scholarly journals Eye-position error influence over “open-loop” smooth pursuit initiation

2018 ◽  
Author(s):  
Antimo Buonocore ◽  
Julianne Skinner ◽  
Ziad M. Hafed
Keyword(s):  
Eye Movements ◽  
Smooth Pursuit ◽  
Open Loop ◽  
Position Error ◽  
Visual Signals ◽  
Error Signal ◽  
Movement Initiation ◽  
Pursuit Eye Movements ◽  
Pursuit Initiation ◽  
Catch Up

AbstractThe oculomotor system integrates a variety of visual signals into appropriate motor plans, but such integration can have widely varying time scales. For example, smooth pursuit eye movements to follow a moving target are slower and longer-lasting than saccadic eye movements, and it has been suggested that initiating a smooth pursuit eye movement involves an obligatory open-loop interval, in which new visual motion signals presumably cannot influence the ensuing motor plan for up to 100 ms after movement initiation. However, this view runs directly contrary to the idea that the oculomotor periphery has privileged access to short-latency visual signals. Here we show that smooth pursuit initiation is sensitive to visual inputs, even in “open-loop” intervals. We instructed male rhesus macaque monkeys to initiate saccade-free smooth pursuit eye movements, and we injected a transient, instantaneous eye position error signal at different times relative to movement initiation. We found robust short-latency modulations in eye velocity and acceleration, starting only ∼50 ms after transient signal occurrence, and even during “open-loop” pursuit initiation. Critically, the spatial direction of the injected position error signal had predictable effects on smooth pursuit initiation, with forward errors increasing eye acceleration and backwards errors reducing it. Catch-up saccade frequencies and amplitudes were also similarly altered ∼50 ms after transient signals, much like well-known effects on microsaccades during fixation. Our results demonstrate that smooth pursuit initiation is highly sensitive to visual signals, and that catch-up saccade generation is reset after a visual transient.

scholarly journals Role of Primate Cerebellar Hemisphere in Voluntary Eye Movement Control Revealed by Lesion Effects

2009 ◽  
Vol 101 (2) ◽  
pp. 934-947 ◽  
Author(s):  
Masafumi Ohki ◽  
Hiromasa Kitazawa ◽  
Takahito Hiramatsu ◽  
Kimitake Kaga ◽  
Taiko Kitamura ◽  
...  
Keyword(s):  
Eye Movements ◽  
Eye Movement ◽  
Smooth Pursuit ◽  
Movement Control ◽  
Cerebellar Hemisphere ◽  
Target Velocity ◽  
Eye Movement Control ◽  
Pursuit Eye Movements ◽  
Catch Up

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.

Predicting 2D Target Velocity Cannot Help 2D Motion Integration for Smooth Pursuit Initiation

2006 ◽  
Vol 96 (6) ◽  
pp. 3545-3550 ◽  
Author(s):  
Anna Montagnini ◽  
Miriam Spering ◽  
Guillaume S. Masson
Keyword(s):  
Eye Movements ◽  
Smooth Pursuit ◽  
Object Motion ◽  
Line Orientation ◽  
Motion Direction ◽  
Direction Error ◽  
Pursuit Eye Movements ◽  
Pursuit Initiation ◽  
Motion Integration ◽  
Tracking Direction

Smooth pursuit eye movements reflect the temporal dynamics of bidimensional (2D) visual motion integration. When tracking a single, tilted line, initial pursuit direction is biased toward unidimensional (1D) edge motion signals, which are orthogonal to the line orientation. Over 200 ms, tracking direction is slowly corrected to finally match the 2D object motion during steady-state pursuit. We now show that repetition of line orientation and/or motion direction does not eliminate the transient tracking direction error nor change the time course of pursuit correction. Nonetheless, multiple successive presentations of a single orientation/direction condition elicit robust anticipatory pursuit eye movements that always go in the 2D object motion direction not the 1D edge motion direction. These results demonstrate that predictive signals about target motion cannot be used for an efficient integration of ambiguous velocity signals at pursuit initiation.

A Control Systems Model of Smooth Pursuit Eye Movements with Realistic Emergent Properties

1989 ◽  
Vol 1 (1) ◽  
pp. 116-122 ◽  
Author(s):  
R. J. Krauzlis ◽  
S. G. Lisberger
Keyword(s):  
Eye Movements ◽  
Visual Tracking ◽  
Smooth Pursuit ◽  
Oculomotor System ◽  
Difficult Problem ◽  
Visual Signals ◽  
Emergent Properties ◽  
Smooth Pursuit Eye Movements ◽  
Pursuit Eye Movements ◽  
Systems Model

Visual tracking of objects in a noisy environment is a difficult problem that has been solved by the primate oculomotor system, but remains unsolved in robotics. In primates, smooth pursuit eye movements match eye motion to target motion to keep the eye pointed at smoothly moving targets. We have used computer models as a tool to investigate possible computational strategies underlying this behavior. Here, we present a model based upon behavioral data from monkeys. The model emphasizes the variety of visual signals available for pursuit and, in particular, includes a sensitivity to the acceleration of retinal images. The model was designed to replicate the initial eye velocity response observed during pursuit of different target motions. The strength of the model is that it also exhibits a number of emergent properties that are seen in the behavior of both humans and monkeys. This suggests that the elements in the model capture important aspects of the mechanism of visual tracking by the primate smooth pursuit system.

scholarly journals Functional specialization in the middle temporal area for smooth pursuit initiation

2019 ◽  
Vol 2 ◽  
pp. 6 ◽  
Author(s):  
Shahab Bakhtiari ◽  
Christopher C. Pack
Keyword(s):  
Eye Movements ◽  
Smooth Pursuit ◽  
Sensory Information ◽  
Target Velocity ◽  
Multiple Sources ◽  
Temporal Area ◽  
Middle Temporal ◽  
Mt Neurons ◽  
Pursuit Eye Movements ◽  
Pursuit Initiation

Smooth pursuit eye movements have frequently been used to model sensorimotor transformations in the brain. In particular, the initiation phase of pursuit can be understood as a transformation of a sensory estimate of target velocity into an eye rotation. Despite careful laboratory controls on the stimulus conditions, pursuit eye movements are frequently observed to exhibit considerable trial-to-trial variability. In theory, this variability can be caused by the variability in sensory representation of target motion, or by the variability in the transformation of sensory information to motor commands. Previous work has shown that neural variability in the middle temporal (MT) area is likely propagated to the oculomotor command, and there is evidence to suggest that the magnitude of this variability is sufficient to account for the variability of pursuit initiation. This line of reasoning presumes that the MT population is homogeneous with respect to its contribution to pursuit initiation.  At the same time, there is evidence that pursuit initiation is strongly linked to a subpopulation of MT neurons (those with strong surround suppression) that collectively generate less motor variability. To distinguish between these possibilities, we have combined human psychophysics, monkey electrophysiology, and computational modeling to examine how the pursuit system reads out the MT population during pursuit initiation. We find that the psychophysical data are best accounted for by a model that gives stronger weight to surround-suppressed MT neurons, suggesting that variability in the initiation of pursuit could arise from multiple sources along the sensorimotor transformation.

Discharge Properties of Neurons in the Rostral Superior Colliculus of the Monkey During Smooth-Pursuit Eye Movements

2000 ◽  
Vol 84 (2) ◽  
pp. 876-891 ◽  
Author(s):  
Richard J. Krauzlis ◽  
Michele A. Basso ◽  
Robert H. Wurtz
Keyword(s):  
Eye Movements ◽  
Superior Colliculus ◽  
Smooth Pursuit ◽  
Discharge Rate ◽  
Motor Command ◽  
Contralateral Side ◽  
Position Error ◽  
Related Activity ◽  
Tuning Curves ◽  
Pursuit Eye Movements

The intermediate and deep layers of the monkey superior colliculus (SC) comprise a retinotopically organized map for eye movements. The rostral end of this map, corresponding to the representation of the fovea, contains neurons that have been referred to as “fixation cells” because they discharge tonically during active fixation and pause during the generation of most saccades. These neurons also possess movement fields and are most active for targets close to the fixation point. Because the parafoveal locations encoded by these neurons are also important for guiding pursuit eye movements, we studied these neurons in two monkeys as they generated smooth pursuit. We found that fixation cells exhibit the same directional preferences during pursuit as during small saccades—they increase their discharge during movements toward the contralateral side and decrease their discharge during movements toward the ipsilateral side. This pursuit-related activity could be observed during saccade-free pursuit and was not predictive of small saccades that often accompanied pursuit. When we plotted the discharge rate from individual neurons during pursuit as a function of the position error associated with the moving target, we found tuning curves with peaks within a few degrees contralateral of the fovea. We compared these pursuit-related tuning curves from each neuron to the tuning curves for a saccade task from which we separately measured the visual, delay, and peri-saccadic activity. We found the highest and most consistent correlation with the delay activity recorded while the monkey viewed parafoveal stimuli during fixation. The directional preferences exhibited during pursuit can therefore be attributed to the tuning of these neurons for contralateral locations near the fovea. These results support the idea that fixation cells are the rostral extension of the buildup neurons found in the more caudal colliculus and that their activity conveys information about the size of the mismatch between a parafoveal stimulus and the currently foveated location. Because the generation of pursuit requires a break from fixation, the pursuit-related activity indicates that these neurons are not strictly involved with maintaining fixation. Conversely, because activity during the delay period was found for many neurons even when no eye movement was made, these neurons are also not obligatorily related to the generation of a movement. Thus the tonic activity of these rostral neurons provides a potential position-error signal rather than a motor command—a principle that may be applicable to buildup neurons elsewhere in the SC.

scholarly journals Different mechanisms for modulation of the initiation and steady-state of smooth pursuit eye movements

2019 ◽  
Author(s):  
Stuart Behling ◽  
Stephen G. Lisberger
Keyword(s):  
Steady State ◽  
Eye Movements ◽  
Smooth Pursuit ◽  
Smooth Pursuit Eye Movements ◽  
Target Speed ◽  
Pursuit Eye Movements ◽  
Pursuit Initiation ◽  
Visual Motor ◽  
State Tracking ◽  
Eye Velocity

AbstractSmooth pursuit eye movements are used by primates to track moving objects. They are initiated by sensory estimates of target speed represented in the middle temporal (MT) area of extrastriate visual cortex and then supported by motor feedback to maintain steady-state eye speed at target speed. Here, we show that reducing the coherence in a patch of dots for a tracking target degrades the eye speed both at the initiation of pursuit and during steady-state tracking, when eye speed reaches an asymptote well below target speed. The deficits are quantitatively different between the motor-supported steady-state of pursuit and the sensory-driven initiation of pursuit, suggesting separate mechanisms. The deficit in visually-guided pursuit initiation could not explain the deficit in steady-state tracking. Pulses of target speed during steady-state tracking revealed lower sensitivities to image motion across the retina for lower values of dot coherence. However, sensitivity was not zero, implying that visual motion should still be driving eye velocity towards target velocity. When we changed dot coherence from 100% to lower values during accurate steady-state pursuit, we observed larger eye decelerations for lower coherences, as expected if motor feedback was reduced in gain. A simple pursuit model accounts for our data based on separate modulation of the strength of visual-motor transmission and motor feedback. We suggest that reduced dot coherence creates less reliable target motion that impacts pursuit initiation by changing the gain of visual-motor transmission and perturbs steady-state tracking by modulation of the motor corollary discharges that comprise eye velocity memory.

Smooth Pursuit Eye Movements to Isoluminant Targets

2008 ◽  
Vol 100 (3) ◽  
pp. 1287-1300 ◽  
Author(s):  
D. I. Braun ◽  
N. Mennie ◽  
C. Rasche ◽  
A. C. Schütz ◽  
M. J. Hawken ◽  
...  
Keyword(s):  
Eye Movements ◽  
Smooth Pursuit ◽  
Small Difference ◽  
Luminance Contrast ◽  
Sine Wave ◽  
Smooth Pursuit Eye Movements ◽  
Pursuit Eye Movements ◽  
Pursuit Initiation ◽  
All Speeds ◽  
Sine Wave Gratings

At slow speeds, chromatic isoluminant stimuli are perceived to move much slower than comparable luminance stimuli. We investigated whether smooth pursuit eye movements to isoluminant stimuli show an analogous slowing. Beside pursuit speed and latency, we studied speed judgments to the same stimuli during fixation and pursuit. Stimuli were either large sine wave gratings or small Gaussians blobs moving horizontally at speeds between 1 and 11°/s. Targets were defined by luminance contrast or color. Confirming prior studies, we found that speed judgments of isoluminant stimuli during fixation showed a substantial slowing when compared with luminance stimuli. A similarly strong and significant effect of isoluminance was found for pursuit initiation: compared with luminance targets of matched contrasts, latencies of pursuit initiation were delayed by 50 ms at all speeds and eye accelerations were reduced for isoluminant targets. A small difference was found between steady-state eye velocities of luminance and isoluminant targets. For comparison, we measured latencies of saccades to luminance and isoluminant stimuli under similar conditions, but the effect of isoluminance was only found for pursuit. Parallel psychophysical experiments revealed that different from speed judgments of moving isoluminant stimuli made during fixation, judgments during pursuit are veridical for the same stimuli at all speeds. Therefore information about target speed seems to be available for pursuit eye movements and speed judgments during pursuit but is degraded for perceptual speed judgments during fixation and for pursuit initiation.

Experimental and Computational Analysis of Monkey Smooth Pursuit Eye Movements

2001 ◽  
Vol 86 (2) ◽  
pp. 741-759 ◽  
Author(s):  
Mark M. Churchland ◽  
Stephen G. Lisberger
Keyword(s):  
Eye Movements ◽  
Smooth Pursuit ◽  
Sine Wave ◽  
Visual Signals ◽  
Image Motion ◽  
Motion Model ◽  
Image Velocity ◽  
Pursuit Eye Movements ◽  
Feedback Model ◽  
Baseline Image

Smooth pursuit eye movements are guided by visual feedback and are surprisingly accurate despite the time delay between visual input and motor output. Previous models have reproduced the accuracy of pursuit either by using elaborate visual signals or by adding sources of motor feedback. Our goal was to constrain what types of signals drive pursuit by obtaining data that would discriminate between these two modeling approaches, represented by the “image motion model” and the “tachometer feedback” model. Our first set of experiments probed the visual properties of pursuit with brief square-pulse and sine-wave perturbations of target velocity. Responses to pulse perturbations increased almost linearly with pulse amplitude, while responses to sine wave perturbations showed strong saturation with increasing stimulus amplitude. The response to sine wave perturbations was strongly dependent on the baseline image velocity at the time of the perturbation. Responses were much smaller if baseline image velocity was naturally large, or was artificially increased by superimposing sine waves on pulse perturbations. The image motion model, but not the tachometer feedback model, could reproduce these features of pursuit. We used a revision of the image motion model that was, like the original, sensitive to both image velocity and image acceleration. Due to a saturating nonlinearity, the sensitivity to image acceleration declined with increasing image velocity. Inclusion of this nonlinearity was motivated by our experimental results, was critical in accounting for the responses to perturbations, and provided an explanation for the unexpected stability of pursuit in the presence of perturbations near the resonant frequency. As an emergent property, the revised image motion model was able to reproduce the frequency and damping of oscillations recorded during artificial feedback delays. Our second set of experiments replicated prior recordings of pursuit responses to multiple-cycle sine wave perturbations, presented over a range of frequencies. The image motion model was able to reproduce the responses to sine wave perturbations across all frequencies, while the tachometer feedback model failed at high frequencies. These failures resulted from the absence of image acceleration signals in the tachometer model. We conclude that visual signals related to image acceleration are important in driving pursuit eye movements and that the nonlinearity of these signals provides stability. Smooth pursuit thus illustrates that a plausible neural strategy for combating natural delays in sensory feedback is to employ information about the derivative of the sensory input.

scholarly journals Activation and Inactivation of Rostral Superior Colliculus Neurons During Smooth-Pursuit Eye Movements in Monkeys

2000 ◽  
Vol 84 (2) ◽  
pp. 892-908 ◽  
Author(s):  
Michele A. Basso ◽  
Richard J. Krauzlis ◽  
Robert H. Wurtz
Keyword(s):  
Eye Movements ◽  
Superior Colliculus ◽  
Smooth Pursuit ◽  
Superficial Layer ◽  
Smooth Pursuit Eye Movements ◽  
Pursuit Eye Movements ◽  
Pursuit Initiation ◽  
Intermediate Layers ◽  
Deep Layers ◽  
Stimulation Of

Neurons in the intermediate and deep layers of the rostral superior colliculus (SC) of monkeys are active during attentive fixation, small saccades, and smooth-pursuit eye movements. Alterations of SC activity have been shown to alter saccades and fixation, but similar manipulations have not been shown to influence smooth-pursuit eye movements. Therefore we both activated (electrical stimulation) and inactivated (reversible chemical injection) rostral SC neurons to establish a causal role for the activity of these neurons in smooth pursuit. First, we stimulated the rostral SC during pursuit initiation as well as pursuit maintenance. For pursuit initiation, stimulation of the rostral SC suppressed pursuit to ipsiversive moving targets primarily and had modest effects on contraversive pursuit. The effect of stimulation on pursuit varied with the location of the stimulation with the most rostral sites producing the most effective inhibition of ipsiversive pursuit. Stimulation was more effective on higher pursuit speeds than on lower and did not evoke smooth-pursuit eye movements during fixation. As with the effects on pursuit initiation, ipsiversive maintained pursuit was suppressed, whereas contraversive pursuit was less affected. The stimulation effect on smooth pursuit did not result from a generalized inhibition because the suppression of smooth pursuit was greater than the suppression of smooth eye movements evoked by head rotations (vestibular-ocular reflex). Nor was the stimulation effect due to the activation of superficial layer visual neurons rather than the intermediate layers of the SC because stimulation of the superficial layers produced effects opposite to those found with intermediate layer stimulation. Second, we inactivated the rostral SC with muscimol and found that contraversive pursuit initiation was reduced and ipsiversive pursuit was increased slightly, changes that were opposite to those resulting from stimulation. The results of both the stimulation and the muscimol injection experiments on pursuit are consistent with the effects of these activation and inactivation experiments on saccades, and the effects on pursuit are consistent with the hypothesis that the SC provides a position signal that is used by the smooth-pursuit eye-movement system.

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