Ocular Responses to Brief Motion of Textured Backgrounds During Smooth Pursuit in Humans

Sensorimotor-linked reward modulates smooth pursuit eye movements in monkeys

Reward is essential for shaping behavior. Using sensory cues to imply forthcoming rewards, previous studies have demonstrated powerful effects of rewards on behavior. Nevertheless, the impact of reward on the sensorimotor transformation, particularly when reward is linked to behavior remains uncertain. In this study, we investigated how reward modulates smooth pursuit eye movements in monkeys. Three distinct associations between reward and eye movements were conducted in independent blocks. Results indicated that reward increased eye velocity during the steady-state pursuit, rather than during the initiation. The influence depended on the particular association between behavior and reward: a faster eye velocity was linked with reward. Neither rewarding slower eye movements nor randomizing rewards had a significant effect on behavior. The findings support the existence of distinct mechanisms involved in the initiation and steady-state phases of pursuit, and contribute to a deeper understanding of how reward interacts with these two periods of pursuit.

Model of optokinetic responses involving two different visual motion processing pathways

To understand visual motion processing underlying the optokinetic response (OKR), we developed a biomimetic model that reproduces the findings from behavioral experiments. We recorded OKRs induced by drifting gratings with different spatiotemporal frequencies from humans and non-human primates. The characteristics of the initial open-loop responses and the closed-loop eye velocity gains were analyzed using a model developed in this study. The model consists of two pathways with different dynamics. One mediates the transient response (transient pathway) and the other the sustained response (sustained pathway). Each pathway has a different spatiotemporal frequency dependence. Assuming there are different visual sensitivities for these pathways, one tuned to lower spatial and higher temporal frequencies on the retina and the other tuned to stimulus velocity, we successfully reproduced the course of OKRs. Our results suggest that two different neural circuitries/populations contribute to visual processing in the different stages of OKRs.

Motion integration is anisotropic during smooth pursuit eye movements

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.

Two-frame apparent motion presented with an inter-stimulus interval reverses optokinetic responses in mice

Two successive image frames presented with a blank inter-stimulus interval (ISI) induce reversals of perceived motion in humans. This illusory effect is a manifestation of the temporal properties of image filters embedded in the visual processing pathway. In the present study, ISI experiments were performed to identify the temporal characteristics of vision underlying optokinetic responses (OKRs) in mice. These responses are thought to be mediated by subcortical visual processing. OKRs of C57BL/6 J mice, induced by a 1/4-wavelength shift of a square-wave grating presented with and without an ISI were recorded. When a 1/4-wavelength shift was presented without, or with shorter ISIs (≤106.7 ms), OKRs were induced in the direction of the shift, with progressively decreasing amplitude as the ISI increased. However, when ISIs were 213.3 ms or longer, OKR direction reversed. Similar dependence on ISIs was also obtained using a sinusoidal grating. We subsequently quantitatively estimated temporal filters based on the ISI effects. We found that filters with biphasic impulse response functions could reproduce the ISI and temporal frequency dependence of the mouse OKR. Comparison with human psychophysics and behaviors suggests that mouse vision has more sluggish response dynamics to light signals than that of humans.

Difference in perceptual and oculomotor responses revealed by apparent motion stimuli presented with an interstimulus interval

To understand the mechanisms underlying visual motion analyses for perceptual and oculomotor responses and their similarities/differences, we analyzed eye movement responses to two-frame animations of dual-grating 3f5f stimuli while subjects performed direction discrimination tasks. The 3f5f stimulus was composed of two sinusoids with a spatial frequency ratio of 3:5 (3f and 5f), creating a pattern with fundamental frequency f. When this stimulus was shifted by 1/4 of the wavelength, the two components shifted 1/4 of their wavelengths and had opposite directions: the 5f forward and the 3f backward. By presenting the 3f5f stimulus with various interstimulus intervals (ISIs), two visual-motion-analysis mechanisms, low-level energy-based and high-level feature-based, could be effectively distinguished. This is because response direction depends on the relative contrast between the components when the energy-based mechanism operates, but not when the feature-based mechanism works. We found that when the 3f5f stimuli were presented with shorter ISIs (<100 ms), and 3f component had higher contrast, both perceptual and ocular responses were in the direction of the pattern shift, whereas the responses were reversed when the 5f had higher contrast, suggesting operation of the energy-based mechanism. On the other hand, the ocular responses were almost negligible with longer ISIs (>100 ms), whereas perceived directions were biased toward the direction of pattern shift. These results suggest that the energy-based mechanism is dominant in oculomotor responses throughout ISIs; however, there is a transition from energy-based to feature-tracking mechanisms when we perceive visual motion.

Ocular tracking responses to background motion gated by feature-based attention

Involuntary ocular tracking responses to background motion offer a window on the dynamics of motion computations. In contrast to spatial attention, we know little about the role of feature-based attention in determining this ocular response. To probe feature-based effects of background motion on involuntary eye movements, we presented human observers with a balanced background perturbation. Two clouds of dots moved in opposite vertical directions while observers tracked a target moving in horizontal direction. Additionally, they had to discriminate a change in the direction of motion (±10° from vertical) of one of the clouds. A vertical ocular following response occurred in response to the motion of the attended cloud. When motion selection was based on motion direction and color of the dots, the peak velocity of the tracking response was 30% of the tracking response elicited in a single task with only one direction of background motion. In two other experiments, we tested the effect of the perturbation when motion selection was based on color, by having motion direction vary unpredictably, or on motion direction alone. Although the gain of pursuit in the horizontal direction was significantly reduced in all experiments, indicating a trade-off between perceptual and oculomotor tasks, ocular responses to perturbations were only observed when selection was based on both motion direction and color. It appears that selection by motion direction can only be effective for driving ocular tracking when the relevant elements can be segregated before motion onset.

Does the noise matter? Effects of different kinematogram types on smooth pursuit eye movements and perception

We investigated how the human visual system and the pursuit system react to visual motion noise. We presented three different types of random-dot kinematograms at five different coherence levels. For transparent motion, the signal and noise labels on each dot were preserved throughout each trial, and noise dots moved with the same speed as the signal dots but in fixed random directions. For white noise motion, every 20 ms the signal and noise labels were randomly assigned to each dot and noise dots appeared at random positions. For Brownian motion, signal and noise labels were also randomly assigned, but the noise dots moved at the signal speed in a direction that varied randomly from moment to moment. Neither pursuit latency nor early eye acceleration differed among the different types of kinematograms. Late acceleration, pursuit gain, and perceived speed all depended on kinematogram type, with good agreement between pursuit gain and perceived speed. For transparent motion, pursuit gain and perceived speed were independent of coherence level. For white and Brownian motions, pursuit gain and perceived speed increased with coherence but were higher for white than for Brownian motion. This suggests that under our conditions, the pursuit system integrates across all directions of motion but not across all speeds.