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Journal of Gerontology: MEDICAL SCIENCES 2005, Vol. 60A, No. 2, 232–240 Copyright 2005 by The Gerontological Society of America Muscle Coordination During Rapid Force Production by Young and Older Adults Benjamin K. Barry, Stephan Riek, and Richard G. Carson Perception and Motor Systems Laboratory, School of Human Movement Studies, The University of Queensland, Brisbane, Australia. Background. Older adults typically exhibit dramatic reductions in the rate of force development and deficits in the execution of rapid coordinated movements. The purpose of the current study was to investigate the association between the reduced rate of force development exhibited by older adults and the ability to coordinate groups of muscles. Methods. The performance of a visually guided aiming task that required the generation of isometric torque about the elbow joint was compared in 10 young adults (age range, 19 to 29 years) and 10 older adults (age range, 65 to 80 years). Participants were required to exert isometric torque in flexion, extension, pronation, or supination, or in combinations of these directions, to reach a target in minimum time. Surface electromyograms were obtained from the biceps brachii, triceps brachii, brachioradialis, and flexor carpi radialis. Results. Older participants exhibited slower target acquisition times compared with young participants (p , .05), with the extent of the differences between the groups varying markedly between target locations. Conclusions. The impairment in performance, although partially attributable to a general decline in the ability to produce force rapidly, was also affected by the requirements for muscular coordination. At the neuromuscular level, differences between the young and the elderly were expressed most prominently in the bifunctional muscle biceps brachii and in certain temporal aspects of muscular coordination. T HE ability to rapidly develop force declines markedly in older age (1,2) and is closely associated with decrements in the physical capabilities of older adults (3–5). To design rehabilitative strategies intended to enhance the movement capabilities of older adults, the particular mechanisms that contribute to the deterioration of the ability to rapidly develop force must be identified. Beyond the reduction in rapid force development that arises from muscle atrophy and the slowing of muscle contractile properties (6,7), there also exists the potential for alterations in the neural control of muscles to contribute to the lower rate of force development that occurs with increasing age (8–10). The marked slowing of movement in older adults (11) has been linked to reductions in the ability to coordinate muscles effectively (8,10). Christou and Carlton (12) provided evidence that older adults experience particular difficulties in coordination during rapid actions. Older adults exhibited considerably greater inter-trial variability compared with young adults when they repeatedly performed a rapid discrete force trajectory matching task. However, the 2 groups were not distinguished when they produced slow continuous contractions (12). Darling and coworkers (9) reported that older adults varied more in the production of aiming trajectories, particularly when they were required to move rapidly. Less effective timing of agonist–antagonist muscle activation patterns accompanied these performance deficits. In addition, older adults are less accurate and less smooth when they make movements to targets using the elbow joint in conjunction with the shoulder joint, compared with conditions in which the elbow joint is moved alone (10). Progressively greater decreases in performance with an increasing number of joints indicate a coordination deficit 232 in older adults. These findings support the view that older adults exhibit deficiencies in muscle coordination that are exacerbated by increases in the speed and complexity of movement (10,13–15). To produce rapid, goal-directed movements, muscle activation patterns are initially specified in a feed-forward manner and subsequently modified on the basis of visual and proprioceptive feedback (16). Muscle activation patterns are currently believed to be formulated on the basis of an ‘‘internal model’’ that provides an abstract representation of the transformation between the command signal to the motor effectors and consequent movement trajectories (17,18). Necessarily, the ultimate output of an internal model is the specific motor commands to initiate the patterns of muscle activation that are suitable to accomplish a desired motor act (17,18). It is generally accepted that these motor commands do not specify the activity of muscles independently, but rather they control groups of muscles and motor units through a network of common neural inputs (19,20). Clearly, there is sufficient flexibility within these neural circuits to allow muscle activation patterns to be modulated to meet the demands imposed by specific movement tasks (21). At the same time, the possible combinations of muscle activation patterns are constrained by the structure and plasticity of these neural circuits. Degenerative changes in the aging neuromuscular system, such as a decrease in the number of corticospinal fibers (22); a decrease in intracortical inhibition (23); neuronal degradation in other higher nervous centers, such as the cerebellum and the basal ganglia (24–26); and the reduced number of motoneurons in the spinal cord (27) would be expected to limit the flexibility with which muscle coordination patterns are formulated and executed. Potentially this may impede the ability of older adults to coordinate muscles optimally when RAPID FORCE GENERATION BY OLDER ADULTS 233 affecting the elbow joint. The participants were all right handed according to their preferential use of that particular hand during sports (e.g., lawn bowls) and other daily activities. The University of Queensland Medical Research Ethics Committee approved all experimental procedures. Force–Torque Recordings All experimental tasks were performed using only the dominant limb with participants seated and grasping a manipulandum (Figure 1). The manipulandum was instrumented with a multiple-degree-of-freedom force–torque transducer (Delta; ATI Industrial Automation, Apex, NC). Force (flexion–extension, 0.25 N resolution) and torque about the long axis of the forearm (pronation–supination, 0.015 Nm resolution) were sampled at 1000 Hz at an analog-to-digital interface (AT-mio-16E-10; National Instruments, Austin, Texas) and the data stored on a personal computer. Labview (version 5.0; National Instruments) was used to write the custom experimental control and data acquisition routines. Subsequent to collection, flexion and extension force recordings were converted to torque data for all analyses. Figure 1. The experimental setup incorporates a computer display and a manipulandum instrumented with a multidimensional force–torque transducer. Participants were seated in an adjustable-height chair 65 cm from a computer display (display size, 42.5 cm) positioned at eye level. All experimental tasks were performed using only the dominant limb, which was placed in the pendent position with the elbow flexed at 908 and the forearm in a neutral position. The elbow joint was secured in a padded brace with a Velcro strap, and the hand grasped the manipulandum. Padded clamps were located above and below the hand to minimize the force required to grip the manipulandum. The outer edges of the screen display were scaled to 100% MVC in flexion, extension, pronation, and supination (top, bottom, left, and right screen edges, respectively). Targets were displayed at the appropriate percentage of these screen boundaries (i.e., 30% or 50%). The combination targets required that either 30% or 50% of the individual direction MVCs be generated simultaneously (e.g., 50% flexion MVC plus 50% supination MVC). they try to develop force rapidly, especially in circumstances that require the formation of novel patterns of muscle activation. Any deficits exhibited by older adults are therefore likely to be exacerbated by movements that impose greater demands on muscular coordination. The purpose of this experiment was to determine whether the deficiencies in the rapid development of force exhibited by older adults are contingent on inefficiencies in intermuscular coordination. Using the elbow joint as a model, the experimental task required young and older adults to produce isometric flexion, extension, pronation, or supination torques, in isolation or combination, to rapidly acquire visually displayed targets. The task assessed, therefore, the flexibility with which muscle synergies were composed and recomposed to meet the demands of a variety of movement tasks, each of which imposed unique coordination demands. We evaluated age-related performance decrements in terms of the formation of torque trajectories and the associated patterns of muscle activation. METHODS Participants From healthy populations, we recruited 10 older volunteers (9 men, 1 woman; mean age 6 SD, 71.7 6 4.7; age range, 65 to 80 years) and 10 young volunteers (6 men, 4 women; mean age, 22.7 6 2.8; age range, 19 to 29 years) who had no disorders Experimental Procedures Experimental sessions began with adjustment of the equipment dimensions for each participant and then a familiarization program. Participants practiced exerting torque against the manipulandum using only the elbow joint while maintaining wrist and shoulder posture. Once they had become comfortable with this, they performed some practice trials of the aiming task, after which the experimental tests were begun. First we assessed maximal voluntary contractions (MVCs) and then the visually guided aiming task. Maximal voluntary contractions.—Maximal voluntary contractions were obtained for isometric flexion, extension, pronation, and supination to determine separately for each participant the torque levels that would be used in the aiming task. After several practice attempts, the volunteers performed MVCs three times for flexion, extension, pronation, and supination. Successive attempts were separated by 2 to 3 minutes’ recovery (28). The maximum force achieved for the three attempts was taken to be the MVC. If, however, at least two of the attempts were not within 10% of this value, extra attempts were completed to ensure that a maximum had been achieved (28). Visual feedback of the torque produced was provided to participants via a bar scale display on the computer monitor. Visually guided aiming.—The aiming task required the generation of isometric torque about the elbow joint to acquire targets located in positions that corresponded to the application of flexion, extension, pronation, and supination torques, either in isolation or in combination (i.e., flexion and supination, flexion and pronation, extension and supination, extension and pronation). When the target was presented, the participants had to exert torque in the appropriate direction and to reach the target in minimum time. The location of the targets corresponded to isometric force levels that were either 30% or 50% of MVC. The 8 target positions were presented in pseudorandom order, with each target location presented twice in each of 8 blocks of 16 trials (for a total of 128 trials). 234 BARRY ET AL. Figure 2. Sample data are from the torque trajectories produced during the acquisition of a combined extension and supination target by a young adult and an older adult. Torque time-series data are included for the sample trials to depict the information contained in the trajectory descriptors. Dashed lines denote the movement onset and target acquisition. (No trajectory history was displayed during the aiming trials.) Additional analyses of the torque trajectory data required that the X axis (pronation/supination) and Y axis (flexion/extension) of the visually guided aiming torque recordings be combined to determine a resultant torque time series. The peak RTD was obtained from the differentiated time series, and the temporal location of this peak was expressed as a proportion of the target acquisition time and is referred to as the percentage time to peak RTD. To quantify the contribution of the peak RTD burst to the total target acquisition movement, the area under curve of the differentiated time series was calculated for the segment between zero crossings that contained the peak positive value of the time series. This was expressed as a proportion of the area under the curve for the velocity time series from movement onset to target acquisition (% peak RTD/total area). Effectively, this peak RTD burst corresponded to the primary ‘‘submovement’’ of the torque produced in acquiring a target. The advantage of quantifying its contribution to the total aiming movement in terms of the total change in torque, instead of the total movement duration, is that this particular measure also accounts for (by virtue of the normalization) the magnitude of adjustments in the rate of torque production that follow the primary submovement. A temporal index that describes the proportion of the total target acquisition time at which the primary submovement ended does not incorporate consideration of the magnitude of subsequent adjustments in torque, but rather only their duration. With reference to the sample data, it is clear for the young adult that the burst of contraction containing the peak RTD occupies most of the target acquisition period. In contrast, for the older adult, the initial burst only represented a small proportion of the trial length and many peaks and troughs occurred on the ‘‘velocity’’ trace. Trajectory error (in newton-meters) was defined as the RMS of the departure of the resultant trajectory from a straight line between the home position and the target. This measure indicated the extent to which torque was produced purely in the required direction. The number of discrete modifications to the torque trajectory was quantified as the instances in which a switch in the sign of the acceleration occurred (i.e., zero crossings of the acceleration time series). For the first 64 trials, the targets were defined at 30% MVC. In the second block of 64 trials, they were defined at 50% MVC. At the start of each trial, the computer screen displayed a yellow dot in the middle, corresponding to the zero torque (resting) position of the arm. When a cursor indicating the torque level currently generated by the participant fell within this ‘‘home zone,’’ the color of the dot changed from yellow to red. The participant had to maintain zero net torque at the start of every trial. After a random foreperiod (1 to 3 seconds), a target was presented, accompanied by an auditory cue (370 milliseconds, 1.2 kHz square wave). The target was also displayed as a yellow dot, which changed to red whenever the applied torque fell within a target zone (defined for all directions as 65% of the smallest of the MVCs for flexion, extension, pronation, or supination relative to the target force level [e.g., 65% supination torque]; the home zone was defined by the same criteria). Once the level of applied torque was maintained in the target zone for a continuous period of 0.1 second, a second auditory cue was generated to signify the end of a trial. Torque Data Processing and Analysis The torque time series data recorded in the visually guided aiming task were digitally low-pass filtered by using a second-order, dual-pass Butterworth filter with a 15 Hz cutoff frequency. Custom software (Labview) was used to identify the movement onset and target contact. Movement onset was defined as the point in time at which the torque in either direction exceeded the boundary of the home zone. Trials in which the target was not acquired within the designated period (10 s) or the starting torque was not within the required limits when the target was presented were discarded. Reaction time was defined as the elapsed time from target presentation to movement onset. Target acquisition time was calculated as the elapsed time from movement onset to the time when the target was first acquired, provided that contact with the target was maintained for the subsequent 100 milliseconds. Subsequent analyses (Figure 2) were completed using custom software written in Matlab (Mathworks, Natick, MA). Electromyographic Data After standard skin preparation procedures, miniature preamplified bipolar surface electrodes (stainless steel) were placed over the long head of the biceps brachii, the lateral head of triceps brachii, brachioradialis, and flexor carpi radialis. The electrodes (separation 13 mm) were positioned over the midbelly of each muscle. One self-adhesive gel electrode (Conmed, Utica, NY) was placed on the posterior aspect of the wrist as a common grounding electrode. The electromyographic (EMG) signals were amplified (2000 times) and band-pass filtered (30–500 Hz). These data were sampled at 1000 Hz and stored in the manner described previously. The EMG recordings for each muscle were full-wave RAPID FORCE GENERATION BY OLDER ADULTS 235 rectified and digitally low-pass filtered at 40 Hz (Butterworth dual pass). The root mean square (RMS) of the EMG recorded during the visually guided aiming task was calculated for the period between target presentation and acquisition. The values thus obtained were then expressed as a percentage of the maximum RMS recorded for that muscle during a corresponding MVC (e.g., the maximum RMS value obtained for the triceps during an extension MVC). Custom software (Labview) was used to identify distinct bursts of activity recorded from each muscle that occurred during the target acquisition movements. The primary burst detection algorithm identified burst onsets when the restinglevel EMG was exceeded by 2.5 standard deviations, and offsets when the EMG returned to below this level. Additional temporal and threshold criteria were also imposed to enhance the reliable detection of EMG bursts. Statistical Analyses Comparison of the young and older groups, for values obtained at both the 30% and 50% target force levels, were conducted based on simple main effects analysis of variance designs fage (between) 3 target (within)g. The main effect of age was determined across all target positions and within each target position. Because the preliminary analysis failed to reveal the presence of reliable age-related differences between the 30% and 50% MVC conditions, the values were combined for the purposes of the current analyses. Separate analyses of variance were conducted for each dependent measure. Effect sizes were calculated according to the method of Cohen (29). By convention, a small effect size is indicated by an f value of .1, a medium effect size by an f value of .25, and a large effect size by an f value of .4 (29). RESULTS Visually Guided Aiming Performance Reaction time was consistently slower for the older volunteers by an average of 28% (young adults: 402.6 milliseconds; older adults: 514.5 milliseconds; F(1,18) ¼ 7.45, p , .05, f ¼ .15) (Figure 3A). The difference in reaction time between young and older adults was very similar across the different target directions. Target acquisition times were longer overall for older volunteers, by an average of 79% (young adults, 791.7 milliseconds; older adults, 1417.5 milliseconds; F(1,18) ¼ 7.04, p , .05, f ¼ .15) (Figure 3B). The extent of the age-related difference varied markedly among the different target locations, ranging from essentially equivalent target acquisition times for combined extension and pronation (F(1,18) ¼ 0.01, p ¼ .942, f ¼ .01), to the marked differences observed for extension, supination, and extension plus supination. In the latter conditions, the target acquisition times recorded for the older adults were approximately 1.5 to nearly 2.5 times longer than those exhibited by the young adults. The peak rate of torque development (RTD) was also lower by 45% for the older volunteers across the 8 target Figure 3. (A) Reaction time (s), (B) target acquisition time (s), and (C) peak rate of torque development (newton-meters s1) are shown for young and older participants in the visually guided aiming task. *p , .05; ysmall effect size; z moderate effect size; §large effect size. Shaded regions indicate the 95% confidence intervals. Flex, flexion; flesup, flexion and supination; supn, supination; extsup, extension and supination; extd, extension; extpro, extension and pronation; pron, pronation; flepro, flexion and pronation. BARRY ET AL. 236 Table 1. Trajectory Descriptors for Young and Older Participants During the Visually Guided Aiming Task Flex Flesup Supn Extsup Extd Extpro Pron Flepro %ttpk_RTD Young Older 11.9 6 4.8 13.8 6 13.8 11.4 6 7.1 16.1 6 8.1 13.8 6 9.7 30.6 6 24.9*y 11.9 6 6.2 17.1 6 13.0 17.4 6 13.4 16.2 6 16.0 13.7 6 9.6 19.7 6 25.6 10.2 6 6.9 16.1 6 16.0 11.2 6 4.6 14.6 6 11.2 76.7 6 14.4 58.3 6 18.1*y 59.8 6 10.9 52.3 6 20.7 66.0 6 16.0 37.4 6 20.9*y 64.5 6 11.8 36.4 6 20.2*y 72.6 6 16.6 43.1 6 21.7*y 49.5 6 19.9 38.8 6 15.7 59.1 6 21.9 41.9 6 20.9 72.3 6 9.9 43.7 6 20.0*y 0.30 6 0.15 0.42 6 0.30 0.58 6 0.26 1.53 6 1.29*y 1.74 6 0.97 0.51 6 0.24*y 0.52 6 0.25 1.14 6 0.90*y 0.31 6 0.19 0.46 6 0.27 1.12 6 1.37 1.62 6 1.56 2.20 6 1.78 0.61 6 0.29*y 0.44 6 0.23 1.31 6 1.11*y 8.7 6 3.0 12.3 6 6.5* 12.7 6 4.5 21.4 6 21.7 7.7 6 5.1 22.3 6 20.0* 13.0 6 5.9 36.0 6 25.0*y 9.7 6 4.0 22.6 6 17.2*y 27.6 6 30.6 24.6 6 15.3 10 6 5.8 17.5 6 9.9*y 10.3 6 4.2 18.4 6 10.0*y pkRTD: area, % Young Older Traj Error, Nm Young Older No. submvts Young Older Mean 6 standard deviation for young (top) and (bottom) participants. The percentage of the target acquisition time to peak rate of torque development (RTD) (%ttpk_RTD), impulse in the peak RTD burst as a percentage of the total impulse (pkRTD: area), root mean square of the trajectory ‘error’ (Traj. Error), the number of discrete modifications to the torque trajectory or number of ‘sub-movements’ (No. submvts). *p , .05 young vs older adults. yEffect sizes 0.40. Flex ¼ flexion; Flesup ¼ flexion and supination; Supn ¼ supination; Extsup ¼ extension and supination; Extd ¼ extension; Extpro ¼ extension and supination; Pron ¼ pronation; Flepro ¼ flexion and pronation. locations (young adults, 155.4 Nm1; older adults, 85.7 Nm1; F(1,18) ¼ 5.35, p , .05, f ¼ .13) (Figure 3C). This difference was statistically significant for 4 of the 8 target locations: flexion (44%; F(1,18) ¼ 5.34, p , .05, f ¼ .37), extension (48%; F(1,18) ¼ 4.99, p , .05, f ¼.35), extension plus pronation (54%; F(1,18) ¼ 7.57, p , .05, f ¼ .44), and flexion plus pronation (51%; F(1,18) ¼8.37, p , .01, f¼.46); and it was expressed prominently for 3 of the remaining target positions: flexion plus supination (38%; F(1,18) ¼ 3.77, p ¼ .068, f ¼.31), pronation (46%; F(1,18) ¼ 3.49, p ¼ .078, f ¼.30), and extension plus supination (43%; F(1,18) ¼ 3.27, p ¼ .087, f ¼ .29). For movements directed to supination targets, however, the young and older adults did not differ appreciably (11%; F(1,18) ¼ 0.09, p ¼ .772, f ¼.05). In addition to the lower peak RTD exhibited by the older group, the peak RTD tended to occur later (Table 1). This trend was expressed across the 8 targets (young adults, 12.7%; older adults, 18%; F(1,18) ¼ 2.87, p ¼ .108, f ¼ .09), but only for the supination target was this difference statistically significant (F(1,18) ¼ 9.10, p , .01, f ¼ .48). The proportion of the total trial impulse achieved during the peak RTD burst was clearly lower for the older volunteers (young adults, 65.1%; older adults, 44%; F(1,18) ¼ 5.26, p , .01, f ¼ .22). The older adults also displayed a larger number of switches in the sign of the acceleration time series. The overall difference was such that approximately 75% more zero crossings were exhibited by the older volunteers (young adults, 12.5; older adults, 22, F(1,18) ¼ 6.15, p , .05, f ¼ .14) and we observed statistically significant differences for 6 of the 8 targets. The RMS of the trajectory error quantified the departure from a straight line trajectory toward the specified target. For flexion plus supination (F(1,18) ¼ 11.33, p , .01, f ¼ .53), extension plus supination (F(1,18) ¼ 18.89, p , .01, f ¼ .69), and flexion plus pronation (F(1,18) ¼ 22.48, p , .01, f ¼ .75), older adults exhibited greater trajectory deviations than did the young adults. These data indicate that older adults were typically less able than the young adults to coordinate the production of torque in 2 degrees of freedom. There was no overall age- related difference in trajectory error because the young group exhibited much larger trajectory deviations for the supination and pronation targets compared with the older group. Investigations conducted in our laboratory indicate that minimization of the trajectory error when acquiring targets in these particular directions does not necessarily enhance performance. Instead it may indicate that older adults adopt a more ‘‘conservative’’ strategy in these instances by focusing on torque production in the target axis only and avoiding the coordination of torque in both degrees of freedom. Electromyographic Variables The overall patterns of muscular activation were very similar between the young and older adults for the triceps brachii, brachioradialis, and flexor carpi radialis (Figure 4). This is apparent in the pattern of variation for each muscle in the normalized amplitude (RMS) of EMG across the 8 target locations. We observed statistically significant differences only for the biceps brachii between the two groups, whereby the older adults exhibited greater activation of this muscle for extension targets (young adults, 3.16%; older adults, 5.81%; F(1,18) ¼ 6.87, p , .05, f ¼ .41) and pronation targets (young adults, 2.24%; older adults, 4.86%; F(1,18) ¼ 7.62, p , .05, f ¼ .44). In contrast, for the combined flexion and supination target, the older group exhibited a tendency to activate biceps brachii to a lesser degree than did the young group (young adults, 51.8%; older adults, 34.6%; F(1,18) ¼ 4.24, p ¼ .054, f ¼ .33). The pattern of results for the normalized rate of burst onset (Figure 5) very closely resembled that of the normalized EMG RMS. For the biceps brachii, we observed a tendency for the older adults to exhibit faster onset rates during extension (F(1,18) ¼ 3.14, p ¼ .094, f ¼ .28) and pronation (F(1,18) ¼ 3.24, p ¼ .089, f ¼ .28) while producing a significantly slower onset rate during combined flexion and supination (F(1,18) ¼ 5.37, p , .05, f ¼ .37), and a tendency to also do so when pure flexion was required (F(1,18) ¼ 3.39, p ¼ .082, f ¼ .29). A clear difference in the muscle recruitment patterns adopted by the young and older adults was evident in the RAPID FORCE GENERATION BY OLDER ADULTS 237 Figure 4. Normalized RMS of EMG were recorded from (A) biceps brachii, (B) triceps brachii, (C) brachioradialis, and (D) flexor carpi radialis during the visually guided aiming task.*p , .05; ylarge effect size. Error bars display 95% confidence intervals. Flex ¼ flexion; Flesup ¼ flexion and supination; Supn ¼ supination; Extsup ¼ extension and supination; Extd ¼ extension; Extpro ¼ extension and supination; Pron ¼ pronation; Flepro ¼ flexion and pronation. timing of muscle burst onsets (Figure 6). Across all 8 targets, the average EMG burst onset time, relative to the time of movement initiation, occurred later in the older adults. When the action of a particular muscle opposed the required direction of torque, the older adults tended to activate the muscle later than did the young adults. In some instances, and more frequently for the older group, the muscle burst onsets occurred after the initiation of movement. Clearly, the initiation of bursts at this latency was preceded by activity in other muscles, primarily the agonists. DISCUSSION In a simple two-degree-of-freedom isometric aiming task, we found that the ability of older adults to rapidly produce torque to acquire a visually displayed target varied according to the coordination demands of the required movement. The dependence of the age-related difference in rapid torque production on the direction of isometric torque application is indicative of dysfunctions in muscular coordination in the elderly. Older adults are apparently less able than young adults to modulate the pattern of activity of groups of muscles to match the demands posed by specific movement tasks. This contention is supported by the differences we observed between the young and older adults in both the timing and magnitude of muscle activation. Differences in Rapid Torque Production The torque trajectories generated during the aiming task displayed many of the primary characteristics observed in other visually guided aiming tasks (16). This was an initial impulse that preceded peak ‘‘velocity’’ and was typically sustained for most of the duration of the ‘‘movement.’’ This initial phase was frequently followed by one or several relatively brief additional impulses. For the older adults, not only was the peak rate of torque development lower but the initial impulse during which the peak rate of torque development was achieved represented a smaller proportion of the total impulse required to reach the target. Consequently, the older adults exhibited a much greater number of additional impulses or ‘‘submovements’’ in acquiring a target. This may reflect a reduction in the quality of feedforward movement programming and an increased use of on-line control to achieve targets, as has been frequently reported for older adults when they perform aiming tasks (13,15,30). A reduced ability to plan movements was also implied by the increased reaction times displayed by older adults in general, and in particular by the trend for the time taken to initiate movements to combined extension and supination to be most prolonged (10,13). Combined extension and supination, for which the performance of the older adults was most impaired, imposes significant demands with respect to the coordination of muscles acting about the elbow joint. In producing combined extension and supination torques, triceps brachii generates extension torque (31,32). Biceps brachii, in producing a component of the supination torque, also generates a flexion torque, and hence acts in opposition to triceps brachii (31,32). This constraint presents a particularly challenging problem for central nervous system control 238 BARRY ET AL. Figure 5. The normalized mean rate of EMG burst onset were recorded from (A) biceps brachii, (B) triceps brachii, (C) brachioradialis, and (D) flexor carpi radialis during the visually guided aiming task. *p , .05; ymoderate effect size. Error bars show 95% confidence intervals. The rate at which the EMG increased during the onset of each burst was calculated on a second copy of the EMG channel low-pass filtered at 6 Hz. From the derivative of this time series, the peak rate of increase of the EMG was identified for the first burst of activity in each muscle. The mean burst onset rate was defined as the mean slope of the EMG in the region about the peak rate of increase of the EMG for which the magnitude of the signal was increasing (i.e., the average of the segment between zero crossings of the differentiated time series that contained the peak positive value of this time series). The values thus obtained were normalized with respect to the peak amplitude of EMG achieved during an MVC. Flex ¼ flexion; Flesup ¼ flexion and supination; Supn ¼ supination; Extsup ¼ extension and supination; Extd ¼ extension; Extpro ¼ extension and supination; Pron ¼ pronation; Flepro ¼ flexion and pronation. when a task requires that extension and supination torque be generated either rapidly or at near-maximal levels. The particular difficulties exhibited by the older adults when faced with conflicting task demands suggest that the aged neuromuscular system may no longer retain the flexibility necessary to rapidly recompose muscle synergies in a functionally adaptive manner. Deficiencies in motor planning and reliance on feedbackbased control pose crucial limitations on the ability of older adults to execute rapid movements (13,33,34). Feed-forward control of movements and the associated internal models are frequently ascribed to the cerebellum (17). Potentially, the deficits in aged motor function may be explained in part by the cerebellar degeneration that is reported to occur in older adults (24). Both animal (25) and human (26) studies have shown that cerebellar degeneration has a close association with the deterioration of motor skills. The findings of this study suggest that in older adults the muscle activation patterns devised based on feed-forward control are either inappropriate for the specific movement task, or that there is a decrease in the flexibility with which muscle synergies may be modified to implement the desired patterns of muscle activation. Differences in Muscle Activation Particular problems with the biceps brachii were implicated because the target location for which older adults performed mostly poorly posed substantial coordination demands on that muscle. In addition, the age-related differences in the EMG data were most prominently expressed in the biceps brachii muscle. We observed increased levels of activation for targets for which the biceps acted as an antagonist, and the rate of biceps activation was lower for older adults during movements for which it was the primary agonist. During MVC, older adults exhibit less consistency in the activation of the biceps brachii muscle than do young adults, but such differences have not been observed for the triceps brachii (35). Correspondingly, although it has been reported that the elbow extensors and flexors undergo a similar degree of atrophy as part of the aging process, the decrease in strength is markedly greater in the elbow flexors (36). When they evaluated decreases in motor performance in older adults, Shinohara and colleagues (37) recently suggested that when there is a disproportionate change in the force-generating capabilities of muscles involved in a particular synergy, previously suitable combinations of neural commands become less appropriate (37). In this regard, the accentuated degeneration of biceps brachii may act to disrupt the utility of the muscle activation patterns that mediate the generation of torque about the elbow joint. It is important to acknowledge, however, that although a disproportionate change in the force-generating capabilities of muscles involved in a particular synergy may disturb the RAPID FORCE GENERATION BY OLDER ADULTS 239 Figure 6. Burst onset time of EMG were recorded from (A) biceps brachii, (B) triceps brachii, (C) brachioradialis, and (D) flexor carpi radialis during the visually guided aiming task. *p , .05; ylarge effect size. Error bars display 95% confidence intervals. Burst onset time was quantified as the occurrence of the first burst for each muscle expressed relative to the movement onset time. As noted in Methods, some burst detection criteria in addition to the 2.5 standard deviation threshold were also imposed to enhance the reliable detection of EMG bursts. To ensure that all burst activity was identified, including that of low amplitude, the peak EMG value was identified for each trial, in the period between target presentation and target acquisition, and a threshold was established at 20% of this value. This threshold was substituted in place of the mean plus 2.5 standard deviations criterion, and the burst detection procedure was reapplied to those data in which a burst was not identified by the primary algorithm. Any burst shorter than 20 ms yielded by either algorithm was discarded. The remaining bursts, for which the gap between multiple bursts of a given muscle were less than 60 ms, were combined. A final test was imposed to ensure that the bursts thus identified had lasted at least 100 ms. Flex ¼ flexion; Flesup ¼ flexion and supination; Supn ¼ supination; Extsup ¼ extension and supination; Extd ¼ extension; Extpro ¼ extension and supination; Pron ¼ pronation; Flepro ¼ flexion and pronation. formation of muscle activation patterns, it is also possible that such changes may be well compensated for by the nervous system but would still result in different patterns of EMG. The possibility also exists that significant differences in the magnitude of muscle activation were only identified in the biceps brachii because this muscle may have been activated in the most reproducible way across the participants and the trials. Although not reported in the results, the coefficient of variation of EMG activity across trials was very similar for young and older adults and for all four muscles from which recordings were made. Another alternative explanation for the observed differences in biceps brachii EMG is the possibility of agerelated differences in the normalized EMG–force relationship arising from changes in the muscle properties of older adults. Ng and Kent-Braun (38) reported that older adults exhibit increased levels of normalized EMG for the same relative force at low percentages of MVC. It is very likely, however, that their findings (38) are attributable to increased levels of agonistantagonist activation that are typical of the elderly. Therefore, the observed differences in normalized EMG in the current study may be expected to indicate genuine differences in the degree of biceps brachii activation (38,39). Implications The ability to rapidly generate torque has been identified as an important contributor to the decrements in the physical capabilities of older adults (3–5) and may be a crucial factor in the recovery of balance and the production of protective responses when they fall (2,40). In addition to the loss of muscle mass and the slowing of muscle contractile properties, deterioration of the capacity to coordinate muscles also appears to contribute to the reduced ability to develop torque rapidly. Indirectly, therefore, deficiencies in the coordination of muscles will impair the functional capabilities of older adults by contributing to the age-related reduction in the rate of torque development. Deficiencies in muscle coordination may also be expected to directly impair functional capabilities by rendering older adults less able to produce the specific muscle actions required to perform effectively the wide variety of movement tasks that are encountered in everyday living. Resistance training interventions tailored to enhance the rapid development of force have been advocated as a key strategy to improve the movement capabilities of older adults (41). The observed deficits in the ability of older adults to 240 BARRY ET AL. appropriately coordinate muscles when producing rapid contractions suggests that a significant benefit of resistance training interventions may be derived from adaptations in muscular coordination. Adaptations that benefit the facility for muscular coordination are likely to be a particularly important consideration for resistance training interventions prescribed to older adults, because there is an expectation that the adaptations accrued through the repeated performance of a small number of exercises will transfer to a broad range of movement tasks. The capacity of older adults to modulate patterns of muscle activation according to the requirements of different functional tasks will determine the effectiveness of the transfer of these adaptations. ACKNOWLEDGMENTS Supported by the Australian Research Council. 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