The role of the cerebellum in the spatial tuning of goal-directed multi-joint movements in human is unknown. We analyzed the directional tuning of phasic EMG activities associated with upper limb reaching movements (12 targets) in the vertical plane in healthy subjects and in patients exhibiting cerebellar ataxia. Tuning of phasic EMG activities was investigated in seven muscles (brachioradialis, biceps, medial and long head of triceps, anterior and posterior deltoid, latissimus dorsi). We digitally compressed the EMG activities corresponding to slow reaches to the same targets into the time frame of the fast EMG traces. Estimates of gravity-related components were subtracted. Peaks of EMG activities in the resulting phasic traces were identified for each muscle and each target. Aberrant privileged directions of M Peak EMG (directions associated with the maximal peak of EMG amongst the 12 peaks of EMG activity in the sagittal plane) were found in all ataxic patients. Directional dominance, defined as the ratio of the M Peak EMG divided by the peak EMG in the opposite direction, was significantly higher in controls than in ataxic patients for one distal muscle (brachioradialis) and one proximal muscle (anterior deltoid). The spreading of EMG activities assessed by the global areas of the polar plots of phasic traces was broader in patients for the biceps and medial head of triceps. The distribution of densities of EMG activities (DDEMG) amongst the four quarters of the vertical plane, an index of the contrast in the intensities between quarters in polar plots, revealed increased values in control subjects for the brachioradialis, the biceps and the anterior deltoid as compared to ataxic patients. Representation of Net Vectors obtained from polar plots of peaks of EMG activities demonstrated an abnormal directional tuning in ataxic patients. In the majority of the cases, the Net Vector was outside the normal range for the following muscles: brachioradialis, biceps, anterior deltoid, posterior deltoid. This study reveals that cerebellar ataxia is associated with defective spatial properties of EMG activity during multiple joint movements. Privileged directions associated with M Peak EMG and Net Vectors are erroneous. We demonstrate that the cerebellum plays a determinant and unsuspected role in the spatial modulation of activation during speed-related action for reaching. [Neurol Res 2003; 25: 434-444]
Keywords: Movement; phasic spatial tuning; EMG; direction; cerebellum; ataxia
The physiological basis underlying reaching movements in human are compound. Elaborate equations used to compute the kinematics and kinetics of movements have been developed, taking into account inertial, centripetal, Coriolis and gravitational forces1. Still, there are many unsolved questions regarding the neural control of multi-joint reaching movements. One of the reasons is the mechanical complexity of the movement. Also, detailed studies of electromyographic (EMG) activation have been proposed. They have led to the unraveling of activation patterns. These patterns can be considered as the interface between the central commands and the biomechanics of the moving arm1,2. One of the methods used to investigate the temporal pattern of EMG activities is the decomposition of the EMG signals into a speed-related (phasic) and a gravity-related (tonic) component2. Interestingly, it has been found that:
1. A directional tuning of phasic EMG is associated with goal-directed multi-joint movements in the vertical plane.
2. The timing and intensity of bursts activity do not exhibit the same pattern1.
3. Neither the timing nor the intensity pattern correspond to the patterns of forces and joint torques required for straight hand paths3.
The study of the modulation of phasic EMG activity could represent a useful tool for the assessment of the directional control of movement, especially for proximal arm movements. Recently, the analysis of the tuning of phasic EMG activities in upper limbs has shown that the direction of the maximal peak of EMG activity (M Peak EMG) is a robust parameter to estimate the directional control of reaches in the sagittal plane4.
Several theories about cerebellar system operation have been suggested in the last 30 years5. Despite their seeming diversity, theories have converged significantly. However, a consensus has not been achieved. The hypothesis of Marr-Albus, the model of adjustable generator of muscle activation patterns, the representation of cerebellar operation by a matrix of gains, the hypothesis of the adaptative timer/adaptative linear filter, and the hypothesis of the internal dynamic models have allowed simulation studies of cerebellar operations6-8. These theoretical models have taken into account that the cerebellum is essential for the control of multijoint movements9. Indeed, when the cerebellum is lesioned, the performance error is more than the summed errors produced by single joints. Several investigators have provided evidence that incoordination of movement in cerebellar ataxia might originate from deficient compensation of dynamic interaction forces during movement10. Magnitudes of dynamic interaction and other forces are scaled to the square of movement speed. This contributes to explain the observation that cerebellar dysmetria is more prominent during fast movements. Cerebellar hypermetric movements are associated with smaller peak muscular torques and smaller rates of torque change at elbow and shoulder joints. Particularly, the patient's deficit in generating appropriate magnitudes of muscular force are prominent during two phases of the pointing movement:
1. Peak muscular forces are decreased during the initial phase of the task when the shoulder joint flexion generates an extensor effect upon the elbow joint10-11.
2. When attempting to terminate the movement, gravitational and dynamic interaction as well as inertial forces induce overshooting extension at the elbow joint.
The observation that sensory deafferentation results in deficits reminiscent of cerebellar dysfunction in terms of movement dynamics12 but affects different phases of the movement has prompted the idea that cerebellar pathways might be part of a three-stage control system made of anticipatory mechanisms, error correction and mechanisms of postural control13. In such a scheme, the cerebellum would contribute by holding an internal model of the biomechanic properties of the body which is continuously updated and recalibrated by afferent sensory information. How the internal model would take into account the constraints linked to the necessary modulation of muscular activation during directional variation of pointing movements has not been established so far.
In the present study, we analysed the spatial modulation of EMG activities in the vertical plane in cerebellar patients, taking into account gravity-related and speed-related components. We tested the hypothesis that cerebellar dysfunction is associated with an impairment of the directional modulation of phasic activation associated with multi-joint reaching.
MATERIALS AND METHODS
Informed consent was obtained following full explanation of the experimental procedure. Recordings of reaching movements on the right side were made in seven right-handed healthy subjects (mean age: 65; range from 39 to 77; two women) and in seven patients presenting a sporadic or familial degenerative cerebellar syndrome (mean age: 61; range from to 32 to 74; three women). Neurological examination showed ocular dysmetria, scanning speech, dysmetria in limbs and ataxic gait in all the patients. Muscle strength was normal and plantar reflexes were flexor. None of the patients had sensory loss in upper limbs. In all the cases, brain MRI showed atrophy of the cerebellum.
Targets were located in 12 directions in a sagittal plane14, at a distance of 25 cm from the central starting position (Target 1 : 0 degrees; target 2: 30 degrees; target 3: 60 degrees; target 4: 90 degrees; target 5: 120 degrees; target 6: 1 50 degrees; target 7: 180 degrees; target 8: 210 degrees; target 9: 240 degrees; target 10: 270 degrees; target 11: 300 degrees; target 12: 330 degrees). Each subject maintained initially the right upper arm vertically and the forearm horizontally (elbow angle: 90 degrees). Subjects were comfortably seated in a chair. The right upper limb was parallel to the midsagittal plane of the body. Subjects were asked to move as fast as possible from the central starting position to the target position after a 'go' signal. Three practice trials were followed by sets of 12 fast reaching movements for each direction of movement. A light infra-red emitting diode (LED) was affixed at the level of the index. The positioning of the LED was recorded by a Selspot II system (Selcom, Sweden) with two cameras. Sampling rate was 100 Hz; accuracy was
To isolate the phasic aspects of the EMG activity, a subtraction procedure was applied1. The rectified and averaged EMG activity related to slow movements (12 movements for each direction, recorded after three practice trials for each direction) was digitally compressed into the time frame of the fast EMG trace. Subsequently, the fast EMG trace and the slow EMG trace were subtracted. The result is called the phasic trace. For each target, the peak of EMG activity of the phasic trace was identified for each of the seven muscles. Polar plots of peak EMG activities for each muscle were obtained to analyse the spatial tuning. For each muscle, peak EMG intensities were expressed in % of the largest peak EMG in the sagittal plane (for each muscle, the maximal peak EMG among the 12 peaks of EMG activity in the sagittal plane is called M peak EMG). We defined the directional dominance as the ratio of the M Peak EMG divided by the Peak EMG in the opposite direction. The directional dominance is an indicator of the directional asymmetry4. We also computed the global areas of the polar plots, as well as the ratios of the areas corresponding to each quarter (quarter 1 : 0 to 90 degrees, quarter 2: 90 to 180 degrees, quarter 3: 180 to 270 degrees, quarter 4: 270 to 360 degrees) divided by the global areas. A five steps scale (level 1 : 0 to 14.99%; level 2: 1 5 to 29.99%; level 3: 30 to 44.99%; level 4: 45 to 59.99%; level 5: 60 to 75%) was used to estimate the distribution of densities of EMG activities for each quarter. A corresponding score of 1 to 5 was given according to the values of the ratios. We computed the following equation:
With DDEMG corresponding to the distribution of densities of EMG activities, Qmax corresponding to the score of the quarter with maximal intensity, Q^sub opp^ corresponding to the score of the quarter opposite to the quarter with maximal intensity, Q^sub adj1^ and Q^sub adj2^ corresponding to the scores of the two remaining quarters.
In addition, we computed the Net Vectors for each subject and each muscle. Net Vectors were obtained by calculating the sum of horizontal/vertical coordinates of each peak of EMG for each muscle.
The following statistical analysis was performed to compare the kinematic and EMG parameters in the control subjects and in the patients (SigmaStat Software, Jandel Scientific, Germany). The Student test was used to compare the amplitudes of both slow and fast reaching movements in the two groups. Level of significance was set at 0.05. The same procedure was applied to compare the path ratios. To assess the differences in the directional dominance, we applied the Student test for the brachioradialis, biceps, medial head of triceps, anterior deltoid, posterior deltoid and latissimus dorsi, and the Mann-Whitney Rank sum test for the long head of triceps. The Mann-Whitney rank sum test and the Student test were used to compare the areas of the polar plots between the two groups.
Figure 1 illustrates the hand paths in one healthy subject and one ataxic patient, for both fast and slow movements. Movement paths were characterized by slight curvatures for both tasks in the control subject. Curvatures were marked in the patient presenting a cerebellar disorder, who performed hypermetric movements (overshoot of the targets). Amplitudes of movements and path ratios for fast movements were significantly higher in patients than in controls (Table 7), as confirmed by the Student test (p = 0.012 and p = 0.005, respectively). The same observation was made for slow movements (p = 0.01 and p = 0.008 for the amplitudes of movements and the path ratios, respectively).
Figure 2 shows the spatial tuning of the phasic EMG activity in the sagittal plane in a healthy subject and in two ataxic patients. In the healthy subject, polar plots were characterized by a sharp tuning of EMG activities. For each of the seven muscles, the EMG activity was always greater in some directions (directional preference). For instance, EMG activity was greater in directions 1 (0 degrees) to 4 (90 degrees) for the AD, while the level of activity was low in the other directions. For each muscle, a privileged direction for the M Peak EMG was always identified (illustrated by arrows). These privileged directions were as follows: 0 degrees for the anterior deltoid, 90 degrees for the brachioradialis, 120 degrees for the biceps, 180 degrees for the long head of triceps/posterior deltoid, 270 degrees for the medial head of triceps. In cerebellar patients, tuning of EMG activities was characterized by multiple peaks (for instance in the brachioradialis and medial head of triceps) and errors in the selection of the privileged direction. The errors ranged from 30 to 120 degrees for the illustrated cases. In the first patient, the spatial tuning of the anterior deltoid was similar to the spatial tuning of the brachioradialis in the healthy subject. In the other patient, the directional tuning of the posterior deltoid was similar to the tuning found in the healthy subject for the medial head of triceps.
The directional dominance (ratio of M Peak EMG divided by the Peak of EMG in the opposite direction) was significantly higher in healthy subjects than in patients for the brachioradialis and the anterior deltoid (Figure 3), as confirmed by the Student test (p
The global areas of polar plots (Figure 4) were significantly higher in patients than in controls for two of the seven muscles: biceps (Mann-Whitney rank sum test, p
Figure 7 summarizes the privileged directions for the healthy subjects and the patients. With the exception of the latissimus dorsi which showed a variability of the privileged direction amongst control subjects, we found identical directions for the other muscles: 0 degrees for the anterior deltoid, 90 degrees for the brachioradialis, 120 degrees for the biceps, 180 degrees for the posterior deltoid and long head of triceps, 270 degrees for the medial head of triceps. Aberrant privileged directions were observed in patients. For the brachioradialis, the privileged direction varied from 120 to 210 degrees. No patient had an appropriate privileged direction for the biceps: one patient had a privileged direction at 0 degrees, three patients at 150 degrees, two patients at 180 degrees and one patient at 210 degrees. The privileged direction for the medial head of triceps ranged from 300 to 0 degrees, whereas it ranged from 210 to 30 degrees for the long head of triceps. Only one patient had a privileged direction of O degrees for the anterior deltoid. The others showed privileged directions varying from 30 degrees to 90 degrees. The values of the privileged directions were 180 degrees for one patient, 210 degrees for three patients and 270 degrees for three patients. The privileged direction for the latissimus dorsi were similar than in controls for four of the patients. In the others, the values were 240 degrees (two patients), 270 degrees (one patient).
Net Vectors obtained for each muscle in the control subjects are shown in Figure 8. Both the brachioradialis and the biceps were characterized by Net Vectors localized in the second quarter. The angle of the mean Net Vector was 118.9 degrees and 118.6 degrees for the brachioradialis and the biceps, respectively. The medial head of triceps was characterized by an angle for the mean Net Vector of 281.3 degrees. Three muscles had Net Vectors localized in the third quarter: the long head of triceps (mean angle: 210.5 degrees), the posterior deltoid (mean angle: 213.0 degrees) and the latissimus dorsi (mean angle: 197.6 degrees). The anterior deltoid was the only muscle with Net Vectors found in the first quarter (mean angle: 39.6 degrees). Figure 9 illustrates the Net Vectors in cerebellar patients. Scattering of vectors was larger than in controls: the range of angles was 47.2 to 227.9 degrees for the brachioradialis, 51.2 to 203.4 degrees for the biceps, 288.4 to 15.7 degrees for the medial head of triceps, 49.8 to 243.4 degrees for the long head of triceps, 20.6 to 118.2 degrees for the anterior deltoid, 166.0 to 295.3 degrees for the posterior deltoid, 165.7 to 273.5 degrees for the latissimus dorsi. Mean of Net Vectors felt outside the normal range (mean 2.5 + or - SDs of control values) for the following muscles: brachioradialis, biceps, anterior deltoid, latissimus dorsi. In terms of angles of vectors, only the brachioradialis showed angles of Net Vectors which were statistically different in patients than in controls (Mann-Whitney rank sum test: p = 0.026).
The main findings of this study can be summarized as follows:
1. Directional dominance, an index of directional asymmetry, is decreased in cerebellar patients for two critical muscles in the reaching task: the brachioradialis and the anterior deltoid.
2. In ataxic patients, the distribution of the densities of EMG activities is abnormal for both proximal and distal muscles.
3. The privileged direction associated with M Peak EMG is strongly distorted in cerebellar patients
4. Net Vectors are characterized by a broader scattering in ataxic patients.
From the physiological point of view, selection of appropriate spatio-temporal patterns of neuronal discharges is a fundamental operation for the central nervous system. This results in a suitable spatial tuning of activities, which is a general property of neurons in sensory and motor systems1-3. For reaching, the motor cortex has been studied the most comprehensively15-17. It is established that movement direction is encoded by populations of neurones in motor cortex. Individual neurones participate mainly in movements in a preferred direction, and to lesser degrees in a specified variety of directions. Schwartz and Moran18 have recorded the extracellular activity from single cells in motor and premotor cortex in monkeys tracing figure-eights on a monitor with the index finger. Population vectors isomorphically represented the shape of the drawn figures. It has even been possible to visualize with the cortical activity the hand's trajectory in monkeys tracing spirals on a planar surface19, population vectors being used to predict accurately the directions of movements. The time interval between the prediction and the corresponding movement varied linearly with the instantaneous radius of the curvature, while EMG activity and joint kinematics varied harmonically throughout the task with similar features than those of single cortical cells.
Reaching movements provide a useful model for the knowledge of motor coordination, since muscle activities acting at the shoulder must be controlled and sequenced with those at the elbow to move the hand in space20. The analysis of features of the initial agonist activity, onset time and magnitude at the shoulder and elbow in different spatial directions in combination with the study of the neural behavior of motor cortical cells has shown that variations in the discharge pattern of motor cortical cells before movements mirror those observed for muscles spanning the shoulder and elbow20. These results expand previous findings on the covariation of motor cortical discharge with the onset and magnitude of muscle activity during single-joint movements to multijoint movements where the spatio-temporal EMG patterns must be coordinated with accuracy21,22. In the present study, phasic EMG activities were sharply tuned in control subjects. We found that, although each muscle has a distinct pattern, the privileged direction associated with phasic activation is highly similar between subjects for each muscle, except for the latissimus dorsi. Earlier studies have shown rather uniform distributions of preferred directions for motor cortical cells during reaching23 . This is due to the position of the upper limbs20, which has direct consequences in terms of kinematic and kinetic features of movements.
For both proximal and distal muscles, tonic EMG activity is considered as a broadly tuned function of movement and force direction24,25. Flanders and Soechting26 have hypothesized that the spatial tuning of static EMG represents the convergence of multiple descending motor commands. Dynamic shoulder and elbow torques are nearly cosine tuned with movement direction1,3 and angles and torques are nearly cosine tuned with final hand position3. Therefore, given the preferred directions for the cortical neurons and the preferred directions for motoneurons, the transformation between the two could be modeled as a weighted mapping1. The results of phasic muscle activation suggests that cosine tuning is an incomplete description, and that multimodal tuning curves could correspond to the activity of different subpopulations of motor units preferentially contributing to the generation of forces in selected directions27,28. The reliability of the direction associated with M Peak EMG makes of this parameter an excellent candidate to assess the contributions of groups of motor units in the multimodal tuning curves.
In healthy subjects, the inertial resistance to movement is least in the direction perpendicular to the forearm1. This is explained by the fact that only the mass of the forearm resists acceleration in this direction (target 4: 90 degrees and target 10: 270 degrees). For the horizontal direction (target 1 : 0 degrees and target 7: 180 degrees), the inertia is greatest. This is called the anisotropy in the inertial resistance to movement. This anisotropy implies that movements in various directions have various force requirements, and that the directional tuning of a given muscle cannot be easily compared between movement and isometric conditions1. For movements in the sagittal plane, shifts in phasic EMG activation are not entirely dictated by the mechanical requirements. Shoulder torques computed from the hand paths show gradual shifts corresponding to the pattern of EMG, and suggesting that gradual variation of phasic activity represents a strong neuromuscular control strategy.
In primate, cerebellar dentate nuclei and interpositus nuclei have a function of postural fixation of proximal joints, modifying antigravity tone during initiation of movement29. The responses elicited by cerebellar stimulation involve mainly proximal muscles. Very few distal limb movements are seen. One of the main movements observed is arm flexion and shoulder elevation in the forelimb. Analysis of the motor responses has disclosed that the interpositus nucleus has a stronger function in postural mechanisms as compared to that of the dentate nucleus. Responses are thought to represent adjustments in flexor posture and are mediated by brainstem structures. Schultz et al.29 have stressed that control over both flexor posture and discrete distal movements is inherent in the initiation of voluntary movements. This key function is abnormal in our patients. All the muscles playing a role in flexion of upper limb segments displayed errors in the spatial modulation of activities, especially muscles acting at the proximal level. It is conceivable that the hypothesis that a fundamental function of the cerebellum would be to play a major role in stereotyped flexions of proximal parts of extremities is also valid in human.
Animal studies of cerebellar function have also shown that coordination of movement is not achieved just through a selection of Purkinje cells along beams of parallel fibers30. Investigations of the organizations of reaching and grasping movements using focal muscimol inactivations have disclosed that a prominent anteroposterior specialization was observed within the forelimb zone of the cerebellar interpositus nucleus30. Injections placed posteriorly produced deficits especially in the aiming of reach, hence the terminology of 'posterior reach zone'. By contrast, anterior injections induced mainly mistakes in the manipulation of objects ('anterior hand zone'). On the basis of these results and given the very large population of nuclear cells involved in voluntary movement, it has been suggested that coordination of proximal/distal musculature is obtained thanks to the adaptative influences on climbing fibers to Purkinje cells, by a nonspecific recruitment of anterior and posterior nuclear cells due to positive feedback in the limb premotor network, which is then shaped into an appropriate spatiotemporal pattern of discharge through the inhibitory input from Purkinje cells30. The effects of focal inactivation of the posterior reach zone on the directional tuning of EMG activities in the vertical plane have not been investigated. Such a study would increase our knowledge of the roles of this area on the spatio-temporal modulation of action in the upper limb.
The cerebellum generates a signal that varies with the direction of movement of the proximal arm during aimed reaching movements31. In monkeys trained to perform whole-arm reaching movements from a central starting position towards radially arranged targets, cerebellar neurons (Purkinje cells, unidentified cortical cells, interpositus neurons, dentate units) display significant changes in discharge during one or more of the following phases: reaction time, movement time, holding phase. The distribution of preferred directions of the population of cerebellar neurons cover all movement directions. When the preferred direction of each cell in the sample population is aligned, the mean direction-related activity of the cerebellar population forms a bellshaped tuning curve. Directional tuning is even supposed to be an elemental feature of Purkinje cells after learning9. In the present study, we found mistakes in the vector representation in the ataxic patients. These errors might represent the consequences of the mistakes induced by a wrong signal sent by cortico-nuclear cerebellar units to the motor-premotor network32,33. Interestingly, motor cortex neurons are more strongly related to active maintenance of various arm postures than cerebellar units and the motor cortex population has a higher percentage of single cells with tonic responses while the hand is held over different targets34. Cerebellar cortical neurons better reflect preparatory motor strategies formed from the anticipation of cutaneous and proprioceptive stimuli acquired by previous experience and, proportionally, more cerebellar cells are phasically related to the movement.
We did not address here the relationship between tuning of phasic EMG activities and the geometry of the segments in upper limb. For many motor cortical cells the discharges are strongly influenced by attributes of movement related to the geometry and mechanics of the arm, and not only by the spatial attributes of the trajectory of the hand36. The correlates with tuning of phasic EMG discharges deserve further investigations. The distribution of movement-related preferred directions differs strongly between cells receiving passive input predominantly from the shoulder or the elbow. The EMG activity of most prime movers at the shoulder and elbow is tuned in a pattern which may resemble the tuning observed in proximal arm-related motor cortical cells . In cerebellar patients, an abnormal tuning of proximal arm-related motor cortical cells might be the consequences of a distorted spatial modulation of speed-related action.
Supported by a grant from the Belgian National Research Foundation.
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M-U. Manto* and P. Bosse[dagger]
*Fonds National de la Recherche Scientifique, Universite Libre de Bruxelles, Bruxelles
[dagger]Universite du Travail, HEC, Charleroi, Belgium
Correspondence and reprint requests to: Mario-Ubaldo Manto, MD, Fonds National de la Recherche Scientifique, Universite Libre de Bruxelles, Hopital Erasme Neurologie, 808, Route de Lennik, 1070 Bruxelles, Belgium, [firstname.lastname@example.org] Accepted for publication December 2002.
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