Accounting for direction and speed of eye motion in planning visually guided manual tracking

Accurate motor planning in a dynamic environment is a critical skill for humans because we are often required to react quickly and adequately to the visual motion of objects. Moreover, we are often in motion ourselves, and this complicates motor planning. Indeed, the retinal and spatial motions of an object are different because of the retinal motion component induced by self-motion. Many studies have investigated motion perception during smooth pursuit and concluded that eye velocity is partially taken into account by the brain. Here we investigate whether the eye velocity during ongoing smooth pursuit is taken into account for the planning of visually guided manual tracking. We had 10 human participants manually track a target while in steady-state smooth pursuit toward another target such that the difference between the retinal and spatial target motion directions could be large, depending on both the direction and the speed of the eye. We used a measure of initial arm movement direction to quantify whether motor planning occurred in retinal coordinates (not accounting for eye motion) or was spatially correct (incorporating eye velocity). Results showed that the eye velocity was nearly fully taken into account by the neuronal areas involved in the visuomotor velocity transformation (between 75% and 102%). In particular, these neuronal pathways accounted for the nonlinear effects due to the relative velocity between the target and the eye. In conclusion, the brain network transforming visual motion into a motor plan for manual tracking adequately uses extraretinal signals about eye velocity.

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Recasting the Smooth Pursuit Eye Movement System

Journal of Neurophysiology ◽

10.1152/jn.00801.2003 ◽

2004 ◽

Vol 91 (2) ◽

pp. 591-603 ◽

Cited By ~ 285

Author(s):

Richard J. Krauzlis

Keyword(s):

Eye Movements ◽

Brain Stem ◽

Smooth Pursuit ◽

Visual Motion ◽

Saccadic Eye Movements ◽

Extrastriate Cortex ◽

High Acuity ◽

Voluntary Eye Movements ◽

New Perspective ◽

The Brain

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

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Enhancement of Multiple Components of Pursuit Eye Movement by Microstimulation in the Arcuate Frontal Pursuit Area in Monkeys

Journal of Neurophysiology ◽

10.1152/jn.00409.2001 ◽

2002 ◽

Vol 87 (2) ◽

pp. 802-818 ◽

Cited By ~ 61

Author(s):

Masaki Tanaka ◽

Stephen G. Lisberger

Keyword(s):

Eye Movements ◽

Eye Movement ◽

Visual Motion ◽

Gain Control ◽

Target Velocity ◽

Stationary Target ◽

Electrical Microstimulation ◽

Eye Motion ◽

On Line ◽

Eye Velocity

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

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Modeling of Smooth Pursuit-Related Neuronal Responses in the DLPN and NRTP of the Rhesus Macaque

Journal of Neurophysiology ◽

10.1152/jn.00588.2004 ◽

2005 ◽

Vol 93 (1) ◽

pp. 108-116 ◽

Cited By ~ 39

Author(s):

Seiji Ono ◽

Vallabh E. Das ◽

John R. Economides ◽

Michael J. Mustari

Keyword(s):

Smooth Pursuit ◽

Component Model ◽

Pontine Nucleus ◽

Neurophysiological Studies ◽

Eye Motion ◽

Dorsolateral Pontine Nucleus ◽

Velocity Information ◽

Linear Regression Modeling ◽

Component Models ◽

Eye Velocity

The dorsolateral pontine nucleus (DLPN) and nucleus reticularis tegmenti pontis (NRTP) comprise obligatory links in the cortico-ponto-cerebellar system supporting smooth pursuit eye movements. We examined the response properties of DLPN and rNRTP neurons during step-ramp smooth pursuit of a small target moving across a dark background. Our neurophysiological studies were conducted in awake, behaving juvenile macaques ( Macaca mulatta). We used multiple linear-regression modeling to estimate the relative sensitivities of neurons to eye parameters (position, velocity, and acceleration) and retinal-error parameters (position, velocity, and acceleration). We found that a large proportion of pursuit-related DLPN neurons primarily code eye-velocity information, whereas a large proportion of rNRTP neurons primarily code eye-acceleration information. We calculated the relative decrease in variance found when using a six-component model that included both eye- and retinal-error parameters compared with three-component models that include either eye or retinal error. These comparisons show that a majority of DLPN (14/20) and rNRTP (17/19) neurons have larger contributions from eye compared with retinal-error parameters ( P < 0.001, paired t-test). Even though eye-motion parameters provide the strongest contributions in a given model, a significant contribution from retinal error was often present (i.e., >20% reduction in variance in 6-component model compared with 3-component models). Thus our results indicate that the DLPN plays a larger role in maintaining steady-state smooth pursuit eye velocity, whereas rNRTP contributes to both the initiation and maintenance of smooth pursuit.

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

Journal of Neurophysiology ◽

10.1152/jn.00710.2019 ◽

2020 ◽

Vol 123 (3) ◽

pp. 1265-1276 ◽

Cited By ~ 4

Author(s):

Stuart Behling ◽

Stephen G. Lisberger

Keyword(s):

Steady State ◽

Eye Movements ◽

Smooth Pursuit ◽

Visual Motion ◽

Smooth Pursuit Eye Movements ◽

Target Speed ◽

Pursuit Eye Movements ◽

Visual Motor ◽

State Tracking ◽

Eye Velocity

Smooth 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 toward 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 allows us to observe evidence for separate modulations of the gain of visual-motor transmission during pursuit initiation and of the motor corollary discharges that comprise eye velocity memory and support steady-state tracking. NEW & NOTEWORTHY We exploit low-coherence patches of dots to control the initiation and steady state of smooth pursuit eye movements and show that these two phases of movement are modulated separately by the reliability of visual motion signals. We conclude that the neural circuit for pursuit includes separate modulation of the strength of visual-motor transmission for movement initiation and of eye velocity positive feedback to support steady-state tracking.

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Motion dependence of smooth pursuit eye movements in the marmoset

Journal of Neurophysiology ◽

10.1152/jn.00197.2015 ◽

2015 ◽

Vol 113 (10) ◽

pp. 3954-3960 ◽

Cited By ~ 23

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.

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Gravity-dependent estimates of object mass underlie the generation of motor commands for horizontal limb movements

Journal of Neurophysiology ◽

10.1152/jn.00061.2014 ◽

2014 ◽

Vol 112 (2) ◽

pp. 384-392 ◽

Cited By ~ 6

Author(s):

F. Crevecoeur ◽

J. McIntyre ◽

J.-L. Thonnard ◽

P. Lefèvre

Keyword(s):

Grip Force ◽

Mechanical Load ◽

Parabolic Flight ◽

Precision Grip ◽

Motor Planning ◽

Zero Gravity ◽

Visually Guided ◽

Motor Commands ◽

Significant Movement ◽

The Brain

Moving requires handling gravitational and inertial constraints pulling on our body and on the objects that we manipulate. Although previous work emphasized that the brain uses internal models of each type of mechanical load, little is known about their interaction during motor planning and execution. In this report, we examine visually guided reaching movements in the horizontal plane performed by naive participants exposed to changes in gravity during parabolic flight. This approach allowed us to isolate the effect of gravity because the environmental dynamics along the horizontal axis remained unchanged. We show that gravity has a direct effect on movement kinematics, with faster movements observed after transitions from normal gravity to hypergravity (1.8g), followed by significant movement slowing after the transition from hypergravity to zero gravity. We recorded finger forces applied on an object held in precision grip and found that the coupling between grip force and inertial loads displayed a similar effect, with an increase in grip force modulation gain under hypergravity followed by a reduction of modulation gain after entering the zero-gravity environment. We present a computational model to illustrate that these effects are compatible with the hypothesis that participants partially attribute changes in weight to changes in mass and scale incorrectly their motor commands with changes in gravity. These results highlight a rather direct internal mapping between the force generated during stationary holding against gravity and the estimation of inertial loads that limb and hand motor commands must overcome.

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Instantaneous midbrain control of saccade kinematics

10.1101/305003 ◽

2018 ◽

Author(s):

Ivan Smalianchuk ◽

Uday Jagadisan ◽

Neeraj J. Gandhi

Keyword(s):

Spatial Representation ◽

Primary Motor Cortex ◽

Visually Guided ◽

Rate Code ◽

Serial Process ◽

Lower Brain Stem ◽

Eye Velocity ◽

The Brain ◽

Correlative Relationship ◽

Instantaneous Control

AbstractThe ability to interact with our environment requires the brain to transform spatially-represented sensory signals into temporally-encoded motor commands for appropriate control of the relevant effectors. For visually-guided eye movements, or saccades, the superior colliculus (SC) is assumed to be the final stage of spatial representation, and instantaneous control of the movement is achieved through a rate code representation in the lower brain stem. We questioned this dogma and investigated whether SC activity also employs a dynamic rate code, in addition to the spatial representation. Noting that the kinematics of repeated movements exhibits trial-to-trial variability, we regressed instantaneous SC activity with instantaneous eye velocity and found a robust correlation throughout saccade duration. Peak correlation was tightly linked to time of peak velocity, and SC neurons with higher firing rates exhibited stronger correlations. Moreover, the strong correlative relationship was preserved when eye movement profiles were substantially altered by a blink-induced perturbation. These results indicate that the rate code of individual SC neurons can control instantaneous eye velocity, similar to how primary motor cortex controls hand movements, and argue against a serial process for transforming spatially encoded information into a rate code.

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Postsaccadic Enhancement of Initiation of Smooth Pursuit Eye Movements in Monkeys

Journal of Neurophysiology ◽

10.1152/jn.1998.79.4.1918 ◽

1998 ◽

Vol 79 (4) ◽

pp. 1918-1930 ◽

Cited By ~ 63

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.

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Role of Arcuate Frontal Cortex of Monkeys in Smooth Pursuit Eye Movements. II. Relation to Vector Averaging Pursuit

Journal of Neurophysiology ◽

10.1152/jn.2002.87.6.2700 ◽

2002 ◽

Vol 87 (6) ◽

pp. 2700-2714 ◽

Cited By ~ 22

Author(s):

Masaki Tanaka ◽

Stephen G. Lisberger

Keyword(s):

Eye Movements ◽

Smooth Pursuit ◽

Gain Control ◽

Image Motion ◽

Internal Gain ◽

Vector Averaging ◽

A Site ◽

Eye Velocity ◽

The Brain

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

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