Coordination of smooth pursuit and saccade target selection in monkeys

Interactions between Saccades and Smooth Pursuit Eye Movements in Marmosets

Animals use a combination of eye movements to track moving objects. These different eye movements need to be coordinated for successful tracking, requiring interactions between the systems involved. Here, we study the interaction between the saccadic and smooth pursuit eye movement systems in marmosets. Using a single-target pursuit task, we show that saccades cause an enhancement in pursuit following a saccade. Using a two-target pursuit task, we show that this enhancement in pursuit is selective toward the motion of the target selected by the saccade, irrespective of any biases in pursuit prior to the saccade. These experiments highlight the similarities in the functioning of saccadic and smooth pursuit eye movement systems across primates.

Interactions between saccades and smooth pursuit eye movements in marmosets

Animals use a combination of eye movements to track moving objects. These different eye movements need to be coordinated for successful tracking, requiring interactions between the systems involved. Here, we study the interaction between the saccadic and smooth pursuit eye movement systems in marmosets. Using a single target pursuit task, we show that saccades cause an enhancement in pursuit following a saccade. Using a two-target pursuit task, we show that this enhancement in pursuit is selective towards the motion of the target selected by the saccade, irrespective of any biases in pursuit prior to the saccade. These experiments highlight the similarities in the functioning of saccadic and smooth pursuit eye movement systems across primates.

SIGNIFICANCE STATEMENT

We study the coordination between the smooth-pursuit and saccadic eye movement systems in marmosets using single and multiple object motions. We find that saccade to a target increases pursuit velocity towards the target. If multiple objects are visible, saccade choice makes pursuit more selective towards the saccade target. Our results show that coordination between different eye movement systems to successfully track moving objects is similar between marmosets and primates.

Differential saccade-pursuit coordination under sleep loss and low-dose alcohol

Introduction

Ocular tracking of a moving object requires tight coordination between smooth pursuit and saccadic eye movements. Normally, pursuit drives gaze velocity to closely match target velocity, with residual position offsets corrected by catch-up saccades. However, how/if common stressors affect this coordination is largely unknown. This study seeks to elucidate the effects of acute and chronic sleep loss, and low-dose alcohol, on saccade-pursuit coordination, as well as that of caffeine.

Methods

We used an ocular tracking paradigm to assess three metrics of tracking (pursuit gain, saccade rate, saccade amplitude) and to compute "ground lost" (from reductions in steady-state pursuit gain) and "ground recouped" (from increases in steady-state saccade rate and/or amplitude). We emphasize that these are measures of relative changes in positional offsets, and not absolute offset from the fovea.

Results

Under low-dose alcohol and acute sleep loss, ground lost was similarly large. However, under the former, it was nearly completely recouped by saccades, whereas under the latter, compensation was at best partial. Under chronic sleep restriction and acute sleep loss with a caffeine countermeasure, the pursuit deficit was dramatically smaller, yet saccadic behavior remained altered from baseline. In particular, saccadic rate remained significantly elevated, despite the fact that ground lost was minimal.

Discussion

This constellation of findings demonstrates differential impacts on saccade-pursuit coordination with low-dose alcohol impacting only pursuit, likely through extrastriate cortical pathways, while acute sleep loss not only disrupts pursuit but also undermines saccadic compensation, likely through midbrain/brainstem pathways. Furthermore, while chronic sleep loss and caffeine-mitigated acute sleep loss show little residual pursuit deficit, consistent with uncompromised cortical visual processing, they nonetheless show an elevated saccade rate, suggesting residual midbrain and/or brainstem impacts.

Visual motion integration of bidirectional transparent motion in mouse opto-locomotor reflexes

Visual motion perception depends on readout of direction selective sensors. We investigated in mice whether the response to bidirectional transparent motion, activating oppositely tuned sensors, reflects integration (averaging) or winner-take-all (mutual inhibition) mechanisms. We measured whole body opto-locomotor reflexes (OLRs) to bidirectional oppositely moving random dot patterns (leftward and rightward) and compared the response to predictions based on responses to unidirectional motion (leftward or rightward). In addition, responses were compared to stimulation with stationary patterns. When comparing OLRs to bidirectional and unidirectional conditions, we found that the OLR to bidirectional motion best fits an averaging model. These results reflect integration mechanisms in neural responses to contradicting sensory evidence as has been documented for other sensory and motor domains.

Presaccadic motion integration drives a predictive postsaccadic following response

Saccadic eye movements sample the visual world and ensure high acuity across the visual field. To compensate for delays in processing, saccades to moving targets require predictions: The eyes must intercept the target's future position to then pursue its direction of motion. Although prediction is crucial to voluntary pursuit, it is unclear whether it is an obligatory feature of saccade planning. Saccade planning involves an involuntary enhanced processing of the target, called presaccadic attention. Does this presaccadic attention recruit smooth eye movements automatically? To test this, we had human participants perform a saccade to one of four apertures, which were static, but each contained a random dot field with motion tangential to the required saccade. In this task, saccades were deviated along the direction of target motion, and the eyes exhibited a following response upon saccade landing. This postsaccadic following response (PFR) increased with spatial uncertainty of the target position and persisted even when we removed the motion stimulus in midflight of the saccade, confirming that it relied on presaccadic information. Motion from 50-100 ms prior to the saccade had the strongest influence on PFR, consistent with the time course of perceptual enhancements reported in presaccadic attention. Finally, the PFR magnitude related linearly to the logarithm of stimulus velocity and generally had low gain, similar to involuntary ocular following movements commonly observed after sudden motion onsets. These results suggest that presaccadic attention selects motion features of targets predictively, presumably to ensure successful immediate tracking of saccade targets in motion.

Dissecting patterns of preparatory activity in the frontal eye fields during pursuit target selection

We investigated the composition of preparatory activity of frontal eye field (FEF) neurons in monkeys performing a pursuit target selection task. In response to the orthogonal motion of a large and a small reward target, monkeys initiated pursuit biased toward the direction of large reward target motion. FEF neurons exhibited robust preparatory activity preceding movement initiation in this task. Preparatory activity consisted of two components, ramping activity that was constant across target selection conditions, and a flat offset in firing rates that signaled the target selection condition. Ramping activity accounted for 50% of the variance in the preparatory activity and was linked most strongly, on a trial-by-trial basis, to pursuit eye movement latency rather than to its direction or gain. The offset in firing rates that discriminated target selection conditions accounted for 25% of the variance in the preparatory activity and was commensurate with a winner-take-all representation, signaling the direction of large reward target motion rather than a representation that matched the parameters of the upcoming movement. These offer new insights into the role that the frontal eye fields play in target selection and pursuit control. They show that preparatory activity in the FEF signals more strongly when to move rather than where or how to move and suggest that structures outside the FEF augment its contributions to the target selection process.NEW & NOTEWORTHY We used the smooth eye movement pursuit system to link between patterns of preparatory activity in the frontal eye fields and movement during a target selection task. The dominant pattern was a ramping signal that did not discriminate between selection conditions and was linked, on trial-by-trial basis, to movement latency. A weaker pattern was composed of a constant signal that discriminated between selection conditions but was only weakly linked to the movement parameters.

Dynamic integration of information about salience and value for smooth pursuit eye movements

Eye movement behavior can be determined by bottom-up factors like visual salience and by top-down factors like expected value. These different types of signals have to be combined for the control of eye movements. In this study we investigated how smooth pursuit eye movements integrate salience and value information. Observers were asked to track a random-dot kinematogram containing two coherent motion directions. To manipulate salience, the coherence or the density of one of the motion signals was varied. To manipulate value, observers won or lost money in a separate experiment if they were tracking one or the other motion direction. Our results show that pursuit direction was initially determined only by salience. 300-400 ms after target motion onset, pursuit steered towards the rewarded direction and the salience effects disappeared. The time course of this effect depended crucially on the difficulty to segment the two signal directions. These results indicate that salience determines early pursuit responses in the same way as saccades with short latencies. Value information is processed slower and dominates pursuit after several 100 ms.

Contrast dependence of smooth pursuit eye movements following a saccade to superimposed targets

Dorsal stream areas provide motion information used by the oculomotor system to generate pursuit eye movements. Neurons in these areas saturate at low levels of luminance contrast. We therefore hypothesized that during the early phase of pursuit, eye velocity would exhibit an oculomotor gain function that saturates at low luminance contrast. To test this, we recorded eye movements in two macaques trained to saccade to an aperture in which a pattern of dots moved left or right. Shortly after the end of the saccade, the eyes followed the direction of motion with an oculomotor gain that increased with contrast before saturating. The addition of a second pattern of dots, moving in the opposite direction and superimposed on the first, resulted in a rightward shift of the contrast-dependent oculomotor gain function. The magnitude of this shift increased with the contrast of the second pattern of dots. Motion was nulled when the two patterns were equal in contrast. Next, we varied contrast over time. Contrast differences that disappeared before saccade onset biased post-saccadic eye movements at short latency. Changes in contrast occurring during or after saccade termination did not influence eye movements for approximately 150 ms. Earlier studies found that eye movements can be explained by a vector average computation when both targets are equal in contrast. We suggest that this averaging computation may reflect a special case of divisive normalization, yielding saturating contrast response functions that shift to the right with opposed motion, averaging motions when targets are equated in contrast.

Reward action in the initiation of smooth pursuit eye movements

Reward has a powerful influence on motor behavior. To probe how and where reward systems alter motor behavior, we studied smooth pursuit eye movements in monkeys trained to associate the color of a visual cue with the size of the reward to be issued at the end of the target motion. When the tracking task presented two different colored targets that moved orthogonally, monkeys biased the initiation of pursuit toward the direction of motion of the target that led to larger reward. The bias was larger than expected given the modest effects of reward size on tracking of single targets. Experiments with three different reward sizes suggested that the bias afforded a given target depends mainly on the size of the larger reward. To analyze the effect of reward on directional learning in pursuit, monkeys tracked a single moving target that changed direction 250 ms after the onset of motion. Expectation of a larger reward led to a larger learned eye movement during the acquisition of the learned response and during subsequent probes of what had been learned, implying that reward influenced the expression rather than the acquisition of learning. The specific effects of reward size on learning and two-target stimuli imply that the site of reward modulation is at a level where multiple target motions compete for control of eye movement, downstream from sensory processing and learning and upstream from final motor processing.

Superior colliculus inactivation alters the weighted integration of visual stimuli

The primate superior colliculus (SC) is important for the winner-take-all selection of targets for orienting movements. Such selection takes time, however, and the earliest motor responses typically are guided by a weighted vector average of the visual stimuli, before the winner-take-all selection of a single target. We tested whether SC activity plays a role in this initial stage of orienting by inactivating the SC in two macaques (Macaca mulatta) with local muscimol injections. After SC inactivation, initial orienting responses still followed a vector average, but the contribution of the visual stimulus inside the affected field was decreased, and the contribution of the stimulus outside the affected field was increased. These results demonstrate that the SC plays an important role in the weighted integration of visual signals for orienting, in addition to its role in the winner-take-all selection of the target.

Inactivation of primate superior colliculus biases target choice for smooth pursuit, saccades, and button press responses

In addition to its well-known role in the control of saccades, the primate superior colliculus (SC) has been implicated in the processes of target choice for overt orienting movements and for covert spatial attention. We focally inactivated the SC, by muscimol injection, while monkeys selected the target of a smooth pursuit, saccade, or button press response from two competing stimuli. The choice stimuli were placed so that one appeared within and the other appeared outside the affected visual field. SC inactivation biased the subject to choose stimuli out of the affected visual field for all three types of responses, although the effects on target choice were significantly smaller for button presses. Inactivation caused no changes in the selection of single stimuli within or out of the affected visual field, indicating the choice bias was not caused by deficits in response execution. The inactivation-induced bias for smooth pursuit and button press responses indicates SC activity is important for selecting the target, independent of any role in saccade preparation.

Target Selection by the Frontal Cortex during Coordinated Saccadic and Smooth 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.