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.

Object Motion Computation for the Initiation of Smooth Pursuit Eye Movements in Humans

2005 ◽  
Vol 93 (4) ◽  
pp. 2279-2293 ◽  
Author(s):  
Julian M. Wallace ◽  
Leland S. Stone ◽  
Guillaume S. Masson
Keyword(s):  
Eye Movements ◽  
Smooth Pursuit ◽  
Object Motion ◽  
Type I ◽  
Type Ii ◽  
Smooth Pursuit Eye Movements ◽  
Motion Direction ◽  
Pursuit Eye Movements ◽  
Motion Computation ◽  
Tracking Direction

Pursuing an object with smooth eye movements requires an accurate estimate of its two-dimensional (2D) trajectory. This 2D motion computation requires that different local motion measurements are extracted and combined to recover the global object-motion direction and speed. Several combination rules have been proposed such as vector averaging (VA), intersection of constraints (IOC), or 2D feature tracking (2DFT). To examine this computation, we investigated the time course of smooth pursuit eye movements driven by simple objects of different shapes. For type II diamond (where the direction of true object motion is dramatically different from the vector average of the 1-dimensional edge motions, i.e., VA ≠ IOC = 2DFT), the ocular tracking is initiated in the vector average direction. Over a period of less than 300 ms, the eye-tracking direction converges on the true object motion. The reduction of the tracking error starts before the closing of the oculomotor loop. For type I diamonds (where the direction of true object motion is identical to the vector average direction, i.e., VA = IOC = 2DFT), there is no such bias. We quantified this effect by calculating the direction error between responses to types I and II and measuring its maximum value and time constant. At low contrast and high speeds, the initial bias in tracking direction is larger and takes longer to converge onto the actual object-motion direction. This effect is attenuated with the introduction of more 2D information to the extent that it was totally obliterated with a texture-filled type II diamond. These results suggest a flexible 2D computation for motion integration, which combines all available one-dimensional (edge) and 2D (feature) motion information to refine the estimate of object-motion direction over time.

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.

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.

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.

scholarly journals Motion integration is anisotropic during smooth pursuit eye movements

2019 ◽  
Vol 121 (5) ◽  
pp. 1787-1797
Author(s):  
David Souto ◽  
Jayesha Chudasama ◽  
Dirk Kerzel ◽  
Alan Johnston
Keyword(s):  
Eye Movements ◽  
Visual System ◽  
Eye Movement ◽  
Object Motion ◽  
Global Motion ◽  
Local Motion ◽  
Pursuit Eye Movements ◽  
Motion Integration ◽  
Retinal Motion ◽  
Motion Measurements

Smooth pursuit eye movements (pursuit) are used to minimize the retinal motion of moving objects. During pursuit, the pattern of motion on the retina carries not only information about the object movement but also reafferent information about the eye movement itself. The latter arises from the retinal flow of the stationary world in the direction opposite to the eye movement. To extract the global direction of motion of the tracked object and stationary world, the visual system needs to integrate ambiguous local motion measurements (i.e., the aperture problem). Unlike the tracked object, the stationary world’s global motion is entirely determined by the eye movement and thus can be approximately derived from motor commands sent to the eye (i.e., from an efference copy). Because retinal motion opposite to the eye movement is dominant during pursuit, different motion integration mechanisms might be used for retinal motion in the same direction and opposite to pursuit. To investigate motion integration during pursuit, we tested direction discrimination of a brief change in global object motion. The global motion stimulus was a circular array of small static apertures within which one-dimensional gratings moved. We found increased coherence thresholds and a qualitatively different reflexive ocular tracking for global motion opposite to pursuit. Both effects suggest reduced sampling of motion opposite to pursuit, which results in an impaired ability to extract coherence in motion signals in the reafferent direction. We suggest that anisotropic motion integration is an adaptation to asymmetric retinal motion patterns experienced during pursuit eye movements. NEW & NOTEWORTHY This study provides a new understanding of how the visual system achieves coherent perception of an object’s motion while the eyes themselves are moving. The visual system integrates local motion measurements to create a coherent percept of object motion. An analysis of perceptual judgments and reflexive eye movements to a brief change in an object’s global motion confirms that the visual and oculomotor systems pick fewer samples to extract global motion opposite to the eye movement.

Visuomotor Velocity Transformations for Smooth Pursuit Eye Movements

2010 ◽  
Vol 104 (4) ◽  
pp. 2103-2115 ◽  
Author(s):  
Gunnar Blohm ◽  
Philippe Lefèvre
Keyword(s):  
Eye Movements ◽  
Reference Frame ◽  
Smooth Pursuit ◽  
Eye Position ◽  
Smooth Pursuit Eye Movements ◽  
Velocity Transformation ◽  
Pursuit Eye Movements ◽  
Pursuit Initiation ◽  
Retinal Motion ◽  
Frame Transformation

Smooth pursuit eye movements are driven by retinal motion signals. These retinal motion signals are converted into motor commands that obey Listing's law (i.e., no accumulation of ocular torsion). The fact that smooth pursuit follows Listing's law is often taken as evidence that no explicit reference frame transformation between the retinal velocity input and the head-centered motor command is required. Such eye-position-dependent reference frame transformations between eye- and head-centered coordinates have been well-described for saccades to static targets. Here we suggest that such an eye (and head)-position-dependent reference frame transformation is also required for target motion (i.e., velocity) driving smooth pursuit eye movements. Therefore we tested smooth pursuit initiation under different three-dimensional eye positions and compared human performance to model simulations. We specifically tested if the ocular rotation axis changed with vertical eye position, if the misalignment of the spatial and retinal axes during oblique fixations was taken into account, and if ocular torsion (due to head roll) was compensated for. If no eye-position-dependent velocity transformation was used, the pursuit initiation should follow the retinal direction, independently of eye position; in contrast, a correct visuomotor velocity transformation would result in spatially correct pursuit initiation. Overall subjects accounted for all three components of the visuomotor velocity transformation, but we did observe differences in the compensatory gains between individual subjects. We concluded that the brain does perform a visuomotor velocity transformation but that this transformation was prone to noise and inaccuracies of the internal model.

scholarly journals Multiple components in direction learning in smooth pursuit eye movements of monkeys

2018 ◽  
Vol 120 (4) ◽  
pp. 2020-2035 ◽  
Author(s):  
Nathan J. Hall ◽  
Yan Yang ◽  
Stephen G. Lisberger
Keyword(s):  
Eye Movements ◽  
Smooth Pursuit ◽  
Slow Component ◽  
Smooth Pursuit Eye Movements ◽  
Behavioral Learning ◽  
Parallel Processes ◽  
Pursuit Eye Movements ◽  
Pursuit Initiation ◽  
Multiple Components ◽  
Temporal Specificity

We analyzed behavioral features of smooth pursuit eye movements to characterize the course of acquisition and expression of multiple neural components of motor learning. Monkeys tracked a target that began to move in an initial “pursuit” direction and suddenly, but predictably, changed direction after a fixed interval of 250 ms. As the trial is repeated, monkeys learn to make eye movements that predict the change in target direction. Quantitative analysis of the learned response revealed evidence for multiple, dynamic, parallel processes at work during learning. 1) The overall learning followed at least two trial courses: a fast component grew and saturated rapidly over tens of trials, and a slow component grew steadily over up to 1,000 trials. 2) The temporal specificity of the learned response within each trial was crude during the first 100 trials but then improved gradually over the remaining trials. 3) External influences on the gain of pursuit initiation modulate the expression but probably not the acquisition of learning. The gain of pursuit initiation and the expression of the learned response decreased in parallel, both gradually through a 1,000-trial learning block and immediately between learning trials with different gains in the initiation of pursuit. We conclude that at least two distinct neural mechanisms drive the acquisition of pursuit learning over 100 to 1,000 trials (3 to 30 min). Both mechanisms generate underlying memory traces that are modulated in relation to the gain of pursuit initiation before expression in the final motor output. NEW & NOTEWORTHY We show that cerebellum-dependent direction learning in smooth pursuit eye movements grows in at least two components over 1,100 behavioral learning repetitions. One component grows over tens of trials and the other over hundreds. Within trials, learned temporal specificity gradually improves over hundreds of trials. The expression of each learning component on a given trial can be modified by external factors that do not affect the underlying memory trace.

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

2018 ◽  
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.

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