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During visual pursuit of a moving target, expected changes in its trajectory often evoke anticipatory smooth pursuit responses. In the present study, we investigated characteristics of anticipatory smooth pursuit decelerations before a change or the end of a target trajectory. Healthy humans had to pursue with the eyes a target moving along a circular path that predictably or unpredictably reversed direction and then retraced its movement back to the starting position. We found that anticipatory eye decelerations were often evoked in temporal expectation of target reversal and of the end of the trajectory. The latency of anticipatory decelerations initiated before target reversal was variable, had poor temporal accuracy and depended on the history of previous trials. Anticipations of the end of the trajectory were more accurate, more precise and were not influenced by previous trials. In this case, subjects probably based their estimate of the end of the trajectory on the duration just experienced before target motion reversal. These results suggest that anticipatory eye decelerations are based on the characteristics of the current or preceding trials depending on the most reliable information available.

Expectation of upcoming events is an essential cognitive function on which anticipatory actions are based. The neuronal basis of this prospective representation is poorly understood. We trained rhesus monkeys in a smooth-pursuit task in which the direction of upcoming target motion was indicated using a color cue. Under these conditions, directional expectation frequently evoked anticipatory smooth movements. We found that the activity of a population of neurons in the supplementary eye fields encoded the expected future direction of the target. Neuronal activity increased after presentation of the cue, indicating future target motion in the preferred direction. Neuronal activity either remained unaltered or was reduced if the antipreferred direction was cued. In addition, ∼30% of these neurons were more active during trials with anticipatory pursuit in the preferred direction than during trials when monkeys did not anticipate target motion onset. This subset of recorded neurons encoded the direction of the subsequent anticipatory pursuit. We hypothesize that the neural representation of directional expectation could be conceptualized as a competitive interaction between pools of neurons representing likely future events, with the winner of this competition determining the direction of the subsequent anticipatory movement. Similar mechanisms could drive prediction before movement initiation in other motor domains.

When objects move in our environment, the orientation of the visual axis in space requires the coordination of two types of eye movements: saccades and smooth pursuit. The principal input to the saccadic system is position error, whereas it is velocity error for the smooth pursuit system. Recently, it has been shown that catch-up saccades to moving targets are triggered and programmed by using velocity error in addition to position error. Here, we show that, when a visual target is flashed during ongoing smooth pursuit, it evokes a smooth eye movement toward the flash. The velocity of this evoked smooth movement is proportional to the position error of the flash; it is neither influenced by the velocity of the ongoing smooth pursuit eye movement nor by the occurrence of a saccade, but the effect is absent if the flash is ignored by the subject. Furthermore, the response started around 85 ms after the flash presentation and decayed with an average time constant of 276 ms. Thus this is the first direct evidence of a position input to the smooth pursuit system. This study shows further evidence for a coupling between saccadic and smooth pursuit systems. It also suggests that there is an interaction between position and velocity error signals in the control of more complex movements.

A saccade triggered during sustained smooth pursuit is programmed using retinal information about the relative position and velocity of the target with respect to the eye. Thus the smooth pursuit and saccadic systems are coordinated by using common retinal inputs. Yet, in the absence of retinal information about the relative motion of the eye with respect to the target, the question arises whether the smooth and saccadic systems are still able to be coordinated possibly by using extraretinal information to account for the saccadic and smooth eye movements. To address this question, we flashed a target during smooth anticipatory eye movements in darkness, and the subjects were asked to orient their visual axis to the remembered location of the flash. We observed multiple orientation saccades (typically 2–3) toward the memorized location of the flash. The first orienting saccade was programmed using only the position error at the moment of the flash, and the smooth eye movement was ignored. However, subsequent saccades executed in darkness compensated gradually for the smooth eye displacement (mean compensation ≅ 70%). This behavior revealed a 400-ms delay in the time course of orientation for the compensation of the ongoing smooth eye displacement. We conclude that extraretinal information about the smooth motor command is available to the saccadic system in the absence of visual input. There is a 400-ms delay for smooth movement integration, saccade programming and execution.

The aim of the present study was to find out whether smooth eye movements (SEMs) evoked by superior colliculus (SC) stimulation are, as suggested by Breznen et al. (1996), artefactual eye movements resulting from a non-physiological response of the saccadic generator. This question was reinvestigated in head-restrained cats. Long-lasting SC stimulation was found to evoke, in a comparable proportion, either a single saccade followed by an uninterrupted SEM or a staircase of two or three saccades interleaved with SEMs. These two different patterns of eye movements could be elicited at a near-threshold current and at low stimulation frequencies. In most cases, SEM direction clearly differed from that of the preceding saccade. This difference between SEM and saccade directions varied in a systematic way as a function of the initial saccade direction. As demonstrated by computer simulation, this observation can be explained if the neural circuit controlling SEMs reaches a saturation level earlier than the saccadic burst-generator. Our results in cats were reminiscent of those reported by Breznen et al. (1996) in the monkey only in some instances, when high frequency stimulation (400-600 Hz) was applied. Indeed, in the case of near-threshold stimulation-elicited staircase saccades, increasing the stimulation frequency led to a progressive disappearance of the smaller subsequent saccades that were substituted by uninterrupted SEM-like movements. Altogether, the present results confirm the view that SEMs are genuine eye movements. These results rule out the hypothesis that SEMs result from a saturation of the saccadic generator and strengthen the hypothesis that SEMs and saccades are distinct movements. We suggest that the same collicular efferent cells carry out the motor command to saccadic and SEM circuits and that the position error originating from the SC may be distributed amongst separate downstream motor systems.

During visual tracking of a moving stimulus, primates orient their visual axis by combining two very different types of eye movements, smooth pursuit and saccades. The purpose of this paper was to investigate quantitatively the catch-up saccades occurring during sustained pursuit. We used a ramp-step-ramp paradigm to evoke catch-up saccades during sustained pursuit. In general, catch-up saccades followed the unexpected steps in position and velocity of the target. We observed catch-up saccades in the same direction as the smooth eye movement (forward saccades) as well as in the opposite direction (reverse saccades). We made a comparison of the main sequences of forward saccades, reverse saccades, and control saccades made to stationary targets. They were all three significantly different from each other and were fully compatible with the hypothesis that the smooth pursuit component is added to the saccadic component during catch-up saccades. A multiple linear regression analysis was performed on the saccadic component to find the parameters determining the amplitude of catch-up saccades. We found that both position error and retinal slip are taken into account in catch-up saccade programming to predict the future trajectory of the moving target. We also demonstrated that the saccadic system needs a minimum period of approximately 90 ms for taking into account changes in target trajectory. Finally, we reported a saturation (above 15°/s) in the contribution of retinal slip to the amplitude of catch-up saccades.

When tracking moving visual stimuli, primates orient their visual axis by combining two kinds of eye movements, smooth pursuit and saccades, that have very different dynamics. Yet, the mechanisms that govern the decision to switch from one type of eye movement to the other are still poorly understood, even though they could bring a significant contribution to the understanding of how the CNS combines different kinds of control strategies to achieve a common motor and sensory goal. In this study, we investigated the oculomotor responses to a large range of different combinations of position error and velocity error during visual tracking of moving stimuli in humans. We found that the oculomotor system uses a prediction of the time at which the eye trajectory will cross the target, defined as the “eye crossing time” ( T XE). The eye crossing time, which depends on both position error and velocity error, is the criterion used to switch between smooth and saccadic pursuit, i.e., to trigger catch-up saccades. On average, for T XEbetween 40 and 180 ms, no saccade is triggered and target tracking remains purely smooth. Conversely, when T XEbecomes smaller than 40 ms or larger than 180 ms, a saccade is triggered after a short latency (around 125 ms).

Recent experimental results show evidence for the corrective role of postsaccadic drifts. This paper addresses the modeling of these slow correcting gaze movements (SCMs). Classical arguments to explain drifts are presented, both in the head fixed condition (pulse-step mismatch) and in the head free condition (vestibulo-ocular reflex (VOR)). The most significant behavioral and electrophysiological experimental data related to SCMs are then briefly reported, with the conclusion that SCMs have a clear corrective role, incompatible with classical explanations of drifts. Based on these experimental data, existing models of the saccadic system are then compared. A theoretical comparison of the classical Robinson model with an alternative model is proposed. Two possible (slow and fast) pathways involved in the control of SCMs are examined, and simulation results are presented. Finally, the discussion addresses the observed species differences in SCMs. The link between natural SCMs and electrical SC stimulations, and the interactions between saccades, VOR, and SCMs are also discussed.

Feeling the beat and meter is fundamental to the experience of music. However, how these periodicities are represented in the brain remains largely unknown. Here, we test whether this function emerges from the entrainment of neurons resonating to the beat and meter. We recorded the electroencephalogram while participants listened to a musical beat and imagined a binary or a ternary meter on this beat (i.e., a march or a waltz). We found that the beat elicits a sustained periodic EEG response tuned to the beat frequency. Most importantly, we found that meter imagery elicits an additional frequency tuned to the corresponding metric interpretation of this beat. These results provide compelling evidence that neural entrainment to beat and meter can be captured directly in the electroencephalogram. More generally, our results suggest that music constitutes a unique context to explore entrainment phenomena in dynamic cognitive processing at the level of neural networks.

When viewing one object move after being struck by another, humans perceive that the action of the first object “caused” the motion of the second, not that the two events occurred independently. Although established as a perceptual and linguistic concept, it is not yet known whether the notion of causality exists as a fundamental, preattentional “Gestalt” that can influence predictive motor processes. Therefore, eye movements of human observers were measured while viewing a display in which a launcher impacted a tool to trigger the motion of a second “reaction” target. The reaction target could move either in the direction predicted by transfer of momentum after the collision (“causal”) or in a different direction (“noncausal”), with equal probability. Control trials were also performed with identical target motion, either with a 100 ms time delay between the collision and reactive motion, or without the interposed tool. Subjects made significantly more predictive movements (smooth pursuit and saccades) in the causal direction during standard trials, and smooth pursuit latencies were also shorter overall. These trends were reduced or absent in control trials. In addition, pursuit latencies in the noncausal direction were longer during standard trials than during control trials. The results show that causal context has a strong influence on predictive movements.

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.

A classic paradigm to study anticipatory pursuit consists in training monkeys to look at a target that appears in the center of a visual display, disappears during a short “gap” period, then reappears and immediately starts to move. To determine the role of prior directional information on anticipatory pursuit eye movements, we trained rhesus monkeys to associate the color of a centrally presented visual cue with the direction of an upcoming target motion. In a first experiment, a gap period occurred randomly in 50% of the trials. Consequently, two possible choices of timing of target motion onset were given to subjects to guide their anticipatory responses. In a second experiment, a gap period occurred during each trial and only a single choice of timing of target motion onset was given to subjects. We found that monkeys used the learned association between the color of the cue and the direction of future target motion to voluntarily initiate anticipatory pursuit movements in the appropriate direction. Anticipatory movements could be classified in two distinct populations: early and late movements. Early movements were most frequent when prior directional information was provided and when two choices of timing of target motion onset were given. The latency of visual pursuit was shortened and its velocity was larger when prior directional information was provided. We conclude that cognitive expectation of future target motion plays a dominant role in determining characteristics of anticipatory pursuit in the monkey.

The influence of position and motion signals on saccades was studied in two dimensions (2D) using a double step-ramp paradigm. We showed the presence of a predictive component in 2D catch-up saccade programming that is based on motion signals and influences both saccade amplitude and orientation. Interestingly, a significant proportion of catch-up saccades was characterized by a large curvature or a sudden change of direction in midflight for large values of retinal slip. For these saccades, a quantitative analysis showed that their trajectory could be explained by an asynchrony between position and motion signals in saccade programming. When the saccade trajectory was not straight, position error was always available first and influenced the initial orientation of the saccade, whereas retinal slip determined the final orientation. This new paradigm could be used in electrophysiological experiments, where it should prove to be very useful to study position and motion pathways separately in catch-up saccades.

It is an essential feature for the visual system to keep track of self-motion to maintain space constancy. Therefore the saccadic system uses extraretinal information about previous saccades to update the internal representation of memorized targets, an ability that has been identified in behavioral and electrophysiological studies. However, a smooth eye movement induced in the latency period of a memory-guided saccade yielded contradictory results. Indeed some studies described spatially accurate saccades, whereas others reported retinal coding of saccades. Today, it is still unclear how the saccadic system keeps track of smooth eye movements in the absence of vision. Here, we developed an original two-dimensional behavioral paradigm to further investigate how smooth eye displacements could be compensated to ensure space constancy. Human subjects were required to pursue a moving target and to orient their eyes toward the memorized position of a briefly presented second target (flash) once it appeared. The analysis of the first orientation saccade revealed a bimodal latency distribution related to two different saccade programming strategies. Short-latency (175 ms) saccades used extraretinal information about the smooth eye displacement during the latency period to program spatially more accurate saccades. Sensory parameters at the moment of the flash (retinal position error and eye velocity) influenced the choice between both strategies. We hypothesize that this tradeoff between speed and accuracy of the saccadic response reveals the presence of two coupled neural pathways for saccadic programming. A fast striatal-collicular pathway might only use retinal information about the flash location to program the first saccade. The slower pathway could involve the posterior parietal cortex to update the internal representation of the flash once extraretinal smooth eye displacement information becomes available to the system.

Anticipatory movements are motor responses occurring before likely sensory events in contrast to reflexive actions. Anticipatory movements are necessary to compensate for delays present in sensory and motor systems. Smooth pursuit eye movements are often used as a paradigmatic example for the study of anticipation. However, the neural control of anticipatory pursuit is unknown. A previous study suggested that the supplementary eye fields (SEFs) could play a role in the guidance of smooth pursuit to predictable target motion. In this study, we favored anticipatory responses in monkeys by making the parameters of target motion highly predictable and electrically stimulated the SEF before and during this behavior. Stimulation sites were restricted to regions of the SEF where saccades could not be evoked at the same low currents. We found that electrical microstimulation in the SEF increased the velocity of anticipatory pursuit movements and decreased their latency. These effects will be referred to as anticipatory pursuit facilitation. The degree of facilitation was the largest if the stimulation train was delivered near the end of the fixation period, before the moment when anticipatory pursuit usually begins. No anticipatory smooth eye movements could be evoked during fixation without an expectation of target motion. These results suggest that the SEF pursuit area might be involved in the process of guiding anticipatory pursuit.

A long-standing belief holds that the saccadic and smooth-pursuit eye movement systems are composed of largely separate premotor circuits, at least in the brainstem. One crucial prediction predicated on this belief is that the tonic discharge of omnipause neurons (OPNs), which are thought to be part of only the saccadic system, should not be modulated during pursuit eye movements. This report shows that the discharge of OPNs, in contradiction, is modulated downward during pursuit movements. In contrast to their behavior during saccades, where they pause completely for the duration of the movement, the downward modulation during pursuit did not totally silence OPNs. The depth of the downward modulation was correlated with the speed of the ongoing pursuit movement. Another type of cell, which we have named saccade/pursuit neurons, was recorded in the paramedian pontine reticular formation near the location of OPNs. This subpopulation of burst cells discharged a cascade of spikes for saccades in a preferred direction. They also displayed a lower-frequency sustained discharge of spikes for the duration of pursuit in the same preferred direction. These data suggest a new type of combined model for the organization of the brainstem saccade/pursuit system. In this new combined model, the OPNs form a common inhibitory mechanism for both types of movements, and the saccade/pursuit neurons participate in the eye-velocity modulation of OPN discharge or membrane polarization during either type of movement.

The study of the saccadic system has focused mainly on neurons active before the beginning of saccades, in order to determine their contribution in movement planning and execution. However, most oculomotor structures contain also neurons whose activity starts only after the onset of saccades, the maximum of their activity sometimes occurring near saccade end. Their characteristics are still largely unknown. We investigated pretectal neurons with saccade-related activity in the alert cat during eye movements towards a moving target. They emitted a high-frequency burst of action potentials after the onset of saccades, irrespective of their direction, and will be referred to as "pretectal saccade-related neurons". The delay between saccade onset and cell activity varied from 17 to 66 ms on average. We found that burst parameters were correlated with the parameters of saccades; the peak eye velocity was correlated with the peak of the spike density function, the saccade amplitude with the number of spikes in the burst, and burst duration increased with saccade duration. The activity of six pretectal saccade-related neurons was studied during smooth pursuit at different velocities. A correlation was found between smooth pursuit velocity and mean firing rate. A minority of these neurons (2/6) were also visually responsive. Their visual activity was proportional to the difference between eye and target velocity during smooth pursuit (retinal slip). These results indicate that the activity of pretectal saccade-related neurons is correlated with the characteristics of eye movements. This finding is in agreement with the known anatomical projections from premotor regions of the saccadic system to the pretectum.

The role of the supplementary eye fields (SEF) during smooth pursuit was investigated with electrical microstimulation. We found that stimulation in the SEF increased the acceleration and velocity of the eyes in the direction of target motion during smooth pursuit initiation but not during sustained pursuit. The increase in eye velocity during initiation will be referred to as pursuit facilitation and was observed at sites where saccades could not be evoked with the same stimulation parameters. On average, electrical stimulation increased eye velocity by ∼20%. At most sites, the threshold for a significant facilitation was 50 μA with a stimulation frequency of 300 Hz. Facilitation of pursuit initiation depended on the timing of stimulation trains. The effect was most pronounced if the stimulation was delivered before smooth pursuit initiation. On average, eye velocity in stimulation trials increased linearly as a function of eye velocity in control trials, and this function had a slope greater than one, suggesting a multiplicative influence of the stimulation. Stimulation during a fixation task did not evoke smooth eye movements. The latency of catch-up saccades was increased during facilitation, but their accuracy was not affected. Saccades toward stationary targets were not affected by the stimulation. The results are further evidence that the SEF plays a role in smooth pursuit in addition to its known role in saccade planning and suggest that this role may be to control the gain of smooth pursuit during initiation. The covariance between pursuit facilitation and the timing of the catch-up saccade as a result of stimulation suggests that these different eye movements systems are coordinated to achieve a common goal.

Visual tracking of moving targets requires the combination of smooth pursuit eye movements with catch-up saccades. In primates, catch-up saccades usually take place only during pursuit initiation because pursuit gain is close to unity. This contrasts with the lower and more variable gain of smooth pursuit in cats, where smooth eye movements are intermingled with catch-up saccades during steady-state pursuit. In this paper, we studied in detail the role of retinal slip in the prediction of target motion during smooth and saccadic pursuit in the cat. We found that the typical pattern of pursuit in the cat was a combination of smooth eye movements with saccades. During smooth pursuit initiation, there was a correlation between peak eye acceleration and target velocity. During pursuit maintenance, eye velocity oscillated at approximately 3 Hz around a steady-state value. The average gain of smooth pursuit was approximately 0.5. Trained cats were able to continue pursuing in the absence of a visible target, suggesting a role of the prediction of future target motion in this species. The analysis of catch-up saccades showed that the smooth-pursuit motor command is added to the saccadic command during catch-up saccades and that both position error and retinal slip are taken into account in their programming. The influence of retinal slip on catch-up saccades showed that prediction about future target motion is used in the programming of catch-up saccades. Altogether, these results suggest that pursuit systems in primates and cats are qualitatively similar, with a lower average gain in the cat and that prediction affects both saccades and smooth eye movements during pursuit.

Differences between gaze shifts evoked by collicular electrical stimulation and those triggered by the presentation of a visual stimulus were studied in head-free cats by increasing the head moment of inertia. This maneuver modified the dynamics of these two types of gaze shifts by slowing down head movements. Such an increase in the head moment of inertia did not affect the metrics of visually evoked gaze saccades because their duration was precisely adjusted to compensate for these changes in movement dynamics. In contrast, the duration of electrically evoked gaze shifts remained constant irrespective of the head moment of inertia, and therefore their amplitude was significantly reduced. These results suggest that visually and electrically evoked gaze saccades are controlled by different mechanisms. Whereas the accuracy of visually evoked saccades is likely to be assured by on-line feedback information, the absence of duration adjustment in electrically evoked gaze shifts suggests that feedback information necessary to maintain their metrics is not accessible or is corrupted during collicular stimulation. This is of great importance when these two types of movements are compared to infer the role of the superior colliculus in the control of orienting gaze shifts.

Missal et al. observed that the responses of inferior temporal (IT) neurons to a shape were reduced markedly when this shape partially overlapped a larger second shape, suggesting that shape interactions determine IT responses. In the present study, we compared the responses of IT neurons with combinations of two shapes which did or did not overlap and studied the effect of the relative and absolute positions of the two shapes. In a first test, a preferred shape (figure) was presented at the fixation point while a second, nonpreferred, shape was displayed either in the background of the figure (overlap) or at one of four peripheral positions (nonoverlap). Controls consisted of presentations of either shape in isolation at each of the five positions. The stimuli were presented during a fixation task. The responses to these combinations of two shapes were, on average, reduced compared with those elicited by the preferred shape presented in isolation. This suppression occurred whether or not the two shapes overlapped, but the degree of suppression in the overlap and nonoverlap conditions did not correlate. These interactions were stronger when the interacting stimulus was located in the contralateral compared with the ipsilateral hemifield. The position of the interacting stimulus within a hemifield significantly affected the suppression associated with combined shapes in some neurons. The strength of the interactions of the two nonoverlapping shapes depended on the shape of the interacting stimulus in half of the neurons. In a second test, the preferred shape and interacting stimulus could appear either at the fixation point or at one eccentric position. Here we found that the suppression was, on average, strongest when the interacting stimulus, rather than the preferred shape, was presented at the fixation position. Also, in 40% of the neurons, the response reduction was similar in overlap and nonoverlap conditions if effects of stimulus position were taken into account. In both tests, we also measured the responses to combinations of a nonpreferred shape and the interacting stimulus and showed that the response to a combination of two nonpreferred shapes was, in general, smaller than the response to a combination of the preferred and nonpreferred shape. Overall the results indicate that stimulus interactions in the receptive fields of IT neurons can be position and shape selective; this can contribute to the coding for the relationships between object parts.

Head-fixed gaze shifts were evoked by electrical stimulation of the deeper layers of the cat superior colliculus (SC). After a short latency, saccades were triggered with kinematics similar to those of visually guided saccades. When electrical stimulation was maintained for more than 150-200 ms, postsaccadic smooth eye movements (SEMs) were observed. These movements were characterized by a period of approximately constant velocity following the evoked saccade. Depending on electrode position, a single saccade followed by a slow displacement or a "staircase" of saccades interspersed by SEMs were evoked. Mean velocity decreased with increasing deviation of the eye in the orbit in the direction of the movement. In the situation where a single evoked saccade was followed by a smooth movement, the duration of the latter depended on the duration of the stimulation train. In the situation where evoked saccades converged towards a restricted region of the visual field ("goal"-directed or craniocentric saccades), the SEMs were directed towards the centre of this region and their mean velocity decreased as the eye approached the goal. The direction of induced SEMs depended on the site of stimulation, as is the case for saccadic eye movements, and was not modified by stimulation parameters ("place" code). On the other hand, mean velocity of the movements depended on the site of stimulation and on the frequency and intensity of the current ("rate" code), as reported for saccades in the cat. The kinematics of these postsaccadic SEMs are similar to the kinematics of slow, postsaccadic correction observed during visually triggered gaze shifts of the alert cat. These results support the hypothesis that the SC is not exclusively implicated in the control of fast refixation of gaze but also in controlling postsaccadic conjugate slow eye movements in the cat.

It is generally accepted that in cats smooth pursuit velocity of the eye never exceeds a few degrees per second. This is in contrast with observations in primates, where smooth pursuit velocity can reach values as high as 100 degrees/s. Cats were trained to fixate and pursue spots of light appearing on a translucent screen. Spots were moved in the horizontal and vertical planes at different constant velocities up to 80%. Eye position was recorded with the scleral search coil technique. Naive cats did not pursue moving targets with high efficiency. Smooth eye movement velocity saturated at 5 degrees/s. After a few days of training, smooth-pursuit eye velocity increased with target velocity and saturated at 25 degrees/s on average. However, velocities twice as high have been observed frequently. When the target was unexpectedly extinguished, smooth eye movement velocity dropped to values close to 0 degree/s in approximately 350 ms. After a short training period (usually 5 times the same target presentation), the eye continued to move smoothly until the target reappeared. These data suggest that smooth pursuit eye movements of the cat are qualitatively similar to those of primates, but reach lower velocities and are more variable in their characteristics.

Inspection of eye saccades made by head-fixed, trained cats revealed the existence of many eye shifts at an approximately constant velocity during the deceleratory phase of the saccade or at the end of it. Slow eye movements occurring at the end of a saccade are usually referred to as "postsaccadic drifts". It is shown that the duration and mean velocity of these "drifts" are related to the amplitude of the movement. The kinematics of these slow eye movements are nevertheless different from those of saccades. Slow movements at the end of the gaze shift have longer durations than those occurring during the intersaccadic interval between a saccade and a reacceleration of the eye. A closer study of the drifts of three trained cats showed that they play an important corrective role in reducing the residual error at the end of a saccade or during an intersaccadic interval. This functional corrective role was demonstrated by relating the amplitude of the slow movement to the amplitude of the residual error when the slow velocity eye shift began. It is therefore proposed to name these eye shifts "slow correcting movements".

The activity of vertical burst neurons (BNs) was recorded in the rostral interstitial nucleus of the medial longitudinal fasciculus (riMLF-BNs) and in the interstitial nucleus of Cajal (NIC-BNs) in head-restrained cats while performing saccades or smooth pursuit. BNs emitted a high-frequency burst of action potentials before and during vertical saccades. On average, these bursts led saccade onset by 14 +/- 4 ms (mean +/- SD, n = 23), and this value was in the range of latencies ( approximately 5-15 ms) of medium-lead burst neurons (MLBNs). All NIC-BNs (n = 15) had a downward preferred direction, whereas riMLF-BNs showed either a downward (n = 3) or an upward (n = 5) preferred direction. We found significant correlations between saccade and burst parameters in all BNs: vertical amplitude was correlated with the number of spikes, maximum vertical velocity with maximum of the spike density, and saccade duration with burst duration. A correlation was also found between instantaneous vertical velocity and neuronal activity during saccades. During fixation, all riMLF-BNs and approximately 50% of NIC-BNs (7/15) were silent. Among NIC-BNs active during fixation (8/15), only two cells had an activity correlated with the eye position in the orbit. During smooth pursuit, most riMLF-BNs were silent (7/8), but all NIC-BNs showed an activity that was significantly correlated with the eye velocity. This activity was unaltered during temporary disappearance of the visual target, demonstrating that it was not visual in origin. For a given neuron, its ON-direction during smooth pursuit and saccades remained identical. The activity of NIC-BNs during both saccades and smooth pursuit can be described by a nonlinear exponential function using the velocity of the eye as independent variable. We suggest that riMLF-BNs, which were not active during smooth pursuit, are vertical MLBNs responsible for the generation of vertical saccades. Because NIC-BNs discharged during both saccades and pursuit, they cannot be regarded as MLBNs as usually defined. NIC-BNs could, however, be the site of convergence of both the saccadic and smooth pursuit signals at the premotoneuronal level. Alternatively, NIC-BNs could participate in the integration of eye velocity to eye position signals and represent input neurons to a common integrator.

The premotor pathways subserving saccades and smooth-pursuit eye movements are usually thought to be different. Indeed, saccade and smooth-pursuit eye movements have different dynamics and functions. In particular, a group of midline cells in the pons called omnipause neurons (OPNs) are considered to be part of the saccadic system only. It has been established that OPNs keep premotor neurons for saccades under constant inhibition during fixation periods. Saccades occur only when the activity of OPNs has completely stopped or paused. Accordingly, electrical stimulation in the region of OPNs inhibits premotor neurons and interrupts saccades. The premotor relay for smooth pursuit is thought to be organized differently and omnipause neurons are not supposed to be involved in smooth-pursuit eye movements. To investigate this supposition, OPNs were recorded during saccades and during smooth pursuit in the monkey (Macaca mulatta). Unexpectedly, we found that neuronal activity of OPNs decreased during smooth pursuit. The resulting activity reduction reached statistical significance in approximately 50% of OPNs recorded during pursuit of a target moving at 40 degrees /s. On average, activity was reduced by 34% but never completely stopped or paused. The onset of activity reduction coincided with the onset of smooth pursuit. The duration of activity reduction was correlated with pursuit duration and its intensity was correlated with eye velocity. Activity reduction was observed even in the absence of catch-up saccades that frequently occur during pursuit. Electrical microstimulation in the OPNs' area induced a strong deceleration of the eye during smooth pursuit. These results suggest that OPNs form an inhibitory mechanism that could control the time course of smooth pursuit. This inhibitory mechanism is part of the fixation system and is probably needed to avoid reflexive eye movements toward targets that are not purposefully selected. This study shows that saccades and smooth pursuit, although they are different kinds of eye movements, are controlled by the same inhibitory system.