In the twenty-five years since the publication of the Cerebellum as a Neuronal Machine (Eccles et al. 1967) the notion that cerebellum plays an important role in motor learning has now become commonly accepted. The important remaining question facing neurophysiologists is no longer whether the cerebellum participates in skill acquisition, but rather how it operates. In view of the current controversy over whether the cerebellum is the single exclusive storage site for motor learning, I propose to assume, (but will rely on the evidence provided by others in this issue) that some significant plastic changes in synapses do occur within the cerebellar cortex during motor learning. However, learning in general, is thought to be a distributed process, and therefore it is not reasonable to assume that all motor learning is limited or otherwise exclusive to the cerebellum. Also missing from this review because of space limitations are considerations of the regional specialization within the cerebellum itself, and the sensory afferent systems that converge there. Instead, I propose to expand upon and modernize an idea first elaborated by Babinski (1899) who drew upon the animal lesion studies of Luciani as well as his own clinical experience to formulate his concept of cerebellar function.
Ataxia, which is associated with large cerebellar lesions, represents an inability to coordinate synergies, or according to Babinski (1899), an "asynergia", which he felt was pathonomonic of cerebellar dysfunction. It was this definition that drew the comment from Holmes (1939) that it was "...unnecessary as it would include symptoms of different origins". Retrospectively, this seems unnecessarily parsimonious considering that many medical terms are used to refer to collective groups of symptoms of different origin. Nevertheless, the critique has found its way into many textbooks of neurology with the explanation that cerebellar asynergia can be explained by increased reaction time, dysmetria, muscle weakness and hypotonia. Yet how accurate is this assertion in the light of modern experimental neurology? For example, Mai et al (1988) found the muscular power to be normal in patients with a wide range of cerebellar syndromes although these same patients had a variety of deficits in controlling isometric finger forces. Although numerous studies have confirmed an increased reaction time and dysmetria after cerebellar lesions (Brooks et al. 1973; Conrad et al. 1974; Diener et al. 1993; Spidalieri et al. 1983), muscle weakness remains a doubtful explanation for the deficient braking action of antagonist muscles. Flament & Hore (1986) demonstrated that cooling the cerebellar nuclei produced hypermetric movements accompanied by delayed recruitment of antagonist muscles, and this observation has now been confirmed in patients with cerebellar lesions (Diener et al. 1993). However, both these same studies showed that although the onset of the antagonist EMG was delayed, the amplitude was increased which argues strongly against the suggestion that muscles are weakened.
In 1902 Babinski published another very short paper reporting that patients with cerebellar lesions show difficulty in performing a rapid succession of alternating movements. He introduced the term "adiodocokinesia" to describe a deficit in the alternate activation and relaxation of antagonist muscles. Babinski considered that asynergia and adiodocokinesia together, represented a breakdown in the spatial and temporal organization of movement, which I will argue, is a fundamental deficit in reciprocally activating the agonist-antagonist muscles regulat-ing joint stiffness.
Simply put, the hypothesis advanced here has three postulates. The first, suggests that the cerebellum, by repeated associations through practice, forms and stores rewarded muscle activation patterns contributing to the time-varying joint or limb stiffness values for particular movements or postures. This limb or joint stiffness is controlled both by individual muscle activation levels as well as by the degree of co-contraction between mechanically opposing muscles. The second postulate is that inhibition from separate microzones of Purkinje cells in the cerebellar cortex can relax the activity in single muscles or groups of muscles, and that multiple microzones acting together optimize time-varying changes in joint stiffness. Finally, the third postulate is that plastic changes in the cerebellar cortex result from repeated temporal associations of proprioceptive and teleceptive stimuli which act as conditioned stimuli to evoke the optimal time-varying changes in joint stiffness.
The following presentation is organized in two sections. The first reviews the evidence that muscle, joint and limb stiffness is controlled by synergies involving mechanically opposing muscles, and the second evaluates the data suggesting a cerebellar involvement in the command strategies which control muscle, joint and limb stiffness.
Controlling the mechanical properties of muscles, joints and limbs
Clarifying the concept of synergy
Unfortunately the term synergy has become somewhat confusing due to the absence of an accepted meaning and inconsistent usage resulting in at least two different and potentially contradictory definitions (see reviews by Lee 1984, Macpherson 1991; McCrea 1992; Windhorst et al. 1991). Originally, Babinski (1899) called synergy an "association of movements" and in a later paper "the ability to simultaneously accomplish diverse movements which constitute a single act" (Babinski and Tournay, 1913). A different use of the term, frequently attributed to Bernstein (1967), suggested that synergies were centrally-organized motor programs for fixed actions. In most tasks requiring movement, the number of parameters which could be controlled by the nervous system exceeds the number needed to achieve the goal thereby creating excess degrees of freedom, and a problem of response selection. Bernstein (1967) hypothesized that the nervous system might simplify motor control by grouping the parameters together under the coordination of a fixed single directive which might be considered as a synergic command. According to this view, synergy was the command algorithm rather than the group of muscles which implement the algorithm. As Macpherson (1988a; 1988b; 1991) has previously noted there is little empirical evidence in favor of fixed single command synergies. Instead, synergies appear to be flexible muscle activation patterns in which any combination of linkages is potentially available.
Macpherson (1991) also suggested that the nervous system uses motor strategies to achieve task-relevant motor objectives requiring the control of position, force or velocity and which are subsequently implemented as muscle synergies. One way in which the notions of fixed and flexible synergies might be brought closer together, although not entirely reconciled, would be to consider that strategies are the command algorithm employed by the nervous system to optimize muscle synergies by a process of continuous adaptive learning. Consequently, synergies would become progressively more efficient and stereotyped with the proper anticipation of ensuing teleceptive and proprioceptive stimuli. In any purposeful movement achieving the task objective (i.e. reinforcement) is the primary criterion for optimization, although the reduction of effort (Hasan 1986), optimizing the speed-accuracy tradeoff (Fitts, 1954), maximizing speed or endurance (Alexander 1989) or minimizing jerk (Hogan and Flash 1987) might be other important influences shaping the behavior. Once optimized, the synergies would remain fixed as long as the objective, the strategy and the feedback signals remain constant, but alteration in any one of these three would initiate a new process of optimization. This paper deals with the contribution of the cerebellum to the development of motor strategies controlling muscle synergies which alter the compliance or stiffness of joints or limbs.
After reviewing the problem of synergy at considerable length, Macpherson (1991) concluded that since no natural movement involves only a single muscle, and therefore synergy could be defined as simply "a group of muscles acting together". Moreover, since mechanically opposing muscles must act together, their cooperation might be considered as a fundamental unit of muscle synergy. That is, a synergistic group should include not only the prime-mover agonist muscles, but also the antagonists which must be either inhibited, disfacilitated or co-contracted. However, as Macpherson (1991) noted, this definition of muscle synergy is extremely broad, and implies some sort of control mechanism for motor coordination without providing any insight as to what this mechanism might be. This question of how the nervous system specifies strategies of muscular activation and inhibition is currently of great interest to neurophysiologists.
The combination of biomechanical analysis and EMG recording techniques has also revealed the presence of hidden, and heretofore unsuspected, agonist-antagonist co-contraction synergies. For example, van Zuylen et al. (1988) discovered that the triceps muscle is activated during forearm supination to compensate for the flexor action of the biceps muscle. Although the triceps makes no contribution to the forearm supination, it insures that the net flexor-extensor torque at the elbow remains zero. The presence of covert synergies in addition to the heterogeneous recruitment of motoneurons during the co-contraction of agonist-antagonist muscles has led Gielen and his colleagues (ter Haar Romeny et al. 1984; Jongen et al. 1989; van Zuylen et al. 1989) to propose the existence of a centrally-driven mechanism for controlling reciprocal inhibition or co-activation of parts of the flexor and extensor motoneuron pools. Taken together, these findings suggest that although some muscle synergies may be extremely covert, they nevertheless perform important functions related to both task requirements and biomechanical constraints. In the light of these data, Macpherson's (1991) definition of muscle synergies might be further qualified to the following: A muscle synergy is a group of muscles acting together whose actions contribute to movement efficiency and postural stability.
The mechanical properties of a multi-jointed limb
Motor control neurophysiologists have been turning increasingly to the study of mechanics for clues as to how the brain controls complex limb movements. The mechanical impedance (i.e. the resistance to movement) of a single joint can be characterized by scalar values of inertia, viscosity and stiffness. This mechanical impedance determines how much the joint will resist a perturbing force. Although the inertial component of the mechanical impedance is approximately constant, the viscous and elastic components depend on reflex gain and the amount of prior muscle activation. The mechanical properties of a multi-segment limb are more complex and require a matrix of coefficients of inertia, viscosity and stiffness.
One of the first great insights into motor control was Sherrington's (1909, 1947) discovery of the spinal reflexes controlling reciprocal inhibition. Today, both reciprocal inhibition and co- contraction are recognized as muscle activation patterns controlled by the brain which would seem to include all skeletal muscles and even the extraocular motor system (Robinson 1981). Reciprocal inhibition and agonist-antagonist co-contraction reflect strategies of motor control which directly affect joint stiffness. Although the purpose of this strategic control is to optimize the limb's mechanical interaction with its environment, the specific objectives to be achieved may vary widely. For example, activation of a muscle as it is being stretched increases the elastic energy of the muscle as in crouching preparatory to jumping in cats (Walmsley et al. 1978; Zomlefer et al. 1977). Co-contraction can also briefly increase the joint stiffness to optimally absorb the momentum of a visually predictable perturbation such as catching a ball (Lacquaniti and Maioli, 1989; Lacquaniti et al 1993) or absorbing the impact of ground reaction forces in the foot-contact, E2 phase of quadrupedal locomotion (Goslow 1973). Alternatively, when the task is to stabilize unpredictable and unstable loads, the subject may resort, with some effort and risk of fatigue, to a strategy of co-contraction (e.g. Akazawa et al 1983; Hasan 1986; Humphrey & Reed 1983; Milner and Cloutier 1993). Nevertheless, with practice, and because co-contraction is fatiguing, even unstable loads are usually transferred to one of the muscle groups whose actions are mutually opposing rather than alternating or co-contracting. For example, Clement and Rezette, (1985) found that better trained gymnasts performing hand-stands prefer a strategy of transferring the load to the forearm extensor muscles alone, whereas co-contraction or rapid sequential activation of the antagonists produced significantly more body sway (and probably more fatigue) in less experienced gymnasts.
A recent examination of muscle activity in bicycle pedaling has pointed out that the direction of joint rotation of individual joints is in inherent conflict with the required joint torque necessary to generate a directed force on the pedal (van Ingen Schenau et al. 1992). According to these authors, the mono-articular hip extensor muscles co-contract with the bi-articular hip flexors to produce the correct balance of joint flexor torque needed to transfer force in the appropriate direction at the distal joints. This pattern of muscle activation is reminiscent of a particular type of co-contraction which occurs during the opposition of the fingers in pinching (Smith 1981). In this instance, co-contraction of the forearm flexors and extensors of the wrist and fingers increases the stiffness at the carpal and metacarpal-phalangeal joints in order to transmit forces to the tips of the fingers more effectively.
It is also important to recognize that co-contraction and reciprocal inhibition are not mutually exclusive. Agonist-antagonist activity can overlap even during reciprocal activation (e.g. the triphasic muscle activation pattern of rapid voluntary movements). In fact, because of the relatively lengthy electromechanical delay between the arrival of the action potential and the consequent change in muscle tension , and the duration of muscle twitches, co-contraction and stiffness increases can occur even when the EMG bursts show no temporal coincidence whatsoever. An analysis of EMGs during rapid alternating movements similar to those studied by Babinski have shown a modulated reciprocal activity superimposed on a background of co- contraction to control joint stiffness (Feldman 1980a, 1980b, Humphrey & Reed 1983; Levin et al., 1992). The control of muscle stiffness
Variations in the stiffness of individual muscles is an important factor contributing to joint or whole limb stiffness. Muscle stiffness is determined, in part, by inherent properties such as the degree of overlap between actin and myosin filaments limiting the number of cross-bridges which can be formed at a given muscle length (Gordon et al 1966). In addition, the stiffness of an active, fully innervated muscle can be further modulated through reflex gain changes (e.g. Hoffer & Andreassen 1981; Houk and Rymer 1981; Nichols and Houk 1976; Rack and Westbury 1974), or supraspinal commands (e.g. (Lacquaniti and Maioli, 1989, 1993; Milner and Cloutier 1993). A full discussion of the reflex control of muscle is beyond the scope of this article. The major concern of the present paper is not whether the brain, or the cerebellum in particular, can contribute to the reflex changes in the stiffness of individual muscles, but whether a more efficient control of joint and limb stiffness can be achieved by an anticipatory command strategy dictating the degree of co-contraction in posture and movement. As will be discussed later, there is good reason to believe that feedback mechanisms (i.e. reflexes) are by themselves inadequate to control the overall stiffness of multi-articular limbs.
The control of joint viscoelastic properties
Lacquaniti and Maioli, (1989) were among the first to point out that combined voluntary and reflex changes in joint stiffness and viscosity significantly reduced both the oscillation, amplitude, and damping time induced by perturbations. Postural stability results partly from the combined activities of agonist-antagonist muscles about a particular joint (Bizzi et al. 1982; Feldman 1980a, 1980b; Mussa-Ivaldi et al. 1985; Rack & Westbury 1969, 1974). This stability of a fixed position in a plane has been represented as a two dimensional postural force field. The postural forces are spring-like and can be characterized as the product of a displacement vector and a stiffness matrix. The stiffness matrix is often represented graphically as an ellipse in which the length and direction of the major and minor axes of the ellipse represent the magnitude and direction of the eigenvectors of the stiffness matrix. Limb stiffness was measured for the entire upper limb and represented both as an endpoint stiffness and joint stiffness (Flash & Mussa-Ivaldi 1990; Mussa-Ivaldi et al. 1985, Shadmehr et al 1993). In general, the shape and the orientation of the stiffness fields were determined by biomechanical properties such as muscle moment arms and limb postures, and were similar between subjects over time. In contrast, only small changes in the magnitude of the stiffness ellipse occurred when subjects voluntarily increased the stiffness to resist sinusoidal force pulse perturbations (Mussa-Ivaldi et al. 1985). From a subsequent study it appeared that to some degree, the changes in the magnitude of the single joint stiffness ellipses were correlated with changes in agonist-antagonist EMG activities (Flash & Mussa-Ivaldi 1990). Furthermore, Shadmehr et al (1993) found that the strength of the postural force fields decreased as the amplitude of the displacement from the original position increased .
To date, none of the studies have proven that limb or joint stiffness per se is a parameter controlled by the nervous system. Conceivably, these fields might be an incidental by-product of the activation of individual muscles. However, from a theoretical standpoint, Hasan (1986) has suggested that optimizing joint stiffness may have certain advantages in executing unperturbed displacements of an inertial load particularly as far as reducing movement "effort" (defined as the non-reflex drive to motoneurons) is concerned. Also Hogan (1990) has pointed out the advantage of making a limb more compliant to avoid "contact instability" when a multi-articular arm of spring-like actuators encounters an object in the environment. These theoretical analyses indicate that because of the delay, mechanical control cannot be adequately regulated by feedback compensation alone. Evidence supporting the notion that myotatic reflexes may be inadequate to maintain unstable loads has been provided by Milner and Cloutier (1993). They found that when particular joint forces and rotation frequencies combined to produce reflexes which were 180o out of phase with angular velocity, the mechanical instability was greatly aggravated. Apart from reflexes, the nervous system has three additional preparatory strategies for modulating limb stiffness; changing individual muscle stiffness, changing the limb position, or changing the degree of co-contraction in agonist-antagonist muscles.
The control of time-varying stiffness
Measures of time-varying stiffness and viscosity depend on the amplitude, duration and frequency of the perturbation used as well as the joint position. Nevertheless measures under static conditions indicate that significant modulation of the viscoelastic property of joints can occur under some conditions ((Lacquaniti and Maioli, 1989; Hunter and Kearney 1982). Estimates of viscoelastic properties during movement has been more difficult to obtain. Indirect estimates made by Latash & Gottlieb (1991) and direct measurement by Milner (1993) suggested that dynamic stiffness was greater for fast movements than slow movements. One of the few studies to measure joint stiffness directly both at rest and during movement was conducted by Bennett et al. (1992). Applying pseudo-random force pulses through a wrist- mounted air jet, Bennett et al. (1992) showed that for the range of planar elbow movements and velocities, the static (i.e. postural) stiffness was greater than the dynamic (i.e. movement) stiffness. Figure 1 illustrates the time-varying changes in stiffness throughout the movement.
[THESE ARE FIGURE CAPTIONS ONLY: FIGURES THEMSELVES ARE ONLY AVAILABLE IN THE PAPER VERSION] Figure 1 The mean time-varying stiffness for 300 oscillations of the elbow joint of fixed duration and amplitude. The * indicates the mean postural stiffness averaged over 4 trials as the subject pointed to targets located at the two extremes and midway between. The vertical bar shows one standard deviation. From Bennett et al. 1992.
The stiffness was lowest at the midway point, and rose at the turning points from flexion to extension, and from extension to flexion. These data also suggest that limb stiffness is higher in static postures which is consistent with what is known about short-range muscle stiffness. Recently both Bennett (1993b) and Milner (1993) found time-varying changes in elbow stiffness during flexion-extension movements which increased with movement velocity. In addition Milner (1993) found the elbow stiffness increased for viscous loads compared to no-load movements of equal velocity. One unresolved difference between these two studies relates to whether stiffness was greater during posture compared to movement. However, both studies agree that tuning joint stiffness to movement speed greatly facilitates the execution of movement. Whether these time-varying changes in stiffness reflect a changing control signal or merely the fortuitous sum of mechanical properties in individual muscle still remains to be determined.
Cerebellar function in the time-varying control of joint stiffness Ataxia results from a feedforward not a feedback deficit
The cerebellum exerts a significant modulatory action over gamma motoneurons (Gilman 1969a, 1969b, Schieber and Thach 1985), and the notion of cerebellar control over stretch reflex gain has been widely accepted (MacKay and Murphy 1977). However, the adequacy of a breakdown in this mechanism to explain cerebellar ataxia has recently been seriously challenged (Gorassini and Prochaska 1993). According to this view, cerebellar ataxia is not primarily caused by deficient proprioceptive reflexes but results instead from an inability to program muscle synergies. In spite of Holmes' (1939) opinion that with respect to co-contraction of agonist-antagonists "no such disturbance exists in sufficient degree to play a part in cerebellar ataxia", many contemporary neurologists have shown that cerebellar lesions are associated with disturbances of the agonist-antagonist muscle relations. For example, Rondot et al. (1979) recorded from a variety of limb muscles and noted that the initiation of fast movements was accompanied by short EMG bursts frequently appearing simultaneously in agonist and antagonist muscles of the shoulder and elbow in patients with cerebellar lesions. Hallett et al. (1975) found that patients with cerebellar lesions when asked to perform ballistic elbow flexion against a tonic triceps activity showed co-contraction of both biceps and triceps which resulted in hypometric movements. Conversely, if a tonically active biceps is suddenly released, the delayed activation of the antagonist triceps causes a hypermetric flexion (Terzuolo et al. 1973). Similarly, the poorly coordinated sequential activation of agonist-antagonist muscles in multi-joint movements severely impaired the ability of cerebellar damaged patients to accurately throw a ball at a target (Fig. 8 in Becker et al. 1990). Co-contraction also disrupts and slows rapidly alternating movements of the wrist (Diener et al. 1993).
[THESE ARE FIGURE CAPTIONS ONLY: FIGURES THEMSELVES ARE ONLY AVAILABLE IN THE PAPER VERSION] Figure 2 EMGs from wrist flexor and extensor muscles in a patient with a unilateral cerebellar lesion asked to perform rapid alternating movements. The hand ipsilateral to the lesion (2B) shows slowing and irregularity of movement as well as a desynchronization between EMG onset and the movement turning points. Re-drawn from Diener et al. 1993.
Figure 2, taken from Diener et al (1993), compares the EMG activity of antagonist muscles during rapidly alternating wrist movements in a patient with a unilateral cerebellar lesion. Figure 2B shows that the movements are slower and more irregular and the temporal relationship between EMG onset and the movement turning points is lost compared to the contralateral hand shown in 2A.
It is also important to emphasize that the co-contraction seen in the EMG activity of patients with cerebellar damage is quite unlike the co-contraction seen in Parkinsonian patients. Parkinsonian rigidity is essentially an increase in tonic EMG activity, whereas the co-contraction deficit of cerebellar patients is most clearly revealed in the dysfunctional time-varying modulation of activity of between agonist-antagonist muscles during movement. Cerebellar activity related to agonist-antagonist muscles
It has been suggested that the increased discharge of some Purkinje cells may be related to muscle relaxation (Smith 1981). If this were true, then one would expect the majority of Purkinje cells to decrease firing frequency during the co-contraction of agonist-antagonist muscles. In order to test this hypothesis several monkeys were trained to perform two types of hand movements. In the first task the animals performed flexion and extension movements of the wrist. In the second task, the monkeys maintained an isometric pinch of the thumb and index finger for one second. The former task was achieved by a reciprocal inhibition of antagonists whereas the latter was accomplished by a co-contraction of both flexor and extensor muscles of the hand. About two thirds of the hand-related Purkinje cells decreased firing in one direction of the reciprocal wrist-movement task as well as during the co-contraction associated with pinching (Frysinger et al. 1984).
[THESE ARE FIGURE CAPTIONS ONLY: FIGURES THEMSELVES ARE ONLY AVAILABLE IN THE PAPER VERSION] Figure 3 Activity of a single Purkinje cell recorded in a monkey during a maintained pinch accomplished by a co-contraction of the forearm flexors of the wrist and fingers shown on the left. On the right, the same Purkinje cell demonstrated reciprocal discharge during performance of a wrist flexion and extension executed by reciprocal activation of wrist muscles. From Frysinger et al. 1984.
Figure 3 shows the decreased activity of a Purkinje cell during co-contraction and the reciprocal activity of the same cell in alternating wrist flexion and extension. The decreased Purkinje cell activity shown in Figure 3A is coincident with the co-contraction of forearm flexors and extensors. Also during extension movements, the decreased Purkinje cell activity shown in Figure 3B (right) was time-locked to flexor relaxation, whereas the increase in Purkinje cell activity lagged the onset of flexor muscle activity during flexion by approximately 250 msec. (3B left). Moreover, an analysis of the activity of 22 individual forearm muscles failed to reveal any flexor muscles with an activity profile which would fit with this Purkinje cell discharge pattern (Smith et al 1983).
[THESE ARE FIGURE CAPTIONS ONLY: FIGURES THEMSELVES ARE ONLY AVAILABLE IN THE PAPER VERSION] Figure 4 Activity of a single dentate cell recorded in a monkey performing a maintained pinch accompanied by a co-contraction of the forearm flexors of the wrist and fingers shown on the left. On the right, the same dentate cell demonstrated a reciprocal discharge during performance of a wrist flexion and extension executed by reciprocal activation of wrist muscles. From Wetts et al. 1985.
In these same two tasks, over 90% of cells in the dentate and interposed nuclei increased discharge frequency during pinching and of these 70% showed reciprocal activity during reciprocal wrist movements (Wetts et al. 1985). Figure 4 shows an example of a dentate neuron which increased discharge frequency during extensor muscle activation and reduced discharge during flexor muscle activity. During co-contraction however, the activity of most nuclear cells, including this neuron, increased activity in contrast to Purkinje cells which decreased their activity during co-contraction. This cerebellar nuclear cell behavior is approximately what one would expect from neurons having a firing frequency proportional to muscle activity. That is, the activity of the nuclear cell shown in figure 4 is probably related to forearm extensors regardless of whether the functional context is one of co-contraction or reciprocal inhibition. These two studies suggest that the output from cerebellar cortical Purkinje cells depends on whether antagonist muscles are reciprocally inhibited or co- contracted, whereas the activity of cerebellar nuclear cells does not.
In spite of these differences, the cerebellum may not be the only supraspinal structure involved in reciprocal inhibition and agonist-antagonist co-contraction. In a similar study of monkeys performing two tasks one involving reciprocal inhibition and the other agonist-antagonist co-contraction, Humphrey and Reed (1983) found two spatially separated populations of motor cortical neurons which were preferentially activated with either reciprocal muscle control or with agonist-antagonist co-contraction respectively. These data are an important indication that other, perhaps all, motor systems structures may play some role in setting joint stiffness.
A second series of experiments was undertaken to examine the effect of a loss of Purkinje cell inhibition on the simple reciprocal organization of ankle muscle antagonists during treadmill locomotion. The mutant mouse Lurcher has a progressive cerebellar cortical atrophy such that no Purkinje cells survive beyond early adulthood. Nonetheless, the Lurcher mouse has a nuclear cell density and volume which is essentially normal (Caddy and Biscoe, 1979). Additional degeneration of granule cells and cells of the inferior olive have been shown to be secondary to the loss of Purkinje cells (Wetts & Herrup 1982a, 1982b).
Using a shuttered video camera, the locomotion of Lurcher mice walking on a treadmill was studied, and EMGs from two antagonist muscles of the ankle, the anterior tibial and the triceps surae, were recorded (Fortier et al. 1987). The video analysis demonstrated a significant uncoupling of the movements between the fore and hind limbs on the same side of the body. A similar aberrant phase relation was found between the two hind limbs which normally should have been 180 degrees out of phase since the mouse, rarely, if ever, gallops. Figure 5 shows that the start of flexor activity with respect to the time the foot contacted the ground was highly irregular,
[THESE ARE FIGURE CAPTIONS ONLY: FIGURES THEMSELVES ARE ONLY AVAILABLE IN THE PAPER VERSION] Figure 5 Activity of the ankle muscles during walking in normal and Lurcher mice. The EMGs are displayed as both rasters and summed activity profiles. Each step cycle was normalized to 100% from foot contact to foot contact. In the Lurcher, the left triceps surae shows little reciprocal inhibition and the activity of the right triceps surae is desynchronized with respect the left footfall. (From Fortier et al. 1987).
And the reciprocal behavior particularly of the extensor muscles appeared to have been replaced by a modulated co-contraction. The locomotion was very ataxic and the frequent interruptions from a loss of equilibrium accounted for the absence of modulation in the contralateral limb also seen in Figure 5. In general, mice without Purkinje cells show deficits in both the ability to simultaneously (e.g. asynergia) and sequentially (e.g. dysdiadocokinesia) command the desired muscle synergies. As Babinski (1899) once remarked "It is in locomotion that the cerebellar asynergia is most evident".
The activity of simple spikes recorded in Purkinje cells during locomotion are also consistent with (but do not prove ) a role for the cerebellum in the time-varying control of limb stiffness. For example Armstrong and Edgley (1984) found that Purkinje cells were more active during locomotion than at rest, and that the Purkinje cell population as a whole was more active during the swing phase compared to the stance phase. Although most antagonist muscles are reciprocally active in locomotion there are occasional brief exceptions. For example, Udo et al (1981) found that Purkinje cell activity related to extensor muscles peaked during the E1 phase to prevent excessive extensor stiffness (i.e. to increase limb compliance) at the moment of foot contact with the ground.
In spite of the circumstantial evidence favoring a reciprocal behavior between cerebellar and nuclear neurons, this has never been adequately proven by simultaneous recording between connected pairs of Purkinje cells and their target nuclear neurons. It is quite possible that parallel modulation can also be present under some circumstances although such activity would moderate the net effect on joint stiffness.
Cerebellar activity related to reaching movements
The cerebellum is thought to play a more important role in compound, multi-articular movements than in simple, single-joint movements. Single cell recording studies during limb movements in primates have yielded somewhat controversial results. Some investigators failed to find any consistent discharge related to the direction of movement (MacKay 1988, Mano and Yamamoto, 1980, Schieber and Thach, 1985), whereas others (Gibson et al 1990) have stressed that hand movements produced stronger modulation than whole-arm reaching. In spite of these reports, ataxic reaching movements and deficits in visuomotor tracking are consistent findings with either degenerative cerebellar disease or experimental inactivation (e.g. Becker et al 1991; Miall et al 1987).
Our own studies were intended to determine whether the discharge of cerebellar neurons in awake monkeys trained to execute visually triggered whole-arm pointing movements were direction-related or not. A monkey seated before a two-dimensional work surface was trained to move a pendulum from a central start position to one of eight radially-arrayed targets in response to a visual cue. Movements to each target was randomized and repeated five times. Most shoulder area neurons in both the cerebellar cortex and cerebellar interpositus and dentate nuclei had a single peak of activity grouped about movements in a particular direction despite that fact that cerebellar neurons discharged with movements over a wide range of directions (Fortier et al 1989).
We also compared cerebellar and motor cortical unit activity in monkeys trained to perform the same multi-joint pointing task (Fortier et al. 1993). The most salient difference between the activity of motor cortex and the cerebellum lay in the greater percentage of "graded" discharge patterns found in cerebellum compared with a greater number of "reciprocal" patterns found in the motor cortex. A majority (58%) of motor cortical cells had reciprocal discharge patterns with the greatest activity for movements in the preferred direction and significant inhibition for movements in the opposite direction. In contrast, about 70% of cerebellar neurons had graded increases in activity for all movement directions but with a single peak direction. In particular, Purkinje cells showed a step-like increase in activity for all 8 movement directions (compared to the stationary posture prior to the go stimulus) in addition to a modulated increase in activity for movements approximating the preferred direction (see Fig. 9B in Fortier et al 1989).
To what parameters of motor control might this Purkinje cell activity be related? Although the Purkinje cell excitability co-varies with movement direction, it seems unlikely that this activity is correlated with kinematic parameters such as position, velocity, or acceleration. A direct relationship to either dynamic parameters such as muscle force or rate of force change, or to the underlying EMG amplitude seems equally unlikely because there is no adequate explanation for the step-like increase in Purkinje cell activity for all directions of reaching. However, the inhibitory action of Purkinje cells over the cerebellar deep nuclei, which are closely related to muscle tone would be consistent with reducing limb stiffness during movements compared to active holding as found by Bennett et al. (1992). The synchronization of movement and posture
As mentioned earlier, initial posture has a significant impact on the forces required for movement because of muscle moment arms and the length-tension properties of muscle. Therefore, both Hogan (1990) and Massion (1992) have postulated the need for a control system to maintain equilibrium and compensate for reaction torques in multi- articular movements. Massion (1992) further pointed out that a semi-independent postural control system can also be used to preserve certain body parts in relation to each other while allowing other segments to move as with maintaining head-to-trunk position or eye-to-hand positions. Although he enumerated various reasons for believing that posture and movement may be controlled by partially independent systems, normally these two must be very closely integrated to produce well coordinated movements. In general, postural adjustments and movements are triggered either simultaneously by external perturbations of body equilibrium, or in the case of self- initiated movements, postural adjustments occur in anticipation of equilibrium changes (Cordo & Nashner 1982; Horak et al. 1984; Lee et al. 1987).
Although the basal ganglia (Viallet et al. 1987) and premotor areas (Viallet et al. 1992), also play a role in postural adjustments, lesions of the cerebellum produce significant postural deficits (Diener et al. 1990; Viallet et al. 1994). Horak and Diener (1994) described normal EMG latencies, and normal spatial patterns of muscle activation accompanying the postural responses to an imposed rotation of the support surface in cerebellar patients. The response amplitude of these reactive postural adjustments were excessively large but nevertheless appropriately scaled to the rotational velocity of the support surface. The other postural deficit described by these authors was an inability of cerebellar patients to use prior experience in order to scale their postural responses to the amplitude of the platform displacement. Sensory afferents to the cerebellum serve as conditioned stimuli
The cerebellum receives a wide variety of sensory inputs including proprioceptive, cutaneous, vestibular, visual and auditory stimuli arising from both the multiple sources of mossy fiber afferents and the single source climbing fiber inputs from the inferior olive. The literature on these sensory inputs to the cerebellum has been thoroughly reviewed recently by Stein and Glickstein (1992). All movements occur within a sensory context, and movements which produce unexpected results or encounter perturbations give rise to error signals which are conveyed back to the cerebellum by fast feedback pathways triggering both error awareness and long-loop corrective reflexes. However, rapid, well-practiced voluntary movements are generally too fast for on-line error correction (Lashley 1951), and the phase lag of reflex feedback would be inappropriate to stabilize some limb oscillations (Milner and Cloutier 1993). Consequently, a feedforward control system is preferable to a control system based on feedback involving detrimental delay. In such a model, feedback drives an adaptive inverse dynamics control strategy which models the limb and its interaction with the environment with increasing accuracy. Learning theory suggests that two or more simultaneously active neural activities will tend to become associated with one another, and when one activity is elicited the associated activities will also be evoked (Hebb 1949). In the cerebellum the sensory afferents could serve as conditioned stimuli for cueing associated and rewarded muscle synergies, which would set critical values of joint stiffness by the same principals of learning theory (stimulus-to-stimulus or stimulus-to-reward associations) as those involved in classical or instrumental conditioning.
A visual stimulus such as the sight of the ball dropping in the Lacquaniti and Maioli (1989) study catching experiment was sufficient (with practice) to trigger anticipatory EMG activity. Similarly, auditory stimuli have been known to trigger anticipatory EMG activity since the classical conditioning experiments of Pavlov. However, the demonstration by Rossignol and Melvill Jones (1977) that movement precedes the musical beat in dancing is perhaps a better example not only of auditory triggered EMG activity, but also of time-varying changes in joint stiffness as well. One would predict that cerebellar damaged patients would perform equally poorly at both ball catching or dancing because of the inability to associate a muscle control strategy with the requisite teleceptive stimuli.
There is now increasing evidence that the cerebellum plays a role in functions which affect motor control indirectly as well as directly. For example, patients with cerebellar lesions have difficulty in making accurate duration estimates of auditory stimuli (Ivry and Keele 1989). Although the reason for these deficits is unclear, a difficulty in predicting the duration of teleceptive stimuli is more likely to be the cause of motor dysfunction rather than the result of it. This is shown, for example, by the impaired velocity perception of patients with cerebellar lesions (Ivry & Diener 1991). Since, the rapid execution of movement sequences requires the precise timing of EMG activity based on the anticipation of teleceptive and proprioceptive cues, the inability to anticipate these stimuli accurately could lead to serious movement timing errors (Ivry et al. 1988) and deficits in organizing sequential movements (Inhoff et al. 1989).
The inability of cerebellar patients to use prior experience in order to scale their postural responses reported by Horak and Diener (1994) is particularly relevant example of how the cerebellum uses proprioceptive cues as conditioned stimuli. In these experiments the perturbation amplitude could not be fully appreciated by the subjects until the termination of the perturbation. The subjects were therefore required to use prior experience in order to scale their responses and cerebellar damaged patients were particularly deficient.
Another example of this function is illustrated by single cell recordings of Purkinje cell discharge in alert monkeys subjected to a series of predictable force-pulse perturbations while trying to maintain a stable hand position. Many Purkinje cells in the anterior lobe have proprioceptive or cutaneous receptive fields on the hand, and their activity is strongly modulated during the grasping and holding movements of the hand as well as to perturbation of the hand position. Figure 6 illustrates the average discharge from 5-trial blocks during a pre-perturbation control period (A), the first five perturbed trials (B) and five trials after adaptation to the 100 ms downward force-pulse (C). The reflex responses appeared immediately upon the first perturbation (B) whereas the anticipatory discharge emerged progressively with repetition. The anticipatory discharge and preparatory increase in grip force preceding the perturbation were visible in Fig. 6B even during the first 5 trials. However, both the anticipatory cellular discharge and the grip force increase commenced earlier after repeated perturbations. In addition, the perturbation produced a smaller change in position after 10 trials (6C) and the reflex response, which probably functioned as an error signal, decreased as the adaptive responses became more efficient. During extinction, the reverse was true. The reflex response ceased immediately once the perturbation had been withdrawn (6D) whereas the anticipatory activity diminished progressively for many trials and had not completely disappeared after 35 extinction trials (6E). The anticipatory activity shown in Figure 6 clearly paralleled the preparatory EMG activity, but the relation between Purkinje cell discharge and stiffness of the wrist and fingers joints is admittedly moot in this example. However, increased stiffness was the primary objective of the task since it allowed the animal to compensate for the perturbation and obtain its reward. What does the cerebellum learn ?
It is suggested the cerebellum learns by forming and storing associated muscle activation patterns for the time-varying control of limb or joint stiffness (i.e. muscle strategies) which contribute to movement efficiency and postural stability. A review of the evidence supporting a cerebellar involvement in the formation and control of muscles synergies was recently presented by Thach et al (1992, 1993) and will therefore not be repeated except to reiterate the potential importance of the long parallel fiber system in establishing facilitatory associative connections between different mediolateral regions of the cerebellum which control muscle groups of different parts of the body. Similarly, evidence that the cerebellum associates teleceptive, particularly visual, information as conditioned stimuli for the sequential organization of movement as been reviewed recently by Stein and Glickstein (1992). The arguments from both these reviews appear to be compatible with the notion that the cerebellum plays an important role in learning muscle synergies.
However, the second part of the thesis - that the optimal time- varying modulation of joint stiffness described above is controlled in part by the cerebellum - requires further justification. First of all, it is important to stress that this hypothesis would include the cerebellar contribution to segmental reflexes causing changes in the stiffness of individual muscles. Moreover, it is the reflex pathways which provide the proprioceptive feedback necessary to developing an anticipatory strategy as a more efficient means to control multi- articular limbs with visco-elastic muscles. The cerebellum hypothesized to provide the muscle co-activation strategies for optimizing joint or limb stiffness values to particular movements or postures. The degree of reciprocal inhibition of antagonist muscles could be increased or decreased by greater or lesser Purkinje cell activity. It is well known that functionally related microzones of Purkinje cells impinge on nuclear cells which excite the motoneurons of functionally agonist muscles over the long descending motor pathways (Andersson and Oscarsson 1978, Ito 1984). Increasing Purkinje cell inhibition of tonic nuclear excitation to the descending motor pathways could decrease motoneuron excitability through the known segmental interneuronal circuits to provide reciprocal relaxation of antagonist muscles. Basket cell inhibition of "off-beam" Purkinje cells (Eccles et al 1967) could accomplish this function. During agonist-antagonist co-contraction the "on-beam" Purkinje cells would also be inhibited, and thus initiating a chain of disinhibition culminating in co-contraction. Similar, but more mathematical models incorporating these features, have been described recently by Gomi and Kawato (1992), Houk and Barto (1992) and Kawato and Gomi (1992).
This hypothesized time-varying control of limb or joint stiffness has two additional implications. First, an important function of the cerebellum would be to provide an essential postural stabilization by appropriately anticipating the required dynamics of incipient movements. Second, the cerebellum could learn to use available teleceptive and proprioceptive stimuli as conditioned triggering cues (Stein and Glickstein 1992), developing the necessary feedforward commands needed to control the mechanical impedance of multi-joint limbs (Kawato and Gomi 1992). Limb or joint stiffness must be optimized in a time-varying, moment-to-moment manner in order to achieve smooth coordinated movements and any failure to achieve adequate stiffness will result in ataxia. How the cerebellum might control joint stiffness
The inhibitory action of Purkinje cells and therefore the entire output of the cerebellar cortex on deep cerebellar nuclei is an important element of cerebellar physiology (Ito & Yoshida 1966; Ito et al. 1966; Ito et al. 1968). Furthermore, with the significant exception of the nucleo-olivary neurons (Nelson et Mugnaini 1989), the entire cerebellar nuclear outflow exerts a tonic excitatory action on descending brain stem motor pathways and the ascending thalamocortical system (Massion 1973). Although some earlier studies of electrical stimulation of the interpositus nuclei had suggested a preferential action on flexor limb muscles, a more recent study in awake monkeys found that low intensity stimulation from a single point in the dentate nucleus could evoke responses in multiple muscles in both fore and hindlimbs which were thought to represent muscle synergies (Rispal-Padel et al. 1982). Although not commented upon by the authors, co-contraction of agonist-antagonist muscles are also clearly evident in their illustrative EMGs (Rispal-Padel et al. 1982). In contrast, stimulation of the cerebellar cortex inhibits nuclear cell activity and produces a disfacilitation of spinal motoneurons (Llinas 1964). However, the effect of cerebellar cortical or nuclear stimulation on joint or limb stiffness has yet to be determined.
Some years ago it was suggested that Purkinje cells might function like supraspinal Ia inhibitory interneurons (Smith 1981). By inhibiting deep cerebellar nuclear cells, groups of Purkinje cells (e.g. microzones) could evoke a cascade of effects culminating in the disfacilitation of motoneuron pools resulting in antagonist muscle relaxation. It is further speculated that the Purkinje cells themselves must be inhibited during the voluntary co-contraction of agonist- antagonist muscles. According to the sequence of actions proposed schematically in Figure 7, two populations of Purkinje cells acting together would be needed to execute the reciprocal switching of excitation from one agonist group to another, or alternatively, to allow agonists and antagonists to co-contract depending on the desired goal of the task. Nevertheless, Purkinje cells respond to a much greater variety of afferents and it would be overly simplistic to consider cerebellar Purkinje cells as merely ectopic spinal Ia inhibitory interneurons.
Measuring stiffness and testing the hypotheses
The speculation that the cerebellum controls the time-varying modulation of joint stiffness would be a more readily testable hypothesis were it not for the fact that stiffness is a difficult parameter to measure. To make matters worse, the force pulse perturbations that are used to cause changes in position are almost certain to evoke reflexes and compensatory strategies. That is, the act of measurement is disruptive to the on-going motor strategy. The application of either small pseudo-random perturbations during movement such as employed by Bennett et al (1992) or alternatively the application of tonic bias forces (Bennett, 1993a, 1993b) would seem to have the best chance of success. A more elaborate example of the application of tonic bias forces was explored by Lackner and DiZio (1994) who found subjects could adapt visually triggered pointing movements to compensate for coriolis force perturbations induced by constant velocity rotation. The compensation, and aftereffects of opposite sign, included both the straightening of movement trajectories as well as improved end-point accuracy and undoubtedly involved changes in the arm stiffness. This experiment also clearly demonstrates that detailed aspects of movement trajectories are revised on a moment-to-moment comparison between motor commands and proprioceptive feedback and supports the utility of time-varying joint stiffness control.
In contrast, the evidence from Mussa-Ivaldi et al (1985) and Flash and Mussa-Ivaldi (1990) casts some doubt as to the extent to which the nervous system can influence the limb stiffness fields to any great degree, because the brain and spinal cord cannot change the inherent mechanical properties of the limb. Consequently the nervous system must find alternate strategies such as changing the initial or starting posture of a limb, or the level of individual muscle stiffness, or regulating whole joint or limb stiffness through co-contraction and reciprocal inhibition. Although it is likely that all three strategies are used at various times, the fatiguing nature of agonist-antagonist co-contraction requires that it be brief (e.g. Clement and Rezetti 1985, Milner and Cloutier 1993) and demand less than maximal voluntary contractions (Tyler and Hutton 1986). However, the lesson from robotics would seem to suggest that even small changes in stiffness at critical moments can resolve difficult problems of intersegmental reaction torques, resonant frequencies, and contact instability.
If the technical problem of stiffness measurement can be satisfactorily resolved, then a number of experiments should be able to establish whether the cerebellum plays any role. The displacement of loads made unstable by supplying positive position or velocity feedback which will evoke voluntary co-contraction as a compensatory strategy offers one promising approach (DeSerres and Milner 1991; Milner and Cloutier 1993), and the addition of tonic bias forces (Bennett 1993a, 1993b, Lackner and DiZio 1994) offers another. Recording single Purkinje cell activity during the displacement of stable and unstable loads should be adequate to demonstrate differences related to changes in stiffness. Increasing movement velocity should also increase stiffness as well as increasing the frequency of rapid alternating movements. Alternatively, patients with cerebellar damage or animals subjected to reversible cerebellar inactivation should show deficits in stiffness regulation.
In an earlier target article on cerebellar function, Bloedel (1992) suggested that, because of its homogeneous structure, the cerebellar cortex should perform a unitary neuronal operation applicable to the entire musculature. The hypothesis that the cerebellum implements real time muscle control strategies over joint and limb stiffness would appear to satisfy at least this one particular requirement.
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The research conducted by the author was supported by a grant from the Medical Research Council of Canada to the Groupe de recherche en sciences neurologiques of the Universite de Montreal. I am grateful for the honest criticisms of H.A. Buchtel, T. Drew, J.F. Kalaska, T.E. Milner and Stephen Scott as well as comments from several helpful BBS reviewers.
Figure legends
[Note: Figures avaiable only in hard copy version]
Figure 6
Acquisition and extinction of an anticipatory response in a Purkinje cell associated with a predictable force-pulse perturbation applied to the hand during position stabilization. Both the behavior and the associated discharge pattern change gradually during the acquisition and extinction of the anticipatory response. From Dugas & Smith (1992).
Figure 7
Two populations of Purkinje cells acting together upon agonist- antagonist muscle groups could facilitate either reciprocal inhibition or antagonist co-contraction depending on the command to move originating outside the cerebellum