Visual-vestibular interaction in the control of head and eye movement: The role of visual feedback and predictive mechanisms

Progress in Neurobiology Vol. 41, pp. 435 to 472, 1993 Printed in Great Britain. All rights reserved

0301-0082/93[$24.00 © 1993 Pergamon Press Ltd

V I S U A L - V E S T I B U L A R I N T E R A C T I O N IN THE C O N T R O L OF H E A D A N D EYE M O V E M E N T : THE ROLE OF V I S U A L FEEDBACK AND PREDICTIVE MECHANISMS G. R. BARNES M R C Human Movement and Balance Unit, Institute of Neurology, 23 Queen Square, London WCIN 3BG, U.K. (Received 2 July 1992)

CONTENTS 1. Introduction 2. Basic control mechanisms of conjugate eye movement 2.1. Vestibulo-ocular reflex 2.1.1. Physiology 2.1.2. Dynamic characteristics 2.2. Optokinetic reflex 2.3. Smooth pursuit eye movements 2.3.1. Dynamic characteristics 2.3.2. Positional versus velocity feedback 2.3.3. Conflicting motion stimuli and the role of attention 2.4. Saccadic eye movements 3. Modification of the VOR by visual and non-visual mechanisms 3.1. Viewing earth-fixed objects--visual enhancement of the VOR 3.2. Viewing head-fixed objects--visual suppression of the VOR 3.3. Evidence for non-visual VOR suppression 3.4. Modelling of the mechanisms of conjugate eye movement control 3.5. Neurophysiology of pursuit and visual-vestibular interactions 4. Changes in performance associated with primary visual feedback characteristics 4.1. General observations 4.2. Effects of target location and size 4.2.1. OKN 4.2.2. Pursuit 4.2.3. VOR suppression 4.3. Effect of tachistoscopic target presentation 4.3.1. Pursuit and OKN 4.3.2. VOR suppression 4.3.3. Head-free pursuit 4.4. Effect of stimulus velocity 4.4.1. OKN 4.4.2. Pursuit 4.4.3. VOR suppression 4.4.4. Head-free pursuit 4.5. The role of visual feedback: conclusions 5. Changes in performance associated with the predictability of the stimulus 5.1. General observations 5.2. Effect of pseudo-random stimuli 5.2.1. Pursuit and OKN 5.2.2. VOR suppression 5.2.3. Non-visual VOR suppression 5.2.4. Head-free pursuit 5.3. Transient changes in stimulus motion 5.3.1. Pursuit 5.3.2. VOR suppression 5.3.3. Head-free pursuit 5.4. Predictive responses evoked by repeated transient stimulation 5.4.1. Pursuit 5.4.2. Head-free pursuit and VOR suppression 5.5. The role of predictive control: conclusions 5.5.1. The mechanism of predictive control 5.5.2. Neurophysiology of prediction 6. General conclusions 6.1. Visual versus non-visual VOR suppression 6.2. Implications for diagnosis and adaptive recovery References 435

436 436 436 436 437 439 44O 440 441 441 443 444 444 445 445 446 447 449 449 449 449 449 449 450 451 451 451 451 453 454 454 455 456 456 456 457 457 459 459 459 460 460 461 462 462 462 463 463 463 464 465 465 467 468

436

G.R. BARNES 1. INTRODUCTION

One of the most remarkable control mechanisms to be found in humans and other vertebrates is the system which allows our view of the outside world to be stabilized on the retina of the eye when engaging in normal locomotor activities. The basis of this behaviour lies in a set of four principal mechanisms for generating reflex eye movements that compensate for the movement of the head and body. Without such a system man would not be able to see objects around him when engaging in activities such as walking and running since if the eyes did not move appropriately with respect to the head the motion of the images formed on the retina would be continuously swept across the retina, causing considerable blurring and consequent loss of visual acuity. Two of these reflex mechanisms, the vestibuio-ocular reflex (VOR) and the optokinetic reflex operate on almost a wholly subconscious level. The remaining two, the smooth pursuit reflex and the more rapidly acting saccadic system are much more heavily influenced by volitional control, although both exhibit aspects of purely reflex behaviour. In order to compare these systems it is important to understand their dynamic properties and the various aspects of non-linear behaviour associated with them. In this review the behaviour of these four basic mechanisms of conjugate eye movement control will first be examined with particular reference to the human subject and the complex manner in which they interact to coordinate head and eye movements will be described. Then various aspects of the detailed behaviour of the feedback mechanisms will be described and the evidence for their participation in each of the eye movement control mechanisms to which they are relevant will be discussed. Although a considerable amount has been learnt about the action of these mechanisms, there is still much debate in this area about the precise nature and similarity of the various mechanisms involved in head-eye coordination. The ultimate resolution of these problems is important in providing reliable diagnostic information in patients with various disorders and in determining the most profitable adaptive therapeutic procedures.

2. BASIC CONTROL MECHANISMS OF CONJUGATE EYE MOVEMENT

are made during visual searching manoeuvres, stimulate activity within the semicircular canals. As indicated in Fig. 1, during a rotational acceleration of the head the fluid (endolymph) within the canal tends to remain stationary in space because of its inertia, thus causing the cupula, which contains the transducing hair cells, to become deflected by the relative motion of the fluid with respect to the canal walls. However, endolymph is a viscous fluid and its motion tends to be slowed by viscous friction at the fluid-canal boundary. The motion of the fluid within the canal is also resisted by the elasticity of the cupula which tends to push the endolymph back around the canal. The deflection of the cupula is only sustained if there is a continuous angular acceleration of the head, but because of the viscous nature of the endolymph this deflection is only slowly built up in an exponential manner, with a time constant which is of the order of 10 sec in the human. Thus, for short duration ( < 5 see), or high frequency, head movements cupula deflection is actually proportional to angular head velocity. When the head is rotated to the right (i,e. clockwise when viewed from above, Fig. 1) the deflection of the cupula causes an increase in the firing rate in the vestibular nerve of the right semicircular canal that is approximately proportional to the angle of cupula deflection (Fernandez and Goldberg, 1971). The most direct pathway for the transmission of this neural

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2.1.1. Physiology The vestibular apparatus of the inner ear contains two distinct types of transducer: the semicircular canals, which are sensitive to angular accelerations, and the otolith organs, that sense linear acceleration and thereby are also affected by changes in orientation with respect to gravitational acceleration. In this review only the behaviour of the semicircular canals will be considered, since little is known at present about the otolith-ocular reflexes and their interaction with the visual system. Rotational movements of the head, whether they be induced by passive stimulation of the head as occurs during activities such as running or walking, or actively by the sort of volitional head movements that

FIG. 1. A simplified diagram of the vestibulo-ocular pathways involved in the control of lateral eye movements. A clockwise rotation of the head induces excitatory activity in the right semicircular canal (SCC) which is relayed via the Vlllth cranial nerve (NVIII) to the vestibular nuclei (VN) in the brainstem. This activity is conveyed to the contralateral abducens nucleus (ABN) that is directly responsible for contraction of the left lateral rectus eye muscle(LR) through the 6th cranial nerve (NVI) and to abducens internuclear neurons that indirectly excite the right medial rectus muscle (MR) via a crossed connection through the oculomotor nucleus (OMN) and the 3rd cranial nerve (NIII). Other interconnections are responsible for the reciprocal innervation of other eye muscles, resulting in a coordinated eye rotation to the left with respect to the head.

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FIo. 2. Examples of vestibular nystagmus induced by whole body rotation on a turntable, stimulating the lateral semicircular canals with different frequencies of sinusoidal oscillation. Note the manner in which the slow-phase component of eye velocity is sinusoidally modulated but has opposite polarity to the head velocity stimulus. activity is via the vestibular nuclei in the brainstem to the contralateral abducens nucleus which then induces excitatory activity in the lateral rectus muscle of the left eye. Other inhibitory pathways and mechanisms of reciprocal innervation (Leigh and Zee, 1991) result in conjugate eye movements. The most important point is that, in general, the firing rate in the vestibular nerve is proportional to eye velocity, which is thus proportional to head velocity over a wide dynamic range. 2.1.2. Dynamic characteristics The dynamic behaviour of this stabilizing vestibulo-ocular reflex has now been extensively investigated in humans (Benson, 1970; Hixson, 1974; Barr et al., 1976; Wolfe et al., 1978; Tomlinson et al., 1980 ) and in other mammals (Keller, 1978; Furman et al., 1979, 1982; Donaghy, 1980; Buettner et al.,

1981). Typical responses of the vestibulo-ocular reflex to controlled sinusoidal oscillation of a turntable are shown in Fig. 2. At low frequencies ( < 1.0Hz) of angular oscillation a direction-changing eye movement, known as nystagmus, may be observed. It is the slow-phase components of the nystagmus that are compensatory for the movement of the head, the fast-phase eye movements constituting a rapid resetting mechanism. The distinction between these two components may be easily appreciated by differentiation of the eye and head position signals with respect to time. The component of the derived eye velocity trace corresponding to the slow-phase component of the nystagmus is modulated in accord with the head velocity signal, but it is of opposite polarity. The efficacy of this compensatory eye movement can be assessed by determination of two features of the response. One is the gain, or amplitude ratio between slow-phase eye velocity and head velocity,

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which should be unity for perfect compensation. The other is the phase relationship between stimulus and response; this should be zero for perfect compensation. In practice these two measures of performance vary not only with the frequency of head oscillation but also with the general level of arousal of the subject and the instruction set, a feature that will be discussed in more detail later. The normal method of eliciting the response is either to give no specific instruction or to ask the subject to carry out some alerting task such as mental arithmetic. Then, as indicated in Fig. 3, at frequencies between 0.05 and 0.5 Hz eye velocity is approximately proportional to head velocity, although the gain of the response is less than unity, varying widely amongst individuals in the range 0.3-0.7. But in the important frequency range between 0.5 and 2 Hz, in which most voluntary head movements (Barnes, 1979; Zangemeister et al., 1981) and those induced by locomotor activities (Melvill Jones and Watt, 1971a,b; Grossman et al., 1988; Gresty, 1987, 1989 ) are made, the gain is closest to unity and the phase differs little from zero. There is some evidence that the VOR functions in yaw and pitch at frequencies up to 20 Hz (Gauthier et al., 1984; Stott, 1984). At frequencies below 0.05 Hz eye velocity is effectively proportional to head angular acceleration and thus gain decreases with decreasing frequency. This low frequency behaviour may also be

examined by administering a transient change in head acceleration, such as a rapid stop from constant angular velocity. This stimulus induces a nystagmus in which slow-phase velocity decreases exponentially with a time constant of 10-20 sec in humans. This time constant was originally assumed to reflect the dynamic behaviour of the cupula-endolymph system as indicated above, but it is now known from comparisons in animal studies that the time constant of the nystagmus is generally considerably longer than that of the end organ (Goldberg and Fernandez, 1971). The dynamic modification is thought to be accomplished by a central integration process which is also involved in the optokinetic response (Raphan et aL, 1977) as described in the next section. One of the most important stimuli to the semicircular canals comes from active head movements made during head-free pursuit and target search. The gain of the VOR evoked by active head movement tends to be slightly higher than that induced by passive rotation on the turntable (Takahashi et al., 1981; Jell et al., 1982; Barnes et al., 1985), particularly at frequencies below 0.5 Hz. The origin of this increased gain is not known at present. It could represent the effect of a general increase in arousal brought about by the volitional activity or it could be a small additional contribution from the cervico-ocular reflex (COR). The COR is a mechanism for inducing

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FIG. 3. The dynamic characteristics of the vestibulo-ocular reflex response to sinusoidaLangular oscillation of the head about the yaw axis. Gain represents the ratio of slow-phase eye velocity to angular head velocity. Phase is defined on the assumption that eye velocity is compensatory for head velocity. The results have been obtained from the following sources with peak velocities (V) and numbers of subjects tested (N) as indicated: O and • (Benson, 1970)--man, V = 30°/s¢c (N =9); [] (Hixson, 1974)--man, V = 50°/see (N = 10); + (Wolfe et al., 1978)---man, V ---50°/see (N = 50); x (Barnes and Forbat, 1979)--man, V = 50°/see (N = 12); A (Keller, 1978)--monkey, V = 100°/scc (N = 4).

VISUAL-VESTIBULARINTERACTION compensatory eye movements as a result of the stimulation of receptors within the neck. In normal humans it is largely vestigial (Dichgans, 1974; Barnes and Forbat, 1979; Takemori and Suzuki, 1971), but there is some evidence that it becomes potentiated in patients with bilateral loss of vestibular function (Dichgans et al., 1973; Bronstein and Hood, 1986), effectively taking over the role of the VOR during active head movements.

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@18 0.4 m 2.2. OPTOKINETIC REFLEX Optokinetic nystagmus (OKN) is traditionally thought of as an eye movement induced by the motion of a large visual field. This is typified by the eye movements evoked when viewing the visual scene from a moving railway carriage ('Eisenbahn nystagmus'). Like vestibular nystagrnus, it is characterized by the presence of two distinct types of eye movement, a slow-phase component which is in the same direction as the moving visual field and a fast-phase component, which produces rapid resetting of eye position within the orbit. It is predominantly the slow-phase component which will be discussed here. In the laboratory or clinic this nystagmus is generally evoked by instructing the subject to stare at a large moving pattern of stripes or random dots without actively attempting to follow any particular feature in the display. At low stimulus velocities eye velocity closely matches the velocity of the display. In this way the velocity of images formed on the retina is maintained close to zero and objects in the visual field can be seen clearly without blur, although the actual portion of the visual scene presented on the fovea changes with each fast-phase component. At higher velocities (>40-60°/sec) slow-phase eye velocity does not match display velocity so closely, exhibiting a saturation effect which will be discussed in more detail later. In this type of 'stare nystagrnus' the fast-phase components normally direct eye position into that part of the visual field from which the motion originates. If the subject is requested to 'look' at the moving display a different pattern of nystagrnus is elicited in which the eye deviates in the direction of the motion and the fast-phases return the eye to its central position (Hood and Leech, 1974). In such circumstances the slow-phase eye velocity is slightly greater than that evoked by the 'stare' instruction (Honrubia et al., 1967) and the amplitude of the slow-phase components is increased as the subject attempts to look at and follow the elements of the pattern. One of the most important features of OKN lies in the transient dynamic characteristics of the response. In a phylogenitically primitive animal such as the rabbit the slow-phase velocity of the OKN response to a constant velocity display motion may take as long as 10-20 sec to build up to its asymptotic level (Collewijn, 1985). In contrast, in the monkey, there is a very rapid ( < 1 sec) rise in eye velocity to a gain of approximately 0.6, followed by a much slower rise to a higher asymptotic level that is close to unity (Cohen et al., 1977). In man the rapid onset

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component is even more dominant. It has become evident that this bi-phasic response reveals the activity of two separate mechanisms of oculomotor control. The slower response is mediated by a subeorticai 'indirect' pathway that contains what has been termed a velocity storage mechanism (Cohen et al., 1977), which is essentially a low-pass filter with a rather long time constant (10-20 see). The rapid response is brought about through the 'direct' pathway, which involves transmission through visual cortex and the cerebellum (Tusa and Zee, 1989). As the phylogenetic scale is ascended the activity of the 'indirect' pathway can still be observed in higher animals as the slowly decaying pattern of optokinetic after-nystagmus (OKAN) which is present when the subject is suddenly plunged into darkness after prolonged optokinetic stimulation and the velocity store decays exponentially (Raphan et al., 1977). The storage mechanism is intimately associated with the response of the semicircular canals as outlined above and is, indeed, dependent on their integrity (Cohen et al., 1973). In essence its function seems to be that of complementing and extending the dynamic range of the canals for the purpose of equating the effects of whole-body and visual-world rotation and thus enhancing spatial orientation. The dynamic properties of OKN have also been extensively investigated through the use of sinusoidaily oscillating optokinetic stimuli in a number of species (rabbit--Baarsma and Coilewijn, 1974; cat--Evinger and Fuchs, 1978; Godaux and Vanderkelen, 1984; monkey--Paige, 1983; man--Yasui and Young, 1984). In man slow-phase eye velocity gain is very close to unity at frequencies between 0.05 and 0.5 Hz (Fig. 4) but decreases rapidly at frequencies between 0.5 and 3 Hz, with a corresponding increase in phase lag. This fall off in high frequency behaviour is associated with the initial rapid response of the 'direct' pathway of the optokinetic system.

440

G.R. BARNES 2.3. SMOOTH PURSUIT EYE MOVEMENTS

2.3.1. Dynamic characteristics Animals with binocular vision have developed an additional oculomotor control system, the pursuit reflex, that is not present in lower animals such as the rabbit, specifically for tracking small moving objects. If the human subject is instructed to follow the sinusoidal motion of a small target in the horizontal plane with the head fixed the eye movement is composed of both slow and fast-phase components (Fig. 5). At low frequencies ( < 0.4 Hz) the movement is almost wholly smooth and eye velocity closely matches target velocity. At higher frequencies eye velocity is not able to match target velocity so adequately, but the saccadic system interjects small catch-up saccades that re-align the image of the target on the fovea. The overall performance of the pursuit system is best described by consideration of two measures: (a) the eye displacement gain, that is the ratio of overall eye displacement (including the saccadic components) to target displacement and (b)

slow-phase eye velocity gain, that is the ratio of the smooth component of eye velocity (after removal of the saccadic components) to target velocity. In response to a sinusoidal stimulus the gain of slow-phase eye velocity is very similar to that of the optokinetic system (cf Fig. 6 with Fig. 4), breaking down at frequencies between 0.5 and 3 Hz. In contrast, the saccadic system maintains overall eye displacement gain close to unity up to frequencies of I Hz. Like the optokinetic response, the pursuit reflex is subject to velocity saturation, the response breaking down when the velocity of target movement is too great ( > 40-60°/see). The basic performance of the pursuit reflex was recognized by early experimenters (Stark et al., 1962; Dallos and Jones, 1963), although they were not able to separate the fast and slow components of the response. Nevertheless, it was realized that the pursuit reflex must contain some form of predictive element. This was evident from the ability to achieve a higher level of gain and less phase error when pursuing a target oscillating with a regular periodic waveform than when following a target which moved in a more random manner. A more

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(B). Spikes on the eye velocity trace represent the catch-up saceadi¢ movements which, at the lower frequency, are of very low amplitude and velocity and are almost undetectable on the eye displacement trace.

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FIG. 6. The gain and phase characteristics of the ocular pursuit response to discrete sinusoidal target oscillation at frequencies between 0.1 and 1.6 Hz. Common symbols represent responses to target motion stimuli in which peak target displacement was held constant throughout the frequency range. Peak displacements were + 5, 10 and 15° as indicated. Broken lines represent the ratio of overall eye displacement, (i.e. including any saecadic components), to target displacement, whereas the solid lines represent the ratio of slow-phase eye velocity to target velocity. Eye displacement phase has been omitted for clarity, but is similar to eye velocity phase. Mean of 20 subjects (controls used in various experiments, e.g. Waterston et aL, 1992) + 1 SEM. detailed discussion of prediction will be presented later. Pursuit and optokinesis are generally treated as if they were separate types of eye movement, yet they clearly share a number of features in common. Some of the confusion surrounding this topic has been associated with the inability to separate differences arising from the type of visual motion stimuli used from those which are due to the underlying neural mechanisms. Whereas the optokinetic response is traditionally associated with stimulation of the velocity drive mechanisms of the visual system by a large moving field, pursuit is normally described as an attempt to track a small object so as to maintain its position on the fovea. In fact, eye movements indistinguishable from optokinetic nystagmus can be induced even by a very small moving target. Cheng and Outerbridge (1979) showed that the motion of a small target could evoke a short burst of nystagmus with peak slow-phase velocity comparable to target velocity as it passed across the fovea even though the subjects did not actively pursue it. Similarly, Barnes and Hill (1984) found that it was almost impossible for subjects to prevent the development of a sustained direction changing nystagmus when viewing a small, sinusoidally oscillating target, provided that there were no other stationary visual cues present, even though they attempted not to actively pursue it, but to hold fixation as it moved (Fig. 7).

2.3.2. Positional versus velocity feedback These results emphasize the importance of retinal velocity error in the control of smooth pursuit, but it is evident that positional control is also important. The original emphasis on velocity feedback came from the experiments of Rashbass(1961), who showed that when the target steps to one side but then moves at constant velocity towards the other side (the

so-called step-ramp stimulus), the eye did not appear to respond to the inital step, only to the ramp component. Subsequent experiments using more sensitive techniques (Wyatt and Pola, 1987) have shown that there is some smooth eye movement response to the step displacement and there is some evidence for continuous positional feedback for small ( < 1°) displacement errors (de Bie, 1984). Larger target displacements can also give rise to smooth eye movements but in this instance the effective stimulus appears to operate through the velocity feedback system as an impulsive velocity drive forming an input to the predictive mechanisms of pursuit (Kowler and Steinman, 1979; Barnes et al., 1987; Carl and Gellman, 1987; Barnes and Asselman, 1991, 1992). The most important aspect of positional control in the normal pursuit response is the involvement of the saccadic system which continually attempts to realign the image on the fovea if the velocity of the eye does not match that of the target. Such a manoeuvre allows the greatest level of visual feedback gain to be achieved by centring the target over the foveal area, which is far more sensitive to retinal image motion than the peripheral retina (Dubois and Collewijn, 1979). However, it is important to emphasize that pursuit is not a response that is necessarily restricted to stimulation of the fovea. It is quite feasible for the subject to pursue a moving target which is kept in the peripheral visual field (Rashbass, 1961; Michaiski et al., 1977; Winterson and Steinman, 1978) (Fig. 7), although eye velocity may be degraded (Barnes and Hill, 1984) as described in Section 4.2.

2.3.3. Conflicting motion stimuli and the role o f attention One of the implications of the findings described so far is that the motion of any stimulus in the visual

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field has the potential to evoke eye movement. If so, it might be expected that when the subject is presented with a number of such moving stimuli a conflict could arise. A simple example is that it ought to be more difficult to track a target against a structured background rather than a blank background, because the relative motion of the background should induce an antagonistic optokinetic drive tending to slow the eye movement. It is possible to demonstrate such interactions, although they tend to cause a decrease in eye velocity of no more than 10-20% in normal circumstances (Kowler et al., 1984; Collewijn and Tamminga, 1984; Barnes and Crombie, 1985). The major reason for this appears to be that pursuit involves the potentiation, through volitional activation, of the available visual feedback information from one particular selected source. This mechanism allows the subject to overcome almost totally the influence of more powerful moving stimuli, although their influence can still be demonstrated if the visual feedback for the selected 'pursuit' target is degraded (Barnes and Crombie, 1985; Collewijn and Tamminga, 1984; Worfolk and Barnes, 1992) (Fig. 8). It appears that the interaction depends on the weighting of the visual motion stimuli, which is dependent on such factors as their peripheral location (Dubois and Collewijn, 1979; Barnes and Crombie, 1985). One way of demonstrating the effects of potentiation is to compare the oculomotor response during normal 'active' pursuit and a 'passive' stimulation condition

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in which the subject is instructed to attempt to ignore the motion of the stimulus (Barnes and Hill, 1984). Such conditions are comparable to the 'look' and 'stare' instructions for OKN described above. In such conditions, the velocity of the slow-phase component during passive stimulation is normally only 60-70% of that induced during active pursuit, as verified by subsequent experiments (Pola and Wyatt, 1985; Barnes and Crombie, 1985). Most importantly, if the visual feedback is degraded, for example, by peripheral target location, both active and passive responses are reduced, indicating that the potentiated response is still dependent on the visual feedback. The similarity in the frequency response characteristics of pursuit and OKN at frequencies above 0.5 Hz probably indicates that both functions share common access to the 'direct' cortical pathways that are responsible for the rapid onset component of OKN, although it is possible that the basic response is manipulated in different ways in pursuit and OKN (Miles, 1991). It is of particular interest that the high frequency attenuation of the gain can be observed in both the actively and passively induced eye movements whether the visual stimulation arises from the peripheral or foveal areas (Barnes and Hill, 1984), suggesting that all parts of the retina have access to the direct pathway. Optokinetic stimulation from the periphery also exhibits the rapid onset component, which is the temporal domain equivalent of the high frequency attenuation (Buttner et al., 1983). In ad-

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FIG. 8. Examples of eye movements induced during active pursuit of a target oscillating sinusoidaUy with peak displacement of + 5° and frequency 0.2 Hz against a stationary background. The target was either a single image (upper traces) or a pair of images separated vertically by + 3.5°. The background was either non-structured (a) or composed of random dots (b). (From Barnes and Crombie, 1985.)

dition, there is some evidence that prolonged constant velocity pursuit can induce an optokinetic afternystagrnus (Muratore and Zee, 1979), suggesting that pursuit may also have access to the 'indirect' pathway and its associated velocity storage mechanism. On the basis of all these observations a more adequate definition of the pursuit reflex might be as follows. The ocular pursuit system allows the subject to maintain the position of the image of a selected object at a specific location in relation to the fovea through two mechanisms: (a) volitional control of the velocity of the eye through the potentiation of visual feedback from any area of the retina and (b) the interjection of saccadic corrective movements that enable overall eye displacement to closely match target displacement.

2.4. SACCADICEVE MOVEMENTS It is evident from the foregoing discussion that saccadic eye movements play a very important part as a rapid resetting mechanism in the VOR, O K N and pursuit responses in addition to the smooth eye movements. Saccadic eye movements tend to have a

velocity that is constant for a particular displacement, the relationship between velocity and displacement being referred to as the main sequence (Bahill et al., 1975). For eye displacements greater than approximately 20 ° peak eye velocity is normally between 400 and 600°/see (see Becker, 1989 for a review of saccade metrics). Saccadic eye movements are generated within two specific brainstem sites, the paramedian pontine reticular formation for horizontal saccades and the mesencephalic reticular formation for vertical saccades (Henn et al., 1982). Neurons in these areas have been shown to fire with a short burst of activity for the duration of the saccade. What is more, these units fire in much the same way for voluntary saccades and the fast-phases of vestibular and optokinetic nystagmus (Ron et al., 1972). The normal laboratory assessment of saccade metrics is carried out by instructing the subject to transfer gaze between stationary fixation targets, in which condition the amplitude of the saccade is determined by the difference between the current position of the target image on the retina and the fovea. During pursuit there is evidence that the amplitude of catch-up saccades is based not only on this displacement error but also on target velocity, so that there is some compensation

444

G.R. BAgNES

for the extra displacement error that accrues in the latent period before the saccade is completed (Robinson, 1965; Thurston et aL, 1988).

with frequency. At low frequencies the difference in gain would result in relative motion of seen objects with respect to the retina, which would therefore appear as a moving visual stimulus. The pursuit system would be able to reduce the velocity error at frequencies up to 0.5-1.0 Hz, but not at higher frequencies, where the VOR gain would need to be close to unity to operate effectively. It is now realized that the gain of the VOR can be raised to near unity at frequencies below 0.5 Hz (Gauthier and Robinson, 1975; Barr et al., 1976.) If the subject is instructed to imagine fixating an earth-fixed target in darkness (Fig. 9), which appears to render the pursuit system redundant in this capacity. However, there is some evidence (Baloh et al., 1984) that the pursuit system is still necessary to enhance the VOR for large amplitude movements ( > 50 °) at low frequencies ( < 0.2 Hz) of stimulation. The difference in the dynamic frequency range of the pursuit and vestibulo-ocular reflex responses may be demonstrated by a simple experiment (Benson and

3. M O D I F I C A T I O N O F THE VOR BY VISUAL AND NON-VISUAL M E C H A N I S M S 3.1. VIEWINGEARTH-FIXEDOBJECTS---VISUAL ENHANCEMENTOF THE VOR Although the purpose of the vestibulo-ocular reflex is clearly to compensate for angular motion of the head it is evident from the results presented in Fig. 3 that at frequencies below 0.5 Hz the gain of the response is inadequate to achieve full compensation. Originally, it was generally assumed that the reduced gain was of no importance because the error could easily be accommodated by the action of the visually driven pursuit mechanisms. This, indeed, seemed to present a rational explanation for the changes in gain

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445

VISUAL-VESTIBULARINTERACTION

Barnes, 1978). If the observer shakes an object held in the hand from side to side then the object can be tracked very effectively at low frequency ( < 1 Hz) so that the object can be seen quite clearly, but if the frequency is above this range the image becomes blurred because the eyes can no longer match the velocity of the target. In contrast, if the head is shaken from side to side at frequencies up to at least 6 Hz the observer has no problem in clearly seeing the target because of the compensatory nature of the VOR, which effectively stabilizes the eye in space. 3.2. VIEWING HEAD-FIXED OBJECTS---VISUAL

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The vestibulo-ocular reflex serves a very useful purpose in allowing the visual world to be stabilized during body movements, but there are some practical conditions in which the compensatory effects of the vestibulo-ocular response are not appropriate. The most important situation is that which operates during a coordinated head and eye movement to follow a smoothly moving target (head-free pursuit). Rotation of the head in the direction of the target motion necessarily evokes a slow-phase compensatory eye movement that would effectively null the velocity of the eye with respect to an earth-referenced coordinate system if the gain of the VOR were unity. In order to match gaze velocity to the velocity of the moving target it is necessary to suppress the activity of the VOR in this situation. There are other situations in which suppression of the VOR is required, none of them perhaps more demanding than those created by modern man in his attempts to travel in high-speed vehicles. A subject travelling in a fastmoving car is well able to see stationary objects, such as signposts, which are outside the moving vehicle, but may have considerable difficulty reading a map held in the hand because both man and map are subjected to similar levels and frequencies of vibration. The latter represents a complex situation in which relative motion between body components must be taken into consideration. A more simplified situation can be created in the laboratory by fixing the subject and the display to a turntable and exposing both to angular oscillation at various frequencies. The results of such experiments (Barnes et al., 1978; Lau et al., 1978; Lisberger et al., 1981; Baloh et al., 1986) have shown that normal subjects are able to suppress the VOR induced by whole-body rotation at frequencies up to 0.5-1.0 Hz, but that at higher frequencies there is a rapid deterioration, so that at 2 Hz eye velocity gain during attempted fixation is nearly as great as that in the dark. Associated with this eye movement relative to the head-fixed display there is a blurring of visual images leading to a decrement in visual acuity (Barnes et al., 1978). The range of frequencies in which the ability to suppress the vestibular response breaks down is similar to that in which the pursuit reflex also becomes ineffective. Indeed, when direct comparisons have been made in the same groups of subjects (Fig. 10), based on the predictions of models of the type described below, no statistically significant difference has been observed (Barnes et al., 1978; Paige, 1983; Lisberger et al., 1981; Koenig et al., JPN 41/4--D

Frequency (Hz) Fro. 10. A comparison of the frequency characteristics of pursuit and VOR suppression. The gain of pursuit error represents the difference between eye velocity and target velocity expressed as a ratio of target velocity. Peak target velocity was _ 40°/sec. VOR suppression gain represents the ratio of eye velocity during viewing of a head-fixed target to the eye velocity recorded in darkness. The stimulus was a sinusoidal whole-body oscillation with peak velocity ± 40°/sec. (Redrawn from Barnes et al., 1978.) Mean of 12 subjects ± I S.D. 1986, 1987). These observations led to the suggestion that pursuit and VOR suppression are subserved by similar neurological mechanisms. In support of this concept there is a considerable body of clinical evidence which indicates that those patients who have difficulty in pursuit also have impaired suppression of the VOR (Zee et al., 1976; Dichgans et al., 1978; Halmagyi and Gresty, 1979; Henriksson et al., 1984; Baloh et al., 1986). This is notably true of patients with cerebellar degeneration and lesion studies in monkeys also support this conclusion (Zee et al., 1981). The administration of drugs such as alcohol also has a similar effect of degrading both pursuit and VOR suppression (Baloh et al., 1979; Barnes et al., 1985). However, there is now convincing evidence that other non-visual mechanisms can play a significant part in the interaction in some circumstances.

3.3. EVIDENCE FOR NoN-VISUAL V O R SUPPRESSION

The gain of the VOR can be raised to near-unity even in the absence of a visual stimulus, as noted above (Gauthier and Robinson 1975; Barr et al., 1976), if subjects are instructed to imagine an earthfixed target (Fig. 9). A notable feature of this response is that the fast-phase activity tends to disappear or to become reversed, resembling the catch-up saccades of pursuit when imagining an earth-fixed target. These authors also showed that the VOR gain could be suppressed by asking the subject to imagine a head-fixed target in darkness (Fig. 9) and this has since been substantiated in a number of experiments involving both passive (Baloh et al., 1984; McKinley and Peterson, 1985; Barnes and Eason, 1988) and active head movement (Jell et al., 1982;). Other evidence has often been cited in support of non-visual suppression (Tomlinson and Robinson, 1981). First, it has been observed when recording

446

G.R. BARNES

from cells surrounding the vestibular nuclei that there is often a dissociation between their sensitivity to pursuit and VOR suppression (Tomlinson and Robinson, 1981; May and McCrea, 1985). Second, torsional VOR responses can be suppressed even though there is no adequate torsional OKN and there is nothing that corresponds to pursuit for torsional eye movements (Leigh et al., 1989). Third, there is mounting clinical evidence that appears to show that some patients are able to perform one task much better than the other (Chambers and Gresty, 1983; Ranalli and Sharpe, 1988). In addition it has been shown by Mai et al. (1986) that there can be a dissociation between the two in the wash-out phase with barbiturates, although it should be noted that the authors did not compare strictly identical responses in this experiment. On the basis of this evidence Robinson (1982) constructed a powerful hypothesis about the role of non-visual mechanisms in the suppression of the VOR, which has influenced much of the research in this area. He stated that this function could be achieved, wholly or partially, through central mechanisms which do not require visual feedback. He reasoned that since the velocity saturation effects were so restrictive in head-fixed pursuit (see Section 4.4) it would improve tracking performance if the system did not have to rely on the same restrictions to suppress the VOR during head-free pursuit. In theory, a suitable signal to cancel the VOR signal could easily be provided during head-free pursuit by an efference copy of the head movement drive command. In addition, during passive stimulation

Non-visual enhancement i

Robinson suggested that predictive mechanisms could provide an internal representation of the head motion signal which could be used to suppress the VOR. Unfortunately, Robinson did not give any indication of whether this central suppressive mechanism might give total or only partial suppression. In reality it is most likely that some form of central suppression does take place in addition to visual feedback, but that both of these mechanisms participate in VOR suppression in different ways for different experimental conditions (Barnes and Eason, 1988). 3.4. MODELLINGTHE MECHANISMSOF CONJUGATE EYE MOVEMENTCONTROL The simplest way to represent these possibilities is through the development of a mathematical model of the interactive mechanisms. Initially a simplified model of the system will be used as shown in Fig. I I. A more complex model will be presented later. The basic vestibuio-ocular reflex arc is represented by Pathway l, in which head velocity (6) is transduced by the semicircular canals (SCC), giving the signal 6 ' and transmitted to the extraocular muscles (EOM) resulting in eye velocity (6I). The visual feedback originates at the retina (junction A), where the relative motion of images across the retina represents the difference between target velocity (~) and eye velocity (0) or retinal velocity error (~). The visual feedback is represented by Pathway 2, in which the retinal velocity error signal is dynamically modified by the function F(s), where s is the Laplacian operator. The

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FIG. 11. A simplified model of the possible mechanisms of visual vestibular interaction in the control of eye movement. Pathway (1) represents the basic vestibulo-ocular reflex arc defined in Fig. 1. Pathway (2) represents the visual feedback mechanisms responsible for the control of pursuit eye movements and visual suppression of the VOR. Pathways (3) and (4) are hypothetical mechanisms for the non-visual suppression or enhancement of the VOR which rely on central volitional control for their initiation. The dynamic characteristics of the elements of the model are represented as follows: Gv(s)--the semicircular canals; GE(s)--the extraocular muscles; F(s)-visual feedback, which includes a delay of approximately 100 msec; Gu(s)-the central reconstruction of a head velocity estimate (6') (Gu(s)= l/Gv(s); KE, Kc--constants. 6--head velocity; 6--target velocity; 0---eye velocity; ~--retinal error velocity; ~"----estimateof gaze velocity, s is the Laplace operator.

447

VISUAL-VESTIBULARINTERACTION

visual feedback is assumed to interact with Pathway 1 at junction B to inhibit the vestibulo-ocular reflex. In addition there are two other pathways that are involved in VOR modification. Pathway 3 is responsible for non-visual VOR suppression. This mechanism may take the form of an inhibitory feedback of the efference copy of eye velocity as indicated in this diagram (see Barnes and Eason, 1988) or a non-linear system which brings about a parametric VOR gain reduction as proposed by Miles and Lisberger (1981). Similarly, Pathway 4 is responsible for the augmentation of VOR gain when the subject imagines an earth-fixed target in darkness, which may be accomplished by a parametric gain change or the switching in of an alternative channel of VOR control. The detailed behaviour of non-visual suppression mechanisms will not be considered here. The behaviour of the system for the various stimulus conditions considered will be as follows: Head-free pursuit: The relationship between target velocity (g)) and gaze velocity (~'), which is defined as the sum of head velocity (6) and eye velocity (O) may be represented by the following equation: ~r = 0 + $ = F'(s)/(l + F'(s))'~ +(1 -Gv'(S))/(1 + F ' ( s ) ) ' 6

(1)

where F'(s) = F(s)" GE(s) and

G~,(s) = Gv(s )" Gds). F(s) represents the dynamic response of the visual feedback system, Gv(s) that of the semicircular canal system and GE(s) that of the extraocular muscle system. Head-fixed pursuit and OKN: During pursuit of a moving target with the head stationary, q~ = 0, so that eye velocity (Op) is given by Eqn (1) as: 0~ = F'(s)/(1 + F'(s)). ~

(2)

VOR in darkness: During head motion in the dark there is no visual feedback, so that F(s) = 0. Then eye velocity (ODRK)is given by:

0DR~ = - Gt, RK(S)"$

(3)

where GDRK is the gain of the VOR recorded in darkness with mental alerting. VOR enhancement; viewing an earth-fixed target: In this condition (EFT) the target remains stationary so that 6 --0. Then eye velocity (OEFT) is given by: 0EFT= -- (GEFr + F'(s))/(1 + F'(s))' q~

(4)

where GEvr is the gain of the VOR relevant to the EFT condition. VOR suppression; viewing a head-fixed target: in this condition (HFT) target motion (~) is equal to head motion (6) and eye velocity (0aFT) is given by: OaFr= -- Gavr/(1 + F'(s))-$ = OD~K/(I + F'(s)). GHFr/GDRK (5) where G,vr is the VOR gain achieved during nonvisual suppression. In order to compare VOR suppression with pursuit it is necessary to calculate the efficiency of VOR

suppression (?~HFT)which may be defined by reference to Eqns (2) and (5) as: ~HFT =

1 -- OHFT/0DRK

= F ' ( s ) / ( l + F'(s)

+ (1 - GHFr/GDRK)/(I + F'(s)) = O/qJ"GHFr/GDRK+ 1 -- GHFr/GDRK. (6) From this it can be seen that if there were no non-visual suppression of the VOR (i.e. GHFT = GDRK), pursuit and VOR suppression would be equivalent irrespective of the detailed dynamic characteristics of the visual feedback (F(s)). However, because the characteristics of the visual feedback are highly non-linear such comparisons can only be made legitimately when the conditions for generating retinal velocity error are precisely similar in the two tasks. Although the precise dynamic behaviour of the visuomotor feedback is complex and includes the effects of prediction, it has become apparent from the results of a number of experiments (Barnes and Ruddock, 1989; Barnes and Asselman, 1991) that the response may be approximated by a low-pass filter as follows: F'(s) = Kv/(l + Ts).e "

(7)

where Kv is the gain of visual feedback, which normally has a value between 10 and 20 and T is the time constant of decay of the oculomotor response, which is approximately 0.5--1 sec. In the feedback mode this function contributes to the attenuation of eye velocity gain and the increase in phase lag at frequencies above 0.5 Hz (Fig. 6). This function also determines the initial transient response of the system which will be discussed later. The function e-'S in this pathway represents the processing delay of approximately 100 msec in the visuomotor feedback pathways (Carl and Gellman, 1987). When more detailed effects of changes in phase are taken into account (Barnes and Ruddock, 1989; Barnes, 1992) it appears likely that a band-pass filter would actually provide a more realistic simulation of the oculomotor dynamics (see Fig. 32). The function F(s) does not, however, take into account the dynamic behaviour of the 'indirect' velocity storage pathways, which undoubtedly play a negligible role in pursuit. 3.5. NEUROPHYS1OLOGYOF PURSUIT AND VISUAL-VESTIBULAR INTERACTIONS

As a result of a large number of experiments in various species it is now possible to identify many of the areas involved in pursuit, optokinesis and VOR suppression. As indicated earlier it is evident that there are two principal pathways of visual-vestibular interaction, the 'direct', cortical pathway and the 'indirect', subcortical pathway (Cohen et al., 1977). In lower animals such as the rabbit, in which there is solely a subcortical mechanism, the pathways have been traced from the retina, through the nucleus of the optic tract (NOT) and accessory optic system (AOS) to the vestibular nuclei by way of the nucleus prepositus hypoglossi (NPH) (Collewijn, 1975, 198 l). Similar pathways also exist in higher vertebrates (Hoffman and Schoppman, 1975, 1981; Hoffman

448

G.R. BARr~ES

et al., 1976; Precht, 1981), including man (Fredericks et al., 1988). Neurons in NOT and the dorsal terminal

nucleus (DTN) exhibit sensitivity to image motion on the retina, particularly for large field stimuli (Hoffman et al., 1988; Hoffman and Distler, 1989), but the response is non-linear and saturates at high velocities as discussed later (Section 4.4). Recent evidence has shown that stimulation of NOT and DTN in monkeys induces a nystagmus with slowly increasing slow-phase velocity (Schiff et al., 1988) and lesions of these areas abolish the velocity storage element of O K N whilst pursuit remains unaffected (Kato et al., 1988; Schiff et al., 1990). Units in the vestibular nuclei that respond to semicircular canal stimulation have also been shown to respond to large field optokinetic stimuli (Dichgans and Brandt, 1972; Henn et al., 1974; Waespe and Henn, 1977; Buettner and Bfittner, 1979). Waespe and Henn (1977a) reported that units within the vestibular nuclei of the monkey responded to both whole-body rotation and optokinetic stimuli and that the response was attenuated during suppression of the vestibular reflex. During constant rotation in the dark the response decayed exponentially in accord with the expected behaviour of the semicircular canals, whereas in the presence of a stationary display the VN units responded with a constant discharge. However, interaction was not complete, the response of the vestibular units saturating when the optokinetic display velocity exceeded 60°/sec, whereas the nystagmus reached much higher velocities. VN units were also found to be active during optokinetic after-nystagmus (Waespe and Henn, 1977b). There are clearly dissociations therefore between VN activity and eye movement and this is in part due to the predominance of the alternative cortical pathways in the control of eye movement in the monkey. The precise nature of the pathways for the cortical control of eye movements is still not clear although certain elements are well defined. Tusa and Zee (1989) have given an excellent rrsum~ of the cortical pathways, which is summarized in Fig. 12. The major link involves transmission of visual motion information from retinal ganglion cells through the lateral geniculate body of the thalamus to primary visual cortex (V l). Here, so-called complex cells which are sensitive to visual motion exhibit similar velocity saturation characteristics to those found in NOT. Neurons in VI project directly and indirectly via extrastriate cortex (V2), to two areas in visual association cortex referred to as MT (middle temporal) and MST (medial superior temporal) which are thought to lie on the temporo-occipito-parietal border in humans (Tusa and Zee, 1989). Area MT encodes retinal error velocity but MST appears to be the first location in the pursuit pathway in which there is also some representation of eye velocity (Newsome et al., 1988). The major corticofugal pathway for pursuit is then probably through the dorsolateral pontine nuclei (DLPN) in the brainstem. However, two other cortical areas appear to be involved in pursuit. One is the posterior parietal cortex (PPC), which receives input from MT, is in bidirectional contact with MST and is thought to be involved with spatial attentional mechanisms (Tusa and Zee, 1989). The other is the frontal eye field (FEF) which receives input from MT,

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FIG. 12. A schematic diagram of the major pathways involved in the generation of the pursuit reflex response. The output from the left hemi-retina in each eye, which receives input from the right half of the visual field, is carried via crossed and uncrossed fibres to the left lateral geniculate body (LGN) and the primary visual cortex (V l). Fibres from Vl pass ipsilaterally to area MT (middle temporal cortex) both directly and indirectly via extrastriate cortex (V2). Fibres from MT pass to area MST (medial superior temporal cortex) on both sides. Posterior parietal cortex (PPC) is probably involved in spatial attentional mechanisms for the control of activity in MST. The major efferent pathway is via the dorsolateral pontine nuclei (DLPN) in the brainstem, although there are other connections via the frontal eye fields (FEF) and the nucleus reticularis tegmenti pontis (NRTP) the activity in the brainstem sites (DLPN and NRTP) is predominantly ipsidirectional. Fibres from these areas cross to the contralateral flocculus and dorsal vermis of the cerebellum (CER) and thence to the vestibular nuclei (VN) and probably also the deep cerebellar nuclei. Fibres from VN again cross the midline to excite the abducens nuclei (ABN) and the extraocular muscles (EOM) on the same side as the DLPN (adapted from Tusa and Zee, 1989). MST and PPC and projects fibres to another group of pontine cells, the nucleus reticularis tegmenti pontis (NRTP). The relationship of these two parallel coticofugal pathways in the generation of pursuit eye movements is not known at present, but lesions in either the frontal pathway (Lynch, 1987; Keating, 1991) or in the M S T - D L P N pathway (May et al., 1988) can cause a decrement in pursuit gain. The next stage in the pathway is the cerebellum (Fig. 12), an area that has long been known to be essential for pursuit (Westheimer and Blair, 1974; Zee et al., 1981). Both the flocculus and the vermis of lobules VI and VII are involved in pursuit and VOR suppression and both receive direct projections from DLPN and NRTP (Langer et al., 1985; Yamada and Noda, 1987). Purkinje cells in both cerebellar areas encode retinal error velocity and eye velocity signals (Lisberger and Fuchs, 1978; Noda, 1986; Suzuki and Keller, 1988a,b). More importantly, both areas carry activity related to VOR suppression. In fact it has been suggested that many of the units carry a signal representing gaze velocity (Lisberger and Fuchs, 1978; Suzuki and Keller, 1988a). During optokinetic stimulation all of the units recorded in the cerebellum exhibit the characteristic rapid onset response of the 'direct' cortical system and they continue to respond at higher velocities ( > 60°/sec) when the vestibular

VISUAL-VESTIBULARINTERACTION

units mentioned above, which are sensitive to optokinetic stimuli, have become saturated (Waespe et al., 1981). The output of the cerebellum is relayed via the vestibular nuclei and ocular motor nuclei to the extraocular muscles.

4. CHANGES IN P E R F O R M A N C E ASSOCIATED W I T H PRIMARY VISUAL FEEDBACK CHARACTERISTICS 4.1. GENERAL OBSERVATIONS

In order to operate as a feedback system for retinal velocity error the oculomotor system must obtain an estimate of error from the motion of images passing across the retina. The source of this retinal error information is likely to be the motion sensitive mechanisms in retinal ganglion cells (Barlow and Hill, 1963; Barlow et al., 1964; Oyster and Barlow, 1967), in the nucleus of the optic tract (Collewijn, 1975; Hoffman and Schoppmann 1975, 1981) and in visual association cortex (Griisser and Griisser-Cornehls, 1973). It is probable that the mechanism by which the oculomotor system obtains its initial estimate of retinal velocity error is through the temporal summation of the output of spatially separated retinal receptors converging upon retinal ganglion cells (Griisser and Griisser-Cornehls, 1973). The distribution of motion sensitive cells is not uniform throughout the retina and, moreover, they do not provide a linear transduction of image velocity. There are three main ways in which this knowledge has been exploited to show just how important visual feedback is to the process of oculomotor control: by changing the location or size of the target; by tachistoscopic presentation of the target; and by stimulation at high velocities of target motion. 4.2. EFFECT OF TARGET LOCATION AND SIZE Evidence suggests that the motion sensitive mechanisms in the retina are less numerous and have larger receptive fields in the peripheral retina (Hoffman, 1972; Hoffman and Schoppmann, 1975; Hoffman et al., 1976; Stone and Fukuda, 1974; Fukuda and Stone, 1974); thus they will respond to a greater range of relative image velocities but with less sensitivity than those in the fovea. Modification of the size and peripheral location of the moving visual stimulus should thus have a profound effect on the visual feedback. 4.2.1. O K N

It has long been realized that optokinetic nystagmus is dependent on the size and peripheral location of the visual stimulus. Early experiments by Hood (1967) and later by Dichgans (1977) showed that the velocity at which saturation started to occur decreased as the optokinetic stimulus occupied less and less of the peripheral visual field (Fig. 13), although modifying the height of the stimulus over a range of 2-100 ° had no effect on the velocity generated. Undoubtedly a large part of this effect is attributable to the presence of the stationary contours at the edge of the display

449

that can act as a fixation reference (Schor and Narayan, 1981; Barnes and Hill, 1984) in conventional closed-loop stimulation conditions. In fact, Barnes and Crombie (1985) were able to show that there was a graded effect of fixation targets as they were moved further into the periphery. Other experiments by Cheng and Outerbridge (1975) have demonstrated that a nystagmus can be evoked from motion in the peripheral retina alone, although there was a considerable decrement in velocity when the stimulus fell off the foveal area, emphasizing the dominance of this area in the response. These effects were later substantiated by the work of Barnes and Crombie (1985) and Pola and Wyatt (1985). Similar results have been obtained through the use of open-loop techniques both in the monkey (Koerner and Schiller, 1972) and in man (Dubois and Collewijn, 1977). The latter study involved a systematic investigation of the effects of varying both the area and peripheral location of the optokinetic stimulus which, in the absence of the stationary edge effects indicated the effects of increasing area to be small, whereas the importance of foveal stimulation was most apparent. 4.2.2. Pursuit One of the important features of most of the experiments outlined above was that the visual stimulus was generally fairly large and therefore its weighting function value in driving the oculomotor system was quite high. As we shall see later this is quite important in allowing the motion stimulus to overcome the effect of fixation features such as the edges of the optokinetic display. However, it is also possible to see changes in the pursuit response that are dependent on the retinal location of the visual stimulus. It has been known since the early experiments of Rashbass (1961) and Robinson (1965) that the velocity drive for the pursuit system can be derived from the parafoveal area, since in the initial part of the response to a constant velocity or step-ramp stimulus the eye may follow the target whilst it remains at an eccentricity of a few degrees to the fovea. Several subsequent experiments have demonstrated that smooth pursuit eye movements can be achieved in the complete absence of a foveal stimulus (Steinman et al., 1969; Michalski et al., 1977; Winterston and Steinman, 1978; Steinbach, 1976). Barnes and Hill (1984) were able to show that when subjects were instructed to pursue the mid-point between two peripherally located targets, the slow-phase eye velocity of the response progressively decreased with increasing eccentricity from 5-20 ° (Figs 7 and 14) in a similar manner to that for optokinetic stimuli. Comparable results have been obtained by other authors (Pola and Wyatt, 1985; Collewijn and Tamminga, 1986). Most recently the technique of examining the initial response to a ramp target motion stimulus has been used to show that initial eye acceleration is affected in the same way, being negligible for a target eccentricity of more than ! 5° (Lisberger and Pavelko, 1989; Carl and Gellman, 1987). 4.2.3. V O R suppression The effects of peripheral stimulation on visual suppression of the VOR have been shown to be very

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similar to those for pursuit (Barnes, 1983). This was demonstrated by instructing the subject to fixate an imaginary point midway between two small, peripherally located head-fixed targets during oscillation on a turntable. As the targets were placed further into the periphery the degree of suppression of the response evoked in darkness became progressively reduced (Fig. 15). However, some suppression remained even when the targets

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FIG. 15. Slow-phase eye velocity gain during sinusoidal oscillation on a turntable with a peak velocity of +60°/sec at frequencies between 0.25 and 2.0 Hz. Subjects were in darkness (D) or viewed small (< 1°) head-fixed targets placed centrally (0°) or in pairs at + 2.5, 5, 10 or 20° in the periphery. Mean of six subjects. (Replotted from Barnes, 1983.) were placed at + 2 0 ° in the periphery. These effects were subsequently confirmed in two further experiments ( Barnes and Edge, 1983; Barnes and Eason, 1988). These results emphasize the importance of visual feedback in achieving the highest level of VOR suppression. Although the task of fixating a point midway between the most eccentric targets was not dissimilar to that of imagining a head-fixed target in darkness and resulted in similar VOR gain reductions, further suppression of the VOR could not be achieved without a more centrally located target.

4.3. EFFECTOF TACHISTOSCOPICTARGET PRESENTATION

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FIG. 14. The effects of peripheral target location on the gain of slow-phase eye velocity in pursuit. In active pursuit the subjects tracked the single target or an imaginary point midway between the paired peripheral targets. During passive stimulation the subject attempted to hold fixation around the central position. Data points on the right-hand side were obtained during pseudo-random target motion. (Plotted from data in Barnes and Hill, 1984.) Mean of four subjects.

Another way of modifying the visual feedback available to the ocuiomotor system is to intermittently illuminate the visual motion stimulus. There are two variables which may be manipulated in this paradigm: pulse duration and pulse interval. In the majority of experiments in which pursuit and VOR suppression have been examined pulse duration has been kept very short ( < l0 msec), so that the subject was unable to perceive any target motion during the very brief period of presentation. In such circumstances the velocity information must be derived from successive displacements of the image across the retina. As indicated above, if the visual velocity information is derived from the temporal integration of responses from spatially separated cells within the retina the output will be degraded by increasing pulse interval. If the target light source were pulsed in such a way that, in its passage across the retina, the periods of illumination coincided with only a proportion of the total number of receptors, the firing rate of the cell would be reduced in proportion to the interval between pulses. In fact, direction sensitive motion detectors within the visual association cortex of the cat have been shown to exhibit such a behaviour pattern during stroboscopic illumination of moving visual stimuli (Griisser and Grfsser-Cornehls, 1973).

VISUAL-VESTIBULARINTERACTION

451

4.3.1. Pursuit and OKN

4.3.2. VO R suppression

Experiments on pursuit of intermittently illuminated targets fall into two categories, those in which the target itself moves and those in which a succession of stationary targets is illuminated. The latter stimulus gives rise to an apparent motion effect and once smooth eye movements have been initiated they can be sustained by the relative displacement of retinal images in successive presentations (Heywood and Churcher, 1973) that reinforces the perception of motion. The eye movement induced by this type of stimulus has been referred to as Sigma-pursuit or Sigma-OKN and has been extensively investigated by Gr/isser and colleagues (Griisser et al., 1979; Adler and Griisser, 1979; Behrens and Griisser, 1979). These experiments have shown that when a stationary pattern of stripes or an array of dots is presented stroboscopically there is a linear relationship between slow-phase eye velocity and the product of strobe rate and the spatial period of the pattern. In theory, there should be little or no difference in performance for stationary or moving targets if the duration of exposure is very brief since there is no instantaneous registration of velocity error. Undoubtedly, one of the most important aspects of the oculomotor response which allows intermittently illuminated targets to be pursued with some smooth eye movement is the persistence of eye movement in darkness. This was demonstrated by Morgan and Turnbull (1978), who systematically increased pulse interval (PI) up to 300 msec and observed that saccadic corrective movements became progressively more prominent between the smooth eye movements. Subsequently Barnes and Asselman (1992) have reexamined this type of response, but have extended pulse interval up to 960 msec, using both a sinusoidal (0.2 Hz) and mixed-sinusoid (0.11 Hz + 0.19 Hz) target motion stimulus. Extraction of the smooth component eye velocity indicated that the gain showed a progressive decline with increasing pulse interval up to 960 msec (Fig. 16A), although even at this longest interval there was still some smooth eye movement present, average gain for the sinusoidal response being 0.32. Barnes and Asselman (1992) also demonstrated that if pulse interval was held constant at 640 msec there was a progressive increase in eye velocity gain as pulse duration was increased from 10 to 640 msec (Fig. 16B). Detailed examination of the smooth eye movement evoked by tachistoscopic stimulation revealed a pulsatile eye velocity trajectory in response to each target presentation that was predictive of the onset of target illumination. Tachistosopic target presentation has also been used to demonstrate the interaction between conflicting motion stimuli in oculomotor control. Barnes and Hill (1984) showed that when subjects were presented with a moving background stimulus and a tachistoscopically illuminated fixation target the ability to suppress the oculomotor drive from the background was progressively degraded as the inter-pulse interval was increased from 0.04 to 3 sec. More recently, Worfolk and Barnes (1992) have shown that the same interactive effects can be demonstrated during pursuit of a tachistoscopically illuminated moving target against a moving structured background.

When the human subject is oscillated on a turntable and views a head-fixed target that is intermittently illuminated the degree of VOR suppression is also dependent on the inter-pulse interval. In an experiment by Barnes and Edge(1983) subjects were oscillated at 0.5 Hz with a peak velocity of ___60°/sec, yielding an average gain for the VOR in the dark of 0.65. For a centrally located target the gain of slow-phase eye velocity was reduced to 0.12 when inter-pulse interval was 10 or 30 msec (i.e. efficiency of 0.82 from equation 6) but gradually increased to a value of 0.67 when pulse interval was 3000 msec (Fig. 17A). VOR suppression has also been examined with tachistoscopic target illumination during voluntary oscillation of the head (Barnes, 1988). In this experiment the degree of suppression was also dependent on pulse interval (PI). As for passive stimulation, the maximum efficiency of VOR suppression was attained for a PI of 2-30 msec when eye velocity gain was reduced from 0.75 to 0.15 (efficiency 0.80) at 0.5 Hz (Fig. 17B). However, when PI was 1000 msec there was no reduction of the VOR response recorded in darkness at 0.5 or 1.0 Hz, even though this was a condition that was very similar to the instruction to imagine a head-fixed target in darkness. These results emphasize that, even during a planned repetitive voluntary head movement, the ability to suppress the VOR is still heavily dependent on the quality of the visual input. In fact, as indicated later, it is possibly more difficult to suppress the VOR during active head movement, contrary to Robinson's (1982) hypothesis. 4.3.3. Head-free pursuit More recently Waterston and Barnes (1992) have examined the performance during head-free pursuit of a tachistoscopically illuminated target and have made a direct comparison with head-fixed pursuit in the same group of five subjects. The stimulus was composed of two sinusoids of frequency 0.11 and 0.19 Hz with a peak velocity of 8°/sec for each component. Gain in the head-free condition fell from 0.98 for continuous target illumination to 0.62 when the target was presented for 20 msec at intervals of 640 msec. As in many of the comparisons of head-fixed and head-free pursuit that will be discussed later, slow-phase gaze velocity gain was, on average, marginally better when the head was free, but the effect did not reach statistical significance (Fig. 18). This small difference between the two conditions would be expected if the gain of the VOR were slightly less than unity (Eqn (1)) and if the same mechanisms are responsible for pursuit and VOR suppression. 4.4. EFFECT OF STIMULUSVELOCITY In order to transduce retinal velocity most effectively it might be expected that the velocity sensitive cells within the visuomotor pathways should give a response in which firing rate is always proportional to retinal velocity error. In other words, to obtain a constant feedback gain the ratio of firing rate to retinal velocity error should be constant irrespective

452

G.R. BARNES

of velocity error. In fact, this is far from true as initially pointed out by Oyster (1968). Velocity sensitive ganglion cells in the rabbit retina exhibit a pattern of activity in which the ratio of firing rate to retinal error velocity gradually diminishes with increasing velocity (Oyster et al., 1972). Subsequent experiments have shown that this general pattern of behaviour can also be observed in the accessory optic system (Simpson et al., 1979), in visual cortex (Orban et al., 1981), in visual associ-

ation cortex (Griisser and Griisser-Cornehls, 1973) and in pontine nuclei (Baker et al., 1976; Suzuki and Keller, 1984), areas known to lie on the pursuit pathways. As shown by Orban et aL (1981) the velocity 'tuning' of the visual cortical cells is dependent on the eccentricity of the stimulus in the retinotopic map. Given that these non-linear characteristics are so fundamental to the transduction of retinal velocty error it is not surprising that their features pervade all aspects of oculomotor control.

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FIG. 16. The gain and phase of slow-phase eye velocity during pursuit of an intermittently illuminated target. Broken lines represent responses to a single sinusoid of frequency 0.2 Hz; solid lines represent responses for each of the two frequency components (0.11 and 0,19 Hz) of a mixed-frequency target motion stimulus. In (A) the target was illuminated for durations (PD) of 10~=~) msec at an inter-pulse interval (PI) of 640 msec, the largest value of PD representing continuous illumination. Mean of 8 Ss + 1 S.E.M. In (B) the target was illuminated for a duration of I0 msec at inter-pulse intervals (PI) of 0-960 msec, the lowest value of PI representing continuous illumination. Mean of 8 Ss + 1 S.E.M. (From Barnes and Asselman, 1992.)

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FIG 17. Slow-phase eye velocity gain during attempted suppression of the VOR by viewing of a head-fixed, tachistoscopically illuminated target. In (A) the subjects were sinusoidaily oscillated on a turntable with a peak velocity of + 60°/sec and frequency of 0.5 Hz. Subjects were in darkness (D) or viewed small ( < 1°) head-fixed targets placed centrally (0°) or in a pair at + 10° in the periphery. The targets were tachistoscopically illuminated for 100/~sec at intervals between I0 and 3000 msec. Mean of six subjects + 1 S.E.M. In (B) the subjects executed voluntary oscillation of the head at frequencies of 0.5 or 1 Hz and mean peak velocities of 29 and 42°/sec respectively. Mean of 8 subjects _ I S.E.M. (Data from Barnes and Edge, 1983; Barnes, 1988.) 4.4.1.

OKN

If the moving visual field totally surrounds the subject, the ratio of slow-phase eye velocity to target velocity (eye velocity gain) remains close to unity for stimulus velocities up to 60°/sec, but the gain falls off progressively at higher velocities (Fig. 13). If the width of a horizontally moving optokinetic display is reduced, the gain of eye velocity may still be close to unity for low stimulus velocities but the velocity at which the saturation effect occurs becomes progressively diminished (Fig. 13) (Dichgans, 1977). This saturation effect is almost certainly rooted in the

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non-linear characteristics of the motion-sensitive visual feedback mechanisms outlined above. This was initially demonstrated in experiments using the technique of opening the feedback loop (Koerner and Schiller, 1972). Results from such an experiment on h u m a n subjects (Dubois and Collewijn, 1979) are shown in Fig. 19A, for which the optokinetic field subtended 10° at the eye. the effect can also be demonstrated by calculating the visual feedback gain (Kv) from conventional closed-loop experiments and plotting it against retinal velocity error. K v is given by the function G o K N / ( I - GOKr~), where GoKN is the closed-loop gain of the response and retinal velocity

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FIe. 18. The gain and phase of slow-phase gaze velocity during head-fixed (solid lines) and head-free pursuit (broken lines) of a target moving in the horizontal plane with a mixed-frequency stimulus composed of two sinusoids (0. l I and 0.19 Hz) the target was tachistoscopically illuminated for 20 msec at intervals of 20--640 msec. Mean of 5 subjects + 1 S.E.M. (From Waterston and Barnes, 1992.)

454

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FIG. 19. A comparison of the visual feedback gain obtained from three types of experiment: (A) Optokinetic stimulation----(i) Dubois and Collewijn, 1979, open-loop, display width I0°; (ii)-(iv) Dichgans, 1977, closed-loop, display width 15, 30 and 90° (v). Unit recordings from a directionally selective neuron in visual association cortex---Griisser and Grfisser-Cornehls, 1973--firing rate/retinal error velocity in arbitrary units. (B) VOR suppression---O) Gilson et al., 1970, central target subtending > 3°; (ii) Barnes and Edge, 1983 using single central target (0°) or (iii) pair of peripheral targets at _+20°. Pursuit--(iv) Sehalen, 1980, steady-state ramp response; (v) Carl and Gellman, 1987, transient ramp response.

error g = ~ - 0. The results from one such experiment (Dichgans, 1977--see Fig. 13) are also shown in Fig. 19A for field sizes of 30-90 °. For each set of results Kv exhibits a relationship with retinal velocity error (g) which may be approximated by the function: K v = C.~-=

but active pursuit raised the open-loop gain (Kv) by a factor of 4-5. The temporo-spatial characteristics of the visual velocity feedback that give rise to this velocity non-linearity have been more thoroughly investigated by Miles et al. (1986) by examination of the first 200 msec of the eye movement induced by the rapid transient motion of a large field stimulus. Both the latency and velocity of eye movement were found to be related to the temporal frequency with which the edges of the display passed across the visual field. Induced eye velocity exhibited a temporal frequency tuning curve similar to that found previously in the various parts of the pathways described earlier.

(8)

where C and ~t are constants. Although both sets of data exhibit similar slopes (i.e. values of ct) the larger field stimulus induces a generally increased level of gain, that is represented by a higher value of C. The values of gain obtained are quite low when compared with those for the pursuit response (described in Section 4.4.2, Fig. 19B) but this may reflect the difference between the active and passive response. Barnes and Crombie (1985) were able to show that the same non-linear decline in visual feedback could be observed in both active and passive stimulation,

Similar velocity saturation characteristics are also observed in the pursuit reflex response. Although it had long been appreciated that there was a limitation in the velocity at which human subjects could track a moving target (Robinson, 1965), the first quantitative assessment of the effect appears to be that of Schalen (1980), who examined responses to constant velocity stimuli up to a velocity of 80°/sec. Calculated values of visual feedback gain derived from these experimental results (Fig. 19B) also exhibit a pattern in which there is a steady decline in gain with increasing velocity error above 1°/sec, similar to that for the O K N responses. However, overall gain was higher than for any OKN stimulus subtending less than 30 ° in width (Fig. 19A), presumably because pursuit represents an active response as discussed above. The calculated values of gain obtained below retinal slip velocities of l°/sec may well be unreliable. During pursuit of a periodic target motion stimulus the velocity saturation effects become most evident at frequencies above 0.5 Hz (Lisberger et al., 1981; Sharpe et al., 1979; Barnes and Ruddock, 1989) as demonstrated by the results shown in Fig. 6. The major reason for this is that it is easier to generate high velocity stimuli that stay within the displacement bounds of normal eye movement at frequencies above 0.5 Hz. It is possible to demonstrate a small reduction in average gain at 0.4 Hz when velocity is increased beyond 60°/sac (Fig. 21), but the variability does not normally allow a significant difference to be found (Waterston and Barnes, 1992). Lisberger et al. (1981) presented arguments to suggest that the decrease in gain with increasing velocity actually represents a saturation of acceleration rather than velocity but it is likely that the underlying mechanism is in fact the same as for the OKN response. As frequency increases above 0.5 Hz pursuit performance progressively breaks down because of the dynamic limitations of the visuomotor pathways as described earlier (Eqn (7)), and, as a first approximation, eye acceleration becomes proportional to target velocity in this frequency range (see also Section 5.3.1). 4.4.3. V O R suppression The effect of velocity saturation in visual suppression of the VOR can readily be demonstrated during rotation on a turntable because it is possible to generate high velocity stimuli at very low frequencies. The effect was originally observed by Gilson et al.

455

VISUAL-Vi~TIBULAR INTERACTION

(1970) and subsequently examined in more detail by Barnes and Edge (1983) using a sinusoidal oscillation frequency of 0.05 Hz and peak velocity of 120°/see (Fig. 20). At such low stimulus frequencies the high frequency dynamic charcteristics of the visuomotor pathways can almost certainly be ignored. Then, the effectiveness of VOR suppression may be assessed by comparison of the slow-phase eye velocity during suppression (0neT) with that of the unmodified VOR recorded in darkness (0DRK). The theoretical amplitude ratio (see Barnes, 1983) may be expressed as: 0HFT/0DR K ~-~ 1/(1

+ Kv).

(9)

By measuring values of the amplitude ratio corresponding to different turntable velocities Barnes and Edge(1983) were able to estimate visual feedback gain as a function of retinal velocity error (identical to eye velocity in this context). As indicated in Fig. 19B, Kv was fairly constant for retinal velocities up to 2°/sec but thereafter declined progressively in a similar manner to the pursuit responses. Results derived from the experiment of Gilson et al. (1970) exhibited a similar trend but with slightly lower gain. Barnes and Edge (1983) also examined the suppression induced by two small targets placed at + 20 ° in the periphery. Feedback gain in this condition was much lower than for a central target (Fig. 19B). It remained fairly constant for retinal velocites up to 9°/sec but then progressively declined in a similar manner to the other suppression tasks. Barnes et al. (1988) found

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that these non-linear visual feedback characteristics even remained under the influence of alcohol, although overall feedback gain was considerably reduced. 4.4.4. Head-free pursuit This is one condition in which the normal human subject will frequently execute high velocity head movements in response to rapidly moving targets and it is the condition in which Robinson (1982) suggested that non-visual VOR suppression would be most useful. However, the effects of velocity saturation can still be demonstrated in this condition 0Haterston and Barnes, 1992) at high target velocities as shown in Fig. 21. In this experiment the stimulus was composed of two frequencies, 0.4 Hz and 1.3 Hz. As the velocity of the higher frequency was increased from 15 to 120°/see, there was a progressive decrease in gaze velocity gain which was similar to that recorded during bead-fixed pursuit (Barnes and Ruddock, 1989). The gain of the lower frequency component was also affected by its velocity, but more markedly by the velocity ratio between the frequency components, for reasons that are described later (Section 5.2.1). In more recent experiments (Barnes and Grealy, unpublished observations) a direct comparison has been made between head-fixed and headfree pursuit using high-velocity (up to 300°/see) sinusoids at frequencies of 0.2-1.6 Hz. In general, gaze velocity gain was slightly higher during head-

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Flo. 20. Examples of velocity saturation during visual suppression of the VOR. Subjects were oscillated at 0.05 Hz with a peak velocity of 60 or 120°/see whilst viewing a head-fixed target. The plot in (a) shows the mean single cycle response of slow-phase eye velocity and head velocity obtained from four cycles of stimulation in six subjects. In the remaining plots average eye velocity is plotted against head velocity in three conditions: (b) during VOR suppression at 60°/see; (c) during VOR suppression at 120°/see and (d) during rotation in darkness. (From Barnes and Edge, 1983.)

456

G R. BARNES 0.4 Saze val. gain t.6

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FIG. 21. The gain of slow-phase gaze velocity during head-free pursuit of a target composed of two sinusoids. Gains for the lower frequency component (0.4 Hz) are shown on the left, those for the higher frequency (1.3 Hz), on the right. The peak velocity (VI) of the lower frequency component was varied from 30 to 90°/sec. The peak velocityof the higher frequencycomponent was varied as a ratio of V1 from 0 to 2. The gain of both components exhibits a progressive decrease with increasing velocity. (From Waterston and Barnes, 1992.) free pursuit, but the effect was small and appeared to be confined to a very limited frequency range (0.8-1.2 Hz). 4.5. THE ROLE OF VISUALFEEDBACK:CONCLUSIONS It is evident that the nature of the visual input can significantly modify the response to pursuit, OKN and VOR suppression. The effects of peripheral target location and size appear to exhibit qualitatively similar changes in pursuit, OKN and VOR suppression, but it is not easy to make direct quantitative comparisons because of the difficulty of precisely matching stimulus conditions. Tachistoscopic target presentation allows an easier comparison to be made and it is evident that the breakdown in effects for pursuit, VOR suppression and OKN suppression (i.e. conflicting motion stimuli) does occur over a similar range of inter-pulse intervals of 100-1000 msec. The progressive breakdown in eye movement control with increasing pulse interval serves to emphasize that continuous visual feedback is necessary to achieve the highest levels of slow-phase control. The results of experiments in which there are high levels of retinal slip velocity indicate that the velocity saturation effects of the visual feedback are also present in all the forms of smooth eye movement control examined here. One of the basic arguments used by Robinson (1982) to support the idea of a central mechanism for the suppression of the VOR was that such a system should operate particularly at high velocities of target movement in order to overcome the velocity saturation effects of visual velocity transduction. However, there is not a great deal of evidence to support this concept in human subjects, since the effects of velocity saturation are always present, even at very high velocities of head move-

ment. Velocity saturation is not always readily visible in the pursuit response, except during the initial stages (i.e. in the first 200 msec) of the response before the visual feedback becomes effective. The non-linearity within the system becomes progressively less important as the response becomes more fully developed because retinal error is reduced in the steady state. So, although, in the response to a high velocity ramp stimulus, retinal velocity error may be high initially with a consequently low feedback gain, in the steady state, velocity error will be much less and feedback gain much higher.

5. CHANGES IN PERFORMANCE ASSOCIATED WITH THE PREDICTABILITY OF THE STIMULUS 5.1. GENERALOBSERVATIONS It has long been realized that there must be some form of predictive behaviour in the pursuit reflex, since the nature of the response evoked is heavily dependent on the type of target motion stimulus used, If the target moves with a constant unidirectional velocity (Westheimer, 1 9 5 4 ; Rashbass, 1961; Robinson, 1965; Schalen, 1980), or with a regular periodic waveform (Fender and Nye, 1961; Dallos and Jones, 1963; Winterson and Steinman, 1978; Wyatt and Pola, 1983; Barnes and Hill, 1984), eye displacement matches target displacement very closely, although breakdown is observed if the frequency of target oscillation exceeds 1 Hz. In contrast, when the target moves in a more unpredictable manner pursuit reflex performance becomes considerably impaired. Comparison of the response to sinusoidal and random stimuli was made by Stark et al.

457

V I S U A L - V E S T I B U L A R INTERACTION

(1962) and by Dallos and Jones (1963), who showed that the ratio of eye displacement to target displacement (i.e. eye displacement gain) was considerably less than unity for a Gaussian noise stimulus at all frequencies above 0.3 Hz. They also observed that the associated phase relationships exhibited considerably greater phase lag than for the sinusoidal responses at frequencies above 0.2 Hz. This latter finding in particular serves to emphasize the importance of prediction in the pursuit response, since the relatively small phase lags obtained with sinusoidal stimulation combined with the high levels of gain up to 1.0 Hz are incompatible with the stable operation of a conventional closed-loop feedback system that was known to contain a finite time delay in visuomotor processing of approximately 125 msec (Robinson, 1965). In these early experiments the slow- and fast-phase components of eye movement were not separated, so that it was not clear which component of the response was most instrumental in prediction. However, it was appreciated from the work of Rashbass (1961) that retinal velocity error formed the most important component of the visual feedback for pursuit. The difficulty in explaining the role of prediction in pursuit is that there is no obvious way in which the subject can initiate smooth eye movements prior to target motion since it is normally impossible for most individuals to make smooth eye movements of more than a few degrees/sec in the absence of a moving visual stimulus (Heywood, 1972; Kowler and Steinman, 1979; Barnes et al., 1987). This is, of course, in distinct contrast to the control of saccadic movements, which can be made at will in complete darkness. In this section the performance of the pursuit and VOR suppression mechanisms will be described for three types of experimental paradigm; pursuit of pseudo-random waveforms, activity during single, non-predictable transient stimuli and responses to repeated, predictable transient stimuli. 5.2.

EFFECT OF PSEUDO-RANDOM

STIMULI

5.2.1. Pursuit and O K N It has been known since the work of Stark et al. (1962) that an effective pseudo-random stimulus can be generated by mixing together a number of harmonically unrelated sinusoidal waveforms. Bahiil et al. (1980) were probably the first to examine both the smooth component eye velocity and the overall (or cumulative) eye displacement gain using this type of stimulus. They showed that although eye displacement gain remained close to unity for frequencies up to 1 Hz, slow-phase eye velocity was slightly less than unity at frequencies up to 0.3 Hz and then exhibited a progressive decline with increasing frequency (Fig. 22). A similar result was obtained by Lisberger et al. (1981) using a somewhat different stimulus referred to as a 'random walk of sinusoids'. In contrast, Collewijn and Tamminga (1984) found eye velocity gain to be relatively constant across the frequency range when the stimulus was composed of only four sinusoids with frequencies between 0.15 and 0.58 Hz. Earlier, it had been found that the overall eye displacement response to random stimuli could be highly modified by the bandwidth and centre fre-

quency of the stimulus (Michael and Jones, 1966; St-Cyr and Fender, 1969). Such variability in the frequency characteristics of the response made it difficult to define a standard non-predictable stimulus with which to examine the pursuit reflex. In an attempt to discover the underlying factors controlling the decline in performance with pseudorandom stimuli Barnes et al. (1987) examined a wide range of frequency and velocity combinations. The results indicated that the critical factor in determining how well the target motion could be followed was not the randomness of the stimulus but the frequency of the highest frequency component. If all frequencies making up the stimulus were less than approximately 0.4 Hz eye movements were very smooth, with very few catch-up saccades (Fig. 23). Thus, high levels ( > 0.9) of eye velocity gain, comparable to those evoked by sinusoidal stimuli were evoked (Fig. 24), even though the stimulus was quite highly randomized. In contrast, when the highest frequency of the combination was increased from 0.4 to 1.6 Hz there was a progressive breakdown in the pursuit response (Fig. 23) which was manifest as a reduction in eye velocity gain of the lower frequency components. However, the highest frequency component itself had a gain which was comparable to that evoked by a sinusoid of the same frequency (Fig. 24). Most importantly, this breakdown in pursuit could be observed even if only two sinusoidal components were mixed together, provided that the higher frequency was above approximately 0.8 Hz, indicating that the effect was not dependent on the complexity of the stimulus as thought previously. In a further set of experiments (Barnes and Ruddock, 1989) it was shown that the same breakdown in gain of the low frequency components of the response to a mixture of either two or four sinusoids could be observed if the velocity ratio between the highest frequency component and the lower frequencies was increased from 0 to 4 provided again that the highest frequency was above 0.4 Hz. Absolute velocity was found to have no significant effect provided that it fell below the range at which velocity satu1.20 "~

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ration started to occur (see above). This technique of changing the velocity ratio of the components has provided a very powerful means of controlling pursuit performance in a simple manner that easily allows the responses to different experimental con-

ditions to be compared. One of the most unexpected findings was that these changes in gain could even be observed during passive stimulation when the subject stared at a fairly large (16 ° w × 12° h) optokinetictype display. This occurred even during open-loop

VISUAL-VESTIBULARINTERACTION

stimulation, suggesting that these characteristics are a feature of the visual feedback itself. Other experiments (Wyatt and Pola, 1988; Yasui and Young, 1984) have also indicated that the optokinetic response appears to exhibit properties normally associated with prediction, emphasizing that it is not something specific to volitional control. 5.2.2. FOR suppression The effects of using pseudo-random motion stimuli are also evident in visual suppression of the VOR. This was first demonstrated by McKinley and Peterson (1985) using a combination of sinusoids between 0.I and 1.9 Hz. Subsequently Barnes and Eason (1988) used the technique of modifying the highest frequency component of the stimulus to examine both visual and non-visual mechanisms of VOR modification. The results showed very clearly that when all frequencies of the stimulus were below 0.4 Hz, optimum suppression levels, indistinguishable from those evoked by single sinusoids, could be obtained (Fig. 25). But, as for pursuit, when the highest frequency of turntable motion was increased to 2.08 Hz there was a progressive decrease in efficiency of VOR suppression for the lower frequency components. Of particular interest was the fact that when the efficiency of VOR suppression was derived from these results (see Eqn (6)) and compared with results obtained from head-fixed pursuit in a different group of subjects there was a remarkable similarity in the ordinal changes in both gain and phase. However, the efficiency of VOR suppression was marginally better than pursuit, a feature that could have been attributable to other, non-visual, mechanisms of VOR gain control, although no direct comparison was made in the same group of subjects.

459

5.2.3. Non-visual FOR suppression Unlike the responses observed with a real headfixed target, the suppression of the VOR by imagined head-fixed targets appears to be little affected by the predictability of the stimulus (Barnes and Eason, 1988), although McKinley and Peterson (1985) found suppression to be better during pseudo-random stimulation. Nevertheless the level of suppression is frequency dependent, with the degree of suppression progressively diminishing at frequencies above 1.0 Hz. In other words, the modifying element during voluntary non-visual changes exhibits the characteristics of a low-pass filter, as originally demonstrated by Barr et al. (1976). One way in which non-visual suppression might be achieved is by the negative feedback of the efference copy of eye velocity to inhibit the vestibular drive, as shown in the model of Fig. 11. If an internal representation of the oculomotor plant dynamics were included in this feedback loop it would exhibit the required features of a low-pass filter, the degree of suppression at low frequencies being equal to 1/(1 + KE), where K E is the gain of efference copy feedback (Barnes and Eason, 1988). This feedback mechanism might be regarded as a generalized gaze holding system. 5.2.4. Head-free pursuit The earliest studies of head-free pursuit using pseudo-random stimuli (Gresty and Leech, 1977) indicated that performance, as assessed by the level of saccadic activity in the response, was impaired when tracking a pseudo-random stimulus. Subsequently, two studies have been performed using the technique of modifying the highest frequency component of the stimulus to compare performance with head-fixed

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FIG. 25. Eye velocity gain during pseudo-random whole-body rotation on a turntable, in which the stimulus was composed of four sinusoids with a peak velocity of + 17.5°/see. The three lowest frequencies remained constant (0.1 i, 0.24 and 0.37 Hz), whilst the highest frequency was varied in each stimulus, taking values of 0.39 Hz (O), 0.78 Hz (A), 1.56 Hz (FI) or 2.08 Hz (O) the broken line indicates gain and phase for responses to discrete frequency sinusoidal stimuli. Responses were examined in four conditions: DRK, darkness; HFT, fixation of a hcad-fixed target; IHFT, attempted fixation of an imagined head-fixed target; THFT, attempted fixation midway between two tachistoscopically illuminated peripheral targets located at + 20°. Mean of 8Ss. (From Barnes and Eason, 1988.) pursuit. The first of these (Barnes and Lawson, 1989) showed that slow-phase gaze velocity gain for frequency components below 0.4 Hz was progressively impaired when the highest frequency was increased from 0.4 to 2.08 Hz and when the velocity of the highest frequency was increased, in the same manner as for head-fixed pursuit (Barnes et al., 1987; Barnes and Ruddock, 1989). In a later study (Waterston and Barnes, 1992) a direct comparison in a single group of subjects revealed no significant difference between gaze velocity gains in head-fixed and head-free pursuit for the same target motion conditions, although, on average, gains were slightly higher with the head free (Fig. 26). In the head-free conditions head displacement made up between 70 and 8 0 0 of total gaze displacement and showed some of the changes in gain and phase associated with gaze control, suggesting that it, too, was driven by the non-linear visual feedback. The importance of these findings is that they do not concur with the hypothesis that there is a major contribution of non-visual mechanisms to the suppression of the VOR during head-free pursuit. The head displacement signal contained all the frequency components of the target motion and an efference copy of the head drive could, in theory, be used to suppress the VOR in those conditions in which visual feedback was degraded by the more non-predictable stimuli, thus giving a higher gain than during headfixed pursuit. In fact, Barnes and Lawson (1989) showed that when the VOR signal was partially eliminated by rotating the subject on a turntable, to counter the head movement, gaze velocity gain did

increase, showing that, in normal circumstances, the system does rely heavily on visual feedback to suppress the VOR. Waterston and Barnes specifically compared the correlation between predicted gaze velocity gain for two methods of assessing VOR gain in darkness. This revealed that the small difference was best accounted for by the average gains recorded when imagining an earth-fixed target (mean gain increasing from 0.87 at 0.11 Hz to 1.05 at 0.78 Hz) rather than when carrying out the apparently more relevant task of attempting to track the imagined target in darkness (mean gain increasing from 0.57 at 0.11 Hz to 0.72 at 0.78 Hz). A similar result was also obtained by Leigh et al. (1987). 5.3. TRANSIENT CHANGES IN STIMULUSMOTION

5.3.1. Pursuit A technique that has been widely used to examine the response of the pursuit and optokinetic systems in the absence of prediction is that of the constant velocity or ramp target motion stimulus. Early experiments by Rashbass (1961) and Robinson (1965) had established that there is a reaction time before the initiation of any smooth eye movement and subsequent experiments have shown this to be at least 100 msec in man (Carl and Geilman, 1987). If the magnitude and/or direction of successive target motion stimuli is suitably randomized each stimulus may be regarded as non-predictable and the response during the period equivalent to the reaction time (i.e. 100 msec after response initiation in man) may be

VISUAL-VESTIBULAR INTERACTION

461

taken to represent the open-loop response, since visual feedback will not have had time to become effective, so that retinal velocity error ~ is equal to target velocity ~. The initial transient response to a ramp target motion visual stimulus will be determined by the visual feedback characteristics F'(s) in Eqn (7), yielding:

they can be seen to exhibit the same trend of decreasing gain for error velocities above 2°/sec that is exhibited in response to other types of stimuli, with a remarkable similarity in gain to that obtained during pursuit and VOR suppression.

0 = Kv" (1 - e-'/7)-~.

Two recent experiments have provided convincing evidence that VOR suppression may take place through an alternative mechanism to that of direct visual suppression. Lisberger (1990) has shown that when there is a sudden change in velocity of the head during attempted VOR suppression the corrective action which nulls the transient response to the velocity change can occur with a latency as short as 36 msec, which is less than would be expected for pursuit mechanisms. This effect was found to be dependent on prior visual suppression having taken place so it is conceivable that it might represent the early release of information which has been stored for the predictive velocity estimation process as described later. It is notable that the earliest part of the VOR response is not modified in this condition, so that there is no evidence for a parametric modification of the VOR having taken place prior to the change in

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Thus, initially, eye acceleration is proportional to target velocity and will remain approximately so for the first 100 msec after the start of the response. This conforms to experimental observations in humans (Fig. 27). However, Carl and Gellman found that the initial acceleration of the eye exhibited saturation for target velocities greater than 10°/see, a feature that is also evident in the responses shown in Fig. 27. This is not surprising, since the acceleration will be determined by the non-linear relationship between Kv and (Fig. 19). When the values of acceleration obtained by Carl and Gellman (their Fig. 3B) are plotted as the ratio of eye acceleration to target velocity (Fig. 19B) Head d t e p l , gain

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FIG. 27. Examples of the transient response of the ocular pursuit system to the unpredictable onset of a constant velocity ramp stimulus at four velocity levels (12.5-50°/sec) the target was exposed for 640 msec as indicated by the square pulses. Broken lines indicate the theoretical openloop response of the model (Eqn (8)) in which feedback gain (Kv) took values of 11.0, 7.8, 6.4 and 5.8 for target velocities of 12.5, 25, 37.5 and 50°/sec respectively and the time constant (T) was 1 sec. head velocity. This finding is also supported by the experiments of Gauthier and Vercher (1990) who showed that the early response to a transient head rotation was similar whether the subject viewed a head-fixed or earth-fixed target or was in darkness. Another attempt was made recently by Cullen et al. (1991) to monitor suppression of the VOR induced by whole-body rotation on a turntable following sudden changes in the head or target motion. They showed clear differences in the VOR gain in the early part of the transient response as a function of the velocity of head motion. These differences were present when there was a sudden change in head acceleration but not when there was a sudden change in target acceleration. Visual feedback mechanisms, including prediction, would be expected to operate equally in both of these conditions, but the observation of a reduced VOR response following a change in head acceleration alone clearly indicates that a modification of the VOR had taken place during the prior fixation period.

5.3.3. H e a d - f r e e pursuit The role of the vestibular response during headfree pursuit was assessed in the experiments of Lanman et al. (1978) by examining responses to constant velocity tracking before and after labyrinthectomy. At an unexpected time during the combined head and eye movement the head was suddenly braked, but, before labyrinthectomy, this made little difference to the overall gaze trajectory, which continued to follow the target. Because there was no change in the visual stimulus the visual feedback was not modified by the change in head velocity. This finding is therefore

completely compatible with the hypothesis that the same neurological mechanism is responsible for both VOR suppression and pursuit, since the component of the visual feedback required to suppress the VOR would automatically be transferred directly to make up the extra velocity drive component to the eye which was formerly accomplished by head movement. The delay in this change-over would be equivalent to the latency of the VOR response, that is approximately 10-15 msec, as reported by Lanman et al. After labyrinthectomy, the same head braking paradigm resulted in a large gaze error which was not corrected for some 80 msec because it was presumably now necessary to generate the extra pursuit drive which was no longer being used to suppress the VOR. This experiment was similar to that of Cullen et al. (1991) on the turntable and it remains to be seen whether active head movements of a higher velocity than those used by Lanman et al. would reveal a similar non-visual suppression of the VOR. 5.4. PREDICTIVERESPONSESEVOKEDBY REPEATED TRANSIENTSTIMULATION 5.4.1. Pursuit

The true nature of the predictive response can be revealed by repeatedly presenting a transient stimulus of the type discussed above without randomisation. This technique was used by Becker and Fuchs (1985) and subsequently by Boman and Hotson (1988) to show that smooth eye movements could be evoked in anticipation of a ramp target motion even when that stimulus did not appear, provided that the subjects had previously made a response to such a stimulus. A similar form of predictive smooth eye movement of rather low velocity can also be observed in response to a square wave target displacement (Kowler and Steinman, 1979; Barnes et al., 1987). Barnes et al. (1987) showed that much higher velocities (20-30°/sec) of smooth eye movement could be evoked by allowing the subject to glimpse the target for a brief period (20-80 msec) at its extreme displacements, even though the instantaneous target velocity during the exposure period was much less than the induced eye velocity. Asselman and Barnes (1989) have subsequently developed this technique further in order to allow the isolated effects of prediction to be examined in more detail. In the simplest form of this stimulus the target moved in the horizontal plane with a regular periodic (triangular wave) motion but was only illuminated for a very brief period (40-320 msec) as it passed through the central field of view (Fig. 28). Subjects attempted to follow the motion of the target as well as possible when it appeared. The smooth component of eye velocity evoked was found to gradually increase over the first 3-4 presentations whilst simultaneously becoming more phase advanced with respect to the onset of target presentation (Fig. 29), even though there was no continuous visual feedback. After a few cycles of this repeated transient stimulation, the target unexpectedly changed direction, velocity or frequency or failed to appear altogether. In this transitional period a predictive eye movement was made with a peak velocity and timing that were

VISUAL-VESTIBULARINTERACTION

463

of repeated stimulation, when the target did not appear as expected, the subject continued to make a head movement with a timing and velocity appropriate to the preceding cycles of stimulation. Associated with this predictive head movement, gaze velocity also exhibited a similar trajectory, indicating that the VOR had been largely suppressed in a predictive manner in the absence of a visual target (Fig. 31). This predictive VOR suppression could also be observed during whole-body rotation on the turntable when the subject attempted to fixate a head-fixed target that was presented for 10-160 msec as the turntable passed through peak velocity of a sinusoidal waveform. In the steady-state there was a transient suppression of the VOR which was initiated prior to target illumination and had a temporal characteristic similar to that observed during headfixed and head-free pursuit.

highly correlated with those of the preceding stimulus and which were completely inappropriate for the concurrent visual stimulus. Such features had previously been noted by a number of authors (Von Noorden and Mackenson, 1962; Eckmiller and Mackeben, 1978; Mitrani and Dimitrov, 1978; Lisberger et al., 1981; Whittaker and Eaholtz, 1982; Becker and Fuchs, 1985; van den Berg, 1988) but could not be unambiguously separated from the simple transient decay of the oculomotor response which has a time constant of 0.5-1 sec in darkness (Barnes and Asseiman, 1991). Examination of the averaged steady-state eye velocity profile evoked by repeated transient stimulation (Barnes and Asselman, 1991) indicated that eye velocity was initiated well before target onset and attained, on average, 66% of its peak velocity 100 msec after target onset at the time when visual feedback would be expected to become effective (Fig. 30). The maximum velocity achieved in this type of response was far greater than that which can be induced normally in the dark without prior stimulation. Most importantly, the predictive velocity profile evoked by the repeated, brief stimulation had a highly stereotyped temporal characteristic irrespective of the interval between presentations and could be reproduced in the dark even when a period as long as 4 sec had elapsed from the previous visual stimulus.

5.5. THE ROLE OF PREDICTIVECONTROL" CONCLUSIONS 5.5.1. The mechanism of predictive control

5.4.2. Head-free pursuit and VOR suppression The same techniques have now been used to isolate the predictive component of the response during VOR suppression on the turntable and during headfree pursuit (Barnes and Grealy, 1992). During headfree pursuit the control of slow-phase gaze velocity and head velocity exhibited characteristics that were very similar to those for eye velocity during headfixed pursuit. In particular, after a number of cycles

The evidence from these experiments indicates that the predictive system probably functions in the following manner. When a stimulus is composed of some regularly repeated pattern a frequency entrainment mechanism or periodicity estimator automatically locks on to this pattern of repeated activity (Bahill and McDonald, 1981; Barnes et al., 1987; Barnes and Asselman, 1991). If the stimulus motion is composed of mixed sinusoids the periodicity estimator becomes tuned to the highest frequency component, presumably because the mechanism is dependent on sensing changes in direction in order to identify the frequency. Information from direct visual feedback can be used to drive the visuomotor system directly but it is probably of fairly low gain (approximately 0.4-0.5). However, this visual feedback infor-

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464

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F[6. 29. (A) Centre traces: Cycle-by-cycleaverages of eye velocity (repeated) and target displacement derived from the responses in Fig. 28, indicating the build-up of eye velocity prior to target appearance. Stimulus frequency 0.69 Hz. Upper traces: the first 2 cycles (solid line) and second 2 cycles (broken line) of eye velocity plotted to the same time-scale as the averaged responses so as to indicate the manner in which the magnitude and timing of the eye velocity response changes with repeated stimulation. Lowest trace: Pulses indicating timing of target exposure.(B) Changes in RMS eye velocity with number of cycles of stimulation. (C) Changes in eye velocityat the transition when there was an unexpected change in both velocity and direction of the target motion. Bar lines in lower trace mark the magnitude and timing of peak velocity points in relation to target velocity pulses. (From Barnes and Asselman, 1991.) mation can be enhanced after the initial presentation of retinal error signals by adding an additional drive component. This additional drive probably comes from the use of efference copy information, a concept that was originally proposed by Yasui and Young (1975) and has since gained increasing acceptance (Young, 1977; Lisberger and Fuchs, 1978; Miles and Lisberger, 1981; Robinson, 1982; Bahill and McDonald, 1983). Based on the evidence from experiments described in Section 5.4.1, Barnes and Asseiman have suggested that the system may use an internally stored copy of the visual feedback information which is derived by sampling of the efference copy of the oculomotor drive signal. In order for the system to operate in a predictive manner the periodicity estimator is crucial in controlling the release of stored information from the memory at the appropriate time in advance of the arrival of further visual feedback information. These concepts have been embodied in a model of the predictive mechanism which is shown in Fig. 32. At low frequencies of stimulation ( < 0.4 Hz) it is assumed that there is a process of continuous prediction mediated by the element PRD that uses current and previous estimates of visual feedback to estimate the required additional drive to the oculomotor system. At higher frequencies ( > 0.4 Hz) this system breaks down because of delays in the visual feedback and the system resorts to a mechanism that relies on

the use of stored velocity estimates from a previous half-cycle of stimulation. The output of the store (MEM) is timed by the periodicity estimator so as to occur in anticipation of the visual feedback and thus overcome the delays in visual processing. In this way the system is able to operate over an extended frequency range between approximately 0.4 and 2 Hz which is critical because it is the frequency range in which most natural head and eye movements occur. An important aspect of the performance of the system is the manner in which the role of visual feedback changes. Initially it provides the necessary means to drive the oculomotor system, but once prediction is underway, it appears to be used to monitor conflict between the predictive estimate and current visual input. The important point that is revealed by the experiments described here is that these features of the predictive system are quite specific to visual feedback mechanisms and do not apply to non-visual suppression of the vestibular reflex, for example. But, in addition, these features operate in a common manner for pursuit, VOR suppression and head-free pursuit. 5.5.2.

Neurophysiology of prediction

A major question that arises from these results is where the sites of the different mechanisms involved in predictive pursuit might lie. In fact it seems quite

VISUAL-VESTIBULARINTERACTION

likely that multiple sites may be involved in this process. There are at least five separate mechanisms involved: (1) A periodicity estimator; (2) a sample and hold mechanism; (3) an intermediate storage mechanism (MEM); (4) a conflict monitor which detects differences between the predictive estimate and the visual velocity feedback; and (5) a mechanism for potentiating the feedback gain from a selected target source. Early experiments pointed to the flocculus and/or the vermis of the cerebellum as being important in prediction. Lisberger and Fuchs (1977) felt that the cerebellum was the site of the efference copy system on the basis that signals proportional to eye velocity as well as retinal error velocity were present there. More convincing was the finding of Noda (1986) that there is activity in flocculus which continues after there has been a change in stimulus frequency. However, all these effects could merely represent the relaying of information which is actually controlled further upstream since the cerebellum is known to be an essential part of the pursuit pathway (Zee et al., 1981). As noted earlier, the MT/MST area is probably the first point in the visuo-motor pathway at which there is any sign of efference copy feedback and this could well be the site of the sample and hold mechanism. It is also quite feasible that the influence of parietal cortex is one of producing enhancement of activity within MST which may in itself be carried out through potentiation of the predictive response. Periodicity estimation is a function which is probably common to many different sensory modalities and recent evidence

465

(Brotchie et al., 1991) suggests that the giobus pallidus in the basal ganglia in particular carries signals of the type which would be useful for controlling the timing of the predictive response in manual control.

6. GENERAL CONCLUSIONS 6. l. VISUALVERSUSNoN-VISUALVOR SUPPRESSION As a result of the experimental work that has been carried out to date it is possible to draw some conclusions about the various mechanisms that control head and eye coordination. It is evident that head-fixed pursuit, head-free pursuit and VOR suppression share much in common. It is probable that the question that should be asked is not "Is there a completely separate system for pursuit and VOR suppression?", but rather "What proportion of the control is carried out by visual and non-visual mechanisms?" it is evident that the VOR is very labile. Its gain can be changed over a very wide range by long-term adaptive processes (Gonshor and MelviU Jones, 1976a,b; Miles and Eighmy, 1980; Robinson, 1976). It can also be modified in the short term by mental set, even exceeding unity in some conditions (Bronstein and Gresty, 1991). It is probable that the lower estimates of VOR gain obtained in darkness reflect "some default performance of a much larger gaze-control system, functioning poorly in the absence of complete information" (Collewijn, 1989).

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FIo. 30. (A) Changes in the magnitude of peak eye velocity during the first 4 presentations of the moving target as a function of the velocity of target motion. Results shown are for a PD of 120 msec during active pursuit and are representative of all values of PD tested. Mean of 4 Ss. + I S.E.M. (B) Continuous lines represent three measures of eye velocity derived from the cycle-by-cycle average (Fig. 29) plotted as a function of target velocity: (i) velocity at target onset (I-q); (ii) velocity 100 msec after target onset (A); and (iii) peak velocity (O). Broken lines indicate the values of peak eye velocity generated (iv) in darkness when the target unexpectedly failed to appear (A) and (v) during the visual stimulus immediately prior to this transition period (O). PD = 240 msec. Mean of 4 subjects. + 1 S.E.M. Note the similarity between the velocity in darkness during the transition period and the velocity of the average response 100 msec after target exposure. (From Barnes and Asselman, 1991.)

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FIG. 31. Centre traces in (A), repeated cycle-by-cycleaverages of gaze velocity (solid line), head velocity (broken line) and target displacement (sinusoid) derived from responses similar to those shown in Fig. 28, but in which both the head and eyes were moved to follow the target. Stimulus frequency 0.78 Hz. Upper traces in (A)---the first cycle of gaze velocity (solid line) and head velocity (broken line) plotted to the same time scale as the average responses so as to indicate the manner in which response velocity changes during the first four target presentations. Lowest trace in (A)---timing of target exposure. (B)--changes in R.M.S. gaze velocity (solid line) and head velocity (broken line) with number of half-cycles of stimulation. (C)--changes in gaze and head velocity at the transition when the target suddenly disappeared. Bar lines in lower trace indicate the magnitude and timing of peak gaze velocity in relation to target velocity stimulus. (From Barnes and Grealy, 1992.) Although VOR gain may be less than perfect it is quite evident that perceptual mechanisms do have access to a fairly precise measure of head position (Guedry et al., 1971; Mergner et al., 1991), which must be derived from the temporal integration of the vestibular output. Such information allows head position to be monitored after whole-body rotation (Guedry et al., 1971; Bioomberg et al., 1991) and probably forms the reference signal by which VOR gain can be raised when imagining an earth-fixed target in darkness (Barnes and Eason, 1988). But there appears to be a restricted range over which mental set can effect VOR suppression, so that even when the process is aided by presentation of restricted visual stimuli, suppression is not as good as with full visual stimulation. In fact, there is some evidence that the level of VOR gain measured with mental arithmetic is lower than that which normally applies during visual stimulation (Barnes and Grealy, 1992), as though the visual stimulus itself may have some general arousal effect on the response, although this was not supported by previous experiments (Barr et al., 1975). In other words, the default level of gain that operates during head-free pursuit is probably closer to that recorded when the subject attempts to visualize an earth-fixed target in darkness. This is supported by the report of Gauthier and Vercher(1990) that VOR gain is initially high (0.8-0.9) irrespective of visual conditions, but gradu-

ally diminishes in darkness. It is also supported by the observations presented here that the small difference between head-fixed and head-free pursuit observed in normal subjects can only be explained if the underlying VOR gain is normally high. So, if it is possible to carry out non-visual suppression, why does it not appear to play a very prominent part in head-free pursuit? The contribution of visual and non-visual mechanisms can be put into perspective by considering their relative effects on VOR suppression. The degree of VOR suppression achieved by non-visual means is rarely better than 0.5, which would be equivalent to a feedback gain of 1. In contrast the degree of suppression achieved by visual feedback is normally around 0.1 or less, implying a feedback gain of 10 or more. Thus, visual feedback is much the more powerful means of control. Whether or not non-visual suppression is likely to be operational during head-free pursuit will be dependent on the actual mechanism involved. If non-visual suppression were accomplished by a parametric change of VOR gain upstream of the point at which visual suppression occurred, it would be advantageous for it to operate during bead-free pursuit. If, on the other hand, the mechanism involved a suppression of eye velocity through the negative feedback of an efference copy of eye velocity, as suggested in Fig. 11, it would be completely inappropriate for it to operate during head-free pursuit, since it would result in suppression of not only the VOR,

VISUAL-VESTIBULARINTERACTION

but also the drive for pursuit itself that originates from the visual feedback. Even if it were possible for non-visual VOR suppression to take place during head-free pursuit, it might not be used because there is no operational need for it in most subjects in normal circumstances. Only at high levels of target velocity is visual feedback likely to break down, as pointed out by Robinson (1982) and there are few situations in which most individuals need to regularly track moving targets at such high velocities. Recent reports (Lisberger, 1990; Cullen et al., 1991) do demonstrate that non-visual suppression increases at high velocities of head movement, although it is evident from other experiments (Barnes and Edge, 1983; Barnes et al., 1988; Waterston and Barnes, 1992) that velocity saturation effects still apply in these circumstances and have not therefore been eliminated by non-visual mechanisms. In humans, although head-free pursuit may be slightly better than head-fixed pursuit at high velocity and high frequency, there is some evidence that VOR gain itself may be reduced in these conditions (Hyden and Larsby, 1991) and therefore may contribute to this difference.

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6.2. IMPLICATIONSFOR DIAGNOSISAND ADAPTIVE RECOVERY There are clearly a number of examples in the clinical literature which indicate that pursuit, O K N and VOR suppression may not always be identical in some patients (Chambers and Gresty, 1983; Ranalli and Sharpe, 1988). This has generally been interpreted as an indication that the same mechanisms may not be involved in all of these tasks. The evidence shown here indicates that in normal subjects there does appear to be a close correspondence between the two tasks, both depending very heavily on the visual input to control eye movement. So what possible explanations can be put forward for these apparent discrepancies? As in many other sensorimotor systems that have multiple sensory inputs there is an inbuilt redundancy. Not all inputs are required to make the system work. As a consequence, those inputs that are most appropriate to the prevailing conditions gain the most control of the process. An example of this behaviour is the pseudo-VOR response that may be observed in patients with total loss of vestibular function during voluntary head movements (Dich-

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F1G. 32. A model of the mechanisms for visual-vestibular interaction in oculomotor control. The visual feedback is composed of two basic components, a direct feedback of retinal velocity error and a secondary pathway incorporating a predictive velocity estimator (PVE) the PVE is a sample and hold mechanism that takes its input from an efference copy of gaze velocity (~' = eye velocity if head velocity = 0). Output from the PVE is controlled by a periodicity estimator (PE) that derives its control from the retinal velocity error signal and thereby estimates the periodicity of the most frequently changing component of the stimulus. The PVE may obtain estimates of required eye velocity either from direct sampling of efference copy, through the predictor (PRD), or from information stored in memory (MEM) based on the previous half-cycle of the response, depending on stimulus frequency. The output from PVE is partially integrated by the filter P(s)[ = (1 + Tps) - :], which has a time constant Tp of approximately 0.15 sec and summated with the retinal velocity error signal before passing through a band-pass filter F(s) [ = s.(l + Ts) -2] with a time constant T of approximately 0.5-I sec. The output of P is also assumed to be directed to the neck muscles to control head rotation as defined by the function H(s). G(s) represents the dynamic characteristics of the semicircular canal system (SCC)[ = KvoR'((l + td)(l + t2s))- t, where Tt ~ 10-20 see; T2 ~ 0.01 sec], s is the Laplace operator, Kv = visual feedback gain, z = delay in visual feedback ~. 0.1 sec. (From Barnes and Grealy, 1992.)

468

G . R. BARNES

gans et al., 1973; Barnes, 1979; Bronstein and Hood, 1986), which is thought to arise largely from potentiation of the normally quiescent cervico-ocular reflex. Likewise, it may be that in a normal subject the visual system is well able to cope with the demands for pursuit and VOR suppression, whereas in a patient with loss of effective visual feedback, it is feasible that other mechanisms such as non-visual suppression of the VOR may become more prominent and allow at least part of the system to function. Non-visual suppression of the torsional VOR may have developed in this way in the absence of an effective torsional O K N control system (Leigh et al., 1989). It is now well established that the cerebellum is the primary site for adaptation and without it the gain of the VOR cannot be modified to accommodate changes in the visual world such as those brought about by the prolonged wearing of magnifying spectacles (Robinson, 1976; Miles and Lisberger, 1981). But the cerebellum is also an essential part of the pursuit pathways, so it may be that cerebellar patients, who make up a large part of those with combined deficiency of pursuit and VOR suppression, are unable to carry out the necessary potentiation of non-visual suppression. If the subject loses effective volitional control of the saccadic system, which is an integral part of the pursuit reflex, this could easily lead to an apparent difference between pursuit and VOR suppression. For example, the inability to initiate catch-up saccades during pursuit would result in the small target rapidly falling outside the most sensitive foveal area, with a consequent loss of drive to the oculomotor system. Such effects could be overcome by using a much larger target for this task. This problem is not likely to arise during VOR suppression because the eye tends to remain around orbital centre. During pursuit, it is also quite common, even amongst normal naive subjects, to find large saccadic eye movements occurring in anticipation of the target displacement, which, again, would lead to the image of the moving target being located in an eccentric area of the retina where it has little power to drive the eye movement. In other words, during pursuit it is quite easy for an uncooperative or ill-motivated subject to ignore the visual velocity feedback cues and simply make saccadic movements instead, whereas the VOR suppression task is more compelling, unless the subject chooses to look to one side of the target. In some cases a dissociation of pursuit and VOR suppression could come about as a result of limitations in the oculomotor range or in abnormalities such as gaze evoked nystagmus. The latter is a nystagmus with fast-phase components directed away from head centre when looking eccentrically and is thought to be associated with loss of central neural integrator function (Cannon and Robinson, 1986). The effects on pursuit are potentially complex because when the target is tracked into the eccentric visual field the gaze evoked nystagmus interacts with pursuit. This is not a simple overlay of the nystagmus but a complex interaction that modifies the retinal velocity error signals for pursuit. Similar arguments may be made for the effects of congenital nystagmus and other disorders of eye movement.

A further possible reason for the dissociation of pursuit and VOR suppression could be that although the visual feedback, with all its attendant non-linearities, may form a common input to the mechanisms of VOR suppression and pursuit, there may be a divergence of efferent pathways prior to the final common oculomotor pathway. It is known that the cerebellum has a duplication of sites for visual-vestibular interaction (Lisberger and Fuchs, 1978a,b; Suzuki and Keller, 1988a,b) and it is possible that the two areas have different weighting levels for the control of pursuit and VOR suppression. Two separate sites have also been identified in the pons, both of which relay corticofugai fibres to the oculomotor centres (Suzuki and Keller, 1984). It is important to bear in mind that the mechanisms of visual-vestibular interaction represent an example of a distributed network system. In such a system not every element of the network need necessarily perform the same function in the same way, although the final result of activity in the whole network will combine to form a coherent response. Thus, different elements of the network for visual-vestibular interaction could have different connectivity weightings for the control of smooth pursuit and the suppression of vestibular responses as implied by the findings of May and McCrea (1985). A lesion in one area might lead to an imbalance between pursuit and VOR suppression and if the lesion happened to affect those areas concerned with adaptive processes, such as the cerebellum, the appropriate balance might never be restored.

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BRONST~IN, A. M. and GRESTY, M. A. (1991) Compensatory eye movements in the presence of conflicting canal and otolith signals. Expl Brain Res. 85, 697. BRONS'mN, A. M. and HOOD, J. D. (1986) The cervico-ocular reflex in normal subjects and patients with absent vestibular function. Brain Res. 373, 399-408. BROTCHm,P., IAIqSEK,R. and HORr,~, M. (1991 ) Motor function of the monkey globus pallidus. 2. Cognitive aspects of movement and phasic neuronal activity. Brain 114(4), 1685-1702. BuFrn~a, U. W., HEh'N, V. and YOUNG, L. R. (1981) Frequency response of the vestibulo-ocular reflex (VOR) in the monkey. Aviat. Space environ. Med. 52, 73-77. B~TTr~R, U. W. and BOTTNER, U. 0979) Vestibular nuclei activity in the alert monkey during suppression of vestibular and optokinetic nystagmus. Expl Brain Res. 37, 581-593. BOTTNL~, U., MEtL~tnERG,O. and SCHIMMELPFENNIG,B. (1983) the effect of central retinal lesions on optokinetic nystagmus in the monkey. Expl Brain Res. 52, 248-256. CAt,rNoN, S. C. and RomlqsoN, D. A. (1986) The final common integrator is in the prepositus and vestibular nuclei. In: Adaptive Processes in Visual and Oculomotor Systems, pp. 307-31 I. Eds. E. L. KELLERand D. S. ZEE. Pergamon Press: Oxford. CARL, J. R. and GELLMAN, R. S. (1987) Human smooth pursuit: stimulus-dependent responses. J. Neurophysiol. 57, 1446-1463. Cn^MnERS, B. R. and GRESTY,M. A. (1983) The relationship between disordered pursuit and vestibulo-ocular reflex suppression. J. Neurol. Neurosurg. Psychiat. 46, 61-66. CHENG, M. and Otn'ERnRIOGE, J. S. (1975) Optokinetic nystagmus during selective retinal stimulation. Expl Brain Res. 23, 129-139. COHEN, B., UEMURA, T. and TAKEMORI, S. (1973) Effects of labyrinthectomy on optokinetic nystagmus (OKN) and optokinetic after-nystagmus (OKAN) Equilibrium Res. 3, 88-93. COr~N, B., RAPnAN, R. and MATStJO,V. (1977) Quantitative analysis of the velocity characteristics of optokinetic nystagmus and optokinetic after-nystagmus. J. Physiol. 270, 321-344. COLLE~V1JN,H. (1975) Direction-selective units in the rabbit's nucleus of the optic tract. Brain Res. 100, 489-508. COLLEWIJN, H. (1981) The Oculomotor System of the Rabbit and its Plasticity. Springer. New York: COLLEWlIN,H. (1985) Integration of adaptive changes of the optokinetic reflex, pursuit and the vestibulo-ocular reflex. In: Adaptive Mechanisms in Gaze Control, pp. 51-69. Eds. A. BERTHOZand G. MELVtLL JONES. Elsevier: Amsterdam. COLLEWIIN,H. (1989) The vestibulo-ocular reflex: is it an independent subsystem? Rev. Neurol., Paris 8-9, 502-512. COLLEWItN, H. and TAMMINGA, E. P. (1984) Human smooth and saccadic eye movements during voluntary pursuit of different target motions on different backgrounds. J. Physiol., Lond. 351, 217-250. COLLEW1JN, H. and TAMMINGA, E P. (1986) Human fixation and pursuit in normal open-loop conditions: effects of central and peripheral retinal targets. J. PhysioL, LoRd. 379, 109-129. CULLEN, K. E., BELTON,T. and McCREA, R. A. (1991) A non-visual mechanism for voluntary cancellation of the vestibulo-ocular reflex. Expl Brain Res. 83, 237-252. DALLOS, P. J. and JONES, R. W. (1963) Learning behaviour of the eye fixation control system. IEEE Trans. Ae41, 218-227.

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