Incorporating prediction in models for two-dimensional smooth pursuit

Right-left hand asymmetry in manual tracking: when poorer control is associated with better adaptation and interlimb transfer

To date, interlimb transfer following visuomotor adaptation has been mainly investigated through discrete reaching movements. Here we explored this issue in the context of continuous manual tracking, a task in which the contribution of online feedback mechanisms is crucial, and in which there is a well-established right (dominant) hand advantage under baseline conditions. We had two objectives (1) to determine whether this preexisting hand asymmetry would persist under visuomotor rotation, (2) to examine interlimb transfer by assessing whether prior experience with the rotation by one hand benefit to the other hand. To address these, 44 right-handed participants were asked to move a joystick and to track a visual target following a rather unpredictable trajectory. Visuomotor adaptation was elicited by introducing a 90° rotation between the joystick motion and the cursor motion. Half of the participants adapted to the rotation first with the right hand, and then with the left, while the other half performed the opposite protocol. As expected during baseline trials, the left hand was less accurate while also exhibiting more variable and exploratory behavior. However, participants exhibited a left hand advantage during first exposure to the rotation. Moreover, interlimb transfer was observed albeit more strongly from the left to the right hand. We suggest that the less effective and more variable/exploratory control strategy of the left hand promoted its adaptation, which incidentally favored transfer from left to right hand. Altogether, this study speaks for further attention to the dominant/non-dominant asymmetry during baseline before examining interlimb transfer of adaptation.

Tuning in to a hip-hop beat: Pursuit eye movements reveal processing of biological motion

Smooth pursuit eye movements are mainly driven by motion signals to achieve their goal of reducing retinal motion blur. However, they can also show anticipation of predictable movement patterns. Oculomotor predictions may rely on an internal model of the target kinematics. Most investigations on the nature of those predictions have concentrated on simple stimuli, such as a decontextualized dot. However, biological motion is one of the most important visual stimuli in regulating human interaction and its perception involves integration of form and motion across time and space. Therefore, we asked whether there is a specific contribution of an internal model of biological motion in driving pursuit eye movements. Unlike previous contributions, we exploited the cyclical nature of walking to measure eye movement's ability to track the velocity oscillations of the hip of point-light walkers. We quantified the quality of tracking by cross-correlating pursuit and hip velocity oscillations. We found a robust correlation between signals, even along the horizontal dimension, where changes in velocity during the stepping cycle are very subtle. The inversion of the walker and the presentation of the hip-dot without context incurred the same additional phase lag along the horizontal dimension. These findings support the view that information beyond the hip-dot contributes to the prediction of hip kinematics that controls pursuit. We also found a smaller phase lag in inverted walkers for pursuit along the vertical dimension compared to upright walkers, indicating that inversion does not simply reduce prediction. We suggest that pursuit eye movements reflect the visual processing of biological motion and as such could provide an implicit measure of higher-level visual function.

Composition and decomposition of visuomotor maps during manual tracking

Adapting hand movements to changes in our body or the environment is essential for skilled motor behavior, as is the ability to flexibly combine experience gathered in separate contexts. However, it has been shown that when adapting hand movements to two different visuomotor perturbations in succession, interference effects can occur. Here, we investigate whether these interference effects compromise our ability to adapt to the superposition of the two perturbations. Participants tracked with a joystick, a visual target that followed a smooth but an unpredictable trajectory. Four separate groups of participants (total n = 83) completed one block of 50 trials under each of three mappings: one in which the cursor was rotated by 90° (ROTATION), one in which the cursor mimicked the behavior of a mass-spring system (SPRING), and one in which the SPRING and ROTATION mappings were superimposed (SPROT). The order of the blocks differed across groups. Although interference effects were found when switching between SPRING and ROTATION, participants who performed these blocks first performed better in SPROT than participants who had no prior experience with SPRING and ROTATION (i.e., composition). Moreover, participants who started with SPROT exhibited better performance under SPRING and ROTATION than participants who had no prior experience with each of these mappings (i.e., decomposition). Additional analyses confirmed that these effects resulted from components of learning that were specific to the rotational and spring perturbations. These results show that interference effects do not preclude the ability to compose/decompose various forms of visuomotor adaptation.NEW & NOTEWORTHY The ability to compose/decompose task representations is critical for both cognitive and behavioral flexibility. Here, we show that this ability extends to two forms of visuomotor adaptation in which humans have to perform visually guided hand movements. Despite the presence of interference effects when switching between visuomotor maps, we show that participants are able to flexibly compose or decompose knowledge acquired in previous sessions. These results further demonstrate the flexibility of sensorimotor adaptation in humans.

Sensorimotor delays in tracking may be compensated by negative feedback control of motion-extrapolated position

Sensorimotor delays dictate that humans act on outdated perceptual information. As a result, continuous manual tracking of an unpredictable target incurs significant response delays. However, no such delays are observed for repeating targets such as the sinusoids. Findings of this kind have led researchers to claim that the nervous system constructs predictive, probabilistic models of the world. However, a more parsimonious explanation is that visual perception of a moving target position is systematically biased by its velocity. The resultant extrapolated position could be compared with the cursor position and the difference canceled by negative feedback control, compensating sensorimotor delays. The current study tested whether a position extrapolation model fit human tracking of sinusoid (predictable) and pseudorandom (less predictable) targets better than the non-biased position control model, Twenty-eight participants tracked these targets and the two computational models were fit to the data at 60 fixed loop delay values (simulating sensorimotor delays). We observed that pseudorandom targets were tracked with a significantly greater phase delay than sinusoid targets. For sinusoid targets, the position extrapolation model simulated tracking results more accurately for loop delays longer than 120 ms, thereby confirming its ability to compensate for sensorimotor delays. However, for pseudorandom targets, this advantage arose only after 300 ms, indicating that velocity information is unlikely to be exploited in this way during the tracking of less predictable targets. We conclude that negative feedback control of position is a parsimonious model for tracking pseudorandom targets and that negative feedback control of extrapolated position is a parsimonious model for tracking sinusoidal targets.

More precise tracking of horizontal than vertical target motion with both the eyes and hand

When tracking targets moving in various directions with one's eyes, horizontal components of pursuit are more precise than vertical ones. Is this because horizontal target motion is predicted better or because horizontal movements of the eyes are controlled more precisely? When tracking a visual target with the hand, the eyes also track the target. We investigated whether the directional asymmetries that have been found during isolated eye movements are also present during such manual tracking, and if so, whether individual participants' asymmetry in eye movements is accompanied by a similar asymmetry in hand movements. We examined the data of 62 participants who used a joystick to track a visual target with a cursor. The target followed a smooth but unpredictable trajectory in two dimensions. Both the mean gaze-target distance and the mean cursor-target distance were about 20% larger in the vertical direction than in the horizontal direction. Gaze and cursor both followed the target with a slightly longer delay in the vertical than in the horizontal direction, irrespective of the target's trajectory. The delays of gaze and cursor were correlated, as were their errors in tracking the target. Gaze clearly followed the target rather than the cursor, so the asymmetry in both eye and hand movements presumably results from better predictions of the target's horizontal than of its vertical motion. Altogether this study speaks for the presence of anisotropic predictive processes that are shared across effectors.

A systematic evaluation of the evidence for perceptual control theory in tracking studies

Perceptual control theory (PCT) proposes that perceptual inputs are controlled to intentional 'reference' states by hierarchical negative feedback control, evidence for which comes from manual tracking experiments in humans. We reviewed these experiments to determine whether tracking is a process of perceptual control, and to assess the state-of-the-evidence for PCT. A systematic literature search was conducted of peer-review journal and book chapters in which tracking data were simulated with a PCT model (13 studies, 53 participants). We report a narrative review of these studies and a qualitative assessment of their methodological quality. We found evidence that individuals track to individual-specific endogenously-specified reference states and act against disturbances, and evidence that hierarchical PCT can simulate complex tracking. PCT's learning algorithm, reorganization, was not modelled. Limitations exist in the range of tracking conditions under which the PCT model has been tested. Future PCT research should apply the PCT methodology to identify control variables in real-world tasks and develop hierarchical PCT architectures for goal-oriented robotics to test the plausibility of PCT model-based action control.

How optimal is bimanual tracking? The key role of hand coordination in space

When coordinating two hands to achieve a common goal, the nervous system has to assign responsibility to each hand. Optimal control theory suggests that this problem is solved by minimizing costs such as the variability of movement and effort. However, the natural tendency to produce similar movements during bimanual tasks has been somewhat ignored by this approach. We consider a task in which participants were asked to track a moving target by means of a single cursor controlled simultaneously by the two hands. Two types of hand-cursor mappings were tested: one in which the cursor position resulted from the average location of two hands (Mean) and one in which horizontal and vertical positions of the cursor were driven separately by each hand (Split). As expected, unimanual tracking performance was better with the dominant hand than with the more variable nondominant hand. More interestingly, instead of exploiting this effect by increasing the use of the dominant hand, the contributions from both hands remained symmetrical during bimanual cooperative tasks. Indeed, for both mappings, and even after 6min of practice, the right and left hands remained strongly correlated, performing similar movements in extrinsic space. Persistence of this bimanual coupling demonstrates that participants prefer to maintain similar movements at the expense of unnecessary movements (in the Split task) and of increased noise from the nondominant hand (in the Mean task). Altogether, the findings suggest that bimanual tracking exploits hand coordination in space rather than minimizing motor costs associated with variability and effort.NEW & NOTEWORTHY When two hands are coordinated to achieve a common goal, optimal control theory proposes that the brain assigns responsibility to each hand by minimizing movement variability and effort. Nevertheless, we show that participants perform bimanual tracking using similar contributions from the dominant and nondominant hands, despite unnecessary movements and a less accurate nondominant hand. Our findings suggest that bimanual tracking exploits hand coordination in space rather than minimizing motor costs associated with variability and effort.

Gaze behavior during visuomotor tracking with complex hand-cursor dynamics

The ability to track a moving target with the hand has been extensively studied, but few studies have characterized gaze behavior during this task. Here we investigate gaze behavior when participants learn a new mapping between hand and cursor motion, such that the cursor represented the position of a virtual mass attached to the grasped handle via a virtual spring. Depending on the experimental condition, haptic feedback consistent with mass-spring dynamics could also be provided. For comparison a simple one-to-one hand-cursor mapping was also tested. We hypothesized that gaze would be drawn, at times, to the cursor in the mass-spring conditions, especially in the absence of haptic feedback. As expected hand tracking performance was less accurate under the spring mapping, but gaze behavior was virtually unaffected by the spring mapping, regardless of whether haptic feedback was provided. Specifically, relative gaze position between target and cursor, rate of saccades, and gain of smooth pursuit were similar under both mappings and both haptic feedback conditions. We conclude that even when participants are exposed to a challenging hand-cursor mapping, gaze is primarily concerned about ongoing target motion suggesting that peripheral vision is sufficient to monitor cursor position and to update hand movement control.

Handedness Matters for Motor Control But Not for Prediction

Skilled motor behavior relies on the ability to control the body and to predict the sensory consequences of this control. Although there is ample evidence that manual dexterity depends on handedness, it remains unclear whether control and prediction are similarly impacted. To address this issue, right-handed human participants performed two tasks with either the right or the left hand. In the first task, participants had to move a cursor with their hand so as to track a target that followed a quasi-random trajectory. This hand-tracking task allowed testing the ability to control the hand along an imposed trajectory. In the second task, participants had to track with their eyes a target that was self-moved through voluntary hand motion. This eye-tracking task allowed testing the ability to predict the visual consequences of hand movements. As expected, results showed that hand tracking was more accurate with the right hand than with the left hand. In contrast, eye tracking was similar in terms of spatial and temporal gaze attributes whether the target was moved by the right or the left hand. Although these results extend previous evidence for different levels of control by the two hands, they show that the ability to predict the visual consequences of self-generated actions does not depend on handedness. We propose that the greater dexterity exhibited by the dominant hand in many motor tasks stems from advantages in control, not in prediction. Finally, these findings support the notion that prediction and control are distinct processes.

Eye movements do not play an important role in the adaptation of hand tracking to a visuomotor rotation

Adapting hand movements to changes in our body or the environment is essential for skilled motor behavior. Although eye movements are known to assist hand movement control, how eye movements might contribute to the adaptation of hand movements remains largely unexplored. To determine to what extent eye movements contribute to visuomotor adaptation of hand tracking, participants were asked to track a visual target that followed an unpredictable trajectory with a cursor using a joystick. During blocks of trials, participants were either allowed to look wherever they liked or required to fixate a cross at the center of the screen. Eye movements were tracked to ensure gaze fixation as well as to examine free gaze behavior. The cursor initially responded normally to the joystick, but after several trials, the direction in which it responded was rotated by 90°. Although fixating the eyes had a detrimental influence on hand tracking performance, participants exhibited a rather similar time course of adaptation to rotated visual feedback in the gaze-fixed and gaze-free conditions. More importantly, there was extensive transfer of adaptation between the gaze-fixed and gaze-free conditions. We conclude that although eye movements are relevant for the online control of hand tracking, they do not play an important role in the visuomotor adaptation of such tracking. These results suggest that participants do not adapt by changing the mapping between eye and hand movements, but rather by changing the mapping between hand movements and the cursor’s motion independently of eye movements.

NEW & NOTEWORTHY Eye movements assist hand movements in everyday activities, but their contribution to visuomotor adaptation remains largely unknown. We compared adaptation of hand tracking under free gaze and fixed gaze. Although our results confirm that following the target with the eyes increases the accuracy of hand movements, they unexpectedly demonstrate that gaze fixation does not hinder adaptation. These results suggest that eye movements have distinct contributions for online control and visuomotor adaptation of hand movements.

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.

Asymmetrical Relationship between Prediction and Control during Visuomotor Adaptation

Current theories suggest that the ability to control the body and to predict its associated sensory consequences is key for skilled motor behavior. It is also suggested that these abilities need to be updated when the mapping between motor commands and sensory consequences is altered. Here we challenge this view by investigating the transfer of adaptation to rotated visual feedback between one task in which human participants had to control a cursor with their hand in order to track a moving target, and another in which they had to predict with their eyes the visual consequences of their hand movement on the cursor. Hand and eye tracking performances were evaluated respectively through cursor–target and eye–cursor distance. Results reveal a striking dissociation: although prior adaptation of hand tracking greatly facilitates eye tracking, the adaptation of eye tracking does not transfer to hand tracking. We conclude that although the update of control is associated with the update of prediction, prediction can be updated independently of control. To account for this pattern of results, we propose that task demands mediate the update of prediction and control. Although a joint update of prediction and control seemed mandatory for success in our hand tracking task, the update of control was only facultative for success in our eye tracking task. More generally, those results promote the view that prediction and control are mediated by separate neural processes and suggest that people can learn to predict movement consequences without necessarily promoting their ability to control these movements.

Different gaze strategies during eye versus hand tracking of a moving target

The ability to visually track, using smooth pursuit eye movements, moving objects is critical in both perceptual and action tasks. Here, by asking participants to view a moving target or track it with their hand, we tested whether different task demands give rise to different gaze strategies. We hypothesized that during hand tracking, in comparison to eye tracking, the frequency of catch-up saccades would be lower, and the smooth pursuit gain would be greater, because it limits the loss of stable retinal and extra-retinal information due to saccades. In our study participants viewed a visual target that followed a smooth but unpredictable trajectory in a horizontal plane and were instructed to either track the target with their gaze or with a cursor controlled by a manipulandum. Although the mean distance between gaze and target was comparable in both tasks, we found, consistent with our hypothesis, an increase in smooth pursuit gain and a decrease in the frequency of catch-up saccades during hand tracking. We suggest that this difference in gaze behavior arises from different tasks demands. Whereas keeping gaze close to the target is important in both tasks, obtaining stable retinal and extra-retinal information is critical for guiding hand movement.

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.

Learning the trajectory of a moving visual target and evolution of its tracking in the monkey

An object moving in the visual field triggers a saccade that brings its image onto the fovea. It is followed by a combination of slow eye movements and catch-up saccades that try to keep the target image on the fovea as long as possible. The accuracy of this ability to track the "here-and-now" location of a visual target contrasts with the spatiotemporally distributed nature of its encoding in the brain. We show in six experimentally naive monkeys how this performance is acquired and gradually evolves during successive daily sessions. During the early exposure, the tracking is mostly saltatory, made of relatively large saccades separated by low eye velocity episodes, demonstrating that accurate (here and now) pursuit is not spontaneous and that gaze direction lags behind its location most of the time. Over the sessions, while the pursuit velocity is enhanced, the gaze is more frequently directed toward the current target location as a consequence of a 25% reduction in the number of catch-up saccades and a 37% reduction in size (for the first saccade). This smoothing is observed at several scales: during the course of single trials, across the set of trials within a session, and over successive sessions. We explain the neurophysiological processes responsible for this combined evolution of saccades and pursuit in the absence of stringent training constraints. More generally, our study shows that the oculomotor system can be used to discover the neural mechanisms underlying the ability to synchronize a motor effector with a dynamic external event.

Violating instructed human agency: An fMRI study on ocular tracking of biological and nonbiological motion stimuli

Previous studies have shown that beliefs about the human origin of a stimulus are capable of modulating the coupling of perception and action. Such beliefs can be based on top-down recognition of the identity of an actor or bottom-up observation of the behavior of the stimulus. Instructed human agency has been shown to lead to superior tracking performance of a moving dot as compared to instructed computer agency, especially when the dot followed a biological velocity profile and thus matched the predicted movement, whereas a violation of instructed human agency by a nonbiological dot motion impaired oculomotor tracking (Zwickel et al., 2012). This suggests that the instructed agency biases the selection of predictive models on the movement trajectory of the dot motion. The aim of the present fMRI study was to examine the neural correlates of top-down and bottom-up modulations of perception-action couplings by manipulating the instructed agency (human action vs. computer-generated action) and the observable behavior of the stimulus (biological vs. nonbiological velocity profile). To this end, participants performed an oculomotor tracking task in an MRI environment. Oculomotor tracking activated areas of the eye movement network. A right-hemisphere occipito-temporal cluster comprising the motion-sensitive area V5 showed a preference for the biological as compared to the nonbiological velocity profile. Importantly, a mismatch between instructed human agency and a nonbiological velocity profile primarily activated medial-frontal areas comprising the frontal pole, the paracingulate gyrus, and the anterior cingulate gyrus, as well as the cerebellum and the supplementary eye field as part of the eye movement network. This mismatch effect was specific to the instructed human agency and did not occur in conditions with a mismatch between instructed computer agency and a biological velocity profile. Our results support the hypothesis that humans activate a specific predictive model for biological movements based on their own motor expertise. A violation of this predictive model causes costs as the movement needs to be corrected in accordance with incoming (nonbiological) sensory information.

Smooth Pursuit Eye Movement Deficits in Patients With Whiplash and Neck Pain are Modulated by Target Predictability

STUDY DESIGN

This is a cross-sectional study.

OBJECTIVE

The purpose of this study is to support and extend previous observations on oculomotor disturbances in patients with neck pain and whiplash-associated disorders (WADs) by systematically investigating the effect of static neck torsion on smooth pursuit in response to both predictably and unpredictably moving targets using video-oculography.

SUMMARY OF BACKGROUND DATA

Previous studies showed that in patients with neck complaints, for instance due to WAD, extreme static neck torsion deteriorates smooth pursuit eye movements in response to predictably moving targets compared with healthy controls.

METHODS

Eye movements in response to a smoothly moving target were recorded with video-oculography in a heterogeneous group of 55 patients with neck pain (including 11 patients with WAD) and 20 healthy controls. Smooth pursuit performance was determined while the trunk was fixed in 7 static rotations relative to the head (from 45° to the left to 45° to right), using both predictably and unpredictably moving stimuli.

RESULTS

Patients had reduced smooth pursuit gains and smooth pursuit gain decreased due to neck torsion. Healthy controls showed higher gains for predictably moving targets compared with unpredictably moving targets, whereas patients with neck pain had similar gains in response to both types of target movements. In 11 patients with WAD, increased neck torsion decreased smooth pursuit performance, but only for predictably moving targets.

CONCLUSION

Smooth pursuit of patients with neck pain is affected. The previously reported WAD-specific decline in smooth pursuit due to increased neck torsion seems to be modulated by the predictability of the movement of the target. The observed oculomotor disturbances in patients with WAD are therefore unlikely to be induced by impaired neck proprioception alone.

LEVEL OF EVIDENCE

3.

Kalman filtering naturally accounts for visually guided and predictive smooth pursuit dynamics

The brain makes use of noisy sensory inputs to produce eye, head, or arm motion. In most instances, the brain combines this sensory information with predictions about future events. Here, we propose that Kalman filtering can account for the dynamics of both visually guided and predictive motor behaviors within one simple unifying mechanism. Our model relies on two Kalman filters: (1) one processing visual information about retinal input; and (2) one maintaining a dynamic internal memory of target motion. The outputs of both Kalman filters are then combined in a statistically optimal manner, i.e., weighted with respect to their reliability. The model was tested on data from several smooth pursuit experiments and reproduced all major characteristics of visually guided and predictive smooth pursuit. This contrasts with the common belief that anticipatory pursuit, pursuit maintenance during target blanking, and zero-lag pursuit of sinusoidally moving targets all result from different control systems. This is the first instance of a model integrating all aspects of pursuit dynamics within one coherent and simple model and without switching between different parallel mechanisms. Our model suggests that the brain circuitry generating a pursuit command might be simpler than previously believed and only implement the functional equivalents of two Kalman filters whose outputs are optimally combined. It provides a general framework of how the brain can combine continuous sensory information with a dynamic internal memory and transform it into motor commands.

Motor synergies during manual tracking differ between familiar and unfamiliar trajectories

Synergistic control of the effector space allows high precision in task-relevant degrees of freedom, while noise is limited to task-irrelevant degrees of freedom. The present study investigates whether this typical structure of the variance-covariance matrix of the joint angles during manual tracking differs between familiar and unfamiliar trajectories. Subjects tracked a target moving in 2D on a graphics tablet with a hand-held pen, while their arm movements were not restricted. Subjects familiarized themselves with one target trajectory during an initial training block with 40 periodic trials. In the following test block, this familiar trajectory and several unfamiliar trajectories were presented in a mixed-block design to study prediction effects at the level of endpoint and joint trajectories. The differences in the synergistic control of arm movements were analyzed using the "uncontrolled manifold method." The results showed smaller variances and weaker motor synergies during tracking of familiar trajectories than during tracking of unfamiliar trajectories. The decrease in the synergy index was due to a stronger decrease in the variance irrelevant than of the variance relevant for pen position. In the context of motor control theory, these results suggest that tracking movements on familiar and unfamiliar target trajectories do not only differ in the available knowledge about target location but also apply different strategies to control the effector space.

Predictive mechanisms in the control of contour following

In haptic exploration, when running a fingertip along a surface, the control system may attempt to anticipate upcoming changes in curvature in order to maintain a consistent level of contact force. Such predictive mechanisms are well known in the visual system, but have yet to be studied in the somatosensory system. Thus, the present experiment was designed to reveal human capabilities for different types of haptic prediction. A robot arm with a large 3D workspace was attached to the index fingertip and was programmed to produce virtual surfaces with curvatures that varied within and across trials. With eyes closed, subjects moved the fingertip around elliptical hoops with flattened regions or Limaçon shapes, where the curvature varied continuously. Subjects anticipated the corner of the flattened region rather poorly, but for the Limaçon shapes, they varied finger speed with upcoming curvature according to the two-thirds power law. Furthermore, although the Limaçon shapes were randomly presented in various 3D orientations, modulation of contact force also indicated good anticipation of upcoming changes in curvature. The results demonstrate that it is difficult to haptically anticipate the spatial location of an abrupt change in curvature, but smooth changes in curvature may be facilitated by anticipatory predictions.

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.

Looking at Breakout: urgency and predictability direct eye events

We investigated the organization of eye-movement classes in a natural and dynamical setup. To mimic the goals and objectives of the natural world in a controlled environment, we studied eye-movements while participants played Breakout, an old Atari game which remains surprisingly entertaining, often addictive, in spite of its graphic and structural simplicity. Our results show that eye-movement dynamics can be explained in terms of simple principles of moments of prediction and urgency of action. We observed a consistent anticipatory behavior (gaze was directed ahead of ball trajectory) except during the moment in which the ball bounced either in the walls, or in the paddle. At these moments, we observed a refractory period during which there are no blinks and saccades. Saccade delay caused the gaze to fall behind the ball. This pattern is consistent with a model by which participants postpone saccades at the bounces while predicting the ball trajectory and subsequently make a catch-up saccade directed to a position which anticipates ball trajectory. During bounces, trajectories were smooth and curved interpolating the V-shape function of the ball with minimal acceleration. These results pave the path to understand the taxonomy of eye-movements on natural configurations in which stimuli and goals switch dynamically in time.

Spatial and temporal aspects of cognitive influences on smooth pursuit

It is well known that prediction is used to overcome processing delays within the motor system and ocular control is no exception. Motion extrapolation is one mechanism that can be used to overcome the visual processing delay. Expectations based on previous experience or cognitive cues are also capable of overcoming this delay. The present experiment was designed to examine how smooth pursuit is altered by cognitive information about the time and/or direction of an upcoming change in target direction. Subjects visually tracked a cursor as it moved at a constant velocity on a computer screen. The target initially moved from left to right and then abruptly reversed horizontal direction and traveled along one of seven possible oblique paths. In half of the trials, a cue was present throughout the trial to signal the position (as well as the time), and/or the direction of the upcoming change. Whenever a position cue (which will be referred to as a timing cue throughout the paper) was present, there were clear anticipatory adjustments to the horizontal velocity component of smooth pursuit. In the presence of a timing cue, a directional cue also led to anticipatory adjustments in the vertical velocity, and hence the direction of smooth pursuit. However, without the timing cue, a directional cue alone produced no anticipation. Thus, in this task, a cognitive spatial cue about the new direction could not be used unless it was made explicit in the time domain.

What is the biological basis of sensorimotor integration?

This Prospects presents the problems that must be solved by the vertebrate nervous system in the process of sensorimotor integration and motor control. The concepts of efference copy and inverse model are defined, and multiple biological mechanisms are described, including those that form the basis of integration, extrapolation, and comparison/cancellation operations. Open questions for future research include the biological basis of continuous and distributed versus modular control, and somatosensory-motor coordination.