Effect of changing feedback delay on spontaneous oscillations in smooth pursuit eye movements of monkeys

1992 ◽  
Vol 67 (3) ◽  
pp. 625-638 ◽  
Author(s):  
D. Goldreich ◽  
R. J. Krauzlis ◽  
S. G. Lisberger
Keyword(s):  
Eye Movements ◽  
Visual Feedback ◽  
Target Motion ◽  
Image Motion ◽  
Target Velocity ◽  
Feedback Delay ◽  
Total Delay ◽  
Internal Feedback ◽  
Pursuit Eye Movements ◽  
Eye Velocity

1. Our goal was to discriminate between two classes of models for pursuit eye movements. The monkey's pursuit system and both classes of model exhibit oscillations around target velocity during tracking of ramp target motion. However, the mechanisms that determine the frequency of oscillations differ in the two classes of model. In "internal feedback" models, oscillations are controlled by internal feedback loops, and the frequency of oscillation does not depend strongly on the delay in visual feedback. In "image motion" models, oscillations are controlled by visual feedback, and the frequency of oscillation does depend on the delay in visual feedback. 2. We measured the frequency of oscillation during pursuit of ramp target motion as a function of the total delay for visual feedback. For the shortest feedback delays of approximately 70 ms, the frequency of oscillation was between 6 and 7 Hz. Increases in feedback delay caused decreases in the frequency of oscillation. The effect of increasing feedback delay was similar, whether the increases were produced naturally by dimming and decreasing the size of the tracking target or artificially with the computer. We conclude that the oscillations in eye velocity during pursuit of ramp target motion are controlled by visual inputs, as suggested by the image motion class of models. 3. Previous experiments had suggested that the visuomotor pathways for pursuit are unable to respond well to frequencies as high as the 6-7 Hz at which eye velocity oscillates in monkeys. We therefore tested the response to target vibration at an amplitude of +/- 8 degrees/s and frequencies as high as 15 Hz. For target vibration at 6 Hz, the gain of pursuit, defined as the amplitude of eye velocity divided by the amplitude of target velocity, was as high as 0.65. We conclude that the visuomotor pathways for pursuit are capable of processing image motion at high temporal frequencies. 4. The gain of pursuit was much larger when the target vibrated around a constant speed of 15 degrees/s than when it vibrated around a stationary position. This suggests that the pursuit pathways contain a switch that must be closed to allow the visuomotor pathways for pursuit to operate at their full gain. The switch apparently remains open for target vibration around a stationary position. 5. The responses to target vibration revealed a frequency at which eye velocity lagged target velocity by 180 degrees and at which one monkey showed a local peak in the gain of pursuit.(ABSTRACT TRUNCATED AT 400 WORDS)

scholarly journals The vestibular-related frontal cortex and its role in smooth-pursuit eye movements and vestibular-pursuit interactions

2006 ◽  
Vol 16 (1-2) ◽  
pp. 1-22 ◽  
Author(s):  
Junko Fukushima ◽  
Teppei Akao ◽  
Sergei Kurkin ◽  
Chris R.S. Kaneko ◽  
Kikuro Fukushima
Keyword(s):  
Eye Movements ◽  
Frontal Cortex ◽  
Smooth Pursuit ◽  
Vestibular Stimulation ◽  
Target Motion ◽  
Head Movements ◽  
Image Motion ◽  
Target Velocity ◽  
Eye Velocity ◽  
Pursuit Neurons

In order to see clearly when a target is moving slowly, primates with high acuity foveae use smooth-pursuit and vergence eye movements. The former rotates both eyes in the same direction to track target motion in frontal planes, while the latter rotates left and right eyes in opposite directions to track target motion in depth. Together, these two systems pursue targets precisely and maintain their images on the foveae of both eyes. During head movements, both systems must interact with the vestibular system to minimize slip of the retinal images. The primate frontal cortex contains two pursuit-related areas; the caudal part of the frontal eye fields (FEF) and supplementary eye fields (SEF). Evoked potential studies have demonstrated vestibular projections to both areas and pursuit neurons in both areas respond to vestibular stimulation. The majority of FEF pursuit neurons code parameters of pursuit such as pursuit and vergence eye velocity, gaze velocity, and retinal image motion for target velocity in frontal and depth planes. Moreover, vestibular inputs contribute to the predictive pursuit responses of FEF neurons. In contrast, the majority of SEF pursuit neurons do not code pursuit metrics and many SEF neurons are reported to be active in more complex tasks. These results suggest that FEF- and SEF-pursuit neurons are involved in different aspects of vestibular-pursuit interactions and that eye velocity coding of SEF pursuit neurons is specialized for the task condition.

Postsaccadic Enhancement of Initiation of Smooth Pursuit Eye Movements in Monkeys

1998 ◽  
Vol 79 (4) ◽  
pp. 1918-1930 ◽  
Author(s):  
Stephen G. Lisberger
Keyword(s):  
Eye Movements ◽  
Smooth Pursuit ◽  
Visual Motion ◽  
Target Position ◽  
Target Motion ◽  
Target Velocity ◽  
Smooth Pursuit Eye Movements ◽  
Motor Pathways ◽  
Pursuit Eye Movements ◽  
Eye Velocity

Lisberger, Stephen G. Postsaccadic enhancement of initiation of smooth pursuit eye movements in monkeys. J. Neurophysiol. 79: 1918–1930, 1998. Step-ramp target motion evokes a characteristic sequence of presaccadic smooth eye movement in the direction of the target ramp, catch-up targets to bring eye position close to the position of the moving target, and postsaccadic eye velocities that nearly match target velocity. I have analyzed this sequence of eye movements in monkeys to reveal a strong postsaccadic enhancement of pursuit eye velocity and to document the conditions that lead to that enhancement. Smooth eye velocity was measured in the last 10 ms before and the first 10 ms after the first saccade evoked by step-ramp target motion. Plots of eye velocity as a function of time after the onset of the target ramp revealed that eye velocity at a given time was much higher if measured after versus before the saccade. Postsaccadic enhancement of pursuit was recorded consistently when the target stepped 3° eccentric on the horizontal axis and moved upward, downward, or away from the position of fixation. To determine whether postsaccadic enhancement of pursuit was invoked by smear of the visual scene during a saccade, I recorded the effect of simulated saccades on the presaccadic eye velocity for step-ramp target motion. The 3° simulated saccade, which consisted of motion of a textured background at 150°/s for 20 ms, failed to cause any enhancement of presaccadic eye velocity. By using a strategically selected set of oblique target steps with horizontal ramp target motion, I found clear enhancement for saccades in all directions, even those that were orthogonal to target motion. When the size of the target step was varied by up to 15° along the horizontal meridian, postsaccadic eye velocity did not depend strongly either on the initial target position or on whether the target moved toward or away from the position of fixation. In contrast, earlier studies and data in this paper show that presaccadic eye velocity is much stronger when the target is close to the center of the visual field and when the target moves toward versus away from the position of fixation. I suggest that postsaccadic enhancement of pursuit reflects activation, by saccades, of a switch that regulates the strength of transmission through the visual-motor pathways for pursuit. Targets can cause strong visual motion signals but still evoke low presaccadic eye velocities if they are ineffective at activating the pursuit system.

scholarly journals Learning on Multiple Timescales in Smooth Pursuit Eye Movements

2010 ◽  
Vol 104 (5) ◽  
pp. 2850-2862 ◽  
Author(s):  
Yan Yang ◽  
Stephen G. Lisberger
Keyword(s):  
Eye Movements ◽  
Target Motion ◽  
Target Velocity ◽  
Single Trial ◽  
Orthogonal Axis ◽  
Pursuit Eye Movements ◽  
Gradual Process ◽  
Eye Velocity ◽  
Consistent Direction

We commonly think of motor learning as a gradual process that makes small, adaptive steps in a consistent direction. We now report evidence that learning in pursuit eye movements could start with large, transient short-term alterations that stoke a more gradual long-term process. Monkeys tracked a target that started moving horizontally or vertically. After 250 ms of motion had produced a preinstruction eye velocity close to target velocity, an orthogonal component of target motion created an instructive change in target direction that was randomly in one of the two directions along the orthogonal axis. The preinstruction eye velocity in each trial expressed single-trial learning as a bias toward the direction of the instruction in the prior trial. The single-trial learning was forgotten within 4 to 10 s. Two observations implied that single-trial learning was not simply cognitive anticipation. First, the magnitude of the trial-over-trial change in eye velocity depended on the ongoing eye velocity at the time of the instruction in the prior trial. Single-trial learning was negligible if the prior trial had provided a well-timed cue without evoking any preinstruction eye velocity. Second, regular alternation of the direction of the instructive target motion caused reactive rather than anticipatory trial-over-trial changes in eye velocity. Humans showed very different responses that appeared to be based on cognitive anticipation rather than learning. We suggest that single-trial learning results from a low-level learning mechanism and may be a necessary prerequisite for longer-term modifications that are more permanent.

Visual tracking in monkeys: evidence for short-latency suppression of the vestibuloocular reflex

1990 ◽  
Vol 63 (4) ◽  
pp. 676-688 ◽  
Author(s):  
S. G. Lisberger
Keyword(s):  
Eye Movements ◽  
Smooth Pursuit ◽  
Initial Conditions ◽  
Short Latency ◽  
Target Motion ◽  
Head Motion ◽  
Target Velocity ◽  
Vestibuloocular Reflex ◽  
Pursuit Eye Movements ◽  
Eye Velocity

1. Monkeys normally use a combination of smooth head and eye movements to keep the eyes pointed at a slowly moving object. The visual inputs from target motion evoke smooth pursuit eye movements, whereas the vestibular inputs from head motion evoke a vestibuloocular reflex (VOR). Our study asks how the eye movements of pursuit and the VOR interact. Is there a linear addition of independent commands for pursuit and the VOR? Or does the interaction of visual and vestibular stimuli cause momentary, "parametric" modulation of transmission through VOR pathways? 2. We probed for the state of the VOR and pursuit by presenting transient perturbations of target and/or head motion under different steady-state tracking conditions. Tracking conditions included fixation at straight-ahead gaze, in which both the head and the target were stationary; "times-zero (X0) tracking," in which the target and head moved in the same direction at the same speed; and "times-two (X2) tracking," in which the target and head moved in opposite directions at the same speed. 3. Comparison of the eye velocities evoked by changes in the direction of X0 versus X2 tracking revealed two components of the tracking response. The earliest component, which we attribute to the VOR, had a latency of 14 ms and a trajectory that did not depend on initial tracking conditions. The later component had a latency of 70 ms or less and a trajectory that did depend on tracking conditions. 4. To probe the latency of pursuit eye movements, we imposed perturbations of target velocity imposed during X0 and X2 tracking. The resulting changes in eye velocity had latencies of at least 100 ms. We conclude that the effects of initial tracking conditions on eye velocity at latencies of less than 70 ms cannot be caused by visual feedback through the smooth-pursuit system. Instead, there must be another mechanism for short-latency control over the VOR; we call this component of the response "short-latency tracking." 5. Perturbations of head velocity or head and target velocity during X0 and X2 tracking showed that short-latency tracking depended only on the tracking conditions at the time the perturbation was imposed. The VOR appeared to be suppressed when the initial conditions were X0 tracking. 6. The magnitude of short-latency tracking depended on the speed of initial head and target movement. During X0 tracking at 15 deg/s, short-latency tracking was modest. When the initial speed of head and target motion was 60 deg/s, the amplitude of short-latency tracking was quite large and its latency became as short as 36 ms.(ABSTRACT TRUNCATED AT 400 WORDS)

scholarly journals Evidence for Object Permanence in the Smooth-Pursuit Eye Movements of Monkeys

2003 ◽  
Vol 90 (4) ◽  
pp. 2205-2218 ◽  
Author(s):  
Mark M. Churchland ◽  
I-Han Chou ◽  
Stephen G. Lisberger
Keyword(s):  
Steady State ◽  
Eye Movements ◽  
Computer Simulations ◽  
Smooth Pursuit ◽  
Constant Velocity ◽  
Object Permanence ◽  
Target Velocity ◽  
Smooth Pursuit Eye Movements ◽  
Pursuit Eye Movements ◽  
Eye Velocity

We recorded the smooth-pursuit eye movements of monkeys in response to targets that were extinguished (blinked) for 200 ms in mid-trajectory. Eye velocity declined considerably during the target blinks, even when the blinks were completely predictable in time and space. Eye velocity declined whether blinks were presented during steady-state pursuit of a constant-velocity target, during initiation of pursuit before target velocity was reached, or during eye accelerations induced by a change in target velocity. When a physical occluder covered the trajectory of the target during blinks, creating the impression that the target moved behind it, the decline in eye velocity was reduced or abolished. If the target was occluded once the eye had reached target velocity, pursuit was only slightly poorer than normal, uninterrupted pursuit. In contrast, if the target was occluded during the initiation of pursuit, while the eye was accelerating toward target velocity, pursuit during occlusion was very different from normal pursuit. Eye velocity remained relatively stable during target occlusion, showing much less acceleration than normal pursuit and much less of a decline than was produced by a target blink. Anticipatory or predictive eye acceleration was typically observed just prior to the reappearance of the target. Computer simulations show that these results are best understood by assuming that a mechanism of eye-velocity memory remains engaged during target occlusion but is disengaged during target blinks.

scholarly journals Temporal dynamics of retinal and extraretinal signals in the FEFsem during smooth pursuit eye movements

2017 ◽  
Vol 117 (5) ◽  
pp. 1987-2003 ◽  
Author(s):  
Leah Bakst ◽  
Jérome Fleuriet ◽  
Michael J. Mustari
Keyword(s):  
Eye Movements ◽  
Smooth Pursuit ◽  
Clustering Algorithm ◽  
Critical Role ◽  
Image Motion ◽  
Frontal Eye Field ◽  
Smooth Pursuit Eye Movements ◽  
Pursuit Eye Movements ◽  
Eye Field ◽  
Eye Velocity

Neurons in the smooth eye movement subregion of the frontal eye field (FEFsem) are known to play an important role in voluntary smooth pursuit eye movements. Underlying this function are projections to parietal and prefrontal visual association areas and subcortical structures, all known to play vital but differing roles in the execution of smooth pursuit. Additionally, the FEFsem has been shown to carry a diverse array of signals (e.g., eye velocity, acceleration, gain control). We hypothesized that distinct subpopulations of FEFsem neurons subserve these diverse functions and projections, and that the relative weights of retinal and extraretinal signals could form the basis for categorization of units. To investigate this, we used a step-ramp tracking task with a target blink to determine the relative contributions of retinal and extraretinal signals in individual FEFsem neurons throughout pursuit. We found that the contributions of retinal and extraretinal signals to neuronal activity and behavior change throughout the time course of pursuit. A clustering algorithm revealed three distinct neuronal subpopulations: cluster 1 was defined by a higher sensitivity to eye velocity, acceleration, and retinal image motion; cluster 2 had greater activity during blinks; and cluster 3 had significantly greater eye position sensitivity. We also performed a comparison with a sample of medial superior temporal neurons to assess similarities and differences between the two areas. Our results indicate the utility of simple tests such as the target blink for parsing the complex and multifaceted roles of cortical areas in behavior. NEW & NOTEWORTHY The frontal eye field (FEF) is known to play a critical role in volitional smooth pursuit, carrying a variety of signals that are distributed throughout the brain. This study used a novel application of a target blink task during step ramp tracking to determine, in combination with a clustering algorithm, the relative contributions of retinal and extraretinal signals to FEF activity and the extent to which these contributions could form the basis for a categorization of neurons.

scholarly journals Motion dependence of smooth pursuit eye movements in the marmoset

2015 ◽  
Vol 113 (10) ◽  
pp. 3954-3960 ◽  
Author(s):  
Jude F. Mitchell ◽  
Nicholas J. Priebe ◽  
Cory T. Miller
Keyword(s):  
Eye Movements ◽  
Smooth Pursuit ◽  
Visual Motion ◽  
Genetic Model ◽  
Mental Disease ◽  
Target Velocity ◽  
Smooth Pursuit Eye Movements ◽  
Pursuit Eye Movements ◽  
Slow Moving ◽  
Eye Velocity

Smooth pursuit eye movements stabilize slow-moving objects on the retina by matching eye velocity with target velocity. Two critical components are required to generate smooth pursuit: first, because it is a voluntary eye movement, the subject must select a target to pursue to engage the tracking system; and second, generating smooth pursuit requires a moving stimulus. We examined whether this behavior also exists in the common marmoset, a New World primate that is increasingly attracting attention as a genetic model for mental disease and systems neuroscience. We measured smooth pursuit in two marmosets, previously trained to perform fixation tasks, using the standard Rashbass step-ramp pursuit paradigm. We first measured the aspects of visual motion that drive pursuit eye movements. Smooth eye movements were in the same direction as target motion, indicating that pursuit was driven by target movement rather than by displacement. Both the open-loop acceleration and closed-loop eye velocity exhibited a linear relationship with target velocity for slow-moving targets, but this relationship declined for higher speeds. We next examined whether marmoset pursuit eye movements depend on an active engagement of the pursuit system by measuring smooth eye movements evoked by small perturbations of motion from fixation or during pursuit. Pursuit eye movements were much larger during pursuit than from fixation, indicating that pursuit is actively gated. Several practical advantages of the marmoset brain, including the accessibility of the middle temporal (MT) area and frontal eye fields at the cortical surface, merit its utilization for studying pursuit movements.

The Influence of Briefly Presented Randomized Target Motion on the Extraretinal Component of Ocular Pursuit

2008 ◽  
Vol 99 (2) ◽  
pp. 831-842 ◽  
Author(s):  
G. R. Barnes ◽  
C. J. S. Collins
Keyword(s):  
Eye Movements ◽  
Intertrial Interval ◽  
Peak Velocity ◽  
Target Motion ◽  
Target Velocity ◽  
Initial Exposure ◽  
Ocular Pursuit ◽  
Dependent Component ◽  
Velocity Information ◽  
Eye Velocity

We assessed the ability to extract velocity information from brief exposure of a moving target and sought evidence that this information could be used to modulate the extraretinal component of ocular pursuit. A step-ramp target motion was initially visible for a brief randomized period of 50, 100, 150, or 200 ms, but then extinguished for a randomized period of 400 or 600 ms before reappearing and continuing along its trajectory. Target speed (5–20°/s), direction (left/right), and intertrial interval (2.7–3.7 s) were also randomized. Smooth eye movements were initiated after about 130 ms and comprised an initial visually dependent component, which reached a peak velocity that increased with target velocity and initial exposure duration, followed by a sustained secondary component that actually increased throughout extinction for 50- and 100-ms initial exposures. End-extinction eye velocity, reflecting extraretinal drive, increased with initial exposure from 50 to 100 ms but remained similar for longer exposures; it was significantly scaled to target velocity for 150- and 200-ms exposures. The results suggest that extraretinal drive is based on a sample of target velocity, mostly acquired during the first 150 ms, that is stored and forms a goal for generating appropriately scaled eye movements during absence of visual input. End-extinction eye velocity was significantly higher when target reappearance was expected than when it was not, confirming the importance of expectation in generating sustained smooth movement. However, end-extinction eye displacement remained similar irrespective of expectation, suggesting that the ability to use sampled velocity information to predict future target displacement operates independently of the control of smooth eye movement.

scholarly journals Role of Arcuate Frontal Cortex of Monkeys in Smooth Pursuit Eye Movements. I. Basic Response Properties to Retinal Image Motion and Position

2002 ◽  
Vol 87 (6) ◽  
pp. 2684-2699 ◽  
Author(s):  
Masaki Tanaka ◽  
Stephen G. Lisberger
Keyword(s):  
Eye Movements ◽  
Smooth Pursuit ◽  
Retinal Image ◽  
Image Motion ◽  
Smooth Pursuit Eye Movements ◽  
Pursuit Eye Movements ◽  
Wide Range ◽  
Image Position ◽  
Eye Velocity ◽  
Pursuit Neurons

Anatomical and physiological studies have shown that the “frontal pursuit area” (FPA) in the arcuate cortex of monkeys is involved in the control of smooth pursuit eye movements. To further analyze the signals carried by the FPA, we examined the activity of pursuit-related neurons recorded from a discrete region near the arcuate spur during a variety of oculomotor tasks. Pursuit neurons showed direction tuning with a wide range of preferred directions and a mean full width at half-maximum of 129°. Analysis of latency using the “receiver operating characteristic” to compare responses to target motion in opposite directions showed that the directional response of 58% of FPA neurons led the initiation of pursuit, while 19% led by 25 ms or more. Analysis of neuronal responses during pursuit of a range of target velocities revealed that the sensitivity to eye velocity was larger during the initiation of pursuit than during the maintenance of pursuit, consistent with two components of firing related to image motion and eye motion. FPA neurons showed correlates of two behavioral features of pursuit documented in prior reports. 1) Eye acceleration at the initiation of pursuit declines as a function of the eccentricity of the moving target. FPA neurons show decreased firing at the initiation of pursuit in parallel with the decline in eye acceleration. This finding is consistent with prior suggestions that the FPA plays a role in modulating the gain of visual-motor transmission for pursuit. 2) A stationary eccentric cue evokes a smooth eye movement opposite in direction to the cue and enhances the pursuit evoked by subsequent target motions. Many pursuit neurons in the FPA showed weak, phasic visual responses for stationary targets and were tuned for the positions about 4° eccentric on the side opposite to the preferred pursuit direction. However, few neurons (12%) responded during the preparation or execution of saccades. The responses to the stationary target could account for the behavioral effects of stationary, eccentric cues. Further analysis of the relationship between firing rate and retinal position error during pursuit in the preferred and opposite directions failed to provide evidence for a large contribution of image position to the firing of FPA neurons. We conclude that FPA processes information in terms of image and eye velocity and that it is functionally separate from the saccadic frontal eye fields, which processes information in terms of retinal image position.

scholarly journals Task-Dependent Modulation of the Sensorimotor Transformation for Smooth Pursuit Eye Movements

2000 ◽  
Vol 84 (6) ◽  
pp. 2725-2738 ◽  
Author(s):  
Vincent P. Ferrera
Keyword(s):  
Eye Movements ◽  
Smooth Pursuit ◽  
Competitive Inhibition ◽  
Substantial Effect ◽  
Image Motion ◽  
Target Color ◽  
Pursuit Eye Movements ◽  
Winner Take All ◽  
Eye Velocity ◽  
Take All

To investigate the transformation of retinal image velocity into smooth pursuit eye velocity, eye movements were measured in the presence of two moving targets. In the first experiment, the targets were identical in all respects except for direction of motion, and the monkey was not cued to attend to either target. In this experiment, smooth pursuit eye velocity elicited by two targets was the vector average of the response evoked by each target alone. In subsequent experiments, we examined the effects of stimulus and task parameters on the selectivity of pursuit. When the targets were made different colors and monkeys were cued for the color of the rewarded target, their pursuit eye movements were biased in the direction of the rewarded target, but still showed a substantial influence of the nonrewarded target (distractor). It did not matter whether the same target color was used for an entire session or whether the color was randomized from trial to trial. Reducing uncertainty about the axis of motion of the rewarded target also had little effect. However, the pattern of image motion appeared to have a substantial effect; radial image motion favored averaging, and winner-take-all pursuit was found only with nonradial image motion. We conclude that the sensorimotor interface for pursuit uses a flexible decision rule that can vary continuously from vector averaging to winner-take-all. We present a simple recurrent network model that reflects this range of behavior. The model has allowed us to identify three computational elements (selection bias, competitive inhibition, and response normalization) that should be taken into consideration in future models of smooth pursuit.

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