Frontal cortical control of smooth-pursuit

To maintain optimal clarity of objects moving slowly in three dimensional space, frontal eyed-primates use both smooth-pursuit and vergence (depth) eye movements to track precisely those objects and maintain their images on the foveae of left and right eyes. The caudal parts of the frontal eye fields contain neurons that discharge during smooth-pursuit. Recent results have provided a new understanding of the roles of the frontal eye field pursuit area and suggest that it may control the gain of pursuit eye movements, code predictive visual signals that drive pursuit, and code commands for smooth eye movements in a three dimensional coordinate frame.     

Tests of a linear model of visual-vestibular interaction using the technique of parameter estimation

The goal of this study was to test whether a superposition model of smooth-pursuit and vestibulo-ocular reflex (VOR) eye movements could account for the stability of gaze that subjects show as they view a stationary target, during head rotations at frequencies that correspond to natural movements. Horizontal smooth-pursuit and the VOR were tested using sinusoidal stimuli with frequencies in the range 1.0–3.5 Hz. During head rotation, subjects viewed a stationary target either directly or through an optical device that required eye movements to be approximately twice the amplitude of head movements in order to maintain foveal vision of the target. The gain of compensatory eye movements during viewing through the optical device was generally greater than during direct viewing or during attempted fixation of the remembered target location in darkness. This suggests that visual factors influence the response, even at high frequencies of head rotation. During viewing through the optical device, the gain of compensatory eye movements declined as a function of the frequency of head rotation (P < 0.001) but, at any particular frequency, there was no correlation with peak head velocity (P > 0.23), peak head acceleration (P > 0.22) or retinal slip speed (P > 0.22). The optimal values of parameters of smooth-pursuit and VOR components of a simple superposition model were estimated in the frequency domain, using the measured responses during head rotation, as each subject viewed the stationary target through the optical device. We then compared the model's prediction of smooth-pursuit gain and phase, at each frequency, with values obtained experimentally. Each subject's pursuit showed lower gain and greater phase lag than the model predicted. Smooth-pursuit performance did not improve significantly if the moving target was a 10 deg × 10 deg Amsler grid, or if sinusoidal oscillation of the target was superimposed on ramp motion. Further, subjects were still able to modulate the gain of compensatory eye movements during pseudo-random head perturbations, making improved predictor performance during visual-vestibular interactions unlikely. We conclude that the increase in gain of eye movements that compensate for head rotations when subjects view, rather than imagine, a stationary target cannot be adequately explained by superposition of VOR and smooth-pursuit signals. Instead, vision may affect VOR performance by determining the context of the behavior. Received: 16 June 1997 / Accepted: 5 December 1997     

Optimizing visual motion perception during eye movements.

We usually perceive a stationary, stable world and we are able to correctly estimate the direction of heading from optic flow despite coherent visual motion induced by eye movements. This astonishing example of perceptual invariance results from a comparison of visual information with internal reference signals predicting the visual consequences of an eye movement. Here we demonstrate that the reference signal predicting the consequences of smooth-pursuit eye movements is continuously calibrated on the basis of direction-selective interactions between the pursuit motor command and the rotational flow induced by the eye movement, thereby minimizing imperfections of the reference signal and guaranteeing an ecologically optimal interpretation of visual motion.     

Anteroposterior dynamic balance reactions induced by circular translation of the visual field

The anteroposterior sway of subjects under conditions of spontaneous dynamic balance on a wobbly platform was measured during visual stimulation by a visual target executing a circular trajectory in the frontal plane. The target was either a component of the whole moving visual scene or moving on a stationary background. With the former stimulation, obtained through the use of rotating prismatic glasses, every point of the visual field appeared to describe a circular trajectory around its real position so that the whole visual field apeared to be circularly translated, undistorted, inducing a binocular pursuit movement. Under these conditions, stereotyped anteroposterior dynamic balance reactions synchronous with the position of the stimulus were elicited. The latter stimulation consisted of pursuing a luminous target describing a trajectory similar to that of the fixation point seen through the rotating prisms on the same, this time stable, visual background. Although pursuit eye movements were comparable, as demonstrated by electro-oculographic recordings, no stereotyped equilibration reaction was induced. It is concluded that the translatory motion of the background image on the retina in the latter experiments contributed to the body's stability as well as to the perception of a stable environment.     

A simple video-based system for examining irregularities in very slow, smooth-pursuit eye movements in cancer patients

Subjective observations made during routine examination of eye movement functions (orthoptic status) reveal that very slow, smooth-pursuit eye movements in cancer patients are irregular. To objectively measure such movements, a video-based system was built to allow analysis of very slow, smooth-pursuit eye movements (1.8 degrees /s). Analysis involves quantification of drift and jerk-like gaze movements that cause deviations in gaze direction from the predicted trajectory. Gaze deviations observed in cancer patients are compared to those for the normal population. Our results show that deviations are more important in cancer patients than in the normal population. The difference is statistically significant (p<0.05) for deviations ranging between 0.75 degrees and 1.75 degrees . In the future, the system may possibly be used in the diagnosis of cancer.     

Saccadic facilitation in natural backgrounds

In visual systems with a fovea, only a small portion of the visual field can be analyzed with high accuracy. Saccadic eye movements shift that center of gaze around several times a second. Saccades have been characterized in great detail and depend critically on a number of visual properties of the stimuli. However, typical experiments have used bright spots on dark backgrounds, while our natural environment has a highly characteristic rich spatial structure. Here we show that the saccadic system, unlike the perceptual system, is able to compensate for the masking caused by structured backgrounds. Consequently, saccadic latencies in the context of natural backgrounds are much faster than unstructured backgrounds at equal levels of visibility. The results suggest that whenever a structured background acts to mask the visibility of the saccade target, it simultaneously preactivates saccadic circuitry and thus ensures a fast reaction to potentially critical stimuli that are difficult to detect in our environment.     

Tuning Properties of MT and MSTd and Divisive Interactions for Eye-Movement Compensation

The primate brain intelligently processes visual information from the world as the eyes move constantly. The brain must take into account visual motion induced by eye movements, so that visual information about the outside world can be recovered. Certain neurons in the dorsal part of monkey medial superior temporal area (MSTd) play an important role in integrating information about eye movements and visual motion. When a monkey tracks a moving target with its eyes, these neurons respond to visual motion as well as to smooth pursuit eye movements. Furthermore, the responses of some MSTd neurons to the motion of objects in the world are very similar during pursuit and during fixation, even though the visual information on the retina is altered by the pursuit eye movement. We call these neurons compensatory pursuit neurons. In this study we develop a computational model of MSTd compensatory pursuit neurons based on physiological data from single unit studies. Our model MSTd neurons can simulate the velocity tuning of monkey MSTd neurons. The model MSTd neurons also show the pursuit compensation property. We find that pursuit compensation can be achieved by divisive interaction between signals coding eye movements and signals coding visual motion. The model generates two implications that can be tested in future experiments: (1) compensatory pursuit neurons in MSTd should have the same direction preference for pursuit and retinal visual motion; (2) there should be non-compensatory pursuit neurons that show opposite preferred directions of pursuit and retinal visual motion.     

A model of the smooth pursuit eye movement system

Human, horizontal, smooth-pursuit eye movements were recorded by the search coil method in response to Rashbass step-ramp stimuli of 5 to 30 deg/s. Eye velocity records were analyzed by measuring features such as the time, velocity and acceleration of the point of peak acceleration, the time and velocity of the peaks and troughs of ringing and steady-state velocity. These values were averaged and mean responses reconstructed. Three normal subjects were studied and their responses averaged. All showed a peak acceleration-velocity saturation. All had ringing frequencies near 3.8 Hz and the mean steady-state gain was 0.95.It is argued that a single, linear forward path with any transfer function G(s) and a 100 ms delay (latency) cannot simultaneously simulate the initial rise of acceleration and ring at 3.8 Hz based on a Bode analysis. Also such a simple negative feedback model cannot have a steady-state gain greater than 1.0; a situation that occurs frequently experimentally. L.R. Young's model, which employs internal positive feedback to eliminate the built-in unity negative feedback, was felt necessary to resolve this problem and a modification of that model is proposed which simulates the data base. Acceleration saturation is achieved by borrowing the idea of the local feedback model for saccades so that one nonlinearity can account for the acceleration-velocity saturation: the main sequence for pursuit. Motor plasticity or motor learning, recently demonstrated for pursuit, is also incorporated and simulated.It was noticed that the offset of pursuit did not show the ringing seen in the onset so this was quantified in one subject. Offset velocity could be characterized by a single exponential with a time constant of about 90 ms. This observation suggests that fixation is not pursuit at zero velocity and that the pursuit system is turned on when needed and off during fixation.     

Complex predictive eye pursuit in monkey: a model system for cerebellar studies of skilled movement

Smooth pursuit eye movements provide a good model system for cerebellar studies of complex motor control in monkeys. First, the pursuit system exhibits predictive control along complex trajectories and this control improves with training. Second, the flocculus/paraflocculus region of the cerebellum appears to generate this control. Lesions impair pursuit and neural activity patterns are closely related to eye motion during complex pursuit. Importantly, neural responses lead eye motion during predictive pursuit and lag eye motion during non-predictable target motions that require visual control. The idea that flocculus/paraflocculus predictive control is non-visual is also supported by a lack of correlation between neural activity and retinal image motion during pursuit. Third, biologically accurate neural network models of the flocculus/paraflocculus allow the exploration and testing of pursuit mechanisms. Our current model can generate predictive control without visual input in a manner that is compatible with the extensive experimental data available for this cerebellar system. Similar types of non-visual cerebellar control are likely to facilitate the wide range of other skilled movements that are observed.     

The neural basis of smooth-pursuit eye movements

Smooth-pursuit eye movements are used to stabilize the image of a moving object of interest on the fovea, thus guaranteeing its high-acuity scrutiny. Such movements are based on a phylogenetically recent cerebro-ponto-cerebellar pathway that has evolved in parallel with foveal vision. Recent work has shown that a network of several cerebrocortical areas directs attention to objects of interest moving in three dimensions and reconstructs the trajectory of the target in extrapersonal space, thereby integrating various sources of multimodal sensory and efference copy information, as well as cognitive influences such as prediction. This cortical network is the starting point of a set of parallel cerebrofugal projections that use different parts of the dorsal pontine nuclei and the neighboring rostral nucleus reticularis tegmenti pontis as intermediate stations to feed two areas of the cerebellum, the flocculus-paraflocculus and the posterior vermis, which make mainly complementary contributions to the control of smooth pursuit.     

Influence of prior and visual information on eye movements in amblyopic children

This study analyzed the characteristics of pursuit and assessed the influence of prior and visual information on eye velocity and saccades in amblyopic and control children, in comparison to adults. Eye movements of 41 children (21 amblyopes and 20 controls) were compared to eye movements of 55 adults (18 amblyopes and 37 controls). Participants were asked to pursue a target moving at a constant velocity. The target was either a ‘standard’ target, with a uniform color intensity, or a ‘noisy’ target, with blurry edges, to mimic the blurriness of an amblyopic eye. Analysis of pursuit patterns showed that the onset was delayed, and the gain was decreased in control children with a noisy target in comparison to amblyopic or control children with a standard target. Furthermore, a significant effect of prior and visual information on pursuit velocity and saccades was found across all participants. Moreover, the modulation of the effect of visual information on the pursuit velocity by group, that is amblyopes or controls with a standard target, and controls with a noisy target, was more limited in children. In other words, the effect of visual information was higher in control adults with a standard target compared to control children with the same target. However, in the case of a blurry target, either in control participants with a noisy target or in amblyopic participants with a standard target, the effect of visual information was larger in children.

     

Anticipatory Smooth Eye Movements in Autism Spectrum Disorder

Smooth pursuit eye movements are important for vision because they maintain the line of sight on targets that move smoothly within the visual field. Smooth pursuit is driven by neural representations of motion, including a surprisingly strong influence of high-level signals representing expected motion. We studied anticipatory smooth eye movements (defined as smooth eye movements in the direction of expected future motion) produced by salient visual cues in a group of high-functioning observers with Autism Spectrum Disorder (ASD), a condition that has been associated with difficulties in either generating predictions, or translating predictions into effective motor commands. Eye movements were recorded while participants pursued the motion of a disc that moved within an outline drawing of an inverted Y-shaped tube. The cue to the motion path was a visual barrier that blocked the untraveled branch (right or left) of the tube. ASD participants showed strong anticipatory smooth eye movements whose velocity was the same as that of a group of neurotypical participants. Anticipatory smooth eye movements appeared on the very first cued trial, indicating that trial-by-trial learning was not responsible for the responses. These results are significant because they show that anticipatory capacities are intact in high-functioning ASD in cases where the cue to the motion path is highly salient and unambiguous. Once the ability to generate anticipatory pursuit is demonstrated, the study of the anticipatory responses with a variety of types of cues provides a window into the perceptual or cognitive processes that underlie the interpretation of events in natural environments or social situations.     

A model of visually-guided smooth pursuit eye movements based on behavioral observations

We report a model that reproduces many of the behavioral properties of smooth pursuit eye movements. The model is a negative-feedback system that uses three parallel visual motion pathways to drive pursuit. The three visual pathways process image motion, defined as target motion with respect to the moving eye, and provide signals related to image velocity, image acceleration, and a transient that occurs at the onset of target motion. The three visual motion signals are summed and integrated to produce the eye velocity output of the model. The model reproduces the average eye velocity evoked by steps of target velocity in monkeys and humans and accounts for the variation among individual responses and subjects. When its motor pathways are expanded to include positive feedback of eye velocity and a switch, the model reproduces the exponential decay in eye velocity observed when a moving target stops. Manipulation of this expanded model can mimic the effects of stimulation and lesions in the arcuate pursuit area, the middle temporal visual area (MT), and the medial superior temporal visual area (MST).     

Which retinal and extra-retinal information is crucial for circular vection?

In contradistinction to conventional wisdom, we propose that retinal image slip of a visual scene (optokinetic pattern, OP) does not constitute the only crucial input for visually induced percepts of self-motion (vection). Instead, the hypothesis is investigated that there are three input factors: 1) OP retinal image slip, 2) motion of the ocular orbital shadows across the retinae, and 3) smooth pursuit eye movements (efference copy). To test this hypothesis, we visually induced percepts of sinusoidal rotatory self-motion (circular vection, CV) in the absence of vestibular stimulation. Subjects were presented with three concurrent stimuli: a large visual OP, a fixation point to be pursued with the eyes (both projected in superposition on a semi-circular screen), and a dark window frame placed close to the eyes to create artificial visual field boundaries that simulate ocular orbital rim boundary shadows, but which could be moved across the retinae independent from eye movements. In different combinations these stimuli were independently moved or kept stationary. When moved together (horizontally and sinusoidally around the subject's head), they did so in precise temporal synchrony at 0.05 Hz. The results show that the occurrence of CV requires retinal slip of the OP and/or relative motion between the orbital boundary shadows and the OP. On the other hand, CV does not develop when the two retinal slip signals equal each other (no relative motion) and concur with pursuit eye movements (as it is the case, e.g., when we follow with the eyes the motion of a target on a stationary visual scene). The findings were formalized in terms of a simulation model. In the model two signals coding relative motion between OP and head are fused and fed into the mechanism for CV, a visuo-oculomotor one, derived from OP retinal slip and eye movement efference copy, and a purely visual signal of relative motion between the orbital rims (head) and the OP. The latter signal is also used, together with a version of the oculomotor efference copy, for a mechanism that suppresses CV at a later stage of processing in conditions in which the retinal slip signals are self-generated by smooth pursuit eye movements.     

Cursive writing with smooth pursuit eye movements

The eyes never cease to move: ballistic saccades quickly turn the gaze toward peripheral targets, whereas smooth pursuit maintains moving targets on the fovea where visual acuity is best. Despite the oculomotor system being endowed with exquisite motor abilities, any attempt to generate smooth eye movements against a static background results in saccadic eye movements [1, 2]. Although exceptions to this rule have been reported [3-5], volitional control over smooth eye movements is at best rudimentary. Here, I introduce a novel, temporally modulated visual display, which, although static, sustains smooth eye movements in arbitrary directions. After brief training, participants gain volitional control over smooth pursuit eye movements and can generate digits, letters, words, or drawings at will. For persons deprived of limb movement, this offers a fast, creative, and personal means of linguistic and emotional expression.     

How Moving Backgrounds Influence Interception

Reaching movements towards an object are continuously guided by visual information about the target and the arm. Such guidance increases precision and allows one to adjust the movement if the target unexpectedly moves. On-going arm movements are also influenced by motion in the surrounding. Fast responses to motion in the surrounding could help cope with moving obstacles and with the consequences of changes in one’s eye orientation and vantage point. To further evaluate how motion in the surrounding influences interceptive movements we asked subjects to tap a moving target when it reached a second, static target. We varied the direction and location of motion in the surrounding, as well as details of the stimuli that are known to influence eye movements. Subjects were most sensitive to motion in the background when such motion was near the targets. Whether or not the eyes were moving, and the direction of the background motion in relation to the direction in which the eyes were moving, had very little influence on the response to the background motion. We conclude that the responses to background motion are driven by motion near the target rather than by a global analysis of the optic flow and its relation with other information about self-motion.     

Visual localization during eye tracking on steady background and during steady fixation on moving background

Experiments were performed to clarify the role of the background motion on the retina in the phenomenon of mislocation of brief visual stimuli during smooth eye tracking. It was found that these visual stimuli were mislocated also relative to a moving background during steady eye fixation. The magnitude of mislocation during pursuit eye movements and during steady fixation was influenced by the stimulus intensity, the background/eye velocity and the place of stimulus presentation in respect to the background; the influence having the same features in both cases. However, the magnitudes of mislocation under the two conditions were quantitatively different. The validity of a hypothesis that the eye movement itself plays no role in the process of localization, and, that this process is based on retinal information only, is considered.     

Pursuit Eye-Movements in Curve Driving Differentiate between Future Path and Tangent Point Models

For nearly 20 years, looking at the tangent point on the road edge has been prominent in models of visual orientation in curve driving. It is the most common interpretation of the commonly observed pattern of car drivers looking through a bend, or at the apex of the curve. Indeed, in the visual science literature, visual orientation towards the inside of a bend has become known as “tangent point orientation”. Yet, it remains to be empirically established whether it is the tangent point the drivers are looking at, or whether some other reference point on the road surface, or several reference points, are being targeted in addition to, or instead of, the tangent point. Recently discovered optokinetic pursuit eye-movements during curve driving can provide complementary evidence over and above traditional gaze-position measures. This paper presents the first detailed quantitative analysis of pursuit eye movements elicited by curvilinear optic flow in real driving. The data implicates the far zone beyond the tangent point as an important gaze target area during steady-state cornering. This is in line with the future path steering models, but difficult to reconcile with any pure tangent point steering model. We conclude that the tangent point steering models do not provide a general explanation of eye movement and steering during a curve driving sequence and cannot be considered uncritically as the default interpretation when the gaze position distribution is observed to be situated in the region of the curve apex.     

Saccadic adaptation to moving targets

Saccades are so called ballistic movements which are executed without online visual feedback. After each saccade the saccadic motor plan is modified in response to post-saccadic feedback with the mechanism of saccadic adaptation. The post-saccadic feedback is provided by the retinal position of the target after the saccade. If the target moves after the saccade, gaze may follow the moving target. In that case, the eyes are controlled by the pursuit system, a system that controls smooth eye movements. Although these two systems have in the past been considered as mostly independent, recent lines of research point towards many interactions between them. We were interested in the question if saccade amplitude adaptation is induced when the target moves smoothly after the saccade. Prior studies of saccadic adaptation have considered intra-saccadic target steps as learning signals. In the present study, the intra-saccadic target step of the McLaughlin paradigm of saccadic adaptation was replaced by target movement, and a post-saccadic pursuit of the target. We found that saccadic adaptation occurred in this situation, a further indication of an interaction of the saccadic system and the pursuit system with the aim of optimized eye movements.     

Segregation of object and background motion in visual area MT: effects of microstimulation on eye movements

To track a moving object, its motion must first be distinguished from that of the background. The center-surround properties of neurons in the middle temporal visual area (MT) may be important for signaling the relative motion between object and background. To test this, we microstimulated within MT and measured the effects on monkeys' eye movements to moving targets. We found that stimulation at "local motion" sites, where receptive fields possessed antagonistic surrounds, shifted pursuit in the preferred direction of the neurons, whereas stimulation at "wide-field motion" sites shifted pursuit in the opposite, or null, direction. We propose that activating wide-field sites simulated background motion, thus inducing a target motion signal in the opposite direction. Our results support the hypothesis that neuronal center-surround mechanisms contribute to the behavioral segregation of objects from the background.