Incorporating Prediction in Models for Two-Dimensional Smooth Pursuit

A predictive component can contribute to the command signal for smooth pursuit. This is readily demonstrated by the fact that low frequency sinusoidal target motion can be tracked with zero time delay or even with a small lead. The objective of this study was to characterize the predictive contributions to pursuit tracking more precisely by developing analytical models for predictive smooth pursuit. Subjects tracked a small target moving in two dimensions. In the simplest case, the periodic target motion was composed of the sums of two sinusoidal motions (SS), along both the horizontal and the vertical axes. Motions following the same or similar paths, but having a richer spectral composition, were produced by having the target follow the same path but at a constant speed (CS), and by combining the horizontal SS velocity with the vertical CS velocity and vice versa. Several different quantitative models were evaluated. The predictive contribution to the eye tracking command signal could be modeled as a low-pass filtered target acceleration signal with a time delay. This predictive signal, when combined with retinal image velocity at the same time delay, as in classical models for the initiation of pursuit, gave a good fit to the data. The weighting of the predictive acceleration component was different in different experimental conditions, being largest when target motion was simplest, following the SS velocity profiles.     

Ocular tracking as a measure of auditory motion perception.

Motion is a potent sub-modality of vision. Motion cues alone can be used to segment images into figure and ground and break camouflage. Specific patterns of motion support vivid percepts of form, guide locomotion by specifying directional heading and the passage of objects, and in case of an impending collision, the time to impact. Visual motion also drives smooth pursuit eye movements (SPEMs) that serve to stabilize the retinal image of objects in motion. In contrast, the auditory system does not appear to be particularly sensitive to motion. We review the ambiguous status of auditory motion processing from the psychophysical and electrophysiological perspectives. We then report the results of two experiments that use ocular tracking performance as an objective measure of the perception of auditory motion in humans. We examine ocular tracking of auditory motion, visual motion, combined auditory + visual motion and imagined motion in both the frontal plane and in depth. The results demonstrate that ocular tracking of auditory motion is no better than ocular tracking of imagined motion. These results are consistent with the suggestion that, unlike the visual system, the human auditory system is not endowed with low-level motion sensitive elements. We hypothesize however, that auditory information may gain access to a recently described high-level motion processing system that is heavily dependent on 'top-down' influences, including attention.     

Independent aftereffects of attention and motion

In the motion aftereffect (MAE), a stationary pattern appears to move in the opposite direction to previously viewed motion. Here we report an MAE that is observed for a putatively high level of visual analysis-attentive tracking. These high-level MAEs, visible on dynamic (but not static) tests, suggest that attentive tracking does not simply enhance low-level motion signals but, rather, acts at a subsequent stage. MAEs from tracking (1) can overrule competing MAEs from adaptation to low-level motion, (2) can be established opposite to low-level MAEs seen on static tests at the same location, and (3), most striking, are specific to the overall direction of object motion, even at nonadapted locations. These distinctive properties suggest MAEs from attentive tracking can serve as valuable probes for understanding the mechanisms of high-level vision and attention.     

Finding our way around the sensory-motor corner

Our understanding of how sensory information is transformed into motor commands has grown increasingly sophisticated. In this issue of Neuron, Wilmer and Nakayama use a novel analysis to show that the initial changes in smooth-pursuit eye speed are driven by low-level motion signals, whereas the later eye speed is determined by high-level signals.     

Neural correlates of target choice for pursuit and saccades in the primate superior colliculus

We have examined the role of the superior colliculus (SC) in choosing targets for pursuit and saccades by comparing neuronal activity at sites representing the possible choices. After recording during a two-alternative forced-choice paradigm, we measured the difference in activity of the populations representing the two choices by computing receiver operating characteristic (ROC) curves on a millisecond timescale. A signal indicating the correct choice emerged from noise over time, forming a tradeoff between speed and accuracy. The observed performance corresponded to particular points along the predicted speed-accuracy curves-pursuit emphasizing speed and saccades emphasizing accuracy. These results show that activity from the same set of neurons in the superior colliculus can predict target choices for both pursuit and saccades.     

Consistency of hand preference across low-level and high-level tasks in capuchin monkeys (Cebus apella)

Numerous studies investigating behavioral lateralization in capuchins have been published. Although some research groups have reported a population-level hand preference, other researchers have argued that capuchins do not show hand preference at the population level. As task complexity influences the expression of handedness in other primate species, the purpose of this study was to collect hand preference data across a variety of high- and low-level tasks to evaluate how task complexity influences the expression of hand preference in capuchins. We tested eleven captive brown capuchin monkeys (Cebus apella) to determine if they show consistent hand preferences across multiple high- and low-level tasks. Capuchins were expected to display high intertask consistency across the high-level tasks but not the low-level tasks. Although most individuals showed significant hand preferences for each task, only two of the high-level tasks that involved similar hand motions were significantly positively correlated, indicating consistency of hand preference across these tasks only. None of the tasks elicited a group-level hand preference. High-level tasks elicited a greater strength of hand preference than did low-level tasks. No sex differences were found for the direction or strength of hand preference for any task. These results contribute to the growing database of primate laterality and provide additional evidence that capuchins do not display group-level hand preferences.     

Expansion of direction space around the cardinal axes revealed by smooth pursuit eye movements

It is well established that perceptual direction discrimination shows an oblique effect; thresholds are higher for motion along diagonal directions than for motion along cardinal directions. Here, we compare simultaneous direction judgments and pursuit responses for the same motion stimuli and find that both pursuit and perceptual thresholds show similar anisotropies. The pursuit oblique effect is robust under a wide range of experimental manipulations, being largely resistant to changes in trajectory (radial versus tangential motion), speed (10 versus 25 deg/s), directional uncertainty (blocked versus randomly interleaved), and cognitive state (tracking alone versus concurrent tracking and perceptual tasks). Our data show that the pursuit oblique effect is caused by an effective expansion of direction space surrounding the cardinal directions and the requisite compression of space for other directions. This expansion suggests that the directions around the cardinal directions are in some way overrepresented in the visual cortical pathways that drive both smooth pursuit and perception.     

Effect of speed and precision demands on human shoulder muscle electromyography during a repetitive task

Effects of speed and precision on electromyography (EMG) in human shoulder muscles were studied during a hand movement task where five points were marked repeatedly with a pencil. Six female subjects performed with three precision demands and at four speeds. Three of the speeds were predefined, while the last speed was performed as fast as possible. The EMG were recorded from 13 shoulder muscles or parts of muscles. Elbow velocity, acceleration and rectified EMG were calculated for each task. The mean elbow velocity and acceleration increased with speed and precision demands. There was an increase in EMG as the speed demand increased for all three precision demands (P < 0.001), and as the precision demand increased for the two highest predefined speed demands (P < 0.05). The combination of a high speed and a high precision demand resulted in the highest EMG. Different EMG levels were attained for the 13 muscles and the supraspinatus muscle always showed the highest normalized EMG. However, analysis of variance showed the same relative increase for all muscles with speed and precision demands. The EMG changes in response to precision demand can only be explained in part by the differences in movement velocity and acceleration, and other factors such as increased co-contraction must also be taken into account. Accepted: 25 May 1998     

Anticipatory Smooth Eye Movements in Autism Spectrum Disorder

Smooth pursuit eye movements are important for vision because they maintain the line of sight on targets that move smoothly within the visual field. Smooth pursuit is driven by neural representations of motion, including a surprisingly strong influence of high-level signals representing expected motion. We studied anticipatory smooth eye movements (defined as smooth eye movements in the direction of expected future motion) produced by salient visual cues in a group of high-functioning observers with Autism Spectrum Disorder (ASD), a condition that has been associated with difficulties in either generating predictions, or translating predictions into effective motor commands. Eye movements were recorded while participants pursued the motion of a disc that moved within an outline drawing of an inverted Y-shaped tube. The cue to the motion path was a visual barrier that blocked the untraveled branch (right or left) of the tube. ASD participants showed strong anticipatory smooth eye movements whose velocity was the same as that of a group of neurotypical participants. Anticipatory smooth eye movements appeared on the very first cued trial, indicating that trial-by-trial learning was not responsible for the responses. These results are significant because they show that anticipatory capacities are intact in high-functioning ASD in cases where the cue to the motion path is highly salient and unambiguous. Once the ability to generate anticipatory pursuit is demonstrated, the study of the anticipatory responses with a variety of types of cues provides a window into the perceptual or cognitive processes that underlie the interpretation of events in natural environments or social situations.     

Frame of reference transformations in motion perception during smooth pursuit eye movements

Smooth pursuit eye movements change the retinal image velocity of objects in the visual field. In order to change from a retinocentric frame of reference into a head-centric one, the visual system has to take the eye movements into account. Studies on motion perception during smooth pursuit eye movements have measured either perceived speed or perceived direction during smooth pursuit to investigate this frame of reference transformation, but never both at the same time. We devised a new velocity matching task, in which participants matched both perceived speed and direction during fixation to that during pursuit. In Experiment 1, the velocity matches were determined for a range of stimulus directions, with the head-centric stimulus speed kept constant. In Experiment 2, the retinal stimulus speed was kept approximately constant, with the same range of stimulus directions. In both experiments, the velocity matches for all directions were shifted against the pursuit direction, suggesting an incomplete transformation of the frame of reference. The degree of compensation was approximately constant across stimulus direction. We fitted the classical linear model, the model of Turano and Massof (2001) and that of Freeman (2001) to the velocity matches. The model of Turano and Massof fitted the velocity matches best, but the differences between de model fits were quite small. Evaluation of the models and comparison to a few alternatives suggests that further specification of the potential effect of retinal image characteristics on the eye movement signal is needed.     

Head-centred motion perception in the ageing visual system

Stationary objects appear to move in the opposite direction to a pursuit eye movement (Filehne illusion) and moving objects appear slower when pursued (Aubert-Fleischl phenomenon). Both illusions imply that extra-retinal, eye-velocity signals lead to lower estimates of speed than corresponding retinal motion signals. Intriguingly, the velocity (i.e. speed and direction) of the Filehne illusion depends on the age of the observer, especially for brief display durations (Wertheim and Bekkering, 1992). This suggests relative signal size changes as the visual system matures. To test the signal-size hypothesis, we compared the Filehne illusion and Aubert-Fleischl phenomenon in young and old observers using short and long display durations. The trends in the Filehne data were similar to those reported by Wertheim and Bekkering. However, we found no evidence for an effect of age or duration in the Aubert-Fleischl phenomenon. The differences between the two illusions could not be reconciled on the basis of actual eye movements made. The findings suggest a more complicated explanation of the combined influence of age and duration on head-centred motion perception than that described by the signal-size hypothesis.     

Extra-retinal adaptation of cortical motion-processing areas during pursuit eye movements

Repetitive eye movement produces a compelling motion aftereffect (MAE). One mechanism thought to contribute to the illusory movement is an extra-retinal motion signal generated after adaptation. However, extra-retinal signals are also generated during pursuit. They modulate activity within cortical motion-processing area MST, helping transform retinal motion into motion in the world during an eye movement. Given the evidence that MST plays a key role in generating MAE, it may also become indirectly adapted by prolonged pursuit. To differentiate between these two extra-retinal mechanisms we examined storage of the MAE across a period of darkness. In one condition observers were told to stare at a moving pattern, an instruction that induces a more reflexive type of eye movement. In another they were told to deliberately pursue it. We found equally long MAEs when testing immediately after adaptation but not when the test was delayed by 40 s. In the case of the reflexive eye movement the delay almost completely extinguished the MAE, whereas the illusory motion following pursuit remained intact. This suggests pursuit adapts cortical motion-processing areas whereas unintentional eye movement does not. A second experiment showed that cortical mechanisms cannot be the sole determinant of pursuit-induced MAE. Following oblique pursuit, we found MAE direction changes from oblique to vertical. Perceived MAE direction appears to be influenced by a subcortical mechanism as well, one based on the relative recovery rate of horizontal and vertical eye-movement processes recruited during oblique pursuit.     

The level of friend retrovirus replication determines the cytolytic pathway of CD8+ T-cell-mediated pathogen control

Cytotoxic T cells (CTL) play a central role in the control of viral infections. Their antiviral activity can be mediated by at least two cytotoxic pathways, namely, the granule exocytosis pathway, involving perforin and granzymes, and the Fas-FasL pathway. However, the viral factor(s) that influences the selection of one or the other pathway for pathogen control is elusive. Here we investigate the role of viral replication levels in the induction and activation of CTL, including their effector potential, during acute Friend murine leukemia virus (F-MuLV) infection. F-MuLV inoculation results in a low-level infection of adult C57BL/6 mice that is enhanced about 500-fold upon coinfection with the spleen focus-forming virus (SFFV). Both the low- and high-level F-MuLV infections generated CD8+ effector T cells that were essential for the control of viral replication. However, the low-level infection induced CD8+ T cells expressing solely FasL but not the cytotoxic molecules granzymes A and B, whereas the high-level infection resulted in induction of CD8+ effector T cells secreting molecules of the granule exocytosis pathway. By using knockout mouse strains deficient in one or the other cytotoxic pathway, we found that low-level viral replication was controlled by CTL that expressed FasL but control of high-level viral replication required perforin and granzymes. Additional studies, in which F-MuLV replication was enhanced experimentally in the absence of SFFV coinfection, supported the notion that only the replication level of F-MuLV was the critical factor that determined the differential expression of cytotoxic molecules by CD8+ T cells and the pathway of CTL cytotoxicity.     

Estimating joint kinematics from skin motion observation: modelling and validation

Modelling of soft tissue motion is required in many areas, such as computer animation, surgical simulation, 3D motion analysis and gait analysis. In this paper, we will focus on the use of modelling of skin deformation during 3D motion analysis. The most frequently used method in 3D human motion analysis involves placing markers on the skin of the analysed segment which is composed of the rigid bone and the surrounding soft tissues. Skin and soft tissue deformations introduce a significant artefact which strongly influences the resulting bone position, orientation and joint kinematics. For this study, we used a statistical solid dynamics approach which is a combination of several previously reported tools: the point cluster technique (PCT) and a Kalman filter which was added to the PCT. The methods were tested and evaluated on controlled human-arm motions, using an optical motion capture system (Vicon^TM).

The addition of a Kalman filter to the PCT for rigid body motion estimation results in a smoother signal that better represents the joint motion. Calculations indicate less signal distortion than when using a digital low-pass filter. Furthermore, adding a Kalman filter to the PCT substantially reduces the dispersion of the maximal and minimal instantaneous frequencies. For controlled human movements, the result indicated that adding a Kalman filter to the PCT produced a more accurate signal. However, it could not be concluded that the proposed Kalman filter is better than a low-pass filter for estimation of the motion. We suggest that implementation of a Kalman filter with a better biomechanical motion model will be more likely to improve the results.     

Motion Control in Saccade and Smooth Pursuit for Bionic Eye Based on Three-dimensional Coordinates

Saccade and smooth pursuit are two important functions of human eye.In order to enable bionic eye to imitate the two functions,a control method that implements saccade and smooth pursuit based on the three-dimensional coordinates of target is proposed.An optimal observation position is defined for bionic eye based on three-dimensional coordinates.A kind of motion planning method with high accuracy is developed.The motion parameters of stepper motor consisting of angle acceleration and turning time are computed according to the position deviation,the target's angular velocity and the stepper motor's current angular velocity in motion planning.The motors are controlled with the motion parameters moving to given position with desired angular velocity in schedule time.The experimental results show that the bionic eye can move to optimal observation positions in 0.6 s from initial location and the accuracy of 3D coordinates is improved.In addition,the bionic eye can track a target within the error of less than 20 pixels based on three-dimensional coordinates.It is verified that saccade and smooth pursuit of bionic eye based on three-dimensional coordinates are feasible.     

Tuning Properties of MT and MSTd and Divisive Interactions for Eye-Movement Compensation

The primate brain intelligently processes visual information from the world as the eyes move constantly. The brain must take into account visual motion induced by eye movements, so that visual information about the outside world can be recovered. Certain neurons in the dorsal part of monkey medial superior temporal area (MSTd) play an important role in integrating information about eye movements and visual motion. When a monkey tracks a moving target with its eyes, these neurons respond to visual motion as well as to smooth pursuit eye movements. Furthermore, the responses of some MSTd neurons to the motion of objects in the world are very similar during pursuit and during fixation, even though the visual information on the retina is altered by the pursuit eye movement. We call these neurons compensatory pursuit neurons. In this study we develop a computational model of MSTd compensatory pursuit neurons based on physiological data from single unit studies. Our model MSTd neurons can simulate the velocity tuning of monkey MSTd neurons. The model MSTd neurons also show the pursuit compensation property. We find that pursuit compensation can be achieved by divisive interaction between signals coding eye movements and signals coding visual motion. The model generates two implications that can be tested in future experiments: (1) compensatory pursuit neurons in MSTd should have the same direction preference for pursuit and retinal visual motion; (2) there should be non-compensatory pursuit neurons that show opposite preferred directions of pursuit and retinal visual motion.     

Building with a scaffold: emerging strategies for high- to low-level cellular modeling

Computational cellular models are becoming crucial for the analysis of complex biological systems. An important new paradigm for cellular modeling involves building a comprehensive scaffold of molecular interactions and then mining this scaffold to reveal a hierarchy of signaling, regulatory and metabolic pathways. We review the important trends that make this approach feasible and describe how they are spurring the development of models at multiple levels of abstraction. Pathway maps can be extracted from the scaffold using "high-level" computational models, which identify the key components, interactions and influences required for more detailed "low-level" models. Large-scale experimental measurements validate high-level models, whereas targeted experimental manipulations and measurements test low-level models.     

Estimating joint kinematics from skin motion observation: modelling and validation

Modelling of soft tissue motion is required in many areas, such as computer animation, surgical simulation, 3D motion analysis and gait analysis. In this paper, we will focus on the use of modelling of skin deformation during 3D motion analysis. The most frequently used method in 3D human motion analysis involves placing markers on the skin of the analysed segment which is composed of the rigid bone and the surrounding soft tissues. Skin and soft tissue deformations introduce a significant artefact which strongly influences the resulting bone position, orientation and joint kinematics. For this study, we used a statistical solid dynamics approach which is a combination of several previously reported tools: the point cluster technique (PCT) and a Kalman filter which was added to the PCT. The methods were tested and evaluated on controlled human-arm motions, using an optical motion capture system (Vicon(TM)). The addition of a Kalman filter to the PCT for rigid body motion estimation results in a smoother signal that better represents the joint motion. Calculations indicate less signal distortion than when using a digital low-pass filter. Furthermore, adding a Kalman filter to the PCT substantially reduces the dispersion of the maximal and minimal instantaneous frequencies. For controlled human movements, the result indicated that adding a Kalman filter to the PCT produced a more accurate signal. However, it could not be concluded that the proposed Kalman filter is better than a low-pass filter for estimation of the motion. We suggest that implementation of a Kalman filter with a better biomechanical motion model will be more likely to improve the results.     

Sensory convergence solves a motion ambiguity problem

Our inner ear is equipped with a set of linear accelerometers, the otolith organs, that sense the inertial accelerations experienced during self-motion. However, as Einstein pointed out nearly a century ago, this signal would by itself be insufficient to detect our real movement, because gravity, another form of linear acceleration, and self-motion are sensed identically by otolith afferents. To deal with this ambiguity, it was proposed that neural populations in the pons and midline cerebellum compute an independent, internal estimate of gravity using signals arising from the vestibular rotation sensors, the semicircular canals. This hypothesis, regarding a causal relationship between firing rates and postulated sensory contributions to inertial motion estimation, has been directly tested here by recording neural activities before and after inactivation of the semicircular canals. We show that, unlike cells in normal animals, the gravity component of neural responses was nearly absent in canal-inactivated animals. We conclude that, through integration of temporally matched, multimodal information, neurons derive the mathematical signals predicted by the equations describing the physics of the outside world.     

A ‘tachometer’ feedback model of smooth pursuit eye movements

A new model of smooth pursuit eye movements is presented. We begin by formally analyzing the stability of the proportional-derivative (PD) model of smooth pursuit eye movements using Pontryagin's theory. The PD model is the linearized version of the nonlinear Krauzlis-Lisberger (KL) model. We show that the PD model fails to account for the experimentally observed dependence of the eye velocity damping ratio and the oscillation period on the total delay in the feedback loop. To explain the data, a new `tachometer' feedback model, based on an efference copy signal of eye acceleration, is proposed and analyzed by computer simulation. The model predicts some salient features of monkey pursuit data and suggests a functional role for the extraretinal input to the medial superior temporal area (MST). Received: 9 February 1995 / Accepted in revised form: 13 June 1995