Recasting the Smooth Pursuit Eye Movement System

2004 ◽  
Vol 91 (2) ◽  
pp. 591-603 ◽  
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.

The Brain Stem Saccadic Burst Generator Encodes Gaze in Three-Dimensional Space

2008 ◽  
Vol 99 (5) ◽  
pp. 2602-2616 ◽  
Author(s):  
Marion R. Van Horn ◽  
Pierre A. Sylvestre ◽  
Kathleen E. Cullen
Keyword(s):  
Eye Movements ◽  
Brain Stem ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Saccadic Eye Movements ◽  
Three Dimensions ◽  
Related Information ◽  
Computer Based ◽  
Different Depths ◽  
The Brain

When we look between objects located at different depths the horizontal movement of each eye is different from that of the other, yet temporally synchronized. Traditionally, a vergence-specific neuronal subsystem, independent from other oculomotor subsystems, has been thought to generate all eye movements in depth. However, recent studies have challenged this view by unmasking interactions between vergence and saccadic eye movements during disconjugate saccades. Here, we combined experimental and modeling approaches to address whether the premotor command to generate disconjugate saccades originates exclusively in “vergence centers.” We found that the brain stem burst generator, which is commonly assumed to drive only the conjugate component of eye movements, carries substantial vergence-related information during disconjugate saccades. Notably, facilitated vergence velocities during disconjugate saccades were synchronized with the burst onset of excitatory and inhibitory brain stem saccadic burst neurons (SBNs). Furthermore, the time-varying discharge properties of the majority of SBNs (>70%) preferentially encoded the dynamics of an individual eye during disconjugate saccades. When these experimental results were implemented into a computer-based simulation, to further evaluate the contribution of the saccadic burst generator in generating disconjugate saccades, we found that it carries all the vergence drive that is necessary to shape the activity of the abducens motoneurons to which it projects. Taken together, our results provide evidence that the premotor commands from the brain stem saccadic circuitry, to the target motoneurons, are sufficient to ensure the accurate control shifts of gaze in three dimensions.

Discharge Properties of Monkey Tectoreticular Neurons

2006 ◽  
Vol 95 (6) ◽  
pp. 3502-3511 ◽  
Author(s):  
C. Kip Rodgers ◽  
Douglas P. Munoz ◽  
Stephen H. Scott ◽  
Martin Paré
Keyword(s):  
Eye Movements ◽  
Brain Stem ◽  
Visual Information ◽  
Saccadic Eye Movements ◽  
Evoked Responses ◽  
Tonic Activity ◽  
Temporal Code ◽  
Intermediate Layers ◽  
Saccade Control ◽  
The Brain

The intermediate layers of the superior colliculus (SC) contain neurons that clearly play a major role in regulating the production of saccadic eye movements: a burst of activity from saccade neurons (SNs) is thought to provide a drive signal to set the eyes in motion, whereas the tonic activity of fixation neurons (FNs) is thought to suppress saccades during fixation. The exact contribution of these neurons to saccade control is, however, unclear because the nature of the signals sent by the SC to the brain stem saccade generation circuit has not been studied in detail. Here we tested the hypothesis that the SC output signal is sufficient to control saccades by examining whether antidromically identified tectoreticular neurons (TRNs: 33 SNs and 13 FNs) determine the end of saccades. First, TRNs had discharge properties similar to those of nonidentified SC neurons and a proportion of output SNs had visually evoked responses, which signify that the saccade generator must receive and process visual information. Second, only a minority of TRNs possessed the temporal patterns of activity sufficient to terminate saccades: Output SNs did not cease discharging at the time of saccade end, possibly continuing to drive the brain stem during postsaccadic fixations, and output FNs did not resume their activity before saccade end. These results argue against a role for SC in regulating the timing of saccade termination by a temporal code and suggest that other saccade centers act to thwart the extraneous SC drive signal, unless it controls saccade termination by a spatial code.

Overlap of Saccadic and Pursuit Eye Movement Systems in the Brain Stem Reticular Formation

2001 ◽  
Vol 86 (6) ◽  
pp. 3056-3060 ◽  
Author(s):  
Yi-Jun Yan ◽  
Dong-Mei Cui ◽  
James C. Lynch
Keyword(s):  
Eye Movements ◽  
Brain Stem ◽  
Eye Movement ◽  
Saccadic Eye Movements ◽  
Point Of View ◽  
Medial Longitudinal Fasciculus ◽  
Frontal Eye Field ◽  
Neural Pathways ◽  
Eye Field ◽  
The Brain

Recent physiological studies have suggested that there are several sites of interaction between the neural pathways that control saccadic eye movements and those that control visual pursuit movements. To address the question of saccade/pursuit interaction from a neuroanatomical point of view, we have studied the connections from the smooth and saccadic eye movement subregions of the frontal eye field (FEFsem and FEFsac, respectively) to the rostral interstitial nucleus of the medial longitudinal fasciculus (riMLF) in four Cebus apella monkeys. The riMLF has traditionally been considered to be a premotor center for vertical saccadic eye movements on the basis of single neuron recording experiments, microstimulation experiments, and surgical or chemical lesion experiments. We localized the functional subregions of the FEF with the use of low-threshold (≤50 μA) intracortical microstimulation. Biotinylated dextran amine or lectin from triticum vulgaris (wheat germ), peroxidase labeled, was placed into these functionally defined subregions to label anterogradely the terminals of axons that originated in the FEF. Our results demonstrate that both the FEFsem and FEFsac send direct projections to the ipsilateral riMLF. The distribution and density of labeling from the FEFsem are comparable to those from the FEFsac. The direct FEFsem-to-riMLF projection suggests a possible role of the riMLF in smooth pursuit eye movements and supports the hypothesis that there is interaction between the saccadic and pursuit subsystems at the brain stem level.

Visually evoked slow eye movements, visual-vestibular interaction, and infratentorial lesions

1983 ◽  
Vol 91 (1) ◽  
pp. 76-80 ◽  
Author(s):  
Carsten Wennmo ◽  
Nils Gunnar Henriksson ◽  
Bengt Hindfelt ◽  
Ilmari PyykkÖ ◽  
MÅNs Magnusson
Keyword(s):  
Eye Movements ◽  
Phase Velocity ◽  
Brain Stem ◽  
Smooth Pursuit ◽  
Maximum Velocity ◽  
Slow Phase ◽  
Slow Phase Velocity ◽  
Velocity Gain ◽  
Visual Vestibular Interaction ◽  
Slow Eye Movements

The maximum velocity gain of smooth pursuit and optokinetic, vestibular, and optovestibular slow phases was examined in 15 patients with pontine, 10 with medullary, 10 with cerebellar, and 5 with combined cerebello — brain stem disorders. Marked dissociations were observed between smooth pursuit and optokinetic slow phases, especially in medullary disease. A cerebellar deficit enhanced slow phase velocity gain during rotation in darkness, whereas the corresponding gain during rotation in light was normal.

scholarly journals Spatial and Temporal Integration of Visual Motion Signals for Smooth Pursuit Eye Movements in Monkeys

2009 ◽  
Vol 102 (4) ◽  
pp. 2013-2025 ◽  
Author(s):  
Leslie C. Osborne ◽  
Stephen G. Lisberger
Keyword(s):  
Random Walk ◽  
Eye Movements ◽  
Smooth Pursuit ◽  
Visual Motion ◽  
Target Motion ◽  
Linear Filter ◽  
Smooth Pursuit Eye Movements ◽  
Spatial Averaging ◽  
Spatial Integration ◽  
Pursuit Eye Movements

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.

scholarly journals Saccades and smooth pursuit eye movements trigger equivalent gaze-cued orienting effects

2018 ◽  
Vol 71 (9) ◽  
pp. 1860-1872 ◽  
Author(s):  
Stephen RH Langton ◽  
Alex H McIntyre ◽  
Peter JB Hancock ◽  
Helmut Leder
Keyword(s):  
Eye Movements ◽  
Smooth Pursuit ◽  
Target Location ◽  
Eye Gaze ◽  
Saccadic Eye Movements ◽  
Gaze Shift ◽  
The Gaze ◽  
Orienting Effect ◽  
Motion Speed ◽  
Uncued Target

Research has established that a perceived eye gaze produces a concomitant shift in a viewer’s spatial attention in the direction of that gaze. The two experiments reported here investigate the extent to which the nature of the eye movement made by the gazer contributes to this orienting effect. On each trial in these experiments, participants were asked to make a speeded response to a target that could appear in a location toward which a centrally presented face had just gazed (a cued target) or in a location that was not the recipient of a gaze (an uncued target). The gaze cues consisted of either fast saccadic eye movements or slower smooth pursuit movements. Cued targets were responded to faster than uncued targets, and this gaze-cued orienting effect was found to be equivalent for each type of gaze shift both when the gazes were un-predictive of target location (Experiment 1) and counterpredictive of target location (Experiment 2). The results offer no support for the hypothesis that motion speed modulates gaze-cued orienting. However, they do suggest that motion of the eyes per se, regardless of the type of movement, may be sufficient to trigger an orienting effect.

How the Brain Moves the Eyes

2014 ◽  
pp. 1-25
Author(s):  
Shirley H. Wray
Keyword(s):  
Cardiac Surgery ◽  
Eye Movements ◽  
Progressive Supranuclear Palsy ◽  
Disease Progression ◽  
Frontotemporal Dementia ◽  
Smooth Pursuit ◽  
Cortical Areas ◽  
Initial Symptoms ◽  
The Brain ◽  
Symptoms And Signs

discusses the brain’s visual architecture for directing and controlling of eye movements:the striate, frontal and parietal cortical areas; and the eye movements themselves—saccades, smooth pursuit, and vergence. The susceptibility to disorders of these systems is illustrated in four detailed cases that follow disease progression from initial symptoms and signs to diagnosis and treatment. The case studies and video displays include a patient with Pick’s disease (frontotemporal dementia), another with Alzheimer’s dementia, and two examples of rare saccadic syndromes, one a patient with the slow saccade syndrome due to progressive supranuclear palsy and one with selective saccadic palsy following cardiac surgery.

MST Neuronal Responses to Heading Direction During Pursuit Eye Movements

1999 ◽  
Vol 81 (2) ◽  
pp. 596-610 ◽  
Author(s):  
William K. Page ◽  
Charles J. Duffy
Keyword(s):  
Eye Movements ◽  
Smooth Pursuit ◽  
Visual Motion ◽  
Neuronal Population ◽  
Smooth Pursuit Eye Movements ◽  
Neuronal Responses ◽  
Temporal Area ◽  
Pursuit Eye Movements ◽  
Heading Direction ◽  
Monkey Visual Cortex

MST neuronal responses to heading direction during pursuit eye movements. As you move through the environment, you see a radial pattern of visual motion with a focus of expansion (FOE) that indicates your heading direction. When self-movement is combined with smooth pursuit eye movements, the turning of the eye distorts the retinal image of the FOE but somehow you still can perceive heading. We studied neurons in the medial superior temporal area (MST) of monkey visual cortex, recording responses to FOE stimuli presented during fixation and smooth pursuit eye movements. Almost all neurons showed significant changes in their FOE selective responses during pursuit eye movements. However, the vector average of all the neuronal responses indicated the direction of the FOE during both fixation and pursuit. Furthermore, the amplitude of the net vector increased with increasing FOE eccentricity. We conclude that neuronal population encoding in MST might contribute to pursuit-tolerant heading perception.

scholarly journals Computational Studies on Acquisition and Adaptation of Ocular Following Responses Based on Cerebellar Synaptic Plasticity

2002 ◽  
Vol 87 (3) ◽  
pp. 1554-1571 ◽  
Author(s):  
Kenji Yamamoto ◽  
Yasushi Kobayashi ◽  
Aya Takemura ◽  
Kenji Kawano ◽  
Mitsuo Kawato
Keyword(s):  
Synaptic Plasticity ◽  
Brain Stem ◽  
Visual Motion ◽  
Climbing Fiber ◽  
Inhibitory Synapses ◽  
Ocular Following ◽  
Mst Neurons ◽  
P Cells ◽  
The Brain

To investigate how cerebellar synaptic plasticity guides the acquisition and adaptation of ocular following response (OFR), a large-scale network model was developed. The model includes the cerebral medial superior temporal area (MST), Purkinje cells (P cells) of the ventral paraflocculus, the accessory optic and climbing fiber systems, the brain stem oculomotor network, and the oculomotor plant. The model reconstructed temporal profiles of both firing patterns of MST neurons and P cells and eye movements. Model MST neurons ( n = 1,080) were set to be driven by retinal error and exhibited 12 preferred directions, 30 preferred velocities, and 3 firing waveforms. Correspondingly, each model P cell contained 1,080 excitatory synapses from granule cell axons (GCA) and 1,080 inhibitory synapses. P cells ( n = 40) were classified into four groups by their laterality (hemisphere) and by preferred directions of their climbing fiber inputs (CF) (contralateral or upward). The brain stem neural circuit and the oculomotor plant were modeled on the work of Yamamoto et al. The initial synaptic weights on the P cells were set randomly. At the beginning, P cell simple spikes were not well modulated by visual motion, and the eye was moved only slightly by the accessory optic system. The synaptic weights were updated according to integral-differential equation models of physiologically demonstrated synaptic plasticity: long-term depression and long-term potentiation for GCA synapses and rebound potentiation for inhibitory synapses. We assumed that maximum plasticity was induced when GCA inputs preceded CF inputs by 200 ms. After more than 10,000 presentations of ramp-step visual motion, the strengths of both the excitatory and inhibitory synapses were modified. Subsequently, the simple spike responses became well developed, and ordinary OFRs were acquired. The preferred directions of simple spikes became the opposite of those of CFs. Although the model MST neurons were set to possess a wide variety of firing characteristics, the model P cells acquired only downward or ipsilateral preferred directions, high preferred velocities and stereotypical firing waveforms. Therefore the drastic transition of the neural representation from the population codes in the MST to the firing-rate codes of simple spikes were learned at the GCA-P cell synapses and inhibitory cells-P cell synapses. Furthermore, the model successfully reproduced the gain- and directional-adaptation of OFR, which was demonstrated by manipulating the velocity and direction of visual motion, respectively. When we assumed that synaptic plasticity could only occur if CF inputs preceded GCA inputs, the ordinary OFR were acquired but neither the gain-adaptation nor the directional adaptation could be reproduced.

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