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 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.

Neuronal Responses Related to Smooth Pursuit Eye Movements in the Periarcuate Cortical Area of Monkeys

1998 ◽  
Vol 80 (1) ◽  
pp. 28-47 ◽  
Author(s):  
Masaki Tanaka ◽  
Kikuro Fukushima
Keyword(s):  
Eye Movements ◽  
Smooth Pursuit ◽  
Cortical Area ◽  
Eye Position ◽  
Smooth Pursuit Eye Movements ◽  
Neuronal Responses ◽  
Stationary Target ◽  
Pursuit Eye Movements ◽  
Preferred Direction ◽  
Eye Velocity

Tanaka, Masaki and Kikuro Fukushima. Neuronal responses related to smooth pursuit eye movements in the periarcuate cortical area of monkeys. J. Neurophysiol. 80: 28–47, 1998. To examine how the periarcuate area is involved in the control of smooth pursuit eye movements, we recorded 177 single neurons while monkeys pursued a moving target in the dark. The majority (52%, 92/177) of task-related neurons responded to pursuit but had little or no response to saccades. Histological reconstructions showed that these neurons were located mainly in the posterior bank of the arcuate sulcus near the sulcal spur. Twenty-seven percent (48/177) changed their activity at the onset of saccades. Of these, 36 (75%) showed presaccadic burst activity with strong preference for contraversive saccades. Eighteen (10%, 18/177) were classified as eye-position–related neurons, and 11% (19/177) were related to other aspects of the stimuli or response. Among the 92 neurons that responded to pursuit, 85 (92%) were strongly directional with uniformly distributed preferred directions. Further analyses were performed in these directionally sensitive pursuit-related neurons. For 59 neurons that showed distinct changes in activity around the initiation of pursuit, the median latency from target motion was 96 ms and that preceding pursuit was −12 ms, indicating that these neuron can influence the initiation of pursuit. We tested some neurons by briefly extinguishing the tracking target ( n = 39) or controlling its movement with the eye position signal ( n = 24). The distribution of the change in pursuit-related activity was similar to previous data for the dorsomedial part of the medial superior temporal neurons ( Newsome et al. 1988) , indicating that pursuit-related neurons in the periarcuate area also carry extraretinal signals. For 22 neurons, we examined the responses when the animals reversed pursuit direction to distinguish the effects of eye acceleration in the preferred direction from oppositely directed eye velocity. Almost all neurons discharged before eye velocity reached zero, however, only nine neurons discharged before the eyes were accelerated in the preferred direction. The delay in neuronal responses relative to the onset of eye acceleration in these trials might be caused by suppression from oppositely directed pursuit velocity. The results suggest that the periarcuate neurons do not participate in the earliest stage of eye acceleration during the change in pursuit direction, although most of them may participate in the early stages of pursuit initiation in the ordinary step-ramp pursuit trials. Some neurons changed their activity when the animals fixated a stationary target, and this activity could be distinguished easily from the strong pursuit-related responses. Our results suggest that the periarcuate pursuit area carries extraretinal signals and affects the premotor circuitry for smooth pursuit.

scholarly journals Asymmetric smooth pursuit eye movements and visual motion reaction time

2019 ◽  
Vol 7 (14) ◽  
Author(s):  
Seiji Ono ◽  
Kenichiro Miura ◽  
Takashi Kawamura ◽  
Tomohiro Kizuka
Keyword(s):  
Eye Movements ◽  
Reaction Time ◽  
Smooth Pursuit ◽  
Visual Motion ◽  
Smooth Pursuit Eye Movements ◽  
Pursuit Eye Movements

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

2020 ◽  
Vol 123 (3) ◽  
pp. 1265-1276 ◽  
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.

scholarly journals Sensory versus motor loci for integration of multiple motion signals in smooth pursuit eye movements and human motion perception

2011 ◽  
Vol 106 (2) ◽  
pp. 741-753 ◽  
Author(s):  
Yu-Qiong Niu ◽  
Stephen G. Lisberger
Keyword(s):  
Eye Movements ◽  
Smooth Pursuit ◽  
Visual Motion ◽  
Human Motion ◽  
Stimulus Selection ◽  
Smooth Pursuit Eye Movements ◽  
Motor Processing ◽  
Pursuit Eye Movements ◽  
Vector Averaging ◽  
Winner Take All

We have investigated how visual motion signals are integrated for smooth pursuit eye movements by measuring the initiation of pursuit in monkeys for pairs of moving stimuli of the same or differing luminance. The initiation of pursuit for pairs of stimuli of the same luminance could be accounted for as a vector average of the responses to the two stimuli singly. When stimuli comprised two superimposed patches of moving dot textures, the brighter stimulus suppressed the inputs from the dimmer stimulus, so that the initiation of pursuit became winner-take-all when the luminance ratio of the two stimuli was 8 or greater. The dominance of the brighter stimulus could be not attributed to either the latency difference or the ratio of the eye accelerations for the bright and dim stimuli presented singly. When stimuli comprised either spot targets or two patches of dots moving across separate locations in the visual field, the brighter stimulus had a much weaker suppressive influence; the initiation of pursuit could be accounted for by nearly equal vector averaging of the responses to the two stimuli singly. The suppressive effects of the brighter stimulus also appeared in human perceptual judgments, but again only for superimposed stimuli. We conclude that one locus of the interaction of two moving visual stimuli is shared by perception and action and resides in local inhibitory connections in the visual cortex. A second locus resides deeper in sensory-motor processing and may be more closely related to action selection than to stimulus selection.

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 effect of a moving distractor on the initiation of smooth-pursuit eye movements

1997 ◽  
Vol 14 (2) ◽  
pp. 323-338 ◽  
Author(s):  
Vincent P. Ferrera ◽  
Stephen G. Lisberger
Keyword(s):  
Eye Movements ◽  
Eye Movement ◽  
Smooth Pursuit ◽  
Visual Motion ◽  
Target Selection ◽  
Motion Processing ◽  
Smooth Pursuit Eye Movements ◽  
Response Preparation ◽  
Pursuit Eye Movements ◽  
Visual Motion Processing

AbstractAs a step toward understanding the mechanism by which targets are selected for smooth-pursuit eye movements, we examined the behavior of the pursuit system when monkeys were presented with two discrete moving visual targets. Two rhesus monkeys were trained to select a small moving target identified by its color in the presence of a moving distractor of another color. Smooth-pursuit eye movements were quantified in terms of the latency of the eye movement and the initial eye acceleration profile. We have previously shown that the latency of smooth pursuit, which is normally around 100 ms, can be extended to 150 ms or shortened to 85 ms depending on whether there is a distractor moving in the opposite or same direction, respectively, relative to the direction of the target. We have now measured this effect for a 360 deg range of distractor directions, and distractor speeds of 5–45 deg/s. We have also examined the effect of varying the spatial separation and temporal asynchrony between target and distractor. The results indicate that the effect of the distractor on the latency of pursuit depends on its direction of motion, and its spatial and temporal proximity to the target, but depends very little on the speed of the distractor. Furthermore, under the conditions of these experiments, the direction of the eye movement that is emitted in response to two competing moving stimuli is not a vectorial combination of the stimulus motions, but is solely determined by the direction of the target. The results are consistent with a competitive model for smooth-pursuit target selection and suggest that the competition takes place at a stage of the pursuit pathway that is between visual-motion processing and motor-response preparation.

Target Selection by the Frontal Cortex during Coordinated Saccadic and Smooth Pursuit Eye Movements

2009 ◽  
Vol 21 (8) ◽  
pp. 1611-1627 ◽  
Author(s):  
Krishna Srihasam ◽  
Daniel Bullock ◽  
Stephen Grossberg
Keyword(s):  
Eye Movements ◽  
Smooth Pursuit ◽  
Current Model ◽  
Target Selection ◽  
Motion Processing ◽  
Parallel Model ◽  
Smooth Pursuit Eye Movements ◽  
Pontine Nucleus ◽  
Temporal Area ◽  
Pursuit Eye Movements

Oculomotor tracking of moving objects is an important component of visually based cognition and planning. Such tracking is achieved by a combination of saccades and smooth-pursuit eye movements. In particular, the saccadic and smooth-pursuit systems interact to often choose the same target, and to maximize its visibility through time. How do multiple brain regions interact, including frontal cortical areas, to decide the choice of a target among several competing moving stimuli? How is target selection information that is created by a bias (e.g., electrical stimulation) transferred from one movement system to another? These saccade–pursuit interactions are clarified by a new computational neural model, which describes interactions between motion processing areas: the middle temporal area, the middle superior temporal area, the frontal pursuit area, and the dorsal lateral pontine nucleus; saccade specification, selection, and planning areas: the lateral intraparietal area, the frontal eye fields, the substantia nigra pars reticulata, and the superior colliculus; the saccadic generator in the brain stem; and the cerebellum. Model simulations explain a broad range of neuroanatomical and neurophysiological data. These results are in contrast with the simplest parallel model with no interactions between saccades and pursuit other than common-target selection and recruitment of shared motoneurons. Actual tracking episodes in primates reveal multiple systematic deviations from predictions of the simplest parallel model, which are explained by the current model.

Relation of cortical areas MT and MST to pursuit eye movements. I. Localization and visual properties of neurons

1988 ◽  
Vol 60 (2) ◽  
pp. 580-603 ◽  
Author(s):  
H. Komatsu ◽  
R. H. Wurtz
Keyword(s):  
Eye Movements ◽  
Smooth Pursuit ◽  
Visual Motion ◽  
Receptive Fields ◽  
Motion Processing ◽  
Temporal Area ◽  
Pursuit Eye Movements ◽  
Visual Motion Processing ◽  
Visual Areas ◽  
Visual Properties

1. Among the multiple extrastriate visual areas in monkey cerebral cortex, several areas within the superior temporal sulcus (STS) are selectively related to visual motion processing. In this series of experiments we have attempted to relate this visual motion processing at a neuronal level to a behavior that is dependent on such processing, the generation of smooth-pursuit eye movements. 2. We studied two visual areas within the STS, the middle temporal area (MT) and the medial superior temporal area (MST). For the purposes of this study, MT and MST were defined functionally as those areas within the STS having a high proportion of directionally selective neurons. MST was distinguished from MT by using the established relationship of receptive-field size to eccentricity, with MST having larger receptive fields than MT. 3. A subset of these visually responsive cells within the STS were identified as pursuit cells--those cells that discharge during smooth pursuit of a small target in an otherwise dark room. Pursuit cells were found only in localized regions--in the foveal region of MT (MTf), in a dorsal-medial area of MST on the anterior bank of the STS (MSTd), and in a lateral-anterior area of MST on the floor and the posterior bank of the STS (MST1). 4. Pursuit cells showed two characteristics in common when their visual properties were studied while the monkey was fixating. Almost all cells showed direction selectivity for moving stimuli and included the fovea within their receptive fields. 5. The visual response of pursuit cells in the several areas differed in two ways. Cells in MTf preferred small moving spots of light, whereas cells in MSTd preferred large moving stimuli, such as a pattern of random dots. Cells in MTf had small receptive fields; those in MSTd usually had large receptive fields. Visual responses of pursuit neurons in MST1 were heterogeneous; some resembled those in MTf, whereas others were similar to those in MSTd. This suggests that the pursuit cells in MSTd and MST1 belong to different subregions of MST.

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