Similarity in the response of smooth pursuit and manual tracking to a change in the direction of target motion

Eye-hand coordination all the way: from discrete to continuous hand movements

The differentiation between continuous and discrete actions is key for behavioral neuroscience. Although many studies have characterized eye-hand coordination during discrete (e.g., reaching) and continuous (e.g., pursuit tracking) actions, all these studies were conducted separately, using different setups and participants. In addition, how eye-hand coordination might operate at the frontier between discrete and continuous movements remains unexplored. Here we filled these gaps by means of a task that could elicit different movement dynamics. Twenty-eight participants were asked to simultaneously track with their eyes and a joystick a visual target that followed an unpredictable trajectory and whose position was updated at different rates (from 1.5 to 240 Hz). This procedure allowed us to examine actions ranging from discrete point-to-point movements (low refresh rate) to continuous pursuit (high refresh rate). For comparison, we also tested a manual tracking condition with the eyes fixed and a pure eye tracking condition (hand fixed). The results showed an abrupt transition between discrete and continuous hand movements around 3 Hz contrasting with a smooth trade-off between fixations and smooth pursuit. Nevertheless, hand and eye tracking accuracy remained strongly correlated, with each of these depending on whether the other effector was recruited. Moreover, gaze-cursor distance and lag were smaller when eye and hand performed the task conjointly than separately. Altogether, despite some dissimilarities in eye and hand dynamics when transitioning between discrete and continuous movements, our results emphasize that eye-hand coordination continues to smoothly operate and support the notion of synergies across eye movement types.NEW & NOTEWORTHY The differentiation between continuous and discrete actions is key for behavioral neuroscience. By using a visuomotor task in which we manipulate the target refresh rate to trigger different movement dynamics, we explored eye-hand coordination all the way from discrete to continuous actions. Despite abrupt changes in hand dynamics, eye-hand coordination continues to operate via a gradual trade-off between fixations and smooth pursuit, an observation confirming the notion of synergies across eye movement types.

Bayesian approaches to smooth pursuit of random dot kinematograms: effects of varying RDK noise and the predictability of RDK direction

Smooth pursuit eye movements respond on the basis of both immediate and anticipated target motion, where anticipations may be derived from either memory or perceptual cues. To study the combined influence of both immediate sensory motion and anticipation, subjects pursued clear or noisy random dot kinematograms (RDKs) whose mean directions were chosen from Gaussian distributions with SDs = 10° (narrow prior) or 45° (wide prior). Pursuit directions were consistent with Bayesian theory in that transitions over time from dependence on the prior to near total dependence on immediate sensory motion (likelihood) took longer with the noisier RDKs and with the narrower, more reliable, prior. Results were fit to Bayesian models in which parameters representing the variability of the likelihood either were or were not constrained to be the same for both priors. The unconstrained model provided a statistically better fit, with the influence of the prior in the constrained model smaller than predicted from strict reliability-based weighting of prior and likelihood. Factors that may have contributed to this outcome include prior variability different from nominal values, low-level sensorimotor learning with the narrow prior, or departures of pursuit from strict adherence to reliability-based weighting. Although modifications of, or alternatives to, the normative Bayesian model will be required, these results, along with previous studies, suggest that Bayesian approaches are a promising framework to understand how pursuit combines immediate sensory motion, past history, and informative perceptual cues to accurately track the target motion that is most likely to occur in the immediate future.NEW & NOTEWORTHY Smooth pursuit eye movements respond on the basis of anticipated, as well as immediate, target motions. Bayesian models using reliability-based weighting of previous (prior) and immediate target motions (likelihood) accounted for many, but not all, aspects of pursuit of clear and noisy random dot kinematograms with different levels of predictability. Bayesian approaches may solve the long-standing problem of how pursuit combines immediate sensory motion and anticipation of future motion to configure an effective response.

Age-related decline of online visuomotor adaptation: a combined effect of deteriorations of motor anticipation and execution

The literature has established that the capability of visuomotor adaptation decreases with aging. However, the underlying mechanisms of this decline are yet to be fully understood. The current study addressed this issue by examining how aging affected visuomotor adaptation in a continuous manual tracking task with delayed visual feedback. To distinguish separate contributions of the declined capability of motor anticipation and deterioration of motor execution to this age-related decline, we recorded and analyzed participants' manual tracking performances and their eye movements during tracking. Twenty-nine older people and twenty-three young adults (control group) participated in this experiment. The results showed that the age-related decline of visuomotor adaptation was strongly linked to degraded performance in predictive pursuit eye movement, indicating that declined capability motor anticipation with aging had critical influences on the age-related decline of visuomotor adaptation. Additionally, deterioration of motor execution, measured by random error after controlling for the lag between target and cursor, was found to have an independent contribution to the decline of visuomotor adaptation. Taking these findings together, we see a picture that the age-related decline of visuomotor adaptation is a joint effect of the declined capability of motor anticipation and the deterioration of motor execution with aging.

The perceptual dynamics of the contrast induced speed bias

In this article we present a temporal extension of the slow motion prior model to generate predictions regarding the temporal evolution of the contrast induced speed bias. We further tested these predictions using a novel experimental paradigm that allows us to measure the dynamic perceptual difference between stimuli through a series of manual pursuit open loop tasks. Results show good agreement with our model's predictions. The main findings reveal that hand speed dynamics are affected by stimulus contrast in a way that is consistent with a dynamic model of motion perception that assumes a slow motion prior. The proposed model also confirms observations made in previous studies that suggest that motion bias persisted even at high contrast as a consequence of the dynamics of the slow motion prior.

Eye-hand decoupling decreases visually guided reaching independently of posture but reduces sway while standing: Evidence for supra-postural control

We investigated whether visually guided reaching differs for sitting and standing postures while the eyes and hand are coupled to move in the same direction or decoupled to move in opposite directions. We also investigated how coupled and decoupled reaching tasks influenced standing postural control. Eighteen healthy young adults (M = 21 years) moved a cursor using finger movements along a vertical touchscreen while sitting or standing. In an eye-hand coupling (EH) task, participants moved their finger/cursor from a central target to a peripheral target located either up, down, left, or right. In an eye-hand decoupling (EHD) task, participant's finger movement moved the cursor in the opposite direction. Sway measures during the standing condition and kinematic variables for the cursor offered insight into whole-body control. Performances in EH revealed smaller errors and faster movements than EHD regardless of postural condition. Similar hand movements existed between sitting and standing when accounting for task, while greater variability in absolute endpoint errors existed for standing than sitting when task was ignored. Less postural sway existed for EHD than EH when standing. These data provide evidence that when participants decoupled the eyes and hand movement direction while standing, they attenuated sway to support control of this complex, cognitively demanding, visuomotor task.

Clinical Characterization of Oculomotricity in Children with and without Specific Learning Disorders

Children with specific learning disorders have been associated with oculomotor problems, with their analysis even suggested to be a potential diagnostic tool. A prospective non-randomized comparative study evaluating 59 children (6–13 years old) divided into three groups was conducted: a control group (CG) including 15 healthy emmetropic children; a group of 18 healthy children with oculomotor abnormalities (OAG); and a group of 26 children diagnosed with specific learning disorders (LDG). In all groups, besides a complete eye exam, oculomotricity was characterized with two clinical tests: Northeastern State University College of Optometry’s Oculomotor (NSUCO) and Developmental Eye Movement (DEM) tests. Concerning the NSUCO test, lower ability, precision, and head/body movement associated scorings were obtained for both smooth pursuits and saccades in OAG and LDG when compared to the CG (p < 0.001). Likewise, significantly longer time needed to read the horizontal sheet of the DEM test and a higher DEM ratio were found in OAG and LDG compared to CG (p ≤ 0.003). No differences between LDG and OAG were found in the performance with the two oculomotor tests (p ≥ 0.141). Oculomotor anomalies can be present in children with and without specific learning disorders, and therefore cannot be used as diagnostic criteria of these type of disorders.

Neurofunctional correlates of eye to hand motor transfer

This work investigates the transfer of motor learning from the eye to the hand and its neural correlates by using functional magnetic resonance imaging (fMRI) and a sensorimotor task consisting of the continuous tracking of a virtual target. In pretraining evaluation, all the participants (experimental and control group) performed the tracking task inside an MRI scanner using their right hand and a joystick. After which, the experimental group practiced an eye-controlled version of the task for 5 days using an eye tracking system outside the MRI environment. Post-training evaluation was done 1 week after the first scanning session, where all the participants were scanned again while repeating the manual pretraining task. Behavioral results show that the training in the eye-controlled task produced a better performance not only in the eye-controlled modality (motor learning) but also in the hand-controlled modality (motor transfer). Neural results indicate that eye to hand motor transfer is supported by the motor cortex, the basal ganglia and the cerebellum, which is consistent with previous research focused on other effectors. These results may be of interest in neurorehabilitation to activate the motor systems and help in the recovery of motor functions in stroke or movement disorder patients.

Predictive Smooth Pursuit Eye Movements

Smooth pursuit eye movements maintain the line of sight on smoothly moving targets. Although often studied as a response to sensory motion, pursuit anticipates changes in motion trajectories, thus reducing harmful consequences due to sensorimotor processing delays. Evidence for predictive pursuit includes (a) anticipatory smooth eye movements (ASEM) in the direction of expected future target motion that can be evoked by perceptual cues or by memory for recent motion, (b) pursuit during periods of target occlusion, and (c) improved accuracy of pursuit with self-generated or biologically realistic target motions. Predictive pursuit has been linked to neural activity in the frontal cortex and in sensory motion areas. As behavioral and neural evidence for predictive pursuit grows and statistically based models augment or replace linear systems approaches, pursuit is being regarded less as a reaction to immediate sensory motion and more as a predictive response, with retinal motion serving as one of a number of contributing cues.

Visualization and quantification of eye tracking data for the evaluation of oculomotor function

Oculomotor dysfunction may originate from physical, physiological or psychological causes and may be a marker for schizophrenia or other disorders. Observational tests for oculomotor dysfunction are easy to administer, but are subjective and transient, and it is difficult to quantify deviations. To date, video-based eye tracking systems have not provided a contextual overview of gaze data that integrates the eye video recording with the stimulus and gaze data together with quantitative feedback of metrics in relation to typical values. A system was developed with an interactive timeline to allow the analyst to scroll through a recording frame-by-frame while comparing data from three different sources. The visual and integrated nature of the analysis allows localisation and quantification of saccadic under- and overshoots as well as determination of the frequency and amplitude of catch-up and anticipatory saccades. Clinicians will be able to apply their expertise to diagnose disorders based on abnormal patterns in the gaze plots. They can use the line charts to quantify deviations from benchmark values for reaction time, saccadic accuracy and smooth pursuit gain. A clinician can refer to the eye video at any time to confirm that observed deviations originated from gaze behaviour and not from systemic errors.

Using Smooth Pursuit Calibration for Difficult-to-Calibrate Participants

Although the 45-dots calibration routine of a previous study ( 2) provided very good accuracy, it requires intense mental effort and the routine proved to be unsuccessful for young children who struggle to maintain concentration. The calibration procedures that are normally used for difficult-to-calibrate participants, such as autistic children and infants, do not suffice since they are not accurate enough and the reliability of research results might be jeopardised. Smooth pursuit has been used before for calibration and is applied in this paper as an alternative routine for participants who are difficult to calibrate with conventional routines. Gaze data is captured at regular intervals and many calibration targets are generated while the eyes are following a moving target. The procedure could take anything between 30 s and 60 s to complete, but since an interesting target and/or a conscious task may be used, participants are assisted to maintain concentration. It was proven that the accuracy that can be attained through calibration with a moving target along an even horizontal path is not significantly worse than the accura-cy that can be attained with a standard method of watching dots appearing in random order. The routine was applied successfully for a group of children with ADD, ADHD and learning abilities. This result is important as it provides for easier calibration - especially in the case of participants who struggle to keep their gaze focused and stable on a stationary target for long enough.

Limited Contribution of Primary Motor Cortex in Eye-Hand Coordination: A TMS Study

The ability to track a moving target with the eye is substantially improved when the target is self-moved compared with when it is moved by an external agent. To account for this observation, it has been postulated that the oculomotor system has access to hand efference copy, thereby allowing to predict the motion of the visual target. Along this scheme, we tested the effect of transcranial magnetic stimulation (TMS) over the hand area of the primary motor cortex (M1) when human participants (50% females) are asked to track with their eyes a visual target whose horizontal motion is driven by their grip force. We reasoned that, if the output of M1 is used by the oculomotor system to keep track of the target, on top of inducing short latency disturbance of grip force, single-pulse TMS should also quickly disrupt ongoing eye motion. For comparison purposes, the effect of TMS over M1 was monitored when subjects tracked an externally moved target (while keeping their hand at rest or not). In both cases, results showed no alterations in smooth pursuit, meaning that its velocity was unaffected within the 25-125 ms epoch that followed TMS. Overall, our results imply that the output of M1 has limited contribution in driving the eye motion during our eye-hand coordination task. This study suggests that, if hand motor signals are accessed by the oculomotor system, this is upstream of M1.SIGNIFICANCE STATEMENT The ability to coordinate eye and hand actions is central in everyday activity. However, the neural mechanisms underlying this coordination remain to be clarified. A leading hypothesis is that the oculomotor system has access to hand motor signals. Here we explored this possibility by means of transcranial magnetic stimulation (TMS) over the hand area of the primary motor cortex (M1) when humans tracked with the eyes a visual target that was moved by the hand. As expected, ongoing hand action was perturbed 25-30 ms after TMS, but our results fail to show any disruption of eye motion, smooth pursuit velocity being unaffected. This work suggests that, if hand motor signals are accessed by the oculomotor system, this is upstream of M1.

How Saccade Intrusions Affect Subsequent Motor and Oculomotor Actions

In daily activities, there is a close spatial and temporal coupling between eye and hand movements that enables human beings to perform actions smoothly and accurately. If this coupling is disrupted by inadvertent saccade intrusions, subsequent motor actions suffer from delays, and lack of coordination. To examine how saccade intrusions affect subsequent voluntary actions, we used two tasks that require subjects to make motor/oculomotor actions in response to a visual cue. One was the memory guided saccade (MGS) task, and the other the hand reaction time (RT) task. The MGS task required subjects to initiate a voluntary saccade to a memorized target location, which is indicated shortly before by a briefly presented cue. The RT task required subjects to release a button on detection of a visual target, while foveating on a central fixation point. In normal subjects of various ages, inadvertent saccade intrusions delayed subsequent voluntary motor, and oculomotor actions. We also studied patients with Parkinson's disease (PD), who are impaired not only in initiating voluntary saccades but also in suppressing unwanted reflexive saccades. Saccade intrusions also delayed hand RT in PD patients. However, MGS was affected by the saccade intrusion differently. Saccade intrusion did not delay MGS latency in PD patients who could perform MGS with a relatively normal latency. In contrast, in PD patients who were unable to initiate MGS within the normal time range, we observed slightly decreased MGS latency after saccade intrusions. What explains this paradoxical phenomenon? It is known that motor actions slow down when switching between controlled and automatic behavior. We discuss how the effect of saccade intrusions on subsequent voluntary motor/oculomotor actions may reflect a similar switching cost between automatic and controlled behavior and a cost for switching between different motor effectors. In contrast, PD patients were unable to initiate internally guided MGS in the absence of visual target and could perform only automatic visually guided saccades, and did not have to switch between automatic and controlled behavior. This lack of switching may explain the shortening of MGS latency by the saccade intrusion in PD patients.

Manual tracking enhances smooth pursuit eye movements

Previous studies have reported that concurrent manual tracking enhances smooth pursuit eye movements only when tracking a self-driven or a predictable moving target. Here, we used a control-theoretic approach to examine whether concurrent manual tracking enhances smooth pursuit of an unpredictable moving target. In the eye-hand tracking condition, participants used their eyes to track a Gaussian target that moved randomly along a horizontal axis. In the meantime, they used their dominant hand to move a mouse to control the horizontal movement of a Gaussian cursor to vertically align it with the target. In the eye-alone tracking condition, the target and cursor positions recorded in the eye-hand tracking condition were replayed, and participants only performed eye tracking of the target. Catch-up saccades were identified and removed from the recorded eye movements, allowing for a frequency-response analysis of the smooth pursuit response to unpredictable target motion. We found that the overall smooth pursuit gain was higher and the number of catch-up saccades made was less when eye tracking was accompanied by manual tracking than when not. We conclude that concurrent manual tracking enhances smooth pursuit. This enhancement is a fundamental property of eye-hand coordination that occurs regardless of the predictability of the target motion.

Informational constraints on spontaneous visuomotor entrainment

Past research has revealed that an individual's rhythmic limb movements become spontaneously entrained to an environmental rhythm if visual information about the rhythm is available and its frequency is near that of the individual's movements. Research has also demonstrated that if the eyes track an environmental stimulus, the spontaneous entrainment to the rhythm is strengthened. One hypothesis explaining this enhancement of spontaneous entrainment is that the limb movements and eye movements are linked through a neuromuscular coupling or synergy. Another is that eye-tracking facilitates the pick up of important coordinating information. Experiment 1 investigated the first hypothesis by evaluating whether any rhythmic movement of the eyes would facilitate spontaneous entrainment. Experiments 2 and 3 (respectively) explored whether eye-tracking strengthens spontaneous entrainment by allowing the pickup of trajectory direction change information or allowing an increase in the amount of information to be picked-up. Results suggest that the eye-tracking enhancement of spontaneous entrainment is a consequence of increasing the amount of information available to be picked-up.

Interaction between the premotor processes of eye and hand movements: possible mechanism underlying eye-hand coordination

Interaction between the execution process of eye movement and that of hand movement must be indispensable for eye-hand coordination. The present study investigated corticospinal excitability in the hand muscles during the premotor processes of eye and/or hand movement to elucidate interaction between these processes. Healthy humans performed a precued reaction task of eye and/or finger movement and motor-evoked potentials in the hand muscles were evoked in the reaction time. Leftward eye movement suppressed corticospinal excitability in the right abductor digiti minimi muscle only when little finger abduction was simultaneously executed. Corticospinal excitability in the first dorsal interosseous muscle was not suppressed by eye movement regardless of whether or not it was accompanied by finger movement. Suppression of corticospinal excitability in the hand muscles induced by eye movement in the premotor period depends on the direction of eye movement, the muscle tested, and the premotor process of the tested muscle. The suppression may reflect interaction between the motor process of eye movement and that of hand movement particularly active during eye-hand coordination tasks during which both processes proceed.

A three-component model of the control error in manual tracking of continuous random signals

OBJECTIVE

The performance of human operators acting within closed-loop control systems is investigated in a classic tracking task. The dependence of the control error (tracking error) on the parameters display gain, k(display), and input signal frequency bandwidth, f(g), which alter task difficulty and presumably the control delay, is studied with the aim of functionally specifying it via a model.

BACKGROUND

The human operator as an element of a cascaded human-machine control system (e.g., car driving or piloting an airplane) codetermines the overall system performance. Control performance of humans in continuous tracking has been described in earlier studies.

METHOD

Using a handheld joystick, 10 participants tracked continuous random input signals. The parameters f(g) and k(display) were altered between experiments.

RESULTS

Increased task difficulty promoted lengthened control delay and, consequently, increased control error.Tracking performance degraded profoundly with target deflection components above 1 Hz, confirming earlier reports.

CONCLUSION

The control error is composed of a delay-induced component, a demand-based component, and a novel component: a human tracking limit. Accordingly, a new model that allows concepts of the observed control error to be split into these three components is suggested.

APPLICATION

To achieve optimal performance in control systems that include a human operator (e.g., vehicles, remote controlled rovers, crane control), (a) tasks should be kept as simple as possible to achieve shortest control delays, and (b) task components requiring higher-frequency (> 1 Hz) tracking actions should be avoided or automated by technical systems.

Kinematic property of target motion conditions gaze behavior and eye-hand synergy during manual tracking

This study investigated how frequency demand and motion feedback influenced composite ocular movements and eye-hand synergy during manual tracking. Fourteen volunteers conducted slow and fast force-tracking in which targets were displayed in either line-mode or wave-mode to guide manual tracking with target movement of direct position or velocity nature. The results showed that eye-hand synergy was a selective response of spatiotemporal coupling conditional on target rate and feedback mode. Slow and line-mode tracking exhibited stronger eye-hand coupling than fast and wave-mode tracking. Both eye movement and manual action led the target signal during fast-tracking, while the latency of ocular navigation during slow-tracking depended on the feedback mode. Slow-tracking resulted in more saccadic responses and larger pursuit gains than fast-tracking. Line-mode tracking led to larger pursuit gains but fewer and shorter gaze fixations than wave-mode tracking. During slow-tracking, incidences of saccade and gaze fixation fluctuated across a target cycle, peaking at velocity maximum and the maximal curvature of target displacement, respectively. For line-mode tracking, the incidence of smooth pursuit was phase-dependent, peaking at velocity maximum as well. Manual behavior of slow or line-mode tracking was better predicted by composite eye movements than that of fast or wave-mode tracking. In conclusion, manual tracking relied on versatile visual strategies to perceive target movements of different kinematic properties, which suggested a flexible coordinative control for the ocular and manual sensorimotor systems.

Following and intercepting scribbles: interactions between eye and hand control

The smooth pursuit eye movement system appears to be importantly engaged during the planning and execution of interceptive hand movements. The present study sought to probe the interaction between eye and hand control systems by examining their responses during an interception task that included target speed perturbations. On 2/3 of trials, the target increased or decreased speed at various times, ranging from about 300 ms before to 150 ms after the onset of a finger movement directed to intercept the target and was triggered by a GO signal. Additionally, the same 2D sum-of-sines target trajectories were followed with the eyes without interception. The smooth pursuit system responded more quickly if the target speed perturbation occurred earlier during the reaction time (i.e., near the time of the GO signal). Similarly, the finger movement began more quickly if target speed was increased earlier during the reaction time. For early perturbation conditions, the initial direction of the finger movement matched the predicted target intercept using the new target speed. For perturbations occurring after finger movement, onset initial direction of finger movement did not match target interception such that the finger path began to curve toward the perturbed target after about 150-200 ms. The results support the idea of an active process of visual target path extrapolation simultaneously used to guide both the eye and hand.

Fear of heights: cognitive performance and postural control

INTRODUCTION

Fear of heights, or acrophobia, is one of the most frequent subtypes of specific phobia frequently associated to depression and other anxiety disorders. Previous evidence suggests a correlation between acrophobia and abnormalities in balance control, particularly involving the use of visual information to keep postural stability. This study investigates the hypotheses that (1) abnormalities in balance control are more frequent in individuals with acrophobia even when not exposed to heights, that (2) acrophobic symptoms are associated to abnormalities in visual perception of movement; and that (3) individuals with acrophobia are more sensitive to balance-cognition interactions.

METHOD

Thirty-one individuals with specific phobia of heights and thirty one non-phobic controls were compared using dynamic posturography and a manual tracking task.

RESULTS

Acrophobics had poorer performance in both tasks, especially when carried out simultaneously. Previously described interference between posture control and cognitive activity seems to play a major role in these individuals.

DISCUSSION

The presence of physiologic abnormalities is compatible with the hypothesis of a non-associative acquisition of fear of heights, i.e., not associated to previous traumatic events or other learning experiences. Clinically, this preliminary study corroborates the hypothesis that vestibular physical therapy can be particularly useful in treating individuals with fear of heights.

Pursuit eye movements involve a covert motor plan for manual tracking

When we make an aiming movement toward a moving visual object, eye-hand coupling is of paramount importance for accurate motor performance. Some studies have suggested that both gaze and manual tracking control systems are driven by a common command signal. However, it has never been demonstrated that a motor plan for the arm is produced even when the object is tracked by the eyes alone. By applying transcranial magnetic stimulation to the motor cortex, we show for the first time that ocular tracking is linked to an overall decrease in the excitability of the motor control system of the relaxed upper limb, as estimated from the amplitude of the motor evoked potentials recorded in contralateral hand and wrist muscles. Furthermore, this reduced excitability is modulated in a manner compatible with a subthreshold neural activation encoding a manual tracking response to the same target pursued by the eyes. In addition, excitability changes are contingent on upper-limb posture, because they are present only with a pronated forearm and not with a supinated hand position. We provide direct evidence that, if the arm is held in a congruent postural configuration, tracking a moving object always entails a coordinated motor plan, which involves both gaze and hand movements. Active inhibitory mechanisms are activated to prevent an overt arm movement, whenever a manual tracking is not requested. Our data provide strong evidence in favor of the existence of a common drive to both eye and hand tracking systems.

Eye-hand interactions in tracing and drawing tasks

We report a preliminary analysis of the interactions between eye and hand during tracing and drawing of four simple shapes. Eye and hand movements were recorded using the ASL 504 system and the Flock of Birds system, respectively. During tracing, pen tip and eye were tightly coupled, with participants making a series of small saccades just in front of the moving pen, interspersed with periods of smooth pursuit. During drawing, saccades were fewer and larger and pursuit was less frequent. Observed eye-hand interactions suggested a bidirectional relationship between the eye and hand. These findings are explained in terms of the differing degree that the two tasks employ visual detail, external or internal cues and eye-hand coordination.

Allocentric cues do not always improve whole body reaching performance

The aim of this investigation was to gain further insight into control strategies used for whole body reaching tasks. Subjects were requested to step and reach to remembered target locations in normal room lighting (LIGHT) and complete darkness (DARK) with their gaze directed toward or eccentric to the remembered target location. Targets were located centrally at three different heights. Eccentric anchors for gaze direction were located at target height and initial target distance, either 30 degrees to the right or 20 degrees to the left of target location. Control trials, where targets remained in place, and remembered target trials were randomly presented. We recorded movements of the hand, eye and head, while subjects stepped and reached to real or remembered target locations. Lateral, vertical and anterior-posterior (AP) hand errors and eye location, and gaze direction deviations were determined relative to control trials. Final hand location errors varied by target height, lighting condition and gaze eccentricity. Lower reaches in the DARK compared to the LIGHT condition were common, and when matched with a tendency to reach above the low target, help explain more accurate reaches for this target in darkness. Anchoring the gaze eccentrically reduced hand errors in the AP direction and increased errors in the lateral direction. These results could be explained by deviations in eye locations and gaze directions, which were deemed significant predictors of final reach errors, accounting for a 17-47% of final hand error variance. Results also confirmed a link between gaze deviations and hand and head displacements, suggesting that gaze direction is used as a common input for movement of the hand and body. Additional links between constant and variable eye deviations and hand errors were common for the AP direction but not for lateral or vertical directions. When combined with data regarding hand error predictions, we found that subjects' alterations in body movement in the AP direction were associated with AP adjustments in their reach, but final hand position adjustments were associated with gaze direction alterations for movements in the vertical and horizontal directions. These results support the hypothesis that gaze direction provides a control signal for hand and body movement and that this control signal is used for movement direction and not amplitude.

Large-field visual motion directly induces an involuntary rapid manual following response

Recent neuroscience studies have been concerned with how aimed movements are generated on the basis of target localization. However, visual information from the surroundings as well as from the target can influence arm motor control, in a manner similar to known effects in postural and ocular motor control. Here, we show an ultra-fast manual motor response directly induced by a large-field visual motion. This rapid response aided reaction when the subject moved his hand in the direction of visual motion, suggesting assistive visually evoked manual control during postural movement. The latency of muscle activity generating this response was as short as that of the ocular following responses to the visual motion. Abrupt visual motion entrained arm movement without affecting perceptual target localization, and the degrees of motion coherence and speed of the visual stimulus modulated this arm response. This visuomotor behavior was still observed when the visual motion was confined to the "follow-through" phase of a hitting movement, in which no target existed. An analysis of the arm movements suggests that the hitting follow through made by the subject is not a part of a reaching movement. Moreover, the arm response was systematically modulated by hand bias forces, suggesting that it results from a reflexive control mechanism. We therefore propose that its mechanism is radically distinct from motor control for aimed movements to a target. Rather, in an analogy with reflexive eye movement stabilizing a retinal image, we consider that this mechanism regulates arm movements in parallel with voluntary motor control.

Oculomotor responses to gradual changes in target direction

Smooth pursuit tracking of targets moving linearly (in one dimension) is well characterized by a model where retinal image motion drives eye acceleration. However, previous findings suggest that this model cannot be simply extended to two-dimensional (2D) tracking. To examine 2D pursuit, in the present study, human subjects tracked a target that moved linearly and then followed the arc of a circle. The subjects' gaze angular velocity accurately matched target angular velocity, but the direction of smooth pursuit always lagged behind the current target direction. Pursuit speed slowly declined after the onset of the curve (for about 500 ms), even though the target speed was constant. In a second experiment, brief perturbations were presented immediately prior to the beginning of the change in direction. The subjects' responses to these perturbations consisted of two components: (1) a response specific to the parameters of the perturbation and (2) a nonspecific response that always consisted of a transient decrease in gaze velocity. With the exception of this nonspecific response, pursuit behavior in response to the gradual changes in direction and to the perturbations could be explained by using retinal slip (image velocity) as the input signal. The retinal slip was parallel and perpendicular to the instantaneous direction of pursuit ultimately resulted in changes in gaze velocity (via gaze acceleration). Perhaps due to the subjects' expectations that the target will curve, the sensitivity to the image motion in the direction of pursuit was not as strong as the sensitivity to image motion perpendicular to gaze velocity.

Fusion of visuo-ocular and vestibular signals in arm motor control

Keeping the finger pointing at an Earth-fixed object during body displacements can be achieved if compensatory arm movements counteract the effect of the rotation on the hand's position in space. Here we investigated the fusion of signals that originated from systems having different neurophysiological properties (i.e., the visuo-oculomotor and vestibular systems) in the production of such compensatory arm movements. To this end, we analyzed the subjects' performance in three conditions that differed according to the information they provided about relative target-body motion. This information originated either from the vestibular or visuo-oculomotor system, or from a combination of the two. To highlight the integration of visuo-oculomotor and vestibular signals, we compared the arm response to motion frequencies presumed to allow or not to allow optimal vestibular and oculomotor responses. When they could be used in isolation, the ocular signals allowed long-latency but precise kinematics control of the arm movement, whereas vestibular signals allowed accurate motor response early in the rotation but their contribution declined as body rotation developed. Optimal performance was obtained throughout the whole movement and for all rotation frequencies when the visuo-oculomotor and vestibular signals could be used together. This increase in hand-tracking performance could not be explained by a unimodal model or an additive model of vestibular and ocular cues, even when using weighted signals. Rather, the results supported a functional model in which vestibular and visuo-oculomotor signals have different influences on the temporal and spatial aspects of hand movement compensating for body motion.

Cortical afferents to the smooth-pursuit region of the macaque monkey’s frontal eye field

In primates, the frontal eye field (FEF) contains separate representations of saccadic and smooth-pursuit eye movements. The smooth-pursuit region (FEFsem) in macaque monkeys lies principally in the fundus and deep posterior wall of the arcuate sulcus, between the FEF saccade region (FEFsac) in the anterior wall and somatomotor areas on the posterior wall and convexity. In this study, cortical afferents to FEFsem were mapped by injecting retrograde tracers (WGA-HRP and fast blue) into electrophysiologically identified FEFsem sites in two monkeys. In the frontal lobe, labeled neurons were found mostly on the ipsilateral side in the (1) supplementary eye field region and lateral area F7; (2) area F2 along the superior limb of the arcuate sulcus; and (3) in the buried cortex of the arcuate sulcus extending along the superior and inferior limbs and including FEFsac and adjacent areas 8, 45, and PMv. Labeled cells were also found in the caudal periprincipal cortex (area 46) in one monkey. Labeled cells were found bilaterally in the frontal lobe in the deep posterior walls of the arcuate sulcus and postarcuate spurs and in cingulate motor areas 24 and 24c. In postcentral cortical areas all labeling was ipsilateral and there were two major foci of labeled cells: (1) the depths of the intraparietal sulcus including areas VIP, LIP, and PEa, and (2) the anterior wall and fundus of the superior temporal sulcus including areas PP and MST. Smaller numbers of labeled cells were found in superior temporal sulcal areas FST, MT, and STP, posterior cingulate area 23b, area 3a within the central sulcus, areas SII, RI, Tpt in the lateral sulcus, and parietal areas 7a, 7b, PEc, MIP, DP, and V3A. Many of these posterior afferent cortical areas code visual-motion (MT, MST, and FST) or visual-motion and vestibular (PP, VIP) signals, consistent with the responses of neurons in FEFsem and with the overall physiology and anatomy of the smooth-pursuit eye movement system.

Deficits in ocular and manual tracking due to episodic ataxia type 2

Four patients with a novel mutation leading to episodic ataxia type 2 were studied in a task that required them to track target motion either with the eyes or with the index finger of the right hand. The target initially moved in a straight line and then changed direction at an unpredictable time by an unpredictable amount. On the day of testing, 3 of the patients were evaluated as normal on a neurological exam, whereas the fourth was severely ataxic. Nevertheless, all 4 showed deficits in tracking behavior with common features. Ocular tracking tended to result in hypermetric saccades at longer than normal latencies. Smooth pursuit tracking was absent in 1 patient and had lower than normal gain in the others. Deficits in manual tracking showed similarities to the deficits in ocular tracking, with hypermetric compensations for changes in target direction. The similarities in the deficits in manual and ocular tracking suggest that they are subject to similar control by the cerebellar structures.

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).

Spatial Transformations for Eye–Hand Coordination

Eye–hand coordination is complex because it involves the visual guidance of both the eyes and hands, while simultaneously using eye movements to optimize vision. Since only hand motion directly affects the external world, eye movements are the slave in this system. This eye– hand visuomotor system incorporates closed-loop visual feedback but here we focus on early feedforward mechanisms that allow primates to make spatially accurate reaches. First, we consider how the parietal cortex might store and update gaze-centered representations of reach targets during a sequence of gaze shifts and fixations. Recent evidence suggests that such representations might be compared with hand position signals within this early gaze-centered frame. However, the resulting motor error commands cannot be treated independently of their frame of origin or the frame of their destined motor command. Behavioral experiments show that the brain deals with the nonlinear aspects of such reference frame transformations, and incorporates internal models of the complex linkage geometry of the eye–head–shoulder system. These transformations are modeled as a series of vector displacement commands, rotated by eye and head orientation, and implemented between parietal and frontal cortex through efficient parallel neuronal architectures. Finally, we consider how this reach system might interact with the visually guided grasp system through both parallel and coordinated neural algorithms.

Internal Models of Target Motion: Expected Dynamics Overrides Measured Kinematics in Timing Manual Interceptions

Prevailing views on how we time the interception of a moving object assume that the visual inputs are informationally sufficient to estimate the time-to-contact from the object's kinematics. Here we present evidence in favor of a different view: the brain makes the best estimate about target motion based on measured kinematics and an a priori guess about the causes of motion. According to this theory, a predictive model is used to extrapolate time-to-contact from expected dynamics (kinetics). We projected a virtual target moving vertically downward on a wide screen with different randomized laws of motion. In the first series of experiments, subjects were asked to intercept this target by punching a real ball that fell hidden behind the screen and arrived in synchrony with the visual target. Subjects systematically timed their motor responses consistent with the assumption of gravity effects on an object's mass, even when the visual target did not accelerate. With training, the gravity model was not switched off but adapted to nonaccelerating targets by shifting the time of motor activation. In the second series of experiments, there was no real ball falling behind the screen. Instead the subjects were required to intercept the visual target by clicking a mousebutton. In this case, subjects timed their responses consistent with the assumption of uniform motion in the absence of forces, even when the target actually accelerated. Overall, the results are in accord with the theory that motor responses evoked by visual kinematics are modulated by a prior of the target dynamics. The prior appears surprisingly resistant to modifications based on performance errors.

Interactions between ocular motor and manual responses during two-dimensional tracking

Tracking of a moving target usually involves coordinated movements of the eye and the hand. To study the extent to which one behavior influences the other, eye and hand movements were recorded during three conditions (eye alone, hand alone, and eye and hand together) where subjects tracked a target that initially moved in a straight line and then made an abrupt and unpredictable change in direction. The response latencies of the eye and hand were influenced by the presence of the other tracking modality. More specifically, the latency for the hand was decreased during concomitant ocular tracking, whereas the latency for the eye was increased during combined hand-eye tracking. Moreover, the velocity profile of the smooth pursuit component of ocular tracking was different when the hand also tracked the target. Taken together, these observations support the hypothesis that at least part of the neural substrate underlying tracking is shared by the two modalities.

Ocular kinematics and eye-hand coordination

Eye-hand coordination is complicated by the fact that the eyes are constantly in motion relative to the head. This poses problems in interpreting the spatial information gathered from the retinas and using this to guide hand motion. In particular, eye-centered visual information must somehow be spatially updated across eye movements to be useful for future actions, and these representations must then be transformed into commands appropriate for arm motion. In this review, we present evidence that early visuomotor representations for arm movement are remapped relative to the gaze direction during each saccade. We find that this mechanism holds for targets in both far and near visual space. We then show how the brain incorporates the three-dimensional, rotary geometry of the eyes when interpreting retinal images and transforming these into commands for arm movement. Next, we explore the possibility that hand-eye alignment is optimized for the eye with the best field of view. Finally, we describe how head orientation influences the linkage between oculocentric visual frames and bodycentric motor frames. These findings are framed in terms of our 'conversion-on-demand' model, in which only those representations selected for action are put through the complex visuomotor transformations required for interaction with objects in personal space, thus providing a virtual on-line map of visuomotor space.

Visuomotor transformations for eye-hand coordination

In recent years the scientific community has come to appreciate that the early cortical representations for visually guided arm movements are probably coded in a visual frame, i.e. relative to retinal landmarks. While this scheme accounts for many behavioral and neurophysiological observations, it also poses certain problems for manual control. For example, how are these oculocentric representations updated across eye movements, and how are they then transformed into useful commands for accurate movements of the arm relative to the body? Also, since we have two eyes, which is used as the reference point in eye-hand alignment tasks like pointing? We show that patterns of errors in human pointing suggest that early oculocentric representations for arm movement are remapped relative to the gaze direction during each saccade. To then transform these oculocentric representations into useful commands for accurate movements of the arm relative to the body, the brain correctly incorporates the three-dimensional, rotary geometry of the eyes when interpreting retinal images. We also explore the possibility that the eye-hand coordination system uses a strategy like ocular dominance, but switches alignment between the left and right eye in order to maximize eye-hand coordination in the best field of view. Finally, we describe the influence of eye position on eye-hand alignment, and then consider how head orientation influences the linkage between oculocentric visual frames and bodycentric motor frames. These findings are framed in terms of our 'conversion-on-demand' model, which suggests a virtual representation of egocentric space, i.e. one in which only those representations selected for action are put through the complex visuomotor transformations required for interaction with actual objects in personal space.

What triggers catch-up saccades during visual tracking?

When tracking moving visual stimuli, primates orient their visual axis by combining two kinds of eye movements, smooth pursuit and saccades, that have very different dynamics. Yet, the mechanisms that govern the decision to switch from one type of eye movement to the other are still poorly understood, even though they could bring a significant contribution to the understanding of how the CNS combines different kinds of control strategies to achieve a common motor and sensory goal. In this study, we investigated the oculomotor responses to a large range of different combinations of position error and velocity error during visual tracking of moving stimuli in humans. We found that the oculomotor system uses a prediction of the time at which the eye trajectory will cross the target, defined as the "eye crossing time" (T(XE)). The eye crossing time, which depends on both position error and velocity error, is the criterion used to switch between smooth and saccadic pursuit, i.e., to trigger catch-up saccades. On average, for T(XE) between 40 and 180 ms, no saccade is triggered and target tracking remains purely smooth. Conversely, when T(XE) becomes smaller than 40 ms or larger than 180 ms, a saccade is triggered after a short latency (around 125 ms).