task. During action observation, gaze behaviour did neither depend on the visibility nor depend on the nature of the actor. However, big variability was found between the subjects suggesting the use of two different strategies in action observation: some subjects were mainly tracking the blocks during stacking movements; others were strongly anticipating. We suggest that gaze behaviour during action observation is not predetermined by rigid neural circuitry, but strongly depends on the context. The possibility to explain the causal mechanism, as well as the ownership of the action may be crucial preconditions for anticipatory gaze behaviour.     

What attracts attention during police pursuit driving?

Efficient deployment of attention is important to the safe execution of tasks with a high content of visual information, such as driving. Chasing a lead vehicle is an extremely demanding and dangerous task, though little is known of the visual skills required. A study is reported that recorded the eye movements of police drivers and two control groups (novices and age‐ and experienced‐ matched controls) while watching a series of video clips of driving. The clips included pursuits, emergency response drives, and control drives (at normal speeds) around Nottinghamshire, UK. Analysis of gaze durations within certain categories of stimuli revealed that daytime pursuit drives correspond with an increase in gaze durations on a lead car (controlled for exposure), though police drivers direct their attention to other sources of potential hazards, such as pedestrians, more so than other drivers. Copyright © 2005 John Wiley & Sons, Ltd.     

Gaze following: why (not) learn it?

We propose a computational model of the emergence of gaze following skills in infant-caregiver interactions. The model is based on the idea that infants learn that monitoring their caregiver's direction of gaze allows them to predict the locations of interesting objects or events in their environment (Moore & Corkum, 1994). Elaborating on this theory, we demonstrate that a specific Basic Set of structures and mechanisms is sufficient for gaze following to emerge. This Basic Set includes the infant's perceptual skills and preferences, habituation and reward-driven learning, and a structured social environment featuring a caregiver who tends to look at things the infant will find interesting. We review evidence that all elements of the Basic Set are established well before the relevant gaze following skills emerge. We evaluate the model in a series of simulations and show that it can account for typical development. We also demonstrate that plausible alterations of model parameters, motivated by findings on two different developmental disorders - autism and Williams syndrome - produce delays or deficits in the emergence of gaze following. The model makes a number of testable predictions. In addition, it opens a new perspective for theorizing about cross-species differences in gaze following.     

视觉运动追踪的加工过程

视觉运动追踪是运动知觉研究的一个重要领域。通过构建视觉运动追踪的过程模型和分析每个阶段的认知加工任务, 可以帮助人们认识运动物体识别的本质。视觉运动追踪包括目标获取和运动追踪两个加工过程：目标获取阶段的主要任务是将目标与背景分离, 集中注意力加工追踪目标; 运动追踪阶段的主要任务是启动平滑追踪眼动和追赶性眼跳, 并发挥行为水平、眼动水平和神经活动水平的预测机制。目标获取同时受背景和目标的运动特征和身份特征影响; 运动追踪系统发挥预测机制的基础是客体表征连续性, 而客体表征连续性的建立同时依赖于目标时空属性和身份特征的编码加工。因此, 视觉运动追踪是视觉系统对客体运动信息和身份语义信息整合的结果。其中, 客体运动信息的加工特性已经获得了比较广泛的研究, 而语义信息加工机制还有待进一步加强。     

The Incomplete Tyranny of Dynamic Stimuli: Gaze Similarity Predicts Response Similarity in Screen-Captured Instructional Videos

Although eye tracking has been used extensively to assess cognitions for static stimuli, recent research suggests that the link between gaze and cognition may be more tenuous for dynamic stimuli such as videos. Part of the difficulty in convincingly linking gaze with cognition is that in dynamic stimuli, gaze position is strongly influenced by exogenous cues such as object motion. However, tests of the gaze-cognition link in dynamic stimuli have been done on only a limited range of stimuli often characterized by highly organized motion. Also, analyses of cognitive contrasts between participants have been mostly been limited to categorical contrasts among small numbers of participants that may have limited the power to observe more subtle influences. We, therefore, tested for cognitive influences on gaze for screen-captured instructional videos, the contents of which participants were tested on. Between-participant scanpath similarity predicted between-participant similarity in responses on test questions, but with imperfect consistency across videos. We also observed that basic gaze parameters and measures of attention to centers of interest only inconsistently predicted learning, and that correlations between gaze and centers of interest defined by other-participant gaze and cursor movement did not predict learning. It, therefore, appears that the search for eye movement indices of cognition during dynamic naturalistic stimuli may be fruitful, but we also agree that the tyranny of dynamic stimuli is real, and that links between eye movements and cognition are highly dependent on task and stimulus properties.     

The mindful eye: Smooth pursuit and saccadic eye movements in meditators and non-meditators

BackgroundThis study examined the effects of cultivated (i.e. developed through training) and dispositional (trait) mindfulness on smooth pursuit (SPEM) and antisaccade (AS) tasks known to engage the fronto-parietal network implicated in attentional and motion detection processes, and the fronto-striatal network implicated in cognitive control, respectively.MethodsSixty healthy men (19–59 years), of whom 30 were experienced mindfulness practitioners and 30 meditation-naïve, underwent infrared oculographic assessment of SPEM and AS performance. Trait mindfulness was assessed using the self-report Five Facet Mindfulness Questionnaire (FFMQ).ResultsMeditators, relative to meditation-naïve individuals, made significantly fewer catch-up and anticipatory saccades during the SPEM task, and had significantly lower intra-individual variability in gain and spatial error during the AS task. No SPEM or AS measure correlated significantly with FFMQ scores in meditation-naïve individuals.ConclusionsCultivated, but not dispositional, mindfulness is associated with improved attention and sensorimotor control as indexed by SPEM and AS tasks.     

Visual motion integration for perception and pursuit

To examine the relationship between visual motion processing for perception and pursuit, we measured the pursuit eye-movement and perceptual responses to the same complex-motion stimuli. We show that humans can both perceive and pursue the motion of line-figure objects, even when partial occlusion makes the resulting image motion vastly different from the underlying object motion. Our results show that both perception and pursuit can perform largely accurate motion integration, i.e. the selective combination of local motion signals across the visual field to derive global object motion. Furthermore, because we manipulated perceived motion while keeping image motion identical, the observed parallel changes in perception and pursuit show that the motion signals driving steady-state pursuit and perception are linked. These findings disprove current pursuit models whose control strategy is to minimize retinal image motion, and suggest a new framework for the interplay between visual cortex and cerebellum in visuomotor control.     

Eighteen-month-olds’ ability to make gaze predictions following distraction or a long delay

The abilities to flexibly allocate attention, select between conflicting stimuli, and make anticipatory gaze movements are important for young children's exploration and learning about their environment. These abilities constitute voluntary control of attention and show marked improvements in the second year of a child's life. Here we investigate the effects of visual distraction and delay on 18-month-olds’ ability to predict the location of an occluded target in an experiment that requires switching of attention, and compare their performance to that of adults. Our results demonstrate that by 18 months of age children can readily overcome a previously learned response, even under a condition that involves visual distraction, but have difficulties with correctly updating their prediction when presented with a longer time delay. Further, the experiment shows that, overall, the 18-month-olds’ allocation of visual attention is similar to that of adults, the primary difference being that adults demonstrate a superior ability to maintain attention on task and update their predictions over a longer time period.     

“Proactive” in many ways: Developmental evidence for a dynamic pluralistic approach to prediction

The anticipation of the forthcoming behaviour of social interaction partners is a useful ability supporting interaction and communication between social partners. Associations and prediction based on the production system (in line with views that listeners use the production system covertly to anticipate what the other person might be likely to say) are two potential factors, which have been proposed to be involved in anticipatory language processing. We examined the influence of both factors on the degree to which listeners predict upcoming linguistic input. Are listeners more likely to predict book as an appropriate continuation of the sentence “The boy reads a”, based on the strength of the association between the words read and book (strong association) and read and letter (weak association)? Do more proficient producers predict more? What is the interplay of these two influences on prediction? The results suggest that associations influence language-mediated anticipatory eye gaze in two-year-olds and adults only when two thematically appropriate target objects compete for overt attention but not when these objects are presented separately. Furthermore, children's prediction abilities are strongly related to their language production skills when appropriate target objects are presented separately but not when presented together. Both influences on prediction in language processing thus appear to be context dependent. We conclude that multiple factors simultaneously influence listeners’ anticipation of upcoming linguistic input and that only such a dynamic approach to prediction can capture listeners’ prowess at predictive language processing.     

Dynamic visuomotor synchronization: Quantification of predictive timing

When a moving target is tracked visually, spatial and temporal predictions are used to circumvent the neural delay required for the visuomotor processing. In particular, the internally generated predictions must be synchronized with the external stimulus during continuous tracking. We examined the utility of a circular visual-tracking paradigm for assessment of predictive timing, using normal human subjects. Disruptions of gaze–target synchronization were associated with anticipatory saccades that caused the gaze to be temporarily ahead of the target along the circular trajectory. These anticipatory saccades indicated preserved spatial prediction but suggested impaired predictive timing. We quantified gaze–target synchronization with several indices, whose distributions across subjects were such that instances of extremely poor performance were identifiable outside the margin of error determined by test–retest measures. Because predictive timing is an important element of attention functioning, the visual-tracking paradigm and dynamic synchronization indices described here may be useful for attention assessment.     

Resolving ambiguous behavioral intentions by means of involuntary prioritization of gaze processing

Anticipation of others' actions is of paramount importance in social interactions. Cues such as gaze direction and facial expressions can be informative, but can also produce ambiguity with respect to others' intentions. We investigated the combined effect of an actor's gaze and expression on judgments made by observers about the end-point of the actor's head rotation toward the observer. Expressions of approach gave rise to an unambiguous intention to move toward the observer, while expressions of avoidance gave rise to an ambiguous behavioral intention (as the expression and motion cues were in conflict). In the ambiguous condition, observers overestimated how far the actor's head had rotated when the actor's gaze was directed ahead of head rotation (compared to congruent or lagging behind). In the unambiguous condition the estimations were not influenced by the gaze manipulation. These results show that social cue integration does not follow simple additive rules, and suggests that the involuntary allocation of attention to another's gaze depends on the perceived ambiguity of the agent's behavioral intentions.     

Visually guided capture of a moving stimulus by the pigeon (Columba livia)

Although the pigeon is a popular model for studying visual perception, relatively little is known about its perception of motion. Three experiments examined the pigeons’ ability to capture a moving stimulus. In Experiment 1, the effect of manipulating stimulus speed and the length of the stimulus was examined using a simple rightward linear motion. This revealed a clear effect of length on capture and speed on errors. Errors were mostly anticipatory and there appeared to be two processes contributing to response locations: anticipatory peck bias and lag time. Using the same birds as Experiment 1, Experiment 2 assessed transfer of tracking and capture to novel linear motions. The birds were able to capture other motion directions, but they displayed a strong rightward peck bias, indicating that they had learned to peck to the right of the stimulus in Experiment 1. Experiment 3 used the same task as Experiment 2 but with naïve birds. These birds did not show the rightward bias in pecking and instead pecked more evenly around the stimulus. The combined results indicate that the pigeon can engage in anticipatory tracking and capture of a moving stimulus, and that motion properties and training experience influence capture.