All data were collected online using V-series transducer couplers (Coulbourn Instruments, USA) and an A/D processor (1401 plus, Cambridge Electronic Design, UK). Analysis was performed offline using the Spike2 data-analysis system with custom software (Cambridge Electronic Design, UK).
The slow drift in the force signal was removed in both the vision and no-vision segments using the DC remove function in the Spike2 software. For each data point, the function subtracted the mean of the signal during a 1-s window centered around the data point, removing frequencies < 0.5 Hz. The subject could not see the target during the no-vision portion of the trial; thus, the purpose of the detrending process was to remove low-frequency drift away from the target during the no-vision segments (Fig. 1). The drift was removed because it does not represent the force fluctuations of interest and would exaggerate the SD of force values. After extensive pilot testing, the 1-s time constant was chosen to remove the drift while preserving the force fluctuations around the drifting force. Accordingly, the SD of force during the vision segments, which do not contain drift, was not significantly affected by the detrending function. Infrequently, when a subject did not perform the trial correctly because of inattention, the trial was repeated. The longest possible segments of detrended vision or no-vision force data were chosen for steadiness analysis (Fig. 1). For most trials, the segment began once the target was acquired and ended when the muscle was relaxed. The values from two trials were averaged.
The frequency spectrum for the force signal was determined using the fast Fourier transform (FFT) function in the Spike2 program. The FFT was performed on the same detrended data segments for the fluctuation calculations and used a Hanning window and a block size of 2048, yielding a frequency-bin resolution of 0.49 Hz. The power in each frequency bin was expressed as a percentage of the total power from 0 to 30 Hz. The total power for the 0- to 4-Hz and 8- to 12-Hz frequency ranges was calculated because these frequency ranges are associated with slower visuomotor correction processes (0-4 Hz) and physiological tremor (8-12 Hz).
The dependent variable for the MVC task was maximal force (N). The dependent variables for the submaximal isometric contractions were mean force (N) for the original (nondetrended) force segment and standard deviation (SD, N) and coefficient of variation [CV = (SD/mean force from nondetrended segment) × 100] of force for the detrended segment. For the spectral analysis, the dependent variables were the total percent power in the 0- to 4-Hz and 8- to 12-Hz bins.
Analysis of variance with repeated measures on the within-subjects factors was used to compare the dependent variables. The between-subjects factor was age group (young, elderly). The within-subjects factors were muscle (elbow flexor, knee extensor), target force (2.5, 30, and 65% MVC), and visual feedback condition (vision, no vision). Planned contrasts were used to examine differences and interactions where appropriate. Values in the text are mean ± SD, and values in the figures are mean ± SEM. When one P value described the stated comparison, statistical significance values were given as exact P values, except in cases of extremely low exact P values, when P < 0.001 or P < 0.0001 was used. For clarity and brevity, when a statistical result involved more than one significance value across factors or levels of factors, P < 0.05 was stated when appropriate. SPSS version 13.0 was used.
Height (1.69 ± 0.11 m, P = 0.1) and body mass (72.8 ± 15 kg, P = 0.1) were not significantly different between young (N = 22) and elderly (N = 23) subjects. Body mass index was greater for the elderly compared with young subjects (27.5 ± 4.1 vs 23.4 ± 3.9 kg·m−2, P = 0.001). For elderly compared with young subjects, MVC force was 37% lower for the knee extensors(339 ± 122 vs 538 ± 215 N, P < 0.001) and 19% lower for the elbow flexors (210 ± 68.4 vs 258 ± 96.7 N, P = 0.06).
Mean Forces for the Steadiness Tasks
As expected (41), the mean elbow flexor force drifted slightly (P < 0.0001) when the visual feedback was removed (Fig. 1). During the 2.5% MVC target force trials, the mean force for a segment increased from 2.67 ± 0.24% MVC with visual feedback to 3.25 ± 0.68% MVC without visual feedback for elderly adults and from 2.60 ± 0.14 to 2.85 ± 0.27% MVC for young adults (P < 0.05). The force drift was significantly greater for elderly than young adults (P < 0.0001). For the 30% target force, the mean force decreased (30.4 ± 0.62 to 28.8 ± 1.6% MVC) for young adults and remained the same (30.5 ± 0.85 vs 30.4 ± 1.5% MVC) for elderly subjects; the drift was significantly greater for the young subjects (P = 0.002). For the 65% target force, the mean force decreased from 65.2 ± 1.6 to 61.6 ± 3.7% MVC for elderly subjects and from 65.3 ± 1.5 to 61.1 ± 3.1% MVC for young subjects; the decrease was similar for young and elderly subjects (P = 0.61). Overall, the increase in force observed during the 2.5% MVC trials (P < 0.05) was significantly different (P < 0.05) than the decrease in force (P < 0.05) for the 30 and 65% MVC target forces.
The mean knee extensor force also drifted slightly (P < 0.0001) when the visual feedback was removed. During the 2.5% MVC target force trials, the mean force for a segment increased (P < 0.001) from 2.64 ± 0.15% MVC with visual feedback to 3.11 ± 0.33% MVC without visual feedback for elderly adults and from 2.55 ± 0.09 to 2.70 ± 0.18% MVC for young adults; the effect was greater for elderly adults (P < 0.0001). For the 30% target force, the mean force did not change (30.6 ± 1.05 to 30.8 ± 2.0% MVC) for elderly subjects and declined from 30.5 ± 0.65 to 29.0 ± 1.4% MVC for young adults; the effect was greater for young subjects (P = 0.002). For the 65% target force, the mean force decreased from 64.8 ± 2.9 to 61.6 ± 4.4% MVC for elderly subjects and from 65.0 ± 1.7 to 62.6 ± 4.2% MVC for young subjects; the effect was similar between young and elderly (P = 0.61). As for the elbow flexors, the increase in mean force at 2.5% MVC (P < 0.05) was significantly different (P < 0.05) than the decrease (P < 0.05) for the 30 and 65% MVC target forces. The changes in mean force from vision to no-vision conditions (P = 0.31) and the age × vision interaction (P = 0.96) were not different between muscle groups.
Effect of target force.
The SD of force exhibited the same pattern of increase with target force (P < 0.0001) for both muscle groups (Figs. 2A, B). The CV of force was greater for the knee extensors compared with the elbow flexors at the 2.5% (P = 0.04) and 30% (P < 0.0001) target forces and was similar between muscles at the 65% (P = 0.96) target force (Figs. 3 and 4). The pattern of change of the CV of force across target forces was not significantly different between muscles (P > 0.05). The CV of force was lower at 30% MVC compared with the 2.5 and 65% target forces (Figs. 3 and 4).
Effect of visual feedback.
The force fluctuations were measured from detrended force data; therefore, drift from the target force did not contribute to the variability measures. For the 2.5, 30, and 65% MVC target forces, the CV of force was 36, 19, and 24% greater (all P < 0.0001) for vision compared with no vision for the elbow flexors and was 38, 20, and 22% greater (all P < 0.0001) for the knee extensors (Fig. 4). The effect of vision was greater at 2.5% MVC than 30 or 65% MVC (vision × target force interaction P < 0.05, Fig. 4). These effects were not different between muscles (P > 0.05).
Age differences in visual feedback effects.
The age effect on CV of force depended on visual condition and target force. Across muscles and force levels, the visual feedback effect was greater for elderly than for young subjects (vision × age group interaction P = 0.004). The age differences in the visual feedback effect were significantly greater (P < 0.05) for 2.5% MVC than for 30 and 65% MVC (Fig. 5).
At the 2.5% MVC target force, the mean force increased when the visual feedback was removed, as previously stated. Despite this, the SD of force declined for the knee extensors but not significantly for the elbow flexors: 2.77 ± 0.2 to 2.29 ± 0.2 N for knee extensors (P = 0.01) and 1.35 ± 0.09 to 1.08 ± 0.09 N for elbow flexors (P = 0.16). The CV of force at 2.5% MVC declined from vision to no vision (P < 0.001), and the change was greater for elderly than for young subjects (P = 0.004 for the age group × vision interaction, Fig. 5). For 30% MVC, the CV of force was greater for young than for elderly subjects (P < 0.001), and the decline from vision to no vision (P < 0.001) was not different (P = 0.24) between age groups (Fig. 5). Similarly, for 65% MVC, the CV of force was greater for young than for elderly subjects (P < 0.001), and the decline from vision to no vision (P < 0.001) was not different (P = 0.51) between age groups (Fig. 5).
The 0- to 4-Hz bins contained the vast majority (91%) of the power. The 0- to 4-Hz power declined at higher target forces and when visual feedback was removed (Table 2, P < 0.05). The decrease in 0- to 4-Hz power from vision to no vision was greater for elderly than for young subjects (age group × vision interaction P = 0.004). This interaction between age group and vision for the elbow flexors was statistically significantly different from the corresponding interaction for the knee extensors (muscle × age group × vision interaction P = 0.03). The 8- to 12-Hz bins contained 2% of the total power. The 8- to 12-Hz power increased with higher target forces and increased when visual feedback was removed (P < 0.05, Table 2). The increase from vision to no vision was greater for elderly than for young subjects (age group × vision interaction P < 0.0001).
Overall, the 0- to 4-Hz bins contained 89% of the total power. The 0- to 4-Hz power declined with higher target forces to a greater extent than for the elbow flexors (muscle × target force interaction P = 0.03) and decreased with removal of visual feedback (P < 0.05, Table 2). The decline from vision to no vision (P = 0.08) was not different between young and elderly subjects (age group × vision interaction P = 0.44). Overall, the 8- to 12-Hz bins contained 3% of the total power. The 8- to 12-Hz power was not different for the 2.5 and 30% MVC target forces (P = 0.13), but it increased at the 65% MVC target force (P = 0.002). The 8- to 12-Hz power increased from vision to no vision (P = 0.02, Table 2). The increase was not different between age groups (age group × vision interaction P = 0.17).
The purpose of the study was to determine the contribution of visuomotor correction to force fluctuations in large proximal muscles of young and elderly adults, by comparing the fluctuations with and without visual feedback of the force. The main novel findings were that 1) for a range of activation levels of the motor neuron pool, elbow flexor and knee extensor force fluctuations were greater when visual feedback of the force was provided and declined when feedback was removed; 2) at low muscle forces and high visual gain, the force fluctuations were greater for elderly adults only when visual feedback was provided; 3) at moderate and high muscle forces, when visual gain was lower, force fluctuations were greater for young adults than for elderly adults; and 4) removal of visual feedback reduced the content in the force signal for visuomotor frequencies (0-4 Hz) and increased the content in tremor frequencies (8-12 Hz) for both muscles; the vision effects were greater for elderly adults than for young adults for the elbow flexors. The findings underscore the contribution of visuomotor correction to the amplitude and frequency of force fluctuations during steadiness tasks with large proximal muscles. The results also indicate that visuomotor processing underlies the impaired steadiness of muscle force for elderly adults compared with young adults at low forces.
A discussion of the following details are necessary to interpret these data in the context of previous work on force fluctuations and visual feedback. The beneficial effects of visual feedback on motor performance are obvious and well documented, and thus our finding of decreased force fluctuations without vision may seem counterintuitive. Much of the previous research on aging and force variability has used visual feedback of the force. Accordingly, our steadiness tasks were designed to assess the contribution of visuomotor correction to the force fluctuations, not the predictable and known effects of visual feedback on target matching. When visual feedback was removed, the force drifted slightly; therefore, we removed the drift (< 0.5 Hz) before the fluctuations were measured (3). Importantly, the detrending did not affect the fluctuations during the vision segment qualitatively or quantitatively (Fig. 1) and, thus, removed only drift during the no-vision segment. Because the absolute amplitude of the fluctuations (SD of force) increases with mean force (36), the SD of force for a segment was divided by the mean force to obtain the CV of force. The detrending and normalization allowed an appropriate comparison of the fluctuations from the vision and no-vision segments. Had the drift remained during the no-vision segment, the result would have been inflated SD of force values that did not represent the fluctuations of interest.
Role of visuomotor correction in force fluctuations of elderly subjects.
Many studies have examined the variability of force in elderly subjects compared with young adults. Greater force fluctuations with aging are most consistently found in small hand muscles (27,38) and have been observed in larger proximal muscles (2,36), though less consistently (12). A feature common to these studies is that subjects matched the force with a visual target and employed visuomotor correction to minimize the force fluctuations around the target. For example, we showed that the CV of force for the knee extensors was greater for elderly adults than for young adults at 2, 5, and 10% MVC, but not at 50% MVC (36). In that study, the horizontal target line was set at the same vertical screen position for all target forces, producing a higher visual gain condition for the lowest target forces. Visual information was thus greater and more important to performance of the task at low muscle forces. Despite a previous suggestion that visual feedback increased power in the force signal at tremor frequencies of approximately 9 Hz (32), the importance of impaired visuomotor processing in elderly adults as a contributor to the age-related changes in steadiness was unclear, especially for large proximal muscles.
Visuomotor correction and force variability.
Studies of visual processing and force fluctuations have manipulated the visual gain (28,31), altered the frequency of presentation of visual feedback (26,29), or compared vision with no-vision conditions (3,27,41). The gain experiments have shown that increased gain enhanced target matching and either reduced the fluctuations (28) or not (31). Presumably, increased gain provided more visual information in the form of greater excursions on the display for a given change in force. When force feedback is provided more frequently, up to approximately 6-7 Hz, better force matching and reduced fluctuations are the usual results (26,29). Although studies that used short (~2 s) detrended force segments have reported no change in fluctuations when visual feedback is removed (3,33), fluctuations are usually greater for no-vision conditions compared with vision conditions (27) when the no-vision segments are long enough for force to drift away from the target. It should not be surprising, however, to observe greater force variability when the subject cannot see the force target, simply because of force drift. Accordingly, Vaillancourt and Russell (41) have examined fluctuations in longer (~10 s) detrended segments from the first dorsal interosseus muscle and have found that force variability was unaffected by removal of visual feedback. In contrast, the young subjects from the present study exhibited a significantly reduced CV of force for the elbow flexors and knee extensors for the no-vision condition (after detrending). This suggests that some of the force variability, even in young subjects, was attributable to visuomotor correction.
Aging, vision, and fluctuations.
The general finding of studies on visual feedback in young and elderly adults is that age differences in steadiness are manifested when the visual gain is highest (28) and persist when force feedback is presented across a 100-fold range (0.2-20 Hz) of frequencies (27). Neither Christou (3) nor Sosnoff and Newell (27), however, found an age-based difference in force variability when vision and no-vision conditions were compared. Although Christou (3) detrended their short segments of no-vision data, Sosnoff and Newell (27) did not. Only distal hand muscles were examined in these studies.
For large proximal muscles, we are not aware of another direct examination of age-related differences in visuomotor correction for isometric force fluctuations. This is, therefore, the first evidence of substantial visuomotor contribution to force fluctuations in large, proximal muscles. We observed greater force fluctuations for elderly adults compared with young adults only at low forces when the visual gain was high and visual information was important to the task. Indeed, without visual feedback, the differences between young and elderly adults were erased at the 2.5% MVC target force (Fig. 5). The data show that the effect on the amplitude of the fluctuations is important at low muscle forces and high visual gain, where changes attributable to age have been greatest and most consistent (36,38). Furthermore, at 2.5% MVC, the SD of force declined significantly as the force exerted increased. The opposite, an increase in the SD of force with increased muscle force, would have been expected (36). This strengthens the notion that the absence of visuomotor correction is the cause of the reduced force fluctuations. At higher forces (30 and 65% MVC), the contribution of visual feedback to the force fluctuations persisted for both age groups, but elderly adults were more steady at these forces-a reversal of the finding at low forces. There is no readily apparent explanation for the finding of greater normalized fluctuations in young adults at these muscle forces, although the general pattern of no age changes at higher forces (12,35,36,38,39), or even a reversal (21,37), has been observed in our results and elsewhere. For 30 and 65% MVC, when visual gain was lower and muscle force was higher, the young subjects experienced greater difficulty controlling the force when the balance of sensory inputs that contributed to force control shifted away from the dominant influence of vision (13) toward greater reliance on proprioceptive and cutaneous sensory feedback from the contracting limb. Because of their greater strength, the absolute target forces were significantly greater for the young subjects. At the higher muscle forces, the synaptic input to motor neurons from recurrent inhibition, muscle spindle, and tendon organ feedback may have a different effect for young versus elderly adults.
Visual feedback and frequency content.
Frequency content in the force signal below approximately 4 Hz has been attributed to voluntary corrections associated with visuomotor and other sensorimotor processing (11,26). Here, the 0- to 4-Hz frequency content declined similarly from vision to no vision for both muscle groups. For the elbow flexors, however, the reduction in this frequency range was greater for elderly adults; this suggests that visuomotor processes underlying the 0- to 4-Hz fluctuations were more affected in the elderly adults than in the young adults. Using a similar experimental task in which visual feedback of force was presented and then removed, Vaillancourt and Russell (41) have documented reduced low-frequency content during no-vision force segments, but Christou (3) observed increased 1- to 2-Hz content and decreased 2- to 3-Hz content when visual feedback was removed.
The majority of the power was contained in the 0- to 4-Hz frequency band (82-94%) during these contractions; therefore, changes in these frequencies have the greatest potential to affect the overall signal. Nonetheless, the greater increase in 8- to 12-Hz power for the elderly with removal of vision, at least for the elbow flexors, strengthens the notion that the shift away from visuomotor toward more involuntary neuromotor processes (11,16) was greater for elderly adults. The larger vision-related changes for elderly adults compared with young adults suggests that visuomotor correction contributed more to the fluctuations for the elderly adults. A caveat for the spectral frequency data in Table 2 is that the vision effect on 0- to 4-Hz frequency content was not greatest for the lowest forces with the highest gains; indeed, it was not significant for the lowest force in the knee extensors. There is no readily apparent explanation for this finding, but it at least suggests that visuomotor processing has a greater impact on the amplitude than the frequency content of the fluctuations.
Elderly adults often rely more on visual information to accomplish motor tasks (23). During low-force tasks, when visual gain was high, the impaired steadiness of elderly adults was most likely caused by a combination of impaired detection (1) and sensory processing (10) of visual stimuli, resulting in an increased minimal time to process a visual stimulus and produce a motor correction (27,28,30) compared with young adults. We cannot determine from these data whether the impairment is the detection of the visual stimulus, the central processing of visual information, the execution of a motor correction, or a combination of these factors. We did not measure visual acuity; however, all subjects reported no difficulty viewing the force and target line on the large monitor 75 cm away. Furthermore, reduced visual acuity in elderly adults is likely unrelated to the amplitude of force fluctuations for elderly adults (28). Nonetheless, the data do raise the possibility that visuomotor correction in elderly adults resulted in larger fluctuations in descending command from higher centers to the motor neuron pool. During the low-force task, with high visual gain and large excursions around the target, the slowed processing likely resulted in overcorrection of the descending command, which may have increased the oscillations in synaptic input to motor neurons. It is also possible that the attention required during a demanding high-gain force control task altered other features of the synaptic input to motor neurons such as the sensitivity of afferent reflex loops (18) or common inputs that produce synchronous discharge (22), both of which could increase the fluctuations. Furthermore, different brain areas are activated during a task with visual feedback (42), which might have altered the quality of the descending input to motor neurons. The present data suggest a significant effect on motor output, which is greater for elderly adults, when the dominant influence of visuomotor processing (13,15) is removed and only proprioeptive and cutaneous afferent feedback remain to be compared with the efference copy to correct and precisely maintain a low muscle force.
These results suggest that the contribution of visuomotor correction to force fluctuations should be considered or controlled for in studies that aim to determine mechanisms of the age-related decline in force steadiness. Furthermore, the fact that the contribution is greater for elderly adults than for young adults at low forces and high visual gains suggests that the age-related increase in force fluctuations documented in previous studies can be explained by an impaired ability to process visuomotor information.
This project was supported by NIH grant K01 AG19171 to B.L. Tracy.
1. Baloh, R. W., K. M. Jacobson, and T. M. Socotch. The effect of aging on visual-vestibuloocular responses. Exp. Brain Res.
2. Bazzucchi, I., F. Felici, A. Macaluso, and G. DeVito. Differences between young and older women in maximal force, force fluctuations, and surface EMG during isometric knee extension and elbow flexion. Muscle Nerve
3. Christou, E. A. Visual feedback attenuates force fluctuations induced by a stressor. Med. Sci. Spts. Exerc.
4. Christou, E. A., and L. G. Carlton. Old adults exhibit greater motor output variability
than young adults only during rapid discrete isometric contractions. J. Gerontol. A Biol. Sci. Med. Sci.
5. DeLuca, C. J., and Z. Erim. Common drive of motor units in regulation of muscle force. Trends Neurosci.
6. DeLuca, C. J., R. S. LeFever, M. McCue, and A. P. Xenakis. Behaviour of human motor units in different muscles during linearly varying contractions. J. Physiol.
7. Dum, R. P., and P. L. Strick. The corticospinal system: a structural framework for the central control of movement. In: Handbook of Physiology. Section 12. Exercise: Regulation and Integration of Multiple Systems
, L. B. Rowell and J. T. Shepherd. New York: Oxford University Press, pp. 217-254, 1996.
8. Erim, Z., M. F. Beg, D. T. Burke, and C. J. deLuca. Effects of aging on motor-unit control properties. J. Neurophysiol.
82: 2081-2091, 1999.
9. Feinstein, B., B. Lindegard, E. Nyman, and G. Wohlfart. Morphologic studies of motor units in normal human muscles. Acta Anat.
10. Fransson, P. A., E. K. Kristinsdottir, A. Hafstrom, M. Magnusson, and R. Johansson. Balance control and adaptation during vibratory perturbations in middle-aged and elderly humans. Eur. J. Appl. Physiol.
11. Freund, H. J., and H. Hefter. The role of basal ganglia in rhythmic movement. Adv. Neurol.
12. Graves, A. E., K. W. Kornatz, and R. M. Enoka. Older adults use a unique strategy to lift inertial loads with the elbow flexor muscles. J. Neurophysiol.
13. Henningsen, H., S. Knecht, and B. Ende-Henningsen. Influence of afferent feedback on isometric fine force resolution in humans. Exp. Brain Res.
14. Katz, R., R. Mazzocchio, A. Pâenicaud, and A. Rossi. Distribution of recurrent inhibition in the human upper limb. Acta Physiol. Scand.
15. Klein, R. M., and M. I. Posner. Attention to visual and kinesthetic components of skills. Brain Res.
16. Kunesch, E., F. Binkofski, and H. J. Freund. Invariant temporal characteristics of manipulative hand movements. Exp. Brain Res.
17. Marsden, C. D., J. C. Rothwell, and B. L. Day. Long-latency automatic responses to muscle stretch in man: origin and function. Adv. Neurol.
18. Nafati, G., C. Rossi-Durand, and A. Schmied. Proprioceptive control of human wrist extensor motor units during an attention-demanding task. Brain Res.
19. Parkis, M. A., J. L. Feldman, D. M. Robinson, and G. D. Funk. Oscillations in endogenous inputs to neurons affect excitability and signal processing. J. Neurosci.
20. Salenius, S., K. Portin, M. Kajola, R. Salmelin, and R. Hari. Cortical control of human motoneuron firing during isometric contraction. J. Neurophysiol.
21. Schiffman, J. M., C. W. Luchies, L. G. Richards, and C. J. Zebas. The effects of age and feedback on isometric knee extensor force control abilities. Clin. Biomech.
22. Schmied, A., S. Pagni, H. Sturm, and J. P. Vedel. Selective enhancement of motoneurone short-term synchrony during an attention-demanding task. Exp. Brain Res.
23. Seidler-Dobrin, R. D., and G. E. Stelmach. Persistence in visual feedback control by the elderly. Exp. Brain Res.
24. Semmler, J. G. Motor unit synchronization and neuromuscular performance. Exerc. Sport Sci. Rev.
25. Semmler, J. G., M. V. Sale, F. G. Meyer, and M. A. Nordstrom. Motor-unit coherence and its relation with synchrony are influenced by training. J. Neurophysiol.
26. Slifkin, A. B., D. E. Vaillancourt, and K. M. Newell. Intermittency in the control of continuous force production. J. Neurophysiol.
27. Sosnoff, J. J., and K. M. Newell. Aging, visual intermittency, and variability in isometric force output. J. Gerontol. B Psychol. Sci. Soc. Sci.
28. Sosnoff, J. J., and K. M. Newell. Information processing limitations with aging in the visual scaling of isometric force. Exp. Brain Res.
29. Sosnoff, J. J., and K. M. Newell. Intermittent visual information and the multiple time scales of visual motor control of continuous isometric force production. Perception & Psychophysics
67: 335-344, 2005.
30. Sosnoff, J. J., D. E. Vaillancourt, and K. M. Newell. Aging and rhythmical force output: loss of adaptive control of multiple neural oscillators. J. Neurophysiol.
31. Stephens, J. A., and A. Taylor. The effect of visual feedback on physiological muscle tremor. Electroencephalogr. Clin. Neurophysiol.
32. Sutton, G. G., and K. Sykes. The effect of withdrawal of visual presentation of errors upon the frequency spectrum of tremor in a manual task. J. Physiol.
33. Taylor, A. M., E. A. Christou, and R. M. Enoka. Multiple features of motor-unit activity influence force fluctuations during isometric contractions. J. Neurophysiol.
34. Tracy B., D. Dinenno, B. Jorgensen, S. Welsh. Visuomotor correction contributes to reduced steadiness
of muscle force in the elbow flexors
and knee extensors
of elderly adults. 2005 Abstract Viewer/Itinerary Planner, 398.11. Washington, DC: Society for Neuroscience. Online, 2005.
35. Tracy B., P. Mehoudar, J. Ortega, R. Enoka. The amplitude of force variability is correlated in the knee extensor and elbow flexor muscles. Exp Brain Res. (In Press 2006, DOI 10.1007/s00221-006-0631-3)
36. Tracy, B. L., and R. M. Enoka. Older adults are less steady during submaximal isometric contractions with the knee extensor muscles. J. Appl. Physiol.
37. Tracy, B. L., and R. A. Howard. Fluctuations in anke dorsiflexor force are similar in young and old men and women. Med. Sci. Sports Exerc. Suppl.
38. Tracy, B. L., K. S. Maluf, J. L. Stephenson, S. K. Hunter, and R. M. Enoka. Variability of motor unit discharge and force fluctuations across a range of muscle forces in older adults. Muscle Nerve
39. Vaillancourt, D. E., L. Larsson, and K. M. Newell. Effects of aging on force variability, single motor unit discharge patterns, and the structure of 10, 20, and 40 Hz EMG activity. Neurobiol. Aging
40. Vaillancourt, D. E., and K. M. Newell. Aging and the time and frequency structure of force output variability. J. Appl. Physiol.
41. Vaillancourt, D. E., and D. M. Russell. Temporal capacity of short-term visuomotor memory in continuous force production. Exp. Brain Res.
42. Vaillancourt, D. E., K. R. Thulborn, and D. M. Corcos. Neural basis for the processes that underlie visually guided and internally guided force control in humans. J. Neurophysiol.
Keywords:©2007The American College of Sports Medicine
STEADINESS; MOTOR OUTPUT VARIABILITY; VISION; ELBOW FLEXORS; KNEE EXTENSORS