Architecture of a gain controller in the pursuit system

Confidence in predicted position error explains saccadic decisions during pursuit

A fundamental problem in motor control is the coordination of complementary movement types to achieve a common goal. As a common example, humans view moving objects through coordinated pursuit and saccadic eye movements. Pursuit is initiated and continuously controlled by retinal image velocity. During pursuit, eye position may lag behind the target. This can be compensated by the discrete execution of a catch-up saccade. The decision to trigger a saccade is influenced by both position and velocity errors, and the timing of saccades can be highly variable. The observed distributions of saccade frequency and trigger time remain poorly understood, and this decision process remains imprecisely quantified. Here, we propose a predictive, probabilistic model explaining the decision to trigger saccades during pursuit to foveate moving targets. In this model, expected position error and its associated uncertainty are predicted through Bayesian inference across noisy, delayed sensory observations (Kalman filtering). This probabilistic prediction is used to estimate the confidence that a saccade is needed (quantified through log-probability ratio), triggering a saccade upon accumulating to a fixed threshold. The model qualitatively explains behavioral observations on the frequency and trigger time distributions of saccades during pursuit over a range of target motion trajectories. Furthermore, this model makes novel predictions that saccade decisions are highly sensitive to uncertainty for small predicted position errors, but this influence diminishes as the magnitude of predicted position error increases. We suggest that this predictive, confidence-based decision-making strategy represents a fundamental principle for the probabilistic neural control of coordinated movements.NEW & NOTEWORTHY This is the first stochastic dynamical systems model of pursuit-saccade coordination accounting for noise and delays in the sensorimotor system. The model uses Bayesian inference to predictively estimate visual motion, triggering saccades when confidence in predicted position error accumulates to a threshold. This model explains saccade frequency and trigger time distributions across target trajectories and makes novel predictions about the influence of sensory uncertainty in saccade decisions during pursuit.

Gain Control in Predictive Smooth Pursuit Eye Movements: Evidence for an Acceleration-Based Predictive Mechanism

The smooth pursuit eye movement system incorporates various control features enabling adaptation to specific tracking situations. In this work, we analyzed the interplay between two of these mechanisms: gain control and predictive pursuit. We tested human responses to high-frequency perturbations during step-ramp pursuit, as well as the pursuit of a periodically moving target. For the latter task, we found a nonlinear interaction between perturbation response and carrier acceleration. Responses to perturbations where the initial perturbation acceleration was contradirectional to carrier acceleration increased with carrier velocity, in a manner similar to that observed during step-ramp pursuit. In contrast, responses to perturbations with ipsidirectional initial perturbation and carrier acceleration were large for all carrier velocities. Modeling the pursuit system suggests that gain control and short-term prediction are separable elements. The observed effect may be explained by combining the standard gain control mechanism with a derivative-based short-term predictive mechanism. The nonlinear interaction between perturbation and carrier acceleration can be reproduced by assuming a signal saturation, which is acting on the derivative of the target velocity signal. Our results therefore argue for the existence of an internal estimate of target acceleration as a basis for a simple yet efficient short-term predictive mechanism.

The Control of Voluntary Eye Movements: New Perspectives

Primates use two types of voluntary eye movements to track objects of interest: pursuit and saccades. Traditionally, these two eye movements have been viewed as distinct systems that are driven automatically by low-level visual inputs. However, two sets of findings argue for a new perspective on the control of voluntary eye movements. First, recent experiments have shown that pursuit and saccades are not controlled by entirely different neural pathways but are controlled by similar networks of cortical and subcortical regions and, in some cases, by the same neurons. Second, pursuit and saccades are not automatic responses to retinal inputs but are regulated by a process of target selection that involves a basic form of decision making. The selection process itself is guided by a variety of complex processes, including attention, perception, memory, and expectation. Together, these findings indicate that pursuit and saccades share a similar functional architecture. These points of similarity may hold the key for understanding how neural circuits negotiate the links between the many higher order functions that can influence behavior and the singular and coordinated motor actions that follow.

The neuronal basis of on-line visual control in smooth pursuit eye movements

Smooth pursuit eye movements allow us to maintain the image of a moving target on the fovea. Smooth pursuit consists of separate phases such as initiation and steady-state. These two phases are supported by different visual-motor mechanisms in cortical areas including the middle temporal (MT), the medial superior temporal (MST) areas and the frontal eye field (FEF). Retinal motion signals are responsible for beginning the process of pursuit initiation, whereas extraretinal signals play a role in maintaining tracking speed. Smooth pursuit often requires on-line gain adjustments during tracking in response to a sudden change in target motion. For example, a brief sinusoidal perturbation of target motion induces a corresponding perturbation of eye motion. Interestingly, the perturbation ocular response is enhanced when baseline pursuit velocity is higher, even though the stimulus frequency and amplitude are constant. This on-line gain control mechanism is not simply due to visually driven activity of cortical neurons. Visual and pursuit signals are primarily processed in cortical MT/MST and the magnitude of perturbation responses could be regulated by the internal gain parameter in FEF. Furthermore, the magnitude and the gain slope of perturbation responses are altered by smooth pursuit adaptation using repeated trials of a step-ramp tracking with two different velocities (double-velocity paradigm). Therefore, smooth pursuit adaptation, which is attributed to the cerebellar plasticity mechanism, could affect the on-line gain control mechanism.

Neural activity in the frontal pursuit area does not underlie pursuit target selection

The frontal pursuit area (FPA) contains neurons that are directionally selective for pursuit eye-movements. We found that FPA neurons discriminate target from distracter too late to account for pursuit directional selection. Rather, the timing of neuronal discrimination is linked to pursuit onset, suggesting a role in motor execution. We also found buildup of activity of FPA neurons prior to pursuit onset that correlated with eye acceleration. These results show that the FPA is unlikely to be involved in selection of initial pursuit direction, but could be involved in motor preparation by increasing pursuit gain prior to pursuit onset.

Ocular Responses to Brief Motion of Textured Backgrounds During Smooth Pursuit in Humans

We studied the effects of horizontal smooth pursuit on the ocular responses to brief vertical perturbations of textured backgrounds in humans. When the subject was fixating on a stationary target, a brief vertical perturbation of the background elicited a small tracking response. When the subject was pursuing a target moving horizontally, the same background perturbation elicited a larger response: that is, the response to vertical background perturbations was enhanced during pursuit (pursuit-related enhancement). On the other hand, the dependencies of the ocular responses on spatial frequency, temporal frequency, and stimulus contrast were similar regardless of the ongoing behavior of the subject. We also found that a low-level energy-based mechanism underlies the ocular responses to vertical perturbations of the background during fixation and smooth pursuit. We conclude that the pursuit-related enhancement is independent of the properties of visual processing for cross-axis motion of backgrounds, which suggests that this enhancement results from uniform facilitation of the visual system and/or from facilitation of visuomotor transmission downstream of the visual processing.

A theory of the dual pathways for smooth pursuit based on dynamic gain control

The smooth pursuit eye movement (SPEM) system is much more sensitive to target motion perturbations during pursuit than during fixation. This sensitivity is commonly attributed to a dynamic gain control mechanism. Neither the neural substrate nor the functional architecture for this gain control has been fully revealed. There are at least two cortical areas that crucially contribute to smooth pursuit and are therefore eligible sites for dynamic gain control: the medial superior temporal area (MST) and the pursuit area of the frontal eye fields (FEFs), which both project to brain stem premotor structures via parallel pathways. The aim of this study was to develop a model of smooth pursuit based on behavioral, anatomical, and neurophysiological results to account for nonlinear dynamic gain control. Using a behavioral paradigm in humans consisting of a sinusoidal oscillation (4 Hz, +/-8 degrees/s) superimposed on a constant velocity target motion (0-24 degrees/s), we were able to identify relevant gain control parameters in the model. A salient feature of our model is the emergence of two parallel pathways from higher visual cortical to lower motor areas in the brain stem that correspond to the MST and FEF pathways. Detailed analysis of the model revealed that one pathway mainly carries eye velocity related signals, whereas the other is associated mostly with eye acceleration. From comparison with known neurophysiological results we conclude that the dynamic gain control can be attributed to the FEF pathway, whereas the MST pathway serves as the basic circuit for maintaining an ongoing SPEM.

Velocity scaling of cue-induced smooth pursuit acceleration obeys constraints of natural motion

Information about the future trajectory of a visual target is contained not only in the history of target motion but also in static visual cues, e.g., the street provides information about the car's future trajectory. For most natural moving targets, this information imposes strong constraints on the relation between velocity and acceleration which can be exploited by predictive smooth pursuit mechanisms. We questioned how cue-induced predictive changes in pursuit direction depend on target speed and how cue- and target-induced pursuit interact. Subjects pursued a target entering a +/-90 degrees curve and moving on either a homogeneous background or on a low contrast static band indicating the future trajectory. The cue induced a predictive change of pursuit direction, which occurred before curve onset of the target. The predictive velocity component orthogonal to the initial pursuit direction started later and became faster with increasing target velocity. The predictive eye acceleration increased quadratically with target velocity and was independent of the initial target direction. After curve onset, cue- and target-induced pursuit velocity components were not linearly superimposed. The quadratic increase of eye acceleration with target velocity is consistent with the natural velocity scaling implied by the two-thirds power law, which is a characteristic of biological controlled movements. Comparison with linear pursuit models reveals that the ratio between eye acceleration and actual or expected retinal slip cannot be considered a constant gain factor. To obey a natural velocity scaling, this acceleration gain must linearly increase with target or pursuit velocity. We suggest that gain control mechanisms, which affect target-induced changes of pursuit velocity, act similarly on predictive changes of pursuit induced by static visual cues.

How do primates anticipate uncertain future events?

The timing of an upcoming event depends on two factors: its temporal position, proximal or distal with respect to the present moment, and the unavoidable stochastic variability around this temporal position. We searched for a general mechanism that could describe how these two factors influence the anticipation of an upcoming event in an oculomotor task. Monkeys were trained to pursue a moving target with their eyes. During a delay period inserted before target motion onset, anticipatory pursuit responses were frequently observed. We found that anticipatory movements were altered by the temporal position of the target. Increasing the timing uncertainty associated with the stimulus resulted in an increase in the width of the latency distribution of anticipatory pursuit. These results show that monkeys relied on an estimation of the changing probability of target motion onset as time elapsed during the delay to decide when to initiate an anticipatory smooth eye movement.

Preparatory Gain Modulation of Visuomotor Transmission for Smooth Pursuit Eye Movements in Monkeys

It has been reported that the visuomotor processing underlying the initiation of smooth pursuit eye movement is modulated in relation to the recent experience of eye movements: the initial pursuit eye velocity is larger after experiencing repeated pursuits than saccades. To assess which parameters of the previously executed pursuits play an essential role in modulating the gain of visuomotor transmission, we recorded the ocular responses of monkeys to a brief perturbing motion of the tracking target injected before the start of the eye movements. First, we compared the perturbation responses among the blocks in which the duration of executing pursuit was varied. We found that the response amplitude increased with the increase of the pursuit duration and it reached a plateau level at 100–200 ms of the duration. Second, a comparison of the perturbation responses in the blocks in which target velocity was different showed a gradual increase of the response as a function of the required pursuit velocity. Third, when the animals repeatedly performed pursuits, the response amplitude gradually increased with increasing interval between the appearance of the target and the onset of perturbation. On the other hand, such an increase was not observed when the animals repeatedly performed saccades. These results suggest that before initiating eye movements, the pursuit system modulates the gain of visuomotor transmission so as to be closely related to the properties of the repeatedly experienced eye movements and this gain modulation is triggered by the target’s appearance.

Anticipatory gain modulation in preparation for smooth pursuit eye movements

We studied the effect of the probability of required tracking on the gain of visuomotor transmission for pursuit initiation in monkeys. We recorded the ocular responses to a brief movement (perturbation) of a target located at an eccentric position from the central fixation spot. As soon as the central fixation spot went off, the animal was required to make a saccade to the target if it remained stationary or to track if it moved. The probability of an upcoming ramp motion of the target (horizontal, 20 degrees /sec), requiring pursuit, was varied (target motion probability [TMP] = 0, 0.25, 0.5, 0.75, and 1, which was fixed in a block). We found that the magnitude of the response to the perturbation increased gradually as the TMP increased. The initial pursuit response and the perturbation response showed very similar dependence on the TMP, suggesting that the response to the perturbation could be used as an index of the gain of visuomotor transmission for pursuit initiation. We also found that the changes in the ocular responses after the TMP was changed from one probability to another occurred rapidly (decay constant of only a few trials). These results suggest that the gain of visuomotor transmission in preparing for pursuit is rapidly modulated in accordance with the anticipated future need for pursuit.

Transcranial magnetic stimulation of frontal oculomotor regions during smooth pursuit

Both the frontal eye fields (FEFs) and supplementary eye fields (SEFs) are known to be involved in smooth pursuit eye movements. It has been shown recently that stimulation of the smooth-pursuit area of the FEF [frontal pursuit area (FPA)] in monkey increases the pursuit response to unexpected changes in target motion during pursuit. In the current study, we applied transcranial magnetic stimulation (TMS) to the FPA and SEF in humans during sinusoidal pursuit to assess its effects on the pursuit response to predictable, rather than unexpected, changes in target motion. For the FPA, we found that TMS applied immediately before the target reversed direction increased eye velocity in the new direction, whereas TMS applied in mid-cycle, immediately before the target began to slow, decreased eye velocity. For the SEF, TMS applied at target reversal increased eye velocity in the new direction but had no effect on eye velocity when applied at mid-cycle. TMS of the control region (leg region of the somatosensory cortex) did not affect eye velocity at either point. Previous stimulation studies of FPA during pursuit have suggested that this region is involved in controlling the gain of the transformation of visual signals into pursuit motor commands. The current results suggest that the gain of the transformation of predictive signals into motor commands is also controlled by the FPA. The effect of stimulation of the SEF is distinct from that of the FPA and suggests that its role in sinusoidal pursuit is primarily at the target direction reversal.

Recasting the Smooth Pursuit Eye Movement System

Primates use a combination of smooth pursuit and saccadic eye movements to stabilize the retinal image of selected objects within the high-acuity region near the fovea. Pursuit has traditionally been viewed as a relatively automatic behavior, driven by visual motion signals and mediated by pathways that connect visual areas in the cerebral cortex to motor regions in the cerebellum. However, recent findings indicate that this view needs to be reconsidered. Rather than being controlled primarily by areas in extrastriate cortex specialized for processing visual motion, pursuit involves an extended network of cortical areas, and, of these, the pursuit-related region in the frontal eye fields appears to exert the most direct influence. The traditional pathways through the cerebellum are important, but there are also newly identified routes involving structures previously associated with the control of saccades, including the basal ganglia, the superior colliculus, and nuclei in the brain stem reticular formation. These recent findings suggest that the pursuit system has a functional architecture very similar to that of the saccadic system. This viewpoint provides a new perspective on the processing steps that occur as descending control signals interact with circuits in the brain stem and cerebellum responsible for gating and executing voluntary eye movements. Although the traditional view describes pursuit and saccades as two distinct neural systems, it may be more accurate to consider the two movements as different outcomes from a shared cascade of sensory–motor functions.

Preparatory modulation of the gain of visuo-motor transmission for smooth pursuit in monkeys

Brief movement of a foveated target is known to elicit higher velocity ocular (tracking) responses if the target is in motion rather than stationary. We determined whether similar perturbations of a stationary target would have greater ocular effects if we merely increased the probability that the target might undergo sustained motion. For this, we examined the effect of interleaving trials in which the target was always stationary with trials in which the target underwent sustained motion that required the animal to track. We found that perturbation of the stationary target had a greater effect when there were interleaved trials in which the target moved, as though the gain of the visuo-motor transmission had been increased in anticipation of future tracking.

Role of arcuate frontal cortex of monkeys in smooth pursuit eye movements. II. Relation to vector averaging pursuit

When monkeys view two targets moving in different directions and are given no cues about which to track, the initiation of smooth pursuit is a vector average of the response evoked by each target singly. In the present experiments, double-target stimuli consisted of two identical targets moving in opposite directions along the preferred axis of pursuit for the neuron under study for 200 ms, followed by the continued motion for 800 ms of one target chosen randomly. Among the neurons that showed directional modulation during pursuit, recordings revealed three groups. The majority (32/60) showed responses that were intermediate to, and statistically different from, the responses to either target presented alone. Another large group (22/60) showed activity that was statistically indistinguishable from the response to the target moving in the preferred (n = 15) or opposite (n = 7) direction of the neuron under study. The minority (6/60) showed statistically higher firing during averaging pursuit than for either target presented singly. We conclude that many pursuit-related neurons in the frontal pursuit area (FPA) carry signals related to the motor output during averaging pursuit, while others encode the motion of one target or the other. Microstimulation with 200-ms trains of pulses at 50 microA while monkeys performed the same double-target tasks biased the averaging eye velocity in the direction of evoked eye movements during fixation. The effect of stimulation was compared with the predictions of three different models that placed the site of vector averaging upstream from, at, or downstream from the sites where the FPA regulates the gain of pursuit. The data were most consistent with a site for pursuit averaging downstream from the gain control, both for double-target stimuli that presented motion in opposite directions and in orthogonal directions. Thus the recording and stimulation data suggest that the FPA is both downstream and upstream from the sites of vector averaging. We resolve this paradox by suggesting that the site of averaging is really downstream from the site of gain control, while feedback of the eye velocity command from the brain stem and/or cerebellum is responsible for the firing of FPA neurons in relation to the averaged eye velocity. We suggest that eye velocity feedback allows FPA neurons to continue firing during accurate tracking, when image motion is small, and that the persistent output from the FPA is necessary to keep the internal gain of pursuit high and permit accurate pursuit.

Enhancement of multiple components of pursuit eye movement by microstimulation in the arcuate frontal pursuit area in monkeys

Periarcuate frontal cortex is involved in the control of smooth pursuit eye movements, but its role remains unclear. To better understand the control of pursuit by the "frontal pursuit area" (FPA), we applied electrical microstimulation when the monkeys were performing a variety of oculomotor tasks. In agreement with previous studies, electrical stimulation consisting of a train of 50-microA pulses at 333 Hz during fixation of a stationary target elicited smooth eye movements with a short latency (approximately 26 ms). The size of the elicited smooth eye movements was enhanced when the stimulation pulses were delivered during the maintenance of pursuit. The enhancement increased as a function of ongoing pursuit speed and was greater during pursuit in the same versus opposite direction of the eye movements evoked at a site. If stimulation was delivered during pursuit in eight different directions, the elicited eye velocity was fit best by a model incorporating two stimulation effects: a directional signal that drives eye velocity and an increase in the gain of ongoing pursuit eye speed in all directions. Separate experiments tested the effect of stimulation on the response to specific image motions. Stimulation consisted of a train of pulses at 100 or 200 Hz delivered during fixation so that only small smooth eye movements were elicited. If the stationary target was perturbed briefly during microstimulation, normally weak eye movement responses showed strong enhancement. If delivered at the initiation of pursuit, the same microstimulation caused enhancement of the presaccadic initiation of pursuit for steps of target velocity that moved the target either away from the position of fixation or in the direction of the eye movement caused by stimulation at the site. Stimulation in the FPA increased the latency of saccades to stationary or moving targets. Our results show that the FPA has two kinds of effects on the pursuit system. One drives smooth eye velocity in a fixed direction and is subject to on-line gain control by ongoing pursuit. The other causes enhancement of both the speed of ongoing pursuit and the responses to visual motion in a way that is not strongly selective for the direction of pursuit. Enhancement may operate either at a single site or at multiple sites. We conclude that the FPA plays an important role in on-line gain control for pursuit as well as possibly delivering commands for the direction and speed of smooth eye motion.

Regulation of the gain of visually guided smooth-pursuit eye movements by frontal cortex

In studies of the neural mechanisms giving rise to behaviour, changes in the neural and behavioural responses produced by a given stimulus have been widely reported. This 'gain control' can boost the responses to sensory inputs that are particularly relevant, select among reflexes for execution by motoneurons or emphasize specific movement targets. Gain control is also an integral part of the smooth-pursuit eye movement system. One signature of gain control is that a brief perturbation of a stationary target during fixation causes tiny eye movements, whereas the same perturbation of a moving target during the active state of accurate pursuit causes large responses. Here we show that electrical stimulation of the smooth-pursuit eye movement region in the arcuate sulcus of the frontal lobe ('the frontal pursuit area', FPA) mimics the active state of pursuit. Such stimulation enhances the response to a brief perturbation of target motion, regardless of the direction of motion. We postulate that the FPA sets the gain of pursuit, thereby participating in target selection for pursuit.