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.     

The neural basis of smooth pursuit eye movements in the rhesus monkey brain

Smooth pursuit eye movements are performed in order to prevent retinal image blur of a moving object. Rhesus monkeys are able to perform smooth pursuit eye movements quite similar as humans, even if the pursuit target does not consist in a simple moving dot. Therefore, the study of the neuronal responses as well as the consequences of micro-stimulation and lesions in trained monkeys performing smooth pursuit is a powerful approach to understand the human pursuit system. The processing of visual motion is achieved in the primary visual cortex and the middle temporal area. Further processing including the combination of retinal image motion signals with extra-retinal signals such as the ongoing eye and head movement occurs in subsequent cortical areas as the medial superior temporal area, the ventral intraparietal area and the frontal and supplementary eye field. The frontal eye field especially contributes anticipatory signals which have a substantial influence on the execution of smooth pursuit. All these cortical areas send information to the pontine nuclei, which in turn provide the input to the cerebellum. The cerebellum contains two pursuit representations: in the paraflocculus/flocculus region and in the posterior vermis. While the first representation is most likely involved in the coordination of pursuit and the vestibular-ocular reflex, the latter is involved in the precise adjustments of the eye movements such as adaptation of pursuit initiation. The output of the cerebellum is directed to the moto-neurons of the extra-ocular muscles in the brainstem.     

Infant attention and the development of smooth pursuit tracking.

The effect of attention on smooth pursuit and saccadic tracking was studied in infants at 8, 14, 20, and 26 weeks of age. A small rectangle was presented moving in a sinusoidal pattern in either the horizontal or vertical direction. Attention level was distinguished with a recording of heart rate. There was an increase across age in overall tracking, the gain of the smooth pursuit eye movements, and an increase in the amplitude of compensatory saccades at faster tracking speeds. One age change was an increase in the preservation of smooth pursuit tracking ability as stimulus speed increased. A second change was the increasing tendency during attentive tracking to shift from smooth pursuit to saccadic tracking when the stimulus speed increased to the highest velocities. This study shows that the development of smooth pursuit and targeted saccadic eye movements is closely related to the development of sustained attention in this age range.     

Effects of Visual Error Timing on Smooth Pursuit Gain Adaptation in Humans

Smooth pursuit (SP) is one of the precise oculomotor behaviors when tracking a moving object. Adaptation of SP is based on a visual-error driven motor learning process associated with predictable changes in the visual environment. Proper timing of a sensory signal is an important factor for adaptation of fine motor control. In this study, we investigated whether visual error timing affects SP gain adaptation. An adaptive change in SP gain is produced experimentally by repeated trials of a step-ramp tracking with 2 different velocities (double-velocity paradigm). The authors used the double-velocity paradigm where target speed changes 400 or 800 ms after the target onset. The results show that SP gain changed in a certain time window following adaptation. The authors suggest that SP adaptation shown in this study is associated with timing control mechanisms.     

Effects of directional uncertainty on visually-guided joystick pointing

Reaction times generally follow the predictions of Hick's law as stimulus-response uncertainty increases, although notable exceptions include the oculomotor system. Saccadic and smooth pursuit eye movement reaction times are independent of stimulus-response uncertainty. Previous research showed that joystick pointing to targets, a motor analog of saccadic eye movements, is only modestly affected by increased stimulus-response uncertainty; however, a no-uncertainty condition (simple reaction time to 1 possible target) was not included. Here, we re-evaluate manual joystick pointing including a no-uncertainty condition. Analysis indicated simple joystick pointing reaction times were significantly faster than choice reaction times. Choice reaction times (2, 4, or 8 possible target locations) only slightly increased as the number of possible targets increased. These data suggest that, as with joystick tracking (a motor analog of smooth pursuit eye movements), joystick pointing is more closely approximated by a simple/choice step function than the log function predicted by Hick's law.     

Cognitive processes involved in smooth pursuit eye movements

Ocular pursuit movements allow moving objects to be tracked with a combination of smooth movements and saccades. The principal objective is to maintain smooth eye velocity close to object velocity, thus minimising retinal image motion and maintaining acuity. Saccadic movements serve to realign the image if it falls outside the fovea, the area of highest acuity. Pursuit movements are often portrayed as voluntary but their basis lies in processes that sense retinal motion and can induce eye movements without active participation. The factor distinguishing pursuit from such reflexive movements is the ability to select and track a single object when presented with multiple stimuli. The selective process requires attention, which appears to raise the gain for the selected object and/or suppress that associated with other stimuli, the resulting competition often reducing pursuit velocity. Although pursuit is essentially a feedback process, delays in motion processing create problems of stability and speed of response. This is countered by predictive processes, probably operating through internal efference copy (extra-retinal) mechanisms using short-term memory to store velocity and timing information from prior stimulation. In response to constant velocity motion, the initial response is visually driven, but extra-retinal mechanisms rapidly take over and sustain pursuit. The same extra-retinal mechanisms may also be responsible for generating anticipatory smooth pursuit movements when past experience creates expectancy of impending object motion. Similar, but more complex, processes appear to operate during periodic pursuit, where partial trajectory information is stored and released in anticipation of expected future motion, thus minimising phase errors associated with motion processing delays.     

Cognitive processes involved in smooth pursuit eye movements

Ocular pursuit movements allow moving objects to be tracked with a combination of smooth movements and saccades. The principal objective is to maintain smooth eye velocity close to object velocity, thus minimising retinal image motion and maintaining acuity. Saccadic movements serve to realign the image if it falls outside the fovea, the area of highest acuity. Pursuit movements are often portrayed as voluntary but their basis lies in processes that sense retinal motion and can induce eye movements without active participation. The factor distinguishing pursuit from such reflexive movements is the ability to select and track a single object when presented with multiple stimuli. The selective process requires attention, which appears to raise the gain for the selected object and/or suppress that associated with other stimuli, the resulting competition often reducing pursuit velocity. Although pursuit is essentially a feedback process, delays in motion processing create problems of stability and speed of response. This is countered by predictive processes, probably operating through internal efference copy (extra-retinal) mechanisms using short-term memory to store velocity and timing information from prior stimulation. In response to constant velocity motion, the initial response is visually driven, but extra-retinal mechanisms rapidly take over and sustain pursuit. The same extra-retinal mechanisms may also be responsible for generating anticipatory smooth pursuit movements when past experience creates expectancy of impending object motion. Similar, but more complex, processes appear to operate during periodic pursuit, where partial trajectory information is stored and released in anticipation of expected future motion, thus minimising phase errors associated with motion processing delays.     

Oculomanual Coordination in Tracking of Pseudorandom Target Motion Stimuli

Oculomanual coordination was investigated in 9 healthy subjects during tracking of pseudorandom motion stimuli. Each subject was required to track visual stimuli under eye-hand (EH) and eye-alone (EA) conditions. Subjects were exposed to 3 types of mixed sinusoidal stimulus with varying frequency or amplitude of the highest frequency component, or various degrees of irregularity. Progressive degradation in tracking performance was nonlinearly induced by an increase in either (a) the highest frequency component or (b) its amplitude, but not by stimulus irregularity. No significant difference was found in eye velocity gain and phase under the EH and EA conditions. Eye and hand responses were found to be highly correlated in gain and phase when compared across frequencies and motion stimuli. The results suggest that frequency and amplitude are dominant factors controlling the breakdown of oculomanual performance in response to pseudorandom stimuli. Frequency responses of smooth pursuit eye movements are not affected by the hand motion in pursuit of unpredictable stimuli. Eye and hand motor systems appear to share common nonlinear drive mechanisms when pursuing pseudorandom target motion stimuli.     

Why eye movements and perceptual factors have to be controlled in studies on "representational momentum"

In order to study memory of the final position of a smoothly moving target, Hubbard (e.g., Hubbard and Bharucha, 1988) presented smooth stimulus motion and used motor responses. In contrast, Freyd (e.g., Freyd and Finke, 1984) presented implied stimulus motion and used the method of constant stimuli. The same forward error was observed in both paradigms. However, the processes underlying the error may be very different. When smooth stimulus motion is followed by smooth pursuit eye movements, the forward error is associated with asynchronous processing of retinal and extraretinal information. In the absence of eye movements, no forward displacement is observed with smooth motion. In contrast, implied motion produces a forward error even without eye movements, suggesting that observers extrapolate the next target step when successive target presentations are far apart. Finally, motor responses produce errors that are not observed with perceptual judgments, indicating that the motor system may compensate for neuronal latencies.     

Comment and Reply Why eye movements and perceptual factors have to be controlled in studies on “representational momentum”

In order to study memory of the final position of a smoothly moving target, Hubbard (e.g., Hubbard & Bharucha, 1988) presented smooth stimulus motion and used motor responses. In contrast, Freyd (e.g., Freyd & Finke, 1984) presented implied stimulus motion and used the method of constant stimuli. The same forward error was observed in both paradigms. However, the processes underlying the error may be very different. When smooth stimulus motion is followed by smooth pursuit eye movements, the forward error is associated with asynchronous processing of retinal and extraretinal information. In the absence of eye movements, no forward displacement is observed with smooth motion. In contrast, implied motion produces a forward error even without eye movements, suggesting that observers extrapolate the next target step when successive target presentations are far apart. Finally, motor responses produce errors that are not observed with perceptual judgments, indicating that the motor system may compensate for neuronal latencies.     

Neurophysiology and neuroanatomy of smooth pursuit in humans

Smooth pursuit eye movements enable us to focus our eyes on moving objects by utilizing well-established mechanisms of visual motion processing, sensorimotor transformation and cognition. Novel smooth pursuit tasks and quantitative measurement techniques can help unravel the different smooth pursuit components and complex neural systems involved in its control. The maintenance of smooth pursuit is driven by a combination of the prediction of target velocity and visual feedback about performance quality, thus a combination of retinal and extraretinal information that has to be integrated in various networks. Different models of smooth pursuit with specific in- and output parameters have been developed for a better understanding of the underlying neurophysiological mechanisms and to make quantitative predictions that can be tested in experiments. Functional brain imaging and neurophysiological studies have defined motion sensitive visual area V5, frontal (FEF) and supplementary (SEF) eye fields as core cortical smooth pursuit regions. In addition, a dense neural network is involved in the adjustment of an optimal smooth pursuit response by integrating also extraretinal information. These networks facilitate interaction of the smooth pursuit system with multiple other visual and non-visual sensorimotor systems on the cortical and subcortical level. Future studies with fMRI advanced techniques (e.g., event-related fMRI) promise to provide an insight into how smooth pursuit eye movements are linked to specific brain activation. Applying this approach to neurological and also mental illness can reveal distinct disturbances within neural networks being present in these disorders and also the impact of medication on this circuitry.     

Neurophysiology and neuroanatomy of smooth pursuit in humans

Smooth pursuit eye movements enable us to focus our eyes on moving objects by utilizing well-established mechanisms of visual motion processing, sensorimotor transformation and cognition. Novel smooth pursuit tasks and quantitative measurement techniques can help unravel the different smooth pursuit components and complex neural systems involved in its control. The maintenance of smooth pursuit is driven by a combination of the prediction of target velocity and visual feedback about performance quality, thus a combination of retinal and extraretinal information that has to be integrated in various networks. Different models of smooth pursuit with specific in- and output parameters have been developed for a better understanding of the underlying neurophysiological mechanisms and to make quantitative predictions that can be tested in experiments. Functional brain imaging and neurophysiological studies have defined motion sensitive visual area V5, frontal (FEF) and supplementary (SEF) eye fields as core cortical smooth pursuit regions. In addition, a dense neural network is involved in the adjustment of an optimal smooth pursuit response by integrating also extraretinal information. These networks facilitate interaction of the smooth pursuit system with multiple other visual and non-visual sensorimotor systems on the cortical and subcortical level. Future studies with fMRI advanced techniques (e.g., event-related fMRI) promise to provide an insight into how smooth pursuit eye movements are linked to specific brain activation. Applying this approach to neurological and also mental illness can reveal distinct disturbances within neural networks being present in these disorders and also the impact of medication on this circuitry.     

Varying the Type and Number of Adaptive Variables in Continuous Tracking

To investigate the effectiveness of various types and numbers of adaptive variables, 48 subjects performed a two-dimensional pursuit tracking task for five 3-min training sessions. In the factorial design resulting in eight experimental conditions, three variables (frequency of the forcing function, ratio of acceleration to rate control, and control stick sensitivity) were either fixed or adaptive. A transfer and retention task in which the tracking situation changed periodically was used to evaluate the ability of subjects to adjust to change. Each adaptive variable was analyzed separately in training. The highest rate of adaptation in frequency occurred when frequency was the only adaptive variable. The rate of adaptation in acceleration was greater early in training when frequency also adapted. More adaptation occurred in gain when another variable also adapted. During transfer subjects trained adaptively generally showed more stable performance in the changing task situation. No reliable differences among conditions appeared in retention. Results are discussed in terms of stimulus and response similarity, the optimum number of adaptive variables, and the appropriateness of a changing task to evaluate adaptive training.     

Smooth pursuit eye movement and schizotypy in the community

Deficits in smooth pursuit eye movements are well documented in schizophrenia and schizotypic psychopathology. The status of eye tracking dysfunction (ETD) as an endophenotype for schizophrenia liability is relatively robust. However, the relation of ETD to schizophrenia-related deviance in the general population has not been confirmed. This study examined smooth pursuit eye tracking and schizotypal personality features in the general population. Smooth pursuit eye movement and schizotypal features were measured in 300 adult community subjects. The sample included both sexes, subjects with a wide age and educational range, and subjects with no prior history of psychosis. Primary outcome measures were peak gain (eye velocity/target velocity), catch-up saccade rate, and schizotypal feature scores. Total schizotypal features were significantly associated with decreased peak gain and were associated at the trend level with increased catch-up saccade rate. These associations were essentially unchanged after controlling for age, sex, and intellectual level effects. These data confirm a hypothesized association between schizotypal features and poorer eye tracking performance (principally, peak gain) in the general population as well as support the conceptualization of ETD as an endophenotype for schizophrenia liability.     

Parallel ocular and manual tracking responses to a continuously moving visual target

Continuous ocular and manual tracking of the same visual target moving horizontally in sinusoids at 0.75 Hz was measured by lag, RMS Error, and Gain. The best measures of accuracy of tracking, error and lag, were remarkably similar in the two systems and were affected similarly by presence of a background and changes in predictability of target movement. Details of within-system performance varied despite the over-all parallels. Gain was different in adjustment of proportion of saccadic to pursuit movement was affected by the presence of the hand, even though this did not affect tracking accuracy. The over-all parallel of response adjustment suggests that a suprasystem decision-maker sets general response goals and each motor system adjusts output details to match these goals.     

Extraretinal and retinal amplitude and phase errors during Filehne illusion and path perception

Pursuit eye movements give rise to retinal motion. To judge stimulus motion relative to the head, the visual system must correct for the eye movement by using an extraretinal, eye-velocity signal. Such correction is important in a variety of motion estimation tasks including judgments of object motion relative to the head and judgments of self-motion direction from optic flow. The Filehne illusion (where a stationary object appears to move opposite to the pursuit) results from a mismatch between retinal and extraretinal speed estimates. A mismatch in timing could also exist. Speed and timing errors were investigated using sinusoidal pursuit eye movements. We describe a new illusion--the slalom illusion--in which the perceived direction of self-motion oscillates left and right when the eyes move sinusoidally. A linear model is presented that determines the gain ratio and phase difference of extraretinal and retinal signals accompanying the Filehne and slalom illusions. The speed mismatch and timing differences were measured in the Filehne and self-motion situations using a motion-nulling procedure. Timing errors were very small for the Filehne and slalom illusions. However, the ratios of extraretinal to retinal gain were consistently less than 1, so both illusions are the consequence of a mismatch between estimates of retinal and extraretinal speed. The relevance of the results for recovering the direction of self-motion during pursuit eye movements is discussed.     

Neurophysiology and neuroanatomy of smooth pursuit: Lesion studies

Smooth pursuit impairment is recognized clinically by the presence of saccadic tracking of a small object and quantified by reduction in pursuit gain, the ratio of smooth eye movement velocity to the velocity of a foveal target. Correlation of the site of brain lesions, identified by imaging or neuropathological examination, with defective smooth pursuit determines brain structures that are necessary for smooth pursuit. Paretic, low gain, pursuit occurs toward the side of lesions at the junction of the parietal, occipital and temporal lobes (area V5), the frontal eye field and their subcortical projections, including the posterior limb of the internal capsule, the midbrain and the basal pontine nuclei. Paresis of ipsiversive pursuit also results from damage to the ventral paraflocculus and caudal vermis of the cerebellum. Paresis of contraversive pursuit is a feature of damage to the lateral medulla. Retinotopic pursuit paresis consists of low gain pursuit in the visual hemifield contralateral to damage to the optic radiation, striate cortex or area V5. Craniotopic paresis of smooth pursuit consists of impaired smooth eye movement generation contralateral to the orbital midposition after acute unilateral frontal or parietal lobe damage. Omnidirectional saccadic pursuit is a most sensitive sign of bilateral or diffuse cerebral, cerebellar or brainstem disease. The anatomical and physiological bases of defective smooth pursuit are discussed here in the context of the effects of lesion in the human brain.     

Neurophysiology and neuroanatomy of smooth pursuit: Lesion studies

Smooth pursuit impairment is recognized clinically by the presence of saccadic tracking of a small object and quantified by reduction in pursuit gain, the ratio of smooth eye movement velocity to the velocity of a foveal target. Correlation of the site of brain lesions, identified by imaging or neuropathological examination, with defective smooth pursuit determines brain structures that are necessary for smooth pursuit. Paretic, low gain, pursuit occurs toward the side of lesions at the junction of the parietal, occipital and temporal lobes (area V5), the frontal eye field and their subcortical projections, including the posterior limb of the internal capsule, the midbrain and the basal pontine nuclei. Paresis of ipsiversive pursuit also results from damage to the ventral paraflocculus and caudal vermis of the cerebellum. Paresis of contraversive pursuit is a feature of damage to the lateral medulla. Retinotopic pursuit paresis consists of low gain pursuit in the visual hemifield contralateral to damage to the optic radiation, striate cortex or area V5. Craniotopic paresis of smooth pursuit consists of impaired smooth eye movement generation contralateral to the orbital midposition after acute unilateral frontal or parietal lobe damage. Omnidirectional saccadic pursuit is a most sensitive sign of bilateral or diffuse cerebral, cerebellar or brainstem disease. The anatomical and physiological bases of defective smooth pursuit are discussed here in the context of the effects of lesion in the human brain.     

Smooth pursuit eye movements in normal and dyslexic children

This paper describes a detailed study of horizontal eye movements associated with visual tracking of a smoothly moving target. Essentially all children, even at target velocities as low as 5 degrees/sec., show some saccadic eye movements superimposed on smooth tracking movements. Detailed analysis of pursuit eye-movements from a group of 26 poor readers and 34 normal controls (8 to 13 yr.) showed that about 25% of poor readers have an abnormally raised saccadic component in smooth pursuit. This suggests that studies of eye movements during tracking of smoothly moving targets at low velocity, combined with a quantitative approach to data analysis, may be useful for early detection of a significant proportion of poor-reading children.     

Effects of antisocial personality, cocaine and opioid dependence, and gender on eye movement control

Substance-dependent patients have been reported to exhibit abnormal smooth pursuit and saccadic eye movements. However, contrasts of the effects of different substances and the effects of comorbid psychiatric symptoms such as antisocial personality have rarely been performed. Separate analyses examined the effects of cocaine dependence, opioid dependence, or antisocial personality disorder. In each analysis, sex was included as an additional grouping factor. The dependent measures were the gain of smooth pursuit eye movement and the delay and accuracy of saccadic eye movement. Analyses of covariance indicated that both cocaine dependence and antisocial personality, but not opiate dependence, were associated with a significant reduction in gain of smooth pursuit eye movement. Cocaine dependence and antisocial personality also slowed the onset of saccadic eye movements, but only in men. No group differences were found in the accuracy of saccadic eye movements. The results suggest that the neurophysiological effects of cocaine dependence and antisocial personality overshadow the effects of heroin. The significance of these findings for visual attention and reading skill has yet to be assessed.