Control of simple arm movements in elderly humans

Neurobiologyof Aging. Vol. 10, pp. 149-157. ©Pergamon Press plc. 1989. Printed in the U.S.A.

0197-4580/89 $3.00 + .00

Control of Simple Arm Movements in Elderly Humans W. G. D A R L I N G , I j. D. C O O K E A N D S. H. B R O W N 2

Department of Physiology, University of Western Ontario, London, Ontario, Canada R e c e i v e d 16 February 1988; A c c e p t e d 12 S e p t e m b e r 1988

DARLING, W. G., J. D. COOKE AND S. H. BROWN. Control of simple arm movements in elderly humans. NEUROBIOL AGING 10(2) 149-157, 1989.- Eight elderly subjects (aged 68-95 years) and 6 young adults (aged 21-24 years) performed elbow flexion and extension movements in a visual step-tracking paradigm. Movement amplitudes ranging from 10°-80° were made under two instructions: "move at own speed" and "move fast and accurate," In a second experiment, 5 elderly subjects practiced 30° movements for a total of 180 flexion and 180 extension movements under the instruction to increase movement speed, while maintaining accuracy, during practice. Movement trajectories became more variable as both movement amplitude and speed increased. Trajectory variability was greater in the elderly subjects for both the acceleratory and deceleratory phases of movements. This was due primarily to a greater rate of increase in trajectory variability during the acceleration phase in the elderly. With practice, elderly subjects could substantially reduce trajectory variability with little change in movement speed. The agonist burst initiating movements was qualitatively normal in the elderly subjects. However, there was considerable tonic cocontraction of agonist and antagonist muscles prior to and during movement. Phasic antagonist EMG activity was obviously abnormal in many elderly subjects. There was often no clear antagonist burst associated with deceleration of the movements or, if present, it was timed inappropriately early. With practice, combined agonist-antagonist EMG variability decreased. A clear antagonist burst also developed during practice in most elderly subjects, but its inappropriate timing remained in all but one subject. The results show that movement trajectories are less accurately controlled in the elderly. This greater movement variability may result from: 1) changes in motor neuron population and motor unit properties with aging and the associated effects on muscle force output and joint torques and 2) abnormal control of phasic and tonic antagonist muscle activity. The ability to improve performance with practice, however, is clearly not lost in the elderly. Aging

Movements

EMGs

Learning

Practice

STUDIES of the relations between movement speed and movement accuracy have shown that elderly subjects have longer movement times (decreased movement speed) at all required accuracies (target widths) (15,16). That is, the elderly can make movements with the same terminal accuracy as the young, but to do so must decrease their movement speed. Conversely, for the same combination of speed and amplitude, their terminal accuracy is less, i.e., the end point of movements is more variable compared to young subjects. These changes in movement with age may be due to age-related changes in muscle. Nelson et al. (13) have observed an increased variability in motor unit discharge rate during submaximal isometric muscle contractions due, possibly, to substitution of larger motor units for smaller ones normally active at low tensions. Such substitution of large motor units for smaller ones at low tension presumably occurs due to an overall loss of muscle fibers with age (11). Greater variability in motor unit discharge rate could result in greater variability in muscle tension output during contraction and thus an increased variability in movement end point. Reductions in muscle output variability could be achieved by reducing the strength of muscle contractions. This would reduce both movement speed and the variability of movement end point.

Any such increases in the variability of muscular tension output should be reflected not only in increased variability at the end of movements but indeed throughout the movements. In the present study we have examined the variability throughout the course of movements made by elderly subjects. Following on previous work with young subjects (5) we studied the variability in the relationship between velocity and position (phase plane trajectory) throughout movement. By using such a method, movement to movement variability in the actual trajectory is measured rather than simply at movement endpoint. Our previous study showed that trajectory variability increases with movement speed and amplitude and decreases with practice. A recent study on elderly subjects (4) indicated increased variability of a number of kinematic parameters of movement in the elderly (movement duration, peak velocity, etc.). The primary purpose of the present investigation was to compare muscle EMG patterns and trajectory variability of movements made by elderly subjects with those of young adults. Since preliminary experiments indicated gross changes in movement-related EMG activity in the elderly, we also studied the effects of practice in elderly subjects to determine whether any age-related changes could be reversed by extended practice.

~Present address: Department of Exercise Science, El01 Field House, University of Iowa, Iowa City, IA, 52242. 2present address: Neurologishe Klinik, University of Dusseldorf, Dusseldorf, Federal Republic of Germany.

149

150

DARLING, COOKE AND BROWN r

t0 °

j!i

i~

[3

•/

iO o

i

i

30° t i

50°

1k

i

/

70 2OO

0

2OO

aoo

FIG. 1. Movement trajectories and EMGs for movements of different amplitude. Shown are averaged phase plane trajectories (left side) and the associated averaged EMGs (right side) for extension movements made by a control subject (A) and an elderly subject (B). Superimposed on the trajectories are ellipses which represent variability in the trajectories at 10 msec intervals. The vertical lines superimposed on the EMG records are 2 s.d.s, in length to indicate variability in EMG amplitude at 20 msec intervals during the movements. The EMGs were lowpass filtered (10 Hz, 0 phase lag) and aligned to acceleration onset prior to averaging. The dashed line indicates acceleration onset.

METHOD

Subjects Nine elderly subjects (aged 68-95 years) and 6 young adults (aged 21-24 years) served as subjects for these experiments. All subjects reported they had no prior history of motor system disorders.

Task The subjects performed movements in a visual step-tracking paradigm. Each subject was seated comfortably and grasped a vertical rod attached to a manipulandum which rotated in the horizontal plane about a vertical axis. The subject's elbow was placed beneath the pivot point of the manipulandum and their arm was supported just distal to this point. Subjects were required to make forearm movements to a visual target displayed as a vertical bar (4°-5 ° in width in terms of elbow position) on an oscilloscope placed about 0.5 m in front of the subject at eye level. Manipulandum position derived from a precision potentiometer was displayed as a vertical line on the oscilloscope. The display was quite bright; none of the elderly subjects reported or exhibited problems in perception of the visual display. The targets were not mechanically detectable or bounded by mechanical stops. Movements were thus self terminated rather than stopped by striking a surface as in paradigms in which movement endpoint variability has been studied previously in elderly subjects (15,16)

Experimental Paradigm In one set of experiments, 8 elderly subjects and 6 young adults performed movements of 10° through 80 ° amplitude (10 ° increments) under two different instructions used to vary movement speed. The two instructions were: 1) make the movements at the

subject's own speed and 2) make the movements fast and accurately. It should be noted that these instructions related only to movement speed. Subjects were not asked to respond as quickly as possible to the target movements as in a reaction time paradigm. Subjects were also instructed to make the movements smoothly into the target and to avoid overshoots and terminal oscillations. Subjects made several practice movements prior to recording 10 flexion and 10 extension movements for each movement amplitude and instruction, resulting in a total of 160 flexion and 160 extension movements recorded from each subject. In a second set of experiments, 5 elderly subjects (4 who participated in the previous experiment, 1 who had not) practiced 30 ° movements for a total of 180 flexion and 180 extension movements. The instruction was to make movements accurately and to attempt to increase movement speed, while maintaining accuracy during practice.

Data Recording Primary data recorded were the angular position and velocity of the manipulandum and surface EMGs from biceps and triceps (lateral head) brachii muscles. Handle position was obtained from a precision potentiometer and angular velocity from the back EMF induced in small linear DC torque motor by the handle movements. EMGs were recorded from disk electrodes, 0.8 cm in diameter, placed about 3 cm apart over the bellies of the muscles. Raw EMGs were filtered (10 to 1000 Hz bandpass) and rectified prior to digitizing. All data were digitized online at a rate of 500 Hz.

Data Analysis Kinematic data were smoothed by digital filtering (10 Hz Butterworth low pass filter with zero phase lag) prior to analysis,

VARIABILITY OF MOVEMENTS IN THE ELDERLY

A 120 60

I ~r=~ r=95

•

),~, c

~C ~i 0 120

40

B

,20

I

60 S

~ "/

151

A

l

..1

!

60

D 120

40

80 I

>g

o

I li.--' 0

I =~-'r- 88

~

i

r 40

-.75 80

,0

D~.c

o

,;

8b

1

#60 .

4O

I

I I /'r=B3 320

-

'11 80

/

|,

_r=.95

,1,) -.,,

=i 9

B

32°r

,60 O~

,

40

~..~.!-,=.~ 80

.SI O0

40

° 80

Movement Arn~itude (°)

Movement An" ~litude (°)

FIG. 2. Acceleration phase variability as a function of movement amplitude. The plotted points are mean values of trajectory variability during acceleration for all elderly (open circles) and control (filled circles) subjects. The top graphs (A and B) are for "fast and accurate" movements while the bottom graphs (C and D) are for "own speed movements." Data for extension movements are shown in A and C (left side) and for flexions in B and D (right side). Error bars are 1 S.E.M.

FIG. 3. Deceleration phase variability as a function of movement amplitude. The plotted points are mean values of trajectory variability for all elderly (open circles) and control (filled circles) subjects. As in Fig. 2, data for extension movements are in A and C and for flexions in B and D. Graphs A and B show data for "fast and accurate" movements. Data for "own speed" movements are shown in C and D. Error bars are 1 S.E.M.

Movements were split into acceleratory and deceleratory phases using an arbitrary acceleration threshold as described previously (5). In the present study the threshold used varied from 80120°/sec 2. Lower acceleration thresholds than those used previously (3) were necessary for analysis of " o w n speed" movements by some elderly and control subjects. This technique limited temporal analysis to the first " m o v e m e n t " toward the target. This is important because some movements made by elderly subjects were discontinuous (1). Thus the movements were made in a jerky manner as a series of 2 or 3 submovements rather than a single movement into the target. A few elderly subjects made a high proportion of their movements in this way for some movement amplitudes. Data from such movement amplitudes were excluded from the present analysis because control of such movements clearly differs from that for continuous movements in which there is a single smooth movement to the target. Trajectory variability was calculated as the average area of ellipses with radii equal to ---1 s.d. in position and velocity calculated at 10 msec intervals throughout the averaged movement (Figs. 1 and 3). Movement trajectories were aligned to the start of acceleration and to a common start position prior to averaging. Variability in movement start positions was typically very low (0.1°-0.4 °) and measurement of variability as described therefore depends on variability in movement-to-movement dynamics. Movements were not scaled in terms of time, amplitude or velocity. Thus the technique described provides a measure of movementto-movement variability taking into account variability in movement amplitude, velocity and timing of the different movement phases. Combined agonist-antagonist EMG variability, hereafter termed EMG variability was determined. This combined variability represents variation in the combined actions of the opposing muscles in determining movement trajectory (6). The combined measure was used because previous work suggested that the variations in kinematics arise from the combined actions of agonist and antagonist muscles (6,7). EMG variability was calculated as

the average area of ellipses with radii equal to 1 s.d. in agonist and antagonist EMG amplitude at 10 msec intervals from 100 msec prior to acceleration onset through the end of deceleration (6). Agonist and antagonist EMGs were aligned to acceleration onset prior to averaging. EMG variability was measured from 100 msec prior to movement onset because the first agonist burst and the premovement antagonist silence begin 50-100 msec prior to movement onset.

Statistical Analyses Data were analyzed for statistical significance using linear regression, correlation and analysis of variance (ANOVA) techniques. Practice effects in elderly subjects were analyzed using a two-way repeated ANOVA [practice by movement type (extension/ flexion)]. Comparisons of elderly and control subjects on various measures were analyzed using a standard 4-way ANOVA [Group (elderly/control) by instruction ("own speed"/"fast and accurate") by movement type by instructed amplitude (10°-80°)]. RESULTS

Trajectory Variability A previous study (4) indicated that movements made by elderly subjects were more variable throughout their course than movements of the same amplitude made by younger subjects. In Fig. 1 are shown averaged movement trajectories from a young (A) and an elderly (B) subject. As described in the Method section, the superimposed ellipses indicate the variability in limb position (horizontal axis) and velocity (vertical axis) taken at 10 msec intervals throughout the movements. These movements were performed under the "fast and accurate" instruction. Trajectory variability, as indicted by the size of the ellipses, increased with increasing amplitude of the movements. At each movement amplitude trajectory variability was greater for the elderly subject. Note also that the mean peak velocity of movements made by the

152

DARLING, COOKE AND BROWN

TABLE 1

FLE x ONS

EXTENSIONS position I

REGRESSION

SLOPES FOR TRAJECTORY VARIABILITY MOVEMENT AMPLITUDE

VERSUS

velocity ~

......

position L ~ J r a (: j ~ s t

Slopes* "Own Speed" Control

Elderly

~

I I

"Fast and Accurate" Control

Elderly

0.89 0.91

1.45

1.67 2.25

2.60 2.54

ontag~'~s t

ant~or~isl I

I

i

I I

4 _~Z___

Acceleration phase Flexions Extensions

0.63 0.69

1.20 1.46

1.51

I I

Deceleration phase I

Flexions Extensions

1.74 1.80

2.49 2.60

Note: all slopes differed significantly from zero (p<0.05). *Slopes of least squares regression lines shown in Figs. 2 and 3. control subject (maximum vertical displacement of trajectory) were generally greater than those for the elderly subject in this particular case. Since faster movements are associated with greater trajectory variability (5) one would have expected greater trajectory variability in the movements made by the control subject. This difference in maximum movement speeds was not seen across all subjects and amplitudes however; mean peak velocities differed by an average of only 10% between control and elderly subjects. Mean trajectory variability from all subjects is shown as a function of movement amplitude in Figs. 2 and 3. The mean variability is the average area of the variability ellipses and thus a measure of the total variability of the movements. Data from movements made under both instructions [(A,B) "own speed": (C,D) "fast and accurate"] are shown. As the processes underlying acceleration and deceleration of movements differ (5,6), the variability of these two phases is shown separately. Figure 2 thus shows the mean area of the variability ellipses during acceleration and Fig. 3 during deceleration. Trajectory variability during acceleration increased with movement amplitude for both groups of subjects, the slopes of the best fit regression lines being greater than zero in all cases (Table 1). That is, the larger the amplitude of movement, the greater was the variability of the movement trajectory during the acceleration phase. As indicated by the greater slopes of the regression lines for elderly subjects (Table 1) this phase of movement was more variable in the elderly subjects. especially in the larger amplitude movements. Instruction had relatively little effect on acceleratory phase variability. The mean variability was somewhat greater for "fast and accurate" than for "own speed" movements [overall means: "'own speed" 40.4 deg2/sec, "fast and accurate" 46.8 deg2/sec; F(1,388) = 3.11, p =0.079]. The relatively small effect observed here may reflect the relatively small increase in peak velocity due to instruction, which averaged about 30-40%. Trajectory variability of the deceleratory phase for all subjects is shown in Fig. 3. Note the different scales for trajectory variability during deceleration in this figure compared to those for variability during acceleration in Fig. 2. In both groups, the trajectory was more variable during deceleration than during acceleration. Elderly subjects had greater trajectory variability during deceleration for flexion (B,D) and extension (A,C) movements of all amplitudes (Fig. 3). The increase in trajectory variability with greater movement speed ("fast and accurate" condition) was greater than for acceleration phase variability

I

I

I I I

i

I

i i I

r

0

400

800ms

[ ± /_ ]

0

i

1 i

. i___ • i ~ _ i ~ ~ O0 @ O 0 ms

FIG. 4. -Unpracticed" movements and associated EMGs. Single movement records of elbow position and velocity and the rectified EMGs of agonist and antagonist muscles are shown for the first 10 movements (5 flexions and 5 extensions) made by one elderly subject at the start of practice.

loverall means: "own speed" 107.5 deg2/sec, ""fast and accurate" 145.1 deg2/sec; F(1,388)=20.34, p<0.001]. Although less apparent in Fig. 3 than in Fig. 2, the slopes of the relationships between trajectory variability and movement amplitude during deceleration were also greater for elderly subjects (Table 1). Effects of Practice on Movements

Since elderly subjects had greater variability in movementto-movement trajectory control, we examined the effects of practice to determine whether the elderly could decrease movement variability with practice. Figure 4 shows records from the first 10 movements made by one elderly subject (5 flexions and 5 extensions). The first two movements made by this subject were discontinuous (1). That is, the movements were not made smoothly between the targets and the velocity profiles had two or more peaks. Subsequent movements were generally smoother, but there was still evidence of discontinuities in the velocity profiles even in

VARIABILITY OF MOVEMENTS IN THE ELDERLY

153

t 240

.~

24( •

Flexions

Extensions

x 2~

x

\"~-

-~.

-,L -~ ,2c

\

j./

/

2~

I I

(D -g

~

I i

~ : : : : : : : ~

I0o

I

200

[

I

0

i

l

I

I

200

I

l

i

I

30 Number of Movements 180

t

I

i

I

180

FIG. 6. Changes in trajectory variability with practice. The plotted points are the mean trajectory variability during acceleration (open circles) and deceleration (closed circles) for 5 subjects during practice (number of movements). Error bars are 1 S.E.M.

I

I

o 3O

I

I

I

400ms

FIG. 5. Effects of practice on variability of movement trajectories and related EMGs. On the left side are shown averaged movement trajectories with superimposed ellipses to show trajectory variability at 10 msec intervals. On the right side are the associated agonist and antagonist muscle EMGs with vertical lines superimposed to show variability in EMG magnitude at 20 msec intervals. Prior to averaging, the rectified EMGs and kinematic records were aligned to acceleration onset. The rectified EMGs were lowpass filtered (10 Hz, 0 phase lag) prior to averaging. The dashed line indicates acceleration onset. Data are for one subject.

the 5th extension movement (9 in Fig. 4). Indeed, in some elderly subjects as many as 20-30% of the first 30 movements were classified as discontinuous (means for all subjects--13% of flexions and 18% of extensions). In the more practiced movements (151-180) 10% or fewer of the movements were discontinuous (mean for all subjects--4% of flexions and 6% of extensions). Shown in Fig. 5 (left side) are averaged movement trajectories superimposed with ellipses to illustrate the movement to movement variability. Data are shown from movements 1-30, 61-90 and 121-150 during practice by an 89-year-old subject. Movementto-movement variability of the trajectories (as indicated by the size of the variability ellipses) decreased with practice. That is, movements were performed in a more stereotyped manner after practice. This was a consistent finding across all subjects. In Fig. 6 the mean trajectory variability during the acceleratory (open circles) and deceleratory (closed circles) phases of movements are shown as a function of practice. Trajectory variability was consistently greater during the deceleratory phase than during the acceleratory phase of the movements even after extended practice. Variability of the movements during both phases decreased with practice, most strikingly so for the variability during deceleration. The decreases in variability with practice were statistically significant for both the acceleratory, F(5,20)= 11.28, p<0.01, and deceleratory phases, F(5,20) = 23.62, p<0.01.

Point-to-Point Trajectory Variability Thus far we have described differences in the mean or average trajectory variability during the two movement phases. As we have described previously for younger subjects (5) and as can be seen in

the trajectories shown in Fig. 1, variability is not constant throughout movement. Rather the variability progressively develops, particularly during the acceleratory phase of movement. We analyzed the development of movement variability by examining how the size (area) of the variability ellipses changed throughout movement in order to determine whether variability increases continuously during the movement or if reductions in variability occur which would indicate corrections to ongoing movements. As we had observed in young adults (5), variability in movements by the elderly subjects rose rapidly during acceleration of the limb. This can be seen in Figs. 1 and 5 where the variability ellipses increase in size from the start of movement to about the point of maximum velocity. The increase in trajectory variability during acceleration indicates an imprecise or variable control of acceleration from movement to movement. The mean rate of increase of variability during acceleration was larger for elderly than young subjects across all movement amplitudes and both instructions [overall means: elderly 684.3 deg2/sec 2, control 419.4 deg2/sec2; F(1,388)= 18.33, p<0.001]. After maximum velocity was reached, the variability ellipses showed little change or an actual decrease in size (Figs. 1 and 5). This was seen in both young and elderly subjects. Across all amplitudes and instructions, there was no difference between the mean rates of change of trajectory variability during deceleration for elderly and control subjects [overall means: elderly 76.8 deg2/sec 2, control: 78.5 deg2/sec2; F(1,388) = 0.013, p = 0.911]. Previous work (5) indicated a negative correlation between the mean rates of change of trajectory variability during acceleration and deceleration. This was also found in the present study for both young and old subjects (Table 2). Strong negative correlations were observed between the mean rates of change of variability during limb acceleration and deceleration across movements of different amplitudes and speeds for most subjects. Such a finding indicates that most of the trajectory variability develops during limb acceleration. During deceleration, variability is maintained about constant or decreases, indicating possible corrections to the limb's trajectory during movement.

Symmetry of Movement In a previous study (4) it was shown that elderly subjects exhibited more asymmetric movement profiles than young adults; elderly subjects spent a greater proportion of the movement time in deceleration than in acceleration of the limb, particularly in small amplitude movements. Thus, ratios of acceleration duration to

154

DARLING, COOKE AND BROWN

TABLE 2 CORRELATIONSOF MEANRATESOF CHANGEOF TRAJECTORY VARIABILITYDURINGTHE ACCELERATORYAND DECELERATORY PHASES OF MOVEMENTS

TABLE 3 CORRELATIONSOF EMG VARIABILITYWITHTRAJECTORY VARIABILITYOF MOVEMENTSOF DIFFERENTAMPLITUDES AND SPEEDS

Correlationst Subject

Flexions

CorrelationsExtensions

Subject

Elderly su~ects

Flexions

Extensions

Elderly su~ects

1

-,84*

-.80*

1

.22

.49*

2 3 4 5 6 7 8

-,62* ,83* ,75" -,89" -.86* -.62* -.96*

.72* .47* .85* -.50* .71" .23 -.78*

2 3 4 5 6 7 8

-.02 .82* .22 .67* .35 .30 ,72"

.03 .56* .47* .68* .49" .71" .53*

-.44*

.49*

10

-.89*

.86*

11 12 13 14

.74* -.50* -.98* -.99*

9 [0 11 12 13 14

Control su~ects 9

Control su~ects

-.72* -.36 -.98* -.43*

*Correlation significantly different from 0 (/9<0.05). +Linear correlation coefficients.

deceleration duration were typically smaller for elderly than for young subjects. This is also indicated in the averaged trajectory of the first 30 movements by an 89-year-old shown in Fig. 5. Although time is not shown explicitly in the phase plane trajectory, it is clear that a greater proportion of the movement was covered during deceleration than during acceleration. The asymmetry appeared to be somewhat reduced with practice by this subject. However, this finding was not confirmed in other subjects as there were, across all subjects, nonsignificant changes in the mean ratio of acceleration to deceleration duration comparing movements 1-30 with movements 151-180 [flexions, t(4)= - 1.56, p>0.1; extensions, t(4)= - 1.32, p>0.1; paired difference t-tests]. Although the overall symmetry of the movements was little altered by practice, variability in this measure of the movement time course decreased with practice. As was seen in Fig. 4, the temporal profile of the first movements made by the elderly subjects was often extremely variable. Movement-to-movement variability in the ratio of acceleration to deceleration duration was compared for movements 1-30 and 151-180. The variability of acceleration/deceleration duration ratios was reduced by practice for both flexion and extension movements [flexions, t(4)= - 2.23, p < 0 . 1 ; extensions, t(4) = - 3.57, p<0.025; paired difference t-tests].

Muscle Activity Patterns Averaged muscle activity patterns associated with "fast and accurate" movements are shown in Fig. 1. The young subject (A) made movements using the typical 2 or 3 burst pattern (2,9) of agonist-antagonist EMG bursts at each of the movement amplitudes shown. Movements were initiated by an initial agonist burst (AG1) starting just before movement onset (vertical dashed line)

.40 .33 .15 .08 .91" .83*

.18 .56* .26 -.03 .93* .20

*Correlation differs significantly from 0 (p<0.05). tLinear correlation coefficients.

and which acts to accelerate the limb. A second agonist burst (AG2) was sometimes observed but its function is currently controversial. This pattern of EMG activity was consistently observed for "fast and accurate" movements made by all of the young subjects. In Fig. 1B are shown averaged EMG records from analogous movements made by an elderly subject. Agl was consistently observed in the movements made by this subject and, indeed, in nearly all of the elderly subjects. Qualitatively, the AG1 burst appeared normal in terms of control over its amplitude and duration with changes in movement speed and amplitude. An antagonist burst (ANT 1), however, was clear only in the averages associated with the 10 and, perhaps, the 70 ° movements shown in Fig. lB. Examination of EMG data from single movement trials (e.g., Figs. 4 and 7) indicated that the ANTI burst was present only inconsistently and was often timed inappropriately. In many elderly subjects there was only a general increase in tonic antagonist activity such as occurred in the 30 ° and 50 ° movements by this subject. This increased tonic antagonist EMG was usually associated with increased tonic agonist EMG.

Effects of Practice on Muscle EMG Patterns Abnormal EMG activity was most pronounced in the first or unpracticed movements made by the elderly subjects. Figure 4 shows records of the first 10 movements made by one elderly subject. The first extension movement was initiated by a burst of activity in the agonist muscle. However, there was no clear burst of antagonist muscle activity in this movement. The first flexion movement (No. 2) was initiated with a very small agonist burst associated with a period of premovement antagonist silence. This was followed by an abnormally early antagonist burst which started at about movement onset and produced the observed discontinuity

VARIABILITY OF MOVEMENTS IN THE ELDERLY

position ~

,

A

155

TABLE 4

ajonist .

MULTIPLECORRELATIONCOEFFICIENTSFROM MULTIPLE REGRESSIONSOF EMG VARIABILITYON TRAJECTORYVARIABILITY, PEAK VELOCITYAND AMPLITUDEOF MOVEMENTS

velocity

Correlationst Subjects

Flexions

Extensions

Elderly su~ects

C

I I I

t~

I I

:

' 2(30

~

()

1

.85*

.93*

2 3 4 5 6 7 8

.56 .85* .46 .97* .86* .68* .81"

.20 .73* .64 .97* .88* .88* .79*

E

' 2 O 0 . 4.0 0.

. 6.0 0. ms

Control subjects

' 62 o '

b'

2

6o . 4.0 0 . .6 0.0 .ms

FIG. 7. Movements and associated EMGs after extended practice. On the left are plotted movement position and velocity records of 5 movements from within movements 151-180 during practice. These 5 movements have nearly identical peak velocities and amplitudes. On the right side are shown the associated agonist and antagonist muscle EMGs. The dashed lines indicate acceleration onset,

in the movement. In subsequent movements an agonist burst was usually present, although it varied considerably in magnitude. The antagonist burst was either absent, present but timed incorrectly, or apparently normal. Elderly subjects can, therefore, perform these simple movements with parts of the "normal" pattern of EMG activity even in initial, unpracticed movements. However, the pattern of muscle activity is highly variable in these initial movements. The pattern of agonist-antagonist muscle activity in the elderly remained quite variable even after extended practice. Figure 7 shows records of single movements and EMGs from 5 flexions of similar peak velocity and amplitude from within movements 151-180 made by a 73-year-old. In movement A there were no clear EMG bursts in either the agonist or antagonist muscle. In movements B - E there were clear antagonist EMG bursts but they were abnormally early for these movement speeds, near the time of movement initiation (dashed vertical line). In all of these practiced movements there were, however, clear reductions in antagonist activity beginning before movement which contributed to movement initiation and acceleration. Averaged EMG activities from movements 1-30, 61-90 and 121-150 during practice by an 89-year-old are shown on the right hand side of Fig. 5. An initial agonist burst was present at each level of practice. There was no clear antagonist burst in the unpracticed movements (movements 1-30), although there was a clear, but variable, increase in antagonist EMG activity after movement onset. With practice, an antagonist burst began to develop (movements 61-90) and was relatively distinct in the practiced movements (121-150). This development of an antagonist burst with practice also occurred in the other elderly subjects. In most of these subjects, however, the burst was timed abnormally early in the movement, resulting in considerable phasic

9 10 11 12 13 14

.84* .91" .83* .88* .94* .93*

.54 .75* .93* .62 .96* .85*

*Correlation differs from 0 (p<0.05). tCorrelation coefficients from multiple regressions of EMG variability on trajectory variability, mean peak velocity and mean amplitude of movements.

agonist-antagonist coactivation rather than the reciprocal phasic agonist-antagonist activation pattern usually seen in young subjects at these movement speeds.

Variability in Movement-Related EMG Patterns As just noted, movement-related EMG activity was both abnormal and variable in the elderly subjects. We examined EMG variability in relation to trajectory variability, movement amplitude and movement speed. In Fig. 1 are shown averaged movement trajectories and EMGs and their associated variabilities for movements of different amplitudes by a young (A) and an elderly subject (B). EMG variability did not depend simply on variability in movement trajectories. For example, 10 ° movements were lower in trajectory variability than larger amplitude movements. Yet for the young subject, EMG variability was greater for the small than the larger movement (note particularly the variability in the antagonist EMG). For the elderly subject, the 10° movements were associated with nearly the same EMG variability as the 30 ° and 50 ° movements which had much greater trajectory variability. Correlations of EMG variability with trajectory variability were generally weak in both young and elderly subjects (Table 3), indicating that trajectory variability does not depend simply on EMG variability. Multiple regression techniques indicated that variability in movement-related EMGs depends on movement amplitude as well as trajectory variability and movement velocity. In this analysis, data from " o w n speed" and "fast and accurate" movements were pooled. For most control and elderly subjects, high multiple correlations were observed (Table 4). Coefficients in the multiple regression equations were always positive for trajectory variability and peak velocity, but usually negative for movement amplitude as

156

DARLING, COOKE AND BROWN

expected from the data shown in Fig. 1. DISCUSSION

It is well established that elderly subjects can make movements with the same or greater terminal accuracy as young subjects, although in order to do so they must make the movements more slowly. The present study has shown that, although terminal accuracy may be unchanged, the variability of the path or trajectory of the movement to the end-point is greatly increased in the elderly. Elderly subjects have greater movement-to-movement variability in both the acceleratory and deceleratory phases of self-terminated arm movements. This difference between the young and the elderly becomes more marked with the larger movements. Associated with these variable movement trajectories were EMG patterns which differed from those commonly observed in young adults. Control of the antagonist muscle appears abnormal since common features included inconsistent antagonist EMG bursts and tonic agonist-antagonist cocontraction prior to and during the movements. Importantly, however, practice can result in decreased variability of movement trajectories and related EMG patterns in elderly subjects. Thus the ability to improve performance in motor tasks is not lost in old age. The issue of accuracy or variability in motor output has been the subject of considerable study since the work of Woodworth (18). Recent models attempting to explain movement variability have focussed on variability in the joint torques controlling movement, the so-called impulse-variability models (7, 12, 14). Variability in joint torques must arise from variability in the timing and magnitude of force output from agonist and antagonist muscles. Since the force developed by a muscle depends on its excitation in addition to length and velocity effects, variations in descending commands to motor neurons and/or neuronal excitability at spinal or higher levels could contribute to variability in muscle force output. The increased trajectory variability of movements made by elderly subjects appeared to result primarily from greater trajectory variability developed during acceleration of the limb. This greater acceleration phase variability must result from movement-tomovement variations in the agonist-antagonist EMGs contributing to movement initiation and acceleration. Although the initial agonist burst appeared qualitatively normal in elderly subjects, there was some inconsistency in terms of its presence in movements by elderly subjects (Figs. 4 and 7) which would contribute to movement variability. Variability in the magnitude of the AG 1 burst was not measured, it is possible that elderly subjects exhibit greater movement-to-movement variations in AG1 than young adults. Control of the antagonist, however, appeared markedly abnormal in the elderly (e.g., Figs. 4 and 7). In a simple model of the elbow joint, we have shown that torque produced by the antagonist muscle is important in decreasing the rate of rise in point-to-point trajectory variability which occurs during acceleration (7). The inconsistent presence and variable timing of the antagonist EMG burst in elderly subjects may, therefore, contribute considerably to the observed greater variability of movement trajectories in the elderly. That is, without an appropriately timed antagonist EMG burst, and its associated torque, trajectory variability would rise to high levels during acceleration. Since this acceleration phase variability carries over into deceleration, overall trajectory variability is greater in elderly subjects. It should also be noted that considerable tonic agonist-antagonist cocontraction prior to and during movement was observed in many elderly subjects. Associated with this cocontraction were clear reductions in antagonist muscle activity starting prior to movement onset (Figs. 1.4 and 7). This premovement antagonist silence (10) would contribute to limb acceleration by reducing elbow imped-

ance and decreasing antagonist muscle force. Variability in the timing and magnitude of this reduction in antagonist activity would therefore also contribute to trajectory variability of the acceleratory period of the movement. Greater variability in muscle force output with age may also result from neuronal changes at the spinal motor neuron level (8). With aging, there is a selective loss of high threshold motor neurons which innervate fast twitch muscle fibers (3). Although some of these denervated muscle fibers necrotize, others may be reinnervated by axons from low threshold motor neurons which normally innervate slow twitch fibers. As a result, there are generally fewer motor units with, possibly, more variable fiber composition in elderly subjects. Such changes in motor unit properties could result in greater variability in muscle force output for two reasons: 1) since there are more muscle fibers per motor unit, there is a greater increment in muscle force output when each additional motor unit is recruited (i.e., control of force output is graded less precisely) and 2) mixed motor units consisting of slow and fast twitch fibers would produce a temporally different twitch profile in comparison to twitch profiles of slow or fast twitch motor units. Also, as described in the Introduction, there is greater variability in motor unit discharge rates in elderly subjects which may also contribute to greater variability in muscle force output (13). Thus there are age related changes in muscle and motor neurons which may contribute to the greater variability in movement trajectories observed in elderly subjects. Why, as movement amplitude increases, does trajectory variability increase at a greater rate in the elderly in comparison to young adult subjects (Figs. 2, 3: Table 1)? Larger movement amplitudes for a given instruction are made with higher peak velocities and greater movement durations. Thus the magnitude of the joint torque impulse for acceleration increases with increasing movement amplitude. It is possible that production of larger joint torques over a longer period of time is more difficult for elderly subjects because it would require additional motor unit recruitment and increases in the firing rate and duration of firing of motor units. As just discussed, motor unit firing rate is more variable and motor unit properties are also different in elderly subjects. Variability in muscle force/joint torque output probably increases at a faster rate with increasing movement amplitude in elderly subjects for these reasons. Although trajectory variability, and its rate of increase, were larger during acceleration for elderly subjects, the rate of change of trajectory variability was decreased during deceleration and was the same for young and elderly subjects. The lower or negative rate of change of variability during deceleration suggests that corrections occur during movement to reduce overall trajectory variability. It is apparent from the present findings that elderly subjects are able to reduce trajectory variability during deceleration as well as young adults. This is supported by the negative correlations observed between the rates of change of variability during acceleration and deceleration for both elderly and control subjects (Table 2). Thus, the greater the rate of increase in trajectory variability during acceleration, the smaller the rate of change (or greater negative rate of change) in variability during deceleration. This presumably occurs through linked agonistantagonist muscle EMG/torque patterns (6,7). In previous work we suggested that control of the antagonist was important incorrecting for variations in movement trajectory during acceleration induced by variations in the first agonist burst (5-7). This cannot be the case for elderly subjects since they show abnormal antagonist control. Thus the question arises: bow can elderly subjects decrease the rise in point-to-point variability which occurs during acceleration? Agonist-antagonist cocontraction increases joint stiffness and, probably, joint viscosity due to the effects of excitation of muscle on its stiffness and force-

VARIABILITY OF MOVEMENTS IN THE ELDERLY

157

velocity relation. The observed increase in tonic antagonist EMG activity and the associated agonist-antagonist cocontraction during movement in elderly subjects may alter joint mechanics (stiffness, viscosity) in a way that compensates for trajectory variability developed during acceleration. We have shown previously in a model of the forearm that joint mechanics acting alone can reduce trajectory variability during deceleration of the limb in the absence of a phasic tongue produced by antagonist muscle contraction (7). A significant finding in the present work was the improvement in movement performance with practice in elderly subjects. Substantial reductions in trajectory variability were observed and were accompanied by decreased variability in the associated agonist-antagonist EMGs. Although we reported increases in EMG variability during practice under similar conditions in young adult subjects, this was associated with increases in movement speed with practice (5). The elderly subjects showed little change in movement speed with practice. Thus the decreased EMG variability observed here concurred with previous findings in those young adult subjects who showed little change in movement speed with practice (5). These findings show that elderly subjects can control movements in a relatively consistent manner after practice. The decrease in movement trajectory variability with practice was also associated with a decrease in movement-to-movement variations in the ratio of acceleration duration to deceleration duration. Thus, the kinematic profile of the movements became more stereotypic during practice. This probably contributed to the observed reductions in trajectory variability with practice and is indicative of the more consistent agonist-antagonist EMG patterns in practiced movements. In conclusion, the results of the present work detail some important findings regarding changes in the motor control process

with age. Increases in variability of movements with age can be attributed to a number of factors which may affect the production of joint torques necessary for acceleration and deceleration of the limb. Control of the phasic activity of the antagonist muscles appears abnormal in the elderly in comparison to young adult subjects. Whether this reflects a deficiency in the planning of movements resulting in inappropriate commands to the antagonist muscles cannot be answered in the present study. Changes in the motor neuron population and firing rate variability and mechanical properties of motor units with age may also result in greater variability in muscle force output even if the motor commands to the agonist and antagonist muscles are not more variable in elderly subjects. It is important to recognize, however, that the elderly can substantially improve performance with practice. This can occur through reductions in movement-to-movement variability of the agonist-antagonist EMG patterns they use and/or by development of a more normal pattern. Since there are a multitude of EMG patterns which could be used to perform apparently similar movements in kinematic terms (Fig. 7), development of a normal agonist-antagonist EMG pattern is not a prerequisite for reduction in movement variability. This lends support to the idea that variability in nervous system output to individual muscles is compensated by linking the activity of agonist and antagonist muscles through afferent feedback or, perhaps, by efference copy mechanisms (6,7). Thus, abnormal control of individual muscles need not be a major limitation to movement performance in the elderly. ACKNOWLEDGEMENT This work was supported by the Physicians' Services Inc. of Ontario.

REFERENCES 1. Brooks, V. B.; Cooke, J. D.; Thomas, J. S. The continuity of movements. In: Stein, R. B.; Pearson, K. G.; Smith, R. S.; Redford, J. B., eds. Control of posture and locomotion. New York: Plenum Press; 1973:257-272. 2. Brown, S. H. C.; Cooke, J. D. Amplitude- and instruction-dependent modulation of movement-related electromyogram activity in humans. J. Physiol. 316:97-107; 1981. 3. Campbell, M. J.; McComas, A. J.; Petito, F. Physiological changes in ageing muscles. J. Neurol. Neurosurg. Psychiatry 36:174-182; 1973. 4. Cooke, J. D.; Brown, S. H.; Cunningham, D. A. Kinematics of arm movements in elderly humans. Neurobiol. Aging 10:159-165; 1989. 5. Darling, W. G.; Cooke, J. D. Changes in the variability of movement trajectories with practice. J. Motor Behav. 19:291-309; 1987. 6. Darling, W. G.; Cooke, J. D. Movement related EMGs become more variable during learning of fast accurate movements. J. Motor Behav. 19:311-331; 1987. 7. Darling, W. G.; Cooke, J. D. A linked muscular activation model for movement generation and control. J. Motor Behav. 19:333-354; 1987. 8. Grimby, G.; Saltin, B. The ageing muscle. Clin. Physiol. 3:209-218; 1983.

9. Hallet, M.; Shahani, B. T.; Young, R. R. EMG analysis of stereotyped voluntary movements in man. J. Neurol. Neurosurg. Psychiatry 38:1154-1162; 1975. 10. Hufschmidt, H. J.; Hufschmidt, T. Antagonist inhibition as the earliest sign of a sensory-motor reaction. Nature 174:607; 1954. 11. Lexell, J.; Henriksson-Larsen, K.; Winblad, B.; Sjostrom, M. Distribution of different fiber types in human skeletal muscles: effects of aging studied in whole muscle cross sections. Muscle Nerve 6: 588-595; 1983. 12. Meyer, D. E.; Smith, J. E. K.; Wright, C. D. Models for the speed and accuracy of aimed movements. Psychol. Rev. 89:445--482; 1982. 13. Nelson, R. M.; Soderberg, G. L.; Urbscheit, N. L. Alteration of motor-unit discharge characteristics in aged humans. Phys. Ther. 64:29-34; 1984. 14. Schmidt, R. A.; Zelaznik, H.; Hawkins, B.; Franks, J. S.; Quinn, J. T. Motor output variability: A theory for the accuracy of rapid motor acts. Psychol. Rev. 86:415--451; 1979. 15. Singleton, W. T. Age and performance timing on simple skills. In: Old age in the modem world. 3rd Congress of the International Association of Gerontologists, Edinburgh: Livingstone; 1955. 16. Welford, A. T.; Norris, A, H.; Shock, N. W. Speed and accuracy of movement and their changes with age. Acta Psychol. 30:3-15; 1969. 17. Woodworth, R. S. The accuracy of voluntary movement. New York: MacMillan; 1899:1-144; (Psychol. Monogr., Suppl. 13.)