scholarly journals The influence of stimulus and behavioral histories on predictive control of smooth pursuit eye movements

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Takeshi Miyamoto ◽  
Yutaka Hirata ◽  
Akira Katoh ◽  
Kenichiro Miura ◽  
Seiji Ono

AbstractThe smooth pursuit system has the ability to perform predictive feedforward control of eye movements. This study attempted to examine how stimulus and behavioral histories of past trials affect the control of predictive pursuit of target motion with randomized velocities. We used sequential ramp stimuli where the rightward velocity was fixed at 16 deg/s while the leftward velocity was either fixed (predictable) at one of seven velocities (4, 8, 12, 16, 20, 24, or 28 deg/s) or randomized (unpredictable). As a result, predictive pursuit responses were observed not only in the predictable condition but also in the unpredictable condition. Linear mixed-effects (LME) models showed that both stimulus and behavioral histories of the previous two or three trials influenced the predictive pursuit responses in the unpredictable condition. Intriguingly, the goodness of fit of the LME model was improved when both historical effects were fitted simultaneously rather than when each type of historical data was fitted alone. Our results suggest that predictive pursuit systems allow us to track randomized target motion using weighted averaging of the information of target velocity (stimulus) and motor output (behavior) in past time sequences.

2021 ◽  
Author(s):  
Takeshi Miyamoto ◽  
Yutaka Hirata ◽  
Akira Katoh ◽  
Kenichiro Miura ◽  
Seiji Ono

The pursuit system has the ability to perform predictive control of eye movements. Even when the target motion is unpredictable due to velocity or direction changes, preceding changes in eye velocity are generated based on weighted averaging of past stimulus timing. However, it is still uncertain whether behavioral history influences the control of predictive pursuit. Thus, we attempted to clarify the influences of stimulus and behavioral histories on predictive pursuit to randomized target velocity. We used alternating-ramp stimuli, where the rightward velocity was fixed while the leftward velocity was either fixed (predictable) or randomized (unpredictable). Predictive eye deceleration was observed regardless of whether the target velocity was predictable or not. In particular, the predictable condition showed that the predictive pursuit responses corresponded to future target velocity. The linear mixed-effects model showed that both stimulus and behavioral histories of the previous two or three trials had influences on the predictive pursuit responses to the unpredictable target velocity. Our results suggest that the predictive pursuit system allows to track randomized target motion using the information from previous several trials, and the information of sensory input (stimulus) and motor output (behavior) in the past time sequences have partially different influences on predictive pursuit.


2006 ◽  
Vol 16 (1-2) ◽  
pp. 1-22 ◽  
Author(s):  
Junko Fukushima ◽  
Teppei Akao ◽  
Sergei Kurkin ◽  
Chris R.S. Kaneko ◽  
Kikuro Fukushima

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.


1998 ◽  
Vol 79 (4) ◽  
pp. 1918-1930 ◽  
Author(s):  
Stephen G. Lisberger

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.


2001 ◽  
Vol 86 (2) ◽  
pp. 550-558 ◽  
Author(s):  
Sophie de Brouwer ◽  
Marcus Missal ◽  
Philippe Lefèvre

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 ∼3 Hz around a steady-state value. The average gain of smooth pursuit was ∼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.


1987 ◽  
Vol 57 (5) ◽  
pp. 1446-1463 ◽  
Author(s):  
J. R. Carl ◽  
R. S. Gellman

We studied pursuit eye movements in seven normal human subjects with the scleral search-coil technique. The initial eye movements in response to unpredictable changes in target motion were analyzed to determine the effect of target velocity and position on the latency and acceleration of the response. By restricting our analysis to the presaccadic portion of the response we were able to eliminate any saccadic interactions, and the randomized stimulus presentation minimized anticipatory responses. This approach has allowed us to characterize a part of the smooth-pursuit system that is dependent primarily on retinal image properties. The latency of the smooth-pursuit response was very consistent, with a mean of 100 +/- 5 ms to targets moving 5 degrees/s or faster. The responses were the same whether the velocity step was presented when the target was initially stationary or after tracking was established. The latency did increase for lower velocity targets; this increase was well described by a latency model requiring a minimum target movement of 0.028 degrees, in addition to a fixed processing time of 98 ms. The presaccadic accelerations were fairly low, and increased with target velocity until an acceleration of about 50 degrees/s2 was reached for target velocities of 10 degrees/s. Higher velocities produced only a slight increase in eye acceleration. When the target motion was adjusted so that the retinal image slip occurred at increasing distances from the fovea, the accelerations declined until no presaccadic response was measurable when the image slip started 15 degrees from the fovea. The smooth-pursuit response to a step of target position was a brief acceleration; this response occurred even when an oppositely directed velocity stimulus was present. The latency of the pursuit response to such a step was also approximately 100 ms. This result seems consistent with the idea that sensory pathways act as a low-pass spatiotemporal filter of the retinal input, effectively converting position steps into briefly moving stimuli. There was a large asymmetry in the responses to position steps: the accelerations were much greater when the position step of the target was away from the direction of tracking, compared with steps in the direction of tracking. The asymmetry may be due to the addition of a fixed slowing of the eyes whenever the target image disappears from the foveal region. When saccades were delayed by step-ramp stimuli, eye accelerations increased markedly approximately 200 ms after stimulus onset.(ABSTRACT TRUNCATED AT 400 WORDS)


1990 ◽  
Vol 63 (4) ◽  
pp. 676-688 ◽  
Author(s):  
S. G. Lisberger

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)


2009 ◽  
Vol 101 (2) ◽  
pp. 934-947 ◽  
Author(s):  
Masafumi Ohki ◽  
Hiromasa Kitazawa ◽  
Takahito Hiramatsu ◽  
Kimitake Kaga ◽  
Taiko Kitamura ◽  
...  

The anatomical connection between the frontal eye field and the cerebellar hemispheric lobule VII (H-VII) suggests a potential role of the hemisphere in voluntary eye movement control. To reveal the involvement of the hemisphere in smooth pursuit and saccade control, we made a unilateral lesion around H-VII and examined its effects in three Macaca fuscata that were trained to pursue visually a small target. To the step (3°)-ramp (5–20°/s) target motion, the monkeys usually showed an initial pursuit eye movement at a latency of 80–140 ms and a small catch-up saccade at 140–220 ms that was followed by a postsaccadic pursuit eye movement that roughly matched the ramp target velocity. After unilateral cerebellar hemispheric lesioning, the initial pursuit eye movements were impaired, and the velocities of the postsaccadic pursuit eye movements decreased. The onsets of 5° visually guided saccades to the stationary target were delayed, and their amplitudes showed a tendency of increased trial-to-trial variability but never became hypo- or hypermetric. Similar tendencies were observed in the onsets and amplitudes of catch-up saccades. The adaptation of open-loop smooth pursuit velocity, tested by a step increase in target velocity for a brief period, was impaired. These lesion effects were recognized in all directions, particularly in the ipsiversive direction. A recovery was observed at 4 wk postlesion for some of these lesion effects. These results suggest that the cerebellar hemispheric region around lobule VII is involved in the control of smooth pursuit and saccadic eye movements.


2009 ◽  
Vol 102 (4) ◽  
pp. 2013-2025 ◽  
Author(s):  
Leslie C. Osborne ◽  
Stephen G. Lisberger

To probe how the brain integrates visual motion signals to guide behavior, we analyzed the smooth pursuit eye movements evoked by target motion with a stochastic component. When each dot of a texture executed an independent random walk such that speed or direction varied across the spatial extent of the target, pursuit variance increased as a function of the variance of visual pattern motion. Noise in either target direction or speed increased the variance of both eye speed and direction, implying a common neural noise source for estimating target speed and direction. Spatial averaging was inefficient for targets with >20 dots. Together these data suggest that pursuit performance is limited by the properties of spatial averaging across a noisy population of sensory neurons rather than across the physical stimulus. When targets executed a spatially uniform random walk in time around a central direction of motion, an optimized linear filter that describes the transformation of target motion into eye motion accounted for ∼50% of the variance in pursuit. Filters had widths of ∼25 ms, much longer than the impulse response of the eye, and filter shape depended on both the range and correlation time of motion signals, suggesting that filters were products of sensory processing. By quantifying the effects of different levels of stimulus noise on pursuit, we have provided rigorous constraints for understanding sensory population decoding. We have shown how temporal and spatial integration of sensory signals converts noisy population responses into precise motor responses.


2013 ◽  
Vol 110 (3) ◽  
pp. 732-747 ◽  
Author(s):  
T. Scott Murdison ◽  
Chanel A. Paré-Bingley ◽  
Gunnar Blohm

To compute spatially correct smooth pursuit eye movements, the brain uses both retinal motion and extraretinal signals about the eyes and head in space ( Blohm and Lefèvre 2010 ). However, when smooth eye movements rely solely on memorized target velocity, such as during anticipatory pursuit, it is unknown if this velocity memory also accounts for extraretinal information, such as head roll and ocular torsion. To answer this question, we used a novel behavioral updating paradigm in which participants pursued a repetitive, spatially constant fixation-gap-ramp stimulus in series of five trials. During the first four trials, participants' heads were rolled toward one shoulder, inducing ocular counterroll (OCR). With each repetition, participants increased their anticipatory pursuit gain, indicating a robust encoding of velocity memory. On the fifth trial, they rolled their heads to the opposite shoulder before pursuit, also inducing changes in ocular torsion. Consequently, for spatially accurate anticipatory pursuit, the velocity memory had to be updated across changes in head roll and ocular torsion. We tested how the velocity memory accounted for head roll and OCR by observing the effects of changes to these signals on anticipatory trajectories of the memory decoding (fifth) trials. We found that anticipatory pursuit was updated for changes in head roll; however, we observed no evidence of compensation for OCR, representing the absence of ocular torsion signals within the velocity memory. This indicated that the directional component of the memory must be coded retinally and updated to account for changes in head roll, but not OCR.


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