Serial linkage of target selection for orienting and tracking eye movements

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.

Micropursuit and the control of attention and eye movements in dynamic environments

It is more challenging to plan eye movements during perceptual tasks performed in dynamic displays than in static displays. Decisions about the timing of saccades become more critical, and decisions must also involve smooth eye movements, as well as saccades. The present study examined eye movements when judging which of two moving discs would arrive first, or collide, at a common meeting point. Perceptual discrimination after training was precise (Weber fractions < 6%). Strategies reflected a combined contribution of saccades and smooth eye movements. The preferred strategy was to look near the meeting point when strategies were freely chosen. When strategies were assigned, looking near the meeting point produced better performance than switching between the discs. Smooth eye movements were engaged in two ways: (a) low-velocity smooth eye movements correlated with the motion of each disc (micropursuit) were found while the line of sight remained between the discs; and (b) spontaneous smooth pursuit of the pair of discs occurred after the perceptual report, when the discs moved as a pair along a common path. The results show clear preferences and advantages for those eye movement strategies during dynamic perceptual tasks that require minimal management or effort. In addition, smooth eye movements, whose involvement during perceptual tasks within dynamic displays may have previously escaped notice, provide useful indictors of the strategies used to select information and distribute attention during the performance of dynamic perceptual tasks.

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.

Numerosities and Other Magnitudes in the Brains: A Comparative View

The ability to represent, discriminate, and perform arithmetic operations on discrete quantities (numerosities) has been documented in a variety of species of different taxonomic groups, both vertebrates and invertebrates. We do not know, however, to what extent similarity in behavioral data corresponds to basic similarity in underlying neural mechanisms. Here, we review evidence for magnitude representation, both discrete (countable) and continuous, following the sensory input path from primary sensory systems to associative pallial territories in the vertebrate brains. We also speculate on possible underlying mechanisms in invertebrate brains and on the role played by modeling with artificial neural networks. This may provide a general overview on the nervous system involvement in approximating quantity in different animal species, and a general theoretical framework to future comparative studies on the neurobiology of number cognition.

GABAergic motor neurons bias locomotor decision-making in C. elegans

Proper threat-reward decision-making is critical to animal survival. Emerging evidence indicates that the motor system may participate in decision-making but the neural circuit and molecular bases for these functions are little known. We found in C. elegans that GABAergic motor neurons (D-MNs) bias toward the reward behavior in threat-reward decision-making by retrogradely inhibiting a pair of premotor command interneurons, AVA, that control cholinergic motor neurons in the avoidance neural circuit. This function of D-MNs is mediated by a specific ionotropic GABA receptor (UNC-49) in AVA, and depends on electrical coupling between the two AVA interneurons. Our results suggest that AVA are hub neurons where sensory inputs from threat and reward sensory modalities and motor information from D-MNs are integrated. This study demonstrates at single-neuron resolution how motor neurons may help shape threat-reward choice behaviors through interacting with other neurons.

Dissociation of pursuit target selection from saccade execution

Pursuit and saccades almost always select the same target. Is this the results of a common selection process or does smooth pursuit obligatorily follow the stimulus targeted by saccades? To address this question, we used microstimulation of the primate superior colliculus (SC) to redirect the eyes from a selected pursuit target to a distracter moving in the opposite direction. During each trial, monkeys pursued a horizontally moving array of colored target stimuli. In half of the trials, this target array was accompanied by a distracter array moving horizontally in the opposite direction, offset by the vertical amplitude of the stimulation-evoked saccade. We stimulated the SC during maintained pursuit on half of the trials, and measured pursuit eye velocity during the 50-ms interval immediately following the stimulation-evoked saccade to the distracter array. Saccades evoked by SC stimulation did not alter pursuit target selection. Pursuit velocity on average changed by less than 10% of that expected if the monkey had completely switched targets. Moreover, the same changes in velocity occurred when there was no distracter, indicating that even these small changes in pursuit velocity were a direct effect of the evoked saccade, not partial selection of the distracter. These results show that motor execution of saccades is not sufficient to select a pursuit target, and support the idea that the coordination of pursuit and saccades is accomplished by a shared target selection process.

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.

Insights into cortical mechanisms of behavior from microstimulation experiments

Even the simplest behaviors depend on a large number of neurons that are distributed across many brain regions. Because electrical microstimulation can change the activity of localized subsets of neurons, it has provided valuable evidence that specific neurons contribute to particular behaviors. Here we review what has been learned about cortical function from behavioral studies using microstimulation in animals and humans. Experiments that examine how microstimulation affects the perception of stimuli have shown that the effects of microstimulation are usually highly specific and can be related to the stimuli preferred by neurons at the stimulated site. Experiments that ask subjects to detect cortical microstimulation in the absence of other stimuli have provided further insights. Although subjects typically can detect microstimulation of primary sensory or motor cortex, they are generally unable to detect stimulation of most of cortex without extensive practice. With practice, however, stimulation of any part of cortex can become detected. These training effects suggest that some patterns of cortical activity cannot be readily accessed to guide behavior, but that the adult brain retains enough plasticity to learn to process novel patterns of neuronal activity arising anywhere in cortex.

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.

Eye movements: the past 25 years

This article reviews the past 25 years of research on eye movements (1986-2011). Emphasis is on three oculomotor behaviors: gaze control, smooth pursuit and saccades, and on their interactions with vision. Focus over the past 25 years has remained on the fundamental and classical questions: What are the mechanisms that keep gaze stable with either stationary or moving targets? How does the motion of the image on the retina affect vision? Where do we look - and why - when performing a complex task? How can the world appear clear and stable despite continual movements of the eyes? The past 25 years of investigation of these questions has seen progress and transformations at all levels due to new approaches (behavioral, neural and theoretical) aimed at studying how eye movements cope with real-world visual and cognitive demands. The work has led to a better understanding of how prediction, learning and attention work with sensory signals to contribute to the effective operation of eye movements in visually rich environments.

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.

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

The frontal pursuit area (FPA) contains neurons that are directionally selective for pursuit eye-movements. We found that FPA neurons discriminate target from distracter too late to account for pursuit directional selection. Rather, the timing of neuronal discrimination is linked to pursuit onset, suggesting a role in motor execution. We also found buildup of activity of FPA neurons prior to pursuit onset that correlated with eye acceleration. These results show that the FPA is unlikely to be involved in selection of initial pursuit direction, but could be involved in motor preparation by increasing pursuit gain prior to pursuit onset.

Visual guidance of smooth-pursuit eye movements: sensation, action, and what happens in between

Smooth-pursuit eye movements transform 100 ms of visual motion into a rapid initiation of smooth eye movement followed by sustained accurate tracking. Both the mean and variation of the visually driven pursuit response can be accounted for by the combination of the mean tuning curves and the correlated noise within the sensory representation of visual motion in extrastriate visual area MT. Sensory-motor and motor circuits have both housekeeping and modulatory functions, implemented in the cerebellum and the smooth eye movement region of the frontal eye fields. The representation of pursuit is quite different in these two regions of the brain, but both regions seem to control pursuit directly with little or no noise added downstream. Finally, pursuit exhibits a number of voluntary characteristics that happen on short timescales. These features make pursuit an excellent exemplar for understanding the general properties of sensory-motor processing in the brain.

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.

Attention governs action in the primate frontal eye field

While the motor and attentional roles of the frontal eye field (FEF) are well documented, the relationship between them is unknown. We exploited the known influence of visual motion on the apparent positions of targets, and measured how this illusion affects saccadic eye movements during FEF microstimulation. Without microstimulation, saccades to a moving grating are biased in the direction of motion, consistent with the apparent position illusion. Here we show that microstimulation of spatially aligned FEF representations increases the influence of this illusion on saccades. Rather than simply impose a fixed-vector signal, subthreshold stimulation directed saccades away from the FEF movement field, and instead more strongly in the direction of visual motion. These results demonstrate that the attentional effects of FEF stimulation govern visually guided saccades, and suggest that the two roles of the FEF work together to select both the features of a target and the appropriate movement to foveate it.

Two distinct visual motion mechanisms for smooth pursuit: evidence from individual differences

Smooth-pursuit eye velocity to a moving target is more accurate after an initial catch-up saccade than before, an enhancement that is poorly understood. We present an individual-differences-based method for identifying mechanisms underlying a physiological response and use it to test whether visual motion signals driving pursuit differ pre- and postsaccade. Correlating moment-to-moment measurements of pursuit over time with two psychophysical measures of speed estimation during fixation, we find two independent associations across individuals. Presaccadic pursuit acceleration is predicted by the precision of low-level (motion-energy-based) speed estimation, and postsaccadic pursuit precision is predicted by the precision of high-level (position-tracking) speed estimation. These results provide evidence that a low-level motion signal influences presaccadic acceleration and an independent high-level motion signal influences postsaccadic precision, thus presenting a plausible mechanism for postsaccadic enhancement of pursuit.

Coordination of smooth pursuit and saccade target selection in monkeys

The coordination of saccadic and smooth pursuit eye movements in macaque monkeys was investigated using a target selection paradigm with two moving targets crossing at a center fixation point. A task in which monkeys selected a target based on its color was used to test the hypothesis that common neural signals underlie target selection for pursuit and saccades, as well as testing whether target selection signals are available to the saccade and pursuit systems simultaneously or sequentially. Several combinations of target color, speed, and direction were used. In all cases, smooth pursuit was highly selective for the rewarded target before any saccade occurred. On >80% of the trials, the saccade was directed toward the same target as both pre- and postsaccadic pursuit. The results favor a model in which a shared target selection signal is simultaneously available to both the saccade and pursuit systems, rather than a sequential model.

Directional cuing of target choice in human smooth pursuit eye movements

Perceptual attention and target choice for movement have many features in common. In particular, both generally are based on selection of a particular location in space. To ask whether motor control, like attention, also can exhibit target choice based on nonspatial features of the stimulus, we assessed the initiation of smooth pursuit eye movements when two targets move in different directions after human subjects have been cued which direction or color to track. The direction cue consisted of a patch of dots undergoing either 0% coherent motion or 50% coherent motion in the direction of motion of one of the subsequent targets. After a delay, the fixation spot was extinguished and two spots moved across the same small region of the visual field, one in the cued direction ("target") and one in an orthogonal direction ("distracter"). After the 0% coherent cue, pursuit was approximately the vector average of responses to the two motions presented singly. After the 50% coherent cue, the initial pursuit response was biased strongly toward the target that moved in the cued direction. The impact of the cued direction persisted over delays of up to 1000 ms. Other cues about the direction of upcoming target motion biased the response similarly. Cues about target color also biased pursuit in the direction of motion of the cued target but were considerably less effective than cues indicating the direction of target motion. We conclude that target choice for movement, like perceptual attention, can be based on the features of the chosen target and not only its location in space.

Saccades exert spatial control of motion processing for smooth pursuit eye movements

Saccades modulate the relationship between visual motion and smooth eye movement. Before a saccade, pursuit eye movements reflect a vector average of motion across the visual field. After a saccade, pursuit primarily reflects the motion of the target closest to the endpoint of the saccade. We tested the hypothesis that the saccade produces a spatial weighting of motion around the endpoint of the saccade. Using a moving pursuit stimulus that stepped to a new spatial location just before a targeting saccade, we controlled the distance between the endpoint of the saccade and the position of the moving target. We demonstrate that the smooth eye velocity following the targeting saccade weights the presaccadic visual motion inputs by the distance from their location in space to the endpoint of the saccade, defining the extent of a spatiotemporal filter for driving the eyes. The center of the filter is located at the endpoint of the saccade in space, not at the position of the fovea. The filter is stable in the face of a distracter target, is present for saccades to stationary and moving targets, and affects both the speed and direction of the postsaccadic eye movement. The spatial filter can explain the target-selecting gain change in postsaccadic pursuit, and has intriguing parallels to the process by which perceptual decisions about a restricted region of space are enhanced by attention. The effect of the spatial saccade plan on the pursuit response to a given retinal motion describes the dynamics of a coordinate transformation.

Attention and selection for predictive smooth pursuit eye movements

Humans cannot typically produce smooth eye movements in the absence of a moving stimulus. However, they can produce predictive smooth eye movements if they expect a target of a known velocity to reappear. Here, we observed that participants could extract velocity information from two simultaneously presented moving targets in order to produce a subsequent predictive smooth eye movement for one of the two targets. Subjects fixated a stationary cross during the presentation of two targets, moving rightward at different velocities. In the next presentation, a single target was presented, which participants tracked with their eyes. A static cue, presented 700 ms before the moving target, indicated which of the two targets would be presented. Predictive eye movements were of an appropriate velocity, even when participants did not know in advance which of the two targets would subsequently be cued. However, the scaling of predictive eye velocity was marginally less accurate in this divided attention condition than when participants knew the identity of the cued target in advance, or a single target was presented during fixation. In a second experiment, we found that the velocity cued on the previous trial had a greater effect than the uncued velocity on the current trial. The negligible effect of the uncued velocity indicates that participants were extremely effective at selectively reproducing one of two recently viewed velocities. However, other influences, such as past history, also affected predictive smooth eye movements.

Coordination of smooth pursuit and saccades

Smooth pursuit and saccades are two components of tracking eye movements. Their coordination has usually been studied by investigating latencies of pursuit onset in response to a moving target appearing simultaneously with the disappearance of the stationary fixation target. The general finding from such studies has been that latencies of saccades and pursuit are different and reflect independent processes. We discuss several limitations of the used targets. In this paper, we study latencies of saccades and smooth pursuit in response to a moving target that overlaps in time with a pursued moving target. We find that saccades and pursuit changes are synchronized. Furthermore, pursuit changes are made fast. Directional changes occur almost entirely within the accompanying saccade. To explain the results we hypothesize a two-stage mechanism for the coordinated generation of saccades and pursuit.

Spatial consequences of bridging the saccadic gap

We report six experiments suggesting that conscious perception is actively redrafted to take account of events both before and after the event that is reported. When observers saccade to a stationary object they overestimate its duration, as if the brain were filling in the saccadic gap with the post-saccadic image. We first demonstrate that this illusion holds for moving objects, implying that the perception of time, velocity, and distance traveled become discrepant. We then show that this discrepancy is partially resolved up to 500 ms after a saccade: the perceived offset position of a post-saccadic moving stimulus shows a greater forward mislocalization when pursued after a saccade than during pursuit alone. These data are consistent with the idea that the temporal bias is resolved by the subsequent spatial adjustment to provide a percept that is coherent in its gist but inconsistent in its detail.

Direct Evidence for a Position Input to the Smooth Pursuit System

When objects move in our environment, the orientation of the visual axis in space requires the coordination of two types of eye movements: saccades and smooth pursuit. The principal input to the saccadic system is position error, whereas it is velocity error for the smooth pursuit system. Recently, it has been shown that catch-up saccades to moving targets are triggered and programmed by using velocity error in addition to position error. Here, we show that, when a visual target is flashed during ongoing smooth pursuit, it evokes a smooth eye movement toward the flash. The velocity of this evoked smooth movement is proportional to the position error of the flash; it is neither influenced by the velocity of the ongoing smooth pursuit eye movement nor by the occurrence of a saccade, but the effect is absent if the flash is ignored by the subject. Furthermore, the response started around 85 ms after the flash presentation and decayed with an average time constant of 276 ms. Thus this is the first direct evidence of a position input to the smooth pursuit system. This study shows further evidence for a coupling between saccadic and smooth pursuit systems. It also suggests that there is an interaction between position and velocity error signals in the control of more complex movements.

A single control system for smooth and saccade-like pursuit in blowflies

During courtship, male blowflies perform aerobatic pursuits that rank among the fastest visual behaviours that can be observed in nature. The viewing strategies during pursuit behaviour of blowflies appear to be very similar to eye movements during pursuit in primates: a combination of smooth pursuit and catch-up saccades. Whereas in primates these two components of pursuit eye movements are thought to be controlled by distinct oculomotor subsystems, we present evidence that in blowflies both types of pursuit responses can be produced by a single control system. In numerical simulations of chasing behaviour the proposed control system generates qualitatively the same behaviour as with real blowflies. As a consequence of time constants in the control system, mimicking neuronal processing times, muscular dynamics and inertia, saccade-like changes in gaze direction are generated if the target is displaced rapidly on the pursuing fly's retina. In the behavioural context of visual pursuit, saccade-like changes of the fly's gaze direction can thus be parsimoniously explained as an emergent property of a smooth pursuit system without assuming a priori different mechanisms underlying smooth and saccadic tracking behaviour.

Discharge properties of MST neurons that project to the frontal pursuit area in macaque monkeys

We have used antidromic activation to determine the functional discharge properties of neurons that project to the frontal pursuit area (FPA) from the medial-superior temporal visual area (MST). In awake rhesus monkeys, MST neurons were considered to be activated antidromically if they emitted action potentials at fixed, short latencies after stimulation in the FPA and if the activation passed the collision test. Antidromically activated neurons (n = 37) and a sample of the overall population of MST neurons (n = 110) then were studied during pursuit eye movements across a dark background and during laminar motion of a large random-dot texture and optic flow expansion and contraction during fixation. Antidromically activated neurons showed direction tuning during pursuit (25/37), during laminar image motion (21/37), or both (16/37). Of 27 neurons tested with optic flow stimuli, 14 showed tuning for optic flow expansion (n = 10) or contraction (n = 4). There were no statistically significant differences in the response properties of the antidromically activated and control samples. Preferred directions for pursuit and laminar image motion did not show any statistically significant biases, and the preferred directions for eye versus image motion in each sample tended to be equally divided between aligned and opposed. There were small differences between the control and antidromically activated populations in preferred speeds for laminar motion and optic flow; these might have reached statistical significance with larger samples of antidromically activated neurons. We conclude that the population of MST neurons projecting to the FPA is highly diverse and quite similar to the general population of neurons in MST.

Smooth pursuit tracking of an abrupt change in target direction: vector superposition of discrete responses

The directional control of smooth pursuit eye movements was studied by presenting human subjects with targets that moved in a straight line at a constant speed and then changed direction abruptly and unpredictably. To minimize the probability of saccadic responses in the interval following the target's change in direction, target position was offset so as to eliminate position error after the reaction time. Smooth pursuit speed declined at a latency of 90 ms, whereas the direction of smooth pursuit began to change later (130 ms). The amplitude of the offset in target position did not affect the subsequent smooth pursuit response. In other experiments, the target's speed or acceleration was changed abruptly at the time of the change in direction. Step changes in speed elicited short-latency responses in smooth pursuit tracking but step changes in acceleration did not. In all instances, the earliest component of the response did not depend on the parameters of the stimulus. The data were fit with a model in which smooth pursuit resulted from the vector addition of two components, one representing a response to the arrest of the initial target motion and the other the response to the onset of target motion in the new direction. This model gave an excellent fit but further analysis revealed nonlinear interactions between the two vector components. These interactions represented directional anisotropies both in terms of the initial tracking direction (which was either vertical or 45 degrees ) and in terms of the cardinal directions (vertical and horizontal).

Involving the motor system in decision making

The control of behaviour is usually understood in terms of three distinct components: sensory processing, decision making and movement control. Recently, this view has been questioned on the basis of physiological and behavioural data, blurring the distinction between these three stages. This raises the question to what extent the motor system itself can contribute to the interpretation of behavioural situations. To investigate this question we use a neural model of sensory motor integration applied to a behaving mobile robot performing a navigation task. We show that the population response of the motor system provides a substrate for the categorization of behavioural situations. This categorization allows for the assessment of the complexity of a behavioural situation and regulates whether higher-level decision making is required to resolve behavioural conflicts. Our model lends credence to an emerging reconceptualization of behavioural control where the motor system can be considered as part of a high-level perceptual system.

Recasting the Smooth Pursuit Eye Movement System

Primates use a combination of smooth pursuit and saccadic eye movements to stabilize the retinal image of selected objects within the high-acuity region near the fovea. Pursuit has traditionally been viewed as a relatively automatic behavior, driven by visual motion signals and mediated by pathways that connect visual areas in the cerebral cortex to motor regions in the cerebellum. However, recent findings indicate that this view needs to be reconsidered. Rather than being controlled primarily by areas in extrastriate cortex specialized for processing visual motion, pursuit involves an extended network of cortical areas, and, of these, the pursuit-related region in the frontal eye fields appears to exert the most direct influence. The traditional pathways through the cerebellum are important, but there are also newly identified routes involving structures previously associated with the control of saccades, including the basal ganglia, the superior colliculus, and nuclei in the brain stem reticular formation. These recent findings suggest that the pursuit system has a functional architecture very similar to that of the saccadic system. This viewpoint provides a new perspective on the processing steps that occur as descending control signals interact with circuits in the brain stem and cerebellum responsible for gating and executing voluntary eye movements. Although the traditional view describes pursuit and saccades as two distinct neural systems, it may be more accurate to consider the two movements as different outcomes from a shared cascade of sensory–motor functions.

Shared response preparation for pursuit and saccadic eye movements

Tracking a single target in the visual world requires coordination between pursuit and saccadic eye movements. The constraints imposed on pursuit and saccade decisions by visual processing and response preparation are difficult to compare because latency differences between the two movements provide different amounts of visual sampling time. The present study compares pursuit and saccade decisions when visual processing was directly manipulated. Human observers were asked to select between two stationary stimuli presented simultaneously at two different locations based on which had the higher contrast. The stimuli were presented for a brief, variable interval and then occluded by masks. Because the masks moved horizontally and were offset vertically, subjects were obliged to make both pursuit and saccadic eye movements to track the mask covering the target stimulus. For each of the exposure durations, we constructed oculometric curves for pursuit and saccades. We found that both systems had similar oculometric thresholds and response biases. The initial pursuit decisions differed from the subsequent saccade decisions on 1-13% of the trials but were the same more often than predicted by independent mechanisms. Moreover, pursuit reversed direction on discordant trials, so that the pursuit decision always matched that of the saccade by the time the saccade was started. These results support the view that, in addition to overlap in early visual areas and the final motor pathways, the pursuit and saccadic systems share processing at the level of response preparation. This shared processing may help ensure the coordination of pursuit and saccadic eye movements in selecting a single target.

Visuomotor origins of covert spatial attention

Covert spatial attention produces biases in perceptual performance and neural processing of behaviorally relevant stimuli in the absence of overt orienting movements. The neural mechanism that gives rise to these effects is poorly understood. This paper surveys past evidence of a relationship between oculomotor control and visual spatial attention and more recent evidence of a causal link between the control of saccadic eye movements by frontal cortex and covert visual selection. Both suggest that the mechanism of covert spatial attention emerges as a consequence of the reciprocal interactions between neural circuits primarily involved in specifying the visual properties of potential targets and those involved in specifying the movements needed to fixate them.

Shared response preparation for pursuit and saccadic eye movements

Tracking a single target in the visual world requires coordination between pursuit and saccadic eye movements. The constraints imposed on pursuit and saccade decisions by visual processing and response preparation are difficult to compare because latency differences between the two movements provide different amounts of visual sampling time. The present study compares pursuit and saccade decisions when visual processing was directly manipulated. Human observers were asked to select between two stationary stimuli presented simultaneously at two different locations based on which had the higher contrast. The stimuli were presented for a brief, variable interval and then occluded by masks. Because the masks moved horizontally and were offset vertically, subjects were obliged to make both pursuit and saccadic eye movements to track the mask covering the target stimulus. For each of the exposure durations, we constructed oculometric curves for pursuit and saccades. We found that both systems had similar oculometric thresholds and response biases. The initial pursuit decisions differed from the subsequent saccade decisions on 1-13% of the trials but were the same more often than predicted by independent mechanisms. Moreover, pursuit reversed direction on discordant trials, so that the pursuit decision always matched that of the saccade by the time the saccade was started. These results support the view that, in addition to overlap in early visual areas and the final motor pathways, the pursuit and saccadic systems share processing at the level of response preparation. This shared processing may help ensure the coordination of pursuit and saccadic eye movements in selecting a single target.

Rapid olfactory processing implicates subcortical control of an olfactomotor system

Sniffs are modulated in response to odor content. Higher concentrations of odor induce lesser-volume sniffs. This phenomenon implicates a neural feedback mechanism that measures sensory input (odor concentration) and modulates motor output (sniffing) accordingly. Here we used air-dilution olfactometry to probe the time course of this olfactomotor mechanism. A stainless-steel computer-controlled olfactometer, equipped with mass flow controllers, temperature and humidity control, and on-line photo-ionization detection, was coupled to a highly sensitive pneumatotachograph that measured nasal flow. The olfactometer was used to generate four ascending concentrations of the odorants propionic acid and phenethyl alcohol. Sniff volume was inversely related to odor concentration (P > 0.0001). Sniffs were uniform and concentration independent for the initial 150 ms but acquired a concentration-dependent flowrate as early as 160 ms following sniff onset for propionic acid (P > 0.05) and 260 ms for phenethyl alcohol (P > 0.05). Considering that odorant transduction takes around 150 ms and odorant-induced cortical evoked potentials have latencies of around 300 ms, the rapid motor adjustments measured here suggest that olfactomotor sniff feedback control is subcortical and may rely on neural mechanisms similar to those that modulate eye movements to accommodate vision and ear movements to accommodate audition.

Neural correlates of decision processes: neural and mental chronometry

Recent studies aim to explain the duration and variability of behavioral reaction time in terms of neural processes. The time taken to make choices is occupied by at least two processes. Neurons in sensorimotor structures accumulate evidence that leads to alternative categorizations, while other neurons within these structures prepare and initiate overt responses. These distinct stages of stimulus encoding and response preparation support variable but flexible behavior.