Influence of Cognitive Expectation on the Initiation of Anticipatory and Visual Pursuit Eye Movements in the Rhesus Monkey

2006 ◽  
Vol 95 (6) ◽  
pp. 3770-3782 ◽  
Author(s):  
C. de Hemptinne ◽  
P. Lefèvre ◽  
M. Missal
Keyword(s):  
Eye Movements ◽  
Rhesus Monkeys ◽  
Dominant Role ◽  
Visual Display ◽  
Target Motion ◽  
Motion Onset ◽  
Directional Information ◽  
Visual Pursuit ◽  
Pursuit Eye Movements

A classic paradigm to study anticipatory pursuit consists in training monkeys to look at a target that appears in the center of a visual display, disappears during a short “gap” period, then reappears and immediately starts to move. To determine the role of prior directional information on anticipatory pursuit eye movements, we trained rhesus monkeys to associate the color of a centrally presented visual cue with the direction of an upcoming target motion. In a first experiment, a gap period occurred randomly in 50% of the trials. Consequently, two possible choices of timing of target motion onset were given to subjects to guide their anticipatory responses. In a second experiment, a gap period occurred during each trial and only a single choice of timing of target motion onset was given to subjects. We found that monkeys used the learned association between the color of the cue and the direction of future target motion to voluntarily initiate anticipatory pursuit movements in the appropriate direction. Anticipatory movements could be classified in two distinct populations: early and late movements. Early movements were most frequent when prior directional information was provided and when two choices of timing of target motion onset were given. The latency of visual pursuit was shortened and its velocity was larger when prior directional information was provided. We conclude that cognitive expectation of future target motion plays a dominant role in determining characteristics of anticipatory pursuit in the monkey.

Temporal properties of visual motion signals for the initiation of smooth pursuit eye movements in monkeys

1994 ◽  
Vol 72 (1) ◽  
pp. 150-162 ◽  
Author(s):  
R. J. Krauzlis ◽  
S. G. Lisberger
Keyword(s):  
Eye Movements ◽  
Eye Movement ◽  
Visual Motion ◽  
Target Motion ◽  
Target Velocity ◽  
Motion Onset ◽  
Image Velocity ◽  
Pursuit Eye Movements ◽  
Onset Delay ◽  
The Relationship

1. Our goal was to assess whether visual motion signals related to changes in image velocity contribute to pursuit eye movements. We recorded the smooth eye movements evoked by ramp target motion at constant speed. In two different kinds of stimuli, the onset of target motion provided either an abrupt, step change in target velocity or a smooth target acceleration that lasted 125 ms followed by prolonged target motion at constant velocity. We measured the eye acceleration in the first 100 ms of pursuit. Because of the 100-ms latency from the onset of visual stimuli to the onset of smooth eye movement, the eye acceleration in this 100-ms interval provides an estimate of the open-loop response of the visuomotor pathways that drive pursuit. 2. For steps of target velocity, eye acceleration in the first 100 ms of pursuit depended on the “motion onset delay,” defined as the interval between the appearance of the target and the onset of motion. If the motion onset delay was > 100 ms, then the initial eye movement consisted of separable early and late phases of eye acceleration. The early phase dominated eye acceleration in the interval from 0 to 40 ms after pursuit onset and was relatively insensitive to image speed. The late phase dominated eye acceleration in the interval 40–100 ms after the onset of pursuit and had an amplitude that was proportional to image speed. If there was no delay between the appearance of the target and the onset of its motion, then the early component was not seen, and eye acceleration was related to target speed throughout the first 100 ms of pursuit. 3. For step changes of target velocity, the relationship between eye acceleration in the first 40 ms of pursuit and target velocity saturated at target speeds > 10 degrees /s. In contrast, the relationship was nearly linear when eye acceleration was measured in the interval 40–100 ms after the onset of pursuit. We suggest that the first 40 ms of pursuit are driven by a transient visual motion input that is related to the onset of target motion (motion onset transient component) and that the next 60 ms are driven by a sustained visual motion input (image velocity component). 4. When the target accelerated smoothly for 125 ms before moving at constant speed, the initiation of pursuit resembled that evoked by steps of target velocity. However, the latency of pursuit was consistently longer for smooth target accelerations than for steps of target velocity.(ABSTRACT TRUNCATED AT 400 WORDS)

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.

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.

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