Neural activity in the frontal pursuit area does not underlie pursuit target selection

Visual selective attention and the control of tracking eye movements: a critical review

People’s eyes are directed at objects of interest with the aim of acquiring visual information. However, processing this information is constrained in capacity, requiring task-driven and salience-driven attentional mechanisms to select few among the many available objects. A wealth of behavioral and neurophysiological evidence has demonstrated that visual selection and the motor selection of saccade targets rely on shared mechanisms. This coupling supports the premotor theory of visual attention put forth more than 30 years ago, postulating visual selection as a necessary stage in motor selection. In this review, we examine to which extent the coupling of visual and motor selection observed with saccades is replicated during ocular tracking. Ocular tracking combines catch-up saccades and smooth pursuit to foveate a moving object. We find evidence that ocular tracking requires visual selection of the speed and direction of the moving target, but the position of the motion signal may not coincide with the position of the pursuit target. Further, visual and motor selection can be spatially decoupled when pursuit is initiated (open-loop pursuit). We propose that a main function of coupled visual and motor selection is to serve the coordination of catch-up saccades and pursuit eye movements. A simple race-to-threshold model is proposed to explain the variable coupling of visual selection during pursuit, catch-up and regular saccades, while generating testable predictions. We discuss pending issues, such as disentangling visual selection from preattentive visual processing and response selection, and the pinpointing of visual selection mechanisms, which have begun to be addressed in the neurophysiological literature.

Dose-dependent sensorimotor impairment in human ocular tracking after acute low-dose alcohol administration

Key points

Oculomotor behaviours are commonly used to evaluate sensorimotor disruption due to ethanol (EtOH).

The current study demonstrates the dose‐dependent impairment in oculomotor and ocular behaviours across a range of ultra‐low BACs (<0.035%).

Processing of target speed and direction, as well as pursuit eye movements, are significantly impaired at 0.015% BAC, suggesting impaired neural activity within brain regions associated with the visual processing of motion.

Catch‐up saccades during steady visual tracking of the moving target compensate for the reduced vigour of smooth eye movements that occurs with the ingestion of low‐dose alcohol.

Saccade dynamics start to become ‘sluggish’ at as low as 0.035% BAC.

Pupillary light responses appear unaffected at BAC levels up to 0.065%.

Abstract

Changes in oculomotor behaviours are often used as metrics of sensorimotor disruption due to ethanol (EtOH); however, previous studies have focused on deficits at blood‐alcohol concentrations (BACs) above about 0.04%. We investigated the dose dependence of the impairment in oculomotor and ocular behaviours caused by EtOH administration across a range of ultra‐low BACs (≤0.035%). We took repeated measures of oculomotor and ocular performance from sixteen participants, both pre‐ and post‐EtOH administration. To assess the neurological impacts across a wide range of brain areas and pathways, our protocol measured 21 largely independent performance metrics extracted from a range of behavioural responses ranging from ocular tracking of radial step‐ramp stimuli, to eccentric gaze holding, to pupillary responses evoked by light flashes. Our results show significant impairment of pursuit and visual motion processing at 0.015% BAC, reflecting degraded neural processing within extrastriate cortical pathways. However, catch‐up saccades largely compensate for the tracking displacement shortfall caused by low pursuit gain, although there still is significant residual retinal slip and thus degraded dynamic acuity. Furthermore, although saccades are more frequent, their dynamics are more sluggish (i.e. show lower peak velocities) starting at BAC levels as low as 0.035%. Small effects in eccentric gaze holding and no effect in pupillary response dynamics were observed at levels below 0.07%, showing the higher sensitivity of the pursuit response to very low levels of blood alcohol, under the conditions of our study.

Oculomotor behaviours are commonly used to evaluate sensorimotor disruption due to ethanol (EtOH).

The current study demonstrates the dose‐dependent impairment in oculomotor and ocular behaviours across a range of ultra‐low BACs (<0.035%).

Processing of target speed and direction, as well as pursuit eye movements, are significantly impaired at 0.015% BAC, suggesting impaired neural activity within brain regions associated with the visual processing of motion.

Catch‐up saccades during steady visual tracking of the moving target compensate for the reduced vigour of smooth eye movements that occurs with the ingestion of low‐dose alcohol.

Saccade dynamics start to become ‘sluggish’ at as low as 0.035% BAC.

Pupillary light responses appear unaffected at BAC levels up to 0.065%.

Mechanisms that allow cortical preparatory activity without inappropriate movement

We reveal a novel mechanism that explains how preparatory activity can evolve in motor-related cortical areas without prematurely inducing movement. The smooth eye movement region of the frontal eye fields (FEF_SEM) is a critical node in the neural circuit controlling smooth pursuit eye movement. Preparatory activity evolves in the monkey FEF_SEM during fixation in parallel with an objective measure of visual-motor gain. We propose that the use of FEF_SEM output as a gain signal rather than a movement command allows for preparation to progress in pursuit without causing movement. We also show that preparatory modulation of firing rate in FEF_SEM predicts movement, providing evidence against the ‘movement-null’ space hypothesis as an explanation of how preparatory activity can progress without movement. Finally, there is a partial reorganization of FEF_SEM population activity between preparation and movement that would allow for a directionally non-specific component of preparatory visual-motor gain enhancement in pursuit.

Neural implementation of Bayesian inference in a sensorimotor behavior

Actions are guided by a Bayesian-like interaction between priors based on experience and current sensory evidence. Here, we unveil a complete neural implementation of Bayesian-like behavior, including adaptation of a prior. We recorded the spiking of single neurons in the smooth eye movement region of the frontal eye fields (FEF_SEM), a region that is causally involved in smooth pursuit eye movements. Monkeys tracked moving targets in contexts that set different priors for target speed. Before the onset of target motion, preparatory activity encodes and adapts in parallel with the behavioral adaptation of the prior. During the initiation of pursuit, FEF_SEM output encodes a maximum a posteriori estimate of target speed based on a reliability-weighted combination of the prior and sensory evidence. FEF_SEM responses during pursuit are sufficient both to adapt a prior that may be stored in FEF_SEM and, through known downstream pathways, to cause Bayesian-like behavior in pursuit.

Smooth Pursuit Eye Movement of Monkeys Naive to Laboratory Setups With Pictures and Artificial Stimuli

When animal behavior is studied in a laboratory environment, the animals are often extensively trained to shape their behavior. A crucial question is whether the behavior observed after training is part of the natural repertoire of the animal or represents an outlier in the animal’s natural capabilities. This can be investigated by assessing the extent to which the target behavior is manifested during the initial stages of training and the time course of learning. We explored this issue by examining smooth pursuit eye movements in monkeys naïve to smooth pursuit tasks. We recorded the eye movements of monkeys from the 1st days of training on a step-ramp paradigm. We used bright spots, monkey pictures and scrambled versions of the pictures as moving targets. We found that during the initial stages of training, the pursuit initiation was largest for the monkey pictures and in some direction conditions close to target velocity. When the pursuit initiation was large, the monkeys mostly continued to track the target with smooth pursuit movements while correcting for displacement errors with small saccades. Two weeks of training increased the pursuit eye velocity in all stimulus conditions, whereas further extensive training enhanced pursuit slightly more. The training decreased the coefficient of variation of the eye velocity. Anisotropies that grade pursuit across directions were observed from the 1st day of training and mostly persisted across training. Thus, smooth pursuit in the step-ramp paradigm appears to be part of the natural repertoire of monkeys’ behavior and training adjusts monkeys’ natural predisposed behavior.

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.

The neuronal basis of on-line visual control in smooth pursuit eye movements

Smooth pursuit eye movements allow us to maintain the image of a moving target on the fovea. Smooth pursuit consists of separate phases such as initiation and steady-state. These two phases are supported by different visual-motor mechanisms in cortical areas including the middle temporal (MT), the medial superior temporal (MST) areas and the frontal eye field (FEF). Retinal motion signals are responsible for beginning the process of pursuit initiation, whereas extraretinal signals play a role in maintaining tracking speed. Smooth pursuit often requires on-line gain adjustments during tracking in response to a sudden change in target motion. For example, a brief sinusoidal perturbation of target motion induces a corresponding perturbation of eye motion. Interestingly, the perturbation ocular response is enhanced when baseline pursuit velocity is higher, even though the stimulus frequency and amplitude are constant. This on-line gain control mechanism is not simply due to visually driven activity of cortical neurons. Visual and pursuit signals are primarily processed in cortical MT/MST and the magnitude of perturbation responses could be regulated by the internal gain parameter in FEF. Furthermore, the magnitude and the gain slope of perturbation responses are altered by smooth pursuit adaptation using repeated trials of a step-ramp tracking with two different velocities (double-velocity paradigm). Therefore, smooth pursuit adaptation, which is attributed to the cerebellar plasticity mechanism, could affect the on-line gain control mechanism.

The effects of smooth pursuit adaptation on the gain of visuomotor transmission in monkeys

Smooth pursuit eye movements are supported by visual-motor systems, where visual motion information is transformed into eye movement commands. Adaptation of the visuomotor systems for smooth pursuit is an important factor to maintain pursuit accuracy and high acuity vision. Short-term adaptation of initial pursuit gain can be produced experimentally using by repeated trials of a step-ramp tracking with two different velocities (double-step paradigm) that step-up (10-30°/s) or step-down (20-5°/s). It is also known that visuomotor gain during smooth pursuit is regulated by a dynamic gain control mechanism by showing that eye velocity evoked by a target perturbation during pursuit increases bidirectionally when ongoing pursuit velocity is higher. However, it remains uncertain how smooth pursuit adaptation alters the gain of visuomotor transmission. Therefore, a single cycle of sinusoidal motion (2.5 Hz, ± 10°/s) was introduced during step-ramp tracking pre- and post-adaptation to determine whether smooth pursuit adaptation affects the perturbation response. The results showed that pursuit adaptation had a significant effect on the perturbation response that was specific to the adapted direction. These results indicate that there might be different visuomotor mechanisms between adaptation and dynamic gain control. Furthermore, smooth pursuit adaptation altered not only the gain of the perturbation response, but also the gain slope (regression curve) at different target velocities (5, 10 and 15°/s). Therefore, pursuit adaptation could affect the dynamic regulation of the visuomotor gain at different pursuit velocities.

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.

Flexible interpretation of a decision rule by supplementary eye field neurons

Since the environment is in constant flux, decision-making capabilities of the brain must be rapid and flexible. Yet in sensory motion processing pathways of the primate brain where decision making has been extensively studied, the flexibility of neurons is limited by inherent selectivity to motion direction and speed. The supplementary eye field (SEF), an area involved in decision making on moving stimuli, is not strictly a sensory or motor structure, and hence may not suffer such limitations. Here we test whether neurons in the SEF can flexibly interpret the rule of a go/nogo task when the decision boundary in the task changes with each trial. The task rule specified that the animal pursue a moving target with its eyes if and when the target entered a visible zone. The size of the zone was changed from trial to trial in order to shift the decision boundary, and thereby assign different go/nogo significance to the same motion trajectories. Individual SEF neurons interpreted the rule appropriately, signaling go or nogo in compliance with the rule and not the direction of motion. The results provide the first evidence that individual neurons in frontal cortex can flexibly interpret a rule that governs the decision to act.

Inactivation and stimulation of the frontal pursuit area change pursuit metrics without affecting pursuit target selection

The frontal pursuit area (FPA) lies posterior to the frontal eye fields in the frontal cortex and contains neurons that are directionally selective for pursuit eye movements. Lesions of the FPA (alternately called "FEFsem") cause deficits in pursuit acceleration and velocity, which are largest for movements directed toward the lesioned side. Conversely, stimulation of the FPA evokes pursuit from fixation and increases the gain of the pursuit response. On the basis of these properties, it has been hypothesized that the FPA could underlie the selection of pursuit direction. To test this possibility, we manipulated FPA activity and measured the effect on target selection behavior in rhesus monkeys. First, we unilaterally inactivated the FPA with the GABA agonist muscimol. We then measured the monkeys' performance on a pursuit-choice task. Second, we applied microstimulation unilaterally to the FPA during pursuit initiation while monkeys performed the same pursuit-choice task. Both of these manipulations produced significant effects on pursuit metrics; the inactivation decreased pursuit velocity and acceleration, and microstimulation evoked pursuit directly. Despite these changes, both manipulations failed to significantly alter choice behavior. These results show that FPA activity is not necessary for pursuit target selection.