Pursuit Initiation Research Articles

Active inference, eye movements and oculomotor delays

We consider the problem of sensorimotor delays in the optimal control of (smooth) eye movements under uncertainty. Specifically, we consider delays in the visuo-oculomotor loop and their implications for active inference. Active inference uses a generalisation of Kalman filtering to provide Bayes optimal estimates of hidden states and action in generalised coordinates of motion. Representing hidden states in generalised coordinates provides a simple way of compensating for both sensory and oculomotor delays. The efficacy of this scheme is illustrated using neuronal simulations of pursuit initiation responses, with and without compensation. We then consider an extension of the generative model to simulate smooth pursuit eye movements - in which the system believes both the target and its centre of gaze are attracted to a (fictive) point moving in the visual field. Finally, the generative model is equipped with a hierarchical structure, so that it can recognise and remember unseen (occluded) trajectories and emit anticipatory responses. These simulations speak to a straightforward and neurobiologically plausible solution to the generic problem of integrating information from different sources with different temporal delays and the particular difficulties encountered when a system - like the oculomotor system - tries to control its environment with delayed signals. Figure 1 This schematic shows the dependencies among various quantities modelling exchanges of an agent with the environment. It shows the states of the environment and the system in terms of a probabilistic dependency graph, where connections denote directed ...

Like a rolling stone: Naturalistic visual kinematics facilitate tracking eye movements

Newtonian physics constrains object kinematics in the real world. We asked whether eye movements towards tracked objects depend on their compliance with those constraints. In particular, the force of gravity constrains round objects to roll on the ground with a particular rotational and translational motion. We measured tracking eye movements towards rolling objects. We found that objects with rotational and translational motion that was congruent with an object rolling on the ground elicited faster tracking eye movements during pursuit initiation than incongruent stimuli. Relative to a condition without rotational component, we compared objects with this motion with a condition in which there was no rotational component, we essentially obtained benefits of congruence, and, to a lesser extent, costs from incongruence. Anticipatory pursuit responses showed no congruence effect, suggesting that the effect is based on visually-driven predictions, not on velocity storage. We suggest that the eye movement system incorporates information about object kinematics acquired by a lifetime of experience with visual stimuli obeying the laws of Newtonian physics.

The Interaction of Bayesian Priors and Sensory Data and Its Neural Circuit Implementation in Visually Guided Movement

Sensory-motor behavior results from a complex interaction of noisy sensory data with priors based on recent experience. By varying the stimulus form and contrast for the initiation of smooth pursuit eye movements in monkeys, we show that visual motion inputs compete with two independent priors: one prior biases eye speed toward zero; the other prior attracts eye direction according to the past several days' history of target directions. The priors bias the speed and direction of the initiation of pursuit for the weak sensory data provided by the motion of a low-contrast sine wave grating. However, the priors have relatively little effect on pursuit speed and direction when the visual stimulus arises from the coherent motion of a high-contrast patch of dots. For any given stimulus form, the mean and variance of eye speed covary in the initiation of pursuit, as expected for signal-dependent noise. This relationship suggests that pursuit implements a trade-off between movement accuracy and variation, reducing both when the sensory signals are noisy. The tradeoff is implemented as a competition of sensory data and priors that follows the rules of Bayesian estimation. Computer simulations show that the priors can be understood as direction-specific control of the strength of visual-motor transmission, and can be implemented in a neural-network model that makes testable predictions about the population response in the smooth eye movement region of the frontal eye fields.

Dynamics of oculomotor direction discrimination.

Successful foveation of a dynamic target depends on good predictions of its movement direction and speed. We measured and compared the temporal dynamics of directional precision of both saccades and smooth pursuit and their interactions. We also compared the directional precision of both eye movements to psychophysical direction discrimination thresholds. Directional thresholds of pure pursuit responses improved rapidly and reached asymptotic values of 1.5°-3° within 300 ms after target motion onset, both for trained and untrained observers and irrespective of the speed of the stimuli. Psychophysical thresholds were in the same range. Directional thresholds for saccades in the ramp paradigm were just slightly higher, but these occurred significantly earlier in time at around 200 ms after target motion onset. At the equivalent time during pure pursuit initiation, thresholds were typically higher by 2°-3°. The rise in directional precision-or decrease in thresholds-over time was more pronounced for trials with longer latencies. As an effect, precision depended mainly on time since stimulus motion onset rather than pursuit onset. Directional precision for saccades to static targets was slightly better than to moving targets, at even shorter latencies. We conclude that directional precision is higher for the saccadic system at saccade onset than for the pursuit system, presumably due to additional position signals that are not available to the pursuit system at that point in time. The pursuit response improves rapidly due to refined sensory processing and motor planning. The combination of initial saccades and pursuit to track moving targets is a good strategy for the oculomotor system to reduce directional errors during the phase of initiation. The target speed has very little effects on the directional precision of both eye movements.

Role of anticipation and prediction in smooth pursuit eye movement control in Parkinson's disease

Patients with Parkinson's disease (PD) have difficulties in the control of self-guided (i.e., internally driven) movements. The basal ganglia provide a nonspecific internal cue for the development of a preparatory activity for a given movement in the sequence of repetitive movements. Controversy surrounds the question of whether PD patients are capable of (1) anticipating (before an external trigger appears; i.e., anticipation) and (2) predicting movement velocity once a moving target shortly disappears from the visual scene (i.e., prediction). To dissociate between these two components, we examined internally driven (extraretinal generated) smooth pursuit eye movements in PD patients and age-matched healthy controls by systematically varying target blanking periods of a trapezoidally moving target in four paradigms (initial blanking, midramp blanking, blanking after a short ramp, and no blanking). Compared to controls, PD patients showed (1) decreased smooth pursuit gain (without blanking), (2) deficient anticipatory pursuit (prolonged pursuit initiation latency; reduced eye velocity before target onset in the early onset blanking paradigm), and (3) preserved extraretinal predictive pursuit velocity (midramp target blanking). Deficient anticipation of future target motion was not related to either disease duration or the general motor impairment (UPDRS). We conclude that PD patients have difficulties in anticipating future target motion, which may play a role for the mechanisms involved in deficient gait initiation and termination of PD. In contrast, they remain unimpaired in their capacity of building up an internal representation of continuous target motion. This may explain the clinical advantage of medical devices that use visual motion to improve gait initiation (e.g., "PD glasses").

Reward Action in the Initiation of Smooth Pursuit Eye Movements

Reward has a powerful influence on motor behavior. To probe how and where reward systems alter motor behavior, we studied smooth pursuit eye movements in monkeys trained to associate the color of a visual cue with the size of the reward to be issued at the end of the target motion. When the tracking task presented two different colored targets that moved orthogonally, monkeys biased the initiation of pursuit toward the direction of motion of the target that led to larger reward. The bias was larger than expected given the modest effects of reward size on tracking of single targets. Experiments with three different reward sizes suggested that the bias afforded a given target depends mainly on the size of the larger reward. To analyze the effect of reward on directional learning in pursuit, monkeys tracked a single moving target that changed direction 250 ms after the onset of motion. Expectation of a larger reward led to a larger learned eye movement during the acquisition of the learned response and during subsequent probes of what had been learned, implying that reward influenced the expression rather than the acquisition of learning. The specific effects of reward size on learning and two-target stimuli imply that the site of reward modulation is at a level where multiple target motions compete for control of eye movement, downstream from sensory processing and learning and upstream from final motor processing.

Suppression of smooth pursuit eye movements induced by electrical stimulation of the monkey frontal eye field

This study was performed to characterize the properties of the suppression of smooth pursuit eye movement induced by electrical stimulation of the frontal eye field (FEF) in trained monkeys. At the stimulation sites tested, we first determined the threshold for generating electrically evoked saccades (Esacs). We then examined the suppressive effects of stimulation on smooth pursuit at intensities that were below the threshold for eliciting Esacs. We observed that FEF stimulation induced a clear deceleration of pursuit at pursuit initiation and also during the maintenance of pursuit at subthreshold intensities. The suppression of pursuit occurred even in the absence of catch-up saccades during pursuit, indicating that suppression influenced pursuit per se. We mapped the FEF area that was associated with the suppressive effect of stimulation on pursuit. In a wide area in the FEF, suppressive effects were observed for ipsiversive, but not contraversive, pursuit. In contrast, we observed the bilateral suppression of both ipsiversive and contraversive pursuit in a localized area in the FEF. This area coincided with the area in which we have previously shown that stimulation suppressed the generation of saccades in bilateral directions and also where fixation neurons that discharged during fixation were concentrated. On the basis of these results, we compared the FEF suppression of pursuit with that of saccades with regard to several physiological properties and then discussed the role of the FEF in the suppression of both pursuit and saccades, and particularly in the maintenance of visual fixation.

Sensory versus motor loci for integration of multiple motion signals in smooth pursuit eye movements and human motion perception

We have investigated how visual motion signals are integrated for smooth pursuit eye movements by measuring the initiation of pursuit in monkeys for pairs of moving stimuli of the same or differing luminance. The initiation of pursuit for pairs of stimuli of the same luminance could be accounted for as a vector average of the responses to the two stimuli singly. When stimuli comprised two superimposed patches of moving dot textures, the brighter stimulus suppressed the inputs from the dimmer stimulus, so that the initiation of pursuit became winner-take-all when the luminance ratio of the two stimuli was 8 or greater. The dominance of the brighter stimulus could be not attributed to either the latency difference or the ratio of the eye accelerations for the bright and dim stimuli presented singly. When stimuli comprised either spot targets or two patches of dots moving across separate locations in the visual field, the brighter stimulus had a much weaker suppressive influence; the initiation of pursuit could be accounted for by nearly equal vector averaging of the responses to the two stimuli singly. The suppressive effects of the brighter stimulus also appeared in human perceptual judgments, but again only for superimposed stimuli. We conclude that one locus of the interaction of two moving visual stimuli is shared by perception and action and resides in local inhibitory connections in the visual cortex. A second locus resides deeper in sensory-motor processing and may be more closely related to action selection than to stimulus selection.

Inactivation and stimulation of the frontal pursuit area change pursuit metrics without affecting pursuit target selection

The frontal pursuit area (FPA) lies posterior to the frontal eye fields in the frontal cortex and contains neurons that are directionally selective for pursuit eye movements. Lesions of the FPA (alternately called "FEFsem") cause deficits in pursuit acceleration and velocity, which are largest for movements directed toward the lesioned side. Conversely, stimulation of the FPA evokes pursuit from fixation and increases the gain of the pursuit response. On the basis of these properties, it has been hypothesized that the FPA could underlie the selection of pursuit direction. To test this possibility, we manipulated FPA activity and measured the effect on target selection behavior in rhesus monkeys. First, we unilaterally inactivated the FPA with the GABA agonist muscimol. We then measured the monkeys' performance on a pursuit-choice task. Second, we applied microstimulation unilaterally to the FPA during pursuit initiation while monkeys performed the same pursuit-choice task. Both of these manipulations produced significant effects on pursuit metrics; the inactivation decreased pursuit velocity and acceleration, and microstimulation evoked pursuit directly. Despite these changes, both manipulations failed to significantly alter choice behavior. These results show that FPA activity is not necessary for pursuit target selection.

Adaptation of catch-up saccades during the initiation of smooth pursuit eye movements

Reduction of retinal speed and alignment of the line of sight are believed to be the respective primary functions of smooth pursuit and saccadic eye movements. As the eye muscles strength can change in the short-term, continuous adjustments of motor signals are required to achieve constant accuracy. While adaptation of saccade amplitude to systematic position errors has been extensively studied, we know less about the adaptive response to position errors during smooth pursuit initiation, when target motion has to be taken into account to program saccades, and when position errors at the saccade endpoint could also be corrected by increasing pursuit velocity. To study short-term adaptation (250 adaptation trials) of tracking eye movements, we introduced a position error during the first catch-up saccade made during the initiation of smooth pursuit-in a ramp-step-ramp paradigm. The target position was either shifted in the direction of the horizontally moving target (forward step), against it (backward step) or orthogonally to it (vertical step). Results indicate adaptation of catch-up saccade amplitude to back and forward steps. With vertical steps, saccades became oblique, by an inflexion of the early or late saccade trajectory. With a similar time course, post-saccadic pursuit velocity was increased in the step direction, adding further evidence that under some conditions pursuit and saccades can act synergistically to reduce position errors.

Cerebellum and Ocular Motor Control

An intact cerebellum is a prerequisite for optimal ocular motor performance. The cerebellum fine-tunes each of the subtypes of eye movements so they work together to bring and maintain images of objects of interest on the fovea. Here we review the major aspects of the contribution of the cerebellum to ocular motor control. The approach will be based on structural–functional correlation, combining the effects of lesions and the results from physiologic studies, with the emphasis on the cerebellar regions known to be most closely related to ocular motor function: (1) the flocculus/paraflocculus for high-frequency (brief) vestibular responses, sustained pursuit eye movements, and gaze holding, (2) the nodulus/ventral uvula for low-frequency (sustained) vestibular responses, and (3) the dorsal oculomotor vermis and its target in the posterior portion of the fastigial nucleus (the fastigial oculomotor region) for saccades and pursuit initiation.

Learned Timing of Motor Behavior in the Smooth Eye Movement Region of the Frontal Eye Fields

Proper timing is a critical aspect of motor learning. We report a relationship between a representation of time and an expression of learned timing in neurons in the smooth eye movement region of the frontal eye fields (FEF(SEM)). During prelearning pursuit of target motion at a constant velocity, each FEF(SEM) neuron is most active at a distinct time relative to the onset of pursuit tracking. In response to an instructive change in target direction, a neuron expresses the most learning when the instruction occurs near the time of its maximal participation in prelearning pursuit. Different neurons are most active, and undergo the most learning, at distinct times during pursuit. We suggest that the representation of time in the FEF(SEM) drives learning that is temporally linked to an instructive change in target motion, and that this may be a general function of motor areas of the cortex.

The effect of a temporary absence of target velocity information on visual tracking

Experiments with the Rashbass ‘step-ramp’ paradigm have revealed that the initial catchup saccade that occurs near pursuit onset uses target velocity as well as position information in its programming. Information about both position and motion also influences smooth pursuit. To investigate the timing of velocity sampling near the initiation of saccades and smooth pursuit, we analyzed the eye movements made in nine ‘step-ramp’ conditions, produced by combining –2, 0 and +2 deg steps with –8, 0 and +8 deg/s ramps. Each trial had either no temporal gap or a 50-ms gap during which the laser target was extinguished, beginning 25, 50, 75 or 100 ms after the step. Six subjects repeated each of the resulting 45 conditions 25 times. With no temporal gap, saccades were larger in the step-ramp-away’ than the ‘step-only’ condition, confirming that saccade programming incorporates ramp velocity information. A temporal gap had no effect on the accuracy of saccades on ‘step-only’ trials, but often caused undershoots in ‘step-ramp’ trials. A 50-ms gap within the first 100 ms also increased the latency of the initial saccade. Although initial pursuit velocity was unaffected by a temporal gap, a gap that started at 25 ms reliably delayed pursuit onset for ramp motion of the target toward the fovea. Later gaps had a minimal effect on initial pursuit latency. The similar timing of the temporal gaps in target motion information that affect the initiation of saccades and pursuit provides further behavioral evidence that the two types of eye movements share pre-motor neural mechanisms.

Attentional constraints on target selection for smooth pursuit eye movements

Saccadic eye movements are strongly influenced by shifts of attention to non-target objects. In contrast, we have shown previously that the initiation of smooth pursuit eye movements is relatively unaffected when attention is shifted to objects that are either stationary or move in the same direction as the pursuit target (Souto & Kerzel, 2008). Here, we asked how attention interacts with target selection when a choice has to be made between objects moving in opposite directions. In a dual-task paradigm, observers had to pursue a designated object while making a perceptual judgment on an object moving in the opposite direction. The perceptual target was briefly presented after motion onset and disappeared before the eye started to move. The priority assigned to the perceptual and pursuit task was varied. When priority of the perceptual task was equal or greater than priority of the pursuit task, observers frequently pursued the wrong target and pursuit was delayed. We conclude that when an oculomotor choice is to be made between two equally salient motion signals, the successful initiation of pursuit eye movements depends on the presence of an attentional bias towards the target location.

Spatial perception during pursuit initiation

Spatial perception is modulated by eye movements. During smooth pursuit, perceived locations are shifted in the direction of the eye movement. During active fixation, visual space is perceptually compressed towards the fovea. In our present study, we were interested to determine the time course of spatial localization during pursuit initiation, i.e. the transition period from fixation to steady-state pursuit. Human observers had to localize briefly flashed targets around the time of pursuit initiation. Our data clearly show that pursuit-like mislocalization starts well before the onset of the eye movement. Our results point towards corollary-discharge as neural source for the observed perceptual effect.

Incorporating Prediction in Models for Two-Dimensional Smooth Pursuit

A predictive component can contribute to the command signal for smooth pursuit. This is readily demonstrated by the fact that low frequency sinusoidal target motion can be tracked with zero time delay or even with a small lead. The objective of this study was to characterize the predictive contributions to pursuit tracking more precisely by developing analytical models for predictive smooth pursuit. Subjects tracked a small target moving in two dimensions. In the simplest case, the periodic target motion was composed of the sums of two sinusoidal motions (SS), along both the horizontal and the vertical axes. Motions following the same or similar paths, but having a richer spectral composition, were produced by having the target follow the same path but at a constant speed (CS), and by combining the horizontal SS velocity with the vertical CS velocity and vice versa. Several different quantitative models were evaluated. The predictive contribution to the eye tracking command signal could be modeled as a low-pass filtered target acceleration signal with a time delay. This predictive signal, when combined with retinal image velocity at the same time delay, as in classical models for the initiation of pursuit, gave a good fit to the data. The weighting of the predictive acceleration component was different in different experimental conditions, being largest when target motion was simplest, following the SS velocity profiles.

Biological motion influences the visuomotor transformation for smooth pursuit eye movements

Humans are very sensitive to the presence of other living persons or animals in their surrounding. Human actions can readily be perceived, even in a noisy environment. We recently demonstrated that biological motion, which schematically represents human motion, influences smooth pursuit eye movements during the initiation period ( Orban de Xivry, Coppe, Lefèvre, & Missal, 2010). This smooth pursuit response is driven both by a visuomotor pathway, which transforms retinal inputs into motor commands, and by a memory pathway, which is directly related to the predictive properties of smooth pursuit. To date, it is unknown which of these pathways is influenced by biological motion. In the present study, we first use a theoretical model to demonstrate that an influence of biological motion on the visuomotor and memory pathways might both explain its influence on smooth pursuit initiation. In light of this model, we made theoretical predictions of the possible influence of biological motion on smooth pursuit during and after the transient blanking of the stimulus. These qualitative predictions were then compared with recordings of eye movements acquired before, during and after the transient blanking of the stimulus. The absence of difference in smooth pursuit eye movements during blanking of the stimuli and the stronger visually guided smooth pursuit reacceleration after reappearance of the biological motion stimuli in comparison with control stimuli suggests that biological motion influences the visuomotor pathway but not the memory pathway.

Visuomotor Velocity Transformations for Smooth Pursuit Eye Movements

Smooth pursuit eye movements are driven by retinal motion signals. These retinal motion signals are converted into motor commands that obey Listing's law (i.e., no accumulation of ocular torsion). The fact that smooth pursuit follows Listing's law is often taken as evidence that no explicit reference frame transformation between the retinal velocity input and the head-centered motor command is required. Such eye-position-dependent reference frame transformations between eye- and head-centered coordinates have been well-described for saccades to static targets. Here we suggest that such an eye (and head)-position-dependent reference frame transformation is also required for target motion (i.e., velocity) driving smooth pursuit eye movements. Therefore we tested smooth pursuit initiation under different three-dimensional eye positions and compared human performance to model simulations. We specifically tested if the ocular rotation axis changed with vertical eye position, if the misalignment of the spatial and retinal axes during oblique fixations was taken into account, and if ocular torsion (due to head roll) was compensated for. If no eye-position-dependent velocity transformation was used, the pursuit initiation should follow the retinal direction, independently of eye position; in contrast, a correct visuomotor velocity transformation would result in spatially correct pursuit initiation. Overall subjects accounted for all three components of the visuomotor velocity transformation, but we did observe differences in the compensatory gains between individual subjects. We concluded that the brain does perform a visuomotor velocity transformation but that this transformation was prone to noise and inaccuracies of the internal model.

Specific vermal complex spike responses build up during the course of smooth-pursuit adaptation, paralleling the decrease of performance error

Contemporary theories of the cerebellum hold that the complex spike (CS) fired by cerebellar Purkinje cells (PCs) reports the error signal essential for motor adaptation, i.e., the CS serves as a teacher reducing the performance error. This hypothesis suggests a monotonic relationship between CS modulation and performance error: the modulation of CS responses should be maximal at adaptation onset and turn back to its pre-adaptation state when the error is nulled. An alternative viewpoint based on studies of saccades suggests that the modulation of the CS discharge builds up as performance error decreases, and maximum and stable CS modulation is found after adaptation has been completed (Catz et al. 2005). We wanted to know whether this pattern can be generalized to other forms of motor adaptation. We resorted to smooth-pursuit adaptation (SPA) as an example of cerebellar-dependent adaptation. SPA is induced by increasing or decreasing target velocity during pursuit initiation that leads to a gradual increase or decrease in eye velocity. We trained 2 rhesus monkeys and recorded CS from PC in vermal lobuli VI and VII during SPA. We find that SPA is accompanied by a pattern of CS firing, which at the onset of adaptation, i.e., when the error is large, is not modulated significantly. On the other hand, when initial eye velocity is stably increased or decreased by adaptation, the probability of CS occurrence during pursuit initiation decreases or increases, respectively. Overall, our results deviate from the predictions made by the classical error-coding concept.

Coordinate system of visual motion signals driving pursuit initiation

Coordinate system of visual motion signals driving pursuit initiation